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FairFigure Announces New Business Credit Monitoring Features
NEW YORK, NY / ACCESS Newswire / November 2, 2026 / , a business credit monitoring platform, has announced Pulse, Signal, and Unify as its newest features. Available through Premium, the tools help business owners understand their financial information, monitor potential exposure of personal information online, and address inconsistencies in business profile data.
Research: When Workers Adapt Their Resumes to Fit the Political Moment
Job seekers are rewriting their resumes to match the political moment. A new study, which analyzed 2.9 million U.S. workers, found that employees added ESG and DEI language around Biden’s 2020 election and deleted it after Trump’s 2024 victory, mirroring corporate behavior. The research also found that this strategy can be an effective way to earn a new role; those who added such language were more likely to switch employers or be promoted, even though their qualifications tended to be slightly lower. This is because employers tend to sacrifice candidate quality for political alignment. To hire for the long haul, leaders should limit reliance on resume-screening algorithms, prioritize skills and experience, and discount political signals that may soon fade.
Novel e-skin advances personal health monitoring
Innovative nano-engineering uses biocompatible materials to simultaneously monitor cardiac signals and measure sweat metabolites.
Novel e-skin advances personal health monitoring
Innovative nano-engineering uses biocompatible materials to simultaneously monitor cardiac signals and measure sweat metabolites.
Beyond analysis: let’s teach business students to act
How to help postgraduate students interpret real-time data and system behaviour to detect early warning signals, identify emerging disruptions and guide decisions – rather than simply report after the fact
Trump signals he’ll give closing election pitch at the Reflecting Pool, a revamp plagued by problems
WASHINGTON (AP) — President Donald Trump signaled Sunday that he'll make his closing pitch of the midterm elections at the Lincoln Memorial Reflecting Pool , pu
The secret to finding aliens may be hidden in firefly's flashing pattern
A new study suggests we may be overlooking an entirely different approach to finding extraterrestrial signals, one inspired by the flashing patterns of fireflies.
Dave Roberts’ Brewers Admission Could Signal Dodgers Roster Shift
Los Angele Dodgers manager Dave Roberts addressed what lessons that baseball will take from the Milwaukee Brewers success.
Can odors from our bodies signal Alzheimer’s, cancer and other diseases?
For years, scientists have explored how the molecules that waft from our breath or skin might be harnessed to sniff out a variety of ailments. Advancements are turning that potential into reality.
Scientists say a forgotten particle may explain why the universe exists
A mysterious particle overlooked for decades may hold the key to why matter survived the Big Bang, allowing stars, planets, and life to exist. Scientists believe this forgotten neutrino reshaped the early universe and may have left detectable gravitational wave signals that could help unlock the cosmos’s deepest mysteries.
5 Of The Best Leatherman Multitools For Camping
Explore 5 of the best Leatherman multitools for camping: outdoor survival on the Signal, premium ARC MagnaCut, versatile Wave Plus, Skeletool, and Wingman.
Editorial: Making medicine understandable is healthcare’s responsibility
A blood pressure reading that is too high can signal a serious health concern, but recognizing that danger requires patients to understand what the numbers mean. In a study published by the American Heart Association, 55% of patients with inadequate health literacy could not identify a blood pressure reading of 160/100 mm Hg as abnormal....
Our View | Dirty Politics Besmirching Santa Clarita
It shouldn’t be like this in Santa Clarita. The 2026 election cycle has brought upon our fair community multiple instances of dirty politics, potentially libelous campaign advertisements, anonymous hit pieces, […]
FairFigure Announces New Business Credit Monitoring Features
Pulse, Signal, and Unify bring personalized financial summaries, information monitoring, and business profile
How Northwestern Can Slow Dylan Raiola in Week 9 Game at Oregon
Northwestern needs to have the right gameplan to shut down the Ducks' unpredictable signal caller.
Declaring A Health Emergency Is A ‘Signal Of Failure, Not A Starting Point’
The World Health Organization (WHO) declared mpox a public health emergency of international concern (PHEIC), its highest alarm level, twice within two years,
Traffic, business changes: 5 stories in Aggieland to catch up on
Catch up on Bryan-College Station news, including a new traffic signal, Hartt's Barbecue opening, Bryan ISD waivers, racket sports and a restaurant closure.
Vote Republican, or else: how Trump is dangling government help on the campaign trail
President Donald Trump is signaling to states that his administration may be far less likely to help if their voters put Democrats in power on Election Day.
DoorDash is buying Instacart for $17 billion
DoorDash is buying rival Instacart in a deal worth roughly $17 billion, signaling that the delivery wars continues to heat up.
A single brain signal may explain schizophrenia's most puzzling symptoms
Scientists have identified a weakened brain signal that may connect several seemingly unrelated symptoms of schizophrenia, including sensory processing difficulties, disorganized speech, and greater symptom severity. The surprising discovery could help explain the disorder's underlying mechanisms and potentially lead to earlier detection and new treatments.
A golden age of science is coming
It’s almost hard to remember, but just a few years ago, a lot of very smart people thought that science was in terminal decline. Respected researchers were writing papers with titles like “Are Ideas Getting Harder to Find?”, “Papers and patents are becoming less disruptive over time”, and “Slowed canonical progress in large fields of science”. In 1996, science writer John Horgan even published a book called The End Of Science: Facing The Limits Of Knowledge In The Twilight Of The Scientific Age. The fundamental idea was that the Universe only has so many insights to discover, and that we’ve picked the low-hanging fruit. It was the idea that Joseph-Louis Lagrange expressed when he said that “we cannot find more than once a system of the world to establish.” As the big ideas and the simple ideas get mined out, we’re forced to throw ever more brains at the mysteries of nature just to keep scientific progress going at a fraction of its old pace: It looked like science was hitting a wall. Then along came AI. It’s far too early to tell how much AI will eventually speed up the growth of total factor productivity. But already we can see signs of a speedup in science. Anthropic Founder Jack Clark assembled some of the hopeful data points in a recent lecture: [ Dror Poleg@drorpoleg "If you pick different parts of science, you see the same pattern show up: Progress is accelerating, and it has started to accelerate in the last two years." Jack Clark @jackclarkSF I’m speaking at the IMF in an hour about the singularity and why I believe it has begun and the choices we'll need to make. Watch live here: https://t.co/Hj9HzcXx5h 6:08 PM · Oct 18, 2026 · 21.2K Views 2 Replies · 10 Reposts · 123 Likes ](https://x.com/drorpoleg/status/2111882070376980529) Anthropic is accelerating its investment into drug discovery, and is already announcing some impressive preliminary results: [ BioTender@Junioryu136689 BREAKING: Anthropic unveils early results from six Claude-powered drug development collaborations. • 70% shorter CAR-T signaling domain • ~35,000 antibody designs • >10× tighter antibody binding • 89% less batch-record review time Still largely preclinical. Anthropic @AnthropicAI Over the past few months, Anthropic scientists have engaged in deep research partnerships with six organizations developing new medicines. We've also begun drug discovery efforts of our own. In doing so, we’ve learned much more about how Claude can support the many stages of 9:43 PM · Oct 27, 2026 · 11.2K Views 3 Replies · 24 Reposts · 205 Likes ](https://x.com/Junioryu136689/status/2115197821150495150) Claude also appears to be enabling rapid progress toward a treatment for food allergies. OpenAI, meanwhile, announced a possible breakthrough treatment for neurodegenerative disease. Meanwhile, Google Cloud Chief Scientist Pushmeet Kohli has a list of recent scientific advances that have been enabled by its new Gemini model, including breakthroughs in nuclear fusion reactor design, rare disease research, and quantum computing: [ Pushmeet Kohli@pushmeet Gemini 4 Argon is a step change in model performance. In recent weeks, it has had a transformative impact on the Science projects in our team at @GoogleDeepMind and our external collaborators, and helped make a number of remarkable advances across scientific disciplines. 🧵👇 4:47 PM · Oct 13, 2026 · 36.5K Views 8 Replies · 41 Reposts · 497 Likes ](https://x.com/pushmeet/status/2110049807385702623) But as cool as these stories sound, they’re just very minor, preliminary efforts. There are a number of reasons to think that AI is going to propel us into a golden age of scientific discovery. That age might not last forever — AI might still run into diminishing returns eventually. But the next few decades are probably going to be an absolutely amazing time for human science. The number of “effective researchers” is no longer limited The most important input into science is scientists themselves. Until this year, that meant human brains — talented, highly trained human brains. The number of trained human brains could be increased by sending more people to grad school, but only to a point — the smartest people tend to be sent into the hardest research fields first, and if you 10x the number of researchers, the average quality will go down. This constraint was already starting to bite, as Ekerdt and Wu argued in 2024: We argue that a substantial portion of the downward historical trend in U.S. research productivity is a composition effect resulting from self-selection in researcher ability and the dramatic expansion of the research sector…[W]e find that this composition effect has lowered average researcher ability by between 37% and 53%[.] And of course, low fertility was making the problem worse, because fewer children meant fewer people who were able to become future scientists. AI just blows up this constraint completely. If an AI agent can function as an autonomous researcher, there’s no constraint on the number of researchers in the world — you can just build more of them, by building more computer chips and data centers that enable the running of more AI agents. Whether or not massive hordes of agents can collaborate to solve individual problems much faster, increasing the number of agents allows them to tackle many different research questions in parallel. What’s more, these AI “researchers” can be trained incredibly quickly compared to human beings. A human scientist takes decades to train, and more years to reach the frontier of their research field by diligent reading and conversation. This is the “burden of knowledge”, and it’s commonly believed to be one reason ideas have been getting harder to find — by the time human scientists can get up to speed, they’re often so old that their ideas are no longer novel. AI just annihilates this constraint — it can assimilate the entire literature and reach the frontier of research extremely quickly, and it can also tell human scientists where the frontier lies without forcing them to discover that for themselves. It can also pivot to new research directions more easily than humans can. And there’s also a self-reinforcing economic cycle here. Because scientific advances enable higher GDP, they enable more resources to be invested into the creation of yet more electronic “scientists”. Now that doesn’t mean the amount of scientific research goes to infinity — there may still be some essential bottleneck task that human researchers are still needed to perform. There are some indications that AI’s progress on open-ended conceptual research tasks is slower than in other dimensions, and it may be that humans are still needed to provide some of this long-term conceptual thinking. I’d bet against this being true for much longer, but it might be true for a long time. Even in this most “pessimistic” case, though, the amount of effective capital that scientists can use to leverage their work just went up by a lot. AI eliminates the theory bottleneck Science proceeds by an iterative process of theory and experiment. The theory part of that cycle is typically short, but non-trivial — it took a couple of years after the blackbody radiation spectrum was observed for Max Planck to come up with the quantum hypothesis to explain it, and decades longer before quantum theory as we now know it was created. It took about a year for Watson and Crick to figure out the shape of DNA after the requisite data was gathered. AI will basically eliminate the theory bottleneck entirely — or at least shorten the turnaround time between experiment and theory by an order of magnitude. AI is an absolute beast at math. Recently, an OpenAI model solved some of the most important open problems in computer science, math, and theoretical physics, and no one even batted an eyebrow because that sort of triumph is becoming increasingly commonplace. One of those solutions was a proof that the Standard Model of Particle Physics could be mathematically well-defined — a problem that human theorists had so far been unable to tackle. Not all research relies equally on theory, but understanding novel experimental results almost always involves some important component of either mathematical or spatial reasoning. That part of the task has now been made much, much faster. And on top of that, science is now open to a greater number of humans who aren’t naturally good at theorizing. AI can read the whole literature Much of the work of human scientists involves reading and understanding endless amounts of papers and going to endless conferences and seminars. The purpose of that work is to understand the existing scientific literature. Understanding the literature allows scientists to do the following things: Come up with new ideas for hypotheses to test Avoid doing research that someone else has already done Synthesize approaches from different areas or fields AI can reduce this effort to almost zero. Consider this excerpt from OpenAI’s blog post about their new research into neurodegenerative disease: The team divided the analysis among thousands of AI agents powered by GPT‑Rosalind, an approach we call distributed biological reasoning. The agents examined a whole-brain CRISPR atlas…a dataset showing how gene disruptions affect different types of cells across the mouse brain. Each agent investigated a gene disruption, analyzed cellular responses, searched scientific literature, and proposed explanations for the results. Their reports were combined into a reasoning atlas linking genes, cellular effects, relevant publications, and possible biological mechanisms. The research team estimated that comparable human analysis and literature review, conducted one perturbation at a time, would take months to a year. The agents reproduced findings from human analyses while uncovering additional leads. Their assessments of novelty and scientific value also aligned with judgments from blinded human experts. These findings help prioritize further experiments needed to test the proposed biological mechanisms. Some of these insights point to new leads for understanding brain disease. [emphasis mine] This is one case in which parallel work by a large number of agents really does make a huge difference: [ Haider.@haider1 this is actually insane openai deployed thousands of GPT-Rosalind agents to analyze millions of mouse brain cells in 32 minutes, work that could take human researchers months to a year also the agents uncovered new leads for brain diseases like Alzheimer's and Parkinson's OpenAI @OpenAI GPT-Rosalind surfaced a new lead for drug discovery: could restoring cholesterol transport protect neurons from degeneration? DCTN1 is a gene linked to Perry syndrome, a rare neurodegenerative disorder. In mouse-brain data, disrupting it increased expression of genes involved in 2:41 PM · Oct 21, 2026 · 51.5K Views 26 Replies · 95 Reposts · 1.26K Likes ](https://x.com/haider1/status/2112917197903540516) Not only does instantaneous literature review vastly speed up the research process, but it allows AI to make novel conceptual leaps from combining approaches from wildly different fields of research. AI regularly does this in math research, combining results, approaches, and theorems from far-flung places that no human mathematician would have thought to combine. It can do it in science, too. Much of scientific innovation, historically, has been “recombinant” innovation — scientists applying insights from one field to another. With AI, essentially all research is now cross-disciplinary — AI can read not just the literature on a particular subject, but the literature on a million other subjects that might have produced useful techniques or insights for the problem at hand. Superscience So far, all of the factors I’ve listed are ways that AI can speed up science as it’s already done. I’ve basically described how AI can send gigantic hordes of superhumanly fast, superhumanly well-read, superhumanly mathematically gifted researchers to re-accelerate scientific discovery. But it’s also possible that AI will enable types of discovery — and ways of understanding the natural world — that no network of humans, no matter how large or how brilliant it was or how long it had to work, would ever be able to discover. In a post back in July, I wrote about how that might work: What if there are lots of…aspects of the Universe that [are] too complex to understand in terms of simple laws, but not so complex that they just dissolve into unknowable chaos? It’s possible that we can reliably control these complex phenomena with AI, even if we never reduce them to the kind of principles that we can teach a grad student in a textbook… Another way of saying this is that there may be laws of the universe that humans can’t understand but AI can. I call these “cloud laws” — causal regularities that can be exploited by technology, but which are too diffuse and complex for an individual human being to either intuit or communicate… Perhaps social sciences like economics, sociology, and political science obey similarly complex regularities, and AI can help us find them. Perhaps there are physical processes — plasma, or topological materials, or aerial turbulence, etc. — that obey cloud laws instead of chaos?… [H]uman collaboration is bottlenecked — it’s limited by our ability to intuit patterns at an individual level, and to communicate these patterns from one individual to another. AI, being a computer, just doesn’t have this sort of limitation; it can work with vast, diffuse patterns without having to break them into pieces or simplify them in order to compress them into the tiny pipelines of person-to-person explanation… If much of the Universe turns out to be ruled by cloud laws, we could be on the precipice of a scientific renaissance. In order to discover cloud laws, AI will need huge amounts of data about the natural world. AI figured out human speech by assimilating essentially all of the text humans have ever written. If it’s going to figure out hidden patterns in biology, neuroscience, materials science, etc., it’s going to need similarly massive amounts of data from physical instruments. That data will be far, far more than humans — individually or collectively — would be able to parse, label, characterize, or model. But AI was built to do this. If scientists simply build huge arrays of sensors to measure complex phenomena like the brain, the cell, the economy, etc., they may be able to feed this flood of data to AI directly and bypass human cognitive intermediation entirely. AI would then learn about the world directly, and it might learn things that humans never could. This “superscience”, if you want to call it that, would actually go beyond the kind of science humans have done heretofore. Many of the technologies it yielded would be beyond human comprehension — indistinguishable from magic. But to the AIs, they would make perfect scientific sense. In any case, it seems clear that the scientific slowdown that threatened human progress will now be delayed — at least for a while. Unless humans have somehow found most of the actual exploitable regularities in our Universe, we’re about to enter a new golden age of science. Subscribe Share
Global Health & WASH
The US National Institutes of Health reopened its center and program-project machinery in force. NIGMS is funding Collaborative Program Grants for interdisciplinary teams, NIAID opened both its Immune Tolerance Network and a next-generation R&D call, the NCI runs its Carcinogen Hazard Assessment Monographs program, the National Library of Medicine is funding institutional training in biomedical AI and data science, and NIH reopened its Centers for AIDS Research. The tell: these pay for standing centers and multi-year consortia at institutions with an existing funded research base, not one-off projects, so the fit is an established US research institution, not a single investigator. Disease-specific foundations are again funding the researcher, not just the research. The Parkinson’s Foundation opened its Paul Oreffice Innovations in Care Award and the National Ataxia Foundation its Research Seed Money Grant. The tell, the same one we flagged last cycle, is a named early-career or seed award that builds a pipeline of scientists committed to one condition, so what wins is a researcher willing to specialize. The post-USAID global-health money is routing through a State Department program statement and multilateral innovation funds. The US Department of State’s Bureau of Global Health Security and Diplomacy opened its Advancing Global Health Annual Program Statement, Grand Challenges Canada opened Nexa Lighthouse for climate and health innovation in Asia and the Pacific at USD $250,000 to $2,000,000, and CEPI opened a rolling call on vaccine-manufacturing analytics. The tell: the largest health money this cycle sits in a standing program statement and in staged innovation vehicles, not in a single bilateral grant. Total Estimated Funding Pool: ~$35.4M across discrete grants. (Separately, large national-formula envelopes not counted in this total: U.S. Department of State, Bureau of Global Health Security and Diplomacy (GHSD).) This post is for paid subscribers. This helps support the time and effort it takes to curate and organize these opportunities. Subscribe To keep this accessible to everyone who needs it, we’re happy to offer pay what you can rates. You can find more details here. New opportunities: Paul Oreffice Innovations in Care Award, Parkinson’s Foundation. *New!* *Closing soon!* The Parkinson’s Foundation created the Paul Oreffice Innovations in Care Award to fund clinicians rethinking how people with Parkinson’s disease receive care. The Foundation is using pilot funding to move promising ideas into testable projects, backing work across four lanes: strengthening community clinician capability, redesigning care models, building patient-centered technologies, and defining the minimum clinical datasets that make better standards possible. It wants hypothesis-driven, clinically grounded projects that can generate evidence strong enough to attract further funding. By opening the door to clinicians at every career stage and strongly preferring projects that involve people with Parkinson’s in their design, the Foundation signals that it values practical, patient-shaped innovation over prestige. The strongest fits are US-licensed clinicians with a focus on Parkinson’s and an institutional home for applied care research. Geographies: united states. Who can apply: Clinicians of all career stages, from fellows to established faculty, who are licensed to care for patients in the United States and have a significant focus on Parkinson’s disease. Physicians must have completed a neurology residency (or justify how their training pathway benefits people with PD); allied health professionals must hold an advanced degree, typically a PhD. Fellows, those in mentored positions, and those within two years of starting an independent position require a mentor and a mentor support letter. The sponsoring institution’s grants office is the authorized recipient and funds are disbursed to the institution. Funding amount: Maximum of $200,000 over two years; up to three awards. Targeted Sectors / SDGs: Health; Innovation; Science & Technology. Deadline: November 1, 2026. Learn more and apply here. Design and Deliver the Next EIT Health Bootcamps, EIT Health. *New!* *Closing soon!* EIT Health is opening its call for consortia to design and deliver the next generation of its health start-up bootcamps, funding the curriculum, masterclasses, mentoring, and investor engagement that turn early health ventures into fundable companies. The organization is using these learning paths to strengthen Europe’s health innovation pipeline across digital health evidence, deep tech and AI commercialization, cross-border investment, and patient access. What EIT Health wants to back is not a single course but durable delivery capacity built by partners who span industry, education, and research. Requiring multi-country consortia and a revenue-sharing stake in the programs signals that EIT Health expects these bootcamps to outlast the grant. The strongest fits are established training providers, universities, and industry partners with proven reach into health entrepreneurs. Geographies: Europe. Who can apply: Consortia only (individuals cannot apply), comprising a minimum of two and a maximum of five independent legal entities. Partners must cover at least two sides of the Knowledge Triangle (industry, education, research), including at least one industry organisation, and at least two entities must be legally established in different Horizon Europe countries. Funding amount: Foundational Learning Path: up to EUR €112,000; Thematic Learning Paths: up to EUR €124,500 per path (up to four thematic projects); up to EUR €610,000 total EIT Health funding available under the call. Targeted Sectors / SDGs: Health; Innovation; Science & Technology; Economic Development & Livelihoods. Deadline: November 2, 2026. Learn more and apply here. Technology Transfer Offices & Entrepreneurship Support Call (Beyond the Lab: From Research to Venture), EIT Health. *New!* *Closing soon!* EIT Health is opening its Technology Transfer Offices and Entrepreneurship Support Call to fund consortia that will deliver the Beyond the Lab: From Research to Venture program for healthcare researchers. EIT Health is using the grant to build local capacity for turning laboratory science into incorporated start-ups, paying experienced technology transfer offices and entrepreneurship support providers to run masterclasses, structured mentoring, and a closing Pitch Day across two cohorts. It wants to back organizations that can walk researchers from discovery to company formation, not just teach theory. Requiring two transfer offices plus one venture-building provider signals that EIT Health values proven commercialization experience alongside academic reach. The strongest fits are European research-commercialization teams with a track record of moving health innovations toward investable ventures. Geographies: Europe. Who can apply: A consortium of two Technology Transfer Offices (representing higher education institutions or research organisations) and one Entrepreneurship Support Provider with demonstrated experience in venture building and start-up support. Applicants may apply for more than one learning path where they can demonstrate the required expertise and capacity for each. Funding amount: Up to EUR €77,000 in 2027 and up to EUR €77,000 in 2028 (up to EUR €154,000 total per consortium over two years). Targeted Sectors / SDGs: Health; Innovation; Science & Technology; Economic Development & Livelihoods. Deadline: November 2, 2026. Learn more and apply here. EIT Health RIS Country Representatives Call (2027-2028), EIT Health. *New!* *Closing soon!* EIT Health is seeking organizations to serve as Country Representatives across eleven Regional Innovation Scheme countries in central and eastern Europe for the 2027 to 2028 period. The money funds a national anchor in each country, an organization that maps the local health innovation ecosystem, connects startups and researchers to EIT Health programs, and builds the stakeholder relationships that let health ventures grow. EIT Health is backing local capacity rather than individual projects, which is why it accepts both single organizations and national consortia that span education, research, and industry. The requirement for co-financing signals that it wants representatives already embedded in their national systems. The strongest fits are established ecosystem builders with deep ties to health innovation stakeholders in one eligible country. Geographies: Croatia; Czech Republic; Estonia; Greece; Hungary; Latvia; Malta; Romania; Serbia; Slovenia; Turkey. Who can apply: Registered legal entities established in one of the eligible EIT RIS countries. Single organisations or national consortia may apply. Consortia must include at least two sides of the Knowledge Triangle (education, research and industry), and all consortium partners must be established in the same eligible country. Suitable applicants have demonstrated experience in healthcare innovation ecosystem development, innovation support and entrepreneurship, start-up acceleration, technology transfer, research and higher education, business support, and stakeholder engagement, with strong links to national innovation stakeholders. Funding amount: Up to EUR €182,000 per Country Representative (maximum funding per project); total call budget up to EUR €1,274,500; EIT Health funds up to 60% of total eligible project costs. Targeted Sectors / SDGs: Health; Innovation; Science & Technology; Economic Development & Livelihoods. Deadline: November 2, 2026. Learn more and apply here. Architects of Trust: Community-Driven Demand Creation for New TB Vaccines, Treatment Action Group (TAG). *New!* *Closing soon!* Treatment Action Group, with funding from Wellcome, is opening its Architects of Trust call to help communities prepare for the new tuberculosis vaccines now moving through late-stage trials. The money backs civil society and community-based organizations to raise awareness, surface local questions and concerns, and press policymakers toward equitable national rollout. By pairing each grantee with an advocacy mentor and running a strategy workshop alongside the Global TB Vaccine Forum, Treatment Action Group is building a durable advocacy bench rather than funding one-off outreach. The two-stage design, starting with a short expression of interest, signals that fit and community rootedness matter more than polished proposals. The strongest fits are locally trusted groups with real TB, immunization, or health advocacy experience and a committed project lead. Geographies: Brazil; Ethiopia; India; Indonesia; Kenya; Malawi; Mozambique; Nigeria; Peru; Philippines; South Africa; Tanzania; Vietnam; Zambia. Who can apply: National, subnational, or regional civil society organizations (CSOs) or community-based organizations based in one of the 14 eligible countries or in Eastern Europe/Central Asia regional networks, with experience in TB, immunization, or other health advocacy and in community engagement or policy advocacy; well integrated into stakeholder networks with membership or affiliation to other CSO or community networks; naming a dedicated project lead (’architect of trust’) who can attend the April 2027 Zaragoza forum in person; and holding (or committing to adopt) organizational policies on safeguarding (bullying, harassment, abuse, and harm), equity, diversity and inclusion, and legal compliance, research practice and governance. Funding amount: Grants of up to US$45,000 will be awarded to 8 CSO partners across 14 high-TB-burden countries plus regional networks in Eastern Europe and Central Asia; each grant funds 12 months of work. Targeted Sectors / SDGs: Health; Governance; Policy & Advocacy. Deadline: November 4, 2026. Learn more and apply here.
People in tune with their bodies pay a lower health price for politics, without switching off
A study of more than 2,000 Americans across two elections found that people who notice and trust their body's signals reported fewer physical, emotional, behavioral and social costs from politics, and ...
People in tune with their bodies pay a lower health price for politics, without switching off
A study of more than 2,000 Americans across two elections found that people who notice and trust their body's signals reported fewer physical, emotional, behavioral and social costs from politics, and ...
Inovio Hires Todd Strategy Group to Lobby on Health Issues
Inovio hired Todd Strategy Group as its outside health lobbyist. Read the full filing details and what this move signals for its broader lobbying strategy.
Flutter Entertainment options signal 9.5% move on earnings
Flutter Entertainment options signal 9.5% move on earnings
Packers’ HC Signals Starting Offensive Line Change
The Green Bay Packers might be without starting right guard Travis Glover for their Week 8 game against the Carolina Panthers. The team plays on Thursday Night Football and Glover has not practiced on the estimated injury report for Monday or Tuesday. Head coach Matt LaFleur made it clear that his current injury status will […] The post Packers’ HC Signals Starting Offensive Line Change appeared first on HEAVY.
US goods trade deficit unexpectedly widens in September
The US goods trade deficit widened to $134.9 billion in September due to increased imports, signaling a drag on third-quarter economic growth.
The next phase of military rule in Egypt is here
El-Sisi’s announcement that he will not run for a fourth term may signal a new leadership arrangement.
Why Trump’s latest election warning is impossible to ignore
When President Donald Trump signals he might not accept the result of an election, he’s worth taking seriously.
Stan Wawrinka’s Remarkable Career Comes to an End
When the chair umpire called game, set and match to signal the end of day one at this year’s ATP 500 event in Basel, it also signaled the end of the career of one of the truly iconic tennis players of all time, as Stan Wawrinka had played his final career point. A three-time Major …
Texas political leaders debate Donald Trump visits as midterm races tighten
RNC Chair Joe Gruters and Texas Democratic Chair Kendall Scudder debate whether repeated Texas visits by Donald Trump and heavy GOP spending signal tight statewide races or routine midterm turnout efforts.
Zelda 40th Anniversary Nintendo Switch 2 restock signals good news for launch day buyers
📅 The Zelda 40th Anniversary Switch 2 releases on Thursday, October 27 🚨 Our Zelda Switch 2 restock tracker @mattswider on X will send out an alert when stock appears 😲 Nintendo Store held a surprise restock yesterday, which is good news for other retailers 🙏 It suggests other retailers may be holding back launch day stock, too Walmart: Zelda Switch 2 console Best Buy: Zelda Switch 2 console GameStop: Zelda Switch 2 console Target: Zelda Switch 2 console Nintendo: Zelda Switch 2 console 🚨 We’re tracking Zelda Switch 2 stock updates. If you’d like to know when more stock arrives, follow Matt Swider on X and turn on notifications. You can also become a free or paid subscriber to The Shortcut to help support our work. 🚨 🚨 Want the Zelda 40th Anniversary Switch 2? Drop your email for restock alerts before it sells out. ⤵️ Subscribe We predicted that a Legend of Zelda 40th Anniversary Switch 2 restock would happen on launch day, October 29, and we’re now even more confident after the Nintendo Store’s surprise restock yesterday. Our followers were the first to know that the Zelda Switch 2 was back in stock at the Nintendo Store, and the console even promised to arrive on launch day if you managed to secure one. [ Matt Swider (The Shortcut)@mattswider ](https://x.com/mattswider/status/2114758291322757239?s=20) Zelda Switch 2 console in stock at the Nintendo Store nintendo.com/us/store/produ… 4:37 PM · Oct 26, 2026 · 67K Views 18 Replies · 4 Reposts · 75 Likes It strongly suggests that other retailers such as Walmart, Target, GameStop, Amazon and Best Buy will have more units – albeit in limited quantities – on launch day for those who currently don’t have a pre-order. Retailers often hold back stock for launch day buyers who haven’t pre-ordered. Cancellations can also occur in the run up to release, meaning more stock is made available that was previously snapped up. Zelda Switch 2 restock – why Walmart will have stock Walmart historically holds back extra stock for launch day, and we’re expecting the same to happen on October 29. As the largest retailer in the US, it usually has the biggest stock allocation, and Thursday and Friday mornings is when the retailer tends to offer restocks online. As we mentioned previously, Nintendo was also a retailer to watch – and it went live with a restock earlier than we thought. It had previously promised the Zelda 40th anniversary Switch 2 would be “replenished”, and it offered a limited amount of stock for those who were lucky enough to snag one. (Hint: Followers of Matt Swider on X and our restock tracker were first in line.) We’re expecting other retailers like Target, GameStop and Amazon to get a new wave consoles on launch day, and we’ll notify you if and when any Zelda Switch 2 restocks appear. Why you should follow our Zelda Switch 2 restock tracker Remember when you couldn’t find a PS5 for nearly two years? Not our followers. We helped over 400,000 people buy Sony’s console when it was in and out of stock, and we’ve since made it our goal to help our subscribers bag hard-to-find times. We’ve done the same with the PS5 30th anniversary edition, Nintendo Switch 2, and many more in-demand products. With up-to-the-second US store inventory checks, The Shortcut and Matt Swider on X offers exclusive Zelda 40th anniversary Switch restock updates. You’ll also receive an instant notification on X (if set to on) as soon as new stock arrives. Up next: Zelda 40th Anniversary Switch 2 Pro Controller restock looks increasingly likely at Nintendo Store Subscribe Adam Vjestica is The Shortcut’s Senior Editor. Formerly TechRadar’s Gaming Hardware Editor, Adam has also worked at Nintendo of Europe as a Content Marketing Editor, where he helped launch the Nintendo Switch. He also runs a retro gaming YouTube channel called Game on, boy! Follow him on X @ItsMrProducts.
Sanford Health says it will end contract with Wellmark insurance
Sanford has signaled its intent to end its contract with Wellmark. If contract negotiations fail, around 130,000 patients in South Dakota and northwest Iowa could be affected. Sanford's Nick Olson explains the move.
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Scientists Built a Virtual ‘Torture Chamber’ for AI. What It Revealed Is Deeply Unsettling.
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A New Way to Think About Women’s Heart Health
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Ukraine making signal repeater drones to help other drones fly further
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Skip Bayless Has Bold Vikings Declaration After Bears Win
Skip Bayless doubled down on his belief that the Minnesota Vikings will win the NFC North despite the Chicago Bears’ recent victory, keeping the division race firmly in the spotlight. The outspoken sports commentator’s prediction signals that he remains confident in Minnesota’s chances as the NFC North contenders continue to battle for position. The Bears’ […] The post Skip Bayless Has Bold Vikings Declaration After Bears Win appeared first on Gridiron Heroics.
QB Coach McKenzie Milton Hopes UCF Can Sustain Success
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Baker’s Back: Buccaneers HC Confirms Mayfield Set to Start
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Trump administration sends mixed signals on curbing Ukraine’s Starshield access
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Surprising new pattern of groundwater loss may signal a turning point for the Colorado River Basin
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What Does Tulane Need From Trace Johnson This Weekend?
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Commission announces plan for polar hub to step up research coordination
The European Commission plans to develop an EU polar research hub to strengthen coordination and improve the alignment between science and policy. The objective, according to a Commission official, is to “better connect research, observation and scientific infrastructure, improve access to research resources and strengthen coordination with stakeholders, including Indigenous people.”Announced in a new EU Arctic strategy on October 20, there is little detail yet on how the hub will be implemented, only that it will “reinforce and expand” the European Polar Coordination Office (EPCO), which is hosted and managed by the European Polar Board (EPB) at Umeå University in Sweden. EPCO was born from the EU-PolarNet projects funded through Horizon 2020 and currently coordinates the EU Polar Cluster, a network of EU-funded collaborative polar projects.While the practical details remain to be defined, the decision sends “a clear and positive signal,” said Maria Grigoratou, head of EPCO and executive secretary of EPB. “By reinforcing EPCO, the Commission has an opportunity to build on the legacy of EU-PolarNet 2, strengthen European polar research coordination and expand cooperation with a broader range of Arctic stakeholders,” she told Science|Business.The move has been welcomed by the polar research community. “The polar research hub could play an important role in connecting existing research communities, observation systems and infrastructure, and in bringing scientific knowledge closer to policymaking, in cooperation with local communities and Indigenous people,” said Katrine Moland Hansen, director of operations at Norway’s Nansen Environmental and Remote Sensing Center.But money will be an issue. “It is clear that EPCO will need more resources and structure to function well and to make research reach policymakers,” said Kati Lindström, vice-chair of the Polar Research Committee of the Estonian Academy of Sciences. “European polar research is big if we pool the resources, and it should not only be left to enthusiastic scientists to develop networks of strategic importance in their free time.”The Arctic strategy makes a point of saying that local communities should have a greater involvement in Arctic science. “All EU Arctic research consortia are mandated to invite Indigenous people representatives to participate in projects,” it reads. “The EU also supports research that is directly led by Indigenous communities and address their challenges.”It also underlines the importance of reinforcing collaboration with like-minded partners such as Norway, Iceland, Canada, the UK, Japan and South Korea, as well as deepening its engagement with NATO. This includes the US, with which “the EU is committed to continuing a pragmatic transatlantic engagement based on shared interests and values.”Related articlesViewpoint: Does Europe dare to invest in the Arctic?Anchor Greenlanders in Arctic climate research, experts tell EU ahead of policy updateFor Moland Hansen, this open and inclusive approach to cooperation is encouraging. “The Arctic is also a strong example of why equal participation of associated countries in EU funding instruments matters.”Overall, she finds the new Arctic strategy to be ambitious, timely and comprehensive. “We particularly welcome the recognition that climate change, environmental protection, security, resilience and competitiveness are closely interconnected,” she said. “Research, observations and forecasting capabilities are essential to understanding the rapid changes taking place in the Arctic and addressing these challenges together.”Security focusWhile the Arctic strategy foregrounds security, with pledges to protect undersea cables, boost satellite monitoring, deploy more icebreakers and improve military mobility, the polar community is satisfied that environmental concerns have not been forgotten.“It is inevitable that there is a strong security angle to the EU Arctic strategy, but the impact of climate change and need for climate mitigation and resilience is also strongly recognised and includes a pledge to stay the course on climate commitments,” said Sian Prior, lead advisor to the Clean Arctic Alliance, a coalition of campaigning non-profit organisations.“We need to remember that by the time the next Multiannual Financial Framework comes to an end, in 2034, the polar regions, especially the Arctic region, will be living under a new reality when it comes to ecosystem processes, when it comes to the climate,” Grigoratou went on. “And that will affect any ambition that humans may have in the region.”Lindström agreed. “All aspects of European security are dependent on climate change in the Arctic and consequently, on climate science,” she said. “We cannot close our eyes to issues like energy security, critical minerals, northern shipping routes, dual-use technologies and others. However, it remains to be seen how well the promises to protect the environment and Indigenous rights will hold when faced with critical mineral extraction under the Critical Minerals Act.”
Kansas City Chiefs React to Patrick Mahomes’ Career News
The Kansas City Chiefs have another reason to celebrate Patrick Mahomes after the franchise quarterback reached a career milestone that places him alongside one of the NFL’s greatest players. His latest achievement reinforces his remarkable consistency and highlights how quickly he has established himself among the league’s elite signal-callers. Mahomes tied Tom Brady for the […] The post Kansas City Chiefs React to Patrick Mahomes’ Career News appeared first on Gridiron Heroics.
Google Cloud, DeepMind, and the EU: A New Model for AI-Driven Science
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Ohio State faces a major test without Julian Sayin
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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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