News & Updates
The latest news and updates from companies in the WLTH portfolio.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 7:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 7:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 6:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 6:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 7:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 6:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 4:33 PM.
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 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 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.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 6:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 7:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 6:33 PM.
Anthropic makes quiet move Nvidia investors must consider
Amir Salek spent four years doing something that looked a lot like walking away from the chip business. After founding and running Google's Tensor Processing Unit program from 2013 to 2022 and shipping seven generations of the custom silicon that now powers much of Google's AI infrastructure, he left to invest in deep-tech startups at Cerberus Capital Management, a press release announced at the time. That detour is why his next move matters more than a routine hire. Anthropic has brought Salek onto its compute team, where he will report to compute lead James Bradbury, according to Bloomberg. He is not being poached out of a rival's office. He is being pulled back into chip design after four years on the sidelines by a company that did not have a hardware team a year ago. Salek is not Anthropic's first hardware hire this year Two months earlier, Anthropic landed Clive Chan, the second engineer ever hired to OpenAI's custom chip program, who had spent more than two years building the Broadcom-designed inference accelerator OpenAI markets as Jalapeno. Chan announced the move himself in June, framing it as a step up rather than a rescue. The pattern is what makes the Salek hire read as strategy instead of opportunism. Anthropic publicly confirmed on Aug. 5 that it is standing up an in-house silicon team, with the explicit goal of co-designing chips and Claude models together to cut inference costs by roughly half, according to TechCrunch. TechCrunch also reported that Anthropic has held early manufacturing talks with Samsung. Two hires in three months, both pulled from the two companies furthest along in custom AI silicon, is not a coincidence. It is a shopping list. Javier Zayas Photography / Getty Images Raiding Google's bench Here is the part most coverage of the Salek hire has skipped past. Google is not a bystander in Anthropic's chip ambitions. It is the supplier. Anthropic agreed in October to buy up to a million of Google's Tensor Processing Units in a deal worth tens of billions of dollars, then expanded that arrangement in April to cover multiple additional gigawatts of TPU capacity through 2027, according to the company's announcement. Google is, in other words, simultaneously arming Anthropic with chips after losing the person most responsible for the chip program that those chips came from. That is an unusual position for a supplier to hold with a customer that competes directly against its own Gemini AI models. It complicates the idea that the relationship is simply commercial. Anthropic still says AWS Trainium, Google TPUs and Nvidia GPUs will remain central to how it scales Claude, and nothing about Salek's hire changes that in the short run. For investors in Nvidia, Alphabet and Broadcom, the practical impact today is limited, since custom silicon takes years to design and manufacture at volume. But each AI lab that builds its own silicon program shrinks the list of frontier customers still fully dependent on Nvidia. Broadcom, which already designs custom chips for OpenAI and Google, is the most likely beneficiary if Anthropic's effort advances that far. The real contest has moved from GPUs to headcount Bidding wars over AI researchers are old news by now. What's newer is the fight over hardware architects, the engineers who can take a chip from blueprint to production line. There are far fewer of them than machine learning researchers, and that scarcity is starting to show. That scarcity has already produced legal fights in other industries. Warner Bros. Discovery sued Amazon in July over an executive who left a fixed-term contract 16 months early, arguing Amazon ran what its complaint called a lawless hiring spree. Salek's move to anthropic carries none of that risk. He had already left Google's payroll years before Anthropic called, which means there is no contract to breach and no lawsuit to file. That is the quieter lesson here. The clean way to build a chip team is not to raid a competitor mid-contract. It is to identify who already built one of these programs once, wait until they are between roles, and make the offer before anyone else does. The custom silicon race Meta's in-house Iris chip is due in production by September. OpenAi's Jalapeno targets the back half of this year. Microsoft has run Maia chips for two years, and Amazon has done the same with Trainium. Anthropic is the last major lab into custom silicon, not the first. Owning hardware talent is not the same as owning working silicon. Anthropic's chip, whatever it becomes, is not expected before 2028 at the earliest. The next test is not who Anthropic hires next. It is whether a lab built on renting other companies' chips can actually ship one of its own. As frontier AI labs and hyperscalers double down on in-house silicon, a critical question emerges for Wall Street: Does this mark the beginning of structural market share erosion for Nvidia? While Nvidia's total addressable market continues to expand rapidly, every successful custom ASIC deployed for inference or specialized training shifts workloads away from general purpose GPUs, slowly chipping away at the revenue concentration of the market's leading chipmaker. The Arena Media Brands, LLC THESTREET is a registered trademark of TheStreet, Inc. This story was originally published August 23, 2026 at 4:33 PM.
Anthropic's Fable 5 accounts for just 6% of purchased tokens as cheaper Opus 5 steals the show
Anthropic's most expensive AI model is struggling to find an audience as users flock to its half-price sibling that performs nearly as well Anthropic built its most powerful AI model ever, slapped a premium price tag on it, and watched customers shrug. Claude Fable 5, the company's flagship "Mythos-class" model launched on June 9, 2026, has captured just 6% of total tokens purchased in its first two months on the market. For a model positioned as the pinnacle of Anthropic's AI capabilities, that's a remarkably thin slice of the pie. Even measured by revenue, where Fable 5's higher prices should inflate its share, the model accounts for only 11.4% of earnings. The price tag problem Fable 5 costs $10 per million input tokens and $50 per million output tokens. Anthropic released Claude Opus 5 on July 24, barely six weeks after Fable 5's debut, priced at exactly half: $5 per million input tokens and $25 per million output tokens. Opus 5 matches or exceeds Fable 5's performance across many benchmarks. When a model that costs 50% less delivers comparable results, the math isn't complicated. Developers and enterprises ran the numbers and made the obvious call. Anthropic frames this as intentional segmentation rather than cannibalization. Fable 5 is designed for "long-horizon projects," the kind of complex, multi-step reasoning tasks where marginal improvements in capability justify the premium. Opus 5, meanwhile, handles "everyday high-value work" for broader enterprise needs. What this means for Anthropic's strategy The company has already started adjusting how users access Fable 5, including temporary subscription inclusions and shifts to usage-based credits. These aren't the moves of a company watching its premium product fly off the shelves. They're the moves of a company trying to get more people to actually try the thing. Anthropic appears to be settling into a dual-market approach. The strategy banks on a small cohort of power users paying the Fable 5 premium. Meanwhile, Opus 5 and other lower-tier models handle the volume. If Fable 5's share stays in the single digits, it raises questions about whether Anthropic can sustain the economics of developing ultra-premium models. A model that generates 11.4% of revenue while presumably consuming a disproportionate share of compute resources to develop is a tough business case to defend indefinitely.
