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NASA Unveils New Science Mission Competition Model
NASA is overhauling science mission selection, with up to 45 percent faster timelines and greater use of commercial space capabilities.
OpenAI makes its Jev competitor widely available as decision model competition heats up
OpenAI is launching its decision model to the world. Can it compete with the original Jev?
Canva releases its first image generation model
Canva is making its new image model available to all users, promising better, more customizable performance at lower costs.
Microsoft’s Mustafa Suleyman says its AI outperforms doctors on hard cases as he chases ‘medical superintelligence’
Microsoft’s new AI diagnostic system beat generalist doctors on hard cases, according to a study in Science. But most of the improvement seems to come from the AI models underneath, not from Microsoft’s system itself.
Funding Cuts Push Global Health Partnerships Toward Local Ownership
Speakers at IDWeek 2026 urged shifting global health partnerships from donor-recipient models to shared, locally led ownership as funding contracts.
Four advantages MacBook Pro redesign will have over current model
A big redesign is coming to the MacBook Pro next week, with at least four rumored advantages compared to current models.
COROS DURA 2 SOLAR Review: Big Upgrade, Bigger Price
Neil's latest review digs into his experience with the COROS DURA 2 Solar, a new bike computer that claims to improve on the first model...
Navvis Introduces New Solution to Help Health Systems Build the Operating Capabilities Required to Achieve High Performance in CJR-X
ST. LOUIS, October 22, 2026--Navvis, the leading value-based care enablement company, today announced a new CJR-X solution built to help health systems achieve high performance in the Centers for Medicare & Medicaid Services (CMS) mandatory and newly finalized Comprehensive Care for Joint Replacement Expanded (CJR-X) model. Joint replacement is one of the most profitable service lines for health systems across the U.S. today, and CJR-X gives health systems a mandatory new way to protect and grow
Breitling Adds Two New Manual-Wind Navitimers To The Core Collection
✓ Breitling has just introduced a pair of new manually-wound Navitimer models to its core collection ✓ Check it out! ✓
Introspection required if EU Inc fails, says start-up lobbyist
European start-ups have a new voice in Brussels. Startups for Europe, created from the merger of lobby groups Allied for Startups and the European Startup Network, is hoping to harness the momentum behind EU-Inc, a campaign that united start-ups and investors behind demands for a new pan-European company regime.At a launch event for the new association in Brussels on October 1, the mood was remarkably upbeat compared to a typical Eurobubble gathering, more Silicon Valley than Schuman roundabout.When asked whether this reflects a feeling that Europe is on the right track, chief executive Serena Borbotti-Frison said it’s a “scary” moment as the continent looks to boost its competitiveness amid a new technological arms race.“What is at stake is quite intense, and the way we can answer is by delivering, but also with hope,” she told Science|Business. “It’s what our industry does. It’s not about identifying a pain point and then saying it’s too hard.”For many in the start-up community, that sense of hope is dwindling. In March, the European Commission presented its proposal for EU Inc, naming its initiative after the grassroots campaign.EU Inc was meant to be a gamechanger: the ability to incorporate within 48 hours for less than €100 and scale up across Europe; a harmonised stock option regime enabling start-ups to compete for talent; and simplified insolvency procedures for innovative start-ups to reduce the cost of failure.However, haggling by EU governments has raised concerns that EU Inc will be stripped of the very features, including stock option harmonisation, that are meant to make it attractive for companies.“I fear we are proving to ourselves that the model doesn’t work,” Borbotti-Frison said of the policymaking process. “Everyone agrees we should have EU Inc. Everyone agrees it’s hard to scale and we need to scale to answer the competitiveness [challenge], and still we cannot deliver? [. . .] What does that say about ourselves?”The Commission has made EU Inc a cornerstone of its single market reform, and has agreed with the European Parliament and the Council of the EU to target an agreement by the end of 2026. However, several points are currently holding up an agreement, including national rules around employee participation in management decisions, and the provision that employee stock options always be taxed at the point of sale. Some EU governments have reportedly pushed back on the Commission’s choice of legal basis, contending that anything related to taxation requires unanimity in the Council.Trade unions have also protested against EU Inc, fearing it will be exploited by companies looking to undermine workers’ rights.“If this doesn’t work, it’s introspection time, on the way our institutions work, maybe the way our lobbies work, and maybe the way the cooperation between them works,” Borbotti-Frison said.“Is it in the national interest? Is it a gap between political will and technical ability to operate? Is it speed? I don't know, but something needs to be fixed.”Ahead of last week’s European Council meeting, EU-Inc campaigners tried a new strategy: appealing directly to EU presidents and prime ministers. In an open letter, they urged EU leaders to “step in and give your negotiating teams a clear mandate to change course and reverse their objections to the Commission’s original proposal.”Lessons from EU-IncLike its predecessors, Startups for Europe will represent national start-up associations, but it is also targeting investors. The founding sponsors are venture capital firm Atomico and EQT, the investor selected earlier this year to manage the €5 billion Scaleup Europe Fund.It also wants to harness the knowledge and cross-border experience of European success stories. “Take the list of the 100 biggest unicorns in Europe. We are speaking to all of them,” Borbotti-Frison said. The association plans to publish a full list of supporters following the Slush tech conference in Helsinki in November.Andreas Klinger and Simon Schaefer, two key figures in the EU-Inc campaign, are both on the board of the new association, and Startups for Europe wants to take the lessons from their campaign.What was unprecedented about EU-Inc was “how rooted it was, and how strong it was in bringing everyone on board behind one clear pain point and solution to fix it,” Borbotti-Frison said. “This is an inspiration for us, and then we need to turn it into something more systematic, more bridged in Brussels, more connected to the policymaking game, and to scale it.”If it’s possible to unite such a broad coalition, it’s because the European start-up ecosystem is now mature, she said. “Maybe it was not ten years ago. Maybe it was not five years ago. But now, it’s mature to speak with one voice.”Open and liberal EuropeThe association plans to campaign on files related to three “pain points,” Borbotti-Frison said: “start and scale in Europe, fundraise and invest in Europe, and making Europe the most innovative continent.”As well as EU Inc, she cited public procurement, the EU’s simplification push, the Savings and Investments Union, and files related to AI adoption and technological sovereignty as priorities for the coming months.What these files have in common is that they relate not to subsidies but to the framework conditions influencing the availability of mostly private, or in the case of procurement, public, funding.Related articlesEmployee participation disagreement delays MEPs’ vote on EU IncCommission urges EU governments not to water down EU IncEU’s ‘ultra-fast’ €5B scale-up fund is set up to win, says its fund managerThe budget dispute over the next Horizon Europe programme will also impact start-ups, which are supported notably through the European Innovation Council. But EU innovation funding is a drop in the ocean compared to venture capital and public procurement budgets.“If competitiveness and innovation are a priority, then the [EU budget] should reflect it,” Borbotti-Frison said. However, she added that the main question is not how much public money is invested, but “how do we create the right conditions for the market to solve the problem?”The Scaleup Europe Fund mixes both approaches, using €1 billion in EU funding to crowd in private investors and address Europe’s lack of large-scale, late-stage growth funds. “It’s a proof of concept. Ideally, then the market will do it itself,” Borbotti-Frison said.Startups for Europe is also focused on bringing an alternative political narrative. Amid competing visions for open, global markets on the one side and a protectionist Europe on the other, it wants to offer “a third voice, to say we can be proudly European and build a strong continent in a liberal economy, open to the world, and global.”It can be tempting, when thinking about how Europe can better support innovation, to look across the Atlantic. But while it’s important to compare statistics to see where Europe needs to catch up, that’s where the comparison should stop, Borbotti-Frison said. “On everything else, we need to do it our own way. We don't have the same history. We don't have the same political model. We don't have the same way of life.”Many of the key files that could benefit the start-up community, including EU Inc and the Savings and Investments Union, rely on closer integration within Europe, making it easier to operate across borders.While the Commission has made deepening the single market a political priority, support at national level is more precarious. The coming months will see pivotal elections in Spain and France, while the German government has also been coming under pressure domestically. In each country, far-right parties have been gaining ground.When asked if she was concerned the political situation could jeopardise this progress, Borbotti-Frison responded: “Of course. I would be lying if I said I wasn’t.” However, she continues to believe that cooperation is the only way forward. “Doing it alone is not the solution. It’s also not who we are, it’s not the model we are building, and it’s not the scale we need.”
Health insurance through work is under strain. What comes next?
Employers are struggling with rising premiums. Some are looking for a different model.
Hugging Face's new AI model Carbon-X analyzes, generates DNA sequences
Hugging Face's new AI model, Carbon-X, can analyze and generate DNA sequences and help scientists develop new gene therapies, the company says.
Hugging Face’s New AI Biology Model Lets You Chat With DNA
The new open-source model speaks the language of DNA and can help researchers understand the effects of any changes on gene activity and health.
Burning through Türkiye's GDP: The high cost of fossil fuel PM2.5 pollution on public health – Centre for Research on Energy and Clean Air
Türkiye’s reliance on fossil fuels is generating massive air pollution health costs both within the country and throughout the region. This report finds that fossil fuels account for more than half (52%) of Türkiye’s population exposure to PM2.5 air pollution. The cumulative health impacts are estimated to cost the Turkish economy approximately USD 55 billion each year, equivalent to 4.1% of national GDP in 2024. The pollution is also responsible for roughly 26,500 deaths per year in the country, including deaths from cardiovascular and respiratory diseases, lung cancer, stroke, and diabetes.The impacts begin at the very start of life, with fossil-fuel-derived PM2.5 pollution contributing to an estimated 8,000 preterm births, 8,200 low-birthweight infants, 5,100 new cases of childhood asthma, and 6,500 emergency-room visits for asthma each year in Türkiye.Beyond the estimated deaths each year in Türkiye, air pollution from the country’s fossil fuel emissions also contributes to deaths and economic losses in neighbouring countries. In 2024, these emissions were estimated to cause: 32,000 deaths and USD 2.1 billion in economic burden in Egypt; 1,700 deaths and USD 0.2 billion in economic burden in Syria; 800 deaths and USD 0.8 billion in economic burden in Iraq; 500 deaths and USD 4.5 billion in economic burden in Israel; and 400 deaths and USD 1.5 billion in economic burden in Greece.Türkiye currently has no national ambient air-quality standard for PM2.5, despite the substantial health burden associated with exposure to the pollutant. Figure — The percentage of annual PM2.5 emissions in Türkiye’s fossil fuel emissions, using the EMEP emission inventory and EMEP MSC-W chemical transport model Key findings Türkiye’s fossil fuel emissions (from domestic sources as well as international aviation and shipping) account for 52% of population exposure to PM₂.₅ nationwide. PM2.5 pollution attributable to Türkiye’s fossil fuel use is responsible for approximately 26,500 deaths in the country every year, including deaths from cardiovascular and respiratory diseases, lung cancer, stroke, and diabetes. Children are among the most affected, with fossil fuel-derived PM2.5 pollution contributing to an estimated 8,000 preterm births, 8,200 low-birth-weight infants, 5,100 new cases of childhood asthma and 6,500 emergency room visits for asthma each year. The cumulative health impacts of fossil fuel-derived PM2.5 pollution are estimated to cost the Turkish economy approximately USD 55 billion each year, equivalent to 4.1% of national GDP in 2024. Transboundary pollution attributable to Türkiye’s land-based fossil fuel emissions also leads to thousands of deaths in five neighbouring countries, with estimated economic burden per year (as of 2024) reaching USD 2.1 billion in Egypt (3,200 deaths), USD 0.2 billion in Syria (1,700 deaths), USD 0.8 billion in Iraq (800 deaths), USD 4.5 billion in Israel (500 deaths), and USD 1.5 billion in Greece (400 deaths). Türkiye currently has no national ambient air quality standard for PM2.5, despite the substantial health burden associated with exposure to the pollutant. Reducing fossil fuel use and emissions across Türkiye’s energy, transport and industrial systems would deliver substantial air quality and public health benefits by reducing exposure to PM2.5 and preventing associated illness and deaths. Figure — Annual deaths attributable to Türkiye’s land-based fossil fuel emissions in the five most affected countries, based on 2024 emissions
UTA Science Learning Center sets up laboratory-themed escape rooms
The event aimed to highlight resources for students and incorporated anatomy models, chemistry model sets and more.
Scientists discover a surprising secret behind the human brain’s wrinkles
Scientists have discovered why common marmosets have unusually small, smooth brains despite starting development much like other primates. The secret lies in subtle changes to brain-building cells that slow neuron production, revealing new clues about how the large, folded human brain evolved.
BTA Sports Expands into Prediction Markets With AI-Powered Analytics
The fourth quarter rollout pairs independent probability modeling with “Ask BTA” to help users assess sports event contractsHORSHAM, Pa., Oct. 21, 2026 (GLOBE NEWSWIRE) -- BTA Sports, a subscription-based sports analytics and decision-intelligence platform, today announced its expansion into sports prediction markets, bringing the data and insights used by its sports betting subscribers to users evaluating sports event contracts. The offering, available in the fourth quarter as part of Version 2
Vivian Wilson, Model and Elon Musk's Daughter, Signs With Echo Lake
Vivian Jenna Wilson, model and estranged daughter of Elon Musk, has signed with Echo Lake Entertainment for representation.
Can scientists forecast earthquakes? A 2026 study offers clues
A decade-long California experiment tested earthquake forecasting models against nearly 600 earthquakes. Here's what it found.
Billionaires turned life insurers into cash machines. Now comes the reckoning.
A lucrative Wall Street strategy has funneled billions from life insurers into their owners' other ventures. Now tougher rules and questions about investment risks are putting the model to the test.
CoreWeave's business model explained: Why investors are worried
In the Loop Host Ejaaz Ahamadeen breaks down exactly how CoreWeave's (CRWV) business model works, the financial challenges facing the AI infrastructure company, and why concerns about its ability to manage debt are growing. Ahamadeen examines an estimate suggesting CoreWeave faces a 55% probability of default over the next five years, and what that could mean for the company.
OpenAI acquired biotech startup Orchestra Bio to expand its life sciences AI tools
OpenAI will fold Orchestra's team and technology into Rosalind, its AI models and tools for life sciences researchers
Writing the AI regulation rule book | Investors Lab
A mix of specialized AI security startups and established compliance leaders are stepping up
Google Cloud, DeepMind, and the EU: A New Model for AI-Driven Science
Google's latest European research initiative signals a shift toward collaborative AI innovation, where technology developers provide the tools and scientific institutions establish the priorities for discovery.
YouTube Gold: The Greatness Of Allen Iverson
Allen Iverson’s game is a good model for Deron Rippey to aspire to.
Will a Chance to Reshape Business Models Help Law Firms Compete With Silicon Valley For Tech Talent?
Technologists without law degrees can't secure equity when working at a law firm. But some observers say that firms offer more rewarding opportunities to build tech infrastructure from the ground up.
College football mega boosters used to fund buildings. Now they buy QBs. What’s the payoff?
“It's absolutely a non-sustainable business model," said SMU booster Bill Armstrong. "But nobody can control themselves."
Partners, not family: How 3 college buddies built dairy business
Austin Copenhaver and his partners turned a shared dream into three dairy operations, and a model for the next generation of farmers.
Leica and Formula 1 Shift Into Gear With Limited Edition Q3 43
The Leica Q3 is the company's most popular model.
Healthcare and Life Sciences Leaders Build on NVIDIA to Advance Drug Discovery and Expand Patient Care
NVIDIA today announced collaborations with leading global healthcare and research organizations to advance protein design — including through a newly released open model, RFD4-Proteina — accelerate drug discovery and bring greater precision to cancer care.
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.
NASA Study Refines Projections for Thwaites Glacier
Antarctica’s Thwaites Glacier could contribute more to sea level rise by the end of the century than some previous estimates. In some model simulations, the glacier’s contribution was as much as twice current projections.
A Big Overhaul Of Xbox Game Pass Is In The Works
The service will reportedly move to a more à la carte model
Apple's Touchscreen OLED MacBook Pro: Everything We Know
Apple is working on a high-end MacBook Pro, and it's nearly ready to launch. It will have several firsts in a Mac, including an OLED display and a touchscreen. Design Apple hasn't redesigned the MacBook Pro since the launch of the M1 Pro and M1 Max models in 2021, so it's due for a new look. The new MacBook Pro is expected to feature some minor design changes.
iPad Mini 8 Expected Next Week With These 10 New Features
Apple reportedly plans to unveil an iPad mini 8 with an OLED display next week, with those invited to Apple's Los Angeles experience on Wednesday, October 28 expected to receive hands-on time with the device, alongside MacBook Pro models with touch-enabled OLED displays, a 14-inch MacBook Pro with an M6 chip, and an iMac with an M6 chip.
Birth centers are linked to better health outcomes, research shows, but 10 states have none
Birth centers are an option for those with low-risk pregnancies and are correlated with more positive health outcomes, but 10 states do not have any birth centers at all, and more could be built with certain state policy solutions and different models of care, a new report suggests.
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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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.
First Apple TV 4K Pre-Order Discount Arrives at Amazon
Following in the footsteps of a small pre-order discount on the HomeView, Amazon is now offering the first cash discount on the brand new A19 Apple TV 4K. You can get this model for $289.99, down from $299.00. Note: MacRumors is an affiliate partner with some of these vendors. When you click a link and make a purchase, we may receive a small payment, which helps us keep the site running.
3 questions with AI Power Breakfast speaker Mike Stitt
Artificial intelligence is creating urgent questions across every part of business, but the most consequential decisions begin well before choosing a model, tool or platform. The Business Record’s Power Breakfast on Oct. 29 will feature a conversation with Iowa State University alum and partner at Texas-based Lateral Group Mike Stitt designed to help executives, business…
What's on Zuck's desk? We pushed Muse to figure it out.
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Oops, Apple's Website Just Hinted at iPad Mini 8
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Closing surveillance detection gaps for emerging digital drug discourse with ontology-enhanced large language models
npj Digital Public Health - Closing surveillance detection gaps for emerging digital drug discourse with ontology-enhanced large language models
The Events Business Is Relentless. Susan Southerland Made Work-Life Balance Part of the Model.
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Microsoft AI CEO says new model beats OpenAI using less compute
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NVIDIA Joins European Commission Initiative to Expand AI Resources for Science
Oct. 15, 2026 — Much of today’s scientific progress begins with computation. But turning accelerated computing’s potential into scientific progress — modeling climate systems, designing molecules, simulating materials and more — depends on more than breakthrough technology. Especially for smaller labs, early-career scientists or science-based startups, the hardest part of research can be everything that […]
Touchscreen MacBook Pro Could Launch on November 6
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Apple TV 4K 2022 vs. 2026 Buyer's Guide: All Differences Compared
Apple announced the fourth-generation Apple TV 4K earlier this week, introducing the A19 chip, built-in microphones for hands-free Siri, four-speaker HomePod surround sound, and an updated Siri Remote. It replaces the third-generation model introduced in 2022, bringing a number of internal changes while retaining the same basic design and most of the same entertainment features. The new model costs $299 and comes with 128GB of storage.
New Mexico Department of Public Safety Forensic Laboratory: Science in service of justice - NM Department of Public Safety
The New Mexico Department of Public Safety Forensic Laboratory stands as a model of scientific precision and integrity, where expert analysts, rigorous training, cutting-edge technology and state-of-the-art facilities unite in pursuit of justice. From firearms and toolmark analysis to DNA, latent fingerprints, controlled substances, fire debris, and evidence processing, every examination reflects the laboratory’s unwavering […]
How Windows is being optimized for Nvidia’s RTX Spark laptops
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Clinton Policy Institute outlines maternal health solutions for states
Health Care Clinton Policy Institute outlines maternal health solutions for states It’s the first major report from the project, which launched in July to foster nonpartisan policies to improve the wellbeing of children and families. Stephanie Akin 10:00 AM, Oct 15, 2026 Dr. Jacob Lenz performs an ultrasound at the Oklahoma State University obstetrics and gynecology clinic in Tulsa, Okla., on Tuesday, July 16, 2024. (AP Photo/Mary Conlon) The Clinton Policy Institute is calling on states to lead efforts to curb maternal mortality, releasing a 61-page playbook Thursday highlighting successful policies that could be adopted nationwide. The playbook is the first major report from the Clinton Foundation’s project, which launched in July to foster nonpartisan state and local policies to improve the wellbeing of children and families. “Eighty percent of maternal deaths are preventable, and we know what works,” CPI Chair Jennifer Klein said. “The solutions are well established and evidence-based.” CPI’s mission is to convene political leaders from both parties, policy experts, state officials and other stakeholders to explore solutions to longstanding problems. “What we aim to do is bring together people who are deeply engaged, but may not be meeting together in the same room,” Klein said, noting that state policymakers might not always be aware of what their peers are doing in other states. In May, CPI brought together lawmakers from Virginia and Pennsylvania, two of the 14 states that have passed bipartisan maternal health “Momnibus” packages modeled after a comprehensive federal proposal that has repeatedly stalled, called the Black Maternal Health Momnibus Act. Other participants included Dr. Mona Hanna, founder of Rx Kids, a Michigan program that provides direct cash allowances to pregnant women and infants. Pennsylvania Rep. Morgan Cephas, who was part of the group, said she learned about funding opportunities she hadn’t come across during her decade in the Legislature. “As legislators we can issue grants, we can pass legislation, we can move policy, but we want to ensure that funding opportunities and programs that are tackling this issue are sustainable,” Cephas said. The playbook outlines broad areas where state policy can make a difference, such as allowing Medicaid to pay for doulas and remote patient monitoring, and using federal and private grant funding to pay for home visits to pregnant and postpartum women. For each category, it highlights innovative programs that can serve as models, with examples of specific actions state lawmakers and governors’ offices can take. Those include the Rx Kids model, which gets funding from the Michigan state budget; Pennsylvania’s Healthy Moms Vibrant Futures strategic action plan, emphasizing equity-centered maternal care, regional collaboration, Medicaid innovation, and workforce development that was launched this year with more than 160 stakeholders; and Kansas’s Bridging Plan, which reserves three slots and provides at least $26,000 in loan forgiveness for obstetric residents who commit to practicing in rural or underserved communities for 36 months. CPI emphasizes that its work is nonpartisan. Klein, the director of the White House Gender Policy Council under former President Joe Biden, acknowledged that CPI also takes positions on abortion, Medicaid funding, and the need to address the economic and social drivers of poor health, which might rankle some conservatives. “We don’t shy away from talking about those things that we think are part and parcel of the maternal health crisis in this country,” Klein said. “That said, there are so many policies that are both evidence-based and have been tried successfully in both red and blue states, and people can see that they can have real impact.” She pointed to the federal option to extend postpartum Medicaid coverage from 60 days to 12 months that was made available during the Biden administration and has since been adopted by every state but Arkansas. Other initiatives embraced across party lines include Medicaid coverage for midwives and doulas, as well as “bundled” payments for prenatal and postpartum care. That alternative payment model, pioneered in states such as Arkansas, Colorado and Tennessee, incentivizes fixed fees to cover all healthcare services associated with pregnancy and childbirth. Advocates say it promotes more coordination among caregivers, discourages unnecessary interventions, and expands postpartum support. In addition to maternal health, the initiative is also focused on addressing family economic security, children’s well-being, and democracy and civic resilience.
Opinion: How politics and policy are rewriting the rules of parcel delivery
By Daniil DavydoffFollowing the U.S. parcel delivery market can feel like tracking a race. Tactical moves to increase network capacity, build facilities, and launch tools, as well as strategic changes in leadership and operating models, dominate assessments of which carriers are gaining or losing ground, but political and policy forces are shaping those decisions. Labor […] The post Opinion: How politics and policy are rewriting the rules of parcel delivery appeared first on FreightWaves.
Precision weather radar visualization requires better science, not just new tech
Learn how multi-source atmospheric science, GRAF modeling, and precision weather radar visualization create a more accurate representation of surface weather.