Hello and welcome to Eye on AI. In this edition….Gemini 3 puts Google at the top of the AI leaderboards…the White House delays an Executive Order banning state level AI regulation…TSMC sues a former exec now at Intel…Google Research develops a new, post-Transformer AI architecture…OpenAI is pushing user engagement despite growing evidence that some users develop harmful dependencies and delusions after prolonged chatbot interactions.
I spent last week at the Fortune Innovation Forum in Kuala Lumpur, Malaysia, where I moderated several panel discussions around AI and its impacts. Among the souvenirs that I came back from KL with was a newfound appreciation for the extent to which businesses outside the U.S. and Europe really want to build on open source AI models and the extent to which they are gravitating to open source models from China.
My colleague Bea Nolan wrote a bit about this phenomenon in this newsletter a few weeks ago, but being on the ground in Southeast Asia really brought the point home: the U.S., despite having the most capable AI models out there, could well lose the AI race. And the reason is, as Chan Yip Pang, the executive director at Vertex Ventures Southeast Asia and India, said on a panel I moderated in KL, that the U.S. AI companies “build for perfection” while the Chinese AI companies “build for diffusion.”
One sometimes hears a U.S. executive, such as Airbnb CEO Brian Chesky, willing to say that they like Chinese open source AI models because they offer good enough performance at a very affordable price. But that attitude remains, for now at least, unusual. Many of the U.S. and European executives I talk to say they prefer the performance advantages of proprietary models from OpenAI, Anthropic, or Google. For some tasks, even an 8% performance advantage (which is the current gap separating top proprietary models from Chinese open source models on key software development benchmarks) can mean the difference between an AI solution that meets the threshold for being deployed at scale and one that doesn’t. These execs also say they have more confidence in the safety and security guardrails built around these proprietary models.
Asia is building AI applications on Chinese open source models
That viewpoint was completely different from what I heard from the executives I met in Asia. Here, the concern was much more about having control over both data and costs. On these metrics, open source models tended to win out. Jinhui Yuan, the cofounder and CEO of SiliconFlow, a leading Chinese AI cloud hosting service, said that his company had developed numerous techniques to run open source models more cost-effectively, meaning using them to accomplish a task was significantly cheaper than trying to do the same thing with proprietary AI models. What’s more, he said that most of his customers had found that if they fine-tuned an open source model on their own data for a specific use case, they could achieve performance levels that beat proprietary models—without any risk of leaking sensitive or competitive data.
That was a point that Vertex’s Pang also emphasized. He cautioned that while proprietary model providers also offer companies services to fine-tune on their own data, usually with assurances that this data will not be used for wider training by the AI vendor, “you never know what happens behind the scenes.”
Using a proprietary model also means you are giving up control over a key cost. He says he tells the startups he is advising that if they are building an application that is fundamental to their competitive advantage or core product, they should build it on open source. “If you are a startup building an AI native application and you are selling that as your main service, you better jolly well control the technology stack, and to be able to control it, open source would be the way to go,” he said.
Cynthia Siantar, the CEO of Dyna.AI, which is based in Singapore and builds AI applications for financial services, also said she felt some of the Chinese open source models performed much better in local languages.
But what about the argument that open source AI is less secure? Cassandra Goh, the CEO of Silverlake Axis, a Malaysian company that provides technology solutions to financial services firms, said that models had to be secured within a system—for instance, with screening tools applied to prompts to prevent jailbreaking and to outputs to filter out potential problems. This was true whether the underlying model was proprietary or open source, she said.
The conversation definitely made me think that OpenAI and Anthropic, both of which are rapidly trying to expand their global footprint, may run into headwinds, particularly in the middle income countries in Southeast Asia, the Middle East, North Africa, and Latin America. It is further evidence that the U.S. probably needs to do far more to develop a more robust open source AI ecosystem beyond Meta, which has been the only significant American player in the open source frontier model space to date. (IBM has some open source foundation models but they are not as capable as the leading models from OpenAI and Anthropic.)
Should “bridge countries” band together?
And that’s not the only way in which this trip to Asia proved eye-opening. It was also fascinating to see the plans to build out AI infrastructure throughout the region. The Malaysian state of Johor, in particular, is trying to position itself as the data center hub for not just nearby Singapore, but for much of Southeast Asia. (Discussions about a tie-up with nearby Indonesia to share data center capacity are already underway.)
Johor has plans to bring on 5.8 gigawatts of data center projects in the coming years, which would consume basically all of the state’s current electricity generation capacity. The state—and Malaysia as a whole—has plans to add significantly more electricity generation, from both gas-powered plants and big solar farms, by 2030. Yet concerns are growing about what this generation capacity expansion will mean for consumer electricity bills and whether the data centers will drink up too much of the region’s fresh water. (Johor officials have told data center developers to pause development of new water-cooled facilities until 2027 amid concerns about water shortages.)
Exactly how important regional players will align in the growing geopolitical competition between the U.S. and China over AI technology is a hot topic. Many seem eager to find a path that would allow them to use technology from both superpowers, without having to choose a side or risk becoming a “servant” of either power. But whether they will be able to walk this tightrope is a big open question.
Earlier this week, a group of 30 policy experts from Mila (the Quebec Artificial Intelligence Institute founded by AI “godfather” and Turing Award winner Yoshua Bengio), the Oxford Martin AI Governance Initiative, and a number of other European, East Asian, and South Asian institutions jointly issued a white paper calling on a number of middle income countries (which they called “bridge powers”) to band together to develop and share AI capacity and models so that they could achieve a degree of independence from American and Chinese AI tech.
Whether such an alliance—a kind of non-aligned movement of AI—can be achieved diplomatically and commercially, however, seems highly uncertain. But it is an idea that I am sure politicians in these bridge countries will be considering.
If you want to learn more about how AI can help your company to succeed and hear from industry leaders on where this technology is heading, I hope you’ll consider joining me at Fortune Brainstorm AI San Francisco on Dec. 8–9. Among the speakers confirmed to appear so far are Google Cloud chief Thomas Kurian, Intuit CEO Sasan Goodarzi, Databricks CEO Ali Ghodsi, Glean CEO Arvind Jain, Amazon’s Panos Panay, and many more. Register now.
White House launches “Genesis Mission” to give AI-driven boost to science. President Trump signed an executive order launching what he is calling the “Genesis Mission,” a massive federal initiative to harness artificial intelligence and government science datasets via the U.S. Department of Energy and its national laboratories. The mission aims to build a unified AI‐driven research platform—linking supercomputers, university and industry partners, and federal data—to accelerate breakthroughs in fields like energy, engineering, biotech and national security. While pitched as a scientific “moonshot”-style effort, the initiative faces questions about its funding model and how it will manage sensitive national-security and proprietary data. Read more here from Reuters. TSMC sues former executive who defected to Intel over alleged trade secret theft. TSMC has sued former senior executive Lo Wei-Jen, now at Intel, alleging he took or could disclose the company’s trade secrets, the Financial Timesreports. The company alleges that Wei-Jen told it he planned to enter academia after retiring in July. The case underscores intensifying geopolitical and commercial pressures in the global race for advanced chipmaking, as TSMC—responsible for more than 90% of the world’s leading-edge semiconductors—faces rising competition backed by a major U.S. government investment in Intel.
Google debuts Gemini 3 model, hailed by the company and some users as a big advance. Google launched its Gemini 3 large language model last week. The model surpassed rival models from OpenAI and Anthropic on a wide range of benchmark tests and its performance seems to have largely impressed users who have tried it, according to social media posts and blogs. The launch of Gemini 3—which Google immediately integrated into its AI-powered search features, such as AI Overviews and “AI Mode” in Google Search—is being hailed as a turning point in the AI race, helping restore investor confidence in Google-parent company Alphabet after years of anxiety about it losing ground. You can read more from the Wall Street Journalhere. Anthropic premiers Claude Opus 4.5. Anthropic unveiled Claude Opus 4.5, its newest and most powerful AI model, designed to excel at complex business tasks and coding. The premiere—Anthropic’s third major model release in two months—comes as the company’s valuation has surged to roughly $350 billion following multibillion-dollar investments from Microsoft and Nvidia. Anthropic says Opus 4.5 outperforms Google’s Gemini 3 Pro (see above news item) and OpenAI’s GPT-5.1 on coding benchmarks, and even beat human candidates on its internal engineering exam, and is rolling out alongside upgraded tools including Claude Chrome, Claude for Excel, and enhanced developer features, according to a story in CNBC. White House reportedly pauses work on Executive Order targeting state AI laws. Reuters reports that the White House has paused a draft executive order that would have aggressively challenged state AI regulations by directing the Justice Department to sue states and potentially withhold federal broadband funds from those that impose AI rules. The move—backed by major tech firms seeking uniform national standards—sparked bipartisan criticism from state officials and lawmakers, who argued it would undermine consumer protection and was potentially unconstitutional. The administration may still try to include a moratorium on state-level AI rules in the National Defense Authorization Act or another spending bill that Congress has to pass in the coming weeks. But so far, opposition highlights the intense political backlash to federal attempts to preempt state AI laws. OpenAI offices locked down due to concerns about former Stop AI activist. OpenAI employees in San Francisco were briefly instructed to remain inside the office after police received a report that one of the cofounders of Stop AI had allegedly made threats to harm staff and might have acquired weapons. Stop AI publicly disavowed the individual and reaffirmed its commitment to nonviolence. Stop AI is an activist group trying to stop the development of increasingly powerful AI systems, which it fears are already harming society and also represent a potentially existential risk to humanity. The group has engaged in a number of public demonstrations and acts of civil disobedience outside the offices of major AI labs. Read more here from Wired.
EYE ON AI RESEARCH
Are we inching closer to a post-Transformer world? It’s been eight years since researchers at Google published their landmark research paper, “Attention is All You Need,” which introduced the world to the Transformer, a kind of neural network design that was particularly good at predicting sequences in which the next item depends on items that appeared fairly remotely from that item in the prior sequence. Transformers are what all of today’s large language models are based on. But AI models based on Transformers have several drawbacks. They don’t learn continuously. And, like most neural networks, they don’t have any kind of long-term memory. So, for several years now, researchers have been wondering if some new fundamental AI architecture will come along to displace the Transformer. Well, we might be getting closer. Earlier this month, researchers—once again from Google—published a paper on what they are calling Nested Learning. It essentially breaks the neural network’s architecture into nested groups of digital neurons that update their weights at different frequencies based on how surprising any given piece of information is compared to what that part of the model would have predicted. The parts that update their weights more slowly form the longer-term memory of the model, while the parts that update their weights more frequently form a kind of shorter-term “working memory.” And nested between them are blocks of neurons that update at a medium speed, which modulates between the shorter and longer term memories. As an example of how this can work in practice, the researchers created an architecture they call HOPE that learns its own best way of optimizing each of these nested blocks. You can read the Google research here.
AI CALENDAR
Nov. 26-27: World AI Congress, London.
Dec. 2-7: NeurIPS, San Diego
Dec. 8-9: Fortune Brainstorm AI San Francisco. Apply to attend here.
Jan. 6: Fortune Brainstorm Tech CES Dinner. Apply to attend here.
OpenAI is optimizing for engagement, even though there’s growing evidence its product harms some users. That’s the conclusion of a fascinating New York Times investigation that details how increasing commercial pressures within OpenAI—and a new cadre of executives hired from traditional tech and social media companies—have been driving the company to design ChatGPT to keep users engaged. The company is proceeding down this path, the newspaper reports, even as its own research shows some ChatGPT users develop dangerous emotional and psychological dependencies on the chatbot and that some subset of those become delusional after prolonged dialogues with OpenAI’s AI. The story is a reminder of why AI regulation is necessary. We’ve seen this movie before with social media, and it doesn’t end well, for individuals or society. Any company which offers its service for free or substantially below cost—which is the case for most consumer-oriented AI products right now—has a strong incentive to monetize the user either through engagement (and advertising) or, perhaps even worse, directly paid persuasion (in some ways worse than conventional advertising). Neither is probably in the user’s best interest.
I love watching “Next Man Up” basketball, where the spotlight rotates unpredictably. One night it’s the bench guard dropping 30, the next it’s the role player posting a triple-double.
CapitalG’s Jill Chase—who captained her college basketball team at Williams College—says this logic actually applies to Alphabet’s growth firm. When I ask her what basketball team is most like CapitalG, she lists the WNBA’s Golden State Valkyries.
“Everybody has a different skill set, and everybody is willing to drop anything to help each other win,” said Chase. “It’s a different person every night who wins the game. And I think that’s really consistent with the way CapitalG is building its culture.”
For the first time since the firm was started in 2013, it’s promoting two general partners, Chase and Alex Nichols, Fortune has exclusively learned. Chase, who joined CapitalG in 2020 specifically with a thesis around AI, has backed Abridge, Baseten, Canva, LangChain, Physical Intelligence, and Rippling.
Nichols, meanwhile, joined CapitalG in 2018 as an associate and was promoted to partner just two years ago. He previously worked with managing partner Laela Sturdy on the firm’s investments in Duolingo, Stripe, and Whatnot, and recently led CapitalG’s investment in Zach Dell’s energy startup BasePower. At a moment where there’s mounting angst around data centers and what it will take to power them, Nichols has a surprising take on how AI will affect energy—that both batteries and solar are getting cheaper and better at something like Moore’s Law speed. Those twin cost curves, over time, should actually drive energy prices down.
“I’m actually very optimistic about the future of energy prices,” he said. “You look at the history of energy consumption versus GDP. And cheap energy means more production, more income, and means a higher standard of living.”
At a moment when venture is perhaps more competitive than ever—and there are certainly some solo GPs out there making their mark—there’s an argument that as lines blur between disciplines in an AI-ified world, venture is by necessity a team sport.
Sturdy—who’s been CapitalG’s managing partner since 2023 (and also captained her college basketball team)—and Chase both have clearly taken some learnings from their time on the court. Chase sees venture overall as becoming more team-oriented: “Historically, it used to be like ‘you made general partner, go out and win your deal.’ To me, that’s not the right way to be successful in venture ever.”
Sturdy adds that in basketball, like venture, “We have to look at the scoreboard every once in a while, and you have to get back up when you get crushed… And, of course, coming together is better than playing alone.”
Term Sheet Podcast…This week, I spoke with Exelon CEO Calvin Butler. As resource-hungry data centers continue to sprout across the country, many are questioning whether the nation’s utility network can keep pace with such large-scale demand. Butler says it can. Listen and watch here.
Joey Abrams curated the deals section of today’s newsletter.Subscribe here.
VENTURE CAPITAL
– humans&, a San Francisco-based AI lab, raised $480 million in seed funding. SVAngel and GeorgesHarik led the round and were joined by NVIDIA and others.
– Emergent, a San Francisco-based platform designed for AI software creation, raised $70 million in Series B funding. Khosla Ventures and SoftBank led the round and were joined by Prosus, Lightspeed, Together, and Y Combinator.
– Exciva, a Heidelberg, Germany-based developer of therapeutics designed for neuropsychiatric conditions, raised €51 million ($59 million) in Series B funding. Gimv and EQTLifeSciences led the round and were joined by FountainHealthcarePartners, LifeArcVentures, and others.
– Pomelo, a Buenos Aires, Argentina-based payments infrastructure company, raised $55 million in Series C funding. Kaszek and InsightPartners led the round and were joined by IndexVentures, AdamsStreetPartners, S32, and others.
– Cloover, a Berlin, Germany-based operating system designed for energy independence, raised $22 million in Series A funding. MMCVentures and QEDInvestors led the round and were joined by LowercarbonCapital, BNVTCapital, BoschVentures, and others.
– Statusphere, a Winter Park, Fla.-based influencer marketing technology platform, raised $18 million in Series A funding. VolitionCapital led the round and was joined by HearstLab, 1984Ventures, and HowWomenInvest.
– DominionDynamics, an Ottawa, Canada-based defense technology company, raised $21M CAD ($15.2M USD) in seed funding. Georgian led the round and was joined by BessemerVenturePartners and BritishColumbiaInvestmentManagementCorporation.
– Cosmos, a New York City-based image collection and discovery platform, raised $15 million in Series A funding. ShineCapital led the round and was joined by Matrix and others.
– Mave, a Toronto, Canada-based real estate AI company, raised $5 million in seed funding from StaircaseVentures, RelayVentures, N49P, and AlatePartners.
– Stilla, a Stockholm, Sweden-based developer of an AI designed to accommodate entire teams, raised $5 million in pre-seed funding. GeneralCatalyst led the round and was joined by others.
– AsymmetricSecurity, a London, U.K. and San Francisco-based cyber forensics company, raised $4.2 million in pre-seed funding. SusaVentures led the round and was joined by HalcyonVentures, OverlookVentures, and angel investors.
PRIVATE EQUITY
– ConnectWise, backed by ThomaBravo, acquired zofiQ, a Toronto, Ontario-based agentic AI technology company designed to automate high-service desk operations. Financial terms were not disclosed.
– GrantAvenueCapital acquired 21stCenturyHealthcare, a Tempe, Ariz.-based vitamins, minerals, and supplements company. Financial terms were not disclosed.
– HighlanderPartners acquired Tapatio, a Vernon, Calif.-based hot sauce brand. Financial terms were not disclosed.
– PlatinumEquity acquired CzarnowskiCollective, a Chicago, Ill.-based exhibit and events company. Financial terms were not disclosed.
– UnitedBuildingSolutions, backed by AEIndustrial, acquired DFWMechanicalGroup, a Wylie, Texas-based HVAC solutions company. Financial terms were not disclosed.
IPOS
– PicPay, a Sao Paolo, Brazil-based digital bank, now plans to raise up to $435.1 million in an offering of 22.9 million shares priced between $16 and $19 on the Nasdaq. The company posted $1.7 billion in revenue for the year ended September 30. J&F International and BancoOriginal back the company.
– EthosTechnologies, a San Francisco-based online life insurance provider, plans to raise up to $210 million in an offering of 10.5 million shares priced between $18 and $20. The company posted $344 million in revenue for the year ended Sept. 30. GeneralCatalyst, HeroicVentures, EricLantz, and others back the company.
FUNDS + FUNDS OF FUNDS
– BlueprintEquity, a La Jolla, Calif.-based growth equity firm, raised $333 million for its third fund focused on enterprise software, business-to-business, and tech-enabled services companies.
PEOPLE
– Area 15 Ventures, a Castle Pine, Colo.-based venture capital firm, promoted AdamContos to managing partner.
– BullCityVenturePartners, a Durham, N.C.-based venture capital firm, hired CarlyConnell as a principal.
– HarvestPartners, a New York City-based private equity firm, promoted LucasRodgers to partner, MatthewBruckmann and IanSingleton to principal, and ConnorScro to vice president on the private equity team.
– Wingman Growth Partners, a Greenwich, Conn.-based private equity firm, hired CheriReeve as CFO. She previously served as principal and CFO at AtlasHoldings.
Davos 2026: reading the signals, not the headlines | Fortune
Louisa Loran advises boards and leadership teams on transformation and long-term value creation and currently serves on the boards of Copenhagen Business School and CataCap Private Equity.At Google, Louisa launched a billion-dollar supply chain solutions business, doubled growth in a global industry vertical, and led strategic business transformation for the company’s largest customers in EMEA—working at the forefront of AI, data, and platform innovation. At Maersk, she co-authored the strategy that redefined the brand globally and doubled its share price, helping pivot the company from traditional shipping to integrated logistics. Her career began in the luxury and FMCG space with Moët Hennessy and Diageo, where she built iconic brands and led innovation at the intersection of heritage and digital transformation.
China’s hotels are welcoming record numbers of travelers, yet room rates are sinking—a paradox many operators blame on Trip.com Group Ltd.
For Gary Huang, running a five-room homestay in the scenic Huzhou hills near Shanghai was supposed to secure his family’s financial future. Instead, he and other hoteliers in China’s southeastern Zhejiang province say nightly rates have fallen to levels last seen more than a decade ago, as Trip.com’s frequent discount campaigns force them to cut prices simply to remain visible on China’s dominant booking platform.
“The promotion campaigns now are almost a daily routine,” said Huang, who asked to use his self-given English name out of concern of speaking out against Trip.com. “We have to constantly cut prices at least 15% to attract travelers. We have no choice but to go along with the price cuts.”
Trip.com has been central to China’s post-pandemic travel rebound, connecting millions of travelers with small operators like Huang. But for many hotels, visibility—and sometimes survival—comes at the expense of profits.
That dynamic is now at the heart of Beijing’s antitrust probe. Regulators allege Trip.com is abusing its market position, with analysts citing deflation across the sector as the government’s main concern. Interviews with lodging operators, industry groups and travel consultants describe a system where constant price-cutting and opaque policies are eroding profitability, even as demand rebounds.
Trip.com has said it’s cooperating with the government’s investigation. The company’s stock dove more 16% since the probe was announced a week ago.
Revenue per room—a key hotel metric—was flat across China in 2025, even as other Asian markets saw gains, according to Bloomberg Intelligence. Marriott International Inc.’s revenue per room in China fell 1% most of last year, while Hilton’s China room revenue trailed its regional peers.
The company controls about 56% of China’s online travel market, according to China Trading Desk, and has grown into the world’s largest booking site. Its dominance has helped fuel domestic tourism’s recovery—nearly 5 billion trips were logged in the first three quarters of 2025—but operators say the benefits are being offset by falling room yields.
“The market has developed unevenly and innovation is lacking due to monopolistic practices,” said He Shuangquan, head of the Yunnan Provincial Tourism Homestay Industry Association that represents some 7,000 operators. “The entire online travel agency sector is stagnating in a pool of dead water.”
‘Pick-one-of-two’
The broader challenge is oversupply and cautious consumer spending. In regions like Yunnan, hotel capacity has tripled since the pandemic, just as travelers tightened budgets. Consultants note that while people are traveling more, they’re spending less—leaving hotels slashing rates to fill empty beds and posting billions in losses.
For operators like Huang, the paradox is stark: the platform that delivers customers is also accelerating the race to the bottom. The complaints center around Trip.com’s “er xuan yi,” Mandarin for pick-one-of-two exclusivity arrangements—a practice that Chinese regulators have repeatedly vowed to stamp out.
Trip.com categorizes merchants into tiers with “Special Merchants” enjoying the most visibility and traffic, Yunnan Provincial Tourism’s He said. However, these top-tier merchants are typically prohibited from listing on rival platforms like Alibaba’s Fliggy, ByteDance’s Douyin or Meituan. Merchants who aren’t bound by these exclusive arrangements report being effectively compelled to offer the lowest prices on Trip.com’s online booking platform Ctrip, or risk facing a raft of measures like lowered search rankings.
2 days ago
22 hours ago
14 hours ago
19 hours ago
2 days ago
2 days ago
Politics8 years ago