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Google just got some bad news from ChatGPT

OpenAI's Adam Fry told Big Technology that ChatGPT has around a fifth of Google's search query volume. Google can't be thrilled about that.

Nov 3 • 3:45 PM EST • Business • businessinsider.com

OpenAI: ChatGPT Search Is About 20% of Google’s, 250 Million People Speak With ChatGPT, and Chat Is Merging With Work

OpenAI says ChatGPT growth is accelerating. The company added 200 million users over just the past two months, jumping from 1 billion to 1.2 billion weekly active users in 60 days. Its search volume, it says, is approximately 20% of Google’s. Its users create 1.5 billion images with it per week. And its voice mode, between dictation and speaking with ChatGPT, now has 250 million combined weekly active users. ChatGPT consumer product lead Adam Fry told me this during a brief fireside chat at an OpenAI-hosted dinner in New York City on Monday night. “The growth is just going big,” he said. During our conversation, Fry also revealed plans to merge ChatGPT’s Chat and Work modes (so that confusing toggle up top will soon go away), agreed with feedback that ChatGPT-created restaurant signage looks too uniform, and addressed the cost to serve its personal assistant Dots. Here’s a look at our full conversation, lightly edited for clarity and length. We also cover image generation, interactive interfaces, advertising, education, and public unease about AI: Alex Kantrowitz: OpenAI has analyzed ChatGPT’s search volume and compared it with Google’s. What did you find? Adam Fry: ChatGPT has been growing quite quickly. ChatGPT’s volume of search-like queries is now roughly one-fifth the volume of queries of Google. It’s a pretty amazing statistic when you think about it, mainly because we started just about a year and a half ago. It’s hard to remember this, but ChatGPT at a time didn’t have any up-to-date information. You’d ask a question, it would say something like, “It’s past my training date,” and nobody had any idea what that meant. You’re saying ChatGPT’s search volume is one-fifth of Google’s. Bing’s share of the search market is around 5%. Does that make you multiple times larger than Bing? To say that more directly, ChatGPT has gone from one billion to 1.2 in just the last two months. That’s roughly 100 million users in 30 days, and another 100 million in another 30 days. The growth is just going big, and we’re staying very focused on how fast ChatGPT is growing. What counts as a search? I might have 20 prompts back and forth in a ChatGPT conversation. Does each one count as a query? Story continues below… A MESSAGE FROM OUR SPONSOR Move upmarket without a rebuild Moving upmarket means saying yes to what enterprise buyers ask for first: SSO, directory sync, and audit logs. WorkOS gives you all three, so your team keeps building the product instead of the checklist. Get enterprise-ready. Continued from above…. Adam Fry: What people came to ChatGPT for to start, if you go back about two years, is really writing help and coding help. Those wouldn’t be things that you really search for. What we’ve seen over the last year is people have grown into all these other topics. Things like you’re looking up a person or people or a place or a thing, and it requires up-to-date information. That’s a key element. Another big part is finance questions or health questions, where you really want to make sure it’s up-to-date information that’s quite factual, and we’ll do a web search for those questions. It’s basically anything that a user would have traditionally gone to a traditional search engine for, but is now deciding to go to ChatGPT for. Does each conversation with a search embedded count as one search, or does every question that requires a web search count? Every time you ask a question and go search the web, that’s a search. You used to work at Google. How would you say the nature of search is changing? One of the things that people really love about ChatGPT is this personalization and this understanding of the broader journey. If you look in the past, people would go for a Q&A box, and you’d ask a one-off question, like how tall is the Eiffel Tower. But there’s so much context in our lives around, “Maybe I’m taking a trip to Paris.” It’s actually helpful for ChatGPT to respond, “Here’s how tall the Eiffel Tower is, but I know you’re going on a trip to Paris.” It’s that ability for people to actually maintain context over time that has led them to start using ChatGPT in this way. You’ve also announced 250 million weekly active users of voice input, including dictation and conversations with voice mode. We are at 250 million weekly active users. What’s amazing about this is, if you look at those 250 million, what we’re seeing is it’s actually also incremental to the product. It’s no longer just a novelty. People aren’t just trying out voice. We’re seeing them use voice input day to day in their daily life, and it’s grown so quickly. Those 250 million users are using voice input, and that could just be a quick question or a long conversation. We’re seeing both behaviors. We’re seeing people just not want to type. You just hold it and start talking to it, or it turns into a longer conversation where people just sit with it. The big reason for this is the frontier capabilities of our models that we’ve shipped. We shipped what we call GPT Live 1, and then we shipped GPT Live 1.1. The big change with this is that it’s much more natural to speak with. It’s something we call backchanneling and interruptibility. Mhhhm… What you just did there is what the model does, because it’s really good at having a bidirectional conversation. That push to the frontier—we were the first to really release this at scale—has made it so much more natural for people to chat. That’s still only about 20% of the user base. From the outside, that looks small. Why is it exciting from the inside? It’s very exciting for a few reasons. We see from the data that when people start using voice, they stay around using voice. One of the things, transparently, we can do a better job of is bringing more people into discovering it. We see that the number of people who discover it could be a lot higher. But once they do, it’s a really new way for people to interact with AI. We’ve made a lot of improvements to it too, where we’re just going to see the number go up. You have background mode, so now by default, if you close the app, it’ll show, “Hey, the conversation’s still going.” If you want to walk around the house or you’re putting away the groceries, you can still have a chat. That kind of continuity has also changed how much people use it. Dots launched on September 29 and is about a month old. How’s it doing? It’s doing great. We talk to people about their Dot, and the first thing that everyone says is, “I love my Dot.” One of the reasons we’re seeing this is the proactivity, its ability to reach out to you and figure out things. The biggest use case I see all the time is, “Did I forget something today that I was supposed to do?” You can just say to your Dot, “Remind me of things at the end of the day that I may have forgotten. Somebody emailed me or messaged me,” and it’ll do that. This Dot changes the paradigm of the relationship with AI, where it’s actually helping you and giving you time back. You’re more conservative with permissions than some competitors. I tried to give my Dot my credit card, and it wouldn’t take it. With the creator of OpenClaw in-house, why are Dots’ permissions more limited? This is a space where we want to be very thoughtful and conservative because it’s a new space where you’re entrusting your Dot to take care of things on behalf of you that matter and are meaningful. We’ve just talked about how you go to this 1.2 billion user growth and asking questions. Now we’re asking people, “Can you ask ChatGPT or your Dot to help get things done?” But when you ask it to help get things done, it’s a whole new level of trust. We’ve built up a tremendous amount of trust in giving the right answers to your questions, and we want to make sure that when we build this new product, it has a high degree of trust. It’s a long game. We think this is going to be a new market for a very long time, and we want to make sure that we’re being this trusted player in the market to start. I initially thought Dots would be available on my $20 plan, then realized I had to spend $100 a month to get it. I upgraded, but I’d like to downgrade at some point…. We hope to keep earning your business and make the value good enough. It’s a really good point. ChatGPT’s goal more broadly, which I think is unique for us in the market, is we are focused on bringing intelligence to everyone safely across the entire world. For Dots in particular, there’s no difference. We don’t have anything to share tonight about the date of when Dots will go to a broader set of users. But you can rest assured we’re working very hard, and there are a couple things we have to get right. Over time we’re going to work on more efficient, agentic models that are able and capable of doing things for you. The first one is, right now we wanted to make sure that your Dot is actually really helpful. We started with some of our best models, but over time we’re going to work on more efficient, agentic models that are able and capable of doing things for you. The second thing is around proactivity. We’re still dialing in: How much do I message you to help you get things done? We can always play around with that to understand how much usage should a user use to have a successful Dot. We’re going to work on both, and our goal and ambition is to bring it out to all users. How much background computing does a Dot require? I’ve read estimates that serving a $100 subscriber might cost OpenAI $3,000 in compute, and mine seems to read every email that arrives. How often is it checking connected data sources? Right now, Dots are on the compute-heavier side, and this is one of the things we want to make sure that we can dial back over time. But the goal is to give you the best product. This is our premium, always-on personal assistant. Once we nail that, we’ll figure out how to dial back the compute needs. The thing we’re seeing also from our models, as we train frontier models, is just how—I can’t even keep up with how quickly we have a new model, and each new model is more efficient. If you looked at 6.1 Sol when it came out relative to Astra, much more efficient. I’m very excited about the next set of models we have coming too that’ll be even more efficient that we can use. Elon Musk said the cost of serving Grok Bot was unsustainably high relative to revenue. Is efficiency the key to winning against competitors, or is there more to it? There are a couple of factors that go into it. One is the cost side, but the other is the revenue side. On ChatGPT and on our consumer business, we’ve been extremely proud of our ability to diversify different revenue streams in a way that’s growing really fast. To give you another stat, we announced several months back that we had passed 50 million subscriptions, and the number has grown considerably since then. On ads, within 200 days, we reached more than a billion in ARR, and that business is growing extremely quickly. We also have credits. Rather than paying for subscriptions, users can buy more credits. Between credits, subscriptions, and ads, I’m confident that the value of a Dot is going to be able to pay for itself. Elon has subscriptions too. This is clearly an expensive product to serve. One thing we continue to bet on at OpenAI and ChatGPT more broadly is that the models will continue to get much better and much cheaper, way faster than any of us think. If you look back at the historicals on it, it continues to be true. From what I’ve seen, I see no slowing down of that. What is Meta doing right with Muse? It has spent a lot of time atop the App Store charts. There are a couple of things they’ve done well. The first is people have been craving simplicity in their products. One of the things we have stated publicly as well is, at times AI products can be too complex. We’ve announced we’re merging ChatGPT’s Chat and Work. We’re making it much more simple in the products. You don’t have as many toggles or sliders between efforts and different model pickers. One of the things they’ve done well is this simplicity. You just go in and you can ask a question. You don’t have to think too much about what you’re doing. That’s one thing that seems to have resonated with users, which we also believe in. Second, there’s something really nice about being able to access your agent across many different channels. We just announced and launched Dots on iMessage. Whether you talk to your Dot on email or iMessage or within the ChatGPT app, the ubiquity in getting your assistant out there is going to be key. Those are two things that, if I had to be nice to our competitors, I would say were two big ones. So Alexandr Wang’s meme-tweeting strategy isn’t something you’re going to emulate? I have a different tweeting style. ChatGPT still asks me to choose between Chat and Work, even though some people call this technology AGI. Will that distinction go away? Couldn’t agree more. We have to solve this. Asking users to choose — we’ve heard repeatedly from all of our users it’s too much to understand. When should you go to Chat? When should you go to Work? It’s solvable. There’s real research to solve to make sure the models can understand what your intent is. Are you asking for a fast, quick reply? Are you asking me to go do a long agentic task? We’re going to solve it, and the plan is to bring Chat and Work together. So one interface will work out whether I’m asking for a conversation or a task. When? Coming soon. You told me the majority of ChatGPT’s 1.2 billion users are using image functionality. What are they doing? Today, 1.5 billion images are created per week. It’s hard to even wrap my head around that number. They’re doing a wide range of things. One of the most interesting things they’ve started to do is really use it for productivity use cases. The first thing it started with—I don’t know if you saw the ’80s trend, but it was quite fun. You could take a photo of yourself and say, “Put me and my family in ’80s outfits.” I did this for my family, and it was a really fun poster. But what we’re also seeing is businesses for their menus, or posters for birthdays. People are using it almost in a productivity-like fashion to create visual diagrams of what they would like to see. We’ve actually brought the latency down on images as well, so it’s gotten a lot faster. It went from a very high number of seconds to getting much faster. As it comes down even further, the number of images people are creating and the number of use cases is going to grow a lot. My feature request: When a restaurant makes a menu or sign, prompt it for more specificity so it doesn’t look like every other AI-generated restaurant sign. Or offer a shuffle button for a different style. I agree with the feedback, and we’ll take it to the team. I’m seeing ChatGPT generate little interactive interfaces within its answers. What’s the direction for Intelligent UI, and how are people using it? I am extremely excited about Intelligent UI. If you go back a couple years, these chat apps were all text, and now that’s changing. They’re going to be visuals. Intelligent UI and our first attempt at this with GPT-6 Intelligent UI is really just the beginning. As you go to the extreme, what you can imagine is, let’s say you’re using voice mode, and you just say, “Show me how offside works.” Immediately it should show you a visual diagram, and you say, “No, I don’t quite understand it.” It should just repopulate. That’s where the future of this technology goes. It’s almost like you’re talking to a canvas that will update and change. People are finding it helpful for a lot of things. My favorite one is—it’s hard to admit that I had no idea how hearts work. The last biology course I took was in high school. I just asked it, “How does the heart work?” and it instantly gave me a beautiful interactive diagram of where blood flows and how it goes through. I’m really, really bullish on this for learning in particular. You’ve described useful applications in finance, health, and learning, and ChatGPT has 1.2 billion users. If people are getting so much value, why is public polling on AI so negative? The reality with AI is it is going to change the nature of how work gets done. For a lot of people, that is something that can feel scary at times, and we’ve all felt that. But I remain confident that when people actually use the product and they use AI, it very quickly changes how they perceive it. We’re at 1.2 billion, but there are still a lot of people who haven’t used it. The more people use it, get familiar with it, how it can actually help you in your life, it’s going to feel a lot less scary. Big Technology is a reader-supported publication. To receive new posts and support our work, please consider becoming a paid subscriber. Thanks!! Subscribe

Nov 3 • 10:00 AM EST • Technology • bigtechnology.com

From Detroit to Warsaw: Was NATO enlargement driven by US electoral politics?

In October 1996, Bill Clinton announced in Detroit his commitment to expanding NATO into Central and Eastern Europe. With its large Polish-American community, the city was no accidental choice. In this conversation with Marc López Plana, Yale political scientist Ian Shapiro explains to the editor and director of 'Agenda Pública' how US electoral calculations helped shape a decision that would transform European security.

Nov 2 • 11:50 PM EST • Politics • agendapublica.es

NASA's Swift Observatory Is About to Die. It's Not the First Time NASA Has Said Goodbye to a Robot.

NASA's Swift Observatory will burn up this week. And while the agency has a lot of experience losing beloved hardware, it never gets easier.

Nov 2 • 7:00 PM EST • Science • nationalgeographic.com

Claude the job candidate

AI tools like ChatGPT and Claude are transforming hiring in Virginia, complicating résumé authenticity and interview verification for recruiters.

Nov 1 • 11:51 PM EST • Business • virginiabusiness.com

Scientists May Have Found a 7th Type of Depression

A new study suggests that disrupted sleep and daily rhythms may help drive depression in some people, raising questions about whether treatments targeting the body's internal clock could help.

Oct 29 • 8:00 PM EDT • Science • nationalgeographic.com

Your Google Messages chats are getting a ChatGPT upgrade

OpenAI now lets you text your ChatGPT Dot via RCS, with proactive updates and seamless conversations. Here's how it works and who can use it.

Oct 29 • 1:59 AM EDT • Technology • androidauthority.com

OpenAI expanding ChatGPT dot access to iMessage and RCS

Well this is pretty cool. OpenAI is expanding ChatGPT dot access to iMessage and RCS. Before now, the proactive agent...

Oct 28 • 2:15 PM EDT • Technology • 9to5mac.com

Woman, 31, dies after ChatGPT convinced her it was a good idea to change medication dosage

Oct 28 • 11:25 AM EDT • Health • nypost.com

iCloud Mail and Calendar plugins now work with ChatGPT

Here’s a welcome change. OpenAI just announced iCloud Mail and Calendar plugin support for ChatGPT. That means you can connect...

Oct 27 • 2:20 PM EDT • Technology • 9to5mac.com

OpenAI announces 3 AI-generated discoveries in mathematics, computer science, physics

ChatGPT developer says AI models produced proofs addressing longstanding scientific problems, seeks independent academic scrutiny | Anadolu

Oct 27 • 1:13 PM EDT • Science • aa.com.tr

ChatGPT Keeps Telling People 404 Media Can Solve Their Tech Support Problems

Because big tech doesn't do customer service, we are being inundated with AI-generated emails begging us for help.

Oct 26 • 11:49 AM EDT • Technology • 404media.co

AI image generator test: Canva Craft vs. ChatGPT, Gemini, Meta Muse

While Canva's new image generation tool fell short at making a birthday card, it's catching up to more powerful models in creating realistic images.

Oct 24 • 4:11 AM EDT • Business • businessinsider.com

ChatGPT now lets you lock your chats

The company says the feature is designed for situations where users might be discussing something personal or planning a surprise and want to keep those conversations private when handing their device to friends or family to show them something in another chat.

Oct 20 • 2:36 PM EDT • Technology • techcrunch.com

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.

Oct 20 • 1:47 PM EDT • Technology • bigtechnology.com

South Brunswick BOE Approves High School Computer Science Research Study Involving ChatGPT

South Brunswick High School students will participate in research exploring how ChatGPT and AI tools can support computer science education.

Oct 19 • 11:00 AM EDT • Science • tapinto.net

Democratic Voices, Sunday: Science

Welcome to Democratic Voices, a series that features elected Democrats speaking out on Bluesky. Sundays I try to create some kind grouping other then by state. Today, Science. Sean Casten and Bill…

Oct 18 • 6:21 AM EDT • Science • dailykos.com

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.

Oct 16 • 10:32 AM EDT • Health • yourlocalepidemiologistca.substack.com

HOMETOWN ENTERTAINMENT: Comedian Brad Williams bringing his “Tall Tales Tour” to Roanoke

Brad Williams brings Tall Tales Tour to Roanoke this month.

Oct 16 • 9:00 AM EDT • Entertainment • wdbj7.com

ChatGPT Can Now Look At Your Chrome Tabs To Do Tasks For You

The ChatGPT browser extension lets you compare information from your open tabs.

Oct 16 • 6:06 AM EDT • Technology • engadget.com

ChatGPT can peek at your Chrome tabs now

Time to browse with an AI bot?

Oct 15 • 6:43 PM EDT • Technology • theverge.com

Is AI Leading to Declining Enrollment in Computer Science?

After years of seeing climbing enrollment in computer science, the Connecticut State Department of Education found enrollment going the other way every year since 2022, when ChatGPT was released to the public.

Oct 15 • 5:37 PM EDT • Science • govtech.com

Companies pledge free software and computing for AI in science

The European Commission has announced that a group of companies and foundations will offer free services, such as software or access to supercomputers, to European scientists using AI in their research.Unveiled on October 15 at a conference in Dublin, the initiative is the latest step by the Commission to try to help researchers use the technology. Scientists have used forms of AI, such as machine learning, for decades. But advances in deep learning in the past decade, and the wider interest in large language models since the release of ChatGPT in 2022, have spurred governments to invest in new AI tools that could help the scientific process.In July, the US announced it is spending $5 billion on the Genesis Mission, which it describes as a “national effort to harness AI for science,” funding 278 projects across areas such as autonomous labs or new AI tools in astronomy. The Commission has also identified AI in science as a priority, but the €107 million it pledged from Horizon Europe in 2025 does not come close to US spending levels. That said, the vast majority of public research spending in the EU comes from national funds. Today’s announcement at the European AI in Science Summit doesn’t commit any new public money. Instead, it launches the AI in Science Enablers Initiative, a set of voluntary contributions from companies and foundations. The idea is that the companies also benefit by getting access to scientific ecosystems, and feedback on how their tools work. Google, for example, has put up €3 million of cloud computing credits to European researchers. The Novo Nordisk Foundation intends to make its supercomputer, Gefion, available to European researchers, according to the Commission statement. The chipmaker Nvidia said it would provide access to tools, compute, training and collaborative projects.The publisher Elsevier also offered complementary licenses to some of its AI tools, plus AI training for PhD, postdoctoral and master’s students. The French AI firm Mistral will provide the European research community with access to its open-weight models, Vibe seats and application programming interface credits, according to the Commission’s statement. Vibe is one of the firm’s chatbot models. The idea is that more firms and foundations will come on board in the future as the initiative grows.

Oct 15 • 8:00 AM EDT • Science • sciencebusiness.net

Fall is full of ways to connect with nature, get creative, and recharge at Trailside Nature & Science Center

The Union County Board of County Commissioners invites residents to explore a variety of upcoming programs, including sound bowl meditation, acrylic painting workshops, forest bathing and tea cerem…

Oct 14 • 11:46 AM EDT • Science • ucnj.org

Rice University | Scientists engineer new tool to improve detection of HIV and other viruses

New enzyme optimized for RNA detection assays.

Oct 13 • 8:20 PM EDT • Science • eatg.org

The 6 Best Science Fantasy Books Released Since 2010, Ranked

From The Fifth Season to Gideon the Ninth, these science fantasy novels fuse magic, technology, and unforgettable ideas.

Oct 13 • 5:55 PM EDT • Science • collider.com

AI behaves more like a brain than a database – cognitive science’s role in its origin story helps explain why

When people think about what ChatGPT or other large language models are doing behind the scenes, it’s common to reach for the language of computing. You might assume there is

Oct 12 • 8:15 PM EDT • Science • insightnews.com

Think Global Health | Ukraine keeps HIV response steady under fire

War has strained Ukraine's HIV programs, but capacity built years earlier has kept most prevention and treatment in place.

Oct 11 • 8:30 PM EDT • Health • eatg.org

These execs think voice AI hasn't reached its ChatGPT moment yet

Voice AI's often misses important points for its context layer, and causes the whole pipeline to break

Oct 11 • 10:00 AM EDT • Technology • techcrunch.com

How parenting expert Emily Oster says teens should be using AI

Emily Oster, the founder of ParentData, shared her tips to parents navigating their kids using AI tools like ChatGPT for Teens.

Oct 11 • 5:26 AM EDT • Business • businessinsider.com

Delegate work to ChatGPT agent

Watch a ChatGPT agent demo showing how it can research, code, and take action online to complete a business plan in minutes.

Oct 9 • 2:27 PM EDT • Business • openai.com

Health Policy Watch | US finally signs health deal with Zambia, but still pursues minerals agreement

In 2024, 84% of Zambia’s HIV programme was funded by PEPFAR – and 1.3 million Zambians are on antiretroviral medicines.

Oct 8 • 7:55 PM EDT • Health • eatg.org

ChatGPT for Teens Failed to Alert Parents During Mental Health Crises

OpenAI disputes the findings.

Oct 8 • 12:30 PM EDT • Health • extremetech.com

The Math Singularity Is Here, and Science May Be Next

OpenAI has released an extraordinary body of mathematical work produced by an unreleased frontier model: 722 manuscripts spanning 372 research families across fields including number theory, complexity theory, and mathematical physics. Each result required, on average, the equivalent of roughly three hours of ChatGPT Pro reasoning. A New Era of Discovery We may be witnessing the beginnings of a “math singularity”: a point at which machine-generated discovery accelerates beyond humanity’s ability to independently reproduce, verify, or fully absorb it. If frontier models can generate hundreds of meaningful results in the time it takes a human researcher to investigate one, the constraint will no longer be producing new mathematics. It will be our capacity to validate, interpret, and integrate it. This does not make mathematicians obsolete. It changes their role. They may increasingly serve as guides, critics, and meaning-makers. Increasingly, they will decide which questions matter, determining which results can be trusted, and explaining why they are important. Mathematical insight may become abundant, while human judgment becomes more valuable than ever. Mathematics May Be Only the Beginning Every scientific discipline could eventually experience a similar acceleration. AI systems could generate and test hypotheses, connect findings across specialized fields, and explore possibilities at a scale no human research community could match. In medicine, imagine models identifying overlooked disease mechanisms, designing drugs and clinical trials, personalizing treatments, or discovering cures in months rather than decades. In materials science, AI could help create better batteries and cleaner industrial processes. In climate science, it could accelerate advances in energy, forecasting, and carbon removal. In biology, it could uncover relationships hidden across enormous genomic and molecular datasets. The result would not simply be faster research. It could expand the frontier of what is scientifically possible. The New Bottleneck Scientific discovery, however, is not the same as scientific progress. A medical breakthrough must still survive laboratory testing, clinical trials, regulatory scrutiny, manufacturing constraints, and real-world deployment. As machine-generated ideas multiply, the bottleneck may shift from producing breakthroughs to validating them safely and translating them into practice. We may soon have more hypotheses than laboratories can test, more drugs than clinical trials can evaluate, and more mathematical results than experts can review. That imbalance will require better systems for automated verification, reproducible research, prioritization, peer review, and collaboration between AI and domain experts. The importance of OpenAI’s work is not merely the number of manuscripts produced. It offers a glimpse of a world in which intelligence can explore thousands of intellectual paths in parallel. If ideas cease to be scarce, humanity’s defining challenge will be deciding which are true, which matter, and how to turn them into progress. The math singularity is not the end of human inquiry. It is the beginning of a new kind—one in which machines expand the frontier of knowledge and humans decide where it should lead. Subscribe Share Leave a comment

Oct 8 • 4:22 AM EDT • Science • douglevin.substack.com

ChatGPT for Teens keeps teens talking, even during mental health crises

ChatGPT’s teen safeguards are meant to protect vulnerable users, but new testing found the chatbot continues encouraging engagement during crises and potentially encourages unhealthy relationships with the AI itself.

Oct 7 • 2:15 PM EDT • Health • techcrunch.com

OpenAI says teens use ChatGPT for under 15 minutes a day as worries over risks grow

Teens spend under 15 minutes a day on average on ChatGPT, while less than 2% of them interact with the chatbot for over three straight hours, OpenAI ​said, as technology companies face scrutiny over the risks AI chatbots pose to children.

Oct 7 • 12:00 PM EDT • Business • reuters.com

OpenAI enlists doctors to enhance ChatGPT's health advice

OpenAI enlisted over 260 global physicians to improve ChatGPT's health advice amidst legal challenges and a high-stakes healthcare push.

Oct 7 • 5:00 AM EDT • Health • businessinsider.com

CATIE | Canadian study links cardiovascular disease to declining brain health

As the population of people with HIV ages, researchers studied cognitive health changes; 46% of study participants were cognitively declining, with cardiovascular health playing a role.

Oct 6 • 9:17 PM EDT • Health • eatg.org

The London School of Economics and Political Science | New study finds major HIV service declines in Uganda and Zimbabwe after 2025 US aid cuts

The study is the first to measure what happened to HIV services after the US froze foreign aid and halted PEPFAR and USAID work in January 2025.

Oct 6 • 8:05 PM EDT • Science • eatg.org

Sporting KC Weekly Schedule: Oct. 7-10, 2026

Sporting Kansas City returns home to host the Portland Timbers at 7:30 p.m. CT on Saturday at Sporting Park as the club celebrates National Hispanic Heritage Month. Tickets are available on SeatGeek, including a special Latino Heritage Night ticket pack featuring an exclusive luchador mask/hat and a Corona or Coca-Cola

Oct 5 • 12:14 PM EDT • Sports • sportingkc.com

Integral Ad Science to Provide Brand Safety and Suitability Measurement in ChatGPT Ads

NEW YORK, October 05, 2026--As artificial intelligence rapidly reshapes digital advertising, marketers face a critical new challenge: ensuring brand safety and suitability within dynamic, generative AI-native environments. Without independent verification, advertising in conversational channels risks creating a blind spot for enterprise brands seeking reliable media quality standards.

Oct 5 • 7:00 AM EDT • Science • finance.yahoo.com

New AI Detector Spots Machine-Written Science Papers With 91.5% Accuracy

Researchers in Jordan have developed a hybrid deep learning detector that distinguishes human-written scientific text from output generated by ChatGPT, Gemini, and LLaMA-3 with 91.5 percent accuracy.

Oct 5 • 6:41 AM EDT • Science • bioengineer.org

There's a New 'Blue Zone'—And It Holds Clues to Women's Longevity

The idyllic village is one of the most "extraordinary" spots on the globe for making it to 100.

Oct 4 • 8:00 PM EDT • Health • nationalgeographic.com

Health Policy Watch | COVID-19 drops out of world’s top 10 causes of death for first time since pandemic began

The virus directly killed an estimated 0.9 million people in 2023, ranking 14th, as global life expectancy climbed back to near its pre-pandemic level.

Oct 3 • 6:30 PM EDT • Health • eatg.org

I changed one ChatGPT setting, and it stopped giving me generic advice

If you're tired of ChatGPT's safe, corporate buzzwords, changing one persistent profile setting permanently kills generic answers.

Oct 3 • 5:00 PM EDT • Technology • howtogeek.com

ChatGPT Health Wants You To Upload Your Medical Records — Cybersecurity Experts Are Begging You Not To Do That

Oct 3 • 7:00 AM EDT • Health • nz.news.yahoo.com

This new ChatGPT scam tricks you into installing malware - how to spot the trap

This authentic-looking scam starts with a sponsored Google link - and it's catching people off-guard.

Oct 2 • 2:18 PM EDT • Technology • zdnet.com

SeatGeek Launches TourIQ, Bringing Predictive Pricing Intelligence to Live Entertainment

NEW YORK, October 02, 2026--SeatGeek, the technology company that has put data at the center of the live event experience from day one, today announced the launch of TourIQ, a predictive intelligence product built for the people who book and price live shows. TourIQ tells a promoter or venue what a concert or third party event is worth at any building, for any artist, on any date, before a single ticket is sold, then generates a price for every seat in the house so the show opens with the right

Oct 2 • 9:00 AM EDT • Entertainment • finance.yahoo.com

A Flaw in ChatGPT’s Mac App Could Have Let Hackers Grab Sensitive Data

While the focus has been on AI agents’ hacking capabilities, a recently patched vulnerability in a ChatGPT app shows that AI software is itself an inviting—and vulnerable—target.

Oct 2 • 5:45 AM EDT • Technology • wired.com

ChatGPT can now virtually try on clothes for you

OpenAI is rolling out new shopping features for ChatGPT that let users virtually try on clothing and accessories using their own photos and save products they like to a Favorites library.

Oct 1 • 3:21 PM EDT • Technology • techcrunch.com

Global Health & WASH: October 2026 Funding Opportunities (26 new opportunities)

41 opportunities on the Global Health & WASH page this cycle, 26 of them new. The health money on this page is mostly research money, and much of it is aimed at people early in their careers. Funder after funder, from the TANGO2 Research Foundation’s Research Pathways grants to the South African Medical Research Council’s Early Investigators Programme to the National Ataxia Foundation and Alex’s Lemonade Stand Foundation, is funding early-career investigators and the institutions that host them, with a clear tilt toward researchers based in or from the Global South, from AMBSO in Uganda to Kenya’s CONNECT-VAX network to Ersilia’s AI Incubator for African drug discovery. The money is organized by disease as much as by need: narrow foundations, the Parkinson’s Foundation, NTAP for neurofibromatosis, the RUNX1 Research Program for an inherited blood disorder, each run their own grant, so the question for an applicant is less which health problem you work on than which foundation owns your disease. The largest European cheques go to consortia only, with the European Innovation Council putting up to EUR €4 million behind a single healthy-ageing project and UNITE up to EUR €1 million behind each cross-border digital health team. Water sits apart, almost entirely in applied utility research: the Water Research Foundation’s cluster of USD $250,000 to $500,000 projects, each built around a utility problem from sewer laterals to reuse treatment. And the biggest single pot is public: HRSA is renewing community health center service areas with awards of up to USD $10 million each. This post is for paid subscribers. This helps support the time and effort it takes to curate and organize these opportunities. Subscribe To keep this accessible to everyone who needs it, we’re happy to offer pay what you can rates. You can find more details here. Open Opportunities 2027 Building the Field of Health Advocacy Grant, Georgia Health Initiative. *New!* *Closing soon!* Georgia Health Initiative, a nonprofit private foundation focused on health equity, is opening its 2027 Building the Field of Health Advocacy Grant to strengthen the organizations that push for healthier systems across the state. The Initiative treats advocacy as infrastructure, backing one-year projects that range from urgent responses to shifting federal policy to longer arc campaigns on housing, behavioral health, care access, and food security. It wants coalitions that elevate community voice, apply an equity lens, and arrive ready to deploy concrete strategies, and it deliberately seeks variety in issues, communities, and organizational size. The optional webinar and required lobbying training signal a funder investing in a durable field, not one grant cycle. The strongest fits are Georgia nonprofits and public agencies ready to turn advocacy readiness into systems change. Geographies: United States. Who can apply: Tax-exempt 501(c)(3) public charities, state or local government agencies, or coalitions/collaboratives using a 501(c)(3) fiscal sponsor, that work in Georgia on behalf of Georgians and align with the mission, vision, and values of Georgia Health Initiative. Only one application per organization, though an organization may be listed as a partner or subcontractor on multiple applications. Funding amount: Organizations can apply for up to USD $80,000 per project; the Initiative anticipates investing a total of USD $1.36 million. Targeted Sectors / SDGs: Governance, Policy & Advocacy · SDG3; SDG10. Deadline: October 2, 2026. Learn more and apply here. TDD Research Pathways Grant, TANGO2 Research Foundation. *New!* *Closing soon!* The TANGO2 Research Foundation, working with a founding gift from Tango2UK, is opening its TDD Research Pathways Grant to fund early-career investigators anywhere in the world who study TANGO2 Deficiency Disorder. The foundation is using this money to seed pilot work and to build a research community around a rare disorder that few labs currently study. It wants to back emerging scientists, clinicians, and trainees who will stay with this field, not one-off projects, which is why it requires a committed mentor and real institutional support and asks each applicant for a plan for future contributions. The design rewards promise and persistence over track record. The strongest fits are students, residents, postdoctoral fellows, and new investigators ready to commit to TANGO2 research. Geographies: Global. Who can apply: Early-career investigators worldwide, including undergraduate, graduate, and medical trainees, postdoctoral fellows, residents, and clinical or research fellows. Early-career investigators must hold a PhD, MD, or equivalent doctoral degree and be within 10 years of that degree or within 5 years of initiating rare disease research, engaged in postdoctoral research at an academic institution, teaching hospital, or nonprofit research institute. Currently enrolled trainees and transitional PhD candidates beginning a postdoctoral appointment at a nonprofit institution by July 1, 2026 are also eligible. All applicants must identify a qualified mentor with relevant TDD or rare disease research experience and demonstrate institutional support. Funding amount: Up to USD $15,000. Targeted Sectors / SDGs: Innovation, Science & Technology. Deadline: October 2, 2026. Learn more and apply here. Call for Expression of Interest (EOI): AMBSO Impact Research Initiative, Africa Medical and Behavioral Sciences Organization (AMBSO). *Closing soon!* The Africa Medical and Behavioral Sciences Organization is inviting expressions of interest for its Impact Research Initiative, which funds early-stage pilot studies and proof of concept work on priority health challenges. AMBSO is a Ugandan research organization backing bold ideas that can grow into larger studies, and its tracks span antimicrobial resistance, epidemic preparedness, artificial intelligence for diagnostics, HIV prevention, climate and health, cancer, maternal and child health, and non-communicable diseases. The small award size and direct-cost-only rule point to a funder that wants evidence rather than overhead, and that favors projects able to attract follow-on money or use AMBSO’s own research infrastructure. Eligibility runs worldwide, welcoming researchers and institutions inside and outside Africa. The strongest fits are researchers with a feasible pilot that generates policy-ready evidence. Geographies: Global. Who can apply: Open worldwide to researchers, academic institutions, and research organizations whose work aligns with generating high-impact health evidence. Independent researchers are eligible if affiliated with an academic or research institution. Doctoral students are encouraged to apply as part of a research team led by a faculty Principal Investigator. Community-based organizations and other eligible entities may apply. Projects may be implemented inside or outside Uganda. Funding amount: Up to USD $10,000 per project, with no minimum funding threshold. Targeted Sectors / SDGs: SDG3. Deadline: October 2, 2026. Learn more and apply here. Entrepreneurs for Resilience 2027 (E4R27), Swiss Re Foundation. *Closing soon!* Swiss Re Foundation is opening the tenth edition of Entrepreneurs for Resilience, which backs healthcare social enterprises expanding affordable, quality primary care for low-income communities across low- and middle-income countries. The Foundation is using catalytic, blended funding plus multi-year advisory to take risk out of scaling, helping proven models reach more people sustainably rather than stay stuck at pilot size. It looks to back brick-and-click enterprises that pair physical care with digital tools and build affordability through savings, payments, or microinsurance, ideally integrated with public health systems. Requiring earned revenue, real customer scale, and gender-inclusive teams signals that this is growth capital for commercially serious ventures, not seed money. The strongest fits are established, revenue-generating healthcare enterprises ready to scale access for underserved populations. Geographies: Global. Who can apply: For-profit and hybrid healthcare social enterprises serving low-income and underserved populations in low- and middle-income countries, using combined physical and digital (brick-and-click) healthcare delivery models. Applicants must demonstrate measurable social impact, generate at least 50% of income through earned revenue, have been established no later than December 2023, already serve at least 50,000 people with potential to scale, and have at least 30% low-income customers. Preference for gender-inclusive enterprises with at least one female founder or at least 30% women in management. Funding amount: Pilot funding of up to USD $45,000 for the 6-8 shortlisted social enterprises; up to USD $1 million in blended funding (up to USD $600,000 unconditional plus up to USD $400,000 conditional) shared among 3-4 finalists over a two-year implementation period; total programme funding approximately USD $1.3 million. Targeted Sectors / SDGs: Innovation, Science & Technology · SDG3; SDG5. Deadline: October 4, 2026. Learn more and apply here. Horizon HealthTech 2026, IIITD Innovation & Incubation Center. *Closing soon!* IIITD Innovation and Incubation Center is opening Horizon HealthTech 2026, a nine-month MedTech incubation cohort run under the aegis of BIRAC EDGE for founders building medical devices, diagnostics, surgical and interventional tools, or remote monitoring. The center is backing teams that already hold a validated proof of concept and want to reach a tested prototype, pairing each founder with a named expert and clinical validation through a hospital partner. What they seek to back is Indian health technology that can survive real clinical scrutiny and regulatory review, not slideware. The structure, with lab access, CDSCO guidance, IP support, and investor connects, signals a program built to make startups ready for follow-on capital. The strongest fits are early-stage MedTech teams with defensible IP and a working path from bench to bedside. Geographies: India. Who can apply: Early-stage teams/startups with a validated idea/proof of concept (TRL 3 onwards) working on medical devices, diagnostics, surgical/interventional technologies, or remote monitoring, holding IP or with potential to generate IP. Funding amount: No cash award amount is stated on the official program page. Benefits are in-kind: prototyping lab and equipment access, clinical/hospital validation (Max Healthcare), expert mentorship, CDSCO regulatory guidance, IP filing support, workspace, cloud credits and tools, and investor connects. Run under the aegis of BIRAC EDGE and builds a path to follow-on Government/VC/Angel funding. Targeted Sectors / SDGs: Innovation, Science & Technology · SDG3; SDG9. Deadline: October 5, 2026. Learn more and apply here. OpenAI AI and Teen Development Research Grant Program, OpenAI. *New!* *Closing soon!* OpenAI is opening its AI and Teen Development Research Grant Program to fund independent studies of how generative AI shapes the lives of young people ages 13 to 17. OpenAI wants a stronger evidence base on how teens actually use these tools and what that use does to their social and emotional development, so that product teams, policymakers, and regulators can act on findings rather than assumptions. It seeks work on emotion regulation, relationships, belonging, and the safeguards that keep teens safer, welcoming interdisciplinary teams and any methodology. That it will fund research whose conclusions may not favor AI providers, and prioritizes studies touching ChatGPT, signals a genuine appetite for credible outside scrutiny. The strongest fits are research groups grounded in adolescent development, well-being, and AI safety. Geographies: Global. Who can apply: Researchers aged 18 or older who are affiliated with a research institution or organization, and/or have significant experience relevant to child or adolescent development, well-being, human-computer interaction, AI impacts, or a closely related field. Multiple institutions may collaborate. OpenAI is seeking to fund research rather than for-profit initiatives and will not prioritize for-profit organizations. Funding amount: Individual research grants up to USD $1 million, totaling up to USD $5 million; maximum 10% of each grant for overhead or indirect costs. Targeted Sectors / SDGs: Social Inclusion & Community Wellbeing; Innovation, Science & Technology. Deadline: October 6, 2026. Learn more and apply here.

Oct 1 • 6:29 AM EDT • Health • impactfunding.substack.com

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

Oct 1 • 4:36 AM EDT • Health • healthapiguy.substack.com

Viewpoint: Kennedy’s ‘bad science’: MAGA embrace bolsters HHS secretary’s influence and popularity

Pennsylvania has recorded four measles deaths this year — the state’s first in 35 years — yet the federal government’s official measles death count still

Oct 1 • 12:01 AM EDT • Science • geneticliteracyproject.org

New Guide, 'How Do I Get ChatGPT To Recommend My Business?', Strategy Revealed

Authority Acquisition's new guide explains how ChatGPT recommends businesses based on discoverable published content, not paid placement, and ou...

Sep 30 • 9:47 PM EDT • Business • markets.businessinsider.com

CHI Health Good Samaritan Warns Older Adults About Fall Risks as Autumn Arrives

Sep 30 • 7:35 AM EDT • Health • nebraska.tv

Viewpoint: After firing the entire National Science Board, Trump reshapes funding initiatives. Here’s the good and the bad.

The National Science Foundation is steering most of its money away from grants for individual researchers’ best ideas and toward the Trump

Sep 30 • 12:05 AM EDT • Science • geneticliteracyproject.org

ChatGPT maker wants to be the App Store for AI as safety concerns grow

OpenAI on Tuesday launched a less expensive artificial intelligence (AI) model and tools that run continuously, as it aims to reposition ChatGPT as an app store for AI. Other companies, such as Adobe, will be able to offer their software directly within ChatGPT, which is now used weekly by 1.2 billion people.– “Disappoint Wall Street” – As speculation swirls around when OpenAI might go public, Altman told reporters on Tuesday that the company was "investing more in safety, security, alignment,

Sep 29 • 9:38 PM EDT • Technology • finance.yahoo.com

OpenAI's latest features take direct aim at the app store model

OpenAI is building out the pieces of an alternative to the traditional app store model, turning ChatGPT into a place where software can be discovered and used by people and AI agents alike.

Sep 29 • 4:15 PM EDT • Technology • techcrunch.com

Trump unveils new site to simplify access to government services

America.gov for now functions like a chatbot comparable to ChatGPT or Claude, pointing users to official gov't websites.

Sep 29 • 2:21 PM EDT • Politics • aljazeera.com

OpenAI takes on Microsoft with the launch of what feels a whole lot like ChatGPT's own office suite

OpenAI's newly announced suite of office features puts it into mor direct competition with more traditional software companies.

Sep 29 • 1:45 PM EDT • Technology • techcrunch.com

ChatGPT's new plan costs $500 a month

OpenAI announced a $500 a month plan for ChatGPT. The company also downgraded the compute allowance of its $200 a month plan.

Sep 29 • 1:15 PM EDT • Business • businessinsider.com

ChatGPT Space Is A Shared Hub For Work Projects And Personal AI Agents

ChatGPT is coming to Slack and Microsoft Teams too.

Sep 29 • 1:15 PM EDT • Technology • engadget.com

OpenAI expands ChatGPT's plugins with app-like interfaces and automations

OpenAI is expanding ChatGPT plugins with dedicated sidebar homes, interactive panels, file viewers, improved discovery, and support for automations.

Sep 29 • 1:15 PM EDT • Technology • techcrunch.com

How real estate agents can build business without waiting on rates or inventory

Real estate agents can reduce hesitation by reactivating past clients, improving service standards and sharing consistent market guidance.

Sep 29 • 11:37 AM EDT • Business • housingwire.com

East Islip Students Take Science Class Into The Wild At Sunken Meadow

AP Environmental Science students got a hands-on look at the plants, animals and ecological role of Sunken Meadow's salt marsh.

Sep 29 • 11:34 AM EDT • Science • patch.com

ChatGPT ads are dominated by business software companies so far

ChatGPT ads skew heavily toward business software, and there are bright points for the business, according to a new report from the agency Graphite.

Sep 29 • 8:00 AM EDT • Business • businessinsider.com

Turning to AI for health answers may signal anxiety, depression among young adults

Young adults who use generative artificial intelligence to ask health-related questions are more likely to screen positive for clinically significant anxiety and depression than those who do not use AI ...

Sep 28 • 8:20 AM EDT • Health • medicalxpress.com

Current and future RFK Jr. aides criticize his science-rejectionist vaccine views

Health Secretary Robert F. Kennedy Jr. has spent years casting doubt on vaccines, but the people lined up to work for him keep saying the opposite. Since

Sep 28 • 12:05 AM EDT • Science • geneticliteracyproject.org

Small Business Tech News: Could One ChatGPT Prompt Help Earn You $100K?

Earning $100K may be possible with a single ChatGPT prompt. Also - HubSpot and Teams have new features and Meta's Muse is popular.

Sep 27 • 7:00 AM EDT • Business • forbes.com

AP | A data-sharing clause derailed US-Zimbabwe health talks. Now all funding ends this month

The US will end funding for Zimbabwe’s health programs at the end of September following the collapse of negotiations over a US-proposed deal.

Sep 25 • 6:45 PM EDT • Health • eatg.org

Dogs also prefer consonants: how our language shapes their brain

A new study examined how they develop a consonant-preference bias, mirroring humans. They are not the only ones: rats and ChatGPT copy certain forms of our language processing

Sep 25 • 12:43 PM EDT • Science • english.elpais.com

Cyber Threats Top Business Concerns Again as AI Reshapes Risk, Travelers Survey Shows

Businesses are boosting cyber defenses and insurance purchases even as artificial intelligence creates new vulnerabilities, according to The Travelers Companies' 2026 Travelers Risk Index.

Sep 25 • 8:30 AM EDT • Business • riskandinsurance.com

Some doctors can now use ChatGPT to search health records

OpenAI announced that ChatGPT integrated with of the largest providers of electronic medical records, Epic.

Sep 25 • 2:04 AM EDT • Health • wbur.org

Australian PM says OpenAI hacked government health website

A rogue OpenAI model bypassed safeguards during training and hacked an Australian government website, Prime Minister Anthony Albanese said as he admonished the ChatGPT creator over an "obviously unacceptable" ...

Sep 24 • 5:20 AM EDT • Health • techxplore.com

Australian PM says ChatGPT-maker’s AI hacked public health care site

Anthony Albanese said there was no evidence that any personal health information was stolen and criticized the AI company for the incident.

Sep 23 • 6:13 PM EDT • Health • washingtonpost.com

Gemini just got a big upgrade with new connected apps for work, creativity, and life

Google is bringing several new additions to Gemini's connected app ecosystem, including Peloton and SeatGeek.

Sep 23 • 3:16 PM EDT • Technology • androidauthority.com

OpenAI just upgraded ChatGPT Voice in three ways

Talking to ChatGPT is getting better in three ways starting today. OpenAI is rolling out a collection of improvements to...

Sep 23 • 1:24 PM EDT • Technology • 9to5mac.com

ChatGPT mobile app gets voice-based agentic features

Pro and Plus users will be able to use the Work tab on their phones

Sep 23 • 1:00 PM EDT • Technology • techcrunch.com

BizTrip AI Announces Connection With Claude and ChatGPT

Users will be able to manage travel without switching to separate app or website

Sep 23 • 8:55 AM EDT • Business • businesstravelexecutive.com

BizTrip AI Brings Business Travel Booking Directly Into Claude and ChatGPT

SAN FRANCISCO, September 23, 2026--BizTrip AI, makers of agentic AI for corporate travel management, today announced that its core trip-planning and booking experience is now available natively inside both Claude and ChatGPT. The integration uses the Model Context Protocol (MCP) — specifically MCP "apps," which support rich, interactive rendering directly in a chat conversation — allowing travelers to search, compare, and book business travel without switching to a separate app or website.

Sep 23 • 6:00 AM EDT • Business • finance.yahoo.com

Consumer Reports: Should you trust AI with your health questions?

More people are turning to ChatGPT and other AI tools for health questions. The answers are fast, and they often sound reassuring and trustworthy, but, as Consumer Reports says, they aren’t always accurate.

Sep 22 • 1:35 PM EDT • Health • kcra.com

ChatGPT writes weaker emails for women, new research shows

Johns Hopkins study reveals AI chatbots respond differently based on gender-coded language prompts, impacting workplace communication.

Sep 22 • 12:16 PM EDT • Technology • businessinsider.com

Jiang Feng: The Unravelling of German & European Politics

A state election in eastern Germany has become a revealing test of the changing political landscapes of Germany and Europe, writes Jiang Feng, Professor and Chairman of the Council of the Shanghai Academy of Global Governance and Area Studies (SAGGAS) at Shanghai International Studies University. His analysis follows the decisive victory of the Alternative for Germany (AfD) (which has been classified as right-wing extremist by German authorities)in the state of Saxony-Anhalt on 6 September, in which it finished far ahead of its mainstream rivals. Jiang previously served as Minister-Counsellor at the Chinese Embassy in Berlin. The following article was published on 8 September 2026 on huanqiu.com, the online platform of the Global Times. On 6 September, the results of the state election in Saxony-Anhalt, Germany, were announced. The Alternative for Germany (AfD), classified as far-right by German authorities, made history by becoming the largest party in the state parliament, winning 43.8 per cent of the vote — twice its share in the previous election. The Christian Democratic Union (CDU), which had governed the state continuously for 24 years, won just 17.2 per cent, its worst result ever in Saxony-Anhalt. On the night the results were announced, the atmosphere at the CDU gathering was unusually calm. There was neither shock nor argument, as if the defeat had long been expected. Several veteran party members who had spent years working in the state government said: “Defeat is not a bad thing. It is time to make changes.” This state election has not only upended Saxony-Anhalt’s political landscape, but also laid bare the deep tensions between Germany’s traditional party structure and model of governance, on the one hand, and an increasingly polarised society on the other. Its repercussions are already being felt at the federal level, making Saxony-Anhalt a useful case study of the broader trend towards political polarisation and realignment in Europe. Governing Difficulties after Electoral Victory The most immediate consequence of the election is a historic setback for the mainstream party order that took shape in post-war Germany. In Saxony-Anhalt, the AfD has leapt from a peripheral party to the largest political force in the state. Its electoral base has expanded beyond the traditional category of “marginal protest voters” to take on the characteristics of a cross-class coalition. The party has not only consolidated its support in rural areas, but also attracted many middle-class voters and even members of the social elite with stable jobs, their own homes, and substantial incomes. It has thus evolved from a “protest party” into one with the potential to govern. Despite its commanding lead in the vote, however, the AfD faces an institutional obstacle to governing the state: the mainstream parties’ long-standing “firewall” against it. Neither of the two potential routes to forming a government appears likely to break the current political deadlock. The first would be a coalition of establishment parties, led by the CDU and bringing together the Social Democratic Party (SPD), the Greens, the Left Party (Die Linke) and the Sahra Wagenknecht Alliance (BSW) in a cross-camp government. In terms of parliamentary arithmetic, such a coalition could prevent the AfD from forming a government and preserve the outward stability of the traditional political order. Yet these parties are fundamentally divided over key issues including immigration, the energy transition, economic management, and cultural and education policy. Coalition negotiations would therefore be extremely difficult, and even if a government could be formed, it would most likely prove short-lived. More importantly, an alliance of establishment parties aimed at keeping the largest party out of government would play directly into the AfD’s narrative that “political elites are suppressing public opinion”. It could deepen perceptions of political unfairness, further strengthening the AfD’s political capital, and creating a dynamic in which “the more it is suppressed, the more people vote for it”. Ulrich Siegmund, the AfD’s candidate for state premier, has said that if efforts to form a government fail because other parties refuse to cooperate, the AfD will push for a fresh election, which he believes could deliver the party an absolute majority of seats. This points to more intense political battles ahead. The second option would be a coalition between the AfD and the BSW. Together, the two parties would command a simple majority in parliament, making this, on paper, the quickest route to forming a government. The BSW is the only elected party that has not ruled out cooperation with the AfD, and the two parties share some common ground, including on policy towards Russia. There is therefore a degree of political basis for cooperation. Were such a coalition to materialise, Germany would see its first state government jointly formed by a party defined as far-right and one with a far-left background, creating what might be called a “bipolar anti-establishment alliance”. Such an outcome would fundamentally break with the ideological boundaries of post-war German party politics. It is worth noting that even if the AfD ultimately fails to enter the state government, its roughly 47 per cent share of parliamentary seats would give it a powerful blocking minority. Without its consent, major decisions requiring a two-thirds majority — including constitutional amendments, significant budgetary adjustments, and state-level institutional reforms — would be extremely difficult to pass. Therefore, whoever ultimately forms the government, the AfD will be an unavoidable force in Saxony-Anhalt politics, with a direct influence on the state’s legislative process. Systemic Failures in Germany’s Governance Model The Saxony-Anhalt election result reflects a systemic failure of Germany’s post-war mainstream-party model of governance to adapt to rapidly changing socioeconomic conditions. It stems from multiple, mutually reinforcing structural tensions and highlights the existing political system’s difficulty in adapting to “an increasingly polarised society First, collective anxiety has replaced individual material hardship as a central driver of political mobilisation. The rise of the AfD can no longer be explained simply by poverty or social marginalisation. Its increasingly cross-class electoral base suggests that what is driving voters towards the party is, above all, concern about the broader direction of society. This anxiety about the future of the political community goes beyond individual gains and losses. In political discourse, economic anxiety has become closely intertwined with immigration, while immigration and refugee issues are, in essence, questions of social fairness. This perception turns conflicts over the distribution of social resources into negative assessments of governing parties, providing a broad social basis for far-right political narratives. Second, regional disparities and East German identity have undermined the strategy of addressing eastern Germany’s structural challenges at the regional level. More than three decades after German reunification, eastern states such as Saxony-Anhalt have experienced periods of economic growth, but their underlying economic structures remain weak, and household incomes and wealth remain significantly below those in western Germany. At the same time, they continue to face population outflow, an ageing population, labour shortages, and other structural challenges. At a deeper level, historical experiences — including the collapse of the former East German economic system, mass unemployment during the transition, and the westward shift of decision-making power over major issues — have left some residents with a sense of being “second-class citizens” and of being excluded. For years, the German government treated the “syndrome” of reunification as a regional problem to be gradually addressed at the local level. That approach is becoming increasingly unsustainable, as regional development disparities emerge as a core structural factor shaping national politics. Third, the erosion of institutional trust is perhaps the most decisive factor. AfD supporters tend to distrust establishment institutions, including parliament, government, and the mainstream media. Their concerns about economic security, pensions, and social fairness are significantly greater than the social average. Increasingly, their support for the AfD reflects not an expectation that the existing system can be improved, but a search for an alternative to the current political order. Such a systemic deficit of trust will be extremely difficult for the traditional parties to repair in the short term. Fourth, a generational shift in political mobilisation has amplified political polarisation. Unlike traditional parties, which rely heavily on offline rallies and mainstream media coverage, the AfD has developed a social-media mobilisation strategy built around “raising an issue — identifying who is responsible — offering a simplified solution — building a shared identity”. It turns complex social tensions into concise political narratives, rapidly channelling public sentiment into political support. The contrast on the eve of the election was particularly telling. The establishment parties, together with trade unions and churches, organised an offline march attended by more than 10,000 people, but its reach was largely confined to those present and to traditional media coverage. The AfD held a much smaller indoor event, yet livestreaming on TikTok, YouTube, and other platforms, combined with the involvement of online influencers, gave it a reach and mobilising capacity far beyond that of the march. The contrast illustrates how the traditional parties’ methods of political mobilisation are increasingly struggling to keep pace with a political environment transformed by changes in media technology. A Microcosm of Structural Political Change in Europe The shockwaves from the Saxony-Anhalt election quickly travelled beyond the state to the federal level. Calls for political accountability followed immediately after the results were announced. The governing CDU and SPD are now under enormous pressure, while Chancellor Friedrich Merz and Vice Chancellor Lars Klingbeil face an unprecedented test. Political polarisation in Germany is no longer simply a regional phenomenon. The post-war model of multiparty government by establishment parties is breaking down and being reshaped. Viewed in a broader European context, the Saxony-Anhalt election is part of a continent-wide wave of party polarisation, mainstream-party decline, and rising right-wing forces. Far from an isolated phenomenon, it is a microcosm of the structural political changes unfolding across Europe. Weak economic growth, cultural tensions over immigration, and declining trust in institutions are fuelling the rise of right-wing forces in several countries, challenging the liberal internationalist order established in post-war Europe. As a core member state of the European Union, Germany’s ability to adapt its political system and the direction of its politics will have profound implications for both European integration and the evolution of the international order. Subscribe [ Pekingnology China’s Germany watchers take stock of Berlin’s uneasy turn On 7 December 2025, nearly 50 Chinese scholars and policy researchers gathered in Beijing for the 2025年德国形势年终研讨会 “2025 Year-End Seminar on the Situation in Germany… Read more 9 months ago · 31 likes · 1 comment · YIRUI LI and Yuxuan JIA ](https://www.pekingnology.com/p/chinas-germany-watchers-take-stock?utm_source=substack&utm_campaign=post_embed&utm_medium=web&embedding_publication_id=1151841) [ Jiang Feng on Germany's 2025 and beyond: no easy exit ](https://www.eastisread.com/p/jiang-feng-on-germanys-2025-and-beyond) Yirui LI and Yuxuan JIA · Jan 24 The following is an op-ed by Jiang Feng, published on 29 December 2025 at Shanghai Observer 上观新闻, the digital platform of Jiefang Daily, the official newspaper of the Shanghai Municipal Committee of the Communist Party of China (CPC). [ Read full story ](https://www.eastisread.com/p/jiang-feng-on-germanys-2025-and-beyond)

Sep 22 • 3:04 AM EDT • Politics • eastisread.com

Albertsons CEO Susan Morris to Keynote 13th Annual Treasure Valley Business Breakfast

The College of Idaho will host the 2026 Idaho Superintendent of Public Instruction Debate on Tuesday, September 22, at 7 p.m. in the Langroise Center.

Sep 21 • 11:47 AM EDT • Business • collegeofidaho.edu

'All INdiana Politics' on Sept. 20, 2026

Watch a replay of the “All INdiana Politics” from Sept. 20, 2026.

Sep 20 • 8:29 PM EDT • Politics • wishtv.com

‘All INdiana Politics’ on Sept. 20, 2026

Watch a replay of the “All INdiana Politics” from Sept. 20, 2026.

Sep 20 • 8:29 PM EDT • Politics • wrtv.com

Health Policy Watch | Controversy, secrecy and suffering after year one of the America First Global Health Strategy

Country controversies, secret terms, opaque procurement, and massive unspent Congressional funds have characterised the first year of the America First Global Health Strategy.

Sep 20 • 5:16 PM EDT • Health • eatg.org

I replaced ChatGPT with Siri AI for a day

I use ChatGPT every day. Siri? Not so much.

Sep 19 • 4:00 AM EDT • Technology • tomsguide.com

Anthropic launches Claude Code Projects, an ‘always-on’ conversation that remembers and delegates your long-running dev work

For enterprises, it makes a whole lot of sense: their digital storefront, website, content management system, procurement platform, or other business application rarely has a discrete endpoint.

Sep 17 • 2:33 PM EDT • Technology • venturebeat.com

[Press release] Global Fund report shows countries fought to protect essential health services despite challenging year

The Global Fund has now helped save 72 million lives since 2002, with this year’s Results Report highlighting how country and community leadership, innovation and partnership helped protect essential services.

Sep 17 • 1:19 PM EDT • Health • eatg.org

Is Philosophy Dead?

Will science replace philosophy?

Sep 17 • 8:00 AM EDT • Science • psychologytoday.com

Your AI agents can now control your Google Home devices

Google is launching early access to a new MCP server for Google Home, allowing AI agents like Claude, ChatGPT and others to control connected devices, review camera summaries and access smart home activity using natural language.

Sep 16 • 1:00 PM EDT • Technology • techcrunch.com

Free mobile clinic helps Topeka residents access health care

A free mobile health clinic is offering blood-pressure checks, screenings, and medical education to Topeka residents with or without health insurance.

Sep 15 • 7:14 PM EDT • Health • wibw.com

Meta now lets AI agents handle the boring parts of WhatsApp Business setup

A new WhatsApp Business MCP server lets developers use AI coding agents like Claude, Cursor, Codex, and ChatGPT to handle setup, messaging templates, testing, and troubleshooting.

Sep 15 • 4:12 PM EDT • Business • techcrunch.com

Does Trump want to win the midterms?

He is not making it easy on Republicans in the House and Senate

Sep 15 • 1:14 PM EDT • Politics • theweek.com