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More than 70 Minnesota children detained during ICE surge, state report finds
A preliminary report from a council established by Gov. Tim Walz details the toll of the federal immigration crackdown on children, schools and the state’s economy.
Zohranomics 101: How Mamdani is reshaping NYC's $1.3 trillion economy
A year after Zohran Mamdani's election, a slow-motion economic revolution is underway — from small wins and filled potholes to rent freezes.
North Carolina early voting tops 2 million as voters cite economy, health care concerns
More than 2 million North Carolinians cast ballots during early voting ahead of Election Day.
Kerrigan in the DC Journal: America's Innovation Economy Runs on Small Business - Why Protecting Bayh-Dole Matters - Small Business & Entrepreneurship Council
In an Op-Ed published in the DC Journal this week and now appearing in local newspapers across the country, SBE Council President & CEO Karen Kerrigan highlights the indispensable role of small businesses and startups in driving American innovation, technological advancement, and economic growth. Kerrigan points to the extraordinary success of the bipartisan Bayh-Dole Act, […]
US Rep Jim Clyburn says Colom election is key for voting rights laws
The economy is key for most voters in the midterm elections. The future of the Voting Rights Act is top of mind for many in the South as well.
Local business confidence concerns have eased compared with 2025, index shows
Southern Nevada business leaders are still feeling uncertain about the economy’s future, but fears have eased when it comes to hiring, sales and profits, according to a new report.
Lines Under the Sea: The Politics of the Middle East’s Data Corridors
The Middle East is using fiber to rebuild the transit economy it once framed around oil and the Suez Canal. Which routes get laid will depend as much on security and sovereignty as on engineering, with the question of Palestine central to the choice
Why Hollywood Is Turning Food Into Its Next Business Opportunity
Explore how the 2026 L.A. Times Food Bowl, BLXST’s Everytable partnership and the creator economy reveal new business opportunities in food and entertainment.
Small business Saturday, culinary edition
Small Business Saturday falls on November 28th this year, the Saturday after Thanksgiving, and it’s the perfect time to strengthen the Island’s local economy by promoting the importance of small businesses. Because the reality is that supporting local businesses isn’t just about shopping, it’s about investing in the well-being of our community. When we purchase […]
Column: America’s innovation economy runs on small business
Small businesses are the engine of America’s economic and technological future, and the Trump administration knows it. Administration officials have repeatedly cited startup formation and entrepreneurship as key to addressing the nation’s m…
The politics of war
Israel went to the polls last Tuesday and it is the turn of the United States next Tuesday. The differences in the two elections are self-evident. Compared with the US, which has favourable geography and does everything at scale, Israel is tiny and part of an unstable region. For its elections, it has adopted an almost pure form of proportional representation based on lists. This encourages multiple parties and can make it almost impossible to form a government, as we can now see. The US system is complex in its own way but discourages third parties. Yet for all the differences in size, geography, and political systems, the fates of the two countries are closely connected. Israel has come to depend on the US to sustain its military strength, and over the past few tumultuous years that dependence has created resentment in the United States. The Biden administration was punished for appearing to give Netanyahu a blank check after the Hamas attacks of 7 October 2023, and not holding Israel back as it employed ruthless tactics in Gaza. Because of the treatment of Palestinians, American views of Israel have grown progressively more negative over the past few years. Only a third now support the Israeli government. While on the left, this is largely because of how Israeli forces have operated in Gaza and, more recently, how the settler movement has behaved in the West Bank, for the American right the issue has been about how Benjamin Netanyahu persuaded Donald Trump to forget his wariness about more Middle Eastern wars and agree to a joint attack on Iran, which has gone badly wrong. The Palestine question was not a big issue for the two large Jewish blocs in last Tuesday’s election. Both supported a tough response to Hamas after October 2023 and neither accepts a two-state solution. It was, however, the threat posed by the ethno-nationalist policies of Itamar Ben-Gvir and Bezalel Smotrich, the two extreme members of Netanyahu’s coalition, and their tolerance, even encouragement, of settler violence, that brought out the Arab voters. (In principle this should strengthen their position though to turn into real power would require the ‘Change Bloc’ overcoming their opposition to involving Arab parties. The alternatives are a National Unity government, defection from the Change Bloc to Netanyahu, or deadlock and another round of elections in the new year.) There was also broad support for the war against Iran among the Jewish parties. The difficulty here is that the objectives behind the war have yet to be met, and that continuing with military operations depends on the United States. In this way the two elections have come together at a crucial moment. If Netanyahu hoped that a victory over Iran would help him retain his majority, cementing his legacy as an Israeli war leader, it did not work out that way. Trump also expected a great victory about which he could boast. He promised at most the end of a hateful and aggressive regime, with a record of hostility to both the United States and Israel, or at least the elimination of Iran’s military capabilities and the end of its nuclear programme. Eight months on, there is not much to boast about; vital objectives remain elusive: the Iranian regime is even more hardline than before; the international economy is barely coping with the closure of the Strait of Hormuz; and Saudi Arabia is struggling with an unwanted conflict with the Yemeni Houthis. For all these reasons, the Iran War has been a dark cloud hanging over both elections. Yet the issue has been approached in different ways. Netanyahu sought to push the issue before the election while Trump has been more cautious. Trump’s essential claim is that there is nothing to worry about and he’s still working out what final steps need to be taken to provide a definitive conclusion to the conflict. Netanyahu’s final pitch was that there was lots to worry about. He focused on Israel’s dire security situation, with the Iran War unfinished and the prospect of imminent economic isolation because of international sanctions. For him it is imperative to defeat Iran decisively, and without delay. Why this different response to the same war? Part of the answer lies in how public opinion in the two countries responded to the war. In this post, I show how this came about. We await the outcome of the US midterms but know the result, at least in terms of the share of the vote if not yet the shape of the new government, of the Israeli election. With the elections out of the way Netanyahu is pressing for another round in the war. Trump is less sure. I conclude with thoughts on the importance of how he decides.
Duets Launches a New Ecosystem for Startups Building in Sports and Entertainment
LOS ANGELES, October 29, 2026--Duets launches today to help startups in sports, entertainment and the creator economy find the people, support and funding they need to grow.
U.S. economy grew at a fast clip in 3rd quarter, thanks to consumer spending
The economy grew at an annual rate of 3.4 percent.
TAAG Angloa partners with AirFi to deliver In-Flight Entertainment
TAAG Angola Airlines, the national carrier of Angola, has entered into a partnership with AirFi to deploy AirFi’s portable streaming in-flight entertainment solution (IFE) across the airline’s mixed fleet of long-haul and regional aircraft. Together, the partners aim to enhance the digital journey for TAAG Angola passengers by delivering modern in-flight entertainment services, which they […]
Trump defends war in Iran, tariffs during Texas campaign swing
Despite polls showing most Texans disapprove of the president's handling of the economy and the war in Iran, Trump can’t stop talking about both.
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
Gallup: Economy, Health Care and Iran Top Voter Concerns Ahead of Midterms
The economy, healthcare, and the war in Iran rank highest in importance to U.S. voters ahead of this week's midterms, according to the latest Gallup poll. With the election five days away, voter responses reflect pushback against President Donald Trump's economic platform and foreign policy agenda.
The midterms will decide who holds power. But who will answer for the broken promises?
Voters are demanding more than partisan rhetoric as they head to the polls to decide the future of the economy.
The Key: Politics in Research a Danger to Innovation
Since the Bayh-Dole Act passed in 1980, the commercialization of federally funded research has contributed trillions of dollars to the American economy and made possible the launch of tens of thousands of start-ups, according to the Bayh-Dole Coalition. Inventions like Google’s search engine, tests for cervical cancer, lithium car battery recycling and high-definition video and audio are all products of the Bayh-Dole system. U.S.
Memphis voters cite economy, health care, and local issues as early voting numbers outpace 2022
One day remains to vote early in Tennessee, and state data shows early voting numbers are outpacing 2022.
Fed hits pause on interest rates
Welcome to The Hill’s Business & Economy newsletter{beacon} Business & Economy Business & Economy The Big Story Fed holds rate steady ahead of midterms Federal Re…
Surprise: The Google Xreal glasses debut at a Meta-beating $1,099
A price drop before launch? In this economy?
V47 Entertainment, VIRTUE Asia and COL Group Reveal 2027 Microdrama Line Up
Launched at Inside Microdramas, the world's first dedicated upfront for microdramas and the vertical entertainment economy, the slate showcases formats designed for the next phase of brand storytelling
Creators are now classified as small businesses, but what does that actually mean?
The Small Business Administration has officially welcomed creators; we unpack what that means for brands, creators, and the economy at large.
Understanding Latin America’s Rightward Political Shift
Latin America has experienced a rightward political shift in recent years, driven largely by voters’ growing concerns over crime, security, and the economy. Experts say the reelection of left-wing President Luiz Inácio Lula da Silva in Brazil bucks this trend, but doesn’t halt it.
From 'socialist' to 'pedophile,' 2026 political ads are betting on fear, anger
A week from Election Day, TV screens across Arizona are filled with campaign ads. But one expert wonders why they’re not talking about the economy, and the role Republicans have played in it.
Amo Celebrates $1.2 Million Federal Investment in Cumberland Stormwater Improvements to Protect Local Businesses and Jobs
Cumberland, RI – TODAY, Congressman Gabe Amo (D-RI-01) joined local leaders today to celebrate the completion of a $1.2 million stormwater infrastructure project along Industrial Road, helping Cumberland address chronic flooding in its largest commercial area and better protect the businesses, workers, and infrastructure that keep its economy moving.
Opinion: Chicago’s push to protect gig workers threatens their independence
Chicago's delivery rules risk gig worker flexibility. States should offer portable benefits, argues an Americans for a Modern Economy adviser.
Business, Society, and Seven Flights: Reflections from My First Recruitment Tour Across India
Michael R. Myers, SOM’s director of admissions for strategic priorities and community engagement, traveled to five cities to meet prospective MBA students and explore the country’s vibrant economy and culture.
No on 87; it will hurt state’s businesses, economy
When I left public service as deputy mayor of Denver, I took with me a conviction that the people who build businesses here are the ones who keep Colorado moving. I started my first company, Seca Secure, from my dining room table with a simple goal: provide good customer service and quality Security equipment to […]
Workers are getting a shrinking slice of America’s economic pie
The US economy continues to grow at a relatively healthy pace, but American workers aren’t fully reaping the financial rewards.
Economy, 'political homelessness' is top of mind for Ohio voters
Morning Edition Host Amy Eddings is back with another installment of the Ideastream election series that interviews voters from the Mahoning Valley ahead of the midterms.
Trump, ignoring polls, predicts economy to help Republicans in midterms
By Trevor Hunnicutt CORINTH, Mississippi, Oct 26 (Reuters) - US President Donald Trump campaigned on Monday in deeply Republican Mississippi, predicting victory for a Republican Senate candidate based
Miller-Meeks focuses on health care, economy as Election Day nears
The Republican is emphasizing her medical background, conservative priorities and efforts to bring federal investment to southeast Iowa
Bioeconomy Needs Supply Chains and Science: David Zilberman
UC Berkeley economist David Zilberman outlines how biotechnology, circular supply chains, and regulation are vital to scale the global bioeconomy.
Opinion: City Hall keeps asking small businesses for more. Enough is enough.
And as City Hall debates how to close another budget deficit, I hope we remember that the small businesses we’re asking to pay more are the very ones we depend on to grow our economy.
The sleeper issue that could decide the U.S. Senate race in Texas
Voters from both parties consistently rank the issue second only to the economy and high prices
Tulane political science professors discuss Iran war, international policy
The Tulane Journal of Policy and Political Economy hosted a panel of Tulane University professors to discuss the 2026 Iran war last Thursday. Christopher Fettweis, an associate professor of political science, began the panel by discussing the Twelve-Day War that occurred in June 2025 between Iran and Israel. “The Iranians were nowhere near nuclear weapons...
The Political Calculus Behind Newsom’s Opposition to California’s Billionaire Tax
Proposition 40 proponents say the tax would help backfill federal Medical cuts. But as Newsom weighs a presidential run, is he also looking ahead to how it might play to donors and voters?
Voters’ rising ire at corruption plays central role in Texas Senate race
The race between Ken Paxton (R) and James Talarico (D) has revolved around the issue that’s a top voter concern, just behind the economy.
City Spotlight 2026
City Spotlight from the Orange County Business Journal explores Anaheim and Riverside: the projects, industries and leaders shaping each city’s economy.
Local businesses weather the effects of international Geneva cuts
For nearly two years, restaurants, hotels, and other parts of the local economy have grappled with the effects of international Geneva job and budget cuts, particularly around the Nations quarter. Two publicly backed studies are now seeking to quantify the losses.
Obama and Trump wage one last battle for even more urgent stakes
Two decades ago, Barack Obama stormed battleground states rebuking a Republican president over a deeply unpopular war and an economy that was crushing working Americans.
Cutting ‘red tape’ is nothing but a red herring
Blaming a moribund economy on too many rules is a hackneyed neoliberal trope – UK plc needs smarter regulation, not less regulation
Commentary: Getting beyond the ideological force behind Michigan’s political and economic woes
The economy consistently ranks among the leading problems cited by voters in Michigan, sentiment that is supported by the evidence.
Iran, Kyrgyzstan seek to expand science and technology cooperation
TEHRAN – Iranian and Kyrgyz officials have called for expanded cooperation in science and technology during a meeting on the sidelines of the 5th World Creative Economy Conference in Jakarta.
Syracuse University wants you to know its Center for the Creator Economy means business
Syracuse University hosted its second annual 'Cuse Creator Con, highlighting content creation as a multi-billion dollar industry.
Jeffrey Epstein has been everywhere this campaign season. But voters wonder how much he should matter
Candidates are spending millions to link their opponents to Jeffrey Epstein and his associates. But in one of the nation’s marquee Senate contests, many Ohio voters told CNN that prices, healthcare and the economy matter more.
Why young men are losing faith in Trump’s economy
On a recent crisp college football Saturday, Michigan State senior Zach Larson sat in a lawn chair sipping a can of Modelo that he said cost nearly twice as much as it did when he was a freshman.
Digging Into the Money Behind the US Healthcare System
Healthcare makes up a growing share of the U.S. economy — and household budgets. We break down how much money the nation is spending and on what.
The Collaboration Economy: Independent Contractors Are Essential to Small Business Growth - Small Business & Entrepreneurship Council
SBE Council Small Business Check Up Survey: Nearly half of small business employers use independent contractors, highlighting their role as a force multiplier for growth and the importance of policies that protect flexibility, choice, and entrepreneurship. By Karen Kerrigan – Independent contractors are an essential part of America’s economy, providing specialized expertise, flexibility, and the […]
New Report Highlights How Private Credit Powers Businesses Across America
Dunham: "Private credit direct lending plays a critical role in our economy, supporting countless small and midsized businesses across the U.S."
Op-ed: Brooklyn’s small businesses can’t wait any longer on child care
Brooklyn is home to more than 74,000 businesses, and the vast majority are small. You cannot build a competitive workforce, or a healthy economy, on top of a broken child care system.
79% of Small Business Owners Put Personal Money Into Their Business in the Past Year, New Flute Report Finds
Flute, the payments platform for the everyday economy, released "The Cost of Waiting To Get Paid," a report finding that 79% of small business owners put personal money into their businesses in the past year.
Trump, tariffs and health care: Takeaways from two Senate debates
Michigan and Kansas Senate candidates clashed over Trump, the economy and health care in high-stakes debates ahead of Election Day.
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.”
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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
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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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Vanderbilt, Carnegie Mellon show Florida business range
Eight months ago, billionaires Stephen Ross and Ken Griffin spoke to a group of business executives gathered at the Norton Museum of Art in West Palm Beach. The February event was billed as a global finance and policy discussion, but at times speakers talked about South Florida's growing economy.
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Dave Roethler is a former Donald Trump supporter in Iowa who feels disillusioned about the economy and believes middle-class families are suffering while the president benefits.
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Dave Roethler is a former Donald Trump supporter in Iowa who feels disillusioned about the economy and believes middle-class families are suffering while the president benefits.
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Dave Roethler is a former Donald Trump supporter in Iowa who feels disillusioned about the economy and believes middle-class families are suffering while the president benefits.
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