News & Updates
The latest news and updates from companies in the WLTH portfolio.
Anthropic's Most Powerful AI Is Struggling: Why Businesses Are Choosing Cheaper Rivals
Anthropic's latest flagship AI model, Fable 5, is reportedly seeing slower-than-expected adoption among enterprise customers. The reason is not performance-related, but it is largely due to the pricing. As AI becomes a daily business tool, companies are increasingly choosing cheaper, efficient language models that offer strong real-world performance at a lower operating cost. Here is all that you need to know. For the last two years, AI companies have become increasingly competitive in building the most intelligent language model. Each major launch comes with better reasoning, stronger coding abilities and more human-like conversations. But the next phase of the AI race may not be decided by intelligence alone. In the real world, pricing also matters. When two AI tools do the same job, businesses prefer going for the one that costs less. Anthropic's flagship Fable 5 model is reportedly witnessing weaker-than-expected demand from enterprise customers, as many businesses increasingly opt for lower-cost alternatives that are capable of handling everyday workloads. The development signals a major shift in how organisations evaluate AI investments and that value is becoming just as important as performance. Here is everything you need to know about this shift in behaviour and how Anthropic is performing:
Anthropic Has a $65 Billion Run Rate. Buy These Stocks to Profit From It.
Anthropic, the owner and operator of the popular Claude chatbot, has an annualized revenue run rate of $65 billion, multiple media outlets just confirmed. That's about seven times what it was at the end of last year. The company has filed with the Securities and Exchange Commission to go public later this year through an initial public offering (IPO) that could value it at $2 trillion or more. But because the AI firm is not yet public, there aren't many ways for retail investors to buy a direct stake in it. Missed Nvidia in 2009? This Rare Signal Is Flashing Again. In 2009, a "Double Down" signal flashed for a little-known chipmaker called Nvidia. For the first time in years, that same "Total Conviction" signal is flashing for a company 1/100th the size of Nvidia. Continue " There is an indirect way to get some exposure to Anthropic, however. That's by owning the stocks of companies that have invested heavily in its pre-IPO shares. Image source: Getty Images. That group starts with Amazon (NASDAQ: AMZN). The company's $33 billion investment in Anthropic gave it an impressive 21% stake. Google's parent company, Alphabet (NASDAQ: GOOGL) (NASDAQ: GOOG), holds a 15% stake in Anthropic and can't invest more because the two are major competitors in the large language model space. (Alphabet owns Gemini AI). Salesforce (NYSE: CRM) has a $5 billion stake in the AI firm. Finally, Zoom Communications (NASDAQ: ZM) has a more modest $1.3 billion stake in it. Like everything else those companies own, their stakes in Anthropic are ultimately owned by their shareholders. So their investors should see a major benefit if Anthropic's IPO brings it a valuation of $2 trillion or more. Several tech firms booked big gains from their SpaceX stakes There's a recent precedent for this. In the second quarter of this year, two major technology firms had the biggest positive impact on overall S&P 500 earnings due to their stakes in other firms. Alphabet reported earnings per share of $9.11, more than three times Wall Street's expectations, driven by $98 billion in unrealized stock gains primarily from its ownership stake in Space Exploration Technologies (NASDAQ: SPCX), which went public that quarter. Similarly, Amazon reported $53.4 billion in income from a revaluation of its investment in Anthropic (pre-IPO companies are officially revalued during each new capital-raising round). Amazon shares soared following the release of its second-quarter results. If Anthropic stages a blockbuster IPO, that investment would be revalued significantly higher again. Neither Amazon nor Alphabet shares have had a particularly great 2026, however. After soaring in 2025, both stocks have delivered much more modest gains this year, mostly due to investors' concerns that their massive investments in AI infrastructure will not produce significant returns on investment. Salesforce's share price is down 22% year to date, as investors fear that AI tools could render the company's software obsolete. It's not clear what the future holds for any of these companies, of course. AI technologies are already proving to be a seriously disruptive force -- both positive and negative -- for many industries. Where to invest $1,000 right now When our analyst team has a stock tip, it can pay to listen. After all, Stock Advisor's total average return is 965%* -- a market-crushing outperformance compared to 212% for the S&P 500. They just revealed what they believe are the 10 best stocks for investors to buy right now, available when you join Stock Advisor. See the stocks " *Stock Advisor returns as of August 24, 2026. Matthew Benjamin has positions in Alphabet. The Motley Fool has positions in and recommends Alphabet, Amazon, Salesforce, and Zoom Communications. The Motley Fool has a disclosure policy.
Anthropic Has a $65 Billion Run Rate. Buy These Stocks to Profit From It.
Anthropic, the owner and operator of the popular Claude chatbot, has an annualized revenue run rate of $65 billion, multiple media outlets just confirmed. That's about seven times what it was at the end of last year. The company has filed with the Securities and Exchange Commission to go public later this year through an initial public offering (IPO) that could value it at $2 trillion or more. But because the AI firm is not yet public, there aren't many ways for retail investors to buy a direct stake in it. Missed Nvidia in 2009? This Rare Signal Is Flashing Again. In 2009, a "Double Down" signal flashed for a little-known chipmaker called Nvidia. For the first time in years, that same "Total Conviction" signal is flashing for a company 1/100th the size of Nvidia. Continue " There is an indirect way to get some exposure to Anthropic, however. That's by owning the stocks of companies that have invested heavily in its pre-IPO shares. That group starts with Amazon (NASDAQ: AMZN). The company's $33 billion investment in Anthropic gave it an impressive 21% stake. Google's parent company, Alphabet (NASDAQ: GOOGL) (NASDAQ: GOOG), holds a 15% stake in Anthropic and can't invest more because the two are major competitors in the large language model space. (Alphabet owns Gemini AI). Salesforce (NYSE: CRM) has a $5 billion stake in the AI firm. Finally, Zoom Communications (NASDAQ: ZM) has a more modest $1.3 billion stake in it. Like everything else those companies own, their stakes in Anthropic are ultimately owned by their shareholders. So their investors should see a major benefit if Anthropic's IPO brings it a valuation of $2 trillion or more. Several tech firms booked big gains from their SpaceX stakes There's a recent precedent for this. In the second quarter of this year, two major technology firms had the biggest positive impact on overall S&P 500 earnings due to their stakes in other firms. Alphabet reported earnings per share of $9.11, more than three times Wall Street's expectations, driven by $98 billion in unrealized stock gains primarily from its ownership stake in Space Exploration Technologies (NASDAQ: SPCX), which went public that quarter. Similarly, Amazon reported $53.4 billion in income from a revaluation of its investment in Anthropic (pre-IPO companies are officially revalued during each new capital-raising round). Amazon shares soared following the release of its second-quarter results. If Anthropic stages a blockbuster IPO, that investment would be revalued significantly higher again.
Scoop: Anthropic asks about mission versus money in candidate interviews
The big picture: CEO Dario Amodei has questioned whether newer employees are joining the AI lab for the right reasons, according to a source familiar. The interview process gets to the heart of that tension. What they're saying: Anthropic candidates all go through a culture interview, conducted by an employee who is nominated for the task. * One applicant -- who spoke to Axios on the condition of anonymity for fear of hurting future job opportunities -- recalled being asked how they would feel if the company someday abandoned its AI ambitions for safety reasons, and that decision sent the stock to zero. * A former Anthropic employee familiar with the process said the questions are suggested, but not fully scripted. * That could explain why some applicants remember the question relating to an actual stock crash while others said it was generally related to safety trade-offs that could impact revenue. Zoom in: Anthropic has a standard process for interviews and compensation, according to a source familiar. * What you're offered is what you get. Negotiations are not part of the process. * During the culture interviews, candidates are also asked to talk about a moral quandary they've faced and how they handled it. * "I was honest and said no, I would not be happy if the stock went to 0. ... I would want to align doing the most good and remaining ethical while building a sustaining business. The interviewer didn't seem to like that answer," a writer on the anonymous workplace site Blind wrote. The other side: According to two former Anthropic employees, this interview question was not previously part of the interview process. * Additional posts on Blind indicate candidates got this interview question in 2025. * "Anthropic's had a culture interview since day one," co-founder and president Daniela Amodei said in a Bain Capital video posted two years ago. Follow the money: Prospective employees presumably expect high salaries and eventual returns on their equity, based on how much they're willing to spend to prepare for their interviews. * Some candidates are paying thousands of dollars for private coaching or for mock interviews with engineers from top AI companies, according to Bloomberg. * "Spend a few thousand dollars, and now your salary goes up by $200,000 -- that calculus makes sense," Aline Lerner, founder of prep company Interviewing.io, told Bloomberg. The intrigue: Dario Amodei himself is on track to be one of the richest people in the world after the company goes public, though he has repeatedly pledged to donate 80% of his wealth. Zoom out: "At the end of the day, the mission is what we're all here for," the company's career page states. * That page includes an overview of the interview process, with the word "mission" mentioned six times. Flashback: The money versus mission interview question mirrors situations Anthropic has found itself in publicly. * The company refused to cut a deal with the U.S. military that would allow the government unfettered use of its technology, resulting in lost government contracts. * The company limited access to Mythos, its most cyber capable model, due to safety concerns. Yes, but: It's not clear that these choices were net negative for revenue, and that's difficult to confirm as Anthropic isn't a public company, yet. * After the Department of War scuffle, for example, Anthropic's Claude app hit No. 1 on U.S. app store charts. The bottom line: If you're interviewing at Anthropic, get ready to talk morality.
Anthropic Has a $65 Billion Run Rate. Buy These Stocks to Profit From It.
Anthropic, the owner and operator of the popular Claude chatbot, has an annualized revenue run rate of $65 billion, multiple media outlets just confirmed. That's about seven times what it was at the end of last year. The company has filed with the Securities and Exchange Commission to go public later this year through an initial public offering (IPO) that could value it at $2 trillion or more. But because the AI firm is not yet public, there aren't many ways for retail investors to buy a direct stake in it. There is an indirect way to get some exposure to Anthropic, however. That's by owning the stocks of companies that have invested heavily in its pre-IPO shares. That group starts with Amazon (AMZN -0.57%). The company's $33 billion investment in Anthropic gave it an impressive 21% stake. Google's parent company, Alphabet (GOOGL +1.22%) (GOOG +1.05%), holds a 15% stake in Anthropic and can't invest more because the two are major competitors in the large language model space. (Alphabet owns Gemini AI). Salesforce (CRM +1.82%) has a $5 billion stake in the AI firm. Finally, Zoom Communications (ZM +1.06%) has a more modest $1.3 billion stake in it. Like everything else those companies own, their stakes in Anthropic are ultimately owned by their shareholders. So their investors should see a major benefit if Anthropic's IPO brings it a valuation of $2 trillion or more. Several tech firms booked big gains from their SpaceX stakes There's a recent precedent for this. In the second quarter of this year, two major technology firms had the biggest positive impact on overall S&P 500 earnings due to their stakes in other firms. Alphabet reported earnings per share of $9.11, more than three times Wall Street's expectations, driven by $98 billion in unrealized stock gains primarily from its ownership stake in Space Exploration Technologies (SPCX +2.22%), which went public that quarter. Similarly, Amazon reported $53.4 billion in income from a revaluation of its investment in Anthropic (pre-IPO companies are officially revalued during each new capital-raising round). Amazon shares soared following the release of its second-quarter results. If Anthropic stages a blockbuster IPO, that investment would be revalued significantly higher again. Neither Amazon nor Alphabet shares have had a particularly great 2026, however. After soaring in 2025, both stocks have delivered much more modest gains this year, mostly due to investors' concerns that their massive investments in AI infrastructure will not produce significant returns on investment. Salesforce's share price is down 22% year to date, as investors fear that AI tools could render the company's software obsolete. It's not clear what the future holds for any of these companies, of course. AI technologies are already proving to be a seriously disruptive force -- both positive and negative -- for many industries.
Nvidia shows interest in Perplexity as valuation hits USD 30 billion
Nvidia is reportedly interested in investing in Perplexity, whose valuation exceeds USD 30 billion. TIONGKOK - Nvidia NVDA.O is in talks to invest in Perplexity as part of an equity funding round that would value the AI startup at more than USD 30 billion, The Information reported on Sunday (22/8), citing sources familiar with the discussions. The funding round would increase Perplexity's valuation by more than 50% compared with its previous funding round a year ago, according to the report. As quoted by Reuters, Perplexity's annualised revenue has risen to more than USD 750 million, from less than USD 250 million at the beginning of the year, according to the report. Part of the revenue growth was driven by Perplexity Computer, a cloud-based AI agent used by professionals to automate various computer-based tasks, the report added, citing sources familiar with the matter. Perplexity declined to comment on The Information's report, while Nvidia did not immediately respond to a request for comment. The Information reported in September last year that Perplexity had finalised a valuation of USD 20 billion. Earlier this year, Perplexity signed a USD 750 million deal with Microsoft MSFT.O to use Microsoft's Azure cloud services, Bloomberg News reported. Perplexity plans to go public in 2028, regardless of how markets respond to the listings of Anthropic and OpenAI, Perplexity CEO Aravind Srinivas said in an interview with CNBC in June. The startup's major backers, besides Nvidia, include Amazon founder Jeff Bezos and Japan's SoftBank Group 9984.T. (DK/ZH)
Anthropic has a $65 billion annual revenue run rate
Anthropic, the AI company behind the Claude product, has reportedly achieved a $65 billion annual revenue run rate by the end of July 2026, according to a report from Motley Fool. This figure marks a significant increase from the $47 billion run rate reported in May and a substantial leap from approximately $9 billion at the end of 2025. The revenue milestone comes ahead of Anthropic's potential initial public offering (IPO) later this year, a development closely monitored by investors and market analysts. The reported growth is seen as a key indicator of Anthropic's expanding market presence and may influence its valuation in upcoming private market assessments. Key Takeaways * Anthropic's revenue run rate appears to have increased substantially, suggesting strong growth momentum. * Market pricing suggests there is confidence in Anthropic reaching a valuation of $1.25 trillion by December 31, with YES outcomes currently priced at 98%. * The anticipation of an IPO later this year adds a notable factor to Anthropic's market dynamics, potentially impacting valuation estimates. What to Watch Observers will be keenly watching for any announcements regarding Anthropic's IPO, as these could significantly impact market sentiment and valuation predictions. Potential strategic moves by major investors such as Amazon and Google may also influence the market. Any updates on Anthropic's revenue projections or strategic partnerships would be consistent with scenarios supporting a higher valuation outcome. Additionally, scrutiny of media coverage and analyst reports will continue to shape market expectations around Anthropic's financial trajectory and its implications for the valuation by year-end. Get live prediction-market analysis, powered by Vera. Sign up for Vera.
Nvidia Eyeing Investment in AI Startup Perplexity
NVIDIA Corporation is the world leader in the design, development, and marketing of programmable graphics processors. The group also develops associated software. Net sales break down by family of products as follows: - computing and networking solutions (89%): data center platforms and infrastructure, Ethernet interconnect solutions, high-performance computing solutions, platforms and solutions for autonomous and intelligent vehicles, solutions for enterprise artificial intelligence infrastructure, crypto-currency mining processors, embedded computer boards for robotics, teaching, learning and artificial intelligence development, etc.; - graphics processors (11%): for PCs, game consoles, video game streaming platforms, workstations, etc. (GeForce, NVIDIA RTX, Quadro brands, etc.). The group also offers laptops, desktops, gaming computers, computer peripherals (monitors, mice, joysticks, remote controls, etc.), software for visual and virtual computing, platforms for automotive infotainment systems and cloud collaboration platforms. Net sales break down by industry between data storage (88.3%), gaming (8.7%), professional visualization (1.4%), automotive (1.3%) and other (0.3%). Net sales are distributed geographically as follows: the United States (46.9%), Singapore (18.2%), Taiwan (15.8%), China and Hong Kong (13.1%) and other (6%).
Nvidia is in talks to back Perplexity at more than $30bn
The chipmaker also weighed a technology licensing arrangement alongside the equity cheque, according to The Information. Nvidia has been discussing an investment in Perplexity that would value the AI search company at more than $30bn, according to The Information, which reported that the two sides also considered a technology licensing arrangement alongside the equity cheque. The talks are the latest turn in a relationship that already runs deeper than the usual investor-and-customer arrangement, since Perplexity was among the first named takers for Nvidia's Vera CPU. At more than $30bn, the valuation would represent a jump of over 50% on the roughly $20bn Perplexity carried after its last reported round, and it would land the company among the most richly priced private AI businesses in the world. The round itself is described as worth billions of dollars, though neither the size of Nvidia's proposed stake nor the identity of the other participants has been reported. Neither company has commented publicly, and it is not clear whether the licensing component is still live or was set aside during the negotiations. What makes the discussions unremarkable, in one sense, is how routine this kind of cheque has become for Nvidia. Its equity commitments passed $40bn in 2026 alone, spread across model developers, neoclouds, and infrastructure companies that, almost without exception, buy Nvidia silicon with the money. That circularity has started to attract a different sort of attention. When the company announced roughly $750bn of AI-related commitments, its own credit default swaps widened to record levels, a signal from the debt market that the arrangement looks less like diversification than like a supplier financing its own order book. Perplexity is an unusually visible example of the type. Founded in 2022 and led by Aravind Srinivas, it built a conversational search product that answers queries directly rather than returning a page of blue links and has spent the past two years trying to make it durable enough to justify its price. In August 2025, the company made an unsolicited $34.5bn offer for Google's Chrome browser, a bid roughly double its own valuation at the time, which Google never entertained. It has since pushed its own AI browser, Comet, as the vehicle for what Srinivas calls agentic browsing. The competitive picture has not softened while all this was going on. Google has folded conversational answers into its own results page, OpenAI has pushed ChatGPT further into search and shipped a browser of its own, and both arrive with distribution that Perplexity has to buy or build. Perplexity has not disclosed audited figures, and the widely circulated estimates of its annualised run rate come from investor briefings and secondary reporting rather than the company itself, which makes any multiple attached to a $30bn valuation an exercise in faith. Nvidia is already on the cap table, having taken part in earlier rounds that also drew in Jeff Bezos. A licensing deal, had it been agreed, would have been a rarer move, giving Perplexity access to Nvidia technology on terms that sit outside the ordinary customer relationship, and giving Nvidia a stake in how AI search actually gets built rather than merely in the hardware underneath it. For now, the round is unconfirmed, which is worth holding onto. Reports of AI valuations have a habit of arriving well before term sheets are signed, and Perplexity itself has been the subject of several such reports over the past 18 months, at $14bn, at $18bn, and at $20bn, each of which arrived with people familiar with the matter attached and each of which took months to settle into a number anyone would put their name to. Nvidia reports its next quarterly results in November. Whether a Perplexity stake shows up in the investment line by then will say more about the pace of this cycle than the valuation itself does.
Huge Aussie winners include CBA as world gears up for record-breaking Anthropic IPO
The investing world collectively lost its mind over the SpaceX IPO, which became the biggest stock market launch of all time, but another debut is gearing up to eclipse it - and there will be a few very big Aussie winners if it all goes according to plan. Elon Musk's space company went public in June at a value of $1.77 trillion, and raised $85.7 billion in its blockbuster initial public offering, the largest in history. The market debut of artificial intelligence start-up Anthropic, a chief rival to OpenAI, could break its record. The maker of the Claude AI models "expects to match or beat the size" of SpaceX's deal, according to Bloomberg. The company's bankers have told potential investors it could seek to raise "more than $100 billion" in its IPO, which could put the company's value at $2 trillion, The New York Times reported on Friday, citing two unnamed sources with knowledge of the talks. It is hoping to launch the IPO by the end of the year, and there will no doubt be a frenzy around the world as investors look to cash in on the hype around AI. CBA sitting on a potential goldmine One of the biggest winners if everything goes to plan will be Commonwealth Bank (CBA), which made a strategic investment in Anthropic back in March 2025. The goal was to secure cutting-edge AI tech to boost cybersecurity, combat fraud and launch digital tools for Australian small businesses. It has been a huge financial win for Australia's biggest bank too. According to CBA's latest annual report, the carrying value of its Anthropic stake sits at over $1.5 billion -- a colossal leap from just $153 million the year prior. "The fair value of the group's investment at 30 June 2026 was determined with reference to the price of Anthropic's most recent funding round completed in May 2026, in which the group did not participate," the report said. "Through our strategic partnership with Anthropic, our teams have been able to work closely together on some important priorities to better serve and protect our customers. We value the access to frontier models, technology and engineering expertise," Group Chief Technology Officer Rodrigo Castillo told news.com.au. "It's important for CBA, and for other major organisations, to build deep relationships with frontier labs and global technology capability as we respond to an increasingly complex and rapidly changing environment." MST Marquee analyst Brian Johnson crunched the numbers. He told the AFR that if Anthropic achieves its $2 trillion IPO target, CBA's estimated 0.1 per cent holding would be worth a staggering $2.9 billion. CBA might not be the only winner, as other Australian companies have exposure to Anthropic. Superannuation giant AustralianSuper earlier this year revealed it had Anthropic shares, and wealth firm Boman Group took part in Anthropic's earlier fundraising rounds. AI about living standards, CBA CEO says Despite a potential windfall coming to CBA, its CEO Matt Comyn said the bank's investment in the technology was about more than just short-term financial wins. He said the adoption of new technology like AI needs to deliver better living standards for Australians. In a speech earlier this year in Sydney, he said that while businesses including CBA were racing to find ways to incorporate AI and improve efficiency, there were also bigger questions that needed to be addressed. "Ultimately, this technology needs to lead to productivity and improvements in living standards, not [corporate] valuations," he said. More important than the next quarter or next year's financial results was the question of "how do we maximise benefits for Australia?", he said. Mr Comyn said the introduction of any new technology was usually accompanied by predictions about problems it could cause. "All technology shifts, early on, look like they could be a real risk, with lots of problems," he said. These concerns have always faded over time as technology was more widely adopted, but the pace and scale of change created by AI was different, and could potentially create volatility in the economy. "It's quite a different period to what we have seen in the past decade or more," Mr Comyn said. He acknowledged not everyone was on board with the AI transition, and that it was causing anxiety about employment and jobs. He warned that AI would trigger job losses, arguing that big companies such as CBA, which employs 55,000 staff, had a responsibility to face up to workforce disruption and allow employees to prepare for a difficult period of retraining and adjustment ahead. "I think a lot of leadership has to be about making sure that we are adapting, or empowering and building capability within our people and our organisations and trying to get that balance right - which will not be easy," he said. With the current oil shock only increasing global volatility and uncertainty, we also need to consider how the economic benefits of AI were shared, "both at a global and national level, but also across different groups within society", Mr Comyn said. SpaceX record set to be broken If Anthropic's IPO goes to plan and the company hits a value of $2 trillion, it would more than double the five-year-old company's previous valuation at $965 billion, reached in its last funding round in June. Only a handful of companies including Apple, Microsoft and chip maker Nvidia have surpassed the $2 trillion mark. After filing to go public in June, the company could reveal its public offering prospectus in the coming weeks, the Times reported, with shares possibly listed before the end of the year. Anthropic could then beat OpenAI, the maker of ChatGPT, to market. That company is hoping to list its shares in 2027. Founded in 2021 by siblings Dario and Daniela Amodei and other former executives at OpenAI, Anthropic has positioned itself as a safety-focused alternative in the AI race. Claude Code, its coding assistant for developers, has become one of its most popular products, helping push its projected annual revenue to $47 billion. Anthropic's commercial success has been accompanied by difficulties in meeting demand for computing power, amid a shortage of chips and servers. Potential investors could be dissuaded by the company's difficult relationship with US President Donald Trump's administration. In March, the government broke off its contracts with Anthropic and designated the company a supply chain risk after it refused to grant the military unfettered access to its AI models. Anthropic called the Defence Department's move unconstitutional retaliation.
Researchers: 152 Polymarket "Orca" Traders Likely Bet on Inside Military Information - NaturalNews.com
According to the group's analysis, first reported by Reuters, the wallets earned about $8 million combined and posted an average win rate of 97.2% across their wagers. The report by ACDC comes as policymakers scrutinize the prediction-market industry. It also followed Army soldier Gannon Ken Van Dyke being charged with using classified information to place bets on a prediction market. The U.S. Department of State has issued a memorandum reminding employees worldwide that using undisclosed official information for financial gain is a "very serious offense" that will not be tolerated, according to a Wall Street Journal report covered by Russia Today . Research Methodology and "Orca" Identification ACDC said it analyzed all settled markets through May 5. It defined a long-shot bet as at least $2,500 placed cumulatively within an hour on an outcome with odds of 35% or less. Under that definition, the group identified 556 "Orca" wallets. The name comes from the killer whale's precise hunting behavior, ACDC said. Those traders often opened accounts, placed successful long-shot bets in niche markets, cashed out and disappeared, according to the group. The group's method mirrors patterns seen in traditional markets. Nearly 10,000 crude oil short contracts, valued at approximately $920 million, were placed at 3:40 a.m. on May 6, and Axios reported that Washington and Tehran were nearing an agreement at 4:50 a.m., according to market commentary platform the Kobeissi Letter . Analysts have also documented approximately $7 billion in suspiciously timed oil futures trades across four separate days in March and April, executed before major U.S.-Iran announcements, according to a separate review . Limitations and Alternative Explanations ACDC said Orca traits could be explained by pure luck, and not all potential insiders fit the pattern. Van Dyke, who was charged with using classified information to bet on the removal of ousted Venezuelan President Nicolas Maduro, built his position slowly and is not among the 152 wallets identified, the group said. Some military Orca wallets had been flagged before, but ACDC said it found dozens more previously unreported wallets. A Department of War spokesperson said the department does not comment on intelligence-related matters or third-party research findings. Copycat Bets and Security Risks The report said military Orca trades appeared to attract copycat bets from deep-pocketed "Whales" and automated bots. This pattern may amplify and broadcast insider signals to foreign adversaries, according to the research. An Orca bet on U.S. military action in Iran hours before June 2025 strikes was followed by copycat wagers of $200,000 and $100,000, the research found. U.S. strikes on Iranian nuclear sites that month were followed by Iranian threats to close the Strait of Hormuz, a critical maritime chokepoint . According to the research, similar Orca bets before the Feb. 28 U.S.-Israeli airstrikes on Tehran prompted a flurry of first-time long-shot bets. The report said the rapid succession of wagers showed that public order books can reveal sensitive trading patterns in real time. Polymarket and Regulatory Response Polymarket did not respond to requests for comment. The company has said it monitors suspicious activity and has referred dozens of trader wallets to authorities, including in the Maduro case. Polymarket has said its public ledger allows for greater scrutiny of trading behavior. The Commodity Futures Trading Commission declined to comment on the findings. The agency has said it will strictly police misconduct and has brought charges in at least three cases. Polymarket has drawn attention for its high-profile political markets; in July 2024, the platform reported that odds of then-Ohio Sen. J.D. Vance being picked as Donald Trump's running mate had risen by 287% . Recommendations and Conclusions ACDC recommends requiring all traders to prove identity, withholding payouts on suspicious trades pending investigation, and banning markets where non-public information may be most actionable and profitable, the group said. ACDC co-founder David Szakonyi said "it would be naive to think foreign-intelligence agencies aren't monitoring these markets." The group said limiting who can bet or relying on law enforcement "will not be enough." The findings also raise broader questions about data collection and privacy. One book describes a future in which artificial intelligence replaces individual choice . Another notes that cybersecurity efforts using large-scale data systems have not yet taken hold, citing breaches at Equifax, Yahoo and Under Armour .
Inherent Says 27 Billion-Parameter AI Agent Beats Larger OpenAI, Anthropic Models In Scientific Research Test
Inherent, a London-based artificial intelligence startup founded by former Google DeepMind researchers, says its new AI agent has outperformed much larger systems from OpenAI and Anthropic in a test designed to measure whether AI can independently reproduce scientific research. The startup, which emerged from stealth just weeks ago with a $50 million seed funding round, said its agent Faraday surpassed Anthropic's Claude Opus 4.8 and OpenAI's GPT-5.5 in a benchmark focused on reproducing the findings of published scientific papers without being given the expected results in advance. The result is notable not simply because Faraday outperformed two larger frontier models, but because Inherent said the agent runs on Qwen 3.6, a comparatively small model with 27 billion parameters. Parameters are a broad measure of the number of learned values in an AI model and are often associated with model size, although parameter count alone does not determine a system's capabilities, training cost, or efficiency. For Inherent, the more important achievement is how Faraday reaches its conclusions. The company is pursuing a much broader objective than simply reproducing existing scientific findings. Its long-term ambition is to develop AI agents capable of discovering new scientific knowledge and contributing to research across multiple disciplines. Edward Hughes, Inherent's cofounder and chief scientist, said reproducing published research is an important starting point because it is also a common exercise for human researchers. "Many PhD students actually start by doing this," Hughes said. The company therefore views paper replication as a test of whether an AI system can independently formulate experiments, execute them and interpret the results rather than simply answer questions based on information already contained in its training data. "What was most interesting to us about this was not so much the result of beating those frontier agents -- which of course we liked -- but was actually the way we went about building this," Hughes told TechCrunch. Inherent said it also set a higher bar than simply measuring whether Faraday could reproduce published results. The company wanted the agent to demonstrate what it calls "research taste," meaning an ability to identify worthwhile questions, determine which experiments are useful, and design those experiments effectively. That capability is difficult to encode through conventional instructions because it involves judgment about which research directions are likely to produce useful information. Inherent uses reinforcement learning to address that problem. Instead of attempting to explicitly teach the agent every step involved in scientific research, the company rewards the system for producing desirable outcomes and allows it to learn strategies that lead to those outcomes. The approach is central to Inherent's broader thesis that an AI scientist should develop transferable research capabilities rather than simply memorize procedures for particular scientific fields. "We're always guided by that north star of building an AI scientist agent and imbuing our agents with taste," Hughes said. That philosophy has also influenced what Inherent has chosen not to build. Rather than developing its own coding system, Faraday uses OpenAI's GPT-5.5 Codex for software development tasks. The company compares that approach with how human scientists work, relying on existing tools rather than attempting to build every piece of software needed for an experiment. The strategy could make a huge difference as AI research systems become more specialized. Instead of competing with every major AI developer on the underlying model, Inherent is attempting to build an agentic layer capable of combining models and tools to perform complex scientific work. Hughes said the company also wants Faraday to behave more like a research collaborator than an AI assistant designed primarily to satisfy its user. The goal, he said, is an agent that can independently investigate a question and return with unexpected findings rather than simply confirming what the user already believes. That is expected to become more useful as AI systems move from generating answers to carrying out autonomous research. A useful scientific agent needs to be capable of challenging assumptions, pursuing alternative hypotheses, and reporting results that may contradict the user's expectations. Inherent's operating model is similarly focused on maintaining a small, concentrated research team. Its roughly dozen employees currently work in person from an office in London's King's Cross, an area that has developed into a major AI research and startup hub partly through the presence of Google DeepMind. "We believe that London is the place to be," Hughes said. The company is nevertheless critical of one aspect of Britain's employment system that can make it harder for startups to recruit experienced AI researchers. Hughes has called for an end to "garden leave," a practice under which employees can be prevented from joining a competitor or starting a competing company for a period after leaving their previous employer. He said that the practice can put British AI startups at a disadvantage compared with companies in the United States, where researchers generally face fewer restrictions when moving between employers. "This is a personal view rather than a company view, but I was affected by the garden leave problem," Hughes said. Hughes eventually overcame the restriction and founded Inherent with two other former DeepMind employees and a fourth cofounder. The startup now plans to increase its workforce to between 20 and 25 employees by the end of the year. Its ambitions extend beyond scientific agents into world models, potentially putting it in competition for talent with much larger AI laboratories. That hiring push could become a major boost as researchers reassess their positions at established AI labs. Demis Hassabis, DeepMind's cofounder and CEO, has taken on a new role, while changes across the broader AI industry are creating opportunities for researchers to move into startups. Inherent's early benchmark results do not establish that a 27 billion-parameter model is generally more capable than much larger frontier systems. The test covers a specific scientific-research task, and performance on paper replication does not necessarily translate into broader reasoning, coding, or general-purpose capabilities. But the result underpins that in AI development, raw model size may not be the only route to stronger performance on complex tasks. Inherent is betting that reinforcement learning, tool use, autonomous experimentation, and specialized agent architecture can allow relatively small underlying models to perform sophisticated research tasks. If that approach generalizes beyond reproducing existing scientific work, the implications could be significant. Instead of simply making AI models larger, developers may focus more on teaching smaller systems how to choose problems, conduct experiments, use external tools, and learn from the results.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 7:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 7:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 7:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 6:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 6:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 7:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 6:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 4:33 PM.