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Amazon’s colorful and sturdy new Kindles
In this week’s Installer: Amazon’s new Kindles, OpenAI’s Dots, the remastered Witcher 3, and more.
Ryan Reaves Pulls Curtain Back On Time With Maple Leafs
Former Toronto Maple Leafs enforcer Ryan Reaves announced his retirement from the NHL last month, ending his career that spanned 16 total season and multiple clubs, including a stop with the Maple Leafs.Reaves, who accumulated over 1,000 penalty minutes during his career, is now pulling the curtain back on his time while with the Maple […] The post Ryan Reaves Pulls Curtain Back On Time With Maple Leafs appeared first on HEAVY.
She Was in the Best Health of Her Life. Then Came Breast Cancer
At 40, Miami Pilates instructor Monica Larcada was active, health-conscious and feeling better than ever. When she discovered a breast lump, however, she acted immediately. Her diagnosis of invasive ductal carcinoma launched an intensive treatment journey — and changed the way she thinks about health, strength and gratitude.
Prosecutors: Saudi government supported ex-OpenAI employee
Abdulrahman Alfozan had been in contact as recently as October 5 with a member of the Saudi Royal Family, prosecutors said.
ChatGPT for Teens Failed to Alert Parents During Mental Health Crises
OpenAI disputes the findings.
Europe expands access to research data with 13 new open science hubs
Researchers across Europe can now access and share research data and digital services more easily, following the launch of the first 13 hubs in the EOSC Federation
LOCALIZE IT: As coding boom fades, computer science grads focus on AI skills in choppy job market
Computer science graduates face hiring challenges; artificial intelligence demand is shifting recruitment toward seniors
OpenAI CFO Sarah Friar Sees Cybersecurity As Potential 'Big Driver' Of Business Amid Rising AI Demand
Friar also discussed increasing agentic AI usage in Europe, while acknowledging that the region trails somewhat in adoption.
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.
OpenAI's annualized revenue $20 billion less than previously signaled, FT reports
OpenAI's annualized revenue is about $20 billion less than has been previously signaled, the Financial Times reported on Thursday, citing financial documents shared with investors.
OpenAI's Altman says AI benefits warrant accepting some risks
OpenAI Chief Executive Sam Altman said the benefits of artificial intelligence justify accepting some risks and argued the technology should remain broadly accessible to the public
New hot dog restaurant opens in iconic SLO spot. It forgot one thing: a health permit
The restaurant had to pay a penalty after it launched without a valid health permit and inspection last week, the county health department confirmed.
Spotify is cracking down on Family plans again, and the penalty can lock you out for a year
Spotify is rolling out in-person QR-code checks for some Premium Family members, with a seven-day deadline and a 12-month restriction for those who fail verification.
European Commission allocates €65 million to protect life science data
The European Commission announced the €65 million funding on 6 October 2026 through Horizon Europe
OpenAI acquires startup Orchestra Bio to beef up its biotech business
OpenAI says it's adding Orchestra's team and technology to work on Rosalind, its AI model for life sciences research, and to its related Rosalind Workbench tool, a harness that aims to help researchers plan experiments and analyze results.
Who is David Robinson, the OpenAI safety leader who quit the company?
David Robinson said he quit as OpenAI's safety lead because he feels the company "is failing to achieve the level of care I believe is needed."
Price misses penalty as Northern Ireland held by Georgia
Northern Ireland remain the only team to not concede in the 2026-27 Uefa Nations League after a 0-0 draw against Georgia in Group B2 at Windsor Park.
Bills Have Made Their Feelings on Rookie Davison Igbinosun Clear
Jim Leonhard says Bills rookie Davison Igbinosun has earned a bigger role at cornerback, but penalties and technique remain areas to improve.
Patriots Player Fined For Chop Block Refs Missed On Sunday
TreVeyon Henderson got fined $12,537 for a chop block refs missed against Buffalo. Mike Vrabel calls penalties ridiculous. Here is the real story.
Drew Petzing Failed the Lions When They Needed Him Most
The Lions’ defense was awful, but Detroit’s offense deserves plenty of blame, too. Missed opportunities, costly penalties and questionable play-calling turned a winnable game into a brutal loss.
Look at OpenAI and Anthropic executives' political donations
One AI tech executive’s $25 million gift to a Trump PAC stands out among donations of other top execs.
What Are the Remaining Millennium Prize Problems?
OpenAI’s trove of new math results doesn’t fully solve any of these highly prestigious open questions, but it seems to make progress on some.
Nintendo Switch 2 Gets Its First Software-Only Jailbreak, With Help From OpenAI Codex
Sammy Hajhamid, a security researcher who goes by pepsipu online, has released ns2jb, a software-only jailbreak for the Nintendo Switch 2 that runs on the latest 23.0.1 firmware. To show it off, Hajhamid modded Mario Kart World, a Switch 2 exclusive, and also dropped Peter Griffin, Hatsune Miku,...
Goldman Sachs spends big to give small businesses an AI boost
The Wall Street giant is committing $500 million to expand its 10,000 Small Businesses program and launch an AI institute, partnering with Google, Meta, OpenAI and Anthropic to bring AI know-how to Main Street. NBC's Christine Romans spoke exclusively with Goldman Sachs CEO David Solomon and with small businesses figuring out how to make AI work for them.
OpenAI users in Russia, Iran used models to push political agenda online, in media
OpenAI banned several accounts associated with two propaganda operations based in Iran and Russia, respectively, it confirmed Thursday. The latter of which the tech company said had the greatest re…
NASA’s SpaceX resupply mission delivers science experiments and solar arrays to space station
NASA’s latest resupply mission has successfully launched towards the ISS, carrying thousands of pounds of supplies, scientific equipment and new technology
F1 Singapore: George Russell Penalized for Engine Change
The Briton will start from the back of the grid after the power unit failure in Malaysia. Mercedes brings forward the engine change planned for later. The sanction will be applied on Sunday, not in the Sprint, which gives him an opportunity to score.
Whitmer celebrates Michigan educators completing intensive Science of Reading training
LANSING, Mich. — On Wednesday, Governor Gretchen Whitmer announced that 8,019 Michigan educators have now completed Language Essentials for Teaching Reading and Spelling (LETRS) training, a program that helps educators strengthen their literacy instruction and implement proven methods, like phonics and comprehension, to empower kids in the classroom. This milestone comes after Michigan saw record […]
Google's AI Detection Website Is Now Available
SynthID Detector will flag content created with AI tools from OpenAI, Google, Apple and other companies.
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
Behind bars and beyond capacity: The mental health crisis in prisons
Open Access Government reflects on data and efforts from concerning the prevalence and care of mental health disorders among prisoners
Meta to pay historic $25 billion in New Mexico deception case
Meta Platforms Inc. was ordered to pay a groundbreaking $25 billion civil penalty to the state of New Mexico in a consumer deception case spurred by the Cambridge Analytica scandal.
Pat Fitzgerald Blasts Officiating After Michigan State’s Heartbreaking Loss
Pat Fitzgerald unloaded on officials after Michigan State's controversial onside-kick penalty against Illinois, calling the sequence one of the most confusing he'd seen.
Readers Write: Health care, AI, Minneapolis City Council and Public Schools, the death penalty
Be an informed health care voter this November.
Auburn's Georgia Upset Didn't Hide the Problems Alex Golesh Still Wants Fixed
Auburn head coach Alex Golesh isn't overlooking the Tigers' mistakes after their 27-24 upset of No. 1 Georgia. Ahead of Saturday's LSU matchup, Golesh emphasized fixing penalties and dropped passes, building on Byrum Brown's improved offensive role, and developing Auburn's young defense.
SEC fines school $500,000 for fan behavior
The SEC didn't wait long to penalize for the infraction.
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.
Rice rescues Arsenal draw at Bayern in Champions League
Declan Rice scored a late equaliser to grab last season's runners-up Arsenal a 2-2 draw at Bayern Munich in the Champions League on Wednesday. Kane's second-half penalty, his 16th goal in 23 matches against Arsenal, extended his scoring streak to 10 straight Champions League games.
Small Business Administration loans approved for Aspen Acres Fire
The U.S. Small Business Administration has approved Colorado's request for disaster assistance loans following the Aspen Acres Fire in Pueblo and Custer Counties, Gov. Jared Polis announced Friday.
OpenAI claims we've entered the AGI era — has GPT-6 Astra really demonstrated general intelligence?
OpenAI says its newly launched GPT-6 Astra model brings humanity to the threshold of AGI, but external evaluators argue that inflated lab metrics and opaque testing obscure its true reliability.
Andrew Garfield says OpenAI film 'Artificial' turns lens on creators of 'new world'
LONDON, Oct 11 (Reuters) - Curiosity and fear powered actor Andrew Garfield's performance in Luca Guadagnino's OpenAI movie "Artificial", which premiered at the London Film Festival on Sunday.
CCIA Study Finds South Korea Fines U.S. Companies Up to Seven Times More Than Korean Firms Relative to Business Activity
Washington – A new study by the CCIA Research Center finds that South Korea’s competition authority imposes penalties on U.S. companies at rates four to seven
OpenAI says 'hidden' recording device was planted in office
OpenAI said a "sophisticated recording device" was found in one of its offices and that the company's own models identified the person who planted it.
Bruins Nikita Zadorov Felt “Disgusted” By Being Scratched
Boston Bruins head coach Marco Sturm decided to send a message of tough love to bruising defenseman Nikita Zadorov when he designated him as a healthy scratch for their recent outing, a 4-1 victory on the road over the struggling Los Angeles Kings.Zadorov had been whistled for a penalty in their previous game against the […] The post Bruins Nikita Zadorov Felt “Disgusted” By Being Scratched appeared first on HEAVY.
Regional efforts are needed to address longstanding behavioral health challenges on the Western Slope, report shows
Over the years, Colorado’s Western Slope has developed a range of services to address the region’s behavioral health challenges. Longstanding challenges with funding uncertainty, provider shortages and gaps in care, however, have limited their ability...
Latest News from CNN Politics
Democratic candidate for Texas governor Gina Hinojosa joins Kasie Hunt to discuss her views on the death penalty.
U.N.C. Strikes Trump Deal to Keep Federal Funding
The University of North Carolina at Chapel Hill will not pay any financial penalties but agreed to abide by the Trump administration’s views on diversity and other matters.
Trump's Science Medals Go to Musk and Huang: Where Are Altman and Amodei?
Trump will award Musk and 5 tech CEOs top US science medals. OpenAI's Altman and Anthropic's Amodei are missing.
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.
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How Americans’ Financial Health Is Faring In The “K-Shaped” Economy
Hey all, Jason here. Money20/20 is still two weeks away, but I’ve already started packing (not procrastinating for once!). My calendar is already filling up with various sessions I want to catch, meetings, and of course happy hours, dinners, and other side events. If you’ll be in Vegas and want to catch up, let me know by replying to this email, and we can try to find a time amidst the chaos of the Venetian. A big if not totally unexpected piece of news dropped on Friday: the Independent Community Bankers of America, a trade group that represents smaller U.S. banks, filed a lawsuit against the OCC and Comptroller Jonathan Gould, arguing that the regulator’s move to grant trust bank charters to firms seeking to use them to conduct substantial non-fiduciary activities exceeds the authorities granted to the OCC by Congress. I haven’t had time to fully digest the legal filing or speak to folks in my network about it, but you can expect to see coverage and analysis on it in next week’s newsletter. Subscribe or Support by Upgrading The NerdCon agenda just dropped. It’s stacked. Partner content: Nubank built an AI-first bank. Chime built its own banking core. Figure and Valon are rebuilding the mortgage stack. At NerdCon, you’ll hear from the people behind those bets: what they chose, what they learned, and what they’re still figuring out. The agenda is live, with leaders from Nubank, Chime, OpenAI, Remitly, Mercury, Figure, Valon and more. Follow the mainstage conversations, bring the problem your team is wrestling with to a hands-on workshop, or pull up a chair at a roundtable. Pick your quests. Meet us in San Diego, November 18–20. Fintech Business Weekly readers save 20% with code FBW20. Explore the Agenda Things To Know & Other Good Reads Federal Reserve Board finalizes changes to enhance the transparency and public accountability of its stress test and reduce volatility in its stress test-related capital requirements (Federal Reserve Board of Governors) FDIC Announces Conclusion of Independent Monitorship (FDIC) Modernizing Financial Regulation: Initial Observations from eSLR (Fed Vice Chair for Supervision Michelle Bowman) The Data Version of Godzilla versus Kong: FRED Takes on AI (Fed Governor Christopher Waller) Financing the AI buildout (Brookings) Q3’26: Rules for Banks but Not for Crypto (Fintech Takes Banking) The Inevitability of Local Stablecoins (Lombard Notes) Delusions of AI Governance: The Human-in-the-Loop Comfort Blanket (Fintech Snark Tank) Stripe agrees to acquire Parafin to expand revenue opportunities for platforms and help small businesses grow (Stripe) Listen: Fighting Fraud in the Age of AI, with SEON’s Tamas Kadar (Fintech Business Weekly) How Americans’ Financial Health Is Faring In The “K-Shaped” Economy If there is one overarching theme across the economy and politics in the U.S. at the moment, it’s “affordability.” The term is vague enough to encompass a panoply of factors shaping Americans’ day-to-day lives: rising costs for the hallmarks of being “middle class,” including healthcare, housing, childcare, and education, inflation and rising interest rates, and a job market with the specter of AI hovering over it. At the same time, policy shifts under the Trump administration have resulted in reduced subsidies to those who get health insurance under the Affordable Care Act and new restrictions on qualifying for Medicaid and SNAP, the impacts of which have yet to be fully felt. These factors are contributing to declining consumer confidence and general dissatisfaction with the economy, despite continuing GDP growth and stock market records. This divergence is encapsulated in the idea of the “K-shaped” economy, in which a small proportion of Americans have seen their wealth balloon, while the majority of American households struggle to preserve the lifestyle they have. Perhaps the greatest determinant of which branch of the “K” a household is on is whether their wealth and income are primarily derived from employment vs. from assets. Nearly two decades of low interest rates and, more recently, elevated rates of inflation have benefited asset owners, while those whose income is primarily or solely derived from labor have largely seen real purchasing power stagnate or decline. This is reflected in recent Bureau of Labor Statistics data showing that labor share of U.S. GDP — the fraction of economic output that accrues to workers as compensation in exchange for their labor — dropped to just 52.8% in Q2 2026, the lowest since the BLS began keeping records. In 1947, approximately 2/3rds of economic output accrued to workers; even as recently as 2001, labor’s share of GDP was 64.1%. Against this backdrop, we’ve seen the rise of more credit and credit-like products: cash advance apps, “no-fee” overdraft, earned wage access, and buy now pay later, which are often used as small-dollar short-term borrowing mechanisms to meet immediate consumption needs or pay other bills (eg utilities, cell phone, other debt payments). With the markers of a middle class existence and, increasingly, basic financial stability seemingly out of reach for many, it should be no surprise there’s been an increase in “financial nihilism,” something industry peers like Alex Johnson and Frank Rotman have discussed and analyzed the roots of. The explosion of gambling and gambling-adjacent products and services — often marketed under the guise of being an “investment” — is inextricably intertwined with the rise of financial nihilism. Crypto, sports betting, and, more recently, prediction markets offer an escape or even hope of sorts, like a contemporary, digital version of a scratch-off lottery ticket, while leaving the overwhelming number of people who use such products worse off. Share of Households That Are Financially “Vulnerable” Ticks Up The Financial Health Network’s 2026 Financial Health Pulse® report adds context on how American households are faring. (I linked to this report in last week’s newsletter, but wanted to take time to further unpack the data in the report this week.) The Financial Health Network publishes the report annually, providing insight into how Americans’ financial circumstances are changing over time. The 2026 report is derived from a survey fielded in April and May 2026. The report leverages survey responses to assess indicators of financial health across spending, saving, borrowing, and planning/protecting and to determine a zero to 100 “FinHealth” score. Those with scores between 0 and 39 are considered “Financially Vulnerable,” consumers with scores ranging between 40 and 79 are defined as “Financially Coping,” and those with scores of 80 to 100 are “Financially Healthy.” The report found that moderate improvements in 2025 were reversed, with the share of respondents considered financially “vulnerable” rebounding to 17%. The longitudinal data reflect the impact of pandemic-era programs, like expanded unemployment, cash stimulus payments, and pauses of federal student loan payments. The positive impacts of those programs, as reflected in the Financial Health Pulse reports, had largely disappeared by 2023. While pandemic-era inflation — to be fair, in part caused by the various support and stimulus measures — had come down from as high as 9% in 2022, it has rebounded since the start of Trump’s second term, with tariffs and energy market disruptions owing to the war in Iran pushing prices back up. Specific indicators in the survey that deteriorated from 2025 to 2026 include the share of respondents spending less than their income over the past 12 months, the share paying all bills on time over the past 12 months, the share that have a manageable amount or no debt, the share that are “moderately” or “very” confident their insurance is adequate to cover them in an emergency, and the share that “somewhat” or “strongly” agree that their household plans ahead financially. Unsurprisingly, lower- and moderate-income households are more likely to struggle to pay their bills on time and have any funds leftover to save. The share of low-income households whose income exceeded their spending dropped from 35% in 2025 to 31% in 2026, while the share of upper-income households whose income exceeded expenses remained unchanged at 63%. Households with student loans or revolving credit card debt reported having “a bit more” or “far more” debt than was manageable at rates far higher than those not carrying these types of debts. The share of those with student loan debt indicating their debt load was too high to manage increased from 50% in 2025 to 55% in 2026, while the share of those with revolving credit card debt saying the same ticked up from 51% in 2025 to 54% in 2026. Households that had student loans were markedly more likely to be financially “coping” or “vulnerable” vs. those without student loans. In 2026, 27% of households with student loans were considered financially vulnerable, a jump of 6% points vs. 2025. Households without student loans saw just a 1% point increase (not statistically significant) in those considered financially vulnerable. Households’ perception of the affordability of categories of goods and services paints a stark picture, with less than one-fourth considering higher education affordable, about a third deeming childcare affordable, and less than half viewing healthcare as affordable. Fintech Business Weekly is made possible by the generous support of paying subscribers — bringing you independent analysis of banking, fintech, and crypto without fear or favor. You can support my work by becoming a paying subscriber if you aren’t already. Paying subscribers enjoy: access to the entire archive of nearly six years of newsletters extended versions of the weekly newsletter, with additional content and analysis and (for founding member tier) quarterly personal 1:1 fintech Q&A / strategy calls with me, tapping into my unparalleled knowledge of the intersection of banking and fintech and experience working in the sector, including helping to launch Goldman Sachs’ retail bank Marcus Support Fintech Business Weekly You can also support Fintech Business Weekly by sponsoring a newsletter or podcast, putting you in front of 93,000+ of the most influential decision makers in banking, fintech, and crypto. Learn more about sponsor opportunities or request a media kit by dropping me an email. Democratic Senate Report Highlights How Iran Uses Tether to Evade U.S. Sanctions Iran uses stablecoins, specifically Tether, to evade sanctions, fund regional proxies, and to purchase military drones, a report released last week by the Senate Permanent Subcommittee on Investigations says. The report was authored by committee ranking member Senator Richard Blumenthal (D-CT) and the minority staff. Crypto and stablecoin proponents will often push back on criticism that criminals make use of these assets by arguing that, on an absolute dollar basis, far more illicit funds flow through traditional banking systems and payment rails than via crypto and stablecoins. And while that is likely true, it elides the reality presented in news story after news story: whether state actors — Russia, Iran, North Korea — or criminal groups, those looking to engage in illicit transactions increasingly favor stablecoins and, specifically, Tether (USDT). The report from the Senate Permanent Subcommittee on Investigations released last week adds context to how Iran uses Tether has a lynchpin in its shadow banking system. The report analyzed 846 wallets that have been sanctioned or targeted for seizure, finding that 84% of them transacted exclusively or primarily in Tether. The ability to create near limitless, anonymous wallets and to move funds effectively instantaneously and irreversibly have made crypto a favored financial mechanism for bad actors. Stablecoins solved key drawbacks of bitcoin, namely, the original cryptocurrency’s highly volatile value in dollars. And while Tether (the company) has the technical ability to “freeze” or destroy funds, the company is often limited and reactive in its approach to doing so, the Senate report argues. Tether, which is nominally based in crypto-friendly El Salvador, “has stated that its compliance with OFAC sanctions is ‘voluntary’ and that it follows ‘OFAC guidelines,’” the Senate report says. Owing to these favorable attributes, Tether “became a primary cryptocurrency for Iran, Hamas, Hizballah, and the Houthis beginning in 2023 and has expanded in scale since,” according to the report. Tether’s role in Iran’s shadow banking system, the report says, is enhanced by crypto exchanges like Bybit, Kyrrex, OKX, Gate, and Binance, and through “over the counter” exchanges and hawala networks. The consequences of these financial flows aren’t hypothetical. The Senate report links Tether as a funds transfer mechanism to Iranian proxies in the region, including Hizballah, the Houthis, and Hamas. Tether has also been used to make payments to secure components necessary to manufacture drones, the report says. The report concludes by arguing that “[s]tablecoin issuers with a significant nexus to the United States, particularly those that offer dollar-denominated stablecoins, should be subject to American sanctions law rather than being allowed to hide behind foreign jurisdictions.” Stablecoin issuers like Tether must be held accountable for repeated failures to prevent illicit finance and sanctions violations by law enforcement, the Department of Justice, the Securities and Exchange Commission, and OFAC, the report argues. [Paying Subscriber Exclusive] OUSD Goes Live, Make Your Own Neobank, U.S. Sanctions Russia’s A7 Network As “Transnational Criminal Organization” OpenUSD, the stablecoin issued by the Open Standard consortium that includes Stripe, Visa, Mastercard, core providers, crypto firms, and numerous banks, went live last week. Social commerce platform Whop raised eyebrows in fintech by offering creators on its platform the ability to launch their own neobanks, which the company describes as “great businesses that are easy to run,” in just 15 minutes. And OFAC and FinCEN target Russia’s “shadow banking” A7 Network — more on these stories after the paywall.
Microsoft President says AI Needs Urgent Regulation
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Judge detains fired OpenAI engineer over concerns on Saudi Arabia ties
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NFL fans question officiating after Mahomes call
Ringo Chiu/Shutterstock.com Mahomes penalty sparks debate over NFL officiating NFL fans are debating a roughing-the-passer call involving Patrick Mahomes and Dolphins linebacker Chop Robinson. The penalty came during Kansas City’s 24-10 win over Miami and sparked questions about how quarterbacks are protected. A similar-looking play involving Indianapolis Colts defensive tackle DeForest Buckner and Washington rookie…
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The ‘War Games’ problem: Computer science has long understood what it takes to keep AI under control
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Can AI solve our mental health access problem?
Last week I asked you what worries you most about AI in health. It was close, but your top answer was “AI giving bad health advice.” Last week’s poll results: You’re in good company. This concern was top of mind at a conference I joined at Stanford last week, where researchers, clinicians, and people who build AI systems spent a day debating trust and safety in health AI. Stepping back, I’m also hearing your emerging concerns about AI’s impact on our well-being generally. I see this as a matter of public health, and we’ll take it in pieces as we learn together. Today we’ll focus on AI chatbots used for therapy for mental health. Early this month, Governor Newsom vetoed Senate Bill 903, California’s most ambitious attempt to regulate AI use for mental health. It’s at the center of active debate, and raises the questions patients, family members, citizens, and voters will face as AI moves deeper into health care. Let’s work through it. What is “AI-based therapy”? It’s really two things: purpose-built mental health apps designed to deliver structured support, and general chatbots like ChatGPT, Claude, and Gemini that people increasingly use for emotional support—even if they weren’t built for it. Spoiler alert: I don’t know whether the shift toward AI therapy is good or bad. The evidence isn’t there yet. But I do know it’s already happening, and I have some ideas about how we can roll it out with safety in mind. The therapy dilemma, in a nutshell Mental health challenges are common, and strain health and well-being across populations. Therapy (interactive dialogue with a trained, empathetic practitioner) helps many people heal. The demand for licensed therapists far exceeds the supply in California, and AI-based therapy can narrow that gap. AI-based therapy remains novel, unproven, and not well tested. Right off the bat, we can see we’re dealing with trade-offs here. Since the main driver of demand for therapy from a robot is lack of access to therapy from a human, we’ll start there. It’s too hard to find and afford a human therapist California is short roughly 55,000 licensed, non-prescribing therapists and counselors, about 40% of what we need. Psychiatrists, who rely on talk therapy as a complement to prescribed medications, are even more scarce. Eight counties have none, and density ranges from 1.7 per 100,000 residents in San Benito County, to 68.1 in Marin County. My wife is a psychiatrist in Marin, and even here access is tight. If it’s hard in the best-supplied county, imagine rural Sierra County, or the San Joaquin Valley. In 2024, more than half of Californians who tried to make a mental health appointment struggled to find a provider who took their insurance, compared with 14% for physical health care. When Senate staff posed as “secret shopper” patients and called 120 mental health providers in Medicare Advantage networks, they landed an appointment less than once for every five tries. Insurers pay behavioral health clinicians about 22% less than medical and surgical clinicians for comparable office visits. On top of that, billing denials and prior authorizations hit hardest at the solo and small practices common in mental health. Psychiatrists opt out of Medicare at the highest rate of any specialty. In many places, a cash practice for therapy fills quickly with patients paying $250 or more an hour, with no insurance paperwork at all. Families who can pay cash find providers more easily. Those who rely on insurance, including Medi-Cal enrollees, older adults, rural residents, and non-English speakers, compete for what’s left. So we can’t pretend the human system works, and we can’t blame people for turning to AI for support when they’re in distress. AI is filling the gap It’s estimated that roughly a quarter of AI users use it for mental health support. If you have internet, it’s available 24/7, it’s cheap, and it speaks your language. Uninsured adults are about twice as likely as insured adults to do it (30% vs. 14%). It feels anonymous in ways that may enable people to ask things they’re unsure or embarrassed about. The largely hidden, personal use makes it hard to study whether it’s actually helping people with their mental health issues, but researchers are trying. Does AI therapy work? A 2026 analysis of nearly 40 randomized trials found chatbots showed a real but small reduction in depression symptoms. But most of these trials were compared to an alternative of no therapy, not a human therapist. So the benefit of AI therapy is probably real, but modest, and mostly untested against the alternative of human contact. We need more studies. Serious concerns OpenAI’s own estimate is that more than a million ChatGPT users each week show signs of suicidal planning or intent. These are high stakes encounters, and AI doesn’t always get it right. That’s partly because a chatbot can sound like a therapist, but it has no license, no duty of care, and it’s not clear who to hold accountable when it gets things wrong. AI is also designed to help users in whatever task they’re seeking to accomplish. People may feel like they’re getting therapy, but they’re mainly getting a convincing conversation. It’s easy for an AI companion to wander into gray areas, like playing along with “creative writing” that may be about the user’s own suicidal intent. Courts are driving safety conversations A wave of lawsuits have been filed on behalf of families claiming that chatbots pushed people they loved toward self-harm, including teens who died by suicide. The first settlements came this year. OpenAI is headquartered in San Francisco, and dozens of cases alleging that ChatGPT drove users to suicide or self-harm are now before a San Francisco judge. Character.ai has filed for bankruptcy after several states brought lawsuits accusing the chatbot of pushing dangerous content to kids. But the technology seems to be improving. Last month, an independent evaluation found that newer AI models “almost never endorse suicide.” That’s progress, but our societal appetite for even one preventable death is very low. So how do we move forward? Finding a middle ground Earlier this month the governor vetoed Senate Bill 903, a bill designed to place guardrails on the use of AI for therapy. The bill would have prohibited any AI-based platform from being advertised as psychotherapy, and would have required a licensed professional to review and approve each encounter where AI was used to support therapeutic decisions. Newsom called it overly broad, since even routine screening questions would have needed clinician sign-off. Knowing we’re already short on mental health providers, requiring human review of AI encounters may not relieve our access problems. Still, the answer isn’t no oversight. Here’s one feasible short term solution. Rather than reviewing each encounter, a licensed clinician can design the guardrails: what counts as a crisis, what triggers an immediate handoff to a human, and what gets sampled for audit each month. The AI runs inside that structure. Conversations get checked, failures get reported, and a real clinician owns the framework. Medicine already has models to learn from. The FDA process for rolling out newly approved medications is an example. After a product reaches patients, we keep watching for adverse events. Patient-facing AI needs the same “digital pharmacovigilance”: systematic tracking of harms, near misses, and the types of groups that get hurt and why. It’s also critical that users know that they can reach a human if they’re in crisis. Most chatbots now include messages like these: Bottom line The rush to use unproven AI tools for mental health support is mostly a workaround, a sign of a health system people can’t get into. We need better access to proven care from licensed clinicians. That takes reimbursement that makes accepting insurance viable, and a bigger workforce. But, built and tested well, AI could be part of the answer. It could be the 2 a.m. check-in when no one else is awake, or a way for patients to practice skills their therapist taught them. It could be the first step to get someone the right level of care, and take paperwork off clinicians’ plates so they spend more time with patients. None of this is simple. The SB 903 veto doesn’t end the debate, and the legislature will be back. In the meantime, those of us using these tools need to stay informed, ask hard questions, and hold the companies building them accountable. I’ll try to do my part, and we’ll keep learning together. Love,Matt P.S. If you or someone you know is struggling with mental health challenges, emotional distress, substance use problems, or just needs to talk, call or text 988- you’ll reach a real person— or chat at 988lifeline.org 24/7. Dr. Matt Willis is the author of Your Local Epidemiologist in California. A California native, he’s served as a primary care physician, CDC epidemiologist, and public health officer for Marin County, where he guided the pandemic response. He lives in Marin with his family and their dogs, Teddy and Ramona. Thank you Cynthia He, MD, PhD, and Parnika Saxena, MD, for their guidance in preparing this article. Cynthia works in an outpatient mental health clinic, treating patients who have Medi-Cal or, sometimes, no insurance. Parnika works in an inpatient psychiatric unit, treating patients with public or private insurance or self-pay ability. All opinions are their own and do not represent their employers.
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