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The Rise of Origin Lab As AI begins to interact with the physical world, new types of labs are working to build world models that could be used to operate physical robotics or model objects in physical space. Unlike large language models, there isn’t an easy source of data for those models, which has left many labs scrambling to assemble the necessary training sets. Origin Lab's Innovative Approach Now, one startup is emerging with an unlikely data source: the video game industry. Origin Lab, which just announced an $8 million seed funding round led by Lightspeed Ventures, aims to serve as a marketplace where world-model-focused labs can buy high-quality licensed data. The Data Conversion Process On the other side of the trade, video game companies can squeeze additional revenue out of the digital assets they’ve already created. In the middle, Origin Lab will convert the video game assets into a form that works as training data — something that could be as simple as a rendering run or as complex as automating hours of walkthrough footage. Market Impact and Future Outlook Origin Lab's success in fundraising is a sign of a growing market — not just for training data, but for startups that can serve as essential suppliers to major AI labs. The success of companies like Scale.AI has made the opportunity impossible to ignore. Origin Lab's innovative approach has the potential to bridge the gap between the video game industry and AI labs, providing a valuable source of training data for world models.

The Shift in AI Leadership For the first time, Anthropic has more verified business customers than OpenAI, according to this month’s AI Index from the fintech firm Ramp. The survey, compiled from Ramp’s clients’ expense data, shows 34.4% of participating businesses are paying for Anthropic services, more than any other AI lab, while only 32.3% pay for OpenAI. Key Statistics 34.4% of businesses pay for Anthropic services 32.3% of businesses pay for OpenAI services Over 50,000 companies represented in the survey Anthropic's share of business customers increased by 26% in the past 12 months OpenAI's share of business customers declined by 1% in the past 12 months The Impact of Anthropic's Strategy “Anthropic has already been in the lead amongst the high adoption groups like finance, tech, professional services,” Ramp economist Ara Kharazian told TechCrunch. “It’s across the other firms where OpenAI still has a lead, but that has been shrinking over the past couple of months.” The Future Outlook Kharazian is skeptical about whether this advantage will last, but said the success of the past year was proof that Anthropic had chosen a good strategy. “What Anthropic did worked really well,” Kharazian told TechCrunch, “which was — start with a very technical customer base, focus on their needs, really succeed in execution and then start broadening out through tools like Cowork.”

Adaption announced the launch of AutoScientist, a new AI‑training product that automates fine‑tuning and data optimization to help frontier models acquire specific capabilities faster. Co‑founder and CEO Sara Hooker highlighted the system’s ability to co‑optimize both data and model, positioning it as a potential catalyst for broader, outside‑lab AI breakthroughs. AutoScientist: Automated Fine‑Tuning for Faster Capability Gains The platform builds on Adaption’s existing Adaptive Data service, turning continuously improving datasets into continuously improving models. By automating the conventional fine‑tuning workflow, AutoScientist aims to make high‑quality model adaptation a plug‑and‑play process for a wide range of domains. Performance Claims: Doubling Win‑Rates Across Models Launch materials state that AutoScientist has more than doubled win‑rates across different model families. Traditional benchmarks such as SWE‑Bench or ARC‑AGI are not directly applicable due to the tool’s task‑specific adaptation focus. The service is free for the first 30 days to encourage early adoption and real‑world validation. Strategic Implications for Frontier AI Labs By reducing the manual effort required for data curation and model fine‑tuning, AutoScientist could lower the barrier to entry for labs aiming to train cutting‑edge models. This aligns with the broader industry trend of “neolabs” leveraging heavy investment to accelerate self‑improving AI research outside of traditional corporate labs. Future Outlook: Open Access and the Race to Self‑Improving Models If the promised performance gains hold up in practice, AutoScientist may become a standard component of AI development pipelines, spurring faster iteration cycles and potentially democratizing access to frontier AI capabilities. Hooker predicts that, similar to the impact of code‑generation tools, this platform could unlock a wave of innovation across multiple fields.

The Trump-Xi Summit: A Pivotal Moment in US-China Relations Donald Trump's state visit to China this week – the first by the US president in nearly a decade – comes amid a time of geopolitical upheaval, a new and intractable conflict in the Middle East, and a sometimes rocky relationship between the world's two major superpowers. There is much for Trump and Xi Jinping to discuss, but a few key issues are likely to dominate the agenda. Five Critical Issues on the Summit Agenda The high-stakes meeting between the two leaders addresses several pressing matters that could reshape the global landscape: The Iran Conflict and Hormuz Strait Crisis Trump is eager for China to lean on Tehran to advance peace talks and reopen the strait of Hormuz. To now, Beijing has sat back and watched the US struggle against Iran, at least publicly. But with about half of China's crude oil imports passing through the strait, Xi does want the waterway unblocked. China knows its exports will suffer if a global recession results from an oil supply crisis. Complicating the picture, the US this week put sanctions on several Chinese firms accused of assisting Iranian oil shipments and supplying satellite imagery allegedly used in Iranian military operations, claims that Beijing denied. Trump's arrival comes after Iran's foreign minister, Abbas Araghchi, visited Beijing last week. Taiwan: The Flashpoint in US-China Relations Beijing is keen to push the US on Taiwan, with Trump saying he is prepared to raise the issue of arms sales to the island, which China claims as a breakaway territory despite never having ruled it. In December, Trump authorised an $11bn arms package for Taiwan, the largest weapons sale ever to the island, but no shipments have been made yet. Xi may seek changes in how the US refers to Taiwan. Ideally, from the perspective of Beijing, this would be a statement from Washington "opposing" Taiwan's independence rather than "not supporting" it. Taiwan will be watching closely. Just two weeks ago, China's foreign minister in a phone call with Marco Rubio urged the US to "make the right choices" on Taiwan. With Trump known to veer off script, John Kirby, a former US state department and Pentagon spokesperson cautioned: "They just have to be so extraordinarily precise when you're talking about Taiwan because, quite frankly, the stakes are enormously high." The AI Cold War: Technological Supremacy at Stake China and the US are locked into a race on artificial intelligence that is becoming something of a technological cold war. In April, the White House accused China of stealing US AI labs' intellectual property on an industrial scale, claims Beijing denied. Meanwhile, Beijing has been frustrated by Washington's reluctance to allow Nvidia to export its most powerful processing chips to China. In January, the White House said Nvidia could export its second most powerful chip, the H200, but no shipments have been sent yet. Analysts and ethics leaders hope Trump and Xi will discuss non-binding AI guidelines, including sharing information about AI misuse and safety, which are seen as critical guardrails amid the advent of AI weaponry and military adoption. Trade War: Rare Earth Minerals and Economic Leverage Trump has repeatedly threatened China over trade, imposing tariffs above 140% last year. But Xi held some cards of his own and did not fold. Instead, China blocked exports of its rare earth minerals and magnets to the US. Trump, finally, backed down. The US has depleted notable levels of its weapons arsenal in the war against Iran, with many weaponry components requiring critical minerals that are linked to supply chains dominated by China. China is expected to announce purchases related to Boeing airplanes, American agriculture and energy, US officials have said. In turn, Beijing wants the US to ease curbs on exports of advanced semiconductors. Beijing also wants to reduce barriers to investment in the US, and hopes to establish a Board of Investment to match the Trump-back Board of Trade. Fentanyl: The Drug War and Political Posturing Fentanyl is a key item on Trump's agenda this week, Politico reported, citing an administration official granted anonymity to preview the closed-door sessions. The US has long accused Chinese businesses of knowingly supplying the chemical precursors to Mexican cartels who use them to make the drug. Trump knows that being seen to press China hard over fentanyl and precursors plays well with his Maga base. But Trump lost important leverage on the fentanyl front when China defied his tariffs threats. In March, the US and China clashed over fentanyl and trade at a UN drugs meeting. China wants to be removed from the state department's annual list of "major drug transit or illicit drug producing countries", due to be updated in September.

The Tech Diplomacy Mission to BeijingPresident Donald Trump is embarking on a high-stakes visit to China this week, accompanied by an impressive delegation of American tech industry leaders. The guest list reads like a who's who of Silicon Valley and corporate America, suggesting that technology will be a central focus of discussions with Chinese President Xi Jinping, though potentially following any developments regarding the situation in Iran.A-List of Tech Titans Joining the Presidential DelegationThe presidential delegation includes some of the most influential figures in American technology. Outgoing Apple CEO Tim Cook, SpaceX and Tesla CEO Elon Musk, Meta's recently appointed president Dina Powell McCormick, Micron CEO Sanjay Mehrotra, Cisco CEO Chuck Robbins, and Qualcomm CEO Cristiano Amon are all confirmed to join the president.The Notable Absence of Jensen HuangSurprisingly absent from the delegation is Jensen Huang, CEO of Nvidia - the world's most important chip manufacturer. Huang, who has close ties to Trump, previously criticized US limitations on chip sales to China in an April interview, expressing concern that a "loser mentality" could cost America its edge in AI. His absence suggests that a major semiconductor deal may be less likely, though an announcement from Micron remains possible.Cook's Diplomatic Role and Apple's China SuccessTrump's inclusion of Tim Cook likely reflects a desire for a familiar face in high-stakes negotiations. Apple's iPhone 17 has proven enormously successful in China, driving the company's quarterly earnings to record highs. Despite moving some manufacturing to India and Vietnam, Apple still produces most of its products in China. In announcing his retirement, Apple highlighted Cook's diplomatic skills, noting that his future responsibilities would include dealing with world leaders, suggesting such diplomatic visits may become a regular feature of his post-Apple career.Following the Middle East Model for Tech DealsWhether Trump's China visit will replicate the flurry of tech deals that emerged from his May 2025 Middle East trip remains to be seen. The president is showcasing America's top business leaders - products of his hands-off approach to fostering technological innovation - while his administration simultaneously appears to be taking cues from China's more stringent approach to AI governance.US Embracing China's AI Regulatory FrameworkChina's AI laws require companies to submit their models to Beijing for review on both security and political sensitivity grounds, prohibiting content that the government finds objectionable. In a similar move, the White House is increasing its involvement with American frontier AI labs. Trump is reportedly considering an executive order that would require AI companies to submit their newest models for White House review. The administration has already announced deals with major players including Google DeepMind, Microsoft, and xAI for national security reviews of their latest releases through the Center for AI Standards and Innovation (CAISI) at the Department of Commerce.Pentagon's Standoff with AnthropicThe relationship between the Pentagon and AI startup Anthropic continues to face challenges in court, as the startup expresses concerns about military applications of its technology while the Pentagon has designated the company as a supply chain risk. Vice President JD Vance has requested that Anthropic not expand access to its powerful cybersecurity-focused model Mythos beyond its initial list of partners, according to the Wall Street Journal, highlighting the growing tensions between AI innovation and national security concerns.

The Rise of Moonshot AI Chinese AI companies are making waves in the industry, despite not having the same level of funding as their Western counterparts. Moonshot AI, a Beijing-based AI lab, has raised about $2 billion at a valuation of $20 billion, according to a post by Huafeng Capital. Investor Interest and Funding Details The round was led by Chinese food delivery company Meituan's VC arm, Long-Z Investments, with participation from Tsinghua Capital, China Mobile, and CPE Yuanfeng. This recent funding brings Moonshot's total raised to $3.9 billion over the past six months. The Data Analysis Valuation: $20 billion Funding raised: $2 billion Annual recurring revenue: $200 million (as of April) Previous valuation: $4.3 billion (end of 2025), $10 billion (early 2026) The Impact Analysis The fundraising comes as investor appetite for open-weight AI models made by Chinese labs surges. Moonshot's Kimi models have gained significant traction, with the latest model, Kimi K2.6, being the second-most used LLM on distribution platform OpenRouter. The Prediction With demand for open source AI models on the rise, Moonshot AI and its competitors are poised for further growth. Other Chinese AI labs, such as DeepSeek, are reportedly in talks to raise outside capital, while some have even gone public on the back of demand for their AI models.

DeepSeek’s Funding Surge: From $20B to $45B in Weeks DeepSeek, the Chinese AI lab known for a cost‑efficient large language model, is in talks to raise its first venture‑capital round that could push its valuation to $45 billion, up from $20 billion just weeks earlier. First Venture Capital Round Targets Chinese AI Champion The round will be led by the state investment vehicle China Integrated Circuit Industry Investment Fund. Potential co‑investors include cloud giants Tencent and Alibaba. Founder Liang Wenfeng, who owns nearly 90% of the company, is seeking capital to retain talent amid competitor poaching. Valuation Leap and Investor Line‑up: Numbers at a Glance Previous valuation: $20 billion Target valuation: $45 billion Founder ownership: ~90% Key investors: China Integrated Circuit Industry Investment Fund, Tencent, Alibaba Model advantage: runs on Huawei chips, lower compute cost Strategic Implications for China’s AI Independence The funding aligns with Beijing’s goal to develop home‑grown AI hardware and software, reducing reliance on U.S. chips. By optimizing models for Huawei silicon, DeepSeek offers a domestic alternative to OpenAI and Anthropic, potentially accelerating China’s AI ecosystem. What the Next Funding Milestone Could Mean for Global AI Competition If the round closes at the projected valuation, DeepSeek could attract further private and state capital, scale its model offerings, and challenge Western AI leaders on both performance and cost. Analysts expect increased pressure on U.S. firms to secure supply chains and consider strategic partnerships in Asia.

Ethos, a London‑based AI startup, closed a $22.75 million Series A round on May 6, 2026, led by a16z with participation from General Catalyst, XTX Markets, Evantic Capital, and Common Magic. The capital will accelerate its voice‑powered expert onboarding system, which promises richer skill signals than traditional job‑title based platforms. Voice‑Powered Onboarding Redefines Expert Matching Ethos replaces static forms with conversational interviews, allowing experts to describe their knowledge in their own words. The platform then parses these recordings to extract granular competencies, enabling companies to pose natural‑language queries such as “find experts who worked at a funded startup backed by A‑grade investors solving finance automation.” Funding Numbers and Investor Line‑up Highlight Market Confidence Series A amount: $22.75 million Lead investor: a16z (Andreessen Horowitz) Other participants: General Catalyst, XTX Markets, Evantic Capital, Common Magic Founders: James Lo (ex‑McKinsey, SoftBank) and Daniel Mankowitz (former DeepMind AI researcher) Implications for the Expert‑Network Landscape and AI‑Driven Talent Mapping By capturing sub‑specializations through voice, Ethos challenges legacy platforms that rely on shallow job‑title signals. The startup also enriches its graph with public data—blogs, academic papers, and social links—creating a hybrid human‑AI talent map. Early adopters include top hedge funds, private‑equity firms, foundational AI labs, and enterprise consultancies, which pay a 30%+ per‑project fee. Future Outlook: Scaling, Revenue Targets, and Competitive Position Ethos aims for “eight‑figure annualized revenue” while keeping its team lean (currently eight members). With roughly 35,000 new experts joining each week, the company plans to deepen its voice‑agent interview pipeline and expand into sectors such as law, health, and finance. Competitors like Listen Labs and Outset offer conversational AI interview tools, but Ethos bets its curated expert network will deliver higher‑value matches for complex, domain‑specific queries.

QuTwo's Quantum Leap in Valuation QuTwo, the Finnish AI lab founded by former AMD Silo AI CEO Peter Sarlin, is now valued at €325 million (approximately $380 million) after raising a €25 million ($29 million) angel round. It’s a sign of enduring tailwinds for AI, quantum computing, and sovereign tech, especially for Europe-made companies. The Intersection of AI and Quantum Computing QuTwo’s name is a nod to quantum computing, but it hasn’t gone all in on quantum. Its core product, QuTwo OS, is an orchestration layer that directs tasks to classical, quantum, or hybrid architectures — with the idea that enterprise use cases are often best served by “quantum-inspired” computing, which uses classical chips to simulate quantum behavior on more reliable hardware. Enterprise AI as the Primary Focus Enterprise AI will be QuTwo’s bread and butter. The company already secured some $23 million in committed revenue thanks to design partnerships with the likes of retail giant Zalando, for which it helped develop AI assistants. “AI is the north star that we will continue to aim for. Quantum is just a new type of compute,” said Sarlin, who is adamant that QuTwo is an AI company. The Funding and Future Plans QuTwo's valuation and round size are modest compared to other AI startups. The company wants the freedom to think long term, with a five- to 10-year horizon. QuTwo secured funding from angel investors, including Yuri Milner, Xavier Niel, Nico Rosberg, Dieter Schwarz, and Niklas Zennström. The Impact on Europe's AI Landscape Momentum has been building around Europe-based AI labs, and several of them have become overnight unicorns. QuTwo’s connection with IQM, a Finnish quantum company set to go public, is a reminder that the company believes we are about to enter the quantum era. The Road Ahead QuTwo recently expanded into Sweden and has been hiring. According to Sarlin, some 50 quantum and AI scientists have joined the team. The company aims to build the globally leading AI company for the next paradigm, given that Europe did not succeed in building the AI company for this era.