News & Updates
The latest news and updates from companies in the WLTH portfolio.
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.
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.
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 5:33 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.
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.
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.
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 4:33 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, OpenAI IPOs May Absorb Liquidity, Intensify AI Capital Competition
Hyperscaler bond surge and U.S. AI listings could divert funds from stocks, contrasting with Samsung, SK Hynix's shareholder returns U.S. artificial intelligence (AI) companies Anthropic and OpenAI are approaching large-scale initial public offerings (IPOs), with forecasts suggesting they could absorb market liquidity. Notably, as bond issuances by hyperscalers surge, this IPO is analyzed to potentially compete not only with existing stocks but also with AI bonds. Choi Bo-young, a researcher at Kyobo Securities, stated, "The moment large unlisted companies enter the public market, they create new supply that directly competes with existing listed stocks for the same investment funds." She added, "Just as SpaceX absorbed approximately 75 billion dollars through its June IPO, if Anthropic and OpenAI proceed with their listings, funds in the stock market could become dispersed." Given the surge in corporate bond issuances by hyperscalers, there is a possibility that higher expected returns on stocks will be demanded. According to Kyobo Securities, the bond issuance scale of major hyperscalers is expected to expand from approximately 250 billion dollars in 2026 to 400 billion dollars in 2027. Choi explained, "Recently, some AI data center bonds and infrastructure loans have been offering annual returns of 7-9%." She added, "Since they can secure contractual cash flows and priority repayment rights over stocks while being exposed to AI growth, AI stocks must provide sufficiently higher expected returns than these." In contrast, Korean semiconductor companies like Samsung Electronics and SK Hynix are focusing on shareholder returns based on their strong cash-generating capabilities. He explained, "While U.S. AI companies supply new stocks and debt to the market to expand investments, Samsung Electronics and SK Hynix are reducing the number of shares circulating in the market through share buybacks and dividends." He added, "This is a capital policy that is the opposite of global AI companies." He further added, "Under the premise that the fundamentals of the AI industry are maintained, the relative supply-demand appeal of companies that generate cash and return it to shareholders may increase compared to those that absorb funds." Earlier, SK Hynix announced that it would repurchase and cancel shares worth approximately 40 trillion Korean won last week and return over 50% of its cumulative free cash flow (FCF) from 2025-2027 to shareholders. Samsung Electronics also stated that it has allocated 90-100 trillion Korean won for shareholder returns in 2026 and will implement a cash dividend of approximately 30 trillion Korean won in the third quarter, including regular dividends.
