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The Final Private Push: Anthropic Secures $65 BillionAnthropic has closed a monumental Series H funding round, raising $65 billion at a $965 billion post-money valuation. This capital injection represents the startup's largest private fundraising effort to date and signals that the company is likely in its final pre-IPO stage. The round brings the company's total capital raised to a staggering level, positioning it as a heavyweight contender in the generative AI sector just as public markets begin to open up to high-growth technology companies.The Infrastructure and Investor EcosystemThe funding round was co-led by a consortium of elite institutional investors, including Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital. Notably, the round saw participation from major infrastructure partners such as Samsung, SK Hynix, and Micron, highlighting the critical role hardware manufacturers are playing in the AI supply chain.Strategic Backing: Hyperscalers committed $15 billion, including a significant $5 billion from Amazon.Investor Demand: The round was highly competitive, with one institutional investor reportedly pledging up to $5 billion just to secure a meeting with the CFO.Use of Funds: Proceeds will be directed toward advancing safety research, expanding compute infrastructure, and scaling enterprise products.Valuation Wars and Revenue TrajectoryThis funding round places Anthropic at the epicenter of a fierce valuation war in the AI industry. The company's massive valuation comes as it reports a $47 billion revenue run rate and expects a 130% revenue surge to achieve its first operating profit. This financial performance contrasts sharply with the broader tech sector, illustrating the intense demand for high-performance AI models.Competitive Landscape: Anthropic's valuation rivals OpenAI, which raised $122 billion in March at an $852 billion valuation.Market Positioning: The company is reportedly preparing to launch models comparable to its powerful cybersecurity model, Mythos, which has been limited due to safety concerns.The Strategic Shift Toward Enterprise SafetyThe inclusion of infrastructure partners like Samsung and SK Hynix suggests a strategic pivot toward vertical integration. By securing hardware support, Anthropic ensures a stable supply chain for the compute-intensive models it is developing, such as the newly released Claude Opus 4.8. This model emphasizes agentic tasks, advanced coding, and self-correction capabilities, addressing a critical need for enterprises seeking reliable and safe AI solutions.The IPO Countdown and Market DominanceWith this massive capital raise and the release of advanced models, Anthropic is poised to lead the next phase of AI innovation. The company's ability to attract top-tier institutional investors and secure hardware partnerships positions it uniquely ahead of its IPO. As the race for AI dominance heats up, Anthropic's valuation and growth trajectory suggest it will be a key player in shaping the future of the public AI market.

The Rise of AI Financial MarketsThe most important market of the future could be in LLM tokens — and financial groups are rushing to build new infrastructure for them. China's Shanghai Futures Exchange is currently designing a derivatives market for AI tokens, while major derivatives exchanges CME Group and the Intercontinental Exchange (the owner of the NYSE) have separately announced they're working on launching futures contracts for renting GPUs.Building the AI Derivatives InfrastructureGPU markets are still maturing, but given the wide range of companies using, selling, and renting GPUs, there's already a robust market for spot prices on GPU rental, typically charged by the hour. This has prompted major financial players to develop futures contracts that would allow businesses to hedge against fluctuating compute costs.Enterprise plans for major AI companies are commonly denominated in tokens: OpenAI, for example, charges $5 per million input tokens, and $30 per million output tokens if you want to use the API for its latest GPT-5.5 model. Even cloud providers are increasingly offering the opportunity to charge per token, as in Amazon's Bedrock system.The Economics of GPU and Token PricingAccording to data from AI Mining Co., which tracks daily GPU rental pricing across 28 marketplaces and cloud providers, median prices for Nvidia H100 GPUs ranged from $1.40 to $4.27 per hour across 13 marketplaces, while the average price for H200 GPUs were between $2.34 and $5 per hour across 10 marketplaces.Just over the past seven days, average H100 prices ranged from $2.79 to $3.33, showing the volatility that makes futures contracts attractive for risk management.Transforming the AI Investment LandscapeThe effort comes amid an unprecedented buildout of AI infrastructure. Cloud service providers, private equity firms, and infrastructure players alike have poured hundreds of billions into building data centers, anticipating that demand for GPUs and compute will continue to rise.An emerging crop of global neocloud companies is also vying for a piece of this demand. Some of these new entrants are specializing, focusing on inference, while others are competing with cloud giants like Oracle, AWS, and Google Cloud to offer their services to AI companies.The Future of AI Financial InstrumentsBy targeting AI tokens, the Shanghai exchange's derivative product would be tied to how AI companies price their services, giving businesses, investors, and data center operators a way to hedge against the cost of compute. As AI becomes increasingly central to business operations, these financial instruments will likely become essential components of the technology investment ecosystem.

The Guardian editorial argues that the UK must treat the plight of NEETs as a national priority, linking rising youth unemployment to inadequate training, housing costs and a fragmented policy framework.Milburn Commission Highlights Over 1 Million UK NEETsThe commission’s report, due in the autumn, shines a bright light on the 1 million young people aged 16‑24 who are not in education, employment or training. It criticises political attacks on welfare and “kids‑these‑days” rhetoric, insisting that the problem is fundamentally a policy failure.The Scale of the Crisis: Over 1 Million Young People Out of Work or Study1 million NEETs – roughly one in eight of the 16‑24 cohort.60 % are economically inactive, meaning they are not actively seeking work.Health‑related universal credit claims have risen in regions with fewer entry‑level jobs.Apprenticeship starts have fallen 35 % over the past decade.Why the UK Is Falling Behind Europe on Youth EmploymentCompared with other wealthy European nations, the UK records one of the highest rates of young people not in work or study. Contributing factors include:Housing inflation limiting independent living for young adults.Restrictive GCSE combinations that disadvantage less academic pupils.Chaotic further‑education reforms and the poorly‑implemented apprenticeship levy.Automation and AI‑driven profit growth that do not translate into entry‑level opportunities.A National Participation System: Pathway to Re‑engaging Young WorkersThe report proposes a new “participation system” that would coordinate work and pensions, health, education and business departments to pull young people into the labour market. While ambitious, the editorial stresses that without a clear, cross‑departmental mission the UK will continue to lose a generation to inactivity.

The LeadSmoke rises over Beirut following an Israeli strike, marking a significant escalation in the already tense region. The incident has drawn international attention as concerns grow over potential wider conflict in the Middle East.The Event DetailsThe Israeli strike targeted an unspecified location in Beirut, causing visible smoke to rise over the Lebanese capital. While details remain limited, the strike represents a notable development in the complex security dynamics between Israel and Lebanon.The Regional ImpactThe strike comes amid heightened tensions in the Middle East, with Lebanon already facing significant political and economic challenges. The incident could further destabilize the region and potentially draw in other actors in the complex web of Middle Eastern geopolitics.The International ResponseInternational bodies and neighboring nations are likely to closely monitor the situation, with concerns that the strike could escalate into a broader conflict. The United Nations and other diplomatic entities may be called upon to intervene and prevent further escalation.The Future OutlookThe coming days will be critical in determining whether this incident represents an isolated event or the beginning of a more sustained confrontation. The international community will be watching closely for any further developments and potential diplomatic responses.

New Coalition Takes Shape Amid Drone ControversyLatvia’s parliament has confirmed a fresh governing alliance after the previous cabinet fell apart over disagreements on anti‑drone defenses. The vote marks a decisive step toward stabilising a nation that has been rattled by several wayward Ukrainian drones crossing its borders.Parliament Votes 66‑34 to Install Andris Kulbergs as Prime MinisterBy a margin of 66 deputies out of a 100‑seat assembly, lawmakers endorsed Andris Kulbergs, a 47‑year‑old centrist, as Latvia’s next prime minister. He will lead the country until the scheduled parliamentary elections on October 3. The new cabinet retains outgoing foreign minister Baiba Braze and appoints Colonel Raivis Melnis as defence minister.Numbers Behind the Power Shift: Seats, Votes, and Demographics66 votes in favour, 34 against.Latvia’s population: roughly 1.8 million people.The coalition comprises four parties, giving it a “healthy majority” in the Saeima.Previous prime minister Evika Silina resigned in mid‑May after losing coalition support.Implications for Latvia’s Security and EU/NATO AlignmentThe new government has pledged to reinforce military and border security, a stance echoed by political scientist Nils Muiznieks who noted a “broad consensus on foreign‑policy priorities.” With NATO and EU membership, Latvia is likely to maintain strong solidarity with Ukraine, especially as President Volodymyr Zelenskyy has offered expert assistance for air‑defence upgrades.What Lies Ahead: Policy Priorities and Regional StabilityAnalysts expect the coalition to focus on:Accelerating anti‑drone and air‑defence capabilities.Ensuring economic and energy security amid regional tensions.Deepening cooperation with NATO allies and the EU.Preparing for the upcoming elections while maintaining a pro‑Ukraine stance.

The LeadThe United States has escalated its threats against Oman, warning that it would "aggressively" impose sanctions if the Gulf ally helps Iran establish a tolling system in the Strait of Hormuz. This intensifies President Donald Trump's recent threats against Oman, including a warning to "blow them up" if they don't comply with US demands regarding the strategic waterway.US Treasury's Aggressive StanceUS Treasury Secretary Scott Bessent stated on Thursday that Washington will "not tolerate" either country imposing fees on commercial ships in the strategic waterway. "Oman, in particular, should know that the US Treasury will aggressively target any actors involved — directly or indirectly — in facilitating tolls for the Strait and any willing partners will be penalized," Bessent said in a social media post."All nations should reject outright any efforts by Iran to disrupt the free flow of commerce. Tehran's days of terrorizing the region and the world are over."Global Energy Security at RiskAbout 20 percent of the world's oil flowed through Hormuz before the conflict, making the Iranian blockade a major strain on global energy supplies. The closure has sent oil prices soaring and threatens economic stability worldwide. The strait's critical importance to global energy markets makes any disruption a matter of international concern.Regional Power Dynamics ShiftThe statement comes less than 24 hours after President Trump threatened to bomb Oman, a key US ally known for its neutrality and mediation efforts in regional crises. This unprecedented threat against a close security and economic partner signals a significant shift in US foreign policy in the Middle East.While Iran has suggested joint Iranian-Omani management of the Hormuz Strait, Oman has not explicitly stated it is seeking control over the waterway, parts of which flow through its territory.Future Outlook for Hormuz StraitThe US and Iran have been indirectly negotiating to reach an agreement for a comprehensive end to the war, with control over the Hormuz Strait emerging as a major point of disagreement. Trump has stressed that the strait must remain a free passageway for international commerce.Ali Bagheri Kani, deputy secretary of Iran's Supreme National Security Council, countered that Tehran will not allow Hormuz to be a source of insecurity for the country, stating that "the powers that have used this passage against Iran's security must be held accountable." The standoff continues as both nations dig in on their positions regarding control of this vital waterway.

The Lease Duration Dispute A controversy has arisen regarding the length of Anthropic's lease with SpaceX, a deal that involves billions of dollars a month for exclusive use of Anthropic's Colossus cluster. Elon Musk claimed on X that the lease is for 180 days with a 90-day notice for mutual cancellation, while SpaceX's recent S-1 filing presents the deal as a three-year agreement. The Details of the Deal According to Musk, the short-term lease was SpaceX's request, not Anthropic's. He stated that SpaceX won't leave Anthropic hanging and will provide a reasonable off-ramp, but might need the compute capacity back if it gets super tight. On the other hand, SpaceX's S-1 filing confirms a 90-day cancellation notice but describes the agreement as lasting through May 2029, with a monthly fee. The Data Analysis The deal involves a significant monthly fee of $1.25 billion, as mentioned in the S-1 filing. This substantial commitment highlights the importance of the compute capacity for both parties. The Impact Analysis The discrepancy between Musk's statement and SpaceX's filing raises questions about the accuracy of the information provided. This situation could be seen as a material misrepresentation made while marketing a security, which could have implications for investors and the companies involved. The Prediction The future of the lease and the relationship between Anthropic and SpaceX will depend on how this situation unfolds. With the SEC possibly involved, the companies will need to clarify the terms of the agreement to avoid any further controversy.

The Rise of Recursive Self-Improvement in AIThe word "recursion" is the latest buzzword in AI circles. Two separate startups have taken on the name, and many more have started referencing recursive self-improvement (RSI) in their roadmaps. Like AGI before it, RSI has become a three-letter byword for a cataclysmic AI takeoff – even if there's still a little disagreement about what it exactly means.In basic terms, RSI refers to an AI system that can continuously upgrade itself. Once AI systems can manage the upgrade cycle better than humans, the process can become a closed loop, limited only by the compute power they can access, and humans are no longer necessary or even helpful.Scary or not, that's a vision that a lot of AI labs are eager to chase.Key Players Pursuing Recursive SystemsEarlier this month, well-known AI researcher Richard Socher launched the aptly named Recursive Superintelligence with RSI as an explicit goal. "Our main focus is to build truly recursive, self-improving superintelligence at scale," Socher told TechCrunch at launch, "which means that the entire process of ideation, implementation, and validation of research ideas would be automatic."A number of other prominent researchers are already chasing that same goal, hoping for a breakthrough that will make recursive self-improvement possible.One of the most prominent is Andrej Karpathy, a legendary figure from Tesla and OpenAI, who is using agent swarms to train LLMs on simple tasks for a project he calls Auto-Research. Karpathy has been unusually open about the project, tweeting about milestones regularly and making the building blocks available through a public GitHub repo. So far, the work has mostly been confined to making minor improvements on a GPT-2 scale model — as Karpathy noted in March, "It's not novel, ground-breaking 'research' (yet)" — but it's been enough to convince lots of other researchers to follow the RSI dream. And with Karpathy now working on pre-training at Anthropic, he will have plenty of opportunity to apply the idea at a larger scale.Adaption — founded by Cohere and Google alum Sara Hooker — recently launched a similar tool called AutoScientist in an effort to automate frontier training. Like Karpathy's auto-researchers, the system trains agents to make incremental improvements — but for Adaption, the goal is to make it easier to train a full-scale frontier model. If those same researchers start to push the frontier forward, the system could quickly spiral into something very much like RSI.Disarray founder Doris Xin drew more specific RSI interest when her self-trained machine learning agent took home 28 medals in a recent Kaggle competition, beating out many human-trained agents. As she sees it, the major challenge is reliability."I would argue, given infinite compute and infinite time horizon, we are already there," Xin told me. "I want to make an argument that this is not a creative endeavor, really. It's just a lot of meat-and-potatoes engineering."The Current State of Self-Improving AIThere's also plenty of evidence that the AI industry isn't very close to recursive systems in any meaningful way — and is still grappling with talking to a wary public about its progress. So Google CEO Sundar Pichai basically admitted in a recent podcast interview."It's a continuum, and we are all definitely making progress," Pichai said. "But in the way people describe RSI, that would represent a next level of acceleration and would have a lot of implications, but we aren't quite there yet."But the continuum includes an awful lot of self-improving AI systems.In January, one of Anthropic's lead programmers for Claude Code estimated that "close to 100%" of his team's code was written by the tool — a frank admission that Claude Code was literally writing itself.Just because engineers are using an AI tool doesn't mean the tool can replace them — but Anthropic seems to be getting close to replacing engineers too. In a recent survey tied to the Mythos preview, five out of 18 Anthropic engineers believed that, with harness improvements, this version of Mythos could soon substitute for an L4 engineer — a midlevel programmer who can take on involved projects without supervision.Still, there were some of the same weaknesses you might expect."Some of Claude's major reported weaknesses compared to an L4 include: self-managing week-long ambiguous tasks, understanding org priorities, taste, verification, instruction-following, and epistemics," the report reads.In other words, its weaknesses are everything involved with self-direction, which is the cornerstone for RSI. But sure, for everything else, Claude is ready to step right in.Expert Perspectives on RSI TimelinesJust like the AGI term before it, the AI industry also can't tell us how far away it is from showcasing a meaningful recursive system. When Georgetown's Center for Security and Emerging Technology assembled a group of experts to study RSI last year, the group found a major split in assessments — some expecting an imminent "superintelligence" style explosion while others expected slower progress and an eventual plateau. But all agreed that recursion made the future especially difficult to predict.Helen Toner, director of CSET and a former board member at OpenAI, told TechCrunch that simply using AI tools to do AI research isn't enough to qualify as RSI. "They're just using AI for as much as they can," Toner told TechCrunch. "And I think that is different from the classic definition of RSI, which is really that there are no humans needed."Toner pointed to a recent post by METR's Ajeya Cotra, which distinguishes different milestones on the path to the AI research takeover. One step, which Cotra calls "adequacy," would come when the system can still perform research after all humans are removed — even if the resulting research isn't as valuable or efficient. "Parity" comes when an AI-only system is as good at research as a human-only system. "Supremacy," the final stage, comes when an AI-only system outperforms a collaborative system between humans and AI.Ultimately, Cotra concludes that AI is very close to the adequacy threshold of being able to produce some work on its own — similar to the incremental changes made by Karpathy's Auto-Research system. "I wouldn't be totally shocked if you told me this milestone had already passed, and I expect it to happen in the next couple years," Cotra wrote.She was less clear on when parity will come, but once it does, she thinks it would "massively accelerate the pace of AI progress, leading to AI research supremacy within another year."The Challenges Ahead for Recursive AIWith so much of AI built on scaling laws, there's a strong tendency to think RSI will follow the same curve. Toner thinks that many of those pursuing AI research and development via RSI "think of it as a pretty smooth ladder, where you can just keep scaling up."But even if AI researchers are able to make incremental improvements like Karpathy's auto-researchers, there will be larger challenges in handing off the whole process of research. Toner put it in terms of the history of computing, which has seen human beings handing off more and more of the process while still directing things from the top."We went from machine languages to assembly language and compiled languages; you're getting further and further from the guts of the computer," Toner said. "But the human is still, in some intuitive sense, running the show."Moving beyond that paradigm will take significant challenges, both in engineering and alignment. But even with the massive investments happening, there's no infinite compute available — and the basic trade-off between human labor and machine intelligence will be hard to overcome.The Future of Recursive Self-ImprovementAs for a total recursive AI system of apocalyptic visions? The only thing researchers essentially agree on is that, like AGI, it's not here yet.

The Lead Enterprise organizations are not rejecting AI. They are rejecting operational instability. This is the shift many founders still misunderstand — and it is becoming one of the defining realities separating enterprise AI companies that scale from the ones that stall after early momentum. The Event Details At TechCrunch Disrupt 2026, taking place October 13–15 at Moscone West in San Francisco, Arsalan Tavakoli-Shiraji, co-founder and SVP of field engineering at Databricks, will unpack that shift during his AI Stage session, “The Enterprise Isn’t Broken. Your Assumptions About It Are.” The Data Analysis The enterprise AI market is full of successful pilots that never became real deployments. Not because the technology failed. But because the organization could not absorb the operational consequences of adopting it. The Impact Analysis Now the reality founders need to face is that startup AI deals rarely die because the model underperformed. They die because the enterprise lost confidence in what the deployment would require. The AI startups gaining traction inside large organizations increasingly share one thing in common: They reduce uncertainty. The Prediction The startups that succeed in enterprise AI over the next several years may not necessarily be the ones with the most advanced models. They may be the ones that best understand how enterprises actually absorb change. That is the kind of operational pressure that Tavakoli-Shiraji and other speakers on the AI Stage at Disrupt will explore.