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The AI Startup Valuation ShiftAnthropic has usurped OpenAI as the world's most valuable artificial intelligence startup, soaring to a $965bn valuation ahead of expected public listings by the rival firms. Anthropic, the maker of the Claude family of chatbots, said on Thursday that it had raised $65bn from private investors after a fundraising round led by Altimeter Capital, Greenoaks, Dragoneer and Sequoia Capital.Funding and Leadership PositionThe announcement catapults Anthropic, led by CEO and cofounder Dario Amodei, ahead of ChatGPT maker OpenAI in value, which attracted an $852bn valuation in its last fundraising round in March. "This funding will help us serve the historic demand we are experiencing, stay at the research frontier, and bring Claude to more of the places where work happens," Anthropic's Chief Financial Officer Krishna Rao said in a statement.Market Recognition and AdoptionAltimeter Capital CEO Brad Gerstner hailed the adoption of Claude among the "world's most demanding organisations" as evidence of Anthropic's command in the field. "This momentum positions Anthropic to lead the next phase of AI innovation and capture the enormous opportunity ahead," Gerstner said.Rapid Growth and Market PositionFounded in 2021 by former OpenAI researchers, Anthropic has rapidly emerged as one of the leading players in Silicon Valley's scramble to dominate AI. Anthropic's Claude, first launched in 2023, is among the most popular AI models worldwide. In March, the San Francisco-based company said that the chatbot was receiving more than 1 million new sign-ups each day.Challenges and Recent DevelopmentsWhile achieving stellar success in rapid time, Anthropic has also faced challenges – in particular, a high-profile dispute with US President Donald Trump's administration, which has labelled the firm a "supply chain risk" over its refusal to allow unrestricted access to its tools for military purposes. Anthropic unveiled its latest iteration of Claude, Opus 4.8, in a separate announcement on Thursday, calling it a "modest but tangible improvement" on its predecessor.Future Outlook and Market DynamicsAnthropic, OpenAI and Elon Musk's rocket company SpaceX are all expected to go public in the near future in what are expected to be among the biggest initial public offerings in history. Jay R Ritter, an emeritus professor at the University of Florida who specialises in IPOs, said Anthropic has generated a lot of market excitement due to its widespread use by companies for software coding. "This is a big market where apparently Anthropic has the best product," Ritter told Al Jazeera.Valuation Trends and Market Analysis"The increase in valuation in a short period of time is unprecedented for a startup, although publicly traded tech companies such as SK Hynix, Nvidia, and Alphabet have seen even bigger increases, although not as much in percentage terms," Ritter said, referring to the South Korean and US chip giants, and Google's parent company. While it remains to be seen whether the massive investments pouring into AI are creating a bubble, Ritter said, the handful of successful firms that are likely to emerge in the field could see enormous profits.Industry Consolidation and Future Prospects"Nobody wants to use the eighth best product, so these companies are either one of the handful of successful firms, or they will have a zero market share," he said. "The tech industry is different than the restaurant industry, where there are not large economies of scale, and where competition limits the profit margins."

The Lead This week at TechCrunch’s StrictlyVC event in Athens, I sat down with three top VCs to discuss the current state of venture investing, the wave of mega-IPOs, and where they see opportunities in AI. VC Insights on AI and Mega-IPOs The conversation featured Niko Bonatsos of Verdict Capital, Andreas Stavropoulos of Threshold Ventures, and Ben Blume of Atomico. They discussed the potential impact of SpaceX's reported $1.75 trillion valuation at IPO, as well as the opportunities and challenges in the AI space. The Data Analysis SpaceX's potential $1.75 trillion valuation at IPO OpenAI and Anthropic potentially not far behind in terms of valuation Three-quarters of all venture capital raised over the last year went into five companies $500 million fund looking at the same opportunities as people investing from a $10 billion or $15 billion fund The Impact Analysis The VCs discussed how the current flood of capital into AI may be justified by future earnings, but also acknowledged the risk of extreme FOMO (fear of missing out). They also touched on the challenges of pricing deals when things are moving fast and the importance of looking beyond age as a proxy for entrepreneurial potential. The Prediction The VCs see opportunities in areas such as consumer fintech, AI interacting with the physical world, and robotics. They predict that the next generation of companies will be able to go after much larger markets and that immigrant founders will continue to play a significant role in driving innovation.

Executive Summary: Glean’s $300M ARR MilestoneGlean announced it has reached $300 million in annual recurring revenue (ARR), a three‑fold increase from the $100 million mark just 15 months earlier. The growth is driven by its “context graph” technology that promises to slash AI token usage and lower enterprise AI spend.Growth in a Crowded Enterprise AI Search LandscapeFounded seven years ago, Glean was once the sole player in enterprise AI search. Today, giants such as Google, Microsoft, OpenAI, Anthropic, Salesforce and Atlassian are launching competing solutions. CEO Arvind Jain argues that first‑mover advantage combined with deeper “context graph” insights gives Glean a competitive edge.Revenue Structure: Consumption‑Based and Hybrid ModelsARR reached $300M, up from $100M in just 15 months.Pricing includes a per‑use consumption model and a hybrid model (fixed monthly fee + usage fees).Recent Series F raised $150M at a $7.2B valuation.Key customers: Databricks, Reddit, Pinterest, Samsung.Cost‑Efficiency as a Market DifferentiatorGlean’s context graph reduces the number of tokens an AI model must process, translating into lower compute costs for clients. In an environment where many firms are “blowing through their AI budgets,” this token‑saving capability has become a major selling point.Looking Ahead: Scaling the Context Graph AdvantageAnalysts expect Glean to leverage its cost‑saving narrative to win additional enterprise contracts, especially as larger vendors struggle to match its token‑efficiency. Continued product enhancements and expansion into new verticals could push ARR beyond the $500M threshold within the next 12‑18 months.

Asana's Strategic AI AcquisitionAsana has acquired the workflow automation company StackAI for $75 million, marking a significant step in the company's broader AI pivot. The acquisition aims to position Asana as an "AI-native workplace platform" and integrate StackAI's agent-building capabilities into Asana's existing work management system. The announcement was made Thursday afternoon to coincide with Asana's earnings and investor call.StackAI's Workflow Automation CapabilitiesStackAI, built as an AI workflow-automation system, designs agents to operate within existing business systems, pulling in data from platforms like Salesforce, Slack, and Gsuite. The company, founded by Tony Rosinol and Bernard Aceituno, will join Asana as part of the acquisition. StackAI has faced competition from automation tools like Zapier as well as AI labs like OpenAI and Anthropic in the rapidly evolving AI automation space.Financial Terms and Funding BackgroundThe acquisition comes as StackAI had raised just under $20 million, according to PitchBook data, with most of it coming in a recent $16 million Series A round. That round included funding from Gradient, Epakon Capital, Lobby VC, LifeX Ventures, and Vercel CEO Guillermo Rauch. While the $75 million acquisition price represents a significant premium over StackAI's funding, it reflects Asana's commitment to accelerating its AI capabilities.Asana's AI-Native TransformationWhile users are most familiar with Asana's work management system, the company has been releasing AI-oriented products in recent years, including the AI Studio agent builder and AI Teammates series of pre-built automations. Asana believes its deep integration into existing corporate workflows provides a key advantage, allowing it to distill context and training data that would otherwise be unavailable. This acquisition specifically aims to "agentify the most complex business processes end-to-end," according to CEO Dan Rogers.Future of Human-Agent Work in EnterpriseAsana has struggled on public markets during the AI era, losing more than half its market cap value since the introduction of ChatGPT. However, revenue has continued to grow steadily, and the new leadership is confident that human-agent products will enable a rebound. With this acquisition, Asana aims to accelerate its roadmap into "the next phase of human-agent work," potentially differentiating itself from both traditional work management platforms and standalone AI automation tools in the competitive enterprise software landscape.

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 Lead Anthropic has released Opus 4.8, the newest version of its most advanced publicly available model, with a new 'dynamic workflow' tool. The model is available everywhere at standard pricing. The Event Details Opus 4.8 comes just 41 days after Opus 4.7 was released, a much faster upgrade cycle than normal for Anthropic. The new model features best-in-class benchmark results and improved handling of bad or uncertain data. Anthropic's early testers found that Opus 4.8 is "more likely to flag uncertainties about its work and less likely to make unsupported claims." The Data Analysis Opus 4.8 is available at standard pricing. The model comes with a new 'dynamic workflow' tool, available in research preview. Anthropic's most advanced Mythos model is still in development, with a tentative preview last month. The Impact Analysis The fast turnaround for Opus 4.8 may be in response to the chilly reception of Opus 4.7 and increasing pressure from competitors like OpenAI's Codex and Google's Gemini Flash model. The new model's ability to handle uncertain data and flag issues with inputs and outputs could give it an edge in the market. The Prediction Anthropic hinted that the Mythos preview period might soon end, once necessary safeguards are complete. The company expects to bring Mythos-class models to all its customers in the coming weeks. With Opus 4.8 and the dynamic workflow tool, Anthropic is positioning itself to compete with other major players in the AI market.

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: Vertu's AI-Powered Foldable Targets Executive Market Luxury smartphone brand Vertu has unveiled the Alphafold, a foldable phone powered by an AI agent designed specifically for executives managing business operations on the move. The device represents Vertu's latest attempt to reinvent itself for the AI era, combining luxury materials with enterprise-focused AI capabilities to target the high-end business market. The Event Details: Luxury Meets AI: The Alphafold's Enterprise Capabilities The Alphafold features Hermes Agent, built on the open-source Hermes project by Nous Research, which can connect to enterprise systems like ERP and CRM. The AI agent coordinates tasks such as approvals, scheduling, sales tracking, travel planning, and operational reporting through natural-language prompts. The device can route requests across multiple AI models including OpenAI's GPT, Anthropic's Claude, Google's Gemini, and selected open-source models, while integrating with more than 80 apps and dozens of native phone functions for cross-platform workflows. Vertu has emphasized the device's privacy-focused architecture featuring a proprietary A5 security chip designed to isolate authentication keys, biometric credentials, and sensitive enterprise information from the main operating system. The company states that commercially sensitive data can be processed locally on the device, while prompts sent to external AI models are redacted or tokenized before leaving the phone. The Data Analysis: Premium Pricing Strategy in the Smartphone Market The Alphafold starts at $6,880 for the calfskin version, with higher-end models featuring bespoke finishes including alligator leather, 18K gold, and natural diamond accents. Vertu's highest-end standard model is currently priced at $46,800, with further customization options available. This pricing strategy positions Vertu firmly in the ultra-premium segment of the smartphone market. While foldable smartphones remain a niche segment globally—with IDC data showing approximately 20 million units shipped in 2025, accounting for less than 2% of total smartphone shipments—Vertu is betting that the combination of luxury materials and AI capabilities will justify its premium pricing. The average price of foldable smartphones was about $1,300 last year, roughly three times the price of non-foldable smartphones. The Impact Analysis: How AI is Transforming Executive Productivity Vertu CEO Molly Ma highlighted that existing AI features on smartphones from major manufacturers remain focused largely on consumer tools such as image editing and voice assistance, leaving room for more advanced AI-agent workflows tied to enterprise systems. The Alphafold aims to address this gap by providing executives with a device that can seamlessly integrate with their business operations and workflows. The device's larger foldable display (8.05-inch inner screen and 6.53-inch outer screen) is better suited for multitasking and productivity-oriented experiences, according to Kiranjeet Kaur, associate research director for mobile phones research at IDC. However, she noted that enterprise AI adoption on smartphones still lags behind computers, with most enterprise smartphone decisions continuing to be driven by ecosystem integration and device management support rather than AI capabilities. The Prediction: The Future of Luxury AI-Powered Mobile Devices The Alphafold represents Vertu's significant step forward from its previous AI-focused device, Agent Q, with Ma noting that AI-agent technology has matured rapidly over the past year, with improvements in memory, automation, and app integration. While the company has not yet undergone third-party security audits for the device, it has confirmed that independent audits and certification remain on its security roadmap. As the first 115-unit batch of Vertu's Alphafold begins shipping across major markets including the U.S., the device will serve as a test case for whether there's a market for luxury smartphones with enterprise AI capabilities. If successful, Vertu's approach could inspire other manufacturers to develop similar devices targeting the executive market, potentially accelerating the integration of AI agents into mobile workflows.