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Dallas business owner pistol whipped during robbery, police search for suspect
Dallas Police are searching for a robbery suspect who they say pistol whipped a Cedar Crest business owner and sent him to the hospital.
'Nobody knows what to do': How Long COVID left Physics Girl searching for answers
San Diego's Dianna Cowern, also known as Physics Girl, was one of the internet's most popular science communicators. Long COVID left her bedbound and facing a medical mystery with life-and-death stakes.
Spurs, Victor Wembanyama Searching For Answers After Loss to Thunder
The San Antonio Spurs lost their first game of the season to the Oklahoma City Thunder on Tuesday night.
Suspects wanted for string of business burglaries in Fairfax County
Police are searching for suspects accused in a string of Fairfax County business burglaries.
Scientists Use Ancient Rains to Map the Possible Origin Life on Mars
Billions of years ago, rain may have helped shape where the chemistry of life could begin on Mars. A new study maps how formaldehyde, an important prebiotic molecule, may have reached the surface. This map could help guide future missions searching for signs of past life on Mars.
Experts Reveal How MS Can Be Misdiagnosed Amid Christina Applegate’s Surprising Health Update
Christina Applegate is searching for answers after learning that she was misdiagnosed with multiple sclerosis (MS) five years ago — and medical experts say several conditions can be mistaken for MS, m...
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.
Green Bay Packers add former first-round pick amid defensive line injury concerns
The Green Bay Packers are searching for defensive line help after injuries weakened their options up front. With starting nose tackle Javon Hargrave out, veteran Chris McClellan is expected to fill the role, but Green Bay has limited depth behind him. To strengthen the rotation, the Packers have signed a former first round pick to [...]
Regional Science Consortium Researching Harmful Algal Blooms
If you've noticed large buoys or boats out on the bayfront and wondered what they were, you're not alone. The Regional Science Consortium is collaborating with Princeton Hydro on a research project funded by the U.S. Army Corps of Engineers to study ways to control harmful algal blooms. Dr. Jeanette Schnars, the Executive Director of the Regional Science Consortium, explained the goal of the research."We are researching different ways to control blue-green algae, which creates harmful algal blooms and releases toxins," Dr. Schnars said.The project aims to identify potential techniques for controlling harmful algal blooms in Presque Isle Bay.Schnars explained that people may notice circular floats in the water near Perry's Landing and Liberty Park. Those floats are part of the testing process."You might see a circular float, almost like a hula hoop, that is out in the bay, near Perry's Landing and Liberty Park area, and those limn corrals go all the way to the bottom. And what we will do are some treatments within the limn corral in the bottom," Schnars said.After samples are collected, they are brought back to the laboratory at the Tom Ridge Environmental Center for analysis."A lot of those samples are coming back here. We are going to test them for the harmful algal bloom toxins before, during, and after, and see how effective the testing was," Schnars said.Sarah Magyan, an aquatic biologist with the Regional Science Consortium, explained that the team also collects samples from locations throughout the region."We pull samples every week from 30 different sites, and then we bring those back here, we preserve them and run them through the ELISA test," Magyan said.Schnars said researchers hope the results will help them develop effective ways to reduce harmful algal blooms in the future."If we can do some treatments over space and time in upcoming seasons, we may be able to reduce the number of harmful algal blooms we have in this area," Schnars said.The research is also important for public and animal safety. Magyan explained that toxins produced by certain algae can affect the skin, nervous system or liver.While toxin levels may be low for people, she emphasized the importance of protecting pets that swim in local waterways."Toxins can either be skin toxins, nerve toxins, or liver toxins. While we have low levels for people, it is important that we are keeping our pets safe because we recreate with our animals in the water, and we see hundreds and hundreds of dogs on Presque Isle and the rest of the shoreline," Magyan said.Testing began in September, and Schnars said researchers expect to conduct at least another six to eight weeks of testing to better understand the effectiveness of the treatments.
Why millennial women are 'leaning out' of the corporate world
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Arsenal have business reasons for job losses, but it symbolises the bleak reality of how football is run
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Bears offense searching for consistency
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Your Business Probably Has More Data Than Insight by Nathan Tayloe
Most businesses know more about themselves than they ever have. Leaders have access to financial reports, sales pipelines, customer data, employee metrics, website analytics, and dashboards for almost every part of the organization. CRMs track every stage of the sales process. Marketing platforms report results in real time. AI can analyze and summarize enormous amounts of information in seconds. Yet I've sat in plenty of meetings where all of that information is available, and some of the most important questions are still surprisingly difficult to answer. What's actually working? Why are customers choosing us? Where are we losing opportunities? What should we do differently? Having the data and understanding what it means are two very different things. More Information Doesn't Always Create More Clarity Over the past decade, businesses have invested heavily in visibility, and that's a good thing. We can understand performance with a level of detail that would have been unimaginable not long ago. But there's an unintended consequence. The easier something becomes to measure, the easier it is to assume it must be important. Website traffic goes up, so that looks positive. Leads increase, so marketing appears to be working. Sales activity climbs, so the pipeline looks healthy. Maybe. The numbers tell us what happened. Understanding why it happened, whether it matters, and what we should do next still requires judgment. Not Everything That Matters Fits on a Dashboard Consider a customer who ultimately contacts your company through Google. The data may attribute that lead to search. What it may not show is that the customer heard about you from a colleague six months earlier, saw your company mentioned in an industry publication, followed one of your employees on LinkedIn, and read several reviews before finally searching for your company. Google may have produced the click. It didn't necessarily create the decision. This happens throughout a business. Some of the things that matter most are difficult to reduce to a single metric: Why your best customers stay Why talented employees choose your company Why a prospect trusts one provider over another Why one service is gaining momentum while another isn't Why the market perceives your business the way it does Data can help answer those questions, but it needs context. Better Decisions Start With Better Questions One of the easiest traps for leaders is starting with the information in front of them rather than the decision they're trying to make. Instead of opening a dashboard and asking, "What does the data show?" it can be more useful to start with a different set of questions: What are we trying to understand? What decision are we trying to make? What would we need to know to make that decision confidently? That changes the role of data. Instead of looking at every number available and searching for meaning, you're using information to understand something specific about the business. Information Still Requires Judgment More sophisticated analytics and AI will continue to give leaders access to better information, faster. That's valuable, but I don't think it reduces the importance of experience and judgment. If anything, it increases it. Someone still has to decide which numbers deserve attention, which patterns matter, what context might be missing, and when the data isn't telling the whole story. The goal isn't to know more about your business simply because you can. It's to understand your business well enough to make better decisions. Good data can tell you what happened. Good leadership has to decide what it means. — Learn more about how we help organizations turn business, customer, and marketing insights into smarter strategies at tayloegray.com, or reach out directly at nathan@tayloegray.com.
BUSINESS UPDATE: A 138-year-old New York Manufacturer Gets Another Life in Fulton
E.J. Willis Co. was founded in New York City in 1888 and for generations it has made ship’s bells and other equipment for the U.S. Navy and American shipbuilders. This summer, the new owner moved the company’s equipment to Fulton By Stefan Yablonski E. J. Willis Co. cast brass ship’s bells — handcrafted in the United States since 1888. Ship bells, “built to last a lifetime at sea,” are now manufactured in Fulton. E.J. Willis Co. has moved its operation and manufacturing business to Fulton. They are currently operating out of N.E.T & Die. The company is now under the ownership of Jonathan Hyatt. He recently acquired the company after seeing a for sale note on Craigslist. [caption id=attachment_11110 align=alignright width=400] Entrepreneur Jonathan Hyatt is the new owner of E.J. Willis Co. He bought the business this summer after finding a listing on Craigslist by chance.[/caption] “I had been looking for something to do. I had been 20 years in corporate America and I was just tired of building someone else’s empire, you know what I mean? I was in consulting, pretty much a jack of all trades. I wanted to do something that I could call my own,” he explained. “I’d been on this path of trying to find a business to buy for about a year. One night I am on Craigslist about 11:30 in mid-April searching for something completely unrelated. At the bottom of Craigslist was a ‘things you might be interested in from outside of your area.’ There was an ad that said 138-year-old bell manufacturing company for sale. So, I clicked; why not, right? I wasn’t looking to buy a manufacturing company, but I went down the rabbit hole, absolutely fell in love with the history and ended up buying it.” He read the ad and responded. “I called and I am talking to the owner of the business for about two hours. We ended with, let’s have another chat and then come on out here and have a look. I figured, well I might wind up getting kidnapped and getting murdered or there is a real business here. But I gotta see it through,” he quipped. “And sure enough, there is a big machine shop operation there. The gentleman who owned it was retiring and in the corner of this shop is a little room where they make bells and they have been doing this ever since the company had started.” That’s the one constant thing that has survived the changes of the business. [caption id=attachment_11061 align=alignright width=300] Sales 1929 general catalog published by E. J. Willis Co, listing all the merchandise it sold. It’s like the Sears Roebuck and Co. catalog for marine parts.[/caption] “I drove home and told my wife, ‘This is what I am doing for the rest of whatever we are calling this — mid-life crisis.’ And she said, ‘absolutely you got to do it.’ I took out a loan and off we go.” He put in an offer on the business and they closed on July 1. He didn’t disclose what he paid for the company. “In terms of price, the seller and I have agreed to keep those terms private.” “I am finding that I am a business owner, an archeologist, opening files and cabinets that haven’t been opened in 100 years. It’s just amazing, just cool things that I am finding,” he said. “I want to build the business back. I want to be able to sell the bells to outsiders. I think they are beautiful. “It’s really a wild story about a company that started in lower Manhattan, exploded in the automotive space, sold parts to the Wright Brothers, moved into the aeronautical world and then landed in marine. The cool thing, I have been digging around and the gentleman who owned the company prior to me was not a digital guy. There is nothing out there. “Now I am sitting here with all the art from like the 1930s, the E.J. Willis boat catalog it’s like 250 pages of things this company used to make. It’s like the Sears-Roebuck and Co. catalog for marine parts. We are modernizing, we are staying true to the heritage of the business. It’s exciting to be the next steward of the whole business.” Initially he thought he’d move everything from the company’s plant in Middleville, Herkimer County, to Boston, out of convenience. “Then I thought let’s keep the foundry where it is. Let’s not move anything right away,” he said. “I want to get a good sense of what we’ve got, what works and what doesn’t. “I went to the foundry and met with the people there, lovely people, and said here is my position — I am buying a company where everyone is retiring. There is machining and polishing to be done, who would you work with around here? Without hesitation they said, ‘you need to go to NET Tool & Die and talk to Michelle [Shatrau]. She is a third-generation machinist and she runs the company now.’” So, he drove to Fulton. “I knocked on the door, they let me in. And she said, ‘how’d you get in here?’” he said with a laugh. “We became fast friends. I told her what I am doing. It must have struck a nerve. She has a very entrepreneurial background. I must have said something right because she came out and she said, ‘I’d love to help you. Why don’t we move the equipment that you have into my large building and I will give you a space to work at and use my team?’” [caption id=attachment_11058 align=alignleft width=300] Bell in progress awaiting assembly[/caption] It’s a great relationship so far. “We are bringing the business into the modern world. It’s been a lot of stuff all at once. But it has been very exciting,” he said. “We moved in a month ago [in July]. We closed on the business July 1. We moved a couple weeks later. We had all our equipment set up, electrical being run, everything. [caption id=attachment_11059 align=alignright width=300] Bell attached to a lathe going through the machining process[/caption] “We’re working with NET Tool & Die to rebuild production and preserve manufacturing processes that, in some cases, existed mostly in the heads and hands of the people who had been doing them for decades. We’re currently working on several 200-pound ship’s bells and bringing an old two-way manual bilge pump back into production.” He said he will be working with NET employees for the time being, adding, “I’d love to get to a point where I have so much growth that I need to hire people.” No one wakes up and says, ‘I am buying a bell today,’ Hyatt admitted. [caption id=attachment_11060 align=alignleft width=225] Bell after receiving a custom etching toward the bell mouth[/caption] “Everyone does wake up and has things that deserve acknowledgment and remembering — a promotion, a marriage, the birth of a child,” he said. “These are the things I feel like if there was something that could capture a particular moment in time and will literally outlast the person that bought it, a bell is that. We can engrave a bell if you get married or the birth of a child. We can put anything on a bell. “I have orders, yes. I am working on several orders right now. We have a little bit of busyness. But there are still some things to work out. I want to make things consistently and continue to move forward.”
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Studying Science in an Anti-Scientific Time
This Chronicle Review Deep Cut was first published in 2025. By Julianne Werlin Thanks for reading The Chronicle Review! Subscribe for free to receive new posts and support my work. Subscribe The last two decades have not been kind to science studies. Already bruised and battered by the “science wars” of the 1990s, by the 2000s sociologists of science — who had long argued that science had to be understood in its human context — were encountering the funhouse-mirror version of their own views in right-wing critiques of climate scientists. It was enough to give some prominent scholars pause. “Was I wrong to participate in the invention of this field known as science studies?” asked Bruno Latour, the most famous sociologist of science in the world, in 2003. “Should we apologize for having been wrong all along? Or should we rather bring the sword of criticism to criticism itself and do a bit of soul-searching here: What were we really after when we were so intent on showing the social construction of scientific facts?” In response, Latour proposed a change of method and attitude. Science studies, now chastened and contrite, would no longer seek to strip facts of their authority, but to enrich and enhance them. What this meant in practice was never fully clear. But his diagnosis of problems resonated, even if his solutions did not. Latour’s exercise in public hand-wringing signaled a shift in mood. By 2016, with the first election of Donald Trump, the idea that skepticism of science was a right-wing position, not a left-wing one, had become a commonplace, discussed eagerly in The New York Times. For liberals, vaccine denial during the Covid era and Trump’s second-term attacks on the funding of scientific research, covered extensively in these pages, added a new urgency to the defense of science on both practical and principled grounds. There was little appetite for a sociology or philosophy of science that emphasized the messiness and missteps of the scientific process rather than its integrity and triumphs. The distinguished historian of science Peter Dear’s new book, The World as We Know It: From Natural Philosophy to Modern Science (Princeton University Press, 2025), which seeks to tell the story of 18th- and 19th-century science for a general public, may seem comfortably remote from these bitter contests. In its 16 short chapters, Dear draws swift, sure sketches of major discoveries from Newton to Einstein, ably guiding the reader through debates on stellar nebulae, animal taxonomy, atomic chemistry, evolution, and other flashpoints in the history of science. But though a work of history, Dear’s book must still negotiate our polarized present. In a blurb on its back cover, the historian of biology Lynn K. Nyhart alludes to the “present moment, when scientific knowledge is being swamped by misinformation and its institutions are under siege.” Dear himself, in his conclusion, refers to the “yard signs” and “bumper stickers” that proclaim “Science Is Real.” One antidote to both anti-science propaganda and to reductive slogans in science’s defense is a robust history and philosophy of science: exactly what Dear’s scholarship has long offered. But his new book illustrates how difficult such work has become. Dear, an emeritus professor of history at Cornell University, is best known as a creative and philosophically minded historian of the Scientific Revolution. His edited volume The Literary Structure of Scientific Argument (1991) analyzed the rhetoric of Galileo’s thought experiments to brilliant effect. Discipline and Experience: The Mathematical Way in the Scientific Revolution (1995) was a major contribution to the analysis of scientific experiments in early modern Europe and beyond, while Revolutionizing the Sciences: European Knowledge in Transition, 1500-1700 (2001), now in its third edition, remains one of the best overviews of the profound epistemological upheavals of 16th- and 17th-century science. But Dear has also ventured into later periods. Nearly two decades ago, in The Intelligibility of Nature: How Science Makes Sense of the World (2006), he turned to the 18th and 19th centuries to sketch a history and theory of scientific knowledge. Aimed at a generalist audience, Dear’s simple prose belied serious philosophical ambitions. Science, Dear argued, has two aspects: “natural philosophy,” the quest to understand the true nature of the universe, and “instrumentality,” the applied skills and technologies that allow us to manipulate the world for human advantage. Both strands are ancient, but the innovation of the phenomenon we call “science” was to yoke them together. As Francis Bacon wrote, “Human knowledge and human power meet in one; for where the cause is not known, the effect cannot be produced,” an insight typically abridged to “knowledge is power.” Or, in Bertrand Russell’s characteristically blunt phrase, science has two functions, “1. to enable us to know things, and 2., to enable us to do things.” So far, so conventional. But Dear took issue with this familiar story in one respect. Bacon’s formula implied that theory and practice could be fused in a single method. In fact, Dear argued, the quest to understand nature and the desire to manipulate it were coupled only loosely. They could come together, but they could also pull apart. Focusing on natural philosophy, the “knowing” half of the scientific circle, he used a series of case studies from cosmology, taxonomy, chemistry, electromagnetism, and quantum theory to show how theories changed over time, in dialogue with practice, but never reducible to it. Take the case of matter, the basic substrate of the physical world. In the 18th and 19th centuries, scientists not only disagreed about what it was, but also about how well it could be known. In 1789, the chemist Antoine Lavoisier dismissed speculation about the atomic composition of chemicals as “discussions entirely of a metaphysical nature,” as he sought to orient chemistry away from philosophical abstraction and toward laboratory results. But in the 19th century, atoms returned with a vengeance in the atomic chemistry of John Dalton, who wanted to explain the underlying structure of nature. It was not just that Dalton and Lavoisier had a different set of experimental results, or even a different theory, Dear showed. What counted as an explanation had changed. In arguing that scientific theories depended on their intelligibility to human beings with complex arrays of beliefs and commitments, Dear was in sympathy with science studies. Key figures such as the sociologist Steven Shapin emphasized the importance of psychological mechanisms like trust in the formation and acceptance of scientific ideas. But in focusing on the scientific pursuit of knowledge, not its politics or economics, Dear resisted the more cynical perspective of some of his colleagues. The Intelligibility of Nature strikes a very different note than Shapin’s collection of a few years later, Never Pure: Historical Studies of Science as If It Was Produced by People With Bodies, Situated in Time, Space, Culture, and Society, and Struggling for Credibility and Authority (2010), to name just one example. Walking a very fine line, Dear depicted science as driven at once by complex social dynamics and by the intellectual power of real discoveries. It was a testament not only to his own acumen but also to the vitality of the field that he was able to do so. Nearly two decades later, The World as We Know It returns to the questions broached in The Intelligibility of Nature. Like Dear’s earlier study, it begins with the Newtonian cosmos and ends with debates between Einstein and Bohr on quantum physics. Beyond its terminal figures, many of the same characters appear in both studies, including the naturalists John Ray and the Comte de Buffon; the chemists Étienne François Geoffroy, Antoine Lavoisier, and John Dalton; as well as Charles Darwin and Michael Faraday, among others. Its subject is nearly identical: As in The Intelligibility of Nature, The World as We Know It considers natural philosophy as opposed to instrumentality, here defined as the “desire to create a picture of what the world is really like — the world as God knows it — rather than simply having instrumental or operational control over it.” The two books also overlap in insights — and sometimes even in language. The reader who has learned in The Intelligibility of Nature that Buffon’s method of classifying animals “reflected his belief in the importance of the senses and empiricism in learning about nature (a doctrine associated with Newton and the philosopher John Locke)” will experience a sense of déjà vu on reading, in The World as We Know It, that the classification “reflects Buffon’s commitment to the epistemological stance of Newton and his philosophical underlaborer John Locke, who stressed the role of the senses in creating natural knowledge.” Later in the passage, we read that, “because of its stress on understanding the ways of life of animals in their environments, Buffon’s approach could almost be labeled (anachronistically) as ‘ecological.’” And again, “an anachronistic way of putting it would be to say that Buffon recommends an ecological mode of understanding.” Likewise, in The Intelligibility of Nature we read of Dalton that he was initially drawn to meteorology, and that: He did a bit of experimental work on these things, especially having to do with the water-holding capacity of gases, but his real interest lay in understanding what, at an underlying natural-philosophical level, was really going on physically.” Whereas, in The World as We Know It: He did experimental work on these things, especially concerning the water-holding capacity of gases — although not at a very refined level quantitatively — but he was continually trying to develop a theoretical conception of what was happening physically. The final full chapter of each book closes on the same resigned note. Intelligibility: These days, most serious work on the natural philosophical underpinnings and implications of quantum mechanics is performed not by physicists but by philosophers of science. Among scientific practitioners themselves, Bohr’s attempt to use instrumentality as sufficient grounds for a respectable science has met with a high degree of success. And again, in The World as We Know It: Bohr’s and Einstein’s concerns are now questions that are mostly discussed by philosophers of science rather than by physicists themselves. The marginalization of these sorts of questions amounts to the demise of natural philosophy, at least in physics, in the 20th century. Quantum mechanics “works,” and that’s good enough for most scientists who encounter it. Examples could be multiplied. When handling the same subject matter, some echoes are inevitable. Scholars should not feel that because they have written “Isaac Newton died in 1727” in one book, in the next they must describe him as perishing, expiring, or meeting his maker. But the repetitions of language and arguments (not to mention six reproduced images) threaded throughout The World as We Know It are more extensive than that. They should have been caught by Princeton University Press or its reviewers, and revised. Because the two books have so much in common, it is easy to see where they diverge. The World as We Know It is a less theoretical work than its predecessor. The sociology of knowledge that organized The Intelligibility of Nature has been reduced in scale and folded into readings and examples. The taut interplay between history and theory, which gave the earlier study so much interest, is there, but it is subtle. In the earlier book, the case studies demonstrated theoretical claims about the character and development of science. In the later work, each narrative of discovery is an end in itself. Insights emerge from the history, but they do not control the organization of the study. With the theory muted, it can be hard to understand the logic uniting Dear’s sprawling history of more than two centuries of scientific knowledge. The 16 brisk chapters cover an enormous amount of material. But the closer the volume edges to comprehensiveness, the more obvious the missing elements become. A chapter on “Institutions and Pedagogy,” describing the birth of the research university, illustrates the problem. Inserted roughly halfway through the book, the unnumbered chapter is designed as an “entr’acte,” in acknowledgement that it does not fit the study’s organization around scientific discoveries. Yet as Dear is well aware, no general history of the development of modern science can bracket its 19th-century institutionalization and professionalization. It was the 19th-century university, after all, that gave us the “scientist,” a term coined by the Cambridge philosopher William Whewell. Dear’s history of scientific discoveries implies a wider social and institutional history, but it remains largely subterranean, only occasionally extruded under the pressure of the narrative. It must be said that the balance is not all on the side of the earlier study. There are some advantages to the more historical, less theoretical organization of The World as We Know It. Dear’s accounts of paradigm shifts are remarkably lucid, no small accomplishment given that they span fields and centuries. He makes excellent use of the wealth of new scholarship on Darwin and his influences, to which he has himself contributed. It is satisfying to see puzzle pieces from Buffon’s natural history, Georges Cuvier’s animal taxonomy, Thomas Robert Malthus’s demography, and Charles Lyell’s geology recombined seamlessly in the Darwinian jigsaw. Likewise, Dear’s discussion of stellar nebulae, divided between chapters two and 15, shows vividly how Newton, Kant, Herschel, and Hubble reimagined insights and observations as they sought to discover whether the diffuse light that filtered through early telescopes was a glowing, gaseous substance or discrete but distant stars. Yet despite such pleasures, the book remains a more modest work than The Intelligibility of Nature. Dear has clearly not changed his views about the history of science. But in the two decades that have elapsed, the discipline and the world around it have changed, making it harder to write a sociologically and philosophically ambitious history of science for the general reader. That is a shame, because in the age of Silicon Valley and biotechnology, both the reciprocity and the tensions Dear identified between the epistemological and instrumental ambitions of science are more evident than ever. In recent years, some of the most exciting new books on the history of science in early modernity have focused precisely on this pressure point. Important studies such as Pamela H. Smith’s From Lived Experience to the Written Word (2022), James Poskett’s Horizons: The Global Origins of Modern Science (2022), and Vera Keller’s The Interlopers: Early Stuart Projects and the Undisciplining of Knowledge (2023) all shed new light on how early modern science negotiated the relationship between its instrumental and epistemological ambitions, or in Russell’s phrase, knowing and doing. There is every opportunity for a philosophically informed approach to draw new insights from this wealth of material. Dear, unfortunately, has not done so in The World as We Know It. But for future scholars of the history of science, his body of work over nearly four decades may provide just the model. Julianne Werlin is an associate professor of English at Duke University. Thanks for reading The Chronicle Review! Subscribe for free to receive new posts and support my work. Subscribe
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Six games into VfB Stuttgart's 2026/27 season, captain Deniz Undav is still searching for his first goal.Saturday's 0-1 defeat to Borussia Dortmund also proved unsuccessful for the striker, who was ta...
Marc Guiu’s Leipzig Start Interrupted By Hamstring Injury
The Spanish striker’s Bundesliga breakthrough stalls following a training ground setback, leaving RB Leipzig’s depleted frontline searching for solutions as the promising youngster begins his recovery.
Harrison Running Out of Time to Earn Brewers Postseason Role
Deteriorating movement on his fastball and recent struggles have pushed Kyle Harrison to the roster fringe, leaving the Milwaukee Brewers searching for mechanical fixes before the postseason begins.
Mike McDaniel plans to get underutilized weapon more involved
The Los Angeles Chargers are searching for answers following their disappointing Week 1 loss to the Arizona Cardinals. They especially struggled on offense, failing to score on eight of their 10 drives. When wide receiver Ladd McConkey exited the game with a rib injury, other Chargers offensive weapons failed to step up. However, one was […] The post Mike McDaniel plans to get underutilized weapon more involved appeared first on HEAVY.
UFC 331: Muhammad Mokaev vows to return to UFC after controversial release
Muhammad Mokaev tells BBC Sport that he is still searching for answers about why he was cut by the UFC in 2024 and dreams of returning to the organisation.
From Lake Erie’s Algae to Florida’s Coral Reefs, UToledo Senior Chases a Career in Marine Science
Environmental science major Emily Wagner turned a rejection into a return offer and a childhood aquarium visit into a summer researching coral reef restoration in the Florida Keys.
Will Netflix’s Latest Horror Film Save Its Summer? And Introducing a New Data Source...
(Welcome to my weekly streaming ratings report, the single best guide to what’s popular in streaming TV and what isn’t. I’m the Entertainment Strategy Guy, a former streaming executive who now analyzes business strategy in the entertainment industry. If you were forwarded this email, please subscribe to get these insights each week.) All month, I’ve been polling you, my readers, on how we think the summer’s biggest blockbusters will do when they eventually land on streaming, and I wanted to share the results. First up, how readers think The Odyssey will perform when it comes to Peacock... People are pretty bullish that The Odyssey will smash it for Peacock. I don’t know that it will have as much rewatchability as Wicked did for kids, but we’ll see. It is now Universal’s highest-grossing film of all time. One note: almost half of Christopher Nolan’s films weren’t available for streaming the week The Odyssey came to theaters, including some of his biggest films like Inception, Dunkirk, Tenet, Oppenheimer and Insomnia. If you did want to watch the others, Prime Video had Memento and The Dark Knight trilogy, HBO Max only had The Dark Knight trilogy (even though Warner Bros. produced most of Nolan’s films), Hulu had The Prestige and Interstellar, and Paramount+ had Interstellar. So you needed at least two streaming subscriptions to catch the rest. Warner Bros. whiffed right here. I know they have long term licensing deals, but they should have tried to get as many Nolan films on HBO Max for launch as possible. Here are the results for Spider-Man: Brand New Day: The audience is a bit more mixed on this one, with everyone agreeing Spider-Man will swing to a big opening, but not necessarily elite or best all time. On to this week’s issue. Netflix continues searching for a hit straight-to-streaming summer film and Lioness and Ted Lasso allow me to look at the difference between a “hit” and a ‘hit for them”. All that, plus new YA/teen melodramas on Prime Video and Netflix, the House of the Dragon finale, USA Network claims a big opening, more big NFL ratings, all the flops, bombs and misses, and a whole lot more. But we start with a fun new data announcement. Let’s dive right in! (Reminder: The streaming ratings report focuses on the U.S. market and compiles data from Nielsen’s weekly top ten viewership ranks, Luminate’s Top Ten Data, JustWatch and Reelgood interest data, Samba TV household viewership, company datecdotes, Netflix hours viewed data, Google Trends, and IMDb to determine the most popular content. While most data points are current, Nielsen’s data covers the weeks of August 3rd to August 9th, 2026. You can find a link to my terminology here.) Subscribe A New Data Source: Reelgood’s Data on Content Libraries Here’s a fun new treat for you. Reelgood—an online service and app that lets users track where shows or films are streaming—is providing data every month for the Streaming Ratings Report on the size of each streamer’s catalogue, along with the new shows and films for each streamer. Yay! Previously, I had pulled “new shows on streamers premiering on the first of the month”: While I liked that data cut, it was a big wonky since it didn’t show all of the new shows or movies that came to a streamer each month. Instead, I would have preferred something like this from Reelgood’s annual report: And now we have it! I’m going to feature Reelgood’s data monthly, showing both total catalogue size and new shows and films appearing on the charts. That’s going to make these two cool new charts. First, here’s the size of various streamers’ film catalogues… (By the way, Reelgood offered to make the charts for me, but I like doing that task by hand to understand the data better.) They also provided data back to last year. Here’s the number of films timeline: And here are the new films on each streamer for the month prior to Aug: As I get used to this data, I plan to keep tinkering with how I display it, but I’m excited to feature it monthly. Today, I’m sharing the film charts; next issue, I’m going to feature TV shows by streamer. Now, in full disclosure, Reelgood is a sponsor of this little-newsletter-that-could. But in my constant quest to figure out what streamer various shows and films are on, I was already a Reelgood user before this sponsorship. I go to their website all the time, and their data is very accurate on where shows are (or have been). Plus, I’ve been sharing their weekly top ten lists for years now, pre-sponsorship. For me, this is a great win-win, since I get to amplify a service I love, and I get a cool new data source to play with. Now, normally folks don’t usually mention their sponsors directly, but as I wrote before, as I start featuring ads in my newsletter, I plan to be extremely open about who is sponsoring my writing so you can trust what I write. Television - Two Big Returning Shows Look Set to Take Over The Charts One key question when it comes to judging streaming shows is whether a show is a “hit” or a “hit for them”. To be clear, the former means a show that’s one of the top shows on streaming, no questions asked. The latter means a show is one of the biggest, for a given streamer. That distinction makes a big difference! It’s really good to be one of the biggest shows on a streamer; it’s much better to be the biggest on streaming, despite the size of a streamer. Because, as we’ve seen now, nearly every streamer—while lacking the number of subscribers or usage of Netflix—can make hit TV shows: Paramount released Landman, whose first and second seasons were among the top two TV shows the year they came out. HBO Max’s The Pitt’s second season is the biggest show of the year so far. Love Island USA was the top show in 2025 for Peacock. And, crucially for today’s discussion: Wayyyyyyyyyyyyyyyyyyyyyyyyyy back in 2023, Ted Lasso was actually the top streaming show of the year according to Nielsen! So even Apple TV (formerly +) can make hit shows. It just doesn’t make them that often. And looking at the Nielsen charts this week, we have two prime candidates for this discussion: That’s right: Ted Lasso returned to Apple TV for its fourth season. Did it return in all its expected glory? Sure, though right now it’s still just a “hit for Apple TV”, but we’ll see how long it lasts on the charts. Its ten episodes are coming out weekly. (Smart choice, Apple!) Ted Lasso started out strong, actually making the Nielsen charts the week before new episodes dropped, which is a rare feat. (Shows like Stranger Things or Bridgerton have pulled that off. That’s terrific company to join!) On Nielsen, it opened to 14.4 million hours in its first week, and 16.6 million the week of 10-Aug. Here’s how that compares to previous seasons: Apple put out that this is their biggest TV launch through two days ever, and looking at the chart and Apple TV’s viewership history, I’d believe it. Here’s Apple’s top shows for season two and beyond: Other data tells a (mostly) similar story. Ted Lasso made Samba TV and it has elite IMDb scores, an insane 8.7 on 465K reviews. The only outlier is Luminate, where the latest season only had 7.4 million hours, and no other seasons made the top ten. As you’ll see below, that’s well below some other solid, but not spectacular shows like Sterling Point, Ride or Die or Furious. I’d be surprised if Ted Lasso isn’t bigger than those other shows, but it’s fine for different data sources to occasionally disagree. And while it’s sucky to bring this up, given that Warner Bros. produced this show, I do wonder how the streaming wars may have been different if Ted Lasso landed on HBO Max initially instead of Apple. I don’t think one show can make or break a streamer, but given HBO’s brand, it could have helped bring people to that streamer much earlier in its lifespan. (Though yeah, I don’t love calling out executives for passing on hit shows, since that’s just the nature of the job. Even the absolute best execs will pass on lots of successful shows. The key is not greenlighting the under-performers/misses.) The other show I’m thinking about in the “hit or hit for them” category is Lioness from Paramount+. Like Ted Lasso, its first season missed the charts, but it’s grown its audience since then. Here’s how season three opened: We’re just getting started with this issue, but the rest is for paid subscribers of the Entertainment Strategy Guy, so if you’d like to find out… How Lioness did on streaming... Two new melodramas for Netflix and Prime Video... Whether Netflix’s latest horror film saved its summer... Hulu’s Furious and Prime Video’s Ride or Die continuing their strong runs... The latest high profile showrunner to flop on streaming... All the flops, bombs and misses... And a whole lot more... ...please subscribe! We can only keep doing this great work with your support. Next week, we’ve got a double issue—since the week of 17-Aug had very few notable new shows or films—so I’ll look at HBO’s Lanterns, Prime Video’s Reacher, Netflix’s Tires, Outer Banks (which posted up huge numbers four years ago), an Aussie romance, and another baseball event (that didn’t resonate). And a bunch of movies like the latest dramedy from an Adam Sandler daughter, Don’t Say Good Luck, Camp Rock 3 on Disney Channel and Disney+, Michael on Starz, and more. Later this month, we’ve got a ton of shows and films to analyze! Movies will be the big story, featuring a box office bomb (Supergirl on HBO Max) and an “underperformer” (The Mandalorian and Grogu on Disney+) contending with a bunch of star-studded straight-to-streaming films like Netflix’s The Whisper Man (Adam Scott, Michelle Monaghan and De Niro!), Mayday on Apple TV+ (Ryan Reynolds and Kenneth Branagh!), The Runner (Gal Gadot) and The Last Sunrise (Eva Longoria and Maia Reficco) on Prime Video. Plus, a ton of TV shows have sophomore seasons coming out. Will The Gentleman put up big numbers on Netflix or suffer from a sophomore slump? Leanne and Beauty in Black on Netflix seem small, but they both might be bigger than you think. Hulu has a bunch of shows: a new season of The Secret Lives of Mormon Wives (the first after all the controversy last year) and the second season of Chad Powers (from Peyton Manning’s production company and starring Glen Powell). This one flopped last year; can it score a touchdown this year? Same goes for FX’s Adults, which I didn’t track last year; will it hit this year? Peacock’s The Office spinoff, The Paper and Apple TV’s Dark Matter also return for second seasons. And Netflix has more Untold specials featuring Vince Young, Raygun (that horrible breakdancer) and Mr. T. Long term, Paramount+ is rebooting yet another franchise, Clueless, and I’m somewhat bullish on this new show. The talent attached (Alicia Silverstone) and creative Josh Schwartz and Stephanie Savage (of The O.C. and Gossip Girl) also feel solid...if they make it funny like the original.
TiVo launches Agent TiVo for AI entertainment discovery
Viewers could spend less time searching and more time watching as TiVo adds conversational AI search across fragmented TV and streaming catalogues.
Researching Animal Nutrition at Disney World: A Q&A with CALS Student Trinity Forbes
From childhood visits to an internship, animal science major Trinity Forbes has come full circle at Disney’s Animal Kingdom, where she spent the summer researching nutrition for elephants, rhinos, lions and other animals in the park's care.
“I did a lot of soul-searching [this offseason] and …
“I did a lot of soul-searching [this offseason] and …
Packers HC Matt LaFleur Admits Coaching Problem Against Vikings
A squandered fourth-quarter lead and Brian Flores’ relentless blitz packages extended Green Bay’s losing streak, leaving Matt LaFleur searching for answers as offensive line struggles mount.
Donor search: Watertown business leader searching for kidney donor
WATERTOWN – Dave Yelk is a familiar presence around the city. He’s a real estate agent for Realty Executives Platinum, with an office wall filled with dozens of glowing letters
Tottenham 0-0 Everton: Spurs’ Goalscoring Misery Continues
Tottenham Hotspur are still searching for their first Premier League win and goal of the season after Roberto De Zerbi’s team played out a frustrating 0-0 draw with Everton on Saturday afternoon.
Emery left searching for answers after another Villa loss
Aston Villa have lost three of their opening four Premier League games to leave boss Unai Emery struggling for answers.
Tottenham Hotspur vs Everton – Predicted lineup and team news
Tottenham Hotspur host Everton at the Tottenham Hotspur Stadium on Saturday still searching for their first Premier League win of the season. Roberto De Zerbi’s side sit 18th after collecting a sing...
Three Pressing Questions Bucks Will Have to Answer This Season
A new coach and an overhauled roster leave the Bucks searching for their identity in the first season after Giannis Antetokounmpo.
Tulane Looks to Not Define Season With Uncertainty at Quarterback
The Tulane Green Wave are still searching for their successor at quarterback and hope that they're right this weekend.
SETI Resurrects Decades-Old Concept: Searching Through The Lunar Soil For Signs Of Galactic Aliens
According to the paper, we may not be the only species to have left signs of technology on the Moon.
Do black holes have hidden hair? Scientists are searching
If black holes have extra matter around them – aka hidden hair – astronomers could find it by measuring the different characteristics of these ripples.
Indigenous fisherwoman finds ‘lost’ spinach pipefish, not seen by science in 40 years
Founder’s Briefs: An occasional series where Mongabay founder Rhett Ayers Butler shares analysis, perspectives and story summaries. On the final day of a two-week expedition, where researchers were searching for a “lost” species along Papua New Guinea’s Sepik River, Helen Asu arrived with two small, greenish-brown fish. She had caught them while fishing for prawns […]
Bournemouth vs Brentford: Team News, How to Watch & Prediction
Brentford head to the Vitality Stadium unbeaten in the Premier League, while Bournemouth are still searching for their first league victory under Marco Rose.
Rabies testing concerns prompt investigation from Minnesota health officials
The Minnesota Department of Health is searching for customers of a Twin Cities company that it suspects has not been consistently submitting rabies tests for testing.
Mysterious elk deaths in Nevada could offer clues about health of herds across the West
An unusual pattern of springtime elk deaths for more than a decade in northern Nevada has scientists searching for answers. What they find could shed light on broader questions about wildlife health across the West.
Mysterious elk deaths in Nevada could offer clues about health of herds across the West
An unusual pattern of springtime elk deaths for more than a decade in northern Nevada has scientists searching for answers. What they find could shed light on broader questions about wildlife health across the West.
Do De Zerbi's 'football manager' comments 'ring hollow'?
The Telegraph's Luke Edwards says Roberto de Zerbi's comments that "you can't just build the team with the names like in Football Manager" after his Tottenham side drew against Nottingham Forest on Saturday "ring a little bit hollow". After a goalless draw at the City Ground left Spurs still searching for a first win of the season, head coach De Zerbi also told Sky Sports Spurs "have to improve in every part of football, organisation with and without the ball".
Performance in Man City defeat 'a great starting point'
Coventry City defender Bobby Thomas says the performance in Saturday's 1-0 defeat at Manchester City is "a great starting point" for the Sky Blues to build on. Frank Lampard's newly promoted side delivered their best performance so far this season, after Premier League losses at Arsenal and at home to Hull City, but are still searching for their first point of the campaign. "We approached the game differently and had a better gameplan," Thomas told BBC CWR.
Can science explain what happens to us after we die?
A quantum physicist discusses the idea that quantum theory relates to consciousness and how it could exist independently of the brain.
Analysis: Emery's side lack cutting edge
Aston Villa arrived at MKM Stadium still searching for their first shot on target, goal and point of the season - against a defence who were yet to concede this season. Nicolas Jackson's movement caused problems for the Hull backline and Villa created enough openings while generating an expected goals (xG) of 1.74, compared to Hull's xG of 0.58. The striker's departure to Saudi Arabia's Al-Hilal in the final week of the transfer window was always going to leave a void and Villa continue to search for a new identity after the arrival of a host of new names.
Liverpool look for new sporting director after Richard Hughes formally leaves
Liverpool are searching for a fourth sporting director in four years after confirming the departure of Richard Hughes, who is set to join Al-Hilal
Dodgers Still Searching for Answers to Tucker’s Collapse
A $240 million investment faces a baffling crisis as Kyle Tucker’s struggles at home defy logic, leaving the Los Angeles Dodgers scrambling to fix their star.
Las Vegas police searching for suspect in east valley business robbery
Las Vegas police are looking for a suspect in a strong-arm robbery that happened in an east valley business last month.
Las Vegas police searching for suspect in east valley business robbery
Las Vegas police are looking for a suspect in a strong-arm robbery that happened in an east valley business last month.
Las Vegas police searching for suspect in east valley business robbery
Las Vegas police are looking for a suspect in a strong-arm robbery that happened in an east valley business last month.
Las Vegas police searching for suspect in east valley business robbery
Las Vegas police are looking for a suspect in a strong-arm robbery that happened in an east valley business last month.
Las Vegas police searching for suspect in east valley business robbery
Las Vegas police are looking for a suspect in a strong-arm robbery that happened in an east valley business last month.
Las Vegas police searching for suspect in east valley business robbery
Las Vegas police are looking for a suspect in a strong-arm robbery that happened in an east valley business last month.
Las Vegas police searching for suspect in east valley business robbery
Las Vegas police are looking for a suspect in a strong-arm robbery that happened in an east valley business last month.
Las Vegas police searching for suspect in east valley business robbery
Las Vegas police are looking for a suspect in a strong-arm robbery that happened in an east valley business last month.
Las Vegas police searching for suspect in east valley business robbery
Las Vegas police are looking for a suspect in a strong-arm robbery that happened in an east valley business last month.
Las Vegas police searching for suspect in east valley business robbery
Las Vegas police are looking for a suspect in a strong-arm robbery that happened in an east valley business last month.
Las Vegas police searching for suspect in east valley business robbery
Las Vegas police are looking for a suspect in a strong-arm robbery that happened in an east valley business last month.
Las Vegas police searching for suspect in east valley business robbery
Las Vegas police are looking for a suspect in a strong-arm robbery that happened in an east valley business last month.