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The Indian in Western politics
You can be part of the apparatus that governs the Western powers—a mascot that helps legitimize brutality against dissenters at home or populations living under occupation abroad
Libertarianism Is Equality of Permission
“Without shared standards of right and wrong, it’s impossible to settle disputes; it’s impossible to maintain social cohesion and trust. Every healthy society rests on some shared conception of the sacred.”
Apple Will Label Apps 'Made for iPhone Duo' in App Store
In its press release highlighting apps that have been optimized for the iPhone Duo, Apple said the App Store will label apps that are "Made for iPhone Duo". In order for an app to be optimized for the iPhone Duo, the developer needs to build it with the iOS 27.1 SDK or later. Apps optimized for the iPhone Duo fill the entire inner display, and the app's toolbar appears vertically below the status bar.
How Systems Biology Is Adopting an Engineering Framework
Everything from metabolic pathways optimized for efficiency to brain blood vessels designed as protective shock absorbers demonstrates multi-level planning.
Apple Reveals More Than 50 Apps That Will Be Updated for iPhone Duo
Apple today highlighted more than 50 third-party App Store apps that are or will soon be fully optimized for the iPhone Duo and its various layouts and poses.
10X Health Launches Metabolism Genetic Test
A saliva-based test provides genetic insights to help inform personalized nutrition and weight-management plansSCOTTSDALE, Ariz., Oct. 21, 2026 (GLOBE NEWSWIRE) -- 10X Health, a leader in personalized health optimization and performance-driven wellness solutions, today announced the launch of its Metabolism Genetic Test. For individuals looking to optimize their wellness routines, 10X Health’s Metabolism Genetic Test gets at the root of why and how your body responds to food, exercise and appeti
Research report: Digital Science and Sunmedia partner to bring research impact reporting to Japan’s medical affairs teams
Sunmedia will use Dimensions and Altmetric data in customized reports intended to assess attention, sentiment and real-world connections for Japanese medical affairs teams.
New Richland Lab Could Transform How Scientists Study Microbes and Boost Regional Jobs
The BriefGroundbreaking held Tuesday: PNNL officially began construction on the M2PC lab, a 30,800-square-foot facility funded by the U.S. Department of Energy's Office of Science that will study soil microbes to improve crop productivity and develop new biotechnology applications. The facility will be open to researchers from around the nation and the world.Research timelines could shrink dramatically: The facility's automation and AI capabilities could reduce experiments that currently take six months to just 72 hours, allowing scientists to explore more possibilities faster than ever before.New jobs coming to the Tri-Cities: The project is expected to create positions for automation engineers, AI experts, roboticists, technicians, and skilled craftspeople, with the facility opening in 2029.RICHLAND, Wash. — Pacific Northwest National Laboratory broke ground Tuesday on a first-of-its-kind facility that could accelerate scientific discoveries about the microscopic organisms living in soil—organisms that may hold the key to growing more food and developing new energy technologies.The Microbial Molecular Phenotyping Capability, or M2PC, represents a significant investment in automation and artificial intelligence to speed up research that traditionally takes years to complete. The 30,800-square-foot facility will house more than 100 connected automated instruments designed to study microbes at a pace and scale never before possible.Reshaping Agriculture's FutureThe M2PC facility will not put a new tool directly into a farmer's hands tomorrow morning, but it is actively reshaping the commercial pipeline to solve agriculture's biggest headache with biologicals: inconsistent field performance. For years, PNNL researchers have explored how microbes work and how they might help produce useful materials, advance energy technologies, and address challenges involving critical materials and minerals. But those experiments have been limited by what researchers could accomplish by hand."They can be used to provide nutrients to a plant so that the plant would grow more. So, like increasing your crop productivity, for example," said Douglas Mans, PNNL's Associate Laboratory Director for Integrated Discovery Sciences.PNNL's own research shows soil microbes can help plants access nutrients and withstand drought—benefits that could prove crucial as farmers face growing environmental pressures. The M2PC facility will allow scientists to identify and optimize useful microbes faster than ever before, accelerating the development of biological solutions that actually work consistently in the field.What Makes M2PC UniqueThe Microbial Molecular Phenotyping Capability differs from traditional research labs because it operates as a first-of-its-kind, AI-enabled autonomous laboratory designed to shrink experimental timelines from years down to months or weeks. The M2PC lab will connect more than 100 automated instruments to grow microbes, prepare samples, measure their behavior, and link observations to the molecular processes behind them. Artificial intelligence will help analyze results and guide the next experiments, allowing scientists to explore more questions faster.Deb Gracio, PNNL Director, emphasized the transformative potential during Tuesday's groundbreaking ceremony: "Research that has taken years will become possible in months and hopefully in weeks."That acceleration is already being demonstrated. PNNL's smaller automated lab, called the Anaerobic Microbial Phenotyping Platform or AMP2, completed three experimental cycles in just 72 hours—a process that normally would have taken about six months."That normally would have taken us about six months … and we were able to do that in 72 hours," Mans said.The AMP2 laboratory is not being closed or replaced. Instead, the current 1,800-square-foot laboratory serves as an active prototype and precursor for the much larger M2PC facility. AMP2 will continue operating as a separate lab designed to run anaerobic experiments—those conducted in the absence of oxygen—while M2PC will focus on aerobic research.Broader Applications Beyond AgricultureWhile improving crop productivity is one important application, the M2PC facility is designed to support research into multiple areas critical to national priorities. The lab will advance research into biofuels, manufacturing materials, and energy technologies. It will also help researchers understand how microbes respond to environmental changes and how to design biological systems for biotechnology applications.As a flagship component of the Department of Energy's Genesis Mission, M2PC represents a significant investment in using artificial intelligence and automation to accelerate U.S. scientific discovery. Dorothy Koch, Associate Director of the DOE Office of Science Biological and Environmental Research program, highlighted the facility's importance during the groundbreaking."M2PC will accelerate biological discovery and design," Koch said, noting that the facility is expected to conduct a minimum of 500 strain experiments per week, 100 microbiome experiments per week, and take a million measurements per month.Economic Opportunity for the RegionBeyond the scientific breakthroughs, the M2PC project represents significant economic opportunity for the Tri-Cities region. The facility will require hiring automation engineers, AI experts, technicians skilled in operating robotics, and specialized craftspeople to build and maintain the sophisticated equipment."We're anticipating that type of hiring," Mans said when asked about job creation.PNNL has already begun recruiting talent nationally and internationally for positions related to the smaller AMP2 lab, bringing automation engineers from cities like Boston and San Francisco to work in the region. The M2PC facility is expected to accelerate that trend."This capability won't really exist anywhere else in the world," Mans said, suggesting the facility could become a draw for scientific talent seeking to work on cutting-edge biotechnology research.Timeline and Next StepsThe M2PC facility is expected to open in 2029. Between now and then, construction crews will level and prepare the ground, while the building takes shape. Simultaneously, Ginkgo Bio Works, the automation contractor, will build the facility's automation components off-site so they can be installed as the building is completed.In the interim, PNNL researchers and the broader scientific community will begin planning the first experiments to be conducted in the facility, ensuring research is lined up and ready to begin as soon as the doors open.The groundbreaking ceremony included representatives from the Department of Energy, PNNL leadership, and elected officials at the federal, state, and local levels, underscoring the project's significance to the region and the nation's biotechnology future. News The U.S. Department of Energy Secretary tours Pacific Northwest National Laboratory Dan Hanson, Apple Valley News Now News Beyond DNA: Scientists Explore New Frontiers in Biology Research Dan Hanson, Apple Valley News Now News TRIDEC optimistic that Hanford, PNNL will see funding in national budget Robert Desaulniers News Big picture science: monitoring the Yakima River Basin News PNNL research could shape the future of fighting fentanyl COPYRIGHT 2026 BY APPLE VALLEY NEWS NOW. ALL RIGHTS RESERVED. THIS MATERIAL MAY NOT BE PUBLISHED, BROADCAST, REWRITTEN OR REDISTRIBUTED.
Sundar Pichai: Google’s Frontier Imperative, Compute Scarcity Dilemmas, Future AI Products and Businesses
Alphabet CEO Sundar Pichai has little patience for doubts about Google’s willingness or capacity to compete at the frontier of AI. His company’s latest Gemini 4 Argon model — long-promised and recently delivered — beats OpenAI and Anthropic’s latest public models on coding, math, science, and knowledge-work benchmarks and has placed Google’s AI back among the world’s best. Amid chatter that Google was fine with good-enough lightweight ‘Flash’ models, Pichai pushed back hard against any suggestion that company is limiting its research ambitions. “We won’t do it any other way,” he told me in a Big Technology Podcast interview recorded this week at Google’s Mountain View headquarters. Pursuing cutting-edge research is costly for Google, requiring compute and chips that otherwise could be sold at a high markup by its cloud business. But Pichai said allocating resources to frontier AI development is “ground zero” for Google. “Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development,” Pichai told me. In our conversation, we discussed Argon (which Pichai says processed three times as many tokens as Gemini 3 in the 72 hours after launch), AI’s role in developing better models, the AI interface of the future, competition with OpenAI, Google’s partnerships with Anthropic and Apple, data centers in space, and the nature of his optimism. You can read the full conversation, lightly edited for length and clarity, below, or listen to it on Apple Podcasts, Spotify, YouTube, or your podcast app of choice. Alex Kantrowitz: Google is back at the frontier with Gemini 4 Argon, which beats OpenAI’s and Anthropic’s public models on benchmarks spanning coding, math, science, and knowledge work. The conventional wisdom was that Google had given up on the frontier to focus on fast, good-enough models for its products. That was wrong? Sundar Pichai: Very wrong. Look, we are so committed to being at the frontier. It’s in our DNA. We won’t do it any other way. We’ve been thinking about the AI frontier for well over a decade now. The frontier is very dynamic. It’s very competitive. It’s very exciting. I couldn’t be more pleased with how Argon has come together. We took our time with it. We made sure we tested it safely and deployed it carefully. We took a bit longer than our other models, given its capabilities. Across the board, be it for agentic work, knowledge work, coding, creative tasks, Argon is one of the really good frontier models. The first 72 hours since we launched, it’s almost up to 25 trillion tokens used, which is about three times what Gemini 3.0 had in the first 72 hours. And we are capacity constrained as we are serving it. Excited, but there are always areas….. You know, the frontier is very dynamic, and you have to keep evolving the models. There are areas which we can see we need to improve as well. We’ll be at work on all of that as well. Which areas? On any given model, Argon would be across the board better at everything if you just look even two months back. But the space is so evolving. Even on coding, for example, there are pockets where we know we need to do better, and there’s clear feedback. We’ll make it better. The argument for standard models is that they’re already good enough to build great products, with the frontier valuable only for certain tasks. Meta built Muse with good models rather than the best, and Google could put standard models into Maps, Gmail, and Search. Why isn’t that sufficient? It’s definitely not how I have thought about it at all. We are deeply committed to driving the state of the art and actually pushing where this technology can go, all the way from transformers. That’s a journey we’ve been on. You will see us continue to do that. When you’re at the frontier, you get an earlier look into the emerging capabilities, earlier than others, which helps you better prepare for the future. We are fortunate to have a wide set of opportunities across consumer and enterprise. Some of our cloud customers, for sure, want the model at the frontier. The frontier models will be better at developing the next set of models in an era of recursive self-improvement. I would argue it matters there. Internally, we have definitely seen a steep point of inflection by deploying Argon to our developers. It definitely tackles problems which our previous models could not do. Being at the frontier puts you at the innovation frontier and helps you drive that as well. There is room for models of all sizes and capabilities. That’s why we did Flash, Flash-Lite, etc. I agree with you that you can develop very good product experiences with not necessarily the most frontier model, because they tend to be slower and more expensive too. But we care about the Pareto frontier, and we’re committed to doing all of that. You said developing frontier models gives you a look at what’s coming. What do you see on the horizon? What makes this moment so exciting is you build something which you think is a culmination of months of work, and you put it out. You already see clear headroom ahead. We’ve all been working on these agentic, long-horizon capabilities, but clearly the frontier is going to have multiple of these agents working together to do things. That’s an example of an exciting paradigm underway. It’s also clear to me that users, both in consumer and enterprise, will have access to some multi-agent framework for them, working all the time doing things. It feels like a moment of infinite possibilities. Sergey Brin said one of Argon’s core innovations was relying more on the model to help develop the model. Yet incidents involving OpenAI’s bots breaking containment and Google’s bots accessing a site they shouldn’t have suggest these systems still aren’t perfectly aligned. Isn’t there reasonable cause for concern about accelerating toward recursive self-improvement? There are three parts to your question. Let’s first talk about RSI itself. You’re right, Sergey mentioned RSI being a critical contributor as we are developing Argon. But to be very clear, today, in a continuum, we are pretty far from the end state of RSI or something like that. The right way to describe it is you have RSI loops along with AI researchers in various aspects of model development. You almost have agents helping AI researchers in some automated way work together to build these models. It’s good to at least understand where we are today, and it’s super exciting. I expect that continuum to keep making progress as we go into next year. The second question is around safety. Security comes from defense in depth. You’re talking about alignment, obviously. We all are doing a lot of work to make sure the models are as aligned as possible. But it’s an active area of research, and there are clear gaps. That’s not the only thing we rely on. You have the work you do on alignment, but beyond that, we put a lot of effort into real-time monitoring as these models are working. Making sure you have good telemetry into what’s happening so that you can intervene in real time if you see unexpected behaviors. How you do that, the architecture with which you do that, how you make sure it’s all sandboxed and isolated in a way that it can continue doing its job during real-time monitoring — these are all areas of investment. Obviously, when we deploy these models, giving customers, enterprises, control, both with real-time monitoring, but their ability to decide where they deploy, what type of data which models ever have access to, etc. All that work is very, very important, and we are doing a lot of that. As an industry, we need to constantly up our game and take the time to do all this stuff, including dedicating the compute required to make sure you can safely deploy these models. The third part is: Is it all enough? This is why there are a lot of conversations in the industry, and I think it’s reasonable to be worried. The right way to approach something you worry about is early on thinking about what more we can do. As an industry, you’re definitely seeing increased levels of work on alignment, testing for safety, etc., as we deploy these models. The next step would be developing better standards so there are cross-industry standards of how we do these things, including the ability to evaluate using independent evaluators. If you look at areas like financial controls, we have accounting standards, we have independent auditors. Those are all the next natural steps for us as an industry to work toward, and regulation will end up playing a role as we go through all of that as well. Google pursues both language models and world models, while some other AI companies like OpenAI have focused more heavily on LLMs as the path to AGI. Why is world-model research important to you? As humans, you obviously perceive the world around you, and you’re taking all those inputs. Making sure these models are able to understand the laws of physics, simulate the world in high fidelity. All that, I think, are key enabling blocks for intelligence. We are working across all possible applications of this. Take an area like robotics. It’s not an accident: If you look at embodied reasoning benchmarks, Argon is state of the art. That all comes from our experience building world models. Inherently, I would expect there will be architectures which will converge all of this in the future. But for us, we view this as, today, this jagged frontier that is intelligence. We want to be at the frontier of all the possible approaches, and that will help us both drive better research, better insights, and develop a much better AGI model, is how we think about it. Some people argue Google should focus on selling its computing resources rather than using them for AI research. Cloud wants to sell compute at a high markup, while researchers need a very big computer to build the best models. How do you balance those demands? Ground zero for us is making sure we are investing in the compute that’s needed to be at the AI frontier. In 2015, I set the company to be AI-first. AI is that key horizontal ingredient across everything we do, all the way from Search to Cloud to Waymo. That is ground zero for us, making sure both for research and developing the models that we have enough compute needed. Beyond that, we have these independent businesses which each have their own long-range plans. They’re using those long-range plans to project forward, and we plan for compute for all of them. The cloud team, they have a business and they have a projection and they have demand signals. They have committed contracts. With that help, we can plan on a long-term compute trajectory for them. We’re fortunate to have this wide set of opportunities. There’s no company in the world which isn’t making trade-offs at any given moment in time. But the first principles we operate on is making sure we have enough compute to invest in the frontier, and that’s non-negotiable, and everything else works on top. Remember, we are building our own compute, our own data centers. There are long lead times. The compute we have today is a function of decisions I made in 2024. Even if you think back to a year from today, last year the agentic coding takeoff hadn’t happened. Today, obviously, when you sit and look at anything, everyone is short—not just us, other companies—and everyone wishes you had two times what you had planned for. That comes with the territory. At any given moment in time, we are planning for what we would need two to three years out in the future. You’re going to find some decisions you make may look suboptimal two years out, depending on where the state of the art is. I don’t spend too much time thinking about it. The way I think about compute allocation is making sure Google DeepMind, both for research and frontier model development, is cutting edge in terms of compute access. After that, we plan for all our businesses. It’s great we can provide our compute to other people too, like we have done. It allows us to scale that up, get real tests for it in the widest application set possible, test it in the real world, and make sure we are at the cutting edge of technology at every layer of our AI stack as well. Ben Horowitz relayed on a podcast that Andy Jassy had said compute was sold out until 2028. Are you seeing the same thing? If today a customer is coming out and asking us for compute in ’27, that is incredibly difficult to do. Even last year we went out and leased some short-term compute to accommodate some customers and help them out. But yes, we are all dealing with similar timelines. Every major technology shift seems to involve overbuilding, from railroads to fiber. Do you think that’s happening here? It depends on the time frames you’re looking at. This level of build, if I take a long enough time frame, it makes complete sense to me. We are at early stages of the most consequential technology ever, and this is not like fiber. It’s not dark. We are using it. We are capacity constrained on a daily basis. The applications, the underlying technology is improving rapidly. But running a company, the way I work through the moment is you look at your demand signals. You look at your committed revenue opportunities that you’re getting in the form of contracts. You balance that with the underlying technical capability, or internally you balance how we are using it internally, the model trajectories. Based on all that, you take a disciplined approach—a confident, aggressive, but disciplined approach—to plan out compute. But when you talk about the broader economy as a whole, you’re having people operate with various levels of risk. I focus on what I can control as a company and plan through it. If your question is, can there be an overbuild? Yes, because you can have some constrained components. Remember, what matters is a set of everything you need to build out that compute. Memory, electricity, electricians…. Land. Like 2,000 components or more. You could get constrained at some point. There could be things which cause bottlenecks, and then you could have overbuilds. There could be external shocks to the economy. There are macro risks. All that is possible at any given time. But am I confident that the compute we are planning for, we will have uses for it given enough time? Absolutely, yes. I was in the room when you said AI would be as profound as fire and electricity. If you believe that, shouldn’t you give researchers the biggest possible computer, even at the expense of today’s cloud profits? We’re all doing some form of that. Our cloud business is at any given moment in time forgoing short-term revenues because we are making compute trade-offs to support frontier AI development. What you’re seeing is true already. But you want to be thoughtful. Even our AI researchers have some constraints, which are also good. That’s what inspires creativity. That’s what helps you come up with a more efficient algorithmic breakthrough, maybe to use less memory. What we are committed to is to invest what’s needed to stay at the frontier. OpenAI President Greg Brockman told me a few months ago that the ideal AI product might have no interface at all—just as natural as conversation. What do you think the interface looks like in the age of AI? Computing historically has been humans adapting to computing. With AI, it’ll be the other way around. The technology will adapt seamlessly to how humans live and go about their day-to-day life. You want to be able to speak to that AI when you want to. It has context. It can be persistently running somewhere, give you continuity. You’re not dealing with a lot of complexity. It’s natural. All that makes sense to me. That doesn’t mean it won’t have any interface, however. Nowadays, even on my phone, Gemini voice models are so good. I can just press the microphone button. I can just ramble. That’s why we call it Rambler. I can ramble. It intelligently corrects with my personal context. Even my friends’ names, weird names, it gets it right, even if it first guesses it wrong. It’s amazing. I’m not going in, backspacing, editing once I finish saying it. It’s remarkable how good it’s gotten. But there are going to be moments you will need an interface. You may want to entertain yourself. You may want to watch a video. You may ask your AI to create something, and you want to watch it, consume it. The way I think about it is, you want it to be as seamless and as natural as possible, and that you are not doing the hard work adapting to whatever the interface is. The technology is adapting to how you’re working at any given moment in time. When I asked Sam Altman about competition from Google, he argued that OpenAI was building AI-native products and implied Google was bolting AI onto existing ones. Do you accept that framing, and can a “bolt-on” compete with an AI-native product? First of all, it’s a very dynamic moment. We are all pushing each other. OpenAI has pushed us as a company too. This is not just we are doing something to them. Far from it. Yes, Google went into its own version of a code red too. In the AI moment, all of us have to respond with varying levels of urgency at any given moment in time. We are constantly building new products as well. Gemini was built from the ground up as a product—the Gemini app I’m talking about. Or tomorrow, as all of us are adapting to agents, are you bolting agents onto ChatGPT, or are they building it natively? How would you think about that? You can always put these questions back. I don’t think of it that way. I think of it as you want to build world-class product experiences that are AI-native and they are winning. Some of it is adapting products, some of it is rethinking new experiences. They will all be part of how you approach this moment. How do you expect to make money from these AI interfaces? If an agent recommends a product and I buy it, should it take a cut of the sale, even if that’s disclosed? I’m going to put enterprise aside. Consumers are going to increasingly value this technology. Take software developers today. Developers are willing to pay for these coding models because it really helps make them more productive. Nobody would want to code the way they were coding three years ago, or even the same time last year. When you’re delivering value, there’s value to be had. I’ve never seen examples where consumer products really scale to billions of users, where people are using it intensely, and haven’t had monetization to go along with it. If you’re providing value to people, there is inherent value to be had. The nature of it may change. You’re asking a scenario in which agents are doing stuff for you. At the end of the day, you will have commercial needs. The agents need to fulfill those commercial needs. The providers on the other side are going to see value in that. There’s going to be some mechanism by which it gets fleshed out. That’s what an efficient system does. But what matters is that you’re building those world-class consumer experiences. I promised myself one product feature request: Can you make Gemini-powered search in Gmail as good as searching Gmail through ChatGPT? What’s going on here? One of the exciting things we announced recently is the unified Gemini agent for enterprise, and we’re bringing that to consumers. These are persistent agents which run 24/7 in the cloud. We’re spinning up a micro VM effectively for every query, and from the runtime, the harness, the model—it’s all a headless service. It’ll work everywhere, and it has your context with you. You can address this agent whether you’re in Workspace, in Search, in Gemini. Agents are going to drive this unification from a customer experience, which people are looking for. When you have a broad product portfolio and you’re moving forward fast, there are always areas where you’re moving forward faster than some other areas. That’s valid feedback. But we are putting a lot of time and effort into making sure, as we build out our agentic experience, that unification and that capability works well across all these services. People have asked where Google’s equivalent of Muse or Dots is. Do you anticipate creating a new product to compete with them? Our goal with Gemini is to be a personal, proactive, and powerful assistant. That’s what we are working toward. You saw us describe the early versions of it at Google I/O this year with Spark. Effectively, already, if you open the Gemini app as a Pro or an Ultra user, you see Chat and Task, and they start giving you that agentic experience. With Argon now, that capability is dramatically accelerated. What we announced recently in our enterprise event, we are bringing that to consumers as well. Soon in Gemini, you will be able to ask something, and it’s a continuum. You don’t need to think about whether you’re asking a chat or an agentic task. It’ll just automatically do the right thing, and it can work persistently in the background securely and get things done for you. Already, empirically, when I look at what’s coming into Gemini in our app, last year you would have tagged them and most of them would have been chats. But a steadily growing percentage is already agentic tasks in Gemini. Yes, we are going to bring personal agents to our consumers. It’ll work in the Gemini app. It’ll work in Google Search. It’ll work in Gmail. You can address it, call it, etc. We want to make sure we’re getting it right. It’ll be powered by Argon, and we are very excited to bring it to our users. Google has invested and committed tens of billions of dollars to Anthropic. What do you see in Dario Amodei that makes you want such a deep investment and partnership? Very early on, when we looked at the founding team of Anthropic, it was very clear to us this was a world-class team which was involved in some of the earliest GPT models. We were quickly able to assess that they would be at the frontier. We’ve always tried to identify and partner with companies which would be at the cutting edge of technology. We’ve done that with SpaceX. We’ve done that with Anthropic. That’s what we saw, and we had a chance to partner. Is your partnership with Apple to license Gemini for Siri expanding, contracting, or standing still? For both us and Apple, that partnership was about translating the capabilities of AI into better experiences for users. I thought Apple has done a phenomenal job of incorporating—they customize these models and build it into Siri—and it’s been great to see the reception. We are committed to doing more. You’re going to do more with them? There’s nothing specific to comment, but it’s a partnership. It’s working well. What have you learned so far about the feasibility of data centers in space? It’s a very exciting project. Projects like this remind me—I still recall that moment in the desert for the DARPA Grand Challenge, watching the Stanley car compete in it, which ended up being the basis for Waymo. With all these technologies, you’re at a moment in time where it looks a bit like sci-fi, but 10 to 20 years down the line, it’s actually working in a meaningful way. I feel the same in space. We’ve always believed in betting big on these technologies. Quantum has been a great example of it. We’re probably 10 years into the journey. Waymo, we are almost 20 years into the journey. Space, we are two to three years into the journey. It’s clear to me that it’s an approach which will make a lot of sense in the future. Being in sub-synchronous orbits with 24/7 access to the most abundant form of energy we have access to will make a lot of sense for this exponential increase in compute that we are going to need. Having said that, this is a challenging project. The team has disciplined milestones. It was a super exciting milestone to send the TPUs up to space. Sometime, as we are speaking, we are expecting a “hello world” moment from them. I look forward to seeing that happen, and we’ll continue investing here too. You previously said 25% of the code written within Google was written by AI. What’s the number today? That number in our world today is meaningless in the sense that every part of what we now touch is influenced by AI deeply. What we are tracking with Argon, for example, it’s been a point of inflection. People are using Argon to really go tackle complex projects, including projects which affect millions of lines of code. In the four weeks since we have launched Argon, we have seen a 30% increase in CLs, and more importantly, almost a similar increase—a one-third decrease in rollbacks. People are writing code more productively and better code with it. We are tracking it with newer metrics now. How are you dealing with opposition to data centers? If you can’t build in the U.S. the way you want to, where else do you go? We’re very committed to building our data centers very responsibly. When I look at our largest data centers in some of the communities where we have been the longest, I visit them, I talk to people. There are people who come and tell us their kids have gone to college because of our investments in these communities, and we’ve grown in those communities. To me, this is about doing it right. Engaging with the communities early, doing it transparently. We are committed to making sure we are bringing incremental power, and we cover 100% of the cost of our power needs for these projects. It’s understanding the impact on neighborhoods and making sure you’re working thoroughly to address them. Done rightly, you can continue making progress. But we are constantly taking feedback into account. I do worry not everyone operates the same way. People have been surprised by data centers showing up in their backyard. Those are all important. As an industry, we should continue to do better. But part of the reason, in a 20-year time frame, we are thinking about things like data centers in space is making sure we are able to put these data centers where maybe the trade-offs will be different. What unproven area of AI is Google working hardest to crack? Is it continual learning—getting models to keep updating after release—or something else? There are multiple parallel paths. You saw with Argon we have a million output tokens. With our Gemini models early on, we had a one-million context window on the input side. These are all examples of breakthroughs we are constantly working on. How do you think about synthetic data? How do you think about continual learning? How do you think about more efficient architectures? We do dedicate a meaningful percentage of our compute to these research bets too. It always goes hand in hand, including our world models. Those are all bets we are placing. Sometimes, as part of these bets, there are ideas that emerge which just make their way into the mainline models. Maybe we don’t fully talk about it, but we have multiple steps in these areas. Working in technology requires optimism that building something will improve the world, but those bets can leave real consequences when they fail. I recently returned to a town in El Salvador where enthusiasm for Bitcoin had given way to unfinished construction and something resembling a ghost town. How do you maintain the optimism you spoke about in your Stanford commencement address while accounting for those risks? I genuinely have a deep conviction that improving technology and improving access to technology makes people’s lives better. It’s been my personal experience in my life, out of which comes that deep conviction, optimism. But with that, I’ve always felt humanity’s journey is always about working hard to harness that technology to make it work well for society. The optimism is not an optimism that you just build whatever you want, whenever. You work hard to make sure you’re building technology in the service of humanity, to make the human condition better. That’s got to be the defining goal as we are approaching it. With that framework, I’m very, very optimistic. We are in very early stages of the kind of progress that we are going to see on many areas. We’re all talking about areas like healthcare. A lot of the progress is ahead. The ability to make things in a fundamentally cheaper way on many things where things have been getting expensive for a long, long time, discovering new materials, etc., which really bend the curve—it’s tough to step today and understand the impact of all that, but they’re going to be very profound. I’m very optimistic, but we have to be rightfully concerned about all the ways this technology can go wrong. Sundar, I know you don’t do many of these. Thank you. Thanks, Alex. Appreciate it.
Lukashenka optimizes the National Academy of Sciences of Belarus
On October 19, Alyaksandr Lukashenka signed Decree No. 367 "On the Activities of the National Academy of Sciences of Belarus," which liquidates, reorganizes, and alters a number of...
Can AI solve our mental health access problem?
Last week I asked you what worries you most about AI in health. It was close, but your top answer was “AI giving bad health advice.” Last week’s poll results: You’re in good company. This concern was top of mind at a conference I joined at Stanford last week, where researchers, clinicians, and people who build AI systems spent a day debating trust and safety in health AI. Stepping back, I’m also hearing your emerging concerns about AI’s impact on our well-being generally. I see this as a matter of public health, and we’ll take it in pieces as we learn together. Today we’ll focus on AI chatbots used for therapy for mental health. Early this month, Governor Newsom vetoed Senate Bill 903, California’s most ambitious attempt to regulate AI use for mental health. It’s at the center of active debate, and raises the questions patients, family members, citizens, and voters will face as AI moves deeper into health care. Let’s work through it. What is “AI-based therapy”? It’s really two things: purpose-built mental health apps designed to deliver structured support, and general chatbots like ChatGPT, Claude, and Gemini that people increasingly use for emotional support—even if they weren’t built for it. Spoiler alert: I don’t know whether the shift toward AI therapy is good or bad. The evidence isn’t there yet. But I do know it’s already happening, and I have some ideas about how we can roll it out with safety in mind. The therapy dilemma, in a nutshell Mental health challenges are common, and strain health and well-being across populations. Therapy (interactive dialogue with a trained, empathetic practitioner) helps many people heal. The demand for licensed therapists far exceeds the supply in California, and AI-based therapy can narrow that gap. AI-based therapy remains novel, unproven, and not well tested. Right off the bat, we can see we’re dealing with trade-offs here. Since the main driver of demand for therapy from a robot is lack of access to therapy from a human, we’ll start there. It’s too hard to find and afford a human therapist California is short roughly 55,000 licensed, non-prescribing therapists and counselors, about 40% of what we need. Psychiatrists, who rely on talk therapy as a complement to prescribed medications, are even more scarce. Eight counties have none, and density ranges from 1.7 per 100,000 residents in San Benito County, to 68.1 in Marin County. My wife is a psychiatrist in Marin, and even here access is tight. If it’s hard in the best-supplied county, imagine rural Sierra County, or the San Joaquin Valley. In 2024, more than half of Californians who tried to make a mental health appointment struggled to find a provider who took their insurance, compared with 14% for physical health care. When Senate staff posed as “secret shopper” patients and called 120 mental health providers in Medicare Advantage networks, they landed an appointment less than once for every five tries. Insurers pay behavioral health clinicians about 22% less than medical and surgical clinicians for comparable office visits. On top of that, billing denials and prior authorizations hit hardest at the solo and small practices common in mental health. Psychiatrists opt out of Medicare at the highest rate of any specialty. In many places, a cash practice for therapy fills quickly with patients paying $250 or more an hour, with no insurance paperwork at all. Families who can pay cash find providers more easily. Those who rely on insurance, including Medi-Cal enrollees, older adults, rural residents, and non-English speakers, compete for what’s left. So we can’t pretend the human system works, and we can’t blame people for turning to AI for support when they’re in distress. AI is filling the gap It’s estimated that roughly a quarter of AI users use it for mental health support. If you have internet, it’s available 24/7, it’s cheap, and it speaks your language. Uninsured adults are about twice as likely as insured adults to do it (30% vs. 14%). It feels anonymous in ways that may enable people to ask things they’re unsure or embarrassed about. The largely hidden, personal use makes it hard to study whether it’s actually helping people with their mental health issues, but researchers are trying. Does AI therapy work? A 2026 analysis of nearly 40 randomized trials found chatbots showed a real but small reduction in depression symptoms. But most of these trials were compared to an alternative of no therapy, not a human therapist. So the benefit of AI therapy is probably real, but modest, and mostly untested against the alternative of human contact. We need more studies. Serious concerns OpenAI’s own estimate is that more than a million ChatGPT users each week show signs of suicidal planning or intent. These are high stakes encounters, and AI doesn’t always get it right. That’s partly because a chatbot can sound like a therapist, but it has no license, no duty of care, and it’s not clear who to hold accountable when it gets things wrong. AI is also designed to help users in whatever task they’re seeking to accomplish. People may feel like they’re getting therapy, but they’re mainly getting a convincing conversation. It’s easy for an AI companion to wander into gray areas, like playing along with “creative writing” that may be about the user’s own suicidal intent. Courts are driving safety conversations A wave of lawsuits have been filed on behalf of families claiming that chatbots pushed people they loved toward self-harm, including teens who died by suicide. The first settlements came this year. OpenAI is headquartered in San Francisco, and dozens of cases alleging that ChatGPT drove users to suicide or self-harm are now before a San Francisco judge. Character.ai has filed for bankruptcy after several states brought lawsuits accusing the chatbot of pushing dangerous content to kids. But the technology seems to be improving. Last month, an independent evaluation found that newer AI models “almost never endorse suicide.” That’s progress, but our societal appetite for even one preventable death is very low. So how do we move forward? Finding a middle ground Earlier this month the governor vetoed Senate Bill 903, a bill designed to place guardrails on the use of AI for therapy. The bill would have prohibited any AI-based platform from being advertised as psychotherapy, and would have required a licensed professional to review and approve each encounter where AI was used to support therapeutic decisions. Newsom called it overly broad, since even routine screening questions would have needed clinician sign-off. Knowing we’re already short on mental health providers, requiring human review of AI encounters may not relieve our access problems. Still, the answer isn’t no oversight. Here’s one feasible short term solution. Rather than reviewing each encounter, a licensed clinician can design the guardrails: what counts as a crisis, what triggers an immediate handoff to a human, and what gets sampled for audit each month. The AI runs inside that structure. Conversations get checked, failures get reported, and a real clinician owns the framework. Medicine already has models to learn from. The FDA process for rolling out newly approved medications is an example. After a product reaches patients, we keep watching for adverse events. Patient-facing AI needs the same “digital pharmacovigilance”: systematic tracking of harms, near misses, and the types of groups that get hurt and why. It’s also critical that users know that they can reach a human if they’re in crisis. Most chatbots now include messages like these: Bottom line The rush to use unproven AI tools for mental health support is mostly a workaround, a sign of a health system people can’t get into. We need better access to proven care from licensed clinicians. That takes reimbursement that makes accepting insurance viable, and a bigger workforce. But, built and tested well, AI could be part of the answer. It could be the 2 a.m. check-in when no one else is awake, or a way for patients to practice skills their therapist taught them. It could be the first step to get someone the right level of care, and take paperwork off clinicians’ plates so they spend more time with patients. None of this is simple. The SB 903 veto doesn’t end the debate, and the legislature will be back. In the meantime, those of us using these tools need to stay informed, ask hard questions, and hold the companies building them accountable. I’ll try to do my part, and we’ll keep learning together. Love,Matt P.S. If you or someone you know is struggling with mental health challenges, emotional distress, substance use problems, or just needs to talk, call or text 988- you’ll reach a real person— or chat at 988lifeline.org 24/7. Dr. Matt Willis is the author of Your Local Epidemiologist in California. A California native, he’s served as a primary care physician, CDC epidemiologist, and public health officer for Marin County, where he guided the pandemic response. He lives in Marin with his family and their dogs, Teddy and Ramona. Thank you Cynthia He, MD, PhD, and Parnika Saxena, MD, for their guidance in preparing this article. Cynthia works in an outpatient mental health clinic, treating patients who have Medi-Cal or, sometimes, no insurance. Parnika works in an inpatient psychiatric unit, treating patients with public or private insurance or self-pay ability. All opinions are their own and do not represent their employers.
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ON THE JOB: ‘Where Do You See Your Career or Business in 3 to 5 Years?’
“For the next three to five years, I am looking to grow Oswego County Opportunities’ support for the county’s economic development to fight poverty and take advantage of the major investments that are coming to the area.” — Kevin Dean, Executive director, Oswego County Opportunities, Fulton “I love what I’m doing. I’m trying to do this as long as they let me. It’s so exciting to walk the floors at the various factories, talk with community leaders and be part of the solutions to their business problems. As we do this work with manufacturers and community members, we are helping the next generation have these great jobs in skilled manufacturing. I’d like to have the same job title for years to come. I’ve watched the last five years with awe and it makes me proud and excited to be from Upstate New York. I want to keep being part of the conversation that, yes, we can do it in Upstate New York.” — Randy Wolken, President and CEO, Manufacturing Association of Central New York (MACNY) “I oversee the Rochester and Syracuse offices. We’re seeing continual growth as there are more and more job seekers and companies that are looking to fill positions as the economy grows. I’d like to have another Upstate New York office in our region to help promote people under me. I want to see that happen. With an increase in the job market, that is what the end goal is here for sure. We currently have offices in Rochester, Buffalo, Syracuse and Albany, among more than 300 worldwide.” — Briana Calabrese, Marketing director and vice president of finance & accounting and administrative & customer support, Robert Half Recruiters & Employment Agency, Syracuse “Hopefully, we’ll continue to grow by word of mouth. I just took over a couple of years ago. I was an employee for 27 years. Business is great and we’re up on sales from where we were last year and I’m hoping that continues to happen. I get an overwhelming response from people who say they want to support local businesses. It’s my objective when people walk out the door that they want to come back. In a small town like this, it’s crucial. I see myself in five years doing exactly what I’m doing now: sticking with it and trying to grow Fulton Screen Printing.” — Tim Stone, Owner, Fulton Screen Printing, Fulton “I am 85 years old and teach four fitness classes a week and swim four times a week. I hope to live to be 90 — if I can do that, I won’t complain. The older I get, the less afraid I am of dying. What I don’t want to do is get some sickness where I’m lingering and I’m in pain and it just goes on and on. I expect to be exercising as much as I can and I hope I will know when I need to back off to accommodate different problems I may have when I’m older. For a short time, I got up at 6 a.m. to jog for a half hour every morning. But I had to avoid dogs, so I quit jogging. I hope to be able to swim for life. When I swim for half an hour, whatever problems I have wash away. I will still be working in exercise in five years. I also write research articles. It challenges my mind. You have to challenge your mind and body and have some kind of goals and reasons to go on living. My wife died three and a half years ago, so I try to go out and do things, even though she’s no longer here.” — Fred Wilson. Certified personal trainer at Fitness After 50 and leader of senior fitness classes, Syracuse “I expect to continue working as a local financial adviser professional for the next several years. I really enjoy working with my clients and consider it a privilege to come to work every day, helping my clients reach their financial goals.” — Randy L. Zeigler, Certified financial planner practitioner, chartered financial consultant and private wealth adviser, Ameriprise Financial Services, LLC, Oswego “I see myself doing something with young people. I want to open an after-school program as a safe space for high schoolers where they can get tutored, behavioral health, get something to eat. I want to do something with policy. I have thought of doing something with neurodivergent kids where kids can run some kind of business. I want to do anything with community like therapy and psychotherapy. I want to still be able to offer those services to people. At 55, I’m not sure how much I will do. I will see what happens after graduation from Keuka College.” — Della Joyce Smith, Master’s student, Syracuse “I think the core of the gym is in personal training. I don’t see that changing. People will still need a gym and personal training will stay. There may be some loss to AI as there is in just about every industry, but there’s always been the ability to go online and get a workout. I don’t think AI will cut into business any more than the internet has. I think the class structure is shifting. Large group classes might be fading away for a while. I see more people going to specialized classes like Pilates. I wouldn’t be surprised if maybe the traditional classes like boot camps started to fade away. It’s important to adapt. Maybe someday I’ll need to get some new kinds of classes. Everything tends to go in cycles.” — Ryan Vollmer, Certified personal trainer and owner Edge Strength and Conditioning, Syracuse “I have been growing my firm at 24% a year. In five years, we may be purchasing or building a new office building to accommodate the new growth. Right now, our focus is on growth and adding team members, mostly financial advisers and administrative staff.” — Terri Krueger, Chartered financial consultant and senior financial adviser with Orla Wealth Management in Syracuse “Over the next three to five years, I see TDO continuing to experience steady, sustainable growth as new industries establish and expand their presence across Central New York. These investments will create new opportunities throughout the regional manufacturing supply chain, and TDO will continue evolving our capabilities to help both existing manufacturers and emerging industries grow, compete, and succeed.” — Jim D’Agostino, CEO and executive director Central New York TDO (Train, Develop, Optimize), Liverpool
Daldrop Opens for Business in Southern Oswego County
$10 Million Facility in the L. Michael Treadwell Oswego County Industrial Park marks the largest expansion outside of Germany in the company’s 73-year history By Stefan Yablonski [caption id=attachment_11076 align=alignright width=450] Daldrop SBB CEO Jens Daldrop addresses attendees at the 2025 groundbreaking for the project. Daldrop also chairs the advisory board of Germany-based Daldrop Group.[/caption] A new era of cleanroom technology is underway in Central New York. The Daldrop Group’s advanced manufacturing facility and U.S. headquarters is physically built within the L. Michael Treadwell Oswego County Industrial Park. This industrial park is located in the town of Schroeppel. It marks the largest expansion outside of Germany in the company’s 73-year history. Daldrop SBB is based in Neckartailfingen, Germany. It is a global supplier of cleanroom technology, primarily to the pharmaceutical industry. It designs and builds advanced cleanroom environments for the pharmaceutical, biotechnology and medical technology industries. It nvested $10 million in the new project. “We broke ground in 2025; we were under construction all winter. We just opened this spring, early spring,” said Benjamin Morrow, operations manager and control. The company consolidated sites in Salina and DeWitt into the industrial park in Schroeppel, Morrow added. “The next move here is to maximize every square inch of this facility and then we are already looking at the expansion. So, it is more capital investment on equipment — definitely higher-end automation in additional equipment so we can produce more components and then to support the ever-growing base in North America,” Morrow continued. “We are the headquarters for service, maintenance and spare parts. So as Daldrop has more and more installations, they need more and more service, maintenance and spare parts. So that will come out of this facility as well — it already is.” “As a global leader in GMP (global manufacturing support) pharmaceutical cleanrooms for decades, I am very proud to bring manufacturing jobs to Upstate New York,” said Mike Sullivan, president of Daldrop US operations. Key to choosing Southern Oswego County [caption id=attachment_11077 align=alignright width=450] Daldrop SBB at the L. Michael Treadwell Oswego County Industrial Park when the company announced the start of construction.[/caption] Sullivan said that the selection of the Schroeppel industrial park was mainly due to the help of Operation Oswego County and two people in the organization. “Prior to being purchased by Daldrop International from the Stuttgart region of Germany, Vince Bongio was a founding partner in SBB Inc. as well as our head of engineering. We based out of Syracuse due to Vince’s skills in HVAC and the manufacturing capabilities found in Syracuse,” said Sullivan. Bongio moved to Syracuse from California in the 1970s to work in Carrier’s Industrial Division of Large-Scale Petrochemical Refrigeration. Next, he advanced to General Electric’s TV Tube Plant where he got into cleanrooms ,leading to his role of head of engineering for Clestra Cleanrooms where he met Sullivan, their New England distributor. “Vince Bongio is a phenomenal engineer. Formerly of Carrier, he grew up in California and went to Cal Poly,” Sullivan explained. “Carrier hired him right out of college and he moved to Syracuse. He is the reason we are in Syracuse today. He is retiring this year. We are very proud and his legacy is having brought Daldrop to Syracuse.” In 2000, Sullivan, Bazinet, Bongio Inc (SBB) was formed with engineering and manufacturing, based in Syracuse, and sales and construction based in Massachusetts as it is today. “SBB Inc. started in Syracuse. I had a design–build contracting firm out of Massachusetts that was primarily doing all the new technologies coming out of MIT,” Sullivan said. “I started a manufacturing side. A big thing for cleanrooms is the HVAC. Most cleanroom suppliers are architecturally focused people. The strength in Syracuse is HVAC. So, SBB developed with me running sales and construction out of Massachusetts and manufacturing out of Syracuse.” “Daldrop wanted to have a relationship in the States and of those who approached us, they were the only ones who really understood HVAC. So, we were the right fit for them. We did a joint venture focused out of Massachusetts from 2012 to 2018 leveraging their technologies,” Sullivan explained. “The commitment was if we brought their product to the States, we would do that if they built it here. “The pieces that had to be in place to make the investment, they wanted to acquire us, we were great with that. If you looked at business recommendations the general guidance was to build in a low labor area — something like North Carolina — but Syracuse had a strong background in HVAC and we chose Syracuse and Oswego County to be our headquarters in the States. So, it is built off of history, technology and the existing supply chain — bringing jobs back to the area.” During the initial discussions with Daldrop about coming to the U.S., SBB agreed to sell under the conditions Daldrop would manufacture in the U.S. There are many areas that offer incentives and economic packages, but the strength of HVAC expertise and skilled manufacturing was a big part of the discussions for site selection. Coming home [caption id=attachment_11078 align=alignright width=451] Construction moves forward in March at the L. Michael Treadwell Oswego County Industrial Park.[/caption] The second key person to building in Oswego County is Ben Morrow, Sullivan added. “Ben has been working with Daldrop SBB for more than 12 years and has advanced to COO of manufacturing and engineering. Ben grew up in Phoenix, so building a factory for the Germany company in Phoenix is a strong success for both his community and the appreciation of Ben’s skills as a team leader,” Sullivan said. “I went to high school in Phoenix. So, this is like full circle for me. It’s a small world,” Morrow said. “I hadn’t been back to Phoenix since graduation. This is one of the properties that John Trimble of C&S, he is the former president of C&S, he just retired, suggested. He and I were very good personal friends. John was from Mexico and I was from Phoenix. We knew each other from high school. And the architect of this building, Ed Smart of smartDESIGN Architecture in Batavia — I went to high school with him. So, this was a project that’s full circle a coming home kind of thing. The three of us knew each other — kind of like it was meant to be. Very serendipitous.” Schroeppel was one option for Daldrop to consider; the original intent was just to get a warehouse to store some product, he added. The facility is Daldrop’s largest outside of their native country. Total payroll at the facility will be approximately $2.4 million once fully staffed. “Here is 32,000 square feet and we plan to expand and put in an additional 10,000 square feet,” Morrow said. “We have 17.5 acres. We can put at least three more facilities here, just on this property. The master plan submitted for the current building is the first of possible three buildings on the campus.” “If we can find the right people and advance the production according to the plan, we should be able to grow for the next decade. One of the first jobs we filled was our new HR manager, with a primary focus posting and filling new positions,” Sullivan said. Stop the exodus, start hiring [caption id=attachment_11080 align=alignright width=452] Principals at the local Daldrop SBB headquarters, from left: Ben Morrow, Mike Sullivan and Jens Daldrop.[/caption] “I have been coming to Syracuse for 30 years. One of the things I had a hard time watching was the exodus of factories. One of the toughest things is to watch it with my partners’ kids who had to move away for jobs. It is important for us to give opportunity where people’s kids don’t have to leave the area to get work,” Sullivan said. “My responsibility is to find people who have skill sets that want to work and then I have to build opportunity for that work to happen. “After years of watching companies and Vince’s three sons all move out of the areas to get jobs, it is important to us to provide opportunities for the Syracuse region and help grow our company. We have been hiring for our new factory and will continue for the next few years.” “We are hiring and will continue to hire. Currently we have about 19 on staff right now,” Morrow said. “We expect to grow that by about 10 to 15 in the next 12 to 18 months or so. We are at 19 currently — one in the wings. It’s been great being able to hire locally. All these folks that we’ve been hiring, they all live within a few miles from here.” “We hired someone this past week (end of August). She grew up in the area, raised a family and is working down in Florida. She just took a job with us so she can move back and be with her family. We will be moving her back and she should be starting in October. We are very happy to see this happen,” Sullivan said. “I feel strongly about having a spot for the kids to not have to move out of the area. It is better to have people moving into the area.” Currently, Daldrop SBB has openings for finance manager, COO of construction and delivery, as well as mechanical, electrical designers and Revit modelers, construction managers, commissioning agents and many other skills that are needed. Along with Daldrop’s reputation in life science cleanrooms, there is a strong history in semiconductor, electronics, glass, photonics, aerospace and other markets. This may be helpful with any new technologies building in the market such as the Micron expansion and the support network, Sullivan said. “We acquired this property and closed on it two months before any announcement from Micron. It is serendipitous that they’re right down the street from us,” Morrow added. “Everybody started thinking ‘you guys are supporting Micron.’ We were here first. That is not a goal of ours. We may or may not … they are talking to us; it is an opportunity.” The long run [caption id=attachment_11079 align=alignright width=450] Benjamin Morrow, operations manager and control at Daldlrop, speaks during a recent ribbon-cutting event in Schroeppel.[/caption] “Long term, we will expand the Phoenix facility,” Sullivan said. “We built our facility with a campus approach. Sustainability is big. We designed our rooms to be more sustainable. Our building has no gas lines for heat. We put geothermal wells in the ground. We put heat pumps in for heating and cooling out of those wells and we put a large layer of solar panels up on the roof. We worked with National Grid for metering. Our building is a high efficiency model. We upgraded all the instillation and the glass filtering. So, it is a very green building. We will have a very minimal carbon footprint. It also adheres to LEED (Leadership in Energy and Environmental Design) construction standards.” “We are a bunch of HVAC engineers. We did a large scale geothermal and spent the money up front because we knew it made sense in the business sense in the environmental sense and sustainability,” Morrow said. “We have insulated metal panels on walls and roof; we are an envelope from the exterior.” Daldrop, as a global player, has a strong culture of sustainability that is found in all its products including the new facility. The building has been designed with (sixteen) 400-foot deep geothermal wells, high efficiency construction methods, approximately 70 kilowatt solar photovoltaic panels, electric vehicle chargers and 26% recycled content. “Daldrop thinks of long-term investing,” Sullivan said. “On the roof, photovoltaic panels supplement our power. Over half the energy that I use is coming from the sun. We have chargers up front for employee electric vehicles. This place is built to last. This slab that we are walking on, normal buildings are four inches, some go to six inches, we are nine inches all the way through — except where the heavy equipment is — that is 10 to 12 inches thick, solid concrete. It allows us to reconfigure for whatever type of equipment we want to bring in,” Morrow said. “We are authorized by Underwriters Laboratory to self-certify so we don’t need to have an inspector come out and recertify. We get audited often, but we certify our own electronics. The control system in this building is rather high-end. Our thermostat in every room is zoned, independent. We analyze the data; incorporate it with our solar panels.” “There is a lot of competition for people to work. It’s not just about how much salary they are going to make — it’s about the work environment, the ability for stability. We want to make sure our employees have the best environment to work in,” Morrow added. Similarities “One of the reasons I believe why Daldrop chose this area, Phoenix in particular, is because it is a village, a river-based village. Neckartailfingen in Germany where Daldrop is based is also a river-based village, manufacturing community. So, there is a lot of similarities — that smalltown feel,” Morrow said. “We have a lot of connections through multiple employees that lead back to Carrier, also. Everything came together, the timing everything.” “We are thankful for all the economic development support. Everyone has been helping make this happen. So, keep it up, it is working, that is all I got to say, Sullivan said. “If you look at historical industrial manufacturing, this region has skills that have been un-utilized. The northern industrial region has a lot of skills that if we can tap before they go away, we can leverage them. That is what we are trying to do. You’d be surprised at the supply chain left behind from Carrier — that supply chain is still there.” “Operation Oswego County has been fantastic,” Morrow added. “I can’t say enough good things about that group.” What Is Cleanroom Technology Cleanroom technology is a system of specialized engineering, filtration and operational controls used to maintain an extremely low concentration of airborne particles, microbes and chemical vapors. How It Works • Air Filtration: Uses HEPA or ULPA filters to remove 99.97% of tiny particles down to 0.3 microns. • Airflow Control: Directs air in a steady, unidirectional (laminar) or filtered turbulent pattern to push dust away from work areas. • Environmental Regulation: Maintains precise control over temperature, humidity and positive air pressure to block outside air leaks. • Specialized Attire: Requires personnel to wear full-body garments (“bunny suits”), gloves and masks to stop human shedding
N. Syracuse Manufacturer Marks Milestone, Plans for the Future
Air Innovations has grown from a small local manufacturer into a global business, selling its products in 74 countries organizations. Some of its clients include NASA, Blue Origin and SpaceX. By Stefan Yablonski [caption id=attachment_11117 align=alignright width=450] Michael Wetzel, president and CEO, and his father, Larry, who currently is an adviser to the board of directors. Larry served as the chairman of the board until 2024, when the company was acquired by Altus Capital Partners, a private equity firm.[/caption] Air Innovations in North Syracuse hopes to add more employees and possibly even expand its facility in the near future. The company is a global leader in designing and building environmental process control systems for applications that can’t be addressed with standard HVAC equipment, according to Michael Wetzel, president and CEO. “We customize solutions for temperature, humidity, filtration and pressurization, with additional capabilities in direct-expansion, chilled-water and thermoelectric technologies. Our business now is entirely focused on specialty or niche markets.” Air Innovations celebrated its 40th anniversary on Sept. 18, marking four decades of doing business, manufacturing products and growing in Central New York. In the beginning [caption id=attachment_11138 align=alignright width=451] A worker, Ezzy Salehi, tests a Wine Guardian condenser unit at Air Innovations.[/caption] “A guy by the name of Jim Kelley started the business [known as Floratech] in 1986. It was focused on refrigerated display cases for supermarket fresh flowers,” Wetzel said. “My father [Larry] started Clean Room Technology in the early 1980s, then sold that to a French company called Clestra Cleanroom. “My father and I bought Floratech in 1996 — 30 years ago, 10 years after it was started. Then in 1999, Floratech bought a portion of Clestra and their building. At that point everything was still called Floratech. But, as that was not reflective of the diversity of the business, we rebranded as Air Innovations in 2001.” The company rebranded to pursue a strategy of diversification in specialty HVAC systems. Wetzel explained that since then, it has become a trusted global partner, earning the President’s “E” Award for Exports and securing contracts in the most demanding fields, including aerospace, defense and semiconductor manufacturing. Air Innovations has grown from a small local manufacturer into a global business, selling nearly 70,000 units in 74 countries and territories and developing custom environmental control systems for companies and organizations including NASA, Blue Origin and SpaceX. “We work with all the big names you ever heard of and some you never heard of,” Wetzel added. The Wetzels sold the business two years ago to Altus Capital Partners, a private equity firm focused on control investments in lower middle-market, niche manufacturing companies in North America. Founded in 2003, Altus Capital Partners’ headquarters is in Wilton, Connecticut, with an additional office in Lincolnshire, Illinois. “They are an equity firm. Both my father and I both maintain a small minority share. I am going to continue to be involved. I call myself a part-time CEO. I will continue that role for the foreseeable future; I don’t see any change there.” Building to the future “We are at 58 employees right now, which is a little bit down. We had a high of 70. That moves along with the activity we have,” Wetzel said. “We’ll start ramping up here in the fourth quarter into next year. More than 20% of our employees have been with the company for more than a decade. “I am fairly certain that sometime in the next several years we are going to have to enlarge the footprint of our facility and for sure we are going to have to add employees. We already are. We are probably going to have to add five or six people next year. We are always in the market for HVAC technicians; we always need those.” Air Innovations will remain in Central New York, with its current workforce staying in place, he added. “I believe the primary driver of our success over time is the diversity of our business which is a direct result of our willingness to tackle new challenges,” Wetzel said.
PredictX Launches New Travel Policy Analyzer and Optimizer
Tool helps managers see where policy changes can deliver savings
Rice University | Scientists engineer new tool to improve detection of HIV and other viruses
New enzyme optimized for RNA detection assays.
Early planning, documentation key to university property claims: Experts
Universities should involve claims specialists early and carefully document expenses to maximize business interruption insurance recoveries, presenters said Monday at the University Risk Management &
Apple Announces $149 HomePod Mini 2 With Siri AI, 'Sound Glow', and Four-Speaker Surround Sound
Apple today announced a new HomePod mini equipped with Siri AI, new colors, and improved audio experiences. The new HomePod mini has an S10 chip that supports advanced computational audio, and Apple says it optimizes dynamic range, loudness, and acoustic performance in real-time. A Sound Glow feature turns the HomePod mini's top into a "visual canvas" that glows and animates in sync with music, reacting to bass and treble.
Shane Gillis joked about women's gym clothes on 'SNL.' Dan Levy isn't laughing.
The "Schitt's Creek" star said jokes that objectify women contribute to a culture that minimizes sexual assault.
NTT DATA Business Solutions launches "Elevate", its Agentic AI-powered delivery framework, to help accelerate SAP transformations
NTT DATA Business Solutions, a leading global IT service provider and specialist in SAP solutions, today announces the launch of "Elevate", its next-generation Agentic AI-powered delivery framework. Elevate brings together the company's secure AI-enabled platform NTT DATA aXet, Natuvion's data transformation capabilities and SAP technologies, including SAP's Agent-Led Toolchain and SAP Business AI Platform. Elevate is designed to maximize the value clients gain from their investments in SAP and
Biohacking for Better Health
Biohacking has become increasingly trendy, touting novel strategies to optimize performance, well-being, and longevity.
Scientists Say the Older Brain May Be Optimized for Something Different
New research suggests that healthy brain aging may reflect a shift in cognitive priorities rather than simple decline. The aging brain may not simply be a younger brain in decline. New research from the University of Arizona argues that healthy aging involves a shift in cognitive priorities, with less emphasis on preserving precise details and
Heat Your Garage During Cold Months With A Wi-Fi Enabled Solution From Home Depot
The HEAT STORM Ceiling Mounted Hardwired 240-Volt Garage Heater comes with Wi-Fi controls that let you customize your heating remotely.
Apple Stores Will Add Your Name to iPhone Duo's Startup Screen
Apple has something special planned for customers who purchase an iPhone Duo in an Apple Store. Employees will be able to customize the Duo so it displays the name of the buyer at the "Hello" screen when it turns on for the first time. Bloomberg's Mark Gurman says Apple retail stores in the United States will have a personalization system for adding the buyer's name to an iPhone Duo, with English and Spanish language options.
Introducing Air Canada Embarq, a New Self-Serve Business Travel Platform for Canadian Small and Medium-Sized Enterprises
New Air Canada for Business platform helps companies manage, optimize and reward business travel from one convenient platformAir Canada partnered with ZS, a global management consulting and technology firm and Traverse, powered by ARC, to deliver the technology to support Air Canada EmbarqAir Canada is putting business travel management tools and benefits that have traditionally been used by large enterprise customers directly in the hands of Canadian small and medium-sized businesses and non-pr
Meta VP: AI in advertising and the rise of single-person billion-dollar company
Businesses must stop using AI to optimize old processes and start reimagining how they compete.
Hyper-Converged Infrastructure - Global Strategic Business Report: Capitalize on 23.3% CAGR to US$92.7 Billion by 2032 as Dell, Nutanix, Cisco, HPE, and Huawei Disrupt Enterprise IT
Boost IT ROI with HCI: consolidate compute, storage and networking, automate operations, scale by adding nodes, and optimize hybrid-cloud and edge workloads.Dub
New Clinical Guideline Helps Keep Women 'Optimized for the Fight'
The Department of Veterans Affairs and War Department have jointly released a clinical practice guideline to help clinicians provide improved care for women experiencing perimenopause and menopause.
Workforce training program earns another No.1 ranking for Virginia
Virginia’s workforce training program has earned another No. 1 national ranking as the commonwealth competes for companies looking for workers trained for specialized jobs.Area Development, a major national trade publication, ranked Virginia first for workforce training programs in its 2026 Top States for Doing Business report. The recognition highlights the Virginia Talent Accelerator Program, which provides customized recruitment and training at no cost to qualifying companies opening or expanding operations in the commonwealth. a
Apple Announces iPhone Duo Apps Can Now Be Submitted to App Store
Apple today announced that apps optimized for the iPhone Duo can now be submitted for App Store approval, ahead of the foldable device launching on Friday, October 23. While existing App Store apps will automatically run on the iPhone Duo, only apps built with the iOS 27.1 SDK or later can dynamically resize to fill the entire space of the inner display, whereas unoptimized apps will have black borders.
Apple invites developers to submit iPhone Duo-ready apps to the App Store
With the iPhone Duo launch fast approaching, Apple is now accepting submissions of iPhone Duo-optimized apps and games built with Xcode 27.1.
College of Ag Sciences clubs get philanthropy boost from visiting ag company
Three clubs in Penn State’s College of Agricultural Sciences got a recent boost from a new donation from Pivot Bio, a company specializing in products that optimize crop production through specific nitrogen delivery.
Nutritional countermeasures to spaceflight studied at URI
KINGSTON, R.I. – Oct. 5, 2026 – As humans spend longer periods of time in outer space and venture further from Earth, it’s increasingly important for scientists to learn how varied gravity levels affect muscle function and muscle loss, and how those effects can be counteracted or minimized. Theodoros Pavlidis, a second-year doctoral student who […]
Google Pixels could get an all-new way to customize lock screens, for better or for worse
We've dug into the Wallpaper & Style app in the latest Android 17 beta, and discovered a brand-new way to customize your lock screen.
Accenture Completes Acquisition of Mjølner Informatics, Bringing Deep Software Engineering Expertise for Energy, Utilities and Manufacturing Clients in Denmark
Accenture has completed its acquisition of Mjølner Informatics from Norlys, strengthening Accenture’s software engineering, digital engineering and embedded software development capabilities in Denmark.
Lewis Hall Allowed To Shine Under Matthias Jaissle’s New System
The England international is thriving as a dynamic playmaker, trading rigid defensive duties for a versatile role that maximizes his technical composure and aggressive attacking instincts.
Chapel Bell Curve:
You’ve got to do something before kickoff. And if you’re looking to maximize your preparations for today’s matchup with Vanderbilt that something should be listening to Nathan and Yara preview the Commodores. Among other audio goodness in this episode you’ll find the following: As always we ask that you like, rate, subscribe, and patreonize the show wherever […]
iOS 27 adds four new ways to customize your iPhone’s Lock Screen
iOS 27 adds four new Lock Screen customization options, including AI wallpapers and a movable clock. Here's how they work.
Apple says iPhone Duo has ‘replaceable’ folding display layer to minimize crease
Foldables tend to show more crease over time, but Apple says iPhone Duo has a replaceable layer on its folding screen to mitigate that issue.
September Monthly Review: Health MCP Guy?
For all the time I spend talking about APIs and data exchange, this newsletter has had embarrassingly little interoperability of its own. It’s old-school SaaS, baby - UI or bust. Not all of that is my fault! Substack, for all its popularity, is (as mentioned before) really frustrating as my system of record. The primary user it optimizes towards is the reader, whose attention feeds the app, the Notes feed, and the recommendation network that Substack is actually selling. Health API Guy is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe They’re falling into the same trap that Medium once sprinted into, albeit at a much more glacial speed. Younger generations may not remember (or never knew) it, but Medium once lured publications like The Ringer and Signal v. Noise onto its platform, only to lose them as it rebuilt itself around a paywall and an algorithmic feed. Substack’s original pitch circa 2020 was the antidote (you own your list), but every new feed feature chips away at it. I get it: writers are generic supply in the eyes of the Substack product team. Generic supply follows demand, so the consistent pressure on the PMs is to generate demand, which leads to every product cycle going toward discovery (Notes, recommendations, the app, live video). The end result lackluster author tools (laggy and broken analytics are truly crippling) all despite the premium price point. The archive is where it crosses from authorial gripes to actual reader impact, though. Across Substack and LinkedIn, I’ve published 1,218 posts and nearly 900,000 words since 2018. Substack’s native search can see only the 464 posts that live on Substack, and even there it’s woefully inadequate at surfacing relevant content (even for the guy who wrote it)! Readers have the same problem, writ large. Ask the Archive Fixing search (for both my readers and my own use) turned out to be extremely non-trivial, unfortunately: There’s no public API for readers to access content RSS exists for new content notification, but it only carries the 20 most recent posts and cuts paid ones off at the preview The only Substack MCP is an admin tool for analytics The export exists for authors, but it’s painfully awkward and slow. So I built something to work around that: the Health API Guy MCP. It’s a private MCP server holding the full text of everything I’ve written across Substack and LinkedIn. Add it to Claude or ChatGPT as a connector and you can ask things like: It pairs keyword search (for acronyms and case names, of which we have many) with semantic search. Every post is also labeled by topic, form, and court case, so you can pull a lawsuit’s (or multiple cases’) entire docket across Substack and LinkedIn in one query: Hail, Healthapiguyhydra This is also a bit of me eating my own cooking. I’ve spent the year arguing that headless healthcare is arriving and that developers want primitives over abstractions. Last week in Hail, Benihydra, I watched Salesforce plug its platform into Claude and bet that the records underneath outlive whatever interface sits on top: Salesforce must believe that the Hydra’s immortal head is the records, permissions, and business logic (in that they will survive whatever happens to the interface). It felt a bit hypocritical to keep my own archive behind a Substack search bar. The archive is the body. Substack is one head, and now whatever tool you might use is another. Will the EHRs follow my lead? Probably not imminently, but one can hope! Why Founding Members Only The MCP is available to Founding Member subscribers. A few reasons: It costs money and time to run. Hosting, the database, Clerk usage and AI compute for search and labeling are significant operational costs (that increase with usage). Substack gives me no way to automate access. There’s no API to check whether someone is a paid subscriber, so every user is manual operations for now. It’s a beta. We’ll need to improve things and parts will break. I’d rather they break for a small group of dedicated readers who will tell me about it. The Founding tier deserved a real benefit. Until now it was mostly a generous tip. Now it comes with something. If you’re already a Founding Member, reply to this email with the address you’d like provisioned. If you’re not and want in, upgrade here. Larger teams (such as companies) can get access too: group subscriptions at the Founding tier come with the group discount. The admin for the subscription can reply with the list of addresses to provision. Get 20% off a group subscription Pricing Founding membership is now a flat $200 a year, replacing the old suggested $150 that readers could adjust. Existing Founding Members will have access grandfathered in at their previous rate. Month in Review Articles Published Make Networks Dumb Again (Sep 11): AI is making old analog networks cheaper to use and flooding them with machine traffic in the process. A plea for agent-native rails with the intelligence at the endpoints, and for Washington to drag them to ubiquity. Interoperability, Unbuttoned (Sep 29): Interoperability is a series of workflows in a trenchcoat, and this post finally takes the trenchcoat off. A color-coded map shows which provider workflows went digital, which are fragmented, and which still run on fax. Video Content Antitrust’s System of Record Problem (Sep 3): The FTC’s investigation into Epic prompted a ninety-minute webinar, now posted with chapters and a smoothed transcript. We get into why market definition, missing B2B share data, and the SSNIP test leave antitrust poorly suited to systems of record, plus why information blocking may be doing more than any pending lawsuit. The Information Exchange: Cerner Milking Edition (Sep 18): This was so fucking fun. Ryan Tucker, Ryan Brickner, Brad Thorson, and I try an Around the Horn format, complete with points, penalties, and a mute button. We debate whether Oracle Health is dead, who would actually buy Cerner (IBM enters the chat), p(Doom), and why the front desk still hands you a clipboard. Regulatory Ask Not What Your Network Can Do (Sep 23): CDC’s RFI on public health data intermediaries lists use cases already served, unevenly, by eCR, lab reporting, IZ Gateway, and syndromic surveillance. The real opportunity sits in one question about AI: a network that can handle the next emergency without another interface project. Court cases Particle v. Epic: The Naughty Schoolteacher (Sep 4): After a summer-long vigil, the answer on Epic’s early summary judgment bid is two paragraphs and a remedial assignment. Particle advances to the next grade, and market definition gets another year of discovery. The Epic Discovery Files (Sep 8): Texas’s motions to compel arrive with a 251-page appendix of requests, objections, and meet-and-confer letters with Cravath. Inside: Epic using generative AI for document review, denied interoperability requests in scope, and Noerr-Pennington raised against lobbying discovery. Epic v. Health Gorilla: “Working as Designed” (Sep 9): Epic wants nothing to do with the data breach MDL, and explaining why puts fresh discovery on the public docket. The spiciest allegation: Health Gorilla told GuardDog to scrub its law firm business from its website instead of cutting off access. Veeva v. Epic: Legal Bypass Surgery (Sep 15): Veeva asks the Wisconsin Supreme Court to skip the Court of Appeals, while law professors and three policy groups line up as amici. Meanwhile, Epic’s lawyers apologize for another round of citation errors, including a quote that never existed. Texas v. Epic: Behind the Black Bars (Sep 17): The court portal served up Epic’s unredacted filings, revealing a $5 million document review budget and the AI workflow behind it. Also inside: the 200-plus company names Texas wants searched, and one very expensive Zoom invitation. OpenEvidence v. Doximity: Consequences Will Follow (Sep 25): OpenEvidence tells the court it will not comply with a discovery order, and its own lawyers at Quinn Emanuel say they won’t defend the choice. Add years of Slack reported unrecoverable, and Rule 37 sanctions come into view. Health Tech Keeps Choosing Violence (Sep 28): Doximity moves to end OpenEvidence’s case, Epic asks Texas to show its work, and a sleepy Audacious Inquiry patent fight sprouts antitrust and information blocking counterclaims. The main event is a long-sealed Cognizant v. Infosys ruling that hints where system of record antitrust claims can survive. EHRs One Verb for Oracle Health (Sep 14): Oracle’s earnings call quantifies every data center to the decimal point, while Oracle Health gets a single verb: “accelerate.” Panning the few healthcare mentions turns up an agentic care management system, a research-to-care ledger play, and the question of whether healthcare gets Larry’s patience. Epic’s Forretress Under Siege (Sep 30): Judy Faulkner tells a panel Epic paused hundreds of projects to harden its software and calls it a “shame,” while a spokesperson insists the roadmap hasn’t changed. Project Glasswing, a Pokémon-branded QAN sprint, and a trove of Jodel grievances reconcile the two Epics and preview the Jevons paradox coming for all software. Industry Analysis Scanning for a Network (Sep 1): Scan.com raises $220M to build the imaging network labs never got, speedrunning Zocdoc’s consumer-to-B2B pivot. Its wedge to network density may be the most American one available: personal injury litigation. The Front Desk Wants the Damn Whole Building (Sep 16): Hello Patient buys Converse Health, pushing its AI front desk into referrals, chart work, and prior auth. The copilot categories keep blurring, and your distribution partner is still your final boss. Cross-industry Comparisons A Different Patchwork Quilt (Sep 10): Healthcare loves to envy open banking, but the US version has no mandate, a toll booth at Chase, and data quality problems of its own. The grass isn’t greener; it’s another American patchwork quilt, and perhaps a worse one. Hail, Benihydra (Sep 21): Salesforce brings its platform into Claude, Slack, and its own agent, inviting the interfaces that might replace it. Cut off one head and more grow back, so long as the records underneath stay put. Living on A Trade Secret Prayer (Sep 22): Six credit unions are suing Fiserv, the Epic of core banking, by claiming their own member records as trade secrets. Banking has no Cures Act, so its lawyers reach for legal alchemy that healthcare has already tried. Other News None this month External Media Nabla Accelerate NYC: I kicked off fall conference season at Nabla’s Accelerate event in New York, where Delphine Groll opened by asking the room to picture the company it wants to become and the one it doesn’t. I liked her framework of bureaucracy, fear, and ego as the blockers. I also love vendor conferences/events in general - different vibe than industry biggies. Healthcare 101 with Nikhil Krishnan: I briefly guest lectured Out-Of-Pocket’s Healthcare 101 class. Appreciated Nikhil’s takeaways cover whether AI doctors can query HIEs, why healthcare’s data-liberation rules beat most industries’, and the hi-res graphic is in the comments. HCN: Epic Probed by the FTC: I joined the HCN guys to talk through the FTC’s investigation into Epic. Cedric’s new hairdo was an unexpected plot twist. The episode also covers MFN drug pricing, healthcare M&A and Eli Lilly’s acquisition streak. Fall Conferences: At eHealth Exchange’s Annual Meeting in Austin on Oct 27, I’ll moderate a panel on the tensions between AI, HIEs, and timely patient access with Jean Ross (Primary Record), Therasa Bell (Kno2), Byron Crowe (Doctronic), and Michael Marchant (Freenome). Here’s the rest of my schedule if you want to meet up: CommonWell (Redwood Shores, CA): Oct 13-14 Will be participating in a fun Jeopardy event Open@Epic (Madison, WI): Oct 20-23 Will be enjoying Verona, Willy Street, and other local adventures eHealth Exchange and Sequoia Project (Austin, TX): Oct 27-29 Yeehaw HLTH (Vegas): Nov 15-18 Groundhog Day, Venetian Edition RSNA (Chicago): Nov 30-Dec 2 See me at “Governing AI in Breast Imaging: What Health Systems Are Actually Doing” Digital Health Counsel 2026 AI Summit (Seattle): December 2-3 Will likely be speaking to a bunch of lawyers about information blocking Posts I Liked ChatGPT’s Epic integration: game changer or nothing burger?: Joshua Liu, MD offers five thoughts on OpenAI’s Epic launch, starting from the point that it rides the same open APIs available to anyone. He argues read-only access leaves ordering to Art and the ambient startups, and asks why HCA is piloting it alongside Commure. He’s sorta a must-follow at this point - consistently excellent, thought-provoking takes. Epic, Lilly, and the Discovery pass: Seth Chaney reads Epic’s first major Discovery deal (with Eli Lilly), as well as its revised developer terms on commercial displays, as the pipe finally opening between EHRs and pharma. Life sciences and health continue to collide. Scott Rossignol on EHR payer platforms and ePA fees: Scott argues the top ambulatory EHR vendors are turning the prior auth mandate into a per-member-per-year toll on payers, for an API whose operating cost has nothing to do with covered lives. His fix is two lines of regulatory text: put the CRD/DTR/PAS certification criteria in the Base EHR definition, and bring payer-facing ePA connectivity under § 170.404’s cost-based fee rules. It’s a good solution. Health API Guy is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
The Witcher 3 Remastered Crushes GPUs With Path Tracing, but Free Mod Claws Back Up to 30% Performance
Following its surprise announcement during this year's gamescom Opening Night Live, The Witcher 3 Remastered is now available on PC, PlayStation 5, Xbox Series X|S, and Nintendo Switch 2. While the number of improvements to gameplay is staggering and well thought out, what most were looking forward to was the visual uplift, which includes very demanding path tracing support on PC. Thankfully, a mod has already come to the rescue, as it did after the launch of the Next-Gen update, optimizing both ray tracing and path tracing for better performance with minimal loss of quality. "Faster RT/PT in The Witcher […]
The business of living longer is booming in Dallas
New procedures and tests can help people live a more "optimized" life, but they are usually so expensive that they remain largely inaccessible.
With a ‘Box-Bed,’ a Family in a Brooklyn Loft Found (Semi) Privacy
A couple built a box inside their condo that gives everyone in the family a customized space to hang out.
Dove Lab links dialogue about racism and Black maternal health
Researchers at the Dove Lab published two studies exploring how communication between providers and Black women can minimize pregnancy risks.
Adexo Advertising Surpasses 500 Active Businesses and $20 Million in Managed Ad Spend
MINNEAPOLIS, MN / ACCESS Newswire / September 28, 2026 / , a Minneapolis-based AI advertising platform that builds and optimizes Facebook and Google Ads for local and service-based businesses, today announced that it now serves more than 500 active businesses and has managed more than $20 million in advertising spend since launching in 2022.The milestone reflects growing demand among small and mid-sized businesses for advertising measured by qualified leads and booked jobs rather than clicks.
Navigating the American Dream: How Integrated Financial Tools, Credit and Rewards Can Help Small Businesses Succeed
(Feature Impact) Owning a small business has been a cornerstone of the “American Dream” for generations. It represents the chance to transform a passion into a livelihood and legacy. However, turning dreams into reality is rarely a smooth or easy process and requires more than ambition alone. Today’s business owners need support and access to tools that enable them to overcome challenges and keep growing.#placement_678081_0_i{width:100%;margin:0 auto;}var rnd = window.rnd || Math.floor(Math.random()*10e6);var pid678081 = window.pid678081 || rnd;var plc678081 = window.plc678081 || 0;var abkw = window.abkw || '';var absrc = 'https://ads.empowerlocal.co/adserve/;ID=181918;size=0x0;setID=678081;type=js;sw='+screen.width+';sh='+screen.height+';spr='+window.devicePixelRatio+';kw='+abkw+';pid='+pid678081+';place='+(plc678081++)+';rnd='+rnd+';click=CLICK_MACRO_PLACEHOLDER';var _absrc = absrc.split("type=js"); absrc = _absrc[0] + 'type=js;referrer=' + encodeURIComponent(document.location.href) + _absrc[1];document.write('');Recent research conducted by the Capital One Insights Center shows 75% of more than 1,000 surveyed small business owners with more than one employee and annual revenues of up to $20 million are confident about the future, and 69% believe their business is actively primed for growth.While this optimism is promising, 47% of business owners still said their operations either stayed the same or became less efficient over the past year, citing issues like back-office friction and fragmented financial systems that make it difficult to get a clear picture of the health of their businesses.If you’re a small business owner eager to grow but not sure how to get there, start with this advice from real small business owners and experts at Capital One.Identify Sources of FrictionBefore you can pour effort into growth, you must understand what barriers are holding you back. Take time to look under the hood of your business to identify where time and energy is being lost.For example, you may be among the 78% of small business owners who feel stressed and uncertain about expense management – think hours spent hunting for receipts, manually entering numbers into software and reconciling accounts. Operational challenges aren’t just a hassle; they also pull attention away from important priorities like serving your customers and planning for growth. “We were focused on making as many candles as possible, especially during the busy season,” said Katie Roering, co-owner of Fontana Candle Co. “A lot of the back-office tasks like procurement, raw material purchasing, forecasting – all the really important things – were done at 3 a.m., 8 p.m. or on Saturday and Sunday, and there really just was not enough time in the day to get everything done that we needed to. We just knew as we continued to grow, we needed to streamline our processes, build out our team and keep moving forward.”Use Integrated Tools to Manage FinancesInstead of balancing 10 different tracking and analysis tools, you can turn to one-stop solutions to improve efficiency. Time gets lost when you’re forced to manually gather and interpret relevant data before you’re able to act. You need a platform that handles the busywork for you.Integrated, or “all-in-one,” financial tools – like accounting and bookkeeping platforms with automation capabilities or business credit cards featuring built-in analytical tools – allow you to easily stay on top of cash flow and day-to-day operations. For small businesses where every hour and dollar makes a difference, consolidating and automating systems can have an immediate impact. In fact, 51% of survey respondents said integrated tools have already fueled their growth.Leverage Credit Access and Rewards WiselyGrowth requires capital, so access to credit is a game-changer for many business owners, with 77% describing it as a key factor in achieving business resilience. Having funds accessible when you need them makes your business more capable of weathering storms such as equipment failures and seasonal slowdowns. It also puts the power in your hands to act when an exciting opportunity presents itself, like an inventory flash sale or the chance to advertise in a new market.Access to credit comes with another advantage: rewards. By using credit cards for your daily business expenses, you can earn cash back, points or travel rewards. Whether you redeem these to cover everyday expenses, book business trips or reinvest in the business, they can act as a bonus source of income. Learn to maximize rewards like the 84% of small business cardholders surveyed so you aren’t leaving money on the table.To learn more about how small business owners can identify obstacles, employ integrated financial tools and use credit as a tool for growth, read the full report at capitalone.com/about/insights-center.Photos courtesy of Shutterstock
Losing the Same Weight Didn’t Produce the Same Health Benefits
Among several diets tested in a clinical trial, a ketogenic diet produced the greatest improvements in liver and metabolic health. Losing the same amount of weight does not necessarily produce the same metabolic benefits. In a randomized clinical trial, three very different diets helped adults with obesity lose about 10% of their starting weight, but
The Best Time To Eat Probiotic Foods for Gut Health and Immunity
While eating probiotic foods at a certain time of day may not impact their effectiveness, there are specific situations that could maximize their benefits, experts say.
Padres Place All-Star Pitcher on IL Days Before Postseason
The Padres placed Casey Mize on the 15-day injured list with an ankle injury one day after the struggling starter acknowledged his physical limitations.
Slime Molds and the Growing Science Controversy Around “Intelligence”
Instead of claiming, like the eliminationist, that neither humans nor slime molds are really intelligent, the panpsychist will claim that they both are — and then minimize the difference between them.
Intel Panther Lake Teardown, 18A, BSPD, GAAFET, SemiAnalysis STEEL
Panther Lake debuts the first commercial implementation of backside power delivery (BSPDN), introduces Intel’s first iteration of gate-all-around (GAA) transistors, and showcases their advanced packaging capabilities with its Foveros-S assembly. With Panther Lake, Intel’s manufacturing arc has shifted from nebulous roadmaps to shipped silicon, a significant milestone on their long road back to competitive semiconductor manufacturing. To evaluate the extent of Intel’s comeback, we tore down Panther Lake. The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. Our teardown traces 18A from its four-sheet RibbonFETs (Intel’s marketing name for GAAFETs) and gate stacks through contacts, frontside and backside wiring, and the bonded carrier. We explain how these material and integration choices improve gate control and reduce resistance, while adding capacitance, thermal resistance, and process complexity. Our measurements put Panther Lake’s 18A compute logic and TSMC N3E GPU logic at similar logic density. However, 18A does not lead TSMC N3P, N2 or Samsung SF2 in peak density. Panther Lake’s CPU cores are incremental updates, and the high-end GPU still uses TSMC N3E. Panther Lake assembles one compute tile, one GPU tile, and one I/O tile atop a passive base tile using Intel’s Foveros-S advanced packaging. Both compute tile variants use Intel 18A. The Xe3 GPU options are a 4-core GT1 tile on Intel 3 and a larger 12-core GT2 tile on TSMC N3E. Both I/O tile variants use TSMC N6. [1], [2] Our analysis centers on the PTL-U compute tile, both the 4-core and 12-core GPU tiles, as well as the 12-lane I/O tile. In conventional chips, power and signal are routed through the same frontside metal stack towards the device frontend. Power rails consume scarce routing resources near the transistors, while tall via stacks carry VDD and VSS from the coarse upper wires to local rails. Backside power delivery (BSPD) moves the main power network behind the transistor layer, to the backside, separating it from frontside signal routing. We covered BSPD and its impacts in 2024. [3], [4], [5] Intel’s BSPD implementation, branded as “PowerVia”, routes power through dedicated backside metals to nano-TSVs, which connect those rails to local source/drain (S/D) contacts. Implementing that separation requires Intel to build the interconnect stacks from both sides of the wafer. The frontside comprises the M0-M14 signal stack, while the backside comprises the BM0-BM5 power stack. M0 and BM0 are closest to the transistors. The nano-TSVs connect the two sides, but Intel patterns and etches each via from the front after forming the contacts. A narrow via runs from the side of the contact deep into the silicon substrate. Intel then completes the frontside signal metal stack, bonds the wafer to a carrier, flips it and removes the original substrate until the buried via tips are exposed. The backside metal stack is then deposited directly on the revealed vias. The nano-TSV and backside-via profiles taper in opposite directions because Intel forms them from opposite sides of the wafer. The transistor structures form the FEOL. Local contacts and nano-TSVs connect them to the wiring. M0 begins the frontside interconnect stack. The silicon carrier remains attached above the frontside interconnects. It supports the device wafer during substrate removal and backside processing and remains part of the finished chip’s thermal path. PowerVia removes the main power distribution from the congested frontside metals, routing supply through shorter and wider backside wires. Its lateral landing still occupies area in the standard cell, so it recovers less cell area than a direct backside contact. [3] Nano-TSVs beside the logic devices carry VDD or VSS from the backside power network, while signal connections continue upward through the frontside metals. Backside Interconnects Samsung SF2 data is included for comparison to Panther Lake’s within this article. SF2 is the incumbent GAA foundry node but lacks BSPD, serving as a useful reference to evaluate 18A. A full teardown of Samsung’s S26 products, processed on SF2, will be shared soon.Nanosheet-cut EDS comparison. The PowerVia supply path runs from the backside Cu rails through Mo-lined W nano-TSVs to the local transistor contacts. In this cross section, the tapered connection spans roughly 150 nm from the contact level to BM0. The Ta liner confines Cu and promotes adhesion to the surrounding stack; the AlOₓ etch stop controls the next dielectric etch above the rail. Dielectric beneath the ribbons electrically separates the devices from the backside wiring and removes the conducting silicon body below the channel. [6] AlOₓ serves as an etchstop (ES), enabling endpointing and protecting the underlying layers. Low-volatility aluminum fluoride reaction products resist the fluorinated plasma, allowing a thin AlOₓ film to protect the metal while the surrounding low-k dielectric is removed. [6], [7]. While the BM0 and layers above the M1 lines show double AlOx layers, Our SMIC N+3 teardown showed single AlOₓ layers. SMIC uses a simpler local AlOₓ substack, while the remaining cap and etch sequence provide the required landing protection. So why double layers? The closely spaced AlOₓ doublets provide two protected endpoints in the etch sequence. Intel documents an AlOₓ/SiN/AlOₓ stack that explains the benefit. The main dielectric plasma etch stops on the first AlOₓ film; a selective wet clear opens that film; a second plasma etch removes the intermediate SiN and stops on the second AlOₓ film. The final wet clear exposes the metal landing surface. SiN is the intermediate dielectric in Intel’s published example. [8] The second stop protects the metal through a cap breakthrough. Wide openings can etch faster than narrow ones, and etch depth varies across the wafer. Metal under an early-clearing opening would otherwise be exposed while other openings still need more etching. Staged protection widens the process window and reduces metal erosion, corrosion and void formation. [8] TSMC documents AlN/AlOₓ/SiOC/AlOₓ above Cu, with AlN blocking Cu diffusion, and a simpler AlN/SiOC/AlOₓ variant that omits one AlOx film. [9] Levels with different opening sizes, aspect ratios, pattern densities and cap materials need different etch margins. A double AlOx stop is useful where another protected endpoint justifies the added processing. The extra film adds formation, selective opening and cleaning steps, plus another set of interfaces to control adhesion, moisture, and stress. These blanket films are opened through the existing via pattern, so each film does not require another lithography mask. AlOₓ adds parasitic capacitance when it replaces lower-k dielectric; two thin AlOₓ films can nevertheless contain less AlOₓ than one thick film. Total thickness, placement, and theintermediate dielectric determine the electrical cost. Deposition chemistry also changes AlOx permittivity and residual hydroxyl content, which can oxidize the underlying metal. [7], [8], [10], [11] The backside stack separates into relatively fine BM0-BM2 wiring near the devices and coarser BM3-BM5 power distribution. The largest pitch increase occurs between BM2 and BM3. BM0’s pitch closely matches the logic-row height, fitting local power delivery to the cell rows. Higher levels aggregate current through larger conductors: routing density becomes less important than low resistance and current capacity as the network approaches the package. This hierarchy provides wide power wiring for the power delivery network without consuming scarce frontside signal-routing resources. [3] The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. Frontside Interconnects Intel 18A combines Mo-lined W contacts and nano-TSVs with a separate backside Cu power network. Samsung SF2 keeps power on the frontside, using Ti-based contact interfaces and Ta-based barriers and Co liners around Cu wiring. In 18A standard-cell rows, backside power rails supply the devices through nano-TSVs within the cells, freeing frontside routing resources. Samsung’s M0 accommodates both power and signal connections. From the device toward M0, the connection runs through a Ti-based S/D interface, W contact fill, a Mo-lined W via, and the Cu M0 wire. Mo supplies a conductive nucleation and adhesion layer for W, replacing the resistive TiN liner used in conventional W integration. This increases the effective conduction volume within the feature while retaining W fill and its established polishing, cleaning and etching processes. Intel’s Mo/W patent describes this integration tradeoff. The nano-TSV uses the same Mo-lined W construction in the backside supply path. [12] The move from TiN to Mo is an incremental change. While a full Co or Mo fill can also reduce the volume lost to liners in very small features, it requires new integration schemes that increase complexity and risk. Cu remains attractive for wider wires due to its low resistance. As wires and vias shrink, the diffusion barrier consumes an increasing fraction of their cross-section. [12], [12], [14] Intel uses Co/Ru liners at M0-M1, Co at M2-M4, and Nb at M5-M9. The lower-level liners help Cu adhere and reduce void formation during trench fills. Applied Materials’ Endura has new thermal control that facilitate wetting process, so the thin film continuity is good enough that good capillary pressure will drive Cu atoms to the via bottom without voiding. Intel’s choice to use Nb is particularly interesting. Intel’s Nb patent describes a conductive diffusion barrier intended to reduce the barrier’s contribution to resistance relative to conventional Ta-based barriers, particularly at via bottoms where all current crosses the barrier. The patent pairs Nb in coarser levels with the option of lower-cost PVD processing. [15], [16] The upper metal layers support thicker barriers formed through physical vapor deposition (PVD) despite its worse coverage and uniformity. Meanwhile, the lower metal layers require thinner barriers deposited through conformal atomic layer deposition (ALD). Co/Ru adds another material interface and requires controlled deposition and Cu fill. Changing liners and barriers by metal layer allows Intel to optimize interconnect resistance, process complexity, and reliability. [15, 16] RibbonFET, Intel’s name for its gate-all-around FETs (GAAFETs), replaces the FinFET’s vertical fins with four stacked horizontal silicon nanosheets, allowing the gate to surround the channel on every side. The path to GAAFET begins with the planar transistor. A planar MOSFET places the gate above the channel between its source and drain. Pairing an NMOS with a PMOS transistor creates a CMOS inverter, in which the NMOS pulls the output low for a high input, and the PMOS pulls it high for a low input. The gate must retain electrostatic control of the channel to ensure clean switching. As gate lengths shrank, the drain began to compete with the gate for that control, increasing off-state leakage. Electrostatic control was restored through an architectural evolution that raised the channel into a vertical fin and wrapping the gate around three sides. Called “FinFET”, this new architecture packed more effective channel width into a smaller footprint. Further scaling made it harder to maintain both drive current and leakage within smaller cells, and reintroduced the same problems planar MOSFETs faced. Nanosheet GAAFETs close the fourth side by replacing the vertical fin with a stack of horizontal nanosheets, each surrounded by the gate. The tighter electrostatic control suppresses leakage at shorter gate lengths while stacking adds effective channel width within the cell footprint. In a FinFET process, channel width changes in discrete steps as designers must add or remove whole fins. Nanosheet width can instead be adjusted continuously within the process’s design rules. Wider sheets increase drive current, while narrower sheets reduce capacitance at the cost of drive current. Intel 18A uses stacks of four nanosheets each and varies their widths across logic and SRAM. At the process level, adding more sheets to each stack increases effective channel width and drive current, but complicates fabrication. RibbonFET vs MBCFET Samsung began GAAFET production in 2022 with SF3E, following with SF3 and now SF2. Its ‘MBCFET’ provides a useful structural comparison with Intel’s first RibbonFET implementation. [17] STEEL is digging deeper into SF2, used in the Exynos 2600, and TSMC’s GAAFET N2, used in Apple’s A20 Pro, in upcoming newsletter articles. We’re throwing some teasers on X. Let’s compare Samsung SF2’s MBCFET with Intel 18A’s RibbonFET. Subscribe Even to the untrained eye, Intel’s extra nanosheet is obvious. Intel stacks four ribbons to Samsung’s three. Samsung’s sheets are much wider in these fields, so both sheet count and width matter to the available channel perimeter. Sheet width also changes which silicon surfaces carry current. On conventional (001) silicon, wide nanosheets emphasize the broad top and bottom surfaces, favoring electron transport; the larger sidewall contribution in a narrow sheet favors hole transport. Thinner sheets improve gate control but increase confinement and scattering. This makes width and thickness part of the NMOS/PMOS balance, alongside strain and threshold voltage. [18], [19] GAAFET designs like 18A use different work-function-metal (WFM) stacks for NMOS and PMOS. Around each ribbon, a thin SiOx interfacial layer separates the silicon channel from the HfOx high-k dielectric, with La providing dipole tuning and the WFM wrapping the dielectric. NMOS uses a TiAl-based stack, while PMOS uses TiN WFM. W fills the remaining gate trench, providing a lower-resistivity path where the work-function layers are no longer needed. In this field, the PMOS stacks leave room for W between ribbons, while the NMOS stacks occupy more of those gaps. A silicon-based dielectric marks the P/N boundary, allowing the PMOS and NMOS gates, sharing the same gate trench, to be processed sequentially. Fast logic paths, retention circuits, and SRAM need a family of threshold options. Changing threshold without substantially changing device dimensions, capacitance or fabrication complexity is valuable. FinFET processes typically use different work-function-metal stacks. In a four-ribbon GAA stack, the narrow sheet-to-sheet gap limits how much WFM can fit around each channel. La in the gate dielectric creates interfacial dipoles at the SiOx/HfOx boundary, shifting effective work function and tuning threshold voltage. This gives Intel another control alongside its NMOS and PMOS WFM stacks. Low-threshold devices improve critical-path drive; higher thresholds reduce leakage elsewhere. Dipole tuning is especially useful in GAA because it changes threshold without consuming the narrow intersheet gap with thicker WFM. Precise control of La incorporation, diffusion and interface quality has long been a challenge, limiting viability in high volume production but is now seen from every leading-edge foundry. Intel’s patent describes depositing a dipole-forming oxide above HfOx and annealing it toward the interfacial oxide before completing the work-function and fill metals. This separates threshold tuning from the space available for metal. Newer research addresses the thermal cost: imec’s 2026 dipole-middle research inserts the shifter between two HfOx depositions, shortening the diffusion path while protecting SiOx during patterning. [20], [21]Matched-cut EDS, Intel 18A (left) vs. Samsung SF2 (right). Intel retains raised source/drain epi beneath its contacts, while Samsung recesses W deep into the epi to form a V-shaped Ti-lined interface. The deeper contact increases metal-to-semiconductor area and shortens the current path from the lower sheets, reducing contact and spreading resistance. It also removes epi volume and brings the contact etch closer to the channel ends. Retaining more epi preserves the material available for strain transfer, especially from SiGe into PMOS. These geometries balance contact access against stress engineering and etch margin. [22], [23] Samsung stacks three sheets to Intel’s four ribbons, and both processes use sheet width to tune drive strength. In our Samsung cross-sections, widths range roughly from 19 to 30 nm in the NPU rows and 37 to 50 nm in the CU cell. The Samsung nanosheets taper, with the widest sheet at the bottom and the narrowest at the top. Both processes use HfOx gate dielectric and Ti-based work-function stacks, with Al in the NMOS stack. In the Samsung devices shown here, the dielectric and WFM occupy the intersheet gaps, leaving W above the top sheet. Intel’s PMOS stack leaves more room between ribbons, and W fills those gaps while the thicker NMOS stack leaves W mainly in the upper trench. Gate-stack EDS maps. The W between Intel’s PMOS ribbons provides a conductive path close to the lower gates. Where WFM fills the entire gap, the gate still surrounds the channel, but voltage reaches it through the more resistive work-function films. Thinner WFM and dipole tuning preserve room for low-resistivity fill; Mo and Ru are alternative fill metals being developed for further scaling. [24] A masked, sequential WFM flow explains the different gate heights and inter-nanosheet fill. The proposed sequence below shows how separate NMOS and PMOS work-function steps produce that geometry. Enabled by the BSPDN process, Intel replaces the dense-logic silicon subfin with dielectric, removing the parasitic conduction path below the ribbons and reducing substrate-related capacitance. A retained silicon body as in classical, non-SOI, planar and FinFET designs needs junction and punchthrough-stop engineering to suppress leakage. Dielectric isolation makes that leakage less sensitive to the subfin doping profile but adds removal and fill steps. It also weakens the direct thermal path through silicon, making the contacts, metal stacks and package more important for heat extraction. [24], [26] Fluorine is concentrated around selected Intel device structures in the maps. WF6 is a standard precursor for W nucleation and fill, while barrier films protect adjacent dielectrics from fluorine attack. Low-fluorine W processes reduce the residual-F burden. Chloride-based precursors avoid introducing F during W deposition, but require control of chlorine attack, nucleation and fill quality. The integration target is a continuous, low-resistance W path with a thin protective liner and minimal chemical damage to the surrounding stack. [20], [27], [28] The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. We measured cell height, gate pitch, metal geometry, and ribbon dimensions at the XTEM sites shown below. The tables group these dimensions by site and device polarity. Our “sheet cuts” cross the silicon channel and show the ribbons end-on. “gate cuts” run along the channel through successive gates. The 18A logic cell dimensions point to a five-track logic library while the N3E and Intel 3 cell dimensions evidence a seven-track logic library. The DDR-PHY uses wider M0 wires and much larger spacing than core logic. That trades routing density for lower wire resistance and weaker coupling between neighboring nets. The geometry suits the current delivery and coupling requirements of analog, clock, and I/O circuitry. PowerVia lets 18A combine a compact cell height with wider M0 geometry by moving the main power rails off the signal-routing tracks. That relaxes local wire scaling while preserving a small cell footprint. Cell height and gate pitch set the geometric density; pin access and routability determine how much of it a real block can use. [29] The biggest takeaway from our gate-pitch measurements is that Intel 18A compute logic and TSMC N3E GPU logic have similar density in the Bohr representative-cell model. The 18A example is 18.6% denser than the Intel 3 GPU example. Gate pitches are nearly identical across the three sites, so cell height drives most of the difference. The Bohr model combines a four-transistor NAND2 spanning three gate pitches and a 32-transistor scan flip-flop (SFF) spanning nineteen pitches, weighting their densities 60:40. The sensitivity column shows how independently changing cell height and gate pitch by ±1 nm changes the result. This compares representative cell geometries; whole-die density also depends on cell mix and placement. The 18A P-core gives M0 substantially more metal cross section than the N3E vector engine. Treating each profile as a trapezoid gives 2.63 times the area per line and 1.84 times the area after normalization by routing pitch. The larger section reduces the geometric contribution to line resistance and lowers current density for a given current. Taller and wider wires also add capacitance, so circuit delay depends on the balance of resistance and capacitance. The DDR-PHY has less metal area per routing width than the 18A core fields, while remaining above N3E. [30] Area = height × (top CD + bottom CD) / 2, including liners. Area/pitch normalizes by routing width. Taper is the symmetric sidewall angle from vertical, with the largest angle belonging to the DDR-PHY. Compute tile The measurements show how ribbon dimensions and gate-stack geometry vary across the compute tile and between NMOS and PMOS to balance channel drive, gate load and the space needed for the dielectric/WFM stack across logic, SRAM and the DDR-PHY. Width mainly changes available channel perimeter; thickness also changes electrostatic control and carrier confinement. Gate-stack thickness then determines the space left for low-resistivity fill P-core and LP E-core logic Both the P-core and LP E-core use multiple nanosheet widths. Widths are measured on high-magnification XTEMs while wider-field images demonstrate additional width choices within the LP E-core. Multiple widths are expected even within an LP E-core. Timing-critical paths, buffers and cells with different fanout need different drive strengths. The lower-magnification fields show this width diversity beyond the sites quantified in the table. L2 and L3 SRAM GAA gives SRAM designers another way to balance the pull-up (PU), pass-gate (PG), and pull-down (PD) transistors. FinFET bitcells set device strength through fin count while GAA adds nanosheet width as a sizing knob. In a 6T SRAM cell, a strong pull-down relative to the pass-gate limits read disturbance, while a strong pass-gate relative to the pull-up improves writability. During a write, the pass-gate and write driver pull the node storing “1” below the inverter trip point. During a read, the pull-down holds the node storing “0” low. Bias, threshold voltage, mismatch and assist circuitry set the remaining margin. FinFET high-current cells commonly use a PU:PG:PD fin-count pattern of 1:2:2, a device-sizing ratio rather than a current ratio. Ribbon width lets Intel balance SRAM strengths without adding whole fins. The L2 cell uses its narrowest ribbons for PU and widest for PD, improving writability and read stability respectively. Intel’s disclosed HCC operates without assist; its denser HDC uses negative-bitline write assist. Pulling the selected bitline briefly below ground increases pass-gate overdrive so it can overpower the pull-up at lower supply voltage. That buys density and low voltage writability at the cost of boosting circuitry, switching energy, and additional voltage stress that must be controlled. [31], [32] Four rectangular ribbons give the perimeter = 8 × (width + thickness), before corner rounding. PG/PU is 1.49 and PD/PG is 1.16. The L3 structures closely resemble L2 in layout and cell height. Fewer L3 nanosheet widths are tabulated because fewer high-magnification images were available. DDR PHY The DDR-PHY trades density for controlled analog behavior and reliable off-chip signaling. It contains drivers, receivers, delay circuits, and calibration logic that set drive strength, sampling time, and voltage margin. Repeated four-sheet devices with similar widths fit the use of regular transistor units for matching and programmable drive. Its wider local wiring provides room for current delivery and separation of sensitive signals, while consuming more area than a dense core-logic grid. The layout serves the memory channel’s electrical requirements as well as digital logic density. [33] The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page. Intel 3 GPU devices Vector engine logic Intel 3’s XVE logic uses two-fin PMOS and NMOS devices with power rails in M0. Its cell height and M0 pitch give a seven-track geometry, two tracks more than the 18A logic. One-fin groups also appear among the two-fin devices. Intel 3 L2 SRAM The Intel 3 L2 SRAM uses the familiar HCC sizing pattern: one PU fin, two PG fins, and two PD fins. N3E GPU devices Vector engine logic The N3E XVE field contains repeated two-fin devices with seven-track cell geometry. N3E remains a FinFET process, giving Panther Lake a direct FinFET-to-RibbonFET comparison. N3E L2 SRAM The N3E L2 SRAM uses the same PU:PG:PD fin-count pattern of 1:2:2. Panther Lake-U follows Lunar Lake’s floorplan quite closely. Both pair 4 P-cores with 4 LP E-cores and NPU, media and display engines in similar locations. Lunar Lake also uses Xe2, the direct predecessor to Panther Lake’s Xe3 GPU. This makes Lunar Lake the most direct basis for our comparisons. Arrow Lake differs in core count and uses the older Xe-LPG GPU architecture, so we only use it where it offers a more direct component-level comparison. Compute tile Panther Lake compute-tile floorplans remain sparse even months after launch. Intel 18A’s backside metal and dielectric stack must be removed without damaging the underlying structures before a clean transistor-level floorplan can be imaged. Most published die shots hide or heavily process the background, but we are quite proud of the die shot we achieved and are excited to show the work we have done. We measured the areas of the key components on the compute tile and compared them with their Lunar Lake predecessors on TSMC N3B. These help us to capture changes in block area and compare the two chips across process nodes and designs. Our total tile areas exclude the scribe-line area. The compute-plus-GPU subtotal below uses the PTL-U compute tile and GT1 GPU; it excludes the I/O tile and passive base. Individual block areas use the boundaries marked on the floorplans The compute-plus-GPU row is recomputed from the displayed PTL-U and GT1 areas. Component rows use their stated per-region counts and are not an additive partition of the whole tile. The P-core area remains almost unchanged between Lunar Lake and Panther Lake, despite L2 capacity increasing from 2.5 MiB to 3 MiB. Arrow Lake uses the same Lion Cove core as Lunar Lake but also has a 3 MiB L2. Cougar Cove fits 20% more L2 into the same P-core area. The larger private cache keeps more of each core’s working set close to its execution units, reducing access to shared L3 and DRAM. Extra capacity adds storage leakage and lookup energy, so designers balance it against avoided lower-level accesses. The shared P-core L3 cache also shrank by 14.8%. [2] Cougar Cove combines a similar footprint with Intel’s reported power-efficiency improvements. RibbonFET’s tighter channel control reduces leakage, while PowerVia reduces supply droop and allows tighter voltage guardbands. [1] Darkmont’s four-core LP E-core cluster is 5.0% smaller than Skymont’s on Lunar Lake, with most of the reduction in its L2 regions. The 1 MiB region shrank by 8.4% and the 1.5 MiB region by 14.9%. The tag arrays also use one fewer visible row. Tags identify which memory addresses the data array holds, so rearranging them changes the cache’s layout and wiring without requiring less data capacity. [2] The LP E-cores share one L2. This pools capacity and avoids duplicating all the cache machinery, but the four cores contend for its banks and bandwidth. Their separate cluster also keeps light work away from the performance cluster and its L3, allowing that larger domain to sleep. [1], [2] Cache area includes more than the storage cells. Tags identify each line, decoders select rows, sense amplifiers read the small bitline signal, and wires connect to the banks. Splitting an array into smaller sections shortens wordlines and bitlines, improving access speed, but duplicates peripheral circuits. Panther Lake’s smaller cache regions therefore reflect the complete memory implementation, including how much of each region is devoted to storage. [34] Unlike Meteor Lake and Arrow Lake, Panther Lake has no separate SoC tile. The NPU, LP E-cores, memory controllers, PHYs, media and display engines now share the compute tile. This removes an active die and keeps CPU memory traffic on one die. The cost is moving PHY and I/O-related circuitry onto 18A: drivers, receivers and analog circuits must still meet external voltage, loading and signal-integrity requirements, so their area does not shrink like dense digital logic. [1], [2] The biggest shrink comes from the NPU, which occupies 36.9% less area. NPU 5 consolidates the same total INT8 MAC count into half as many neural compute engines. Each of the three NCEs has a larger MAC array to make the complete NCE envelope 22.6% larger than an NPU 4 engine. Consolidation also halves the number of scratchpads and SHAVE DSPs, from 12 to 6. The MAC array handles matrix multiplication and convolution, while SHAVE executes vector and custom operations that fit the array poorly. [1], [2], [35] The paired floorplans identify each NCE envelope and its scratchpad, MAC, and SHAVE regions. Each measured MAC polygon is counted once per NCE in the area accounting below. The scratchpads store weights, activations, and intermediate results near the MAC arrays, allowing repeated use without fetching them again from DRAM. Halving their number delivers the largest measured area saving but leaves less local storage for the same total MAC count. Layers that no longer fit locally require smaller working tiles or more transfers of intermediate data. The benefit depends on keeping the enlarged arrays busy while managing that tighter storage budget. [36] NPU 5 also adds native FP8. Using half the operand width of FP16 reduces storage and transfer demand, helping workloads fit the smaller local memory budget. Lower precision and format-dependent range make scaling and model validation part of deployment. Hardware activation functions further reduce work that would otherwise occupy the programmable DSPs. [1], [2] Microsoft requires an NPU to deliver at least 40 TOPS for Copilot+ PCs. Both Lunar Lake and Panther Lake meet this threshold, but Panther Lake uses significantly less silicon. GPU tiles Panther Lake is Intel’s first product with Xe3, its latest GPU architecture. It offers two different GPU tiles: a smaller GT1 tile with 4 Xe3 cores on Intel 3 and a larger GT2 tile with 12 Xe3 cores on TSMC N3E. Panther Lake allows us to compare the same GPU architecture across both Intel 3 and TSMC N3E. Wildcat Lake adds a third Xe3 implementation on Intel 18A. A future newsletter will detail Xe3 and its implementation differences across all three process nodes. GT2 scales Xe3 to a different physical layout, with render slices arranged vertically instead of GT1’s horizontal arrangement. Slice placement sets the distances to shared cache banks and the D2D interface. Those wires consume area and add delay, so scaling the number of Xe cores also requires a new balance of cache placement, routing and timing. [1] What’s immediately obvious is that the GT2 tile on TSMC N3E has much smaller Xe cores than GT1. These block areas include logic, caches, and routing. An Xe core on the GT1 tile is ~69% larger than one on Lunar Lake, and ~55% larger than one on GT2. Intel 3 therefore uses substantially more area per Xe core. The block-area gap exceeds the measured logic and SRAM density gaps, bringing routing, timing targets, cell mix, and floorplan allocation into the comparison. The measured vector/matrix engine region is almost unchanged between Lunar Lake and Panther Lake’s GT2 tile. Xe3 retains eight 512-bit vector engines and eight 2048-bit XMX engines per core. Its gains also come from feeding those engines more effectively: more resident threads hide stalls, and variable register allocation lets shaders trade registers per thread against the number of threads kept active. [1] The shared L1/SLM capacity increased by 33% from 192 KiB to 256 KiB, while its area increased only 5%, raising effective density by 27%. L1 retains reused cache lines, while software-managed SLM lets a thread group share data locally. Both reduce traffic to more distant memory. Allocating more SLM per group can also limit how many groups reside on a core at once. [1], [37] The GT1 tile carries 4 MiB of L2 against 16 MiB on the GT2 tile. GT1 divides its L2 cache into four 1 MiB banks, while GT2 uses eight 2 MiB banks. Each bank contains 128 macros, but each N3E macro stores 16 KiB, twice the Intel 3 macro’s 8 KiB capacity. The N3E macro is only 54% larger while holding twice as many bits, giving it 30% higher density: ~23.7 Mbit/mm² versus 18.3 Mbit/mm². Including bank-level circuitry, the gap widens to ~16.9 Mbit/mm² on GT2 versus ~10.4 Mbit/mm² on GT1. GT2 gains density with its macros storing more bits per unit area, and those macros occupy more of each cache bank. Larger macros spread decoder and sense-amplifier overhead across more storage, while a more compact bank layout reduces the share spent on control and routing. The compromise is longer wordlines and bitlines that carry more capacitance. [34] I/O tile Panther Lake uses two I/O tile variants, both fabricated on TSMC N6. The smaller one provides 4 PCIe 5.0 and 8 PCIe 4.0 lanes and serves lower-tier systems as well as those without a discrete GPU, while the larger one adds 8 PCIe 5.0 lanes, bringing the total to 20 lanes, for discrete-GPU connectivity. Panther Lake SKUs with the larger 10- or 12-Xe GPUs use the smaller I/O tile. [38] The smaller I/O tile adds a PCIe 4.0 block and a Thunderbolt block to Lunar Lake’s I/O layout, providing four additional PCIe 4.0 lanes and another Thunderbolt 4 port. Its repeated N6 blocks retain nearly identical areas and layouts. Reusing these proven PHYs and controllers avoids porting and requalifying external interfaces on 18A, where faster digital logic offers less benefit to circuits constrained by the off-chip link. [38] SemiAnalysis’s teardown lab (STEEL) dives deep into the world’s advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. We’re hiring technical experts from system to transistor and everywhere in between. Check out our Careers page. Panther Lake offers scalability and modularity through its disaggregated packaging that partition compute, GPU, and I/O silicon into separate tiles allowing for a suite of tile configurations. This partitioning makes the package part of Intel’s node economics as it determines how much leading-edge wafer area each product consumes, which functions can remain on other processes, and how much configuration freedom Intel can offer from a shared set of tiles. Furthermore, fabricating the compute and GPU tiles separately confines the new 18A process to the compute tile and allows graphics and I/O to use other, more established, and more cost-effective processes. For Panther Lake, the GPU and I/O tiles are assembled alongside the compute tile on a passive silicon base using Foveros-S. Intel’s current technology brief lists a nominal 36 µm pitch for Foveros-S. Through-silicon vias (TSVs) in the base connect the fine wiring above to the larger package connections below. The functional tiles sit side by side on that passive base in a 2.5D configuration. [39] Our cross-section through the compute and GPU tiles shows the package’s wiring hierarchy. Microbumps connect each active tile to the passive silicon base; its fine redistribution layer (RDL) carries the short, dense tile-to-tile links. TSVs carry connections through the base to the package substrate, which fans them out to the much coarser motherboard solder joints. The base supplies interconnect, while computation remains in the active tiles above it. [39] At the compute-tile edge, the higher-magnification inset shows a local microbump spacing of approximately 25.24 µm and a feature width of 12.33 µm. These local spacings are finer than Intel’s nominal Foveros-S value. The X-ray fields further confirm tighter neighboring bumps, consistent across every die-to-die area found on each tile. Additional X-ray analysis is offered after the paywall. Putting the memory controller beside the CPU removes the D2D transfer that CPU memory requests required in Meteor Lake and Arrow Lake. This avoids the extra transmitter, receiver, and link traversal, saving interface energy and latency. Panther Lake’s separate GPU still crosses a D2D link to reach DRAM, so its larger local caches also help contain package traffic. [1], [40] Smaller dies are less likely to contain a random fatal defect, and screening them before assembly prevents one bad tile from consuming a complete package of good silicon. Reuse also spreads design and qualification work across more products. Against those gains, Intel pays for the passive base, D2D circuits, extra bonding and test steps, and losses during assembly. Cost per working product across the portfolio captures the combined effect of wafer yield, reuse, test, and assembly. [29] Wildcat Lake packaging Intel launched Core Series 3, formerly Wildcat Lake, on 16 April 2026 for value mobile and edge systems. Wildcat Lake keeps 18A but removes the passive base and combines more functions on one die to simplify the package. The two products therefore reveal two distinct ways to commercialize the same leading-edge process. [41] Wildcat Lake’s 18A die combines up to two Cougar Cove P-cores, four Darkmont LP E-cores, two Xe3 cores and a smaller NPU. A separate platform-controller die supplies I/O, connected through UCIe, Intel’s first processor implementation of the standard. Consolidating graphics remove a tile boundary and the passive base, reducing assembly complexity for a modest-bandwidth value product. It also ties CPU and graphics scaling to the same die, giving up Panther Lake’s ability to swap in a much larger GPU. [42], [43] In July 2021, Intel CEO Pat Gelsinger set out an ambitious process roadmap aimed at regaining performance leadership by 2025, later described as five nodes in four years. Five years and one CEO later, Intel’s comeback story is not as unambiguously positive as Pat may have hoped. [44], [45] Intel once set the pace for process technology, bringing high-k metal gate technology and FinFETs into volume production years ahead of the rest of the industry. Its 22 nm FinFET process reached consumers with Ivy Bridge in 2012. [46] Intel’s integrated device manufacturing (IDM) model allowed its architects and process engineers to co-optimize products and processes. Starting with Sandy Bridge, Intel dominated x86, while AMD struggled with Bulldozer. That lead faltered at 14 nm and broke at 10 nm. Intel targeted a massive 2.7× density increase, but the node arrived years late and required several revisions before it could support Intel’s full lineup. This delay forced Intel to stretch 14 nm across six generations, while TSMC moved ahead in process technology and AMD recovered in x86. By 2019, Intel was still shipping 14 nm across most of its product stack, with its 10 nm client ramp focused on Ice Lake mobile processors. Meanwhile, TSMC was shipping N7 and N7+, and AMD’s Zen 2 compute chiplets used N7 to raise core counts and improve efficiency. Intel’s process failures were central to its decline, but unsound business decisions furthered their downward slide. Product delays compounded product mistakes, pushing client, server, and FPGA roadmaps off schedule. Several attempts to enter AI (Nervana and Gaudi) and networking (Tofino) also failed to establish lasting businesses. Intel’s recovery has focused on consumer CPUs and advanced packaging. Tiger Lake, Alder Lake, Lunar Lake and now Panther Lake have restored Intel’s consumer roadmap. On the process side, Intel 4 shipped with Meteor Lake, Intel 3 with Granite Rapids and Sierra Forest, and Intel 18A with Panther Lake. Intel has also made advanced packaging part of its foundry offering. However, Intel is still playing catch-up in servers. Several Xeon generations arrived years late and trailed contemporary AMD and Arm server CPUs in performance, efficiency, and core count. The process roadmap is back, but Intel does not hold the same process-technology leadership position it held prior to 10 nm. The introduction of gate-all-around nanosheets and backside power delivery are two of the biggest changes to transistor integration in a decade. Intel took on both changes at once: 18A paired its first RibbonFET with PowerVia in Panther Lake. Panther Lake is a substantial manufacturing milestone. Our cross-sections show how RibbonFET and PowerVia reshape local contacts and wiring, while the floorplans show where architectural consolidation and process choices save area. A sustained competitive lead depends on product performance, cost, yield, and the next implementation. The SemiAnalysis STEEL teardown lab breaks down advanced datacenter and AI hardware. To learn more about our pipeline or to commission a teardown, contact sales@semianalysis.com. WE’RE HIRING: Architecture, floorplan, packaging, manufacturing, and labs experts. Opportunities from system to transistor and everywhere in between. Check out our Careers page.. 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ProTributeBands.com Clarifies Direct Booking Model for Corporate Event Entertainment Planners
SAN RAMON, CA - September 25, 2026 - PRESSADVANTAGE -ProTributeBands.com, the curated booking and lead generation platform for high-end tribute bands, has outlined how its direct-booking structure works for event planners seeking corporate event entertainment. Under the model, bands featured on the platform negotiate terms and close each booking directly with the client, while ProTributeBands follows up to keep the transaction moving smoothly.The structure separates ProTributeBands.com from traditional booking agencies that insert themselves into every contract. Rather than acting as an intermediary that controls the final agreement, the platform connects event planners, performing arts centers, festivals, wedding clients, and private party hosts with pre-screened, national-act-caliber tribute acts, then steps back so the parties can settle details themselves. The platform maintains contact with both sides to ensure momentum is not lost during the process.Founded by David Victor, former guitarist and co-lead vocalist of the multiplatinum band BOSTON, ProTributeBands.com features tribute acts covering artists such as Queen, The Beatles, ABBA, Journey, The Eagles, and Pink Floyd. Selected bands receive optimized profile pages and booking leads generated through the platform."Event planners often assume a booking platform means another layer of negotiation and markup," said David Victor, Founder of ProTributeBands.com. "The approach here is different. The bands negotiate terms and close each booking directly, which keeps the conversation honest and the details accurate. The platform stays involved by following up so nothing stalls between the first inquiry and the signed agreement."The direct-booking method reflects how corporate and private event planning typically operates. Planners frequently need to confirm technical requirements, stage dimensions, scheduling, and performance specifics with the people who will actually be on stage. By allowing those conversations to happen between the client and the band, the model aims to reduce miscommunication that can occur when information passes through a third party.ProTributeBands.com applies a screening process before an act appears on the platform, focusing on production quality, musicianship, and readiness for larger venues. The company ranks tribute bands across categories including Queen, The Beatles, The Eagles, Journey, Pink Floyd, and BOSTON tributes, drawing on performance quality and audience response.The ProTributeBands guide to hiring a tribute band offers additional context for planners weighing these decisions, covering topics such as understanding the audience and event, assessing entertainment value, viewing an act in person before hiring, and reviewing rider and insurance requirements. The guide addresses the practical considerations planners face when selecting an act for a corporate function, festival, or private celebration."A tribute production for a corporate audience has to hold the room the same way a headline act would," Victor said. "The vetting exists so planners can trust that the act they see listed can deliver at that level, and the direct-booking structure lets them confirm every detail with the band before committing."ProTributeBands.com serves clients across the United States and abroad, working with tribute acts that perform at performing arts centers, summer concert series, product launches, corporate parties, private parties, and wedding receptions. The platform also accepts artist submissions from tribute bands seeking consideration for inclusion. The company operates online at protributebands.com.###For more information about ProTributeBands.com, contact the company here:ProTributeBands.comDavid Victor(925) 236-0217hello@protributebands.com11040 Bollinger Canyon Road Suite E-938, San Ramon, CA 94582
Bipartisan group of senators urge Trump to disinvite Putin from G-20
Top senators on the Armed Services and Foreign Relations committees argue the invitation legitimizes the Russian assault on Ukraine.
Can the Left Make America Fun Again?
Hi friends, I’ve got a piece in The New York Times today about how collective joy — participatory, youthful, anti-corporate — can defeat Trumpism and transform our lives. The basic argument is that politics used to be embedded in communal life: dances, sports leagues, union halls. As that infrastructure disappeared — and more of everyday life was atomized and privatized — politics became something broadcast at people rather than something they did together. NYC-DSA and Zohran provide another model, where socials and face-to-face organizing are tied to a fight vs the corporations that fenced off so much of the good life. Rebuilding that kind of collective fun, I argue, could help bring young people back into politics and, by redistributing America’s wealth, make everyday life more joyful. I would super appreciate it if you’d read the piece, share it, or post comments on it. Thank you! p.s. FYI, Opinion writers don’t get any say over their headlines! More Take action to support the fight of licensed deck officers at Alaska Tanker Company and Overseas Shipholding Group to win a first union contract. This is one of the most important, and underreported, unionization campaigns in America: these workers have a huge amount of power over domestic energy distribution and maritime supply chains, and they’re still without a contract two years after having voted overwhelmingly to unionize. Please sign the public petition here, and if you’re an academic you can sign this support letter.
To improve chronic care, this Durham startup tracks life outside the doctor's office
Through anonymized mobile surveys, rXperius helps health orgs account for non-medical factors affecting patient well-being.
Apple Watch Ultra 4 includes a new watch face bezel option
Apple Watch Ultra includes a few more ways to customize your watch face than Series models. These include Ultra-only faces,...
Bills news: How Joe Brady is helping maximize Josh Allen
By calling more passing plays on early downs, Joe Brady is unleashing Josh Allen’s full potential for a potent offense.
Google could bring the Pixel 11's customized My Pixel colors to older Pixels
Looking at the latest My Pixel app, we have found evidence suggesting Google may expand the customized app icon colors to older Pixels.
CONTROL Resonant PC Performance Analysis & Tuning Guide – How To Get The Best Experience On PC
CONTROL Resonant offers optimized graphics settings improving performance by 91% without ray tracing and 77% with it on RTX 4060, showcasing Remedy's Northlight Engine.
Censys Shifts To Channel-Only For New Business, Aims To Expand Internet Intelligence With Partners
Censys unveiled an expanded channel program Tuesday that includes a major shift in its sales strategy in the direction of partners, with the aim of accelerating growth for its Internet intelligence platform through the channel, Censys CRO Sarah Ashburn tells CRN.
“Nurturing tomorrow’s Einsteins in Dalseong-gun”: DGIST Science Creativity School opens admissions for the 2027 academic year
- Advanced education in four fields—mathematics, physics, chemistry, and life science—with full tuition support for sixth-grade elementary and first-year middle school students in Dalseong-gun - “Taught Directly by DGIST Faculty”: Customized advanced education for gifted students in the region
Scientists want these 5 'maxxing' trends dead
The “-maxxing” trend promises that extreme optimization of your sleep, appearances, fitness, diet, or wellness routine will somehow unlock a better version of you. But when health advice becomes a competition to optimize every single thing, real science often gets lost. Our scientists break down the -maxxing trends they really want you to stop—and what the evidence actually says.
The Big Holes in Wearable Heart Rate Variability And Readiness Scores
On September 9th, Apple announced it was revamping its Apple Watch Health Sensing System, rolling out a Readiness score (0 to 10), and increasing the frequency of heart rate variability (HRV) outputs 24-fold. This can be viewed as upping its competition with various other consumer wearable sensors. These “readiness scores” as a composite of multiple metrics, with heart rate variability (HRV) being front and center for most. The majority of Americans are now using wearable sensors, which equates to well over 100 million adults. HRV and Readiness scores are increasingly being marketed as a measurement of autonomic nervous system health, a digital marker for future disease, a clock for biological age, and a holistic metric to promote healthspan and even longevity. (Apple also introduced a new longevity tab and “Health Age”.) None of this has been proven. In this edition of Ground Truths I am going to review what we know about heart rate variability and readiness scores. Heart Rate Variability HRV is the variation in normal heart cycle timing. The variability of the heart rate, the barely perceptible millisecond changes in time between consecutive heart beats (see R-R intervals in the Figure below, left panel), is due to interplay between the sympathetic and parasympathetic (vagal nerve) inputs. Distinct from heart rate, individuals with the same heart rate can have very different HRVs. It is a rough reflection of the autonomic nervous system (ANS) activity, inadequate to say whether a person’s ANS function is abnormal. For more than three decades, heart rate variability (HRV) has been measured and several studies have found an association of low HRV and clinical outcomes, particularly a link with higher all-cause and cardiovascular mortality. There have also been less well established links of low HRV to risk of early cognitive impairment, dementia, mental illness, Type 2 diabetes and substance abuse. An important reminder is that HRV is a surrogate marker without any established cause-and-effect relationship. If you increase your HRV, that doesn’t mean it will improve health outcomes. In fact, there is no hard evidence for that. All that work linking to health outcomes was done with electrocardiogram (ECG) derived HRV. Now, in the era of consumer wearables, this is getting assessed differently, by optical pulse (yes, the lights you see) plethysmography (PPG) or what is called pulse rate variability (PRV). They are not the same, as shown below (right panel) and only concordant when the delay between the ECG and pulse is kept constant, which basically means at rest. I should mention there’s also what I will call MPV, a mattress mechanical movement sensor, a derived heart rate variability, that companies like Eight Sleep use, even further away from directly measuring HRV. HRV has not one uniform measurement but many different types of quantification, such as RMSSD, the magnitude of difference between successive R-R intervals of normal sinus beats (N-N) or SDNN, the standard deviation of NN intervals, both in milliseconds. SDNN is one of the so-called frequency domain HRVs (others are LF, HF, LF/HF). Different wearable sensors use different metics; Apple has relied on SDNN and nearly all of the others use RMSSD, which is generally considered the more accurate metric. There’s also the different length of time measured, such as for a matter of minutes, all day, or an overnight’s sleep. Short measurements are especially problematic since they don’t capture enough of respiratory modulation and other factors that influence HRV. Share Ground Truths How well does HRV correlate with PRV? There are very limited studies, especially independently done. One that is commonly cited was conducted by Air Force researchers in only 13 healthy adults assessing Oura ring 3 and 4, Whoop 4.0, and Garmin Fenix 6 and showed a correlation coefficient of 0.88 to 0.97 and a mean absolute percentage error from 6 to 10%. The correlation is not a perfect 1.0, but there’s at least a fairly high level of correlation. HRV is supposed to increase during the night due to takeover of the parasympathetic nervous system, and higher during deep sleep. A recent example of my 1 week, all day “HRV,” and one during sleep is shown below. As you can see, the N of 1 data are inconsistent for the same days from different sensors (Oura, AppleWatch, Fitbit Air, and Eight Sleep) by patterns, absolute numbers, and comparison with prior days and weeks. The largest study in over 8 million Fitbit users (the old version, not Google Fitbit Air, introduced in May 2026) gives you a sense of the effect of age, sex, and the 2 different main HRV (here PRV) metrics, with RMSSD on the left and SDRR (=SDNN) on the right below. That study, from data collected in 2018, is a major outlier, since all the more recent ones are tiny with respect to sample size. Many of the companies have not had independent evaluation of their HRV, such as Eight Sleep, but have published a low standard error on their website. There are some other published studies on the correlation between HRV and PRV, but they are all small and only in healthy adults. A scoping review emphasized the lack of study in underrepresented individuals, including the aged, people of color (which affects the PPG signal), and individuals who are underweight or obese. Add the typical adult age 60 plus with one or more chronic diseases. For example, one study in over 900 adults found poor correlation of HRV and PRV, non-uniformly underestimated across many chronic diseases (cardiovascular, endocrine, neurological, respiratory, and others), concluding PRV is “an invalid surrogate for HRV.” A recent systematic review of 43 studies comparing HRV and PRV found reasonable pooled absolute standardized error (HRV as gold standard) but only 10 of the studies provided quantitative synthesis in ideal conditions. Their main conclusion was similarly cautious: “PPG-derived HRV [PRV] should not be regarded as universally interchangeable with ECG-derived HRV across all devices, populations, and recording contexts.” Factors Affecting HRV and PRV That gets me to the long list of factors that affect HRV (and PRV) besides the device, the type of measurement (RMSSD, SDNN or others), the person’s signal, the sensor site, the duration of data capture, if weighting by sleep stage is used, how artifact is processed and corrected. And this list is not complete!: Oura puts out data from their community of users (who input data) on what affects their overnight HRV. The factors currently provided are: no alcohol (increase 8%), melatonin (increase 2%, float tank (increase 2%), wine (decrease 4%), and party (decrease 14%) in overnight HRV. Must be some big parties! Subscribe What is a PRV measurement good for? It has been falsely characterized as an index of “autonomic balance” and a specific indicator of stress. A 2018 review of the studies available for HRV and its relationship to stress, not using any of the current wearables, found that stress can lower HRV. But so can many other factors. The non-specificity of the signal, indexed to the table above, is striking. Evidence from a UK Biobank study of over 46,000 participants with actual HRV looked at genetically predicted HRV, a genetic risk score, that failed to show the expected HRV-mortality link, indicating that _HRV is likely not causa_l, but rather a reflection of person’s physiologic state. A review of consumer wearable HRV data from 5 longitudinal studies showed that nighttime PRV was not associated with perceived stress, and surprisingly higher HRV, in the largest cohort (N=717 participants), was correlated with higher stress. An Oura ring cohort of 525 first-year college students found a link between overnight PRV and perceived stress, but that was also seen with resting heart rate, sleep, and respiratory rate. Several very small studies have examined the relationship of HRV and athletic injuries or guiding training with mixed, and predominantly negative results. HRV biofeedback training with paced breathing had no significant effect on reducing stress or raising HRV, as demonstrated with sham controlled trials. When HRV for multiple days showed a decline in conjunction with body temperature, the Oura ring published data for prediction of Covid. The WHOOP company sponsored an observational study, published in 2026, of 30,000 users for 72 weeks, without a control group, that reported reduced alcohol intake (5.8 % points) by self-report. That doesn’t tell us much, and particularly about the merits of HRV for behavioral change. If you use the same device and conditions as longitudinal trends for multiple (at least 2-3) weeks that may be the one way to get something useful from the measurements. Data for overnight sleep with minimal motion and using RMSSD is the best proxy for real HRV. The reason to look at trends rather than any given night is that it more likely represents something, even though you won’t know with certainty what the “it” is. Keep in mind there are no data, no peer-reviewed evidence, to show that HRV fluctuation in-person has any correlation with health outcomes. Share Readiness Scores These are proprietary scores that integrate different metrics for each of the wearables: no algorithms have been disclosed. They are unvalidated against health outcomes. In a review of 14 composite health scores of readiness and recovery, HRV contributed 86% to the scores, followed by reading heart rate (79%), physical activity and sleep duration (both at 71%). That review noted the substantial variability in measurement protools and lack of standardization. Sleep staging is notoriously inconsistent and inaccurate by these sensors, which adds further to the HRV uncertainties for what the scores, which use sleep stage data, mean. Only resting heart rate has been shown consistently across devices to be extremely accurate. I’ve made a Table to summarize what we know about which metrics are included, the scores, any peer-reviewed studies that compared the readiness score with health outcomes, and the corresponding (if any, NA-not available) citation. You will note that some companies do not use the term “readiness," such as WHOOP for recovery, and Garmin, which has 2 different scores, one of which is Body Battery. Eight Sleep uses the term “Fitness Score.” They all include HRV; Apple includes a new metric they call “Recovery HRV” which among other components uses 7-days of sleep, but it is unclear what this means or how it is differentiated from other scores (there are clearly no data for outcomes). We have no knowledge of how the different components are weighted or whether any of these scores are better than resting heart rate, HRV alone, physical activity, or any other single metric. Since none of these are standardized, they are not interchangeable, so if you get a 90 for Oura that has no relationship to a 90 on a Google Fitbit Air. Notably, the company can update its algorithm for readiness score at any point without notification to device users. Without any useful evidence of actionability for these scores or established relationship with health outcomes, it is hard to make a case for their value. At the Apple recent announcement they showed their Readiness score (0-10) on the watch (Figure below) but there are no published data on this score, not even on their website. It’s available only on their new Watch Series 12 or Ultra 4 [of course, ;-)]. That exemplifies the problems with these scores, lack of data and evidence for being meaningful to promote health. Perhaps the best study (which isn’t saying much) is the WHOOP Recovery for golfer performance, because it did correlate with an objective outcome, even though there was no control group and the authors were all from the company. Among the 389 pro golfers, an absolute 10-per cent point increase in Recovery score was associated with about 0.5 fewer strokes per round. But that’s hardly a health outcome! WHOOP is also conducting a study in over 2,700 runners to see if their recovery score will be linked to less injuries and improved performance, but that is not yet published and has no control group or randomization. Putting This in Context For two decades I’ve been enthusiastic about the potential for digital health and particularly wearable biosensors. Over the years, we’ve seen some great progress for their ability to promote physical activity and accurately detect atrial fibrillation (the first FDA cleared deep learning AI for consumers). That work was the subject of rigorous research. But there are holes in the data and evidence for other metrics. One notable one is the “VO2 max” story that I wrote about earlier this year. At that time many subscribers asked me to cover heart rate variability, which I finally got to here. When I dived into the research and publication for HRV and readiness scores, I expected to find at least some that were of high quality and demonstrated their utility by linkage to health outcomes. To my surprise, I found none. The wearable sensor measurements for HRV (PRV) are, for the most part, accurate, but that validation work has only been done in small studies of healthy adults and does not take into account the long list of factors, from the device, software side, and the user side, that affect HRV measurements. Moreover, this metric chiefly relies on optical sensing and, as we have learned for heart rate PPG sensing, may be less accurate in people of color. Keep in mind that all of the health outcome association evidence comes from ECG-derived HRV; none are from wearable sensor data. I will repeat the key point: there's no peer-reviewed evidence to show that in-person HRV fluctuation—or efforts to raise your HRV— has any correlation with health outcomes. For those of you who look at your HRV on awakening, or even 2+ week trends of it being low, I hope this context helps to relieve any anxiety. Yes, low HRV (not PRV) has been shown to increase risk of some diseases as summarized above. But efforts to raise your HRV—a surrogate metric— has not been established for improving any health outcomes. HRV does not have any evidence of causality (the genetic evidence actually goes against this possibility). In this summary, I have not included data for other wearable sensors such as Polar, Samsung, Withings, Suunto, Amazfit, Coros, Ultrahuman, or additional mattress sensors. These are beyond my first-hand experience, and as far as I know from my in-depth review none have any peer-reviewed published data that differ from the 6 sensors I’ve reviewed here. From the points I’ve gone over above, we’re not ready for readiness scores. Besides being proprietary, they are predominantly based on metrics that have their own issues. It’s compounding the problem, like building a house without a solid foundation that has never undergone a rigorous inspection, and then selling it. Like I mentioned for PRV, you can look at trends over weeks rather than any single day, to get a handle, but even that may not be helpful. There’s simply no evidence that these scores meaningfully relate to health outcomes. I’d emphasize they might, but that requires doing prospective or randomized studies to prove it. None exist. There’s great promise for HRV/PRV utility_. For example**,**_ Prof Maiken Nedergaard, who discovered the brain glymphatics that are essential in eliminating metabolic waste products from the brain during sleep, has posited that HRV could be a non-invasive marker for neuromodulator oscillations, brain-body regulatory circuits, and brain clearance. That would be extremely useful, but like everything else on HRV and readiness scores it requires solid research and validation. The lay media isn’t helping much to get the story straight. Earlier this year The Economist published a piece entitled “The most useful indicator of your overall health” which ordained HRV as an “accumulated stress score.” That’s akin to the false assertion about VO2max: “V02 max is the singular most powerful marker for longevity.” As I’ve summarized here, that is not established. The fact is that so many things can lower HRV, including physical exercise (especially an intense workout), reduced sleep quality, stress, the list above, no less the device, signal, and software. Whatever fluctuations observed have not been correlated with any health outcome. Sadly, “datamaxxers” are widely using HRV and readiness scores that have never been validated to mean anything. We already know that for some people using the sensors for sleep metrics, it can induce “orthosomnia,” an obsession to get high sleep quality, with associated high levels of anxiety. In an experiment done by a company to promote sleep quality for its employees, “For those employees who did use the trackers, many reported feeling perfectly rested until their tracker told them they had had a terrible night. Others were told that they had slept like a baby when they had actually been lying awake worrying about the quality of their sleep. “ The same problem can result from preoccupation with HRV or readiness scores, with anxiety that would lead to further reduction in both. It you are using a wearable like >100 million American adults, it’s OK to look at these data, but contextualized with the major caveats reviewed here. If you are one to require evidence that HRV or readiness scores are linked to health outcomes, you may not even want to look. The companies make it hard to turn them off! Let me end with the companies that make and sell wearables. Apple’s doubling down on HRV (24-fold more reporting and heart rate very 5 seconds) and introduction of a Readiness score tells us that consumers have bought into these metrics and they are joining the club. However, all of this is occurring with a backdrop of tens millions of users, claims about the data that are not backed up by adequate evidence, marketing way out in front of whatever limited data exists, and not being transparent about their readiness score algorithms. The companies can well afford to do the research that is needed to connect these metrics with health outcomes show, once and for all, that increasing HRV or using readiness scores promotes our health. If they believed and invested in the products they are selling, we’d not be in this position of not knowing. That’s essentially where we are with HRV and readiness scores. Perhaps someday this will change and we’ll have good reason to embrace them. NB: I wrote this post. No AI. I have no conflicts of interest with any of its content. Loading... Ground Truths has 215,000 subscribers from every US state and 214 countries. There are over 300,000 followers of Ground Truths so more than 90,000 folks who can easily convert to be free subscribers. Your subscription to these free essays and podcasts makes my work in putting them together worthwhile. If you’re not a subscriber, please join! If you found this interesting PLEASE share it! Share Ground Truths The proceeds from all voluntary paid subscriptions go to support our summer internship program. It enabled us to accept and support a record number of 62 summer interns that joined us in 2026! These are high school, college and medical students selected from thousands of applicants. We couldn’t do this expanded program without the funds coming in through Ground Truths. Thank you!
Science Vs on the 49ers Substation: Anatomy of a Hatchet Job
In August, Pablo Torre Finds Out and Science Vs released an episode about my theory that electromagnetic fields from the electrical substation beside the 49ers facility may be contributing to the team’s run of soft-tissue injuries. As the originator of the theory, I was also a subject of the episode. I sat was interviewed by Wendy Zukerman and Rose Rimler of Sciene Vs. I sent them research, connected them with scientists, and spent hours digging through the City of Santa Clara’s and Silicon Valley Power’s records to help clarify critical details. Both Wendy and Rose came off as affable and professional, showing curiosity during the interviews, with Wendy going out of her way to question the “conspiracy theory” framing itself. Then they titled the episode We Solve the 49ers Viral Conspiracy Theory. I was familiar enough with their catalog that I never expected them to agree with my theory, but I did expect them to give it a fair hearing and to deliver their findings honestly. On both counts they came up short. They were not directly dishonest in anything they said, but rather in what they left out, in how what remained was cut, and in the picture painted by those two things in combination. They asked me to recorded the interview on my phone for better audio quality, and I held on to my copy for reference later. That turned out to be a fortuitous decision. Here is the raw audio of my first interview, unedited*. Only my side was recorded, so their questions aren’t on it, but you can generally infer them from the answers, and every claim I make below about what I said can be checked against my statements in this clip. (Note: Wendy had connection trouble at the beginning of the interview and was cutting in and out, which accounts for the false starts.) 0:00 -1:19:13 Audio playback is not supported on your browser. Please upgrade. Science Vs is a fun show. It is pitched at roughly a high-school understanding of science, for an audience that is skeptical, Snopes-oriented, and worried about misinformation. Take a claim circulating online, interview a supporter of the claim, interview consensus scientists, and then tell people which side of the line it lands on. I have listened to their episodes on raw milk, seed oils, 5G and other contested issues in the wellness space. I have problems with all of them, but each at least made an honest attempt to represent the actual range of scientific opinion by talking to credentialed scientists with differing perspectives. Dissenting researchers were heard from, answered, and often given a chance to respond. This episode did not do that. This article is not a relitigation of the science. I have written extensively about that already. This post is for the record. It is simply an accounting of what was wrong with their episode. Contents Is there a power plant next to the 49ers practice facility? — the clearest single example of getting something objectively wrong For the record — a high-level overview of all of the problems with their investigation Draw your own conclusions — why they had to make this episode at all What they left out about childhood leukemia — the exposure threshold, and playing games with statistics to minimize sick children What they left out about the mechanism — the body of literature they refused to cover, and evidence for the mechanism used against it The scientists Science Vs interviewed and did not air — four credential scientists who support myhe theory, recorded and cut, or not even called How they misrepresented me and my case — an answer severed from its question, and three telling edits How you would actually study the injuries — it doesn’t actually matter which team is the most injured, overall The theory: magnetic fields, oxidative stress, and collagen Since the episode never states my theory, here it is below. Those who are familiar with my work can skip this section. Electrical equipment produces magnetic fields, and those fields induce faint electrical currents in anything that passes through them, including people. My argument goes further than induced current. Mitochondria — the structures that generate a cell’s energy — run on continuous flows of electrons and protons, and those flows carry faint electromagnetic fields of their own. Maxwell’s principle of superposition shows that when two fields share the same space, they add together. An external field does not need to be strong to alter an internal field, it only needs to be present. The electron transport chain inside the mitochondria leaks a small fraction of its electrons by design, and those become reactive oxygen species — free radicals, which healthy cells use as signals. External magnetic fields cause the rate of leakage to change, increasing free radicals. When free radicals accumulate faster than the cell’s antioxidant systems can clear them, the result is oxidative stress. Oxidative stress is a recognized driver of chronic illness, including cardiovascular disease, neurodegeneration, diabetes and cancer, and it is in every medical school curriculum. One of its ordinary effects in connective tissue is that it switches on matrix metalloproteinases — MMPs, the enzymes that break collagen apart — while suppressing new collagen synthesis. Tendons are made of collagen. An athlete loading his soft tissue heavily six days a week is already creating oxidative stress in the tendons, so the addition of magnetic field exposure compounds the damage and inhibits repair, making him more susceptible to injury when enormous force lands on a tendon in a fraction of a second. That is the theory. We know that EMF causes oxidative stress, and we know that oxidative stress degrades collagen. The only thing missing is a study showing that direct connection. I have never claimed certainty that the substation is contributing to the elevated injury rate. I do believe it is likely, and I believe it warrants caution, and that a revenue machine like a major NFL team can easily afford to remove the exposure out of precaution. Is there a power plant next to the 49ers practice facility? Here is the clearest single instance of the problem with this episode. It requires no knowledge of electromagnetic fields at all. This story first came to me through Jon Feliciano, a former 49er, in an interview on Willard & Dibs on 95.7 The Game. Asked about why the 49ers are always injured, he said players used to joke that it was the power plant behind the practice fields. Wendy Zukerman corrects him on air. “It’s important to say that it’s not a power plant near the 49ers site.” Torre then asks her to explain the difference between a substation and a power plant. Her answer: a power plant generates electricity and transmits it to a substation, which converts the voltage into something your house can use and sends it on to your home or your business. There are two problems with that. The first is that there is a power plant on that site. The Gianera Generating Station is a natural-gas-fired peaker plant owned by Silicon Valley Power, and it has been there since 1986. I have published aerial photographs of the location from 1987 in which the gas plant is the only thing standing, before the practice facility was even there. I even mentioned the gas plant in my first interview. (Feliciano has since gone on record about this issue, and it is clear he had the substation in mind rather than the gas plant.) The second is that her definition describes a distribution substation, and the facility beside the 49ers is not that. It is the Northern Receiving Station, which takes in bulk power from outside the city’s grid and delivers it to distribution substations. Silicon Valley Power’s own map distinguishes receiving stations from substations, and Rose Rimler even reads the label out loud in the episode when she walks through that map on air. A few minutes before the map segment, Zukerman tells Torre: “like I said, we fact check everything.” Well, maybe not everything. I made a mistake On the morning of July 6th, at 10:20, I sent Rose and Wendy two studies. During the interview I had been asked which human studies show oxidative stress from electromagnetic fields, and I had not been able to name one on the spot. Rose emailed asking for the studies, I quickly searched for a couple, and I wrote that I thought these were the most relevant from that search. Unfortunately, I was busy and did not read either one closely at first. I picked them because they were topically relevant — one on substation workers, one on power plant workers. Neither were great studies, and their problems go past the ones raised in the episode. That was careless on my part. There is context that did not make the episode, though. Before that email I had been on a Zoom call with Rose talking about EMF and oxidative stress, and I pointed her to Dr. Henry Lai at the University of Washington, who has spent years aggregating the literature on this question. His tallies show that roughly 90% of studies since the late 1990s find oxidative effects from electromagnetic field exposure — hundreds of studies, systematically counted. Rose told me she was already aware of his work. So when she asked for studies, I understood her to have the aggregate view already and that she would report anything within that context. Not reading those two carefully was still a mistake, but the larger mistake was assuming the episode would be based on a thorough review of the actual body of literature, rather than on whatever I happened to send that morning. The second email At 1:49 that same afternoon — three hours and twenty-nine minutes after the first — I sent them a second email that I had been preparing for a while. It was a structured document in six numbered sections, written in response to a request they had made two weeks earlier, laying out my entire argument with citations attached to every link in the chain. The episode aired on August 13th, five weeks later, and not a single item from the second email is in it. Here is how it opens: The full email is included at the bottom of this post in Appendix B. Nearly 1,500 words in total. It contains two named mechanisms with the physics behind them. Occupational studies in humans. The literature on oxidative stress and collagen. A section addressing the strongest counter-evidence against my own theory, which I raised myself. And a closing section stating plainly what the theory cannot yet show. My entire argument, in writing, with detailed citations for every claim, provided to them five weeks before broadcast, and none of it made it into the episode. That is the single largest omission, but it is not an isolated one. The whole episode is riddled with similar problems, and the conclusion they came to is not merely a difference of opinion about the scientific evidence. Through omission and through strategic editing, Science Vs misinformed its audience — about what the evidence shows, about what I argued, and about who they spoke to. That is a notable outcome for a show whose stated purpose is correcting misinformation. For the record I am not going to tell you that Science Vs set out to discredit me, or that they had come to their conclusion before they reported the story, or that they used misleading editing to make me look like a man retreating from his own theory. I cannot know what was in anyone’s head, and I am not going to pretend otherwise, either. What I can tell you is what is on the record. They asked me for evidence and aired the weakest thing I sent. They interviewed three scientists who supported my theory and aired none of them. They discussed childhood leukemia without ever saying the exposure level at which it appears. And they took an answer I gave weeks before Ken Karipidis, the one EMF scientist who was put on air, was interviewed, and placed it directly after his critique, where it comes off as a major concession. A friend of mine who has worked as a journalist for thirty years read that last one and called it sleazy. I agree with her. Those are just the four issues that are impossible to defend as pure editorial decision, but they are not the only issues. The most glaring issues stem from what they left out: The exposure level at which the childhood leukemia association actually appears — three to four milligauss, a number the episode never states despite it being much lower than what I measured. The mechanism itself: The episode gets as far as “oxidative stress could weaken collagen,” which leaves it sounding like speculation, rather than a known pathway. The second email, and all the studies in it. Dr. Paul Héroux at McGill, whose work my proposed mechanism rests on, whose contact details I supplied, and who was never called. Dr. Beatrice Golomb at UC San Diego, who runs a research group on oxidative stress and mitochondrial function and has specific expdertice in collagen, interviewed and not aired. Dr. David Carpenter at Albany, the most prominent academic voice on the harm from magnetic field exposure, interviewed and not aired. Dr. Joel Moskowitz at Berkeley, interviewed and not even credited. The specific, testable condition I put in writing that would make me abandon the theory. My own unprompted statement of the theory’s evidentiary gap. My caveats about my own measurements. My ranking of EMF as one factor among several rather than the only one. The new equipment installed at those facilities between 2010 and 2014, and the sharp rise in system load from 2013 onward. But that is not all. What they kept, they selectively edited to serve a narrative that was not served by the raw transcripts of the interviews. A description of thousands of commercial routers in a workplace, reduced to the Wi-Fi in your house. My own acknowledgment, multiple times, that "I'm not a scientist" clipped in an episode that spends considerable energy pointing out that I am not a scientist. And a qualification I volunteered about my own measurements, cut from my answer and delivered later by their EMF expert as a correction. Together their edit produce a portrait of a wellness guy with Wi-Fi phobia and two bad studies, backing away from his theory the moment a “real” scientist looked at it. A practice facility where nothing changed because no new substation was built. Injuries written off as random because the 49ers were not quite the single most injured team in the league over the period in question. That portrait is false even though almost no individual statement made in the episode is. Draw your own conclusions At the top of the episode, Pablo Torre says his show had been flooded with requests to investigate the substation — that it was the thing they were asked to look into over and over again. Neither show went hunting for this story. It arrived from their own audience, in volume, and it could not be waved off. A thread I posted on X reached twenty-two million people. A guy with a gaussmeter and a brand-new Substack obligated a Pultizer prize winning program to spend an hour on a question about player health, that is considered fringe enough that most media operations won’t touch it. Pablo Torre Finds Out could not ignore it. So Science Vs came in and ran a “debunking” operation instead of an investigation. Everything below is what had to be left on the cutting room floor to deliver the “debunking”. They could not ignore it. So they tried debunked it instead. The demand was strong enough to force an episode, and since the episodes release the 49ers have sustained more injuries, including season ending ones, and interest has only grown. Demand from fans and playets is strong enough to force a better investigation from someone else. An omission is not a lie until you find out what was omitted. What follows is the detailed record so you can see the full picture. Draw your own conclusions. I have drawn mine. I am going to keep publishing. A note about Pablo Torre Finds Out After the episode aired I posted publicly, calling out Pablo Torre Finds Out for concerns I had about the integrity of their investigation, and about an interview directly with Pablo Torre which had been offered but never happened. I have since spoken with a producer at PTFO. The offer had rested on a misunderstanding about where things stood between us, and it fell away as the Science Vs part of the production widened past the science. He apologized for the miscommunication and I accepted. The producer also confirmed to me that they did essentially hand off the entire investigation to Science Vs for narrative purposes — so Pablo would be genuinely curious or potentially surprised by their findings — while still taking responsibility for what went out under their name. I appreciated the candor and the accountability, and I am comfortable with where we left things. So this post is not about PTFO. My disagreement is with Science Vs. What they left out about childhood leukemia Childhood leukemia appears at three milligauss. They gave no number at all. 1. They built an EMF ruler, then discussed childhood cancer without it. The sequence on air went like this: First I measured almost 9 mG, then I measured up to 50 milligauss. Torre reacts with concern — “that sounds high.” Cut to Karipidis: the public limit is 2,000 milligauss. Torre reacts again — “What happens at 2,000?” Karipidis explains that nothing happens at 2,000, that safety factors are built in. Then: at more than 50,000 milligauss you get flickers of light in the retina, and higher still, nerve stimulation. The listener now has a ruler (their ruler) to measure these numbers with. Fifty is nothing by their ruler. Then the episode turns to childhood leukemia and states, accurately, that there is a real association — but tellingly, they never give the exposure level at which that association appears. Childhood leukemia appears at three milligauss. They conveniently left that out. The pooled analyses that produced the World Health Organization’s carcinogen classification found roughly a doubling of childhood leukemia risk above three to four milligauss. That is the number that belongs in that segment, and it is more than ten times below the reading that had just been dismissed as trivial. I gave them that number myself, on tape, in the interview. Describing my own threshold, I said my comfort level for long-term chronic exposure is three to four milligauss, but preferably one. 2. Six children in thirteen million. The episode reports that these fields might explain one to four percent of childhood leukemias, then reframes it as a German estimate of perhaps six cases among thirteen million children. Torre, to his credit, is uncomfortable. What never gets explained is why that number is small. Almost no children lives above three milligauss in Europe. Fewer than two children in a hundred, in the Italian data. So even if the risk to those children doubles, the number of additional cases across an entire country stays small — not because the hazard is small, but because hardly anyone is exposed to it. Count the whole population and the few who are exposed disappear. And the reason hardly anyone is exposed is that siting rules keep housing away from transmission lines. In Europe, at least. The Dutch government has a standing precautionary policy against building new homes in any zone where the annual average magnetic field exceeds 4 milligauss — the same number the episode never mentioned. Denmark and Norway treat 4 milligauss as the level that triggers a look at mitigation. That is five hundred times below the ICNIRP figure quoted on air. The United States has no federal equivalent. That is evidence of infrastructure siting policy working. It is not evidence that there is no hazard. It is evidence that we already act as though there is one. If you listen to the raw audio you will hear that my proposed solution is EMF exposure is to build better infrastructure. What they left out about the mechanism 3. They accused me of cherry-picking, and then cherry-picked themselves. On air, Zukerman tells Torre that people who worry about electromagnetic fields dismiss the studies showing null results and collect the ones showing harm, and that this is why you have to be careful not to cherry-pick. They had two papers I had rattled off in a hurry, and a second email containing a carefully chosen set. They ran the two weakest, graded them on air, and presented the result as the state of the evidence for not only my theory, but the whole question of oxidative stress from magnetic fields. That is cherry-picking from my emails. The bigger picture is what they did with the literature as a whole. Zukerman acknowledges it exists, dismisses it, and disposes of it in a single stroke. You can go online right now, she tells Torre, and find scores of studies showing these fields increase oxidative stress. The issue, she says, is that they are not studies in people. Many of them are in people. The occupational studies in my second email are in people. That email had been in her inbox for five weeks. She waved off the literature on a factual claim that the documents in her possession contradict. (I have written separately about the evidentiary standard at work here). The effect was that they essentially baited me: ask the subject to supply the evidence, take the weakest thing he sends, and let that stand as a proxy for the whole argument. Wendy has been doing this show for ten years and clearly knows how to extract what she needs for her desired narrative. 4. They presented the collagen-improvement research as a gotcha, but I had already addressed it. The episode treats the existence of studies showing that EMF can improve collagen as a surprise that undercuts me, but I had pre-emptively addressed that five weeks earlier in the email they ignored. Those studies use measured, high-intensity pulsed dosing. The mechanism by which they work is oxidative signalling. The cell reads a controlled rise in reactive oxygen species as a warning, upregulates its antioxidant defenses, mounts a repair response, and the therapy stops before the system is overwhelmed. The key point is that it induces an oxidative response, which means those studies are actually evidence for my proposed mechanism, not against it. A field that produces a therapeutic effect cannot be biologically inert (which is the implication when they say “Nothing happens at 2,000 milligauss). Chronic ambient exposure is the same pathway with no off switch, and it is most consequential during the evening and while sleeping, when the body is in repair mode and the exposure does not stop. Section 5 of my email is titled What about the study showing improved collagen synthesis. I raised the counter-evidence myself, explained why I did not think it refuted the theory, and wrote that I was disappointed the question had not come up in the interview. That is worth holding against the cherry-picking charge in the item above: the studies they presented as inconvenient for me were studies I had gone out of my way to put in front of them. 5. Section 1 of my email stated a critical argument that was never put to the expert directly responsible for it. My email says the exposure limits exist to prevent acute effects and do not address chronic exposure at all, and that my dispute is with the entire framework. Zukerman gestures at this once. After Karipidis gives the 2,000 milligauss figure, she tells Torre that I would object because those levels do not capture “more subtle effects.” That is not my argument, and “subtle” is doing a lot of work here. My argument is that the limits are built to prevent acute effects — nerves firing, muscles twitching, etc — and were not designed to address chronic exposure at all. In fact, ICNIRP’s own documents state as much themselves. Mine is a structural objection to what the standard measures, reduced as a concern about subtlety, it becomes a matter of degree, rather than a categorical difference. They interviewed Ken Karipidis, vice chair of ICNIRP — the body that writes those limits. He was asked what the limit is, but he was never asked how it applies to chronic exposure. The scientists Science Vs interviewed and did not air 6. They interviewed four officials of the standards body. The episode credits roughly a dozen researchers. Four of them are associated with ICNIRP. Ken Karipidis is the vice chair. Rodney Croft chaired ICNIRP from 2020 to 2024 and led the development of its current guidelines. Dan Baaken is ICNIRP’s scientific secretary. Frank de Vocht sits on the Main Commission. One of them speaks in the episode. Their institution’s position is more than adequately represented — the 2,000 milligauss figure, the safety factors, the assurance that nothing happens below the line. 7. The four who were left out. Dr. Beatrice Golomb is Professor of Medicine at UC San Diego — a physics undergraduate degree, a PhD in biology, an MD. She directs a research group whose stated focus is the relationship between oxidative stress, mitochondrial function and health. That is the mechanism the episode spent its first half dismissing. Her published work includes the fluoroquinolone case series behind the FDA’s black box warning on an antibiotic class that ruptures tendons, where the accepted mechanism is oxidative stress and mitochondrial toxicity — the back half of my chain, already on a drug label. She is in the credits. She is not in the episode. She has told me she finds my theory biologically plausible, and that she has a recording of her interview. Dr. David Carpenter directed the Institute for Health and the Environment at the University at Albany for decades and is the most prominent academic voice arguing these fields cause harm. Childhood leukemia is the reason these fields carry a WHO classification at all, and Carpenter is the person you call if you want that case made by someone who has spent a career on it. He is in the credits. He is not in the episode. He has told me that when he was interviewed they could not have been less interested in what he had to say. Dr. Joel Moskowitz directs the Center for Family and Community Health at UC Berkeley’s School of Public Health. He told me directly that they interviewed him and that he thought it went well. He does not appear in the episode, and unlike Golomb and Carpenter, he does not even appear in the credits. Dr. Paul Héroux at McGill is the researcher whose work provides the foundation for the oxidative stress mechanism my theory rests on. I gave Rose his email address and phone number. He was never interviewed. They never even called him. 8. “He’s not a scientist.” The episode leans hard on the fact that I am not a credentialed scientist. Zukerman says it. Torre repeats it. “At all.” Having built a segment on that, they then left out the physicist-biologist-physician, the professor of public health, the director of a university environmental health institute, and the McGill researcher whose work the primary mechanism comes from. They spent the episode telling their audience I am not a scientist, and then kept four actual scientists who support the theory off because their argument does not survive otherwise. How they misrepresented me and my case 9. They played my words as a response to an interview I had never heard. Near the end of the hour, Zukerman says she went to me and told me the evidence was lacking. Then she plays me saying I am not wedded to it being an EMF, that I have staked my reputation on it needing more study, and that I am not certain of anything. That segment was placed immediately after Karipidis had finished taking the cherry-picked papers apart. It plays as a man folding under expert scrutiny. Commenters have used it against me since, but it is incorrect. Here is the sequence as it happened. I was interviewed. Karipidis was interviewed weeks later. I was never told what he said, or even who he was. I was never asked to respond to it. I did not know his name until the episode aired. That is not a simple editing decision. That is a quote from one interview, moved to follow a critique from a different interview it was not a response to, so that it would land as a concession. A friend of mine who has spent thirty years as a journalist read that sequence and called it sleazy. She is right. The full passage is reproduced in Appendix A, and it is worth reading. What airs is the preamble. Four paragraphs later I say “to directly answer your question” — and that answer, about what would change my mind if the team relocated, is not in the episode. Neither is the sentence two paragraphs on, where I say the EMF might turn out to be ten percent of the problem. I will say the underlying point again, though, because I meant it and I still do. I am not wedded to my theory that magnetic fields from the substation are contributing to the 49ers injuries. I could be wrong. What I am wedded to is the process of scientific inquiry, and the fact that we should be cautious around these exposures and we need more independently funded studies. 10. Three telling edits. They cut “I’m not a scientist” mid-sentence. What I said: “...and I am not certain of anything. I’m not a scientist. To me, I find the mechanisms compelling. I will go back to the fact that I got into this not because of the 49ers, but because of clients I was working with who suffer from EDS...” What aired: “...and that I am not certain of anything. I’m not.” The clip ends on the first two words of the sentence in which I say I am not a scientist, in an episode that spends considerable energy establishing that I am not a scientist. The full sequence is in Appendix A. They cut my own description of my work. Asked what I do, I said I run a wellness business, that I am focused on writing software to help people navigate environmental stressors, that environmental health is my focus, and that I also do independent journalism and research. What aired is the wellness business and the environmental health, with the software and the journalism removed from my own answer. The software engineering does come up later — narrated by them, as a hacker who grew up to write firmware — but my current work, in my own words, arrives as “wellness guy.” Thousands of commercial routers became home Wi-Fi. What I described: working at a wireless networking company surrounded by thousands of Wi-Fi routers, and a stress-induced health collapse afterward that working in that environment contributed to. What aired: Wi-Fi, the kind you have at home — reinforced by a clip of Christian McCaffrey talking about turning his router off at night. Three cuts, and every one of them makes me seem less credible. That is not a coincidence. 11. I gave them my own caveats and the test that would disprove me. In the first email I wrote that a well-designed chronic, ambient-level exposure study in tendon showing no collagen degradation, run over many months, would undercut my confidence in the theory. That is a specific, testable condition, stated in advance and in writing. There was a second interview, weeks later, which was not used in the episode, but in that I asked again for the falsification criterion to be included. What the episode presents instead is a man saying “we need more study,” which reads as a hedge, an open-ended request for the benefit of the doubt. It is the opposite of a hedge. Section 6 of my second email says, unprompted, that as far as I am aware there is not a single study showing EMF-driven oxidative stress degrading collagen in a human in vivo or in human tendon in a lab. I wrote that because it is true and because it is the first thing anyone should check. Under their standard it becomes the hinge of the entire first half, framed as something they had to surface without my cooperation. I had handed it to them five weeks earlier. And in the interview I said that my 25 to 50 milligauss readings were taken at knee level, and that these fields attenuate quickly, so by the time it reaches your head it is not that high anymore. That did not air either. The qualification arrives later, from Karipidis, as a correction. How you would actually study the injuries 12. They measured the wrong thing. The episode spends its final act on whether the 49ers are the most injured team in the NFL, finds no clean ranking, and lands on “injuries are random”. That is the wrong test. You would define the exposure — measured field levels at the facility — and the outcome narrowly: soft-tissue injuries, not a single MSK injury count that a broken finger and a ruptured Achilles both land in. Then you would compare the 49ers to themselves before and after the exposure changed, and compare that change against every other team over the same window. That controls for league-wide shifts in rules, turf and training load. It is a difference-in-differences design, and it is standard. I sent them that argument on July 28th, in writing, along with the fact that in eleven of the past twelve seasons the 49ers had finished top ten in Adjusted Games Lost. And by the episode’s own reporting, the 49ers are second in games lost to injury over the past decade, with FTN’s Aaron Schatz confirming that once you adjust for starters they come out second worst in the league — after having been one of the healthiest teams for years before that. A finding like that is where an investigation starts, not where it stops. 13. I did a lot of substation research for the episode that was never aired. I had reported that the substation next to the facility was expanded in 2014. That was wrong, and Rose Rimler and I sorted it out together. They gave me credit on air, which I appreciated, but framed it as a concession on my part to something they had found. In fact I had been investigating it myself, was uncertain before they asked, but was waiting for clarification from Silicon Valley Power. The uncertainty centered around a substation named “Esparanca” that was proposed right behind the facilities as part of the stadium construction, but now appears to never have been built. I spent days in Silicon Valley Power’s records, and did eventually reach Silicon Valley Power for confirmation and indentified the mistake myself. I also gave them highly detailed documents on what we do know about those facilities: new equipment installed between 2010 and 2014, and load growth across the system with an inflection around 2013–2014, with the Northern Receiving Station carrying the highest capacity in the system and sitting closest to the data center corridor. None of that is in the episode. I have a separate piece about it coming out soon. *I cut 2 seconds from the raw audio to remove personal information that had no connection to anything in the episode. Appendix A: the passage the clip was taken from This is the sequence from my first interview, in full. The episode uses one fragment of it. It’s tricky because my understanding is that there’s something like a 15-year half-life on collagen remodeling issues. They’re going to get a new crop of players. What I really need, though, is for the injuries to be broken down so we can see the soft tissue injuries. Right now, they’re categorized as MSK injuries, but let’s say we can actually identify them more specifically. Is that right? He was able to do that? Oh, cool. I wasn’t able to find that information. Interesting — I didn’t know that data existed. I tried so hard to get it, and I didn’t know it was available. Maybe you could connect me with that person. That would be amazing. I’m not wedded to it being an EMF, honestly. I’m not. I would say that, to a certain extent, I’ve staked my reputation on the fact that it needs more study. It’s important to look into it, and I am not certain of anything. I’m not a scientist. To me, I find the mechanisms compelling. I will go back to the fact that I got into this not because of the 49ers, but because of clients I was working with who suffer from EDS, Ehlers-Danlos Syndrome, a tendon hypermobility issue. This condition is documented to be partially caused by oxidative stress. I’ve worked with them to mitigate their EMF exposure and have seen people improve. I think it’s a bigger story. In a way, the 49ers represent an occupational cluster with specific exposure risks. If someone would conduct a study on this, I believe we could learn a lot. Perhaps we would discover that it’s like, okay, maybe it’s 10% of the problem. I don’t know the exact number, but I think either way, conducting the study would provide valuable insights. To directly answer your question, it’s challenging for me because it’s part of a bigger story. If the 49ers move and stop having injuries, I might conclude that it was related to the substation. However, if they move and still experience injuries, I would want to analyze the nature of those injuries. Are they primarily soft tissue injuries? I don’t think it’s necessarily a case closed, but the story might lose traction at that point regardless. Three things are worth noting. The aired fragment stops immediately before the sentence in which I say I am not a scientist — the cut described in item 10. It also stops four paragraphs before the words “to directly answer your question.” What the episode plays is the throat-clearing. The actual answer, about what would change my mind, never airs. And two paragraphs in, I say the EMF might turn out to be ten percent of the problem. That is the ranking the episode says I never gave. Appendix B: the full email, July 6th, 1:39 PM Hi Rose, You asked me to send you some studies a couple of weeks ago. I apologize for the delay. I have been incredibly busy. I also wanted to give you a chance to dig in yourself, and get your own perspective before I influenced you too much with mine. That said, I do want to make sure that the actual argument is abundantly clear, so here it is! One note before I begin, there are really two separate questions here: Does the substation cause the soft-tissue injuries? That was my specific claim, and what the podcast is about. Is the theory biologically sound? Can 50/60 Hz fields at these levels do anything biological below the safety limits? Question two is why people have been calling me a conspiracy theorist. The regulatory and advisory bodies (ICNIRP, etc) maintain that anything below their exposure limits is biologically inert, and that position is broadly accepted within the mainstream, but the actual science paints a different picture. To defend my theory I’ve had to defend a much larger claim: that the advisory bodies have the biology wrong. I can’t honestly answer question 1 without first addressing that. Here’s is a simplified outline of my theory, with links to studies: 1. Advisory body thresholds for biological effects The ELF magnetic-field limits (ICNIRP’s ~2,000 mG public / 10,000 mG occupational) exist to prevent acute effects from exposure. If a magnetic field is strong enough, it makes nerves fire and muscles contract. Muscles twitch. You can see faint flashes of light in your vision. People can even feel tingling or even a shock. That happens due to Faraday’s law, which states that a time-varying magnetic field induces an electric field inside the body via the creation of Eddy currents.The standards assume that those currents do nothing below the twitch threshold. They do not consider chronic effects at all. My argument is that they are biologically active and do have chronic effects. 2. There are multipe ELF-EMF mechanisms for inducing oxidative stress. This is basic biophysics. Below are the two primary mechanisms. Simplest first. Dr. Paul Héroux of McGill has the most intuitive explanation, which rests on Maxwell’s principle of superposition: because Maxwell’s equations are linear, two sets of electromagnetic waves sharing the same space simply add together. In the interview I pictured a pebble dropped into a pond, sending out clean ripples. Then a boat motors past at distance, sending larger waves, and where they meet the ripples, the two add together and the original pattern gets distorted. In our cells, the mitochondria run on continuous currents of electrons and protons that carry their own faint electromagnetic fields. An external field from a substation, by the principle of superposition, adds to those internal currents and shifts the pattern. The electron transport chain in the mitochondria leaks a fraction of its electrons by design as reactive oxygen species (ROS), which act as signalling molecules in a healthy cell. Distorting that field increases that electron leakage, creating oxidative stress. A tiny electromagnetic interference results in a large downstream effect. https://www.sciencedirect.com/science/article/pii/S2405844025006474 The more complex pathway is Dimitris Panagopoulos’s Ion Forced-Oscillation / Voltage-Gated Ion Channel (IFO-VGIC) mechanism. Weak, polarized, low-frequency fields force the ions (calcium, potassium, sodium) next to an ion channel’s voltage sensor to oscillate; because that force scales with the inverse cube of the distance involved, fields far below the stimulation threshold can still force the channel open, disrupting the cell’s ion balance and driving ROS overproduction (Nitric oxide and superoxide interact and produce peroxynitrite, a highly unstable cytotoxin that breaks down into free radicals). https://www.researchgate.net/publication/366088934 https://www.spandidos-publications.com/ijo/59/5/92 https://www.mdpi.com/1422-0067/22/18/10041 https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1585441/full https://pmc.ncbi.nlm.nih.gov/articles/PMC3772193/ 3. Evidence of oxidative stress, in vivo, in humans from ELF-EMF There are many studies, and the strongest are occupational, which applies to the 49ers situation. 115 power-plant workers vs. 145 office controls. Serum malondialdehyde (MDA, the standard lipid-peroxidation marker), superoxide dismutase, and catalase were all significantly higher in the exposed group, and the markers rose with increasing field exposure. https://journals.sagepub.com/doi/abs/10.3233/WOR-203244 A follow-up where they reversed the oxidative stress in power plant workers. A double-blind randomized controlled trial: 91 power-plant workers given vitamin E, vitamin C, both, or placebo for 90 days. The antioxidant groups showed reduced lipid peroxidation and raised antioxidant capacity versus controls. https://pubmed.ncbi.nlm.nih.gov/32191586/ A spot-welder study: 46 welders occupationally exposed at 50 Hz, showed significantly altered red-blood-cell antioxidant enzyme activity and concluded ELF-MF “might act as an oxidative stressor… even at the recommended levels of exposure.” https://pubmed.ncbi.nlm.nih.gov/18504600/ A substation-specific study found oxidative stress and DNA damage https://pubmed.ncbi.nlm.nih.gov/24460415/ 4. Oxidative stress degrades collagen This half isn’t controversial at all. Oxidative stress activates the matrix metalloproteinases (MMPs) that break collagen down and suppresses its synthesis. Here are three example studies: Siwik et al. 2001: Oxidative stress raises MMPs and lowers collagen synthesis in cardiac fibroblasts. https://pubmed.ncbi.nlm.nih.gov/11121376/ Fisher et al. 2009: Collagen fragmentation drives oxidative stress and elevates MMP-1 in aged human skin. https://pmc.ncbi.nlm.nih.gov/articles/PMC2631323/ Varani et al. 2006: Decreased collagen production in oxidatively aged skin. https://pubmed.ncbi.nlm.nih.gov/16723701/ 5. What about the study showing improved collagen synthesis I’m glad you asked this question, and I’m bummed we didn’t get to it in the interview because it is a great question, and very important to understand. Superficially it may appear to be a refutation of my theory, but I would argue that it actually supports the underlying argument. That study used a short, high-intensity pulsed dose: therapeutic-PEMF, the same type of field used clinically to stimulate bone and tissue healing. The reason this works is because it triggers the very same biological pathways that can lead to oxidative stress. The exposure still stimulates ROS production, but done at a controlled dosage, for a limited duration it has a different effect. The cell reads the ROS as a warning signal and it upregulates its antioxidant defenses, and mounts a repair/proliferation response. The therapy is then stopped before the cell gets overwhelmed. That is essentially a hormetic response: a small dose of a stressor producing a beneficial adaptation. Two things follow: At the very least, this means the field is biologically active, which by itself undercuts the regulatory claim that these fields are inert below their thresholds. There is a wealth of literature on PEMF (pulsed EMF) bone regeneration and calcium channel signalling (which is the second mechanims in section one). Here is one. https://www.nature.com/articles/srep13856 At best, it leads us straight to my actual concern, which is that under chronic, chaotic and unregulated exposure, the cell’s antioxidant capacity gets overwhelmed, resulting in oxidative stress. There are plentiful examples of things that are beneficial at controlled doses, but harmful at uncontrolled doses. Excecise is one obvious, uncontroversial example. Botox is perhaps a more interesting example. 6. What about a study that shows EMF causing collagen degradation in humans? As far as I am aware there is not a single study showing EMF-driven oxidative stress degrading collagen in a human, in vivo, or in human tendon in a lab. There are studies involving isolated fibroblasts though, which secrete collagen. The most relevant one showed that human fetal scleral fibroblasts exposed to 50 Hz ELF-EMF showed a significant decrease in collagen synthesis and that MMP-2 expression was upregulated, which is the exact mechanism I described in section 2. https://pmc.ncbi.nlm.nih.gov/articles/PMC3626379/ That’s it! Thanks again for the interview. Best, Peter Anthony Cowan Environmental Health · Wellness Tech · Researcher & Journalist Publisher & Editor, Living Energy Bio: petercowan.comSocial: X · Instagram · TikTokApp: sunlightis.lifePhone: [redacted]
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Engrams Embedding Entendre: Codesign for Efficient DRAM/SSD Offloading
Engram extends standard token embeddings with learned multi-token lookups. Recurring local patterns retrieve vectors directly, reducing the need to reconstruct them through attention and feed-forward layers. With Engram model architecture optimization, it allows for lower HBM capacity to be needed for models at the same quality. This does not mean there won’t be an insane demand for HBM but it just means that model architecture will continue to innovate around constraints. This model architecture design is naturally codesigned for parameter offloading: each token accesses a few embedding rows whose addresses depend on token IDs, not hidden states. The runtime can prefetch those rows from host DRAM while earlier layers compute, keeping the table outside HBM without transferring entire weight matrices. Our Memory model contains our latest estimates of quarter by quarter HBM, DRAM, & NAND supply and demand. Offloading frees HBM for model weights and KV cache, potentially supporting larger batches or more concurrent sessions. When DRAM becomes the next constraint, NVMe offers another tier. Recommendation systems already cache frequently or recently accessed embedding rows in faster memory while backing colder rows with SSDs. After NVIDIA roadmap had to change due to massively despec’ing Rubin Ultra from 1024GB to now ~200GB of HBM per chip, model architecture optimizations like emgram maybe helpful. Our DeepSeek-V4.1-Flash configuration uses roughly 189 GiB of memory for Engram. We replace it with a memory-mapped (mmap) file and measure serving performance with offload to SSD. Later on in our report, we will show our Engram offloading experiments along with the official InferenceX agentic inference serving results on Engram models like DeepSeekv4.1 Flash across all 6 NVIDIA GPU SKUs along with MI355X. Unsurprisingly, the CUDA Moat is still mogging MI355X on the ultra popular DeepSeekV4.1 Flash model. We also show how even on high capacity HBM SKUs, offloading emgrams to DRAM could result in even better performance for most of the pareto than keeping the emgram in HBM. Our benchmark has been widely reproduced, validated and/or supported by almost every major buyer of compute from Google Cloud to Microsoft Azure to Oracle, to Meta and many more. Furthermore, it has the support of the ML community including from vLLM, LMCache, SGLang, PyTorch, Huggingface and the support of major labs like OpenAI, MiniMax, ZAI, Qwen, Moonshot Kimi, etc. Star the InferenceX GitHub repository if you find the open-source benchmark and data useful!. InferenceX is the only inference benchmark in the world to have TPUv7, Jalapeño, Nvidia Rubin NVL72, AMD, and soon, SambaNova and Trainium. Due to how realistic AgentX scenario is to real world agentic inference workloads, AMD has committed to collaborating on MI455X UALoE72 too. DeepSeek did not release the original paper’s two trained Engram models. We replicated its setup on fineweb-edu using the released code and training hyperparameters, at an estimated 6E18 FLOPs per run. We observed the same U-shape scaling: Engram improved performance over pure MoE baselines. We also reproduced DeepSeek’s results, where earlier-layer representations with Engram resembled those of later layers. Like the original Engram paper, it is possible to probe Engram’s gate scores to see what n-grams DeepSeek-V4.1-Flash makes the most use of. Our gate scan finds names, code fragments, relational phrasing, and boilerplate. These examples prioritize interesting-ness over gate strength. One unexpected result was Wright : Ace Attorney. These examples suggest learned memory optimizes the training objective, not a judgment of which facts deserve storage. Licenses, bibliography fragments, API scaffolding, and website furniture can provide prediction shortcuts, so the value of additional Engram capacity may depend on what survives data preparation. This does not show that table capacity is “wasted”: the evaluation-corpus scan establishes neither training exposure nor the capacity occupied by each category. For offloading, strong gates do not identify cache-hot rows. Low gates do not automatically save reads either: computing the gate requires the retrieved key and undoes the performance gain of a fused kernel. Skipping reads would require a separate usefulness predictor before retrieval. In the original paper’s inference-time ablation, factual-knowledge benchmarks retained just 29–44% of their original performance, while reading comprehension retained 81–93%. This is due to the training–inference mismatch. The resulting degradation therefore measures this trained model’s dependence on Engram, not the performance difference between models trained with and without it. In our ablations, suppressing Engram worsens token likelihood across all evaluated domains, especially encyclopedia text and several code corpora. Surprisingly, GSM8K accuracy stays within measured run-to-run variation and removing Engram has no effect. Engram is not a detachable dictionary beside an unchanged MoE. Removing it changes downstream features and expert selection. We tested whether rerouting hurts or compensates by holding tokens fixed in a teacher-forced experiment on CRUXEval, a code-reasoning benchmark of small Python functions where the model predicts a function’s output from its code and an input, and scoring the reference answer. Removing Engram raised answer loss from 0.2848 to 0.3093 bits/token. Forcing the ablated model to use the original Engram-on expert choices made it worse still, at 0.3375 bits/token. Rerouting partially compensates for the missing memory. Memory features and expert selection work together, rather than following a clean “memory stores facts; experts reason” division. On the same CRUXeval, removing Engram during either phase reduced accuracy and increased generated tokens; removing it throughout produced the largest changes. Keeping Engram for prefill leads to more correct answers than keeping for decode likely due to semantically richer KV cache transferred to decode workers, allowing it to mitigate some of the performance loss. Engram’s table is large, but each lookup is small. DeepSeek-V4.1-Flash requests 24 rows at each of two Engram layers, about 12.4 KiB per processed token position across the model, or 3.1 KiB per GPU when split across four GPUs. Currently as of Day 7 since Model Release, MI355X is still 2-4x worse performance per dollar compared to B200 even when normalized by Mi355X’s lower TCO. Our full total cost of ownership breakdown comes from our AI Cloud TCO Model along with monthly market surveys of over 100+ gpu clouds & gpu cloud customers. On the Day 0 release of DeepSeekv4.1 Flash, NVIDIA vLLM works out of the box with zero issues across all 6 SKUs: H100, H200, B200, B300, GB200, GB300! This was thanks to the amazing work by the NVIDIA & Interact teams! In comparison, AMD vLLM did not work on day 0 for DeepSeekv4.1 Flash.Source: SemiAnalysis InferenceX AMD’s vLLM documentation points to using vllm/vllm-openai-rocm:deepseekv41-flash-0909, but from hour 0 of the model release to hour 23, AMD has not publicly released the image. AMD claims, “SPEED IS THE MOAT,” yet it has still not released it by the 23rd hour. We wish that, going forward, the AMD team has a better process for hour 0 model releases. Eventually when they did publicly release for “day 0” image support, performance-wise, it is currently up to 14.8x worse perf per dollar than H200 and up to 42x worse perf per dollar than B200/B300. The power of the CUDA MOAT is NVIDIA’s collaboration with its massive 6 million-developer community ecosystem including most of the vLLM & SGLang & Tokenspeed maintainers which means that CUDA is optimized on day 0. Overall, AMD did make significant improvements but the performance per dollar is still currently 2-4x worse than B200. AgentX Engram DRAM Offloading Improving Performance The HBM and DRAM offload use the same GPU kernel to select and dequantize rows. With HBM, it reads GPU memory; with Unified Virtual Addressing (UVA), it reads pinned host memory directly. Both support full decode graphs. Moving the table into HBM accelerates only the sparse lookup, leaving decoder computation and communication unchanged, resulting in little overall benefit while consuming memory otherwise available to KV cache. Another benefit of Engram offloaded to DRAM which means you can reduce the communication overhead by using less HBM GPUs per replica. For example, when enabling Engram offloading on B300, we are able to switch from TP4 to now TP2 which improves the pareto curve by up to 1.6x. When iso-model quality, less HBM is required as the engrams could be offloaded to host DRAM. Thus HBM bandwidth matters way more than HBM capacity. For inference workloads where memory bandwidth matters the most, 4-hi HBM provides the best $/bandwidth and therefore lowest cost per token. If China continues to make more and more revolutionary model architecture innovations, soon it could potentially 0Hi HBM stacks. [ ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) [ Long Live the Short King: Why 4-hi HBM Wins ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Myron Xie, Bryan Shan, and 3 others · Sep 13 [ Read full story ](https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi) Moreover, on B300 and week-0 stack, moving the Engram table back to HBM did not improve results and stay within run-to-run variance. This is a result of the work optimizing DRAM offload, such as async, and overlap. SSD Offloading On B200, we created a unoptimized vLLM fork and stored the Engram tables in memory-mapped files on local SSDs. File backing lets the OS reclaim table pages when other applications need RAM. Pages already cached in memory can be served without reading the SSD again. Furthermore, note that we were unable to turn on GDS The unoptimized SSD implementation changes how rows reach the GPU. It copies row IDs to the CPU, deduplicates them, gathers the requested rows into pinned buffers, copies those rows back to the GPU and dequantizes them. This work runs between segments of the GPU execution graph. Native UVA performs row selection and dequantization directly on the GPU, avoiding the CPU round trip. A warm filesystem cache removes physical SSD reads, but leaves the coordination, row gathering and transfers. This is why a file already cached in RAM can still perform worse than a pinned DRAM table. The comparison measures the whole serving path; it does not separate the time spent on each of these operations. B200 DRAM dominates both measured SSD serving curves in total tokens per dollar and P90 interactivity. Near 125 tokens/s/user, DRAM delivers 121 million total tokens per dollar versus 52 million for SSD. For production serving, SSD offloading is likely not worth the tradeoff. On the B200 configurations we measured, SSD offloading loses on both measures: every observed SSD point has a DRAM alternative that delivers higher P90 interactivity and more total tokens per dollar. The only points where Cheaper storage does not automatically produce a cheaper inference service. Moving Engram to SSD leaves the same four expensive GPUs and the rest of the server in place. Reclaiming RAM only creates an economic benefit if it enables a cheaper server configuration or additional useful capacity. The current unoptimized path provides neither benefit, and the filesystem cache still consumes RAM when table pages are resident. Next we will look at the mechanisms and specific implementation of ngrams from DeepSeekv4.1 Flash, LongCat, Qwen3.8 Flash Next.
Her postpartum depression spiraled and she couldn't get care. She's not alone
Half of U.S. women had trouble when getting health care, according to new research. One in three women said a doctor minimized or dismissed symptoms.
Executive Profile: Laura Martina
Laura Martina Founder/CEO Leadby What we do: Results-driven leadership development services customized to meet the needs of executives and teams. Education: Bachelor of Science from Fresno State in business administration, human resources
Washington Commanders reveal interior design of planned $3.8B domed stadium with wraparound seating bowl
The Commanders unveiled interior designs for their $3.8 billion domed stadium at the RFK campus, featuring a wraparound bowl designed to maximize crowd noise and sight lines.
Science-rooted tips for optimal aging
September is healthy aging month and it's a great time to review your routine, make those doctor's appointments and check-ups, and make the simple changes that will make you feel better and age better. Amber Freeman, host of Bloom sat down with Physician Dr. Lauren Natoli who gives us a science-based approach to help optimize our lives.
GE HealthCare launches AI-driven operations system
GE HealthCare announced Tuesday the launch of a new artificial intelligence-enabled SaaS application to help healthcare organizations optimize resources and expand care access. | The application—dubbed CareIntellect for Operations—can forecast capacity constraints up to 72 hours in advance, the company says.
GE HealthCare Announces CareIntellect for Operations, Helping Health Systems Optimize Resources and Expand Access to Care
CHICAGO, September 15, 2026--GE HealthCare (Nasdaq: GEHC) today announced CareIntellect™ for Operations, a new AI-enabled Software-as-a-Service (SaaS) application designed to help health systems forecast capacity constraints up to 72 hours in advance, providing comprehensive unit-, department-, and enterprise-level views of emerging bottlenecks. By analyzing hundreds of patient- and operational-level data points—including bed availability, patient delays, staffing, wait times, and ancillary serv
UK’s Be Healthy Bash returns Sept. 19 with free health and wellness resources
Community members can connect with health experts, receive free screenings and enjoy activities for all ages at the annual Be Healthy Bash.
Valve Announces Steam Frame Price, Release Date, and Accessories
Valve today opened pre-orders for Steam Frame, its long-awaited standalone VR headset, which finally reveals pricing info, official accessories, and release date. Steam Frame is set launch at the following prices (inclusive of VAT where applicable): Valve says it’s following a similar approach to how it handled Steam Machine pre-orders, i.e. it’s using a randomized […]
Testimony of Brian Blase before the United States House Judiciary Committee Subcommittee on the Administrative State, Regulatory Reform, and Antitrust — "Examining Healthcare Markets: Fraud and Competition"
Government has created incentives to maximize subsidies while weakening incentives to improve productivity and compete for patients.
Business Monday: Hilo Pizza Co. serving up New York-style pies and slices that patrons can customize
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Bone Health Without the Hype
I am at the Australasian Menopause Society meeting and we had a fantastic lecture on Bone Health on Day 2, called, “Everything you need to know about bones - except the boring bits!” Spoiler alert, there were no boring bits. The lecture was given by Dr. Amanda Beech, who is a senior staff specialist in Obstetric Medicine and Endocrinology at the Royal Hospital for Women, where she is director of the Bone Density Unit. I want to summarize my top 10 take-aways for you. Share Osteoporosis is a disease of low bone mass, disruption of bone microarchitecture, and fragility of the skeleton. It is a silent disease…until someone develops a fracture. The diagnosis of osteoporosis is based on either fragility/minimal trauma fractures or a T-score of less than -2.5 on a DXA (Dual-Energy X-ray Absorptiometry) or bone scan. It is important to recognize that about 50% of minimal trauma fractures occur when women have low bone mass (often referred to as osteopenia), but not osteoporosis. This tells us that bone strength is more complicated than a number on a DXA report. I am going to add a little here that wasn’t in the talk (one can only include so much in 25 minutes), as many women might read the above paragraph and think, “Shouldn’t we be treating everyone with low bone mass if this is when 50% of the fractures occur?” Many fractures happen for women with low bone mass because there are so many women with low bone mass –it is a statement about the population on a whole, not about the fracture risk of low bone mass. For you as an individual, bone density is only one component of fracture risk and many women with lower bone mass will not have a significantly elevated fracture risk. This is why individualized risk assessment matters. Subscribe We build bone in our teens and twenties, and by the time we are about thirty we have reached peak bone mass. This is why, when we discuss risk factors for osteoporosis, it is important to consider factors that might have affected us in our teens and twenties when we were actively building bone, such as nutritional restriction/energy imbalance. It is important to ask women about a history of eating disorders, and for those with such a history, getting a bone scan in perimenopause or at age 50 is likely warranted. (This image below isn’t from the talk, but is similar to one that was). Bone mass is relatively stable until about two years before the final menstrual period, and perimenopause marks a time of rapid bone loss for women. Using urinary markers of bone loss we know that the time of significantly accelerated bone loss starts about 1 year before the final period and ends about 2 years after the final period. The Study of Women’s Health Across the Nation (SWAN) shows that over the menopause transition women lose an average of 10.6% of the bone at their lumbar spine and 9.1% at the femoral neck While this wasn’t covered in the lecture, I want to add that the rapid bone loss during perimenopause is clearly related to more than estradiol, because during this time estradiol levels can be erratic and not uniformly low. Bone loss during perimenopause is likely a multi-hormone event. For example, rising FSH (follicle stimulating hormone) tracks with bone loss better than estradiol, and there is evidence that FSH may act directly on bone. While decreased estrogen matters, there is clearly more going on. FSH and bone is an active area of research. Subscribe Screening for osteoporosis was recommended fairly broadly before age 65, and was taken from the “Practitioner’s Toolkit for Managing Menopause,” from Monash University. Here is a screenshot from the toolkit that was used as a slide: I am going to add a little bit more about body weight here for clarification. Low body mass (typically 152.1 lb): 0 points (risk neutral) 60–69 kg (132.3–152.1 lb): 3 points (adds some risk)
Your Employer's Health Plan Is the Single Largest Tax Break in America, and It Never Shows Up on Your Return
The biggest tax break most American workers receive never appears on their return, never gets debated at filing time, and quietly delivers a bigger federal subsidy to higher earners than anything they could ever itemize.
Wilmington health tech founder launches new venture
Several years after launching his health tech startup Artemis Immersive, founder Adam Isley is setting his sights on new horizons. Co-founded in 2023 by husband-and-wife Adam Isley and Kaylan Barbrey, along with Matthew Raffa and Bill Blakesley, Artemis Immersive began as a spatial medtech company that created digital renderings of medical scans for viewing in augmented reality (AR). Isley said the firm, which won an NC Tech award in the Biotech + HealthTech Innovation category last year, has raised $1.2 million in total in seed funding since launching. Isley has since created a new venture, Research and Me, building on the Artemis platform. Like Artemis Immersive’s core software, VoxScan, Research and Me combines health data with artificial intelligence in a 3D interactive environment to help patients better understand health outcomes and provide integrative wellness support. While the Artemis product is no longer Isley’s primary focus, he said the company’s technology and ambitions have evolved into different ventures, like Research and Me. "It's a different venture building on the Artemis platform, and there'll probably be more,” Isley said. He added, "I was very disappointed in the quality of the information available to general patients about their healthcare... I wanted to give patients more and a better plate of choices." Research and Me is still in its beta phase, Isley said, with usability testing ongoing in partnership with the firm’s partner, Medicap Pharmacy and Wellness Center, owned by Barbrey. "As someone who's kind of dedicated their life to working in healthcare, I've tried to bring this spirit and passion to it,” he said, “and a lot of the resources that we'll be providing are free — like a base level of free care for any patients, or medical education if they've got specific conditions." Isley describes Research and Me as a “patient-first” platform designed to securely store and pseudonymize health data and use AI and medical literature to generate insights. The insights are presented in an interactive 3D environment for patients and providers to explore conditions, treatments and wellness plans together. "It's almost like a democratization of understanding medical information," Isley said. "We take a whole bunch of clinical data, we take a whole bunch of peer‑reviewed, published studies on PubMed, and we try to turn them into chunks of information that normal humans can understand." Like VoxScan, the Research and Me platform lets users interact with 3D anatomical models for visualization. The platform provides a space for tracking, notes and insights. The platform also supports video conferencing, Isley said, allowing providers or coaches to examine models and data together. "We wanted to create a safe environment where you can start to learn and experiment with new features about your health, using agents to do that,” Isley said. While Research and Me is in beta-phase testing with Medicap Pharmacy, Isley said he envisions the platform serving a wellness-oriented community, working with sports performance clinics and hormone optimization. Isley, who is working towards a wellness-coach board certification, also plans to offer functional wellness consults through the platform. Long‑term, Isley says he wants the platform to embody an “integrative health practitioner” approach, “connecting experts of different fields and specializations in a way that they can make a greater impact in people's lives.” “For people in the state of North Carolina, it's already a win,” Isley said of the Medicap rollout, noting that partner clinics get “immediate resources for learning about their health and wellness conditions… out of the box.” Isley plans to launch Research and Me’s provider portal in 2028 and begin pursuing integrations with larger systems, he said.
Phoenix Suns Bold Prediction Could Save 2026-27 Season
Jordan Ott faces a critical rotation gamble as analysts urge a backcourt shakeup, swapping Jalen Green’s explosive scoring for Collin Gillespie’s steady playmaking to maximize Devin Booker.
Here's how iPhone Duo treats apps not optimized for the foldable display
Apple has officially announced the iPhone Duo, its first foldable display device. Additionally, the company has detailed how third-party apps...
How one org taps into neighborhood power to address climate change and health equity in Memphis
[vc_row][vc_column][vc_column_text] Q&A with Center for Transforming Communities For the Center for Transforming Communities, climate change and health equity are not abstract concepts. They show up in the soil, in the quality of drinking water, in neighborhood walkability and in access to food. The organization works closely with residents and institutions to minimize negative impacts of … Continue reading
Peapack Private Expands Specialty Lending Capabilities with Launch of Yacht Financing Business
Jim Velez Jim Velez, Senior Managing Director and President of Yacht Financing at Peapack Private BEDMINSTER, N.J., Sept. 09, 2026 (GLOBE NEWSWIRE) -- Peapack-Gladstone Financial Corporation (NASDAQ Global Select Market: PGC) and Peapack Private announced today its entrance into the yacht financing business, further expanding the Bank’s suite of customized lending solutions for high-net-worth individuals, families and their advisors. As part of the launch, Peapack Private has hired industry vete
The Science Behind Big Mistakes and 4 Things You Can Do to Avoid Them
Researcher shows many big mistakes can be avoided or minimized if people pay more attention to early factors. Here's what you need to know.
Hunter Biden launching a laptop-themed cryptocurrency
Hunter Biden's $Laptop meme coin launches on Base blockchain, with 20% of tokens going to those who lost money on Trump's $TRUMP crypto coin.
Accenture and Google Cloud Deepen Partnership with Formation of New Accenture Gemini Enterprise Business Group
Accenture and Google Cloud today launched the Accenture Gemini Enterprise Business Group, a global group designed to help clients scale Gemini Enterprise outcomes in the agentic AI era.
New Steelers HC Customized 2026 Offense For Aaron Rodgers
Aaron Rodgers and Mike McCarthy are back together once again, this time as members of the Pittsburgh Steelers. The quarterback is in his final NFL season, while McCarthy is back after a year away from the game.The two have a ton of rapport and also have a Super Bowl title together. The opponent in that […] The post New Steelers HC Customized 2026 Offense For Aaron Rodgers appeared first on HEAVY.
Perilla frutescens Benefits: Effects on Allergy, Inflammation, Immunity, and Gut Health
Perilla frutescens contains phenolic acids, flavonoids, and other bioactive compounds that show anti-allergic, immunomodulatory, anti-inflammatory, and gut-protective effects across laboratory and animal studies. Limited human evidence, including a small randomized trial of rosmarinic-acid-enriched Perilla extract for seasonal allergic rhinoconjunctivitis, is promising, but larger standardized clinical trials are needed.
[0.5.5] Twister Gemling Legionnaire - PoE 2 Mercenary Build Guide
Conquer the game with [0.5.5] Twister Gemling Legionnaire PoE 2 Mercenary build! Learn everything about the build: equipment, skill gems, passive tree, gameplay, and mechanics.
UChicago Social Sciences Took a Stand Against AI and Devices. Why?
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Trump says Iran conflict, which has killed 18 US service members and injured hundreds more, is ‘small potatoes’
President Donald Trump on Friday labeled the Iran war “small potatoes,” the latest attempt to minimize a six-month conflict that caused a spike in gas prices and led to the deaths of 18 American service-members.
Sports Stylists Reveal Secrets Behind Spectacular Tunnel Fits
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Fort Bragg Veteran celebrates expansion of high-end experiential entertainment brand
Photo provided by EscapologyAfter 15 years as an Army officer at Fort Bragg, Fayetteville resident Dan Cooke transitioned to business ownership to bring high-end experiential entertainment to North Carolina, applying strict military operational systems to scale his footprint across the state.Cooke got his start in the Army’s Boots to Business program.“Boots to Business was instrumental in preparing me to start a company. The program taught me how to develop a business plan, conduct market and financial analysis and critically evaluate whether a business concept was actually viable,” shared Cooke. “What made the program particularly valuable was that the instructors and mentors had real-world business experience…At the end of the course, I had to present and defend that plan. From there, they directed me to SCORE, where mentors helped me further refine the plan. I eventually presented it to a bank, which was impressed with the level of preparation, and I secured the financing necessary to build the business.”As Cooke neared the end of his military career, he began to wonder what would come next. Through his faith and some valuable mentors, he found the right avenue for his entrepreneurial interests.“While working on my instrument pilot rating, my flight instructor happened to tell me about escape rooms and the economics behind building them. He thought they could make for an interesting business. I took the analytical skills I had developed in the military, along with what I learned through Boots to Business, and began comparing the escape-room model against other opportunities I was considering,” explained Cooke. Cooke opened his first Escapology location in Fayetteville in 2019.“My approach was to start small and prove the model. Fayetteville made sense because I was already there, understood the market and could minimize my initial risk. It also became clear very quickly that I needed a partner that could provide the creative design, branding and industry knowledge that I did not have. After researching a number of options, Escapology became that partner,” added Cooke.Following the success of his initial venue in Fayetteville and a venue in Charlotte that opened in 2023, Cooke recently expanded into Raleigh with his third Escapology venue at Crabtree Valley Mall.His North Carolina footprint now includes:Fayetteville: A 5-room venue launched right after his Army transition in 2019.Charlotte: A 10-room venue opened in 2023, doubling his original operational footprint.Raleigh (Crabtree Valley Mall): A 6-room venue opened in May 2026, with plans to expand to 10 full rooms.Beyond his venues, Cooke expanded his local footprint by launching Jade Solutions in Aberdeen, N.C., an OEM manufacturing business that now builds prop and technical solutions for Escapology venues systemwide.Cooke shared that his long-term goal is to continue expanding Escapology in a healthy and sustainable way while enjoying the journey. “I actually did not start an entertainment business because I personally loved escape rooms. I started a business because I love the game of business itself. Growing up, I loved military simulation games and business tycoon games. I eventually had the opportunity to experience the first of those in the real world — I went to war, led troops and played my part in the military. Today, I would much rather apply that same drive to the real-world game of building businesses.I don't play business computer games anymore. I get to wake up and do it for real every day,” shared Cooke.
Topgolf, Family Entertainment Group team up to create exceptional guest experiences
Family Entertainment Group, a national developer and operator of entertainment experiences, is partnering with Topgolf to create exceptional guest experiences through customized entertainment solutions and operational excellence. The phased rollout follows a successful pilot program at seven Topgolf venues, according to a press release
Mac App Store Apps Can Now Drop Support for Intel Macs
Apple today informed developers that universal Mac App Store apps that require macOS 13 or later can remove support for Intel-based Mac computers. We're reaching out to let you know that universal macOS apps on the Mac App Store that require macOS 13 or later can now remove support for Intel-based Mac computers. By removing support for Intel-based Mac computers, you can simplify your development and optimize your download and on-device size.