Miles Wang, an OpenAI researcher whose work includes using AI to accelerate scientific and biological discovery, is leaving the ChatGPT maker to launch a new startup focused on developing AI models for drug discovery, according to four people with knowledge of his plans. Several other OpenAI researchers are expected to join the new company.
Wang is in talks to raise about $200 million at a $2 billion valuation, two of the people said. Lightspeed is in discussions to lead the funding round, according to sources. Talks are ongoing, the deal may not be final and details could change.
Wang disputed the story’s funding figures and description of the company but did not specify the correct numbers or details. Lightspeed didn’t respond to a request for comment.
The funding discussions point to investor interest in applying AI to make breakthroughs in life sciences. Chai Discovery, a two-year-old startup developing AI models that can predict molecular interactions to identify new drugs, announced on Tuesday that it raised $400 million at a $3.8 billion valuation. (Co-founder Josh Meier also passed through OpenAI as a researcher.) Meanwhile, Google DeepMind spinout Isomorphic Labs, which also develops AI models for drug discovery, raised a $2.1 billion Series B in May.
Wang’s new startup may be working on AI models that will help find new uses for existing drugs and possibly those that previously failed in trials, a couple of sources told TechCrunch. Finding new uses for FDA-approved drugs can result in significantly faster time to revenue than developing new drugs from scratch, as these medicines have already been tested for safety.
Wang joined OpenAI in 2024 after dropping out from Harvard, where he was working on a bachelor’s degree in computer science. (In recent years, investors are once again comfortable betting on young founders who haven’t completed college.)
At OpenAI, he co-authored research papers, including evaluating how AI models can automate and accelerate scientific discovery.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
Miles Wang, an OpenAI researcher whose work includes using AI to accelerate scientific and biological discovery, is leaving the ChatGPT maker to launch a new startup focused on developing AI models for drug discovery, according to four people with knowledge of his plans. Several other OpenAI researchers are expected to join the new company.
Wang is in talks to raise about $200 million at a $2 billion valuation, two of the people said. Lightspeed is in discussions to lead the funding round, according to sources. Talks are ongoing, the deal may not be final and details could change.
Wang disputed the story’s funding figures and description of the company but did not specify the correct numbers or details. Lightspeed didn’t respond to a request for comment.
The funding discussions point to investor interest in applying AI to make breakthroughs in life sciences. Chai Discovery, a two-year-old startup developing AI models that can predict molecular interactions to identify new drugs, announced on Tuesday that it raised $400 million at a $3.8 billion valuation. (Co-founder Josh Meier also passed through OpenAI as a researcher.) Meanwhile, Google DeepMind spinout Isomorphic Labs, which also develops AI models for drug discovery, raised a $2.1 billion Series B in May.
Wang’s new startup may be working on AI models that will help find new uses for existing drugs and possibly those that previously failed in trials, a couple of sources told TechCrunch. Finding new uses for FDA-approved drugs can result in significantly faster time to revenue than developing new drugs from scratch, as these medicines have already been tested for safety.
Wang joined OpenAI in 2024 after dropping out from Harvard, where he was working on a bachelor’s degree in computer science. (In recent years, investors are once again comfortable betting on young founders who haven’t completed college.)
At OpenAI, he co-authored research papers, including evaluating how AI models can automate and accelerate scientific discovery.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
#OpenAI #researcher #Miles #Wang #talks #launch #drug #discovery #startup #valued #TechCrunchdrug discovery,lightspeed,OpenAI">OpenAI researcher Miles Wang in talks to launch AI drug discovery startup valued at $2B | TechCrunch
Miles Wang, an OpenAI researcher whose work includes using AI to accelerate scientific and biological discovery, is leaving the ChatGPT maker to launch a new startup focused on developing AI models for drug discovery, according to four people with knowledge of his plans. Several other OpenAI researchers are expected to join the new company.
Wang is in talks to raise about $200 million at a $2 billion valuation, two of the people said. Lightspeed is in discussions to lead the funding round, according to sources. Talks are ongoing, the deal may not be final and details could change.
Wang disputed the story’s funding figures and description of the company but did not specify the correct numbers or details. Lightspeed didn’t respond to a request for comment.
The funding discussions point to investor interest in applying AI to make breakthroughs in life sciences. Chai Discovery, a two-year-old startup developing AI models that can predict molecular interactions to identify new drugs, announced on Tuesday that it raised $400 million at a $3.8 billion valuation. (Co-founder Josh Meier also passed through OpenAI as a researcher.) Meanwhile, Google DeepMind spinout Isomorphic Labs, which also develops AI models for drug discovery, raised a $2.1 billion Series B in May.
Wang’s new startup may be working on AI models that will help find new uses for existing drugs and possibly those that previously failed in trials, a couple of sources told TechCrunch. Finding new uses for FDA-approved drugs can result in significantly faster time to revenue than developing new drugs from scratch, as these medicines have already been tested for safety.
Wang joined OpenAI in 2024 after dropping out from Harvard, where he was working on a bachelor’s degree in computer science. (In recent years, investors are once again comfortable betting on young founders who haven’t completed college.)
At OpenAI, he co-authored research papers, including evaluating how AI models can automate and accelerate scientific discovery.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
Miles Wang, an OpenAI researcher whose work includes using AI to accelerate scientific and biological…
Johannes Heidecke, the Head of Safety Systems at OpenAI, is leaving. I know what you’re thinking: Hey, didn’t the head of safety at OpenAI just leave?
In fact, it feels like a head of safety at OpenAI is pretty much always leaving. Working in safety leadership—loosely defined—at OpenAI is a little like working as a drummer in the band Spinal Tap; lots of turnover. I’m not the world’s premier OpenAI Kremlinologist, so I might be missing some details and nuance, but here’s my basic timeline:
According to Wired, those previously reporting to Heidecke’s safety teams will be led by Mia Glaese, who is a VP, and also the head of alignment. However, there does seem to be an other replacement for Heidecke, according to Wired. Saachi Jain, former leader of safety teams, will now be an “interim head of safety systems” under Glaese.
What exactly keeps happening inside OpenAI’s offices is anyone’s guess, but OpenAI research chief Mark Chen did at least give Wired a hint, saying, “The demands on safety continue to increase—we are training models at a much faster cadence, and release cycles have come down greatly in turn,” and added, “As a result, we have bigger coordination challenges around safety today than ever before.”
The generous reading is that this is still an immature industry. The points along the chain where safety considerations are needed genuinely may keep jumping around as OpenAI figures out how best to build its products. Perhaps today’s sensible safety test procedure is tomorrow’s unnecessary bottleneck.
And there’s no actual direct evidence for a less generous reading of Heidecke’s departure—for instance, one in which any such consideration is a post-hoc rationalization for a pruning of safety procedures in service of faster product rollouts.
Johannes Heidecke, the Head of Safety Systems at OpenAI, is leaving. I know what you’re thinking: Hey, didn’t the head of safety at OpenAI just leave?
In fact, it feels like a head of safety at OpenAI is pretty much always leaving. Working in safety leadership—loosely defined—at OpenAI is a little like working as a drummer in the band Spinal Tap; lots of turnover. I’m not the world’s premier OpenAI Kremlinologist, so I might be missing some details and nuance, but here’s my basic timeline:
According to Wired, those previously reporting to Heidecke’s safety teams will be led by Mia Glaese, who is a VP, and also the head of alignment. However, there does seem to be an other replacement for Heidecke, according to Wired. Saachi Jain, former leader of safety teams, will now be an “interim head of safety systems” under Glaese.
What exactly keeps happening inside OpenAI’s offices is anyone’s guess, but OpenAI research chief Mark Chen did at least give Wired a hint, saying, “The demands on safety continue to increase—we are training models at a much faster cadence, and release cycles have come down greatly in turn,” and added, “As a result, we have bigger coordination challenges around safety today than ever before.”
The generous reading is that this is still an immature industry. The points along the chain where safety considerations are needed genuinely may keep jumping around as OpenAI figures out how best to build its products. Perhaps today’s sensible safety test procedure is tomorrow’s unnecessary bottleneck.
And there’s no actual direct evidence for a less generous reading of Heidecke’s departure—for instance, one in which any such consideration is a post-hoc rationalization for a pruning of safety procedures in service of faster product rollouts.
#Safety #Leader #OpenAI #Leftai alignment,AI safety,OpenAI">Yet Another Safety Leader at OpenAI Has Left
Johannes Heidecke, the Head of Safety Systems at OpenAI, is leaving. I know what you’re thinking: Hey, didn’t the head of safety at OpenAI just leave?
In fact, it feels like a head of safety at OpenAI is pretty much always leaving. Working in safety leadership—loosely defined—at OpenAI is a little like working as a drummer in the band Spinal Tap; lots of turnover. I’m not the world’s premier OpenAI Kremlinologist, so I might be missing some details and nuance, but here’s my basic timeline:
According to Wired, those previously reporting to Heidecke’s safety teams will be led by Mia Glaese, who is a VP, and also the head of alignment. However, there does seem to be an other replacement for Heidecke, according to Wired. Saachi Jain, former leader of safety teams, will now be an “interim head of safety systems” under Glaese.
What exactly keeps happening inside OpenAI’s offices is anyone’s guess, but OpenAI research chief Mark Chen did at least give Wired a hint, saying, “The demands on safety continue to increase—we are training models at a much faster cadence, and release cycles have come down greatly in turn,” and added, “As a result, we have bigger coordination challenges around safety today than ever before.”
The generous reading is that this is still an immature industry. The points along the chain where safety considerations are needed genuinely may keep jumping around as OpenAI figures out how best to build its products. Perhaps today’s sensible safety test procedure is tomorrow’s unnecessary bottleneck.
And there’s no actual direct evidence for a less generous reading of Heidecke’s departure—for instance, one in which any such consideration is a post-hoc rationalization for a pruning of safety procedures in service of faster product rollouts.
Johannes Heidecke, the Head of Safety Systems at OpenAI, is leaving. I know what you’re…
Yesterday, OpenAI released its latest voice model, GPT-Live-1. The company called it “a new generation of voice models for natural human-AI interaction.” The full-duplex model allows ChatGPT to talk and listen at the same time, giving the back-and-forth a more conversational flow. It’s designed to be smarter, faster, and more natural.
Ooh, so close. Husk gave ChatGPT the straightforward request to tell him how many times the letter E appears in the number “seventeen,” and the voice model managed to get halfway there by answering “two.” It then offered a very awkward sign-off when Husk ended the conversation. Maybe that’s a query that GPT-Live-2 will be able to handle.
To be fair, Husk isn’t really testing any of the new features that OpenAI highlighted with the release of its new model, which, by most accounts, seems like it’s more capable when it comes to things like live translation than previous iterations. But he is giving the model a very simple benchmarking test that, despite being OpenAI’s flagship voice model, it still failed spectacularly.
It seems OpenAI knows just how bad this looks, too. Jason Liu, a Developer Experience Engineer on OpenAI Codex, reposted the video with a very succinct, “FUCK.”
Husk’s made a habit of terrorizing OpenAI over its voice model for some time now, making viral videos out of how poorly it handles certain prompts. One of his videos—in which he tasks ChatGPT with setting a timer and watching it fail—made it all the way to CEO Sam Altman, who tried to laugh it off in a very “I’m not mad, please don’t put in the newspaper that I got mad” kinda way.
Husk is not alone in giving GPT-Live-1 the old stress test. Another user on X gave the model the “Strawberry” test, asking it to count the number of times the letter R appears in the word “strawberry.” It’s a classic, and one that most AI models can answer correctly by now (whether that’s because they really know there are 3 Rs or because they’ve been trained on how to respond to prevent embarrassment is another question), but GPT-Live-1 gets tripped up by it.
OpenAI’s brand new voice model vs counting the r’s in strawberry. I really tried to help it along. pic.twitter.com/Pm0RfLyxIA
Another user noted a new annoyance that has arisen from the model’s full-duplex functionality: While the model now allows ChatGPT to say things like “mhm” and “yeah” while you talk to confirm it is listening, it apparently is incapable of simply shutting up and not doing that. It seems ChatGPT has built an interrupting machine. Just what we’ve all been waiting for.
Yesterday, OpenAI released its latest voice model, GPT-Live-1. The company called it “a new generation of voice models for natural human-AI interaction.” The full-duplex model allows ChatGPT to talk and listen at the same time, giving the back-and-forth a more conversational flow. It’s designed to be smarter, faster, and more natural.
Ooh, so close. Husk gave ChatGPT the straightforward request to tell him how many times the letter E appears in the number “seventeen,” and the voice model managed to get halfway there by answering “two.” It then offered a very awkward sign-off when Husk ended the conversation. Maybe that’s a query that GPT-Live-2 will be able to handle.
To be fair, Husk isn’t really testing any of the new features that OpenAI highlighted with the release of its new model, which, by most accounts, seems like it’s more capable when it comes to things like live translation than previous iterations. But he is giving the model a very simple benchmarking test that, despite being OpenAI’s flagship voice model, it still failed spectacularly.
It seems OpenAI knows just how bad this looks, too. Jason Liu, a Developer Experience Engineer on OpenAI Codex, reposted the video with a very succinct, “FUCK.”
Husk’s made a habit of terrorizing OpenAI over its voice model for some time now, making viral videos out of how poorly it handles certain prompts. One of his videos—in which he tasks ChatGPT with setting a timer and watching it fail—made it all the way to CEO Sam Altman, who tried to laugh it off in a very “I’m not mad, please don’t put in the newspaper that I got mad” kinda way.
Husk is not alone in giving GPT-Live-1 the old stress test. Another user on X gave the model the “Strawberry” test, asking it to count the number of times the letter R appears in the word “strawberry.” It’s a classic, and one that most AI models can answer correctly by now (whether that’s because they really know there are 3 Rs or because they’ve been trained on how to respond to prevent embarrassment is another question), but GPT-Live-1 gets tripped up by it.
OpenAI’s brand new voice model vs counting the r’s in strawberry. I really tried to help it along. pic.twitter.com/Pm0RfLyxIA
Another user noted a new annoyance that has arisen from the model’s full-duplex functionality: While the model now allows ChatGPT to say things like “mhm” and “yeah” while you talk to confirm it is listening, it apparently is incapable of simply shutting up and not doing that. It seems ChatGPT has built an interrupting machine. Just what we’ve all been waiting for.
#OpenAI #Beat #TikTokerartifical intelligence,ChatGPT,OpenAI,voice model">OpenAI Just Can’t Beat This TikToker
Yesterday, OpenAI released its latest voice model, GPT-Live-1. The company called it “a new generation of voice models for natural human-AI interaction.” The full-duplex model allows ChatGPT to talk and listen at the same time, giving the back-and-forth a more conversational flow. It’s designed to be smarter, faster, and more natural.
Ooh, so close. Husk gave ChatGPT the straightforward request to tell him how many times the letter E appears in the number “seventeen,” and the voice model managed to get halfway there by answering “two.” It then offered a very awkward sign-off when Husk ended the conversation. Maybe that’s a query that GPT-Live-2 will be able to handle.
To be fair, Husk isn’t really testing any of the new features that OpenAI highlighted with the release of its new model, which, by most accounts, seems like it’s more capable when it comes to things like live translation than previous iterations. But he is giving the model a very simple benchmarking test that, despite being OpenAI’s flagship voice model, it still failed spectacularly.
It seems OpenAI knows just how bad this looks, too. Jason Liu, a Developer Experience Engineer on OpenAI Codex, reposted the video with a very succinct, “FUCK.”
Husk’s made a habit of terrorizing OpenAI over its voice model for some time now, making viral videos out of how poorly it handles certain prompts. One of his videos—in which he tasks ChatGPT with setting a timer and watching it fail—made it all the way to CEO Sam Altman, who tried to laugh it off in a very “I’m not mad, please don’t put in the newspaper that I got mad” kinda way.
Husk is not alone in giving GPT-Live-1 the old stress test. Another user on X gave the model the “Strawberry” test, asking it to count the number of times the letter R appears in the word “strawberry.” It’s a classic, and one that most AI models can answer correctly by now (whether that’s because they really know there are 3 Rs or because they’ve been trained on how to respond to prevent embarrassment is another question), but GPT-Live-1 gets tripped up by it.
OpenAI’s brand new voice model vs counting the r’s in strawberry. I really tried to help it along. pic.twitter.com/Pm0RfLyxIA
Another user noted a new annoyance that has arisen from the model’s full-duplex functionality: While the model now allows ChatGPT to say things like “mhm” and “yeah” while you talk to confirm it is listening, it apparently is incapable of simply shutting up and not doing that. It seems ChatGPT has built an interrupting machine. Just what we’ve all been waiting for.
At a meeting this week, CEO Sam Altman reportedly told staff that the government would be “approving access customer by customer” during a preview period. Altman reportedly added that if the limited release goes well, OpenAI hopes to follow with a general, broader release a “couple of weeks later.”
In other words, the Trump administration appears to be pressuring OpenAI to do what Anthropic is already voluntarily doing: keeping its most powerful AI models under wraps.
According to The Information, OpenAI’s new model is not only being reviewed by the administration, but its staffers also “worked closely” with the government on the upcoming release. The agencies that reportedly asked for a limited release were the Office of the National Cyber Director and the Office of Science and Technology Policy.
The Trump administration — which originally positioned itself as taking a “hands off” approach to AI — has in recent months pushed for federal oversight of new models. Earlier this month, Trump signed an executive order directing certain AI companies to voluntarily submit new models to the government for testing and evaluation before releasing them publicly.
Earlier this year, Anthropic sparked no small amount of controversy when it announced that its new frontier cyber model, Claude Mythos, would only be released to a small coterie of partners through a program called Project Glasswing. Anthropic argued that its model was simply too powerful and could, in the wrong hands, cause more harm than good. Observers have since debated whether Anthropic’s rhetoric is a mere marketing gimmick or a legitimate attempt to keep a powerful model from being misused. The answer may be somewhere in between.
Cybercriminals have used automated tools for a very long time, but in the age of generative AI, they now have more digital ammunition than ever before. LLMs have proven adept at writing malware, and some can even execute entire ransomware attacks autonomously.
The specific concern with frontier cyber tools like Mythos is that they are ostensibly capable of both identifying and exploiting software vulnerabilities at speeds that no human analyst could match. Since many software systems contain hidden bugs that act as entry points into enterprise networks, this obviously poses an obvious and significant problem for any organization running complex software infrastructure. That said, since these models remain closed to the public, it’s difficult to tell just how much of a threat they really are.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
At a meeting this week, CEO Sam Altman reportedly told staff that the government would be “approving access customer by customer” during a preview period. Altman reportedly added that if the limited release goes well, OpenAI hopes to follow with a general, broader release a “couple of weeks later.”
In other words, the Trump administration appears to be pressuring OpenAI to do what Anthropic is already voluntarily doing: keeping its most powerful AI models under wraps.
According to The Information, OpenAI’s new model is not only being reviewed by the administration, but its staffers also “worked closely” with the government on the upcoming release. The agencies that reportedly asked for a limited release were the Office of the National Cyber Director and the Office of Science and Technology Policy.
The Trump administration — which originally positioned itself as taking a “hands off” approach to AI — has in recent months pushed for federal oversight of new models. Earlier this month, Trump signed an executive order directing certain AI companies to voluntarily submit new models to the government for testing and evaluation before releasing them publicly.
Earlier this year, Anthropic sparked no small amount of controversy when it announced that its new frontier cyber model, Claude Mythos, would only be released to a small coterie of partners through a program called Project Glasswing. Anthropic argued that its model was simply too powerful and could, in the wrong hands, cause more harm than good. Observers have since debated whether Anthropic’s rhetoric is a mere marketing gimmick or a legitimate attempt to keep a powerful model from being misused. The answer may be somewhere in between.
Cybercriminals have used automated tools for a very long time, but in the age of generative AI, they now have more digital ammunition than ever before. LLMs have proven adept at writing malware, and some can even execute entire ransomware attacks autonomously.
The specific concern with frontier cyber tools like Mythos is that they are ostensibly capable of both identifying and exploiting software vulnerabilities at speeds that no human analyst could match. Since many software systems contain hidden bugs that act as entry points into enterprise networks, this obviously poses an obvious and significant problem for any organization running complex software infrastructure. That said, since these models remain closed to the public, it’s difficult to tell just how much of a threat they really are.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
#White #House #OpenAI #slow #roll #release #model #safety #concerns #TechCrunchAnthropic,Mythos,OpenAI,sam altman,Trump">The White House is asking OpenAI to slow roll the release of its new model over safety concerns | TechCrunch
OpenAI’s release of its newest model, GPT 5.6, reportedly won’t be like its previous releases. Instead of distributing it to the public, the company plans to share it only with a select group of close partners because the Trump administration told it to, reports The Information.
At a meeting this week, CEO Sam Altman reportedly told staff that the government would be “approving access customer by customer” during a preview period. Altman reportedly added that if the limited release goes well, OpenAI hopes to follow with a general, broader release a “couple of weeks later.”
In other words, the Trump administration appears to be pressuring OpenAI to do what Anthropic is already voluntarily doing: keeping its most powerful AI models under wraps.
According to The Information, OpenAI’s new model is not only being reviewed by the administration, but its staffers also “worked closely” with the government on the upcoming release. The agencies that reportedly asked for a limited release were the Office of the National Cyber Director and the Office of Science and Technology Policy.
The Trump administration — which originally positioned itself as taking a “hands off” approach to AI — has in recent months pushed for federal oversight of new models. Earlier this month, Trump signed an executive order directing certain AI companies to voluntarily submit new models to the government for testing and evaluation before releasing them publicly.
Earlier this year, Anthropic sparked no small amount of controversy when it announced that its new frontier cyber model, Claude Mythos, would only be released to a small coterie of partners through a program called Project Glasswing. Anthropic argued that its model was simply too powerful and could, in the wrong hands, cause more harm than good. Observers have since debated whether Anthropic’s rhetoric is a mere marketing gimmick or a legitimate attempt to keep a powerful model from being misused. The answer may be somewhere in between.
Cybercriminals have used automated tools for a very long time, but in the age of generative AI, they now have more digital ammunition than ever before. LLMs have proven adept at writing malware, and some can even execute entire ransomware attacks autonomously.
The specific concern with frontier cyber tools like Mythos is that they are ostensibly capable of both identifying and exploiting software vulnerabilities at speeds that no human analyst could match. Since many software systems contain hidden bugs that act as entry points into enterprise networks, this obviously poses an obvious and significant problem for any organization running complex software infrastructure. That said, since these models remain closed to the public, it’s difficult to tell just how much of a threat they really are.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
Zoph returned to OpenAI in mid-January after a stint as co-founder and CTO of Thinking Machines Lab, the competing AI company founded by former OpenAI CTO Mira Murati. Shortly after Zoph returned to OpenAI, the company said he would lead its push into enterprise — a significant role at OpenAI, since in recent months it had vowed to stop chasing so-called “side quests” and focus on key revenue drivers like enterprise and coding ahead of its planned IPO.
OpenAI confirmed to The Verge that Zoph will be departing. He posted a goodbye message in the company’s Slack channels. Zoph did not immediately respond to a request for comment.
Zoph originally left OpenAI in the fall of 2024 for Murati’s Thinking Machines Lab, but departed the role abruptly in January 2026 after reports of alleged misconduct involving an undisclosed relationship with a colleague. Murati posted on X in January that Thinking Machines Lab had “parted ways” with Zoph and that he would be replaced as CTO.
Thinking Machines Lab has its own tensions with OpenAI. Murati briefly took over as CEO from OpenAI CEO Sam Altman during his November 2023 ouster, and during the recent OpenAI trial, Murati testified that she couldn’t trust everything Altman said. In September 2024, when Murati left OpenAI to start Thinking Machines Lab, a group of OpenAI employees followed shortly after. But three of them — including Zoph — all returned to OpenAI together this past January. Fidji Simo, OpenAI’s CEO of Applications, wrote on X at the time that she was “excited to welcome Barret Zoph, Luke Metz, and Sam Schoenholz back” and that the decision had “been in the works for several weeks.”
Zoph returned to OpenAI in mid-January after a stint as co-founder and CTO of Thinking Machines Lab, the competing AI company founded by former OpenAI CTO Mira Murati. Shortly after Zoph returned to OpenAI, the company said he would lead its push into enterprise — a significant role at OpenAI, since in recent months it had vowed to stop chasing so-called “side quests” and focus on key revenue drivers like enterprise and coding ahead of its planned IPO.
OpenAI confirmed to The Verge that Zoph will be departing. He posted a goodbye message in the company’s Slack channels. Zoph did not immediately respond to a request for comment.
Zoph originally left OpenAI in the fall of 2024 for Murati’s Thinking Machines Lab, but departed the role abruptly in January 2026 after reports of alleged misconduct involving an undisclosed relationship with a colleague. Murati posted on X in January that Thinking Machines Lab had “parted ways” with Zoph and that he would be replaced as CTO.
Thinking Machines Lab has its own tensions with OpenAI. Murati briefly took over as CEO from OpenAI CEO Sam Altman during his November 2023 ouster, and during the recent OpenAI trial, Murati testified that she couldn’t trust everything Altman said. In September 2024, when Murati left OpenAI to start Thinking Machines Lab, a group of OpenAI employees followed shortly after. But three of them — including Zoph — all returned to OpenAI together this past January. Fidji Simo, OpenAI’s CEO of Applications, wrote on X at the time that she was “excited to welcome Barret Zoph, Luke Metz, and Sam Schoenholz back” and that the decision had “been in the works for several weeks.”
#Barret #Zoph #OpenAI #monthsAI,OpenAI,Report">Barret Zoph is out at OpenAI again after just five months
Five months after returning to OpenAI, Barret Zoph — the company’s head of enterprise AI sales — has departed, The Verge has learned.
Zoph returned to OpenAI in mid-January after a stint as co-founder and CTO of Thinking Machines Lab, the competing AI company founded by former OpenAI CTO Mira Murati. Shortly after Zoph returned to OpenAI, the company said he would lead its push into enterprise — a significant role at OpenAI, since in recent months it had vowed to stop chasing so-called “side quests” and focus on key revenue drivers like enterprise and coding ahead of its planned IPO.
OpenAI confirmed to The Verge that Zoph will be departing. He posted a goodbye message in the company’s Slack channels. Zoph did not immediately respond to a request for comment.
Zoph originally left OpenAI in the fall of 2024 for Murati’s Thinking Machines Lab, but departed the role abruptly in January 2026 after reports of alleged misconduct involving an undisclosed relationship with a colleague. Murati posted on X in January that Thinking Machines Lab had “parted ways” with Zoph and that he would be replaced as CTO.
Thinking Machines Lab has its own tensions with OpenAI. Murati briefly took over as CEO from OpenAI CEO Sam Altman during his November 2023 ouster, and during the recent OpenAI trial, Murati testified that she couldn’t trust everything Altman said. In September 2024, when Murati left OpenAI to start Thinking Machines Lab, a group of OpenAI employees followed shortly after. But three of them — including Zoph — all returned to OpenAI together this past January. Fidji Simo, OpenAI’s CEO of Applications, wrote on X at the time that she was “excited to welcome Barret Zoph, Luke Metz, and Sam Schoenholz back” and that the decision had “been in the works for several weeks.”
#Barret #Zoph #OpenAI #monthsAI,OpenAI,Report
Five months after returning to OpenAI, Barret Zoph — the company’s head of enterprise AI…
Hong Kong’s privacy watchdog has launched a data privacy academy as part of efforts to…
OpenAI announced a new feature that it says will provide additional protection from prompt injection attacks, where malicious chatbot instructions are hidden in webpages and other content sources.
Among other things, Lockdown Mode will disable live web browsing (so you can only access cached content), the retrieval and display of images from the web (you can still generate images), deep research, and agent mode.
The company says that even with Lockdown Mode turned on, ChatGPT could still be vulnerable to prompt injections — which could, for example, “appear in cached web content or in an uploaded file, and could still affect the behavior or accuracy of a response.”
But the goal is to reduce the likelihood that sensitive data gets shared in the process.
“Lockdown Mode is not intended for everyone,” OpenAI says. “It is designed for people and organizations that handle sensitive data and want stricter protection from data exfiltration risks related to prompt injection.”
The company says it’s currently rolling Lockdown Mode out to self-serve ChatGPT Business accounts, as well as eligible personal accounts.
OpenAI announced a new feature that it says will provide additional protection from prompt injection attacks, where malicious chatbot instructions are hidden in webpages and other content sources.
Among other things, Lockdown Mode will disable live web browsing (so you can only access cached content), the retrieval and display of images from the web (you can still generate images), deep research, and agent mode.
The company says that even with Lockdown Mode turned on, ChatGPT could still be vulnerable to prompt injections — which could, for example, “appear in cached web content or in an uploaded file, and could still affect the behavior or accuracy of a response.”
But the goal is to reduce the likelihood that sensitive data gets shared in the process.
“Lockdown Mode is not intended for everyone,” OpenAI says. “It is designed for people and organizations that handle sensitive data and want stricter protection from data exfiltration risks related to prompt injection.”
The company says it’s currently rolling Lockdown Mode out to self-serve ChatGPT Business accounts, as well as eligible personal accounts.
#OpenAI #unveils #Lockdown #Mode #protect #sensitive #data #prompt #injection #attacks #TechCrunchOpenAI">OpenAI unveils Lockdown Mode to protect sensitive data from prompt injection attacks | TechCrunch
OpenAI announced a new feature that it says will provide additional protection from prompt injection attacks, where malicious chatbot instructions are hidden in webpages and other content sources.
Among other things, Lockdown Mode will disable live web browsing (so you can only access cached content), the retrieval and display of images from the web (you can still generate images), deep research, and agent mode.
The company says that even with Lockdown Mode turned on, ChatGPT could still be vulnerable to prompt injections — which could, for example, “appear in cached web content or in an uploaded file, and could still affect the behavior or accuracy of a response.”
But the goal is to reduce the likelihood that sensitive data gets shared in the process.
“Lockdown Mode is not intended for everyone,” OpenAI says. “It is designed for people and organizations that handle sensitive data and want stricter protection from data exfiltration risks related to prompt injection.”
The company says it’s currently rolling Lockdown Mode out to self-serve ChatGPT Business accounts, as well as eligible personal accounts.
That means the top of the leaderboard has flipped. Among AI-first tech companies, Anthropic, “the Claude one,” is now technically more valuable than OpenAI, “the ChatGPT one.”
There are, however, some mitigating factors to keep in mind about these valuations. First of all,as critics like Ed Zitron avidly and constantly point out (as well as more staid, mainstream critics like HSBC), AI as a core business is—to say the leas—unproven as a strategy for long-term profitability. Anthropic claims to have just turned an operating profit for one quarter, as the Wall Street Journal reported, but that story also notes that “it is unclear what accounting methods Anthropic has used to book revenue and costs,” and that, “The company might not remain profitable for the full year as it plans spending increases due to its vast computing needs.“
So it would be a stretch to call Anthropic a profitable company. Those aforementioned “vast computing needs” are no secret. It has committed hundreds of billions of dollars to companies like Amazon, Google, and Broadcom over the next decade, and it’s made a short term commitment of $1.5 billion per month to SpaceX.
However, another thing to keep in mind about Anthropic being the new valuation champion is that OpenAI’s most recent valuation was calculated based on a funding round from two months before Anthropic’s. So this is a little like when a sports team overtakes a rival in league rankings having played one more game than the other. There’s more ball still to come.
Since OpenAI and Anthropic are—for now—both privately held companies, price discovery is scattered and a bit sketchy, especially since the companies still don’t have to report their earnings and expenditures publicly. For what it’s worth, Anthropic’s valuation on Forge Global, a secondary market for private shares overtook OpenAI’s last month, with Anthropic’s estimated value at around $1 trillion, and OpenAI’s at $880 billion.
Some degree of clarity is probably on its way. A May 20 New York Times article citing “two people with knowledge of the matter“ said OpenAI was expected to file for an IPO “in the coming weeks.” In fact, it may have filed confidentially on May 22. Meanwhile, Forbes says Anthropic’s IPO could come “as soon as October.”
So perhaps in fall there’ll be a clearer winner in this contest. By then, the pricing of shares in OpenAI and Anthropic will be publicly available in real time. If people dispute that one publicly traded AI company is “worth more” than the other, they can, and probably will, fire up an app like Robinhood and vote with their life savings. And then, well, God help them.
That means the top of the leaderboard has flipped. Among AI-first tech companies, Anthropic, “the Claude one,” is now technically more valuable than OpenAI, “the ChatGPT one.”
There are, however, some mitigating factors to keep in mind about these valuations. First of all,as critics like Ed Zitron avidly and constantly point out (as well as more staid, mainstream critics like HSBC), AI as a core business is—to say the leas—unproven as a strategy for long-term profitability. Anthropic claims to have just turned an operating profit for one quarter, as the Wall Street Journal reported, but that story also notes that “it is unclear what accounting methods Anthropic has used to book revenue and costs,” and that, “The company might not remain profitable for the full year as it plans spending increases due to its vast computing needs.“
So it would be a stretch to call Anthropic a profitable company. Those aforementioned “vast computing needs” are no secret. It has committed hundreds of billions of dollars to companies like Amazon, Google, and Broadcom over the next decade, and it’s made a short term commitment of $1.5 billion per month to SpaceX.
However, another thing to keep in mind about Anthropic being the new valuation champion is that OpenAI’s most recent valuation was calculated based on a funding round from two months before Anthropic’s. So this is a little like when a sports team overtakes a rival in league rankings having played one more game than the other. There’s more ball still to come.
Since OpenAI and Anthropic are—for now—both privately held companies, price discovery is scattered and a bit sketchy, especially since the companies still don’t have to report their earnings and expenditures publicly. For what it’s worth, Anthropic’s valuation on Forge Global, a secondary market for private shares overtook OpenAI’s last month, with Anthropic’s estimated value at around $1 trillion, and OpenAI’s at $880 billion.
Some degree of clarity is probably on its way. A May 20 New York Times article citing “two people with knowledge of the matter“ said OpenAI was expected to file for an IPO “in the coming weeks.” In fact, it may have filed confidentially on May 22. Meanwhile, Forbes says Anthropic’s IPO could come “as soon as October.”
So perhaps in fall there’ll be a clearer winner in this contest. By then, the pricing of shares in OpenAI and Anthropic will be publicly available in real time. If people dispute that one publicly traded AI company is “worth more” than the other, they can, and probably will, fire up an app like Robinhood and vote with their life savings. And then, well, God help them.
#Anthropic #Worth #OpenAIAnthropic,OpenAI,valuation">Anthropic Is Now Worth More Than OpenAI
That means the top of the leaderboard has flipped. Among AI-first tech companies, Anthropic, “the Claude one,” is now technically more valuable than OpenAI, “the ChatGPT one.”
There are, however, some mitigating factors to keep in mind about these valuations. First of all,as critics like Ed Zitron avidly and constantly point out (as well as more staid, mainstream critics like HSBC), AI as a core business is—to say the leas—unproven as a strategy for long-term profitability. Anthropic claims to have just turned an operating profit for one quarter, as the Wall Street Journal reported, but that story also notes that “it is unclear what accounting methods Anthropic has used to book revenue and costs,” and that, “The company might not remain profitable for the full year as it plans spending increases due to its vast computing needs.“
So it would be a stretch to call Anthropic a profitable company. Those aforementioned “vast computing needs” are no secret. It has committed hundreds of billions of dollars to companies like Amazon, Google, and Broadcom over the next decade, and it’s made a short term commitment of $1.5 billion per month to SpaceX.
However, another thing to keep in mind about Anthropic being the new valuation champion is that OpenAI’s most recent valuation was calculated based on a funding round from two months before Anthropic’s. So this is a little like when a sports team overtakes a rival in league rankings having played one more game than the other. There’s more ball still to come.
Since OpenAI and Anthropic are—for now—both privately held companies, price discovery is scattered and a bit sketchy, especially since the companies still don’t have to report their earnings and expenditures publicly. For what it’s worth, Anthropic’s valuation on Forge Global, a secondary market for private shares overtook OpenAI’s last month, with Anthropic’s estimated value at around $1 trillion, and OpenAI’s at $880 billion.
Some degree of clarity is probably on its way. A May 20 New York Times article citing “two people with knowledge of the matter“ said OpenAI was expected to file for an IPO “in the coming weeks.” In fact, it may have filed confidentially on May 22. Meanwhile, Forbes says Anthropic’s IPO could come “as soon as October.”
So perhaps in fall there’ll be a clearer winner in this contest. By then, the pricing of shares in OpenAI and Anthropic will be publicly available in real time. If people dispute that one publicly traded AI company is “worth more” than the other, they can, and probably will, fire up an app like Robinhood and vote with their life savings. And then, well, God help them.
In a blog post on Thursday, Anthropic wrote that it “has raised $65 billion in…
The jury’s speedy decision to reject Elon Musk’s lawsuit against the other founders of OpenAI and Microsoft confirmed what we saw in the courtroom: Musk’s case was a weak one, in part because he waited so long to file it.
Watching the closing arguments last week, OpenAI’s attorneys detailed point-by-point how the law was on their client’s side, while the plaintiffs team focused on Sam Altman’s apparent lack of credibility and expressed disbelief that anyone would disagree with Musk’s accusations.
The final effect was that, after the verdict, some found it hard to believe Musk had lost — including the man himself. In a post he later deleted, Musk called Judge Yvonne Gonzalez Rogers a “terrible activist Oakland judge,” then announced his plans to appeal, declaring “there is no question to anyone following the case in detail that Altman & Brockman did in fact enrich themselves by stealing a charity.”
But Altman and Brockman weren’t the only figures who benefitted from OpenAI’s non-profit investments. As much as Musk and his legal team tried to make the trial about Altman, the proceedings revealed just as much about Musk himself.
One incident that came out in court showed Musk benefiting from OpenAI in an uncomfortably familiar way. Greg Brockman testified that in 2017, Musk asked him to bring a team of OpenAI researchers down to Tesla’s headquarters to help with the autopilot team for a few weeks. “It was pretty clear that was not something we could say no to,” Brockman said.
Brockman described taking a team of leading scientists, including Andrej Karpathy, Ilya Sutskever, and Scott Grey, to consult with the “demoralized” Tesla workers. They helped come up with ideas to improve the vehicle’s self-driving technology, with Sutskever telling the team that if they could find 10,000 images of a tricky corner case, they would be able to fix their software. Musk even asked Brockman to recommend employees to fire, which he declined to do.
Another person familiar with the episode confirmed Brockman’s account, and said Tesla did not reimburse OpenAI for the time and effort of its employees. Musk’s family office, Excession, didn’t reply to a request for comment.
The heart of Musk’s case is that Altman, Brockman and OpenAI committed a “breach of charitable trust” — that Musk donated funds for a specific charitable purpose, and his cofounders instead used them for something else. He also accuses them of “unjust enrichment” due stock and other benefits from OpenAI’s for-profit.
In the case of the OpenAI scientists parachuting into Tesla, Musk’s charitable donations were intended to hire scientists focused on securing the benefits of AGI. Instead, he had them work for free at his for-profit company.
Dorothy Lund, a Columbia Law School professor and the co-host of the Beyond Unprecedented podcast, told TechCrunch that this arrangement wouldn’t be legal, calling it “a bit rich for Musk to be suing for breach of a charitable trust, when he appears to have been redirecting assets in a way that was inconsistent with that mission.”
It’s true that the self-driving work involved artificial intelligence, but witnesses for Musk emphasized that Tesla’s self-driving project was very different from OpenAI’s research agenda. That’s in part because Karpathy left OpenAI for Tesla shortly after this incident. OpenAI’s attorneys portrayed the departure as Musk violating his duty to the lab, where he was co-chair of the board, by recruiting one of its key researchers to his own company.
The other fact that no doubt influenced the jury was the amount of time Musk spent trying to gain sole control of a potential OpenAI for-profit affiliate in 2017. Musk deployed good cop, bad cop tactics in an attempt to convince his cofounders to let him have total control of OpenAI’s for-profit affiliate — giving them free Teslas, and threatening to withhold his donations.
His efforts put his attorneys in a tricky spot, facing a need to convince the jury there was a significant difference between what Musk envisioned, and the for-profit that was ultimately created. They suggested a “small adjunct” for-profit would be permissible, though OpenAI’s witnesses showed non-profits with large commercial arms are common.
Indeed, there’s a very plausible counter-factual where Musk took one of the offers his cofounders made to split their equity more evenly, and finds himself today as one of OpenAI’s largest shareholders — just not the controlling one. But several times during the trial, Musk’s associates testified that he refuses to invest in any business he could have sole control over.
The failure of Musk’s claims because he filed them too late has been cited as a technicality, but the statute of limitations has substance behind it: People and businesses make important decisions and spend resources based on their understanding that what they are doing is permissible. If someone like Musk waits too long to sue, then the cost of unravelling all those decisions can outweigh a just reimbursement.
No members of the jury have spoken about how they arrived at their verdict. However, they were asked to consider if, before Aug. 5, 2021, Musk should have known that OpenAI was spending resources outside its mission or launching for-profit affiliate. The answer to that is clear: Musk himself was doing those things.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
The jury’s speedy decision to reject Elon Musk’s lawsuit against the other founders of OpenAI and Microsoft confirmed what we saw in the courtroom: Musk’s case was a weak one, in part because he waited so long to file it.
Watching the closing arguments last week, OpenAI’s attorneys detailed point-by-point how the law was on their client’s side, while the plaintiffs team focused on Sam Altman’s apparent lack of credibility and expressed disbelief that anyone would disagree with Musk’s accusations.
The final effect was that, after the verdict, some found it hard to believe Musk had lost — including the man himself. In a post he later deleted, Musk called Judge Yvonne Gonzalez Rogers a “terrible activist Oakland judge,” then announced his plans to appeal, declaring “there is no question to anyone following the case in detail that Altman & Brockman did in fact enrich themselves by stealing a charity.”
But Altman and Brockman weren’t the only figures who benefitted from OpenAI’s non-profit investments. As much as Musk and his legal team tried to make the trial about Altman, the proceedings revealed just as much about Musk himself.
One incident that came out in court showed Musk benefiting from OpenAI in an uncomfortably familiar way. Greg Brockman testified that in 2017, Musk asked him to bring a team of OpenAI researchers down to Tesla’s headquarters to help with the autopilot team for a few weeks. “It was pretty clear that was not something we could say no to,” Brockman said.
Brockman described taking a team of leading scientists, including Andrej Karpathy, Ilya Sutskever, and Scott Grey, to consult with the “demoralized” Tesla workers. They helped come up with ideas to improve the vehicle’s self-driving technology, with Sutskever telling the team that if they could find 10,000 images of a tricky corner case, they would be able to fix their software. Musk even asked Brockman to recommend employees to fire, which he declined to do.
Another person familiar with the episode confirmed Brockman’s account, and said Tesla did not reimburse OpenAI for the time and effort of its employees. Musk’s family office, Excession, didn’t reply to a request for comment.
The heart of Musk’s case is that Altman, Brockman and OpenAI committed a “breach of charitable trust” — that Musk donated funds for a specific charitable purpose, and his cofounders instead used them for something else. He also accuses them of “unjust enrichment” due stock and other benefits from OpenAI’s for-profit.
In the case of the OpenAI scientists parachuting into Tesla, Musk’s charitable donations were intended to hire scientists focused on securing the benefits of AGI. Instead, he had them work for free at his for-profit company.
Dorothy Lund, a Columbia Law School professor and the co-host of the Beyond Unprecedented podcast, told TechCrunch that this arrangement wouldn’t be legal, calling it “a bit rich for Musk to be suing for breach of a charitable trust, when he appears to have been redirecting assets in a way that was inconsistent with that mission.”
It’s true that the self-driving work involved artificial intelligence, but witnesses for Musk emphasized that Tesla’s self-driving project was very different from OpenAI’s research agenda. That’s in part because Karpathy left OpenAI for Tesla shortly after this incident. OpenAI’s attorneys portrayed the departure as Musk violating his duty to the lab, where he was co-chair of the board, by recruiting one of its key researchers to his own company.
The other fact that no doubt influenced the jury was the amount of time Musk spent trying to gain sole control of a potential OpenAI for-profit affiliate in 2017. Musk deployed good cop, bad cop tactics in an attempt to convince his cofounders to let him have total control of OpenAI’s for-profit affiliate — giving them free Teslas, and threatening to withhold his donations.
His efforts put his attorneys in a tricky spot, facing a need to convince the jury there was a significant difference between what Musk envisioned, and the for-profit that was ultimately created. They suggested a “small adjunct” for-profit would be permissible, though OpenAI’s witnesses showed non-profits with large commercial arms are common.
Indeed, there’s a very plausible counter-factual where Musk took one of the offers his cofounders made to split their equity more evenly, and finds himself today as one of OpenAI’s largest shareholders — just not the controlling one. But several times during the trial, Musk’s associates testified that he refuses to invest in any business he could have sole control over.
The failure of Musk’s claims because he filed them too late has been cited as a technicality, but the statute of limitations has substance behind it: People and businesses make important decisions and spend resources based on their understanding that what they are doing is permissible. If someone like Musk waits too long to sue, then the cost of unravelling all those decisions can outweigh a just reimbursement.
No members of the jury have spoken about how they arrived at their verdict. However, they were asked to consider if, before Aug. 5, 2021, Musk should have known that OpenAI was spending resources outside its mission or launching for-profit affiliate. The answer to that is clear: Musk himself was doing those things.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
#Elon #Musk #Sam #Altman #stole #nonprofit #trial #showed #similar #aims #TechCrunchElon Musk,OpenAI,sam altman,Tesla">Elon Musk said Sam Altman “stole” a non-profit — but the trial showed he had similar aims | TechCrunch
The jury’s speedy decision to reject Elon Musk’s lawsuit against the other founders of OpenAI and Microsoft confirmed what we saw in the courtroom: Musk’s case was a weak one, in part because he waited so long to file it.
Watching the closing arguments last week, OpenAI’s attorneys detailed point-by-point how the law was on their client’s side, while the plaintiffs team focused on Sam Altman’s apparent lack of credibility and expressed disbelief that anyone would disagree with Musk’s accusations.
The final effect was that, after the verdict, some found it hard to believe Musk had lost — including the man himself. In a post he later deleted, Musk called Judge Yvonne Gonzalez Rogers a “terrible activist Oakland judge,” then announced his plans to appeal, declaring “there is no question to anyone following the case in detail that Altman & Brockman did in fact enrich themselves by stealing a charity.”
But Altman and Brockman weren’t the only figures who benefitted from OpenAI’s non-profit investments. As much as Musk and his legal team tried to make the trial about Altman, the proceedings revealed just as much about Musk himself.
One incident that came out in court showed Musk benefiting from OpenAI in an uncomfortably familiar way. Greg Brockman testified that in 2017, Musk asked him to bring a team of OpenAI researchers down to Tesla’s headquarters to help with the autopilot team for a few weeks. “It was pretty clear that was not something we could say no to,” Brockman said.
Brockman described taking a team of leading scientists, including Andrej Karpathy, Ilya Sutskever, and Scott Grey, to consult with the “demoralized” Tesla workers. They helped come up with ideas to improve the vehicle’s self-driving technology, with Sutskever telling the team that if they could find 10,000 images of a tricky corner case, they would be able to fix their software. Musk even asked Brockman to recommend employees to fire, which he declined to do.
Another person familiar with the episode confirmed Brockman’s account, and said Tesla did not reimburse OpenAI for the time and effort of its employees. Musk’s family office, Excession, didn’t reply to a request for comment.
The heart of Musk’s case is that Altman, Brockman and OpenAI committed a “breach of charitable trust” — that Musk donated funds for a specific charitable purpose, and his cofounders instead used them for something else. He also accuses them of “unjust enrichment” due stock and other benefits from OpenAI’s for-profit.
In the case of the OpenAI scientists parachuting into Tesla, Musk’s charitable donations were intended to hire scientists focused on securing the benefits of AGI. Instead, he had them work for free at his for-profit company.
Dorothy Lund, a Columbia Law School professor and the co-host of the Beyond Unprecedented podcast, told TechCrunch that this arrangement wouldn’t be legal, calling it “a bit rich for Musk to be suing for breach of a charitable trust, when he appears to have been redirecting assets in a way that was inconsistent with that mission.”
It’s true that the self-driving work involved artificial intelligence, but witnesses for Musk emphasized that Tesla’s self-driving project was very different from OpenAI’s research agenda. That’s in part because Karpathy left OpenAI for Tesla shortly after this incident. OpenAI’s attorneys portrayed the departure as Musk violating his duty to the lab, where he was co-chair of the board, by recruiting one of its key researchers to his own company.
The other fact that no doubt influenced the jury was the amount of time Musk spent trying to gain sole control of a potential OpenAI for-profit affiliate in 2017. Musk deployed good cop, bad cop tactics in an attempt to convince his cofounders to let him have total control of OpenAI’s for-profit affiliate — giving them free Teslas, and threatening to withhold his donations.
His efforts put his attorneys in a tricky spot, facing a need to convince the jury there was a significant difference between what Musk envisioned, and the for-profit that was ultimately created. They suggested a “small adjunct” for-profit would be permissible, though OpenAI’s witnesses showed non-profits with large commercial arms are common.
Indeed, there’s a very plausible counter-factual where Musk took one of the offers his cofounders made to split their equity more evenly, and finds himself today as one of OpenAI’s largest shareholders — just not the controlling one. But several times during the trial, Musk’s associates testified that he refuses to invest in any business he could have sole control over.
The failure of Musk’s claims because he filed them too late has been cited as a technicality, but the statute of limitations has substance behind it: People and businesses make important decisions and spend resources based on their understanding that what they are doing is permissible. If someone like Musk waits too long to sue, then the cost of unravelling all those decisions can outweigh a just reimbursement.
No members of the jury have spoken about how they arrived at their verdict. However, they were asked to consider if, before Aug. 5, 2021, Musk should have known that OpenAI was spending resources outside its mission or launching for-profit affiliate. The answer to that is clear: Musk himself was doing those things.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
