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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.
#OpenAI #unveils #Lockdown #Mode #protect #sensitive #data #prompt #injection #attacks #TechCrunchOpenAI
Tech-news

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.

#OpenAI #unveils #Lockdown #Mode #protect #sensitive #data #prompt #injection #attacks #TechCrunchOpenAI

OpenAI announced a new feature that it says will provide additional protection from prompt injection…

blog post on Thursday, Anthropic wrote that it “has raised $65 billion in Series H funding led by Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital, valuing the company at $965 billion post-money.” The most recent blog post along similar lines from OpenAI places its valuation at $852 billion.

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.

Investors are no doubt aware of all that spending, but they also know Anthropic’s revenue exploded around the start of the 2026 calendar year because of an influx of enterprise clients. Vibe coding is the apparent norm now, creating a narrative in which companies supposedly no longer need young coders to do menial work thanks to Claude Code—along with competitor products like OpenAI’s Codex. Announcements of small changes to Anthropic’s Claude Code product have started to have huge impacts on the stock market, particularly the valuations of software-as-a-service (SaaS) companies.

Rather than leading lately, OpenAI is seen to be playing catch-up.

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.

Want an even sketchier estimate? Polymarket places the odds of Anthropic having a higher valuation than OpenAI at the end of June at 89% as of this writing.

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
                In a blog post on Thursday, Anthropic wrote that it “has raised  billion in Series H funding led by Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital, valuing the company at 5 billion post-money.” The most recent blog post along similar lines from OpenAI places its valuation at 2 billion. 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 .5 billion per month to SpaceX.

 Investors are no doubt aware of all that spending, but they also know Anthropic’s revenue exploded around the start of the 2026 calendar year because of an influx of enterprise clients. Vibe coding is the apparent norm now, creating a narrative in which companies supposedly no longer need young coders to do menial work thanks to Claude Code—along with competitor products like OpenAI’s Codex. Announcements of small changes to Anthropic’s Claude Code product have started to have huge impacts on the stock market, particularly the valuations of software-as-a-service (SaaS) companies. Rather than leading lately, OpenAI is seen to be playing catch-up. 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  trillion, and OpenAI’s at 0 billion. Want an even sketchier estimate? Polymarket places the odds of Anthropic having a higher valuation than OpenAI at the end of June at 89% as of this writing. 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
Tech-news

blog post on Thursday, Anthropic wrote that it “has raised $65 billion in Series H funding led by Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital, valuing the company at $965 billion post-money.” The most recent blog post along similar lines from OpenAI places its valuation at $852 billion.

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.

Investors are no doubt aware of all that spending, but they also know Anthropic’s revenue exploded around the start of the 2026 calendar year because of an influx of enterprise clients. Vibe coding is the apparent norm now, creating a narrative in which companies supposedly no longer need young coders to do menial work thanks to Claude Code—along with competitor products like OpenAI’s Codex. Announcements of small changes to Anthropic’s Claude Code product have started to have huge impacts on the stock market, particularly the valuations of software-as-a-service (SaaS) companies.

Rather than leading lately, OpenAI is seen to be playing catch-up.

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.

Want an even sketchier estimate? Polymarket places the odds of Anthropic having a higher valuation than OpenAI at the end of June at 89% as of this writing.

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 OpenAIAnthropic Is Now Worth More Than OpenAI
                In a blog post on Thursday, Anthropic wrote that it “has raised $65 billion in Series H funding led by Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital, valuing the company at $965 billion post-money.” The most recent blog post along similar lines from OpenAI places its valuation at $852 billion. 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.

 Investors are no doubt aware of all that spending, but they also know Anthropic’s revenue exploded around the start of the 2026 calendar year because of an influx of enterprise clients. Vibe coding is the apparent norm now, creating a narrative in which companies supposedly no longer need young coders to do menial work thanks to Claude Code—along with competitor products like OpenAI’s Codex. Announcements of small changes to Anthropic’s Claude Code product have started to have huge impacts on the stock market, particularly the valuations of software-as-a-service (SaaS) companies. Rather than leading lately, OpenAI is seen to be playing catch-up. 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. Want an even sketchier estimate? Polymarket places the odds of Anthropic having a higher valuation than OpenAI at the end of June at 89% as of this writing. 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

In a blog post on Thursday, Anthropic wrote that it “has raised $65 billion in Series H funding led by Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital, valuing the company at $965 billion post-money.” The most recent blog post along similar lines from OpenAI places its valuation at $852 billion.

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.

Investors are no doubt aware of all that spending, but they also know Anthropic’s revenue exploded around the start of the 2026 calendar year because of an influx of enterprise clients. Vibe coding is the apparent norm now, creating a narrative in which companies supposedly no longer need young coders to do menial work thanks to Claude Code—along with competitor products like OpenAI’s Codex. Announcements of small changes to Anthropic’s Claude Code product have started to have huge impacts on the stock market, particularly the valuations of software-as-a-service (SaaS) companies.

Rather than leading lately, OpenAI is seen to be playing catch-up.

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.

Want an even sketchier estimate? Polymarket places the odds of Anthropic having a higher valuation than OpenAI at the end of June at 89% as of this writing.

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

In a blog post on Thursday, Anthropic wrote that it “has raised $65 billion in…

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.#Elon #Musk #Sam #Altman #stole #nonprofit #trial #showed #similar #aims #TechCrunchElon Musk,OpenAI,sam altman,Tesla
Tech-news

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.

#Elon #Musk #Sam #Altman #stole #nonprofit #trial #showed #similar #aims #TechCrunchElon Musk,OpenAI,sam altman,Tesla

The jury’s speedy decision to reject Elon Musk’s lawsuit against the other founders of OpenAI…

Elon Musk told us all he doesn’t lose his temper. (He then proceeded to lose his temper on cross-examination.) Or like when Shivon Zilis, the mother of several of his children, told us that she didn’t know Musk was starting xAI — which seemed to be directly contradicted by her text messages. Or when Greg “What will take me to $1B?” Brockman told us he was all about the mission. I certainly believe Altman isn’t trustworthy — I mean, The New Yorker published more than 17,000 words about how much he lies. But unlike with Musk, there are contemporaneous documents backing Altman’s version of the story. At least, mostly.

“My belief is he wanted to have long-term control”

After OpenAI’s Dota 2 win, discussions for a for-profit arm started in earnest. “Mr. Musk felt very strongly that if we were going to form a for-profit he needed to have total control over it initially,” Altman said. “He only trusted himself to make non-obvious decisions that were going to turn out to be correct.”

Altman testified that he was uncomfortable with Musk’s insistence on control, not just because Musk hadn’t been as involved as everyone else, but because OpenAI existed so no one person would control AGI. And at Y Combinator, the startup incubator where he was president, Altman had seen a lot of control fights; no one wanted to give up power when things were going well. With structures like supervoting shares, founders could retain control forever. Curiously, Altman’s example was not the most famous one (Mark Zuckerberg at Meta); it was Musk and SpaceX. When Altman asked Musk about succession plans for OpenAI, he got a particularly “hair-raising” answer: In the event of Musk’s death, Musk said, “I haven’t thought about it a ton, but maybe control should pass to my children.”

I don’t know about that. But I do know that I saw a 2017 email from Altman to Zilis in which he wrote, “I am worried about control. I don’t think any one person should have control of the world’s first AGI — in fact the whole reason we started OpenAI was so that wouldn’t happen.” He went on to say that he didn’t mind the idea of immediate control and was open to “creative structures” — which I understood to mean that, in order to placate Musk, Altman was willing to give him control up to specific milestones in company development.

“I read a vague, like, a lightweight threat in there”

“My belief is he wanted to have long-term control and that he would’ve had that had we agreed to the structure he wanted,” Altman said on the stand. This sounds basically right. In later video testimony from Sam Teller’s deposition, we heard that Musk no longer invests in anything he doesn’t control. This also fits with Musk’s long-term fixation on making sure he can’t get booted from his own company the way he got booted from PayPal.

Musk also tried to recruit Altman to Tesla. We saw texts between Altman and Teller, in which Teller told Altman that Musk was committed to beefing up Tesla’s AI no matter what, and that he hoped that Altman, Brockman, and Ilya Sutskever would want to join eventually. “I read a vague, like, a lightweight threat in there, that he’s gonna do this inside of Tesla with or without you,” Altman said. But he felt that Tesla was primarily a car company — allowing it to acquire OpenAI would betray OpenAI’s mission.

Later, in Teller’s testimony, we saw texts Teller sent to Zilis at 12:40AM on February 4th, 2018: “I don’t love OpenAI continuing without Elon,” he wrote. “Would rather disable it by recruiting the leaders.”

When Musk stopped his quarterly donations, OpenAI was operating on a “shoestring” with an “extremely short runway of cash.” OpenAI did have other donors, none of whom have sued it or joined Musk’s suit. (One donor in the exhibit that wasn’t called out to the courtroom was Alameda Research, the firm owned by Sam Bankman-Fried, who is now in prison for fraud and money laundering.) Musk’s resignation from the board meant “people wondered if he was gonna try to take, uh, vengeance out on us or something.” On the other hand, Altman said Musk had “demotivated some of our key researchers” and done “huge damage for a long time to the culture of the organization.” So it sure seems like some people were relieved to be rid of him.

I’ve seen some fairly shoddy lawyering from Musk’s side throughout this trial

We saw a lot of evidence that throughout the time Altman was setting up OpenAI’s for-profit arm, he kept Musk apprised of what was going on, either directly or through Zilis or Teller. At no point did Musk object, and whatever he said publicly about the Microsoft investments, there was plenty of evidence that privately he’d been made aware.

On the cross-examination, we were treated to more than 10 minutes of Steven Molo telling Altman that various and assorted people had called him a liar: Sutskever, Mira Murati, Helen Toner, Tasha McCauley, Daniela and Dario Amodei (former OpenAI employees and founders of Anthropic), employees at Altman’s first startup Loopt, that recent New Yorker article, a book called The Optimist, etc. Molo did score some points by asking Altman about testimony in the trial, which Altman said he wasn’t paying close attention to. Molo acted as though this was inconceivable. Surely someone had informed Altman of what was said?

It was a little funny and also a little tiresome. Altman kept his cool, though, seeming hurt and confused by the focus on whether he was a liar. It was also the most successful part of the cross, which declined in focus precipitously afterward. I’ve seen some fairly shoddy lawyering from Musk’s side throughout this trial, and today was pretty bad. At one point, when Molo was trying to capitalize on Altman being both CEO and on the company’s board, Altman said — truthfully — that CEOs are almost always on the boards of the companies they run.

(At this point in my notes, I had written, “Boy, Molo is not very good at this.”)

The point of this trial isn’t to win — it’s to punish Altman, Brockman, and OpenAI

There was also an unconvincing argument about fundraising in nonprofits, specifically that if Stanford could raise $3 billion a year, OpenAI should have remained a nonprofit. Okay, let’s just think about that for a minute. Stanford has a donor network of thousands of graduates. It’s a school, which has very different capital requirements. It is not competing with any reputable for-profit companies. But leave that all aside and assume that some fundraising genius took over at the OpenAI Foundation: $3 billion is the initial two Microsoft investments combined, and not enough to scale OpenAI to where it is now. If compute is the main bottleneck on building AI models, then Molo’s line of argument suggests OpenAI never would have managed to be successful as a nonprofit alone. He’s making the defense’s case for them.

But the thing is, Molo doesn’t actually have to be good at this job, because the point of this trial isn’t to win — though I’m sure Musk wouldn’t mind a win. The point is to punish Altman, Brockman, and OpenAI. Musk has done that pretty thoroughly — reinforcing in the public’s mind that Altman is a liar and a snake. This morning, I read an exclusive in The Wall Street Journal that assorted Republican AGs and the House Oversight committee wanted to look into Sam Altman’s investments. References to the trial are peppered throughout the article.

So yes, Altman was convincing on the stand. He may even win the suit. But it sure seems like Musk’s vengeance has just begun.

Follow topics and authors from this story to see more like this in your personalized homepage feed and to receive email updates.
#Sam #Altman #winning #standAI,OpenAI"> Sam Altman was winning on the stand, but it might not be enoughAfter two weeks of hearing from assorted witnesses that he was a lying snake, the jury finally heard from the lying snake himself: Sam Altman. At the end of the testimony, his lawyer William Savitt asked him how it felt to be accused of stealing a charity.“We created, through a ton of hard work, this extremely large charity, and I agree you can’t steal it,” Altman said. “Mr. Musk did try to kill it, I guess. Twice.”Altman was fully in “nice kid from St. Louis” mode, and did a passable impression of a man who was bewildered at what was happening to him. When he stepped down from the stand holding a stack of evidence binders, he even looked a little like a schoolboy. He seemed nervous at the beginning of his direct testimony, though he warmed up fairly quickly. Overall, he seemed to give credible testimony — and at times, it seemed like the jury liked him.Throughout this trial I’ve had some difficulty imagining what the jury is making of all this because I am a little too familiar with the figures who are testifying. I have heard some audacious lies under oath, like when Elon Musk told us all he doesn’t lose his temper. (He then proceeded to lose his temper on cross-examination.) Or like when Shivon Zilis, the mother of several of his children, told us that she didn’t know Musk was starting xAI — which seemed to be directly contradicted by her text messages. Or when Greg “What will take me to B?” Brockman told us he was all about the mission. I certainly believe Altman isn’t trustworthy — I mean, The New Yorker published more than 17,000 words about how much he lies. But unlike with Musk, there are contemporaneous documents backing Altman’s version of the story. At least, mostly.“My belief is he wanted to have long-term control”After OpenAI’s Dota 2 win, discussions for a for-profit arm started in earnest. “Mr. Musk felt very strongly that if we were going to form a for-profit he needed to have total control over it initially,” Altman said. “He only trusted himself to make non-obvious decisions that were going to turn out to be correct.”Altman testified that he was uncomfortable with Musk’s insistence on control, not just because Musk hadn’t been as involved as everyone else, but because OpenAI existed so no one person would control AGI. And at Y Combinator, the startup incubator where he was president, Altman had seen a lot of control fights; no one wanted to give up power when things were going well. With structures like supervoting shares, founders could retain control forever. Curiously, Altman’s example was not the most famous one (Mark Zuckerberg at Meta); it was Musk and SpaceX. When Altman asked Musk about succession plans for OpenAI, he got a particularly “hair-raising” answer: In the event of Musk’s death, Musk said, “I haven’t thought about it a ton, but maybe control should pass to my children.”I don’t know about that. But I do know that I saw a 2017 email from Altman to Zilis in which he wrote, “I am worried about control. I don’t think any one person should have control of the world’s first AGI — in fact the whole reason we started OpenAI was so that wouldn’t happen.” He went on to say that he didn’t mind the idea of immediate control and was open to “creative structures” — which I understood to mean that, in order to placate Musk, Altman was willing to give him control up to specific milestones in company development.“I read a vague, like, a lightweight threat in there”“My belief is he wanted to have long-term control and that he would’ve had that had we agreed to the structure he wanted,” Altman said on the stand. This sounds basically right. In later video testimony from Sam Teller’s deposition, we heard that Musk no longer invests in anything he doesn’t control. This also fits with Musk’s long-term fixation on making sure he can’t get booted from his own company the way he got booted from PayPal.Musk also tried to recruit Altman to Tesla. We saw texts between Altman and Teller, in which Teller told Altman that Musk was committed to beefing up Tesla’s AI no matter what, and that he hoped that Altman, Brockman, and Ilya Sutskever would want to join eventually. “I read a vague, like, a lightweight threat in there, that he’s gonna do this inside of Tesla with or without you,” Altman said. But he felt that Tesla was primarily a car company — allowing it to acquire OpenAI would betray OpenAI’s mission.Later, in Teller’s testimony, we saw texts Teller sent to Zilis at 12:40AM on February 4th, 2018: “I don’t love OpenAI continuing without Elon,” he wrote. “Would rather disable it by recruiting the leaders.”When Musk stopped his quarterly donations, OpenAI was operating on a “shoestring” with an “extremely short runway of cash.” OpenAI did have other donors, none of whom have sued it or joined Musk’s suit. (One donor in the exhibit that wasn’t called out to the courtroom was Alameda Research, the firm owned by Sam Bankman-Fried, who is now in prison for fraud and money laundering.) Musk’s resignation from the board meant “people wondered if he was gonna try to take, uh, vengeance out on us or something.” On the other hand, Altman said Musk had “demotivated some of our key researchers” and done “huge damage for a long time to the culture of the organization.” So it sure seems like some people were relieved to be rid of him.I’ve seen some fairly shoddy lawyering from Musk’s side throughout this trialWe saw a lot of evidence that throughout the time Altman was setting up OpenAI’s for-profit arm, he kept Musk apprised of what was going on, either directly or through Zilis or Teller. At no point did Musk object, and whatever he said publicly about the Microsoft investments, there was plenty of evidence that privately he’d been made aware.On the cross-examination, we were treated to more than 10 minutes of Steven Molo telling Altman that various and assorted people had called him a liar: Sutskever, Mira Murati, Helen Toner, Tasha McCauley, Daniela and Dario Amodei (former OpenAI employees and founders of Anthropic), employees at Altman’s first startup Loopt, that recent New Yorker article, a book called The Optimist, etc. Molo did score some points by asking Altman about testimony in the trial, which Altman said he wasn’t paying close attention to. Molo acted as though this was inconceivable. Surely someone had informed Altman of what was said?It was a little funny and also a little tiresome. Altman kept his cool, though, seeming hurt and confused by the focus on whether he was a liar. It was also the most successful part of the cross, which declined in focus precipitously afterward. I’ve seen some fairly shoddy lawyering from Musk’s side throughout this trial, and today was pretty bad. At one point, when Molo was trying to capitalize on Altman being both CEO and on the company’s board, Altman said — truthfully — that CEOs are almost always on the boards of the companies they run.(At this point in my notes, I had written, “Boy, Molo is not very good at this.”)The point of this trial isn’t to win — it’s to punish Altman, Brockman, and OpenAIThere was also an unconvincing argument about fundraising in nonprofits, specifically that if Stanford could raise  billion a year, OpenAI should have remained a nonprofit. Okay, let’s just think about that for a minute. Stanford has a donor network of thousands of graduates. It’s a school, which has very different capital requirements. It is not competing with any reputable for-profit companies. But leave that all aside and assume that some fundraising genius took over at the OpenAI Foundation:  billion is the initial two Microsoft investments combined, and not enough to scale OpenAI to where it is now. If compute is the main bottleneck on building AI models, then Molo’s line of argument suggests OpenAI never would have managed to be successful as a nonprofit alone. He’s making the defense’s case for them.But the thing is, Molo doesn’t actually have to be good at this job, because the point of this trial isn’t to win — though I’m sure Musk wouldn’t mind a win. The point is to punish Altman, Brockman, and OpenAI. Musk has done that pretty thoroughly — reinforcing in the public’s mind that Altman is a liar and a snake. This morning, I read an exclusive in The Wall Street Journal that assorted Republican AGs and the House Oversight committee wanted to look into Sam Altman’s investments. References to the trial are peppered throughout the article.So yes, Altman was convincing on the stand. He may even win the suit. But it sure seems like Musk’s vengeance has just begun.Follow topics and authors from this story to see more like this in your personalized homepage feed and to receive email updates.Elizabeth LopattoCloseElizabeth LopattoPosts from this author will be added to your daily email digest and your homepage feed.FollowFollowSee All by Elizabeth LopattoAICloseAIPosts from this topic will be added to your daily email digest and your homepage feed.FollowFollowSee All AIOpenAICloseOpenAIPosts from this topic will be added to your daily email digest and your homepage feed.FollowFollowSee All OpenAI#Sam #Altman #winning #standAI,OpenAI
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Elon Musk told us all he doesn’t lose his temper. (He then proceeded to lose his temper on cross-examination.) Or like when Shivon Zilis, the mother of several of his children, told us that she didn’t know Musk was starting xAI — which seemed to be directly contradicted by her text messages. Or when Greg “What will take me to $1B?” Brockman told us he was all about the mission. I certainly believe Altman isn’t trustworthy — I mean, The New Yorker published more than 17,000 words about how much he lies. But unlike with Musk, there are contemporaneous documents backing Altman’s version of the story. At least, mostly.

“My belief is he wanted to have long-term control”

After OpenAI’s Dota 2 win, discussions for a for-profit arm started in earnest. “Mr. Musk felt very strongly that if we were going to form a for-profit he needed to have total control over it initially,” Altman said. “He only trusted himself to make non-obvious decisions that were going to turn out to be correct.”

Altman testified that he was uncomfortable with Musk’s insistence on control, not just because Musk hadn’t been as involved as everyone else, but because OpenAI existed so no one person would control AGI. And at Y Combinator, the startup incubator where he was president, Altman had seen a lot of control fights; no one wanted to give up power when things were going well. With structures like supervoting shares, founders could retain control forever. Curiously, Altman’s example was not the most famous one (Mark Zuckerberg at Meta); it was Musk and SpaceX. When Altman asked Musk about succession plans for OpenAI, he got a particularly “hair-raising” answer: In the event of Musk’s death, Musk said, “I haven’t thought about it a ton, but maybe control should pass to my children.”

I don’t know about that. But I do know that I saw a 2017 email from Altman to Zilis in which he wrote, “I am worried about control. I don’t think any one person should have control of the world’s first AGI — in fact the whole reason we started OpenAI was so that wouldn’t happen.” He went on to say that he didn’t mind the idea of immediate control and was open to “creative structures” — which I understood to mean that, in order to placate Musk, Altman was willing to give him control up to specific milestones in company development.

“I read a vague, like, a lightweight threat in there”

“My belief is he wanted to have long-term control and that he would’ve had that had we agreed to the structure he wanted,” Altman said on the stand. This sounds basically right. In later video testimony from Sam Teller’s deposition, we heard that Musk no longer invests in anything he doesn’t control. This also fits with Musk’s long-term fixation on making sure he can’t get booted from his own company the way he got booted from PayPal.

Musk also tried to recruit Altman to Tesla. We saw texts between Altman and Teller, in which Teller told Altman that Musk was committed to beefing up Tesla’s AI no matter what, and that he hoped that Altman, Brockman, and Ilya Sutskever would want to join eventually. “I read a vague, like, a lightweight threat in there, that he’s gonna do this inside of Tesla with or without you,” Altman said. But he felt that Tesla was primarily a car company — allowing it to acquire OpenAI would betray OpenAI’s mission.

Later, in Teller’s testimony, we saw texts Teller sent to Zilis at 12:40AM on February 4th, 2018: “I don’t love OpenAI continuing without Elon,” he wrote. “Would rather disable it by recruiting the leaders.”

When Musk stopped his quarterly donations, OpenAI was operating on a “shoestring” with an “extremely short runway of cash.” OpenAI did have other donors, none of whom have sued it or joined Musk’s suit. (One donor in the exhibit that wasn’t called out to the courtroom was Alameda Research, the firm owned by Sam Bankman-Fried, who is now in prison for fraud and money laundering.) Musk’s resignation from the board meant “people wondered if he was gonna try to take, uh, vengeance out on us or something.” On the other hand, Altman said Musk had “demotivated some of our key researchers” and done “huge damage for a long time to the culture of the organization.” So it sure seems like some people were relieved to be rid of him.

I’ve seen some fairly shoddy lawyering from Musk’s side throughout this trial

We saw a lot of evidence that throughout the time Altman was setting up OpenAI’s for-profit arm, he kept Musk apprised of what was going on, either directly or through Zilis or Teller. At no point did Musk object, and whatever he said publicly about the Microsoft investments, there was plenty of evidence that privately he’d been made aware.

On the cross-examination, we were treated to more than 10 minutes of Steven Molo telling Altman that various and assorted people had called him a liar: Sutskever, Mira Murati, Helen Toner, Tasha McCauley, Daniela and Dario Amodei (former OpenAI employees and founders of Anthropic), employees at Altman’s first startup Loopt, that recent New Yorker article, a book called The Optimist, etc. Molo did score some points by asking Altman about testimony in the trial, which Altman said he wasn’t paying close attention to. Molo acted as though this was inconceivable. Surely someone had informed Altman of what was said?

It was a little funny and also a little tiresome. Altman kept his cool, though, seeming hurt and confused by the focus on whether he was a liar. It was also the most successful part of the cross, which declined in focus precipitously afterward. I’ve seen some fairly shoddy lawyering from Musk’s side throughout this trial, and today was pretty bad. At one point, when Molo was trying to capitalize on Altman being both CEO and on the company’s board, Altman said — truthfully — that CEOs are almost always on the boards of the companies they run.

(At this point in my notes, I had written, “Boy, Molo is not very good at this.”)

The point of this trial isn’t to win — it’s to punish Altman, Brockman, and OpenAI

There was also an unconvincing argument about fundraising in nonprofits, specifically that if Stanford could raise $3 billion a year, OpenAI should have remained a nonprofit. Okay, let’s just think about that for a minute. Stanford has a donor network of thousands of graduates. It’s a school, which has very different capital requirements. It is not competing with any reputable for-profit companies. But leave that all aside and assume that some fundraising genius took over at the OpenAI Foundation: $3 billion is the initial two Microsoft investments combined, and not enough to scale OpenAI to where it is now. If compute is the main bottleneck on building AI models, then Molo’s line of argument suggests OpenAI never would have managed to be successful as a nonprofit alone. He’s making the defense’s case for them.

But the thing is, Molo doesn’t actually have to be good at this job, because the point of this trial isn’t to win — though I’m sure Musk wouldn’t mind a win. The point is to punish Altman, Brockman, and OpenAI. Musk has done that pretty thoroughly — reinforcing in the public’s mind that Altman is a liar and a snake. This morning, I read an exclusive in The Wall Street Journal that assorted Republican AGs and the House Oversight committee wanted to look into Sam Altman’s investments. References to the trial are peppered throughout the article.

So yes, Altman was convincing on the stand. He may even win the suit. But it sure seems like Musk’s vengeance has just begun.

Follow topics and authors from this story to see more like this in your personalized homepage feed and to receive email updates.

#Sam #Altman #winning #standAI,OpenAI">Sam Altman was winning on the stand, but it might not be enough

After two weeks of hearing from assorted witnesses that he was a lying snake, the jury finally heard from the lying snake himself: Sam Altman. At the end of the testimony, his lawyer William Savitt asked him how it felt to be accused of stealing a charity.

“We created, through a ton of hard work, this extremely large charity, and I agree you can’t steal it,” Altman said. “Mr. Musk did try to kill it, I guess. Twice.”

Altman was fully in “nice kid from St. Louis” mode, and did a passable impression of a man who was bewildered at what was happening to him. When he stepped down from the stand holding a stack of evidence binders, he even looked a little like a schoolboy. He seemed nervous at the beginning of his direct testimony, though he warmed up fairly quickly. Overall, he seemed to give credible testimony — and at times, it seemed like the jury liked him.

Throughout this trial I’ve had some difficulty imagining what the jury is making of all this because I am a little too familiar with the figures who are testifying. I have heard some audacious lies under oath, like when Elon Musk told us all he doesn’t lose his temper. (He then proceeded to lose his temper on cross-examination.) Or like when Shivon Zilis, the mother of several of his children, told us that she didn’t know Musk was starting xAI — which seemed to be directly contradicted by her text messages. Or when Greg “What will take me to $1B?” Brockman told us he was all about the mission. I certainly believe Altman isn’t trustworthy — I mean, The New Yorker published more than 17,000 words about how much he lies. But unlike with Musk, there are contemporaneous documents backing Altman’s version of the story. At least, mostly.

“My belief is he wanted to have long-term control”

After OpenAI’s Dota 2 win, discussions for a for-profit arm started in earnest. “Mr. Musk felt very strongly that if we were going to form a for-profit he needed to have total control over it initially,” Altman said. “He only trusted himself to make non-obvious decisions that were going to turn out to be correct.”

Altman testified that he was uncomfortable with Musk’s insistence on control, not just because Musk hadn’t been as involved as everyone else, but because OpenAI existed so no one person would control AGI. And at Y Combinator, the startup incubator where he was president, Altman had seen a lot of control fights; no one wanted to give up power when things were going well. With structures like supervoting shares, founders could retain control forever. Curiously, Altman’s example was not the most famous one (Mark Zuckerberg at Meta); it was Musk and SpaceX. When Altman asked Musk about succession plans for OpenAI, he got a particularly “hair-raising” answer: In the event of Musk’s death, Musk said, “I haven’t thought about it a ton, but maybe control should pass to my children.”

I don’t know about that. But I do know that I saw a 2017 email from Altman to Zilis in which he wrote, “I am worried about control. I don’t think any one person should have control of the world’s first AGI — in fact the whole reason we started OpenAI was so that wouldn’t happen.” He went on to say that he didn’t mind the idea of immediate control and was open to “creative structures” — which I understood to mean that, in order to placate Musk, Altman was willing to give him control up to specific milestones in company development.

“I read a vague, like, a lightweight threat in there”

“My belief is he wanted to have long-term control and that he would’ve had that had we agreed to the structure he wanted,” Altman said on the stand. This sounds basically right. In later video testimony from Sam Teller’s deposition, we heard that Musk no longer invests in anything he doesn’t control. This also fits with Musk’s long-term fixation on making sure he can’t get booted from his own company the way he got booted from PayPal.

Musk also tried to recruit Altman to Tesla. We saw texts between Altman and Teller, in which Teller told Altman that Musk was committed to beefing up Tesla’s AI no matter what, and that he hoped that Altman, Brockman, and Ilya Sutskever would want to join eventually. “I read a vague, like, a lightweight threat in there, that he’s gonna do this inside of Tesla with or without you,” Altman said. But he felt that Tesla was primarily a car company — allowing it to acquire OpenAI would betray OpenAI’s mission.

Later, in Teller’s testimony, we saw texts Teller sent to Zilis at 12:40AM on February 4th, 2018: “I don’t love OpenAI continuing without Elon,” he wrote. “Would rather disable it by recruiting the leaders.”

When Musk stopped his quarterly donations, OpenAI was operating on a “shoestring” with an “extremely short runway of cash.” OpenAI did have other donors, none of whom have sued it or joined Musk’s suit. (One donor in the exhibit that wasn’t called out to the courtroom was Alameda Research, the firm owned by Sam Bankman-Fried, who is now in prison for fraud and money laundering.) Musk’s resignation from the board meant “people wondered if he was gonna try to take, uh, vengeance out on us or something.” On the other hand, Altman said Musk had “demotivated some of our key researchers” and done “huge damage for a long time to the culture of the organization.” So it sure seems like some people were relieved to be rid of him.

I’ve seen some fairly shoddy lawyering from Musk’s side throughout this trial

We saw a lot of evidence that throughout the time Altman was setting up OpenAI’s for-profit arm, he kept Musk apprised of what was going on, either directly or through Zilis or Teller. At no point did Musk object, and whatever he said publicly about the Microsoft investments, there was plenty of evidence that privately he’d been made aware.

On the cross-examination, we were treated to more than 10 minutes of Steven Molo telling Altman that various and assorted people had called him a liar: Sutskever, Mira Murati, Helen Toner, Tasha McCauley, Daniela and Dario Amodei (former OpenAI employees and founders of Anthropic), employees at Altman’s first startup Loopt, that recent New Yorker article, a book called The Optimist, etc. Molo did score some points by asking Altman about testimony in the trial, which Altman said he wasn’t paying close attention to. Molo acted as though this was inconceivable. Surely someone had informed Altman of what was said?

It was a little funny and also a little tiresome. Altman kept his cool, though, seeming hurt and confused by the focus on whether he was a liar. It was also the most successful part of the cross, which declined in focus precipitously afterward. I’ve seen some fairly shoddy lawyering from Musk’s side throughout this trial, and today was pretty bad. At one point, when Molo was trying to capitalize on Altman being both CEO and on the company’s board, Altman said — truthfully — that CEOs are almost always on the boards of the companies they run.

(At this point in my notes, I had written, “Boy, Molo is not very good at this.”)

The point of this trial isn’t to win — it’s to punish Altman, Brockman, and OpenAI

There was also an unconvincing argument about fundraising in nonprofits, specifically that if Stanford could raise $3 billion a year, OpenAI should have remained a nonprofit. Okay, let’s just think about that for a minute. Stanford has a donor network of thousands of graduates. It’s a school, which has very different capital requirements. It is not competing with any reputable for-profit companies. But leave that all aside and assume that some fundraising genius took over at the OpenAI Foundation: $3 billion is the initial two Microsoft investments combined, and not enough to scale OpenAI to where it is now. If compute is the main bottleneck on building AI models, then Molo’s line of argument suggests OpenAI never would have managed to be successful as a nonprofit alone. He’s making the defense’s case for them.

But the thing is, Molo doesn’t actually have to be good at this job, because the point of this trial isn’t to win — though I’m sure Musk wouldn’t mind a win. The point is to punish Altman, Brockman, and OpenAI. Musk has done that pretty thoroughly — reinforcing in the public’s mind that Altman is a liar and a snake. This morning, I read an exclusive in The Wall Street Journal that assorted Republican AGs and the House Oversight committee wanted to look into Sam Altman’s investments. References to the trial are peppered throughout the article.

So yes, Altman was convincing on the stand. He may even win the suit. But it sure seems like Musk’s vengeance has just begun.

Follow topics and authors from this story to see more like this in your personalized homepage feed and to receive email updates.
#Sam #Altman #winning #standAI,OpenAI

After two weeks of hearing from assorted witnesses that he was a lying snake, the…

 

The OpenAI blog post announcing Daybreak doesn’t mention the word “project” at all, perhaps to make readers slightly less apt to compare it to Anthropic’s Project Glasswing, but watch this: this sounds mighty similar to Anthropic’s Project Glasswing. Like Project Glasswing, it’s a program in which a frontier AI company seeks to partner with corporate and government entities to root out security vulnerabilities using OpenAI’s most advanced models in the hopes of “seeing risk earlier, acting sooner, and helping make software resilient by design.”

Glasswing rolled out last month alongside Anthropic’s announcement of its Claude Mythos Preview model, famously the model so capable—according to its creators at least—that it posed a danger to the world. As Anthropic’s system card for the model, explained:

Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available. Instead, we are using it as part of a defensive cybersecurity program with a limited set of partners.

In other words, because it’s “the most cyber-capable model” Anthropic had ever built, it needs to be locked away for now, unless you’re a VIP. Influential software developer Daniel Stenberg has called this an “amazingly successful marketing stunt for sure.”

Two days after that announcement, reports started materializing about a similar project at OpenAI. An anonymously sourced Axios story described it as “a product with advanced cybersecurity capabilities that it plans to release to a small set of partners.”

The Daybreak announcement is much more public-facing than that, and comes across as significantly less ominous and secretive than Project Glasswing. The top of the page has two buttons: “Request a vulnerability scan” and “Contact sales.” When you click, “Request a vulnerability scan” you get a brief and unchallenging form:

‘Daybreak’: OpenAI’s Answer to Anthropic’s Project Glasswing Has Arrived
                On Monday, OpenAI announced something called “Daybreak,” a project that CEO Sam Altman says is meant to “accelerate cyber defense and continuously secure software.“  OpenAI is launching Daybreak, our effort to accelerate cyber defense and continuously secure software. AI is already good and about to get super good at cybersecurity; we’d like to start working with as many companies as possible now to help them continuously secure themselves. — Sam Altman (@sama) May 11, 2026    The OpenAI blog post announcing Daybreak doesn’t mention the word “project” at all, perhaps to make readers slightly less apt to compare it to Anthropic’s Project Glasswing, but watch this: this sounds mighty similar to Anthropic’s Project Glasswing. Like Project Glasswing, it’s a program in which a frontier AI company seeks to partner with corporate and government entities to root out security vulnerabilities using OpenAI’s most advanced models in the hopes of “seeing risk earlier, acting sooner, and helping make software resilient by design.” Glasswing rolled out last month alongside Anthropic’s announcement of its Claude Mythos Preview model, famously the model so capable—according to its creators at least—that it posed a danger to the world. As Anthropic’s system card for the model, explained:

  Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available. Instead, we are using it as part of a defensive cybersecurity program with a limited set of partners.   In other words, because it’s “the most cyber-capable model” Anthropic had ever built, it needs to be locked away for now, unless you’re a VIP. Influential software developer Daniel Stenberg has called this an “amazingly successful marketing stunt for sure.” Two days after that announcement, reports started materializing about a similar project at OpenAI. An anonymously sourced Axios story described it as “a product with advanced cybersecurity capabilities that it plans to release to a small set of partners.”

 The Daybreak announcement is much more public-facing than that, and comes across as significantly less ominous and secretive than Project Glasswing. The top of the page has two buttons: “Request a vulnerability scan” and “Contact sales.” When you click, “Request a vulnerability scan” you get a brief and unchallenging form:

 © OpenAI Altman said in his X post that OpenAI would “like to start working with as many companies as possible now,” and in fairness, that’s how the effort comes across. Compared to way Project Glasswing rolled out, with frightened governments scurrying around behind the scenes like agitated ants, it’s refreshing. The announcement says Daybreak makes use of Codex Security, which was announced as a research preview back in March, to create a “threat model” of a given system that outlines its functions, who is trusted by the system, and what the vulnerabilities therefore are. With that as its context, it then digs into your actual codebase for the real world exploits. Then, in theory, it Daybreak patches them.      #Daybreak #OpenAIs #Answer #Anthropics #Project #Glasswing #ArrivedArtificial intelligence,Cybersecurity,OpenAI
© OpenAI

Altman said in his X post that OpenAI would “like to start working with as many companies as possible now,” and in fairness, that’s how the effort comes across. Compared to way Project Glasswing rolled out, with frightened governments scurrying around behind the scenes like agitated ants, it’s refreshing.

The announcement says Daybreak makes use of Codex Security, which was announced as a research preview back in March, to create a “threat model” of a given system that outlines its functions, who is trusted by the system, and what the vulnerabilities therefore are. With that as its context, it then digs into your actual codebase for the real world exploits.

Then, in theory, it Daybreak patches them.

#Daybreak #OpenAIs #Answer #Anthropics #Project #Glasswing #ArrivedArtificial intelligence,Cybersecurity,OpenAI"> ‘Daybreak’: OpenAI’s Answer to Anthropic’s Project Glasswing Has Arrived
                On Monday, OpenAI announced something called “Daybreak,” a project that CEO Sam Altman says is meant to “accelerate cyber defense and continuously secure software.“  OpenAI is launching Daybreak, our effort to accelerate cyber defense and continuously secure software. AI is already good and about to get super good at cybersecurity; we’d like to start working with as many companies as possible now to help them continuously secure themselves. — Sam Altman (@sama) May 11, 2026    The OpenAI blog post announcing Daybreak doesn’t mention the word “project” at all, perhaps to make readers slightly less apt to compare it to Anthropic’s Project Glasswing, but watch this: this sounds mighty similar to Anthropic’s Project Glasswing. Like Project Glasswing, it’s a program in which a frontier AI company seeks to partner with corporate and government entities to root out security vulnerabilities using OpenAI’s most advanced models in the hopes of “seeing risk earlier, acting sooner, and helping make software resilient by design.” Glasswing rolled out last month alongside Anthropic’s announcement of its Claude Mythos Preview model, famously the model so capable—according to its creators at least—that it posed a danger to the world. As Anthropic’s system card for the model, explained:

  Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available. Instead, we are using it as part of a defensive cybersecurity program with a limited set of partners.   In other words, because it’s “the most cyber-capable model” Anthropic had ever built, it needs to be locked away for now, unless you’re a VIP. Influential software developer Daniel Stenberg has called this an “amazingly successful marketing stunt for sure.” Two days after that announcement, reports started materializing about a similar project at OpenAI. An anonymously sourced Axios story described it as “a product with advanced cybersecurity capabilities that it plans to release to a small set of partners.”

 The Daybreak announcement is much more public-facing than that, and comes across as significantly less ominous and secretive than Project Glasswing. The top of the page has two buttons: “Request a vulnerability scan” and “Contact sales.” When you click, “Request a vulnerability scan” you get a brief and unchallenging form:

 © OpenAI Altman said in his X post that OpenAI would “like to start working with as many companies as possible now,” and in fairness, that’s how the effort comes across. Compared to way Project Glasswing rolled out, with frightened governments scurrying around behind the scenes like agitated ants, it’s refreshing. The announcement says Daybreak makes use of Codex Security, which was announced as a research preview back in March, to create a “threat model” of a given system that outlines its functions, who is trusted by the system, and what the vulnerabilities therefore are. With that as its context, it then digs into your actual codebase for the real world exploits. Then, in theory, it Daybreak patches them.      #Daybreak #OpenAIs #Answer #Anthropics #Project #Glasswing #ArrivedArtificial intelligence,Cybersecurity,OpenAI
Tech-news

 

The OpenAI blog post announcing Daybreak doesn’t mention the word “project” at all, perhaps to make readers slightly less apt to compare it to Anthropic’s Project Glasswing, but watch this: this sounds mighty similar to Anthropic’s Project Glasswing. Like Project Glasswing, it’s a program in which a frontier AI company seeks to partner with corporate and government entities to root out security vulnerabilities using OpenAI’s most advanced models in the hopes of “seeing risk earlier, acting sooner, and helping make software resilient by design.”

Glasswing rolled out last month alongside Anthropic’s announcement of its Claude Mythos Preview model, famously the model so capable—according to its creators at least—that it posed a danger to the world. As Anthropic’s system card for the model, explained:

Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available. Instead, we are using it as part of a defensive cybersecurity program with a limited set of partners.

In other words, because it’s “the most cyber-capable model” Anthropic had ever built, it needs to be locked away for now, unless you’re a VIP. Influential software developer Daniel Stenberg has called this an “amazingly successful marketing stunt for sure.”

Two days after that announcement, reports started materializing about a similar project at OpenAI. An anonymously sourced Axios story described it as “a product with advanced cybersecurity capabilities that it plans to release to a small set of partners.”

The Daybreak announcement is much more public-facing than that, and comes across as significantly less ominous and secretive than Project Glasswing. The top of the page has two buttons: “Request a vulnerability scan” and “Contact sales.” When you click, “Request a vulnerability scan” you get a brief and unchallenging form:

‘Daybreak’: OpenAI’s Answer to Anthropic’s Project Glasswing Has Arrived
                On Monday, OpenAI announced something called “Daybreak,” a project that CEO Sam Altman says is meant to “accelerate cyber defense and continuously secure software.“  OpenAI is launching Daybreak, our effort to accelerate cyber defense and continuously secure software. AI is already good and about to get super good at cybersecurity; we’d like to start working with as many companies as possible now to help them continuously secure themselves. — Sam Altman (@sama) May 11, 2026    The OpenAI blog post announcing Daybreak doesn’t mention the word “project” at all, perhaps to make readers slightly less apt to compare it to Anthropic’s Project Glasswing, but watch this: this sounds mighty similar to Anthropic’s Project Glasswing. Like Project Glasswing, it’s a program in which a frontier AI company seeks to partner with corporate and government entities to root out security vulnerabilities using OpenAI’s most advanced models in the hopes of “seeing risk earlier, acting sooner, and helping make software resilient by design.” Glasswing rolled out last month alongside Anthropic’s announcement of its Claude Mythos Preview model, famously the model so capable—according to its creators at least—that it posed a danger to the world. As Anthropic’s system card for the model, explained:

  Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available. Instead, we are using it as part of a defensive cybersecurity program with a limited set of partners.   In other words, because it’s “the most cyber-capable model” Anthropic had ever built, it needs to be locked away for now, unless you’re a VIP. Influential software developer Daniel Stenberg has called this an “amazingly successful marketing stunt for sure.” Two days after that announcement, reports started materializing about a similar project at OpenAI. An anonymously sourced Axios story described it as “a product with advanced cybersecurity capabilities that it plans to release to a small set of partners.”

 The Daybreak announcement is much more public-facing than that, and comes across as significantly less ominous and secretive than Project Glasswing. The top of the page has two buttons: “Request a vulnerability scan” and “Contact sales.” When you click, “Request a vulnerability scan” you get a brief and unchallenging form:

 © OpenAI Altman said in his X post that OpenAI would “like to start working with as many companies as possible now,” and in fairness, that’s how the effort comes across. Compared to way Project Glasswing rolled out, with frightened governments scurrying around behind the scenes like agitated ants, it’s refreshing. The announcement says Daybreak makes use of Codex Security, which was announced as a research preview back in March, to create a “threat model” of a given system that outlines its functions, who is trusted by the system, and what the vulnerabilities therefore are. With that as its context, it then digs into your actual codebase for the real world exploits. Then, in theory, it Daybreak patches them.      #Daybreak #OpenAIs #Answer #Anthropics #Project #Glasswing #ArrivedArtificial intelligence,Cybersecurity,OpenAI
© OpenAI

Altman said in his X post that OpenAI would “like to start working with as many companies as possible now,” and in fairness, that’s how the effort comes across. Compared to way Project Glasswing rolled out, with frightened governments scurrying around behind the scenes like agitated ants, it’s refreshing.

The announcement says Daybreak makes use of Codex Security, which was announced as a research preview back in March, to create a “threat model” of a given system that outlines its functions, who is trusted by the system, and what the vulnerabilities therefore are. With that as its context, it then digs into your actual codebase for the real world exploits.

Then, in theory, it Daybreak patches them.

#Daybreak #OpenAIs #Answer #Anthropics #Project #Glasswing #ArrivedArtificial intelligence,Cybersecurity,OpenAI">‘Daybreak’: OpenAI’s Answer to Anthropic’s Project Glasswing Has Arrived

On Monday, OpenAI announced something called “Daybreak,” a project that CEO Sam Altman says is meant to “accelerate cyber defense and continuously secure software.“

OpenAI is launching Daybreak, our effort to accelerate cyber defense and continuously secure software.

AI is already good and about to get super good at cybersecurity; we’d like to start working with as many companies as possible now to help them continuously secure themselves.

— Sam Altman (@sama) May 11, 2026

 

The OpenAI blog post announcing Daybreak doesn’t mention the word “project” at all, perhaps to make readers slightly less apt to compare it to Anthropic’s Project Glasswing, but watch this: this sounds mighty similar to Anthropic’s Project Glasswing. Like Project Glasswing, it’s a program in which a frontier AI company seeks to partner with corporate and government entities to root out security vulnerabilities using OpenAI’s most advanced models in the hopes of “seeing risk earlier, acting sooner, and helping make software resilient by design.”

Glasswing rolled out last month alongside Anthropic’s announcement of its Claude Mythos Preview model, famously the model so capable—according to its creators at least—that it posed a danger to the world. As Anthropic’s system card for the model, explained:

Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available. Instead, we are using it as part of a defensive cybersecurity program with a limited set of partners.

In other words, because it’s “the most cyber-capable model” Anthropic had ever built, it needs to be locked away for now, unless you’re a VIP. Influential software developer Daniel Stenberg has called this an “amazingly successful marketing stunt for sure.”

Two days after that announcement, reports started materializing about a similar project at OpenAI. An anonymously sourced Axios story described it as “a product with advanced cybersecurity capabilities that it plans to release to a small set of partners.”

The Daybreak announcement is much more public-facing than that, and comes across as significantly less ominous and secretive than Project Glasswing. The top of the page has two buttons: “Request a vulnerability scan” and “Contact sales.” When you click, “Request a vulnerability scan” you get a brief and unchallenging form:

‘Daybreak’: OpenAI’s Answer to Anthropic’s Project Glasswing Has Arrived
                On Monday, OpenAI announced something called “Daybreak,” a project that CEO Sam Altman says is meant to “accelerate cyber defense and continuously secure software.“  OpenAI is launching Daybreak, our effort to accelerate cyber defense and continuously secure software. AI is already good and about to get super good at cybersecurity; we’d like to start working with as many companies as possible now to help them continuously secure themselves. — Sam Altman (@sama) May 11, 2026    The OpenAI blog post announcing Daybreak doesn’t mention the word “project” at all, perhaps to make readers slightly less apt to compare it to Anthropic’s Project Glasswing, but watch this: this sounds mighty similar to Anthropic’s Project Glasswing. Like Project Glasswing, it’s a program in which a frontier AI company seeks to partner with corporate and government entities to root out security vulnerabilities using OpenAI’s most advanced models in the hopes of “seeing risk earlier, acting sooner, and helping make software resilient by design.” Glasswing rolled out last month alongside Anthropic’s announcement of its Claude Mythos Preview model, famously the model so capable—according to its creators at least—that it posed a danger to the world. As Anthropic’s system card for the model, explained:

  Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available. Instead, we are using it as part of a defensive cybersecurity program with a limited set of partners.   In other words, because it’s “the most cyber-capable model” Anthropic had ever built, it needs to be locked away for now, unless you’re a VIP. Influential software developer Daniel Stenberg has called this an “amazingly successful marketing stunt for sure.” Two days after that announcement, reports started materializing about a similar project at OpenAI. An anonymously sourced Axios story described it as “a product with advanced cybersecurity capabilities that it plans to release to a small set of partners.”

 The Daybreak announcement is much more public-facing than that, and comes across as significantly less ominous and secretive than Project Glasswing. The top of the page has two buttons: “Request a vulnerability scan” and “Contact sales.” When you click, “Request a vulnerability scan” you get a brief and unchallenging form:

 © OpenAI Altman said in his X post that OpenAI would “like to start working with as many companies as possible now,” and in fairness, that’s how the effort comes across. Compared to way Project Glasswing rolled out, with frightened governments scurrying around behind the scenes like agitated ants, it’s refreshing. The announcement says Daybreak makes use of Codex Security, which was announced as a research preview back in March, to create a “threat model” of a given system that outlines its functions, who is trusted by the system, and what the vulnerabilities therefore are. With that as its context, it then digs into your actual codebase for the real world exploits. Then, in theory, it Daybreak patches them.      #Daybreak #OpenAIs #Answer #Anthropics #Project #Glasswing #ArrivedArtificial intelligence,Cybersecurity,OpenAI
© OpenAI

Altman said in his X post that OpenAI would “like to start working with as many companies as possible now,” and in fairness, that’s how the effort comes across. Compared to way Project Glasswing rolled out, with frightened governments scurrying around behind the scenes like agitated ants, it’s refreshing.

The announcement says Daybreak makes use of Codex Security, which was announced as a research preview back in March, to create a “threat model” of a given system that outlines its functions, who is trusted by the system, and what the vulnerabilities therefore are. With that as its context, it then digs into your actual codebase for the real world exploits.

Then, in theory, it Daybreak patches them.

#Daybreak #OpenAIs #Answer #Anthropics #Project #Glasswing #ArrivedArtificial intelligence,Cybersecurity,OpenAI

On Monday, OpenAI announced something called “Daybreak,” a project that CEO Sam Altman says is…

Daybreak, an AI initiative focused on detecting and patching vulnerabilities before attackers find them. Daybreak uses the Codex Security AI agent that launched in March to create a threat model based on an organization’s code and focus on possible attack paths, validate likely vulnerabilities, and then automate the detection of the higher risk ones.

Its launch comes just over a month after rival Anthropic announced Claude Mythos, a security-focused AI model it claimed was too dangerous to publicly release and only shared privately as a part of its own initiative, dubbed Project Glasswing. Still, that didn’t stop at least a few unauthorized parties from getting access.

However, OpenAI has so far lacked a similar security product. Like Glasswing, Daybreak isn’t built on just one AI model — OpenAI says “Daybreak brings together the most capable OpenAI models, Codex, and our security partners.”

Daybreak also involves specialized cyber models, including GPT-5.5 with Trusted Access for Cyber and GPT-5.5-Cyber, which began rolling out last week. OpenAI also says it’s working with its “industry and government partners” while it prepares to “deploy increasingly more cyber-capable models.”

#OpenAI #released #answer #Claude #MythosAI,Anthropic,News,OpenAI,Security,Tech"> OpenAI just released its answer to Claude MythosOpenAI is launching Daybreak, an AI initiative focused on detecting and patching vulnerabilities before attackers find them. Daybreak uses the Codex Security AI agent that launched in March to create a threat model based on an organization’s code and focus on possible attack paths, validate likely vulnerabilities, and then automate the detection of the higher risk ones.Its launch comes just over a month after rival Anthropic announced Claude Mythos, a security-focused AI model it claimed was too dangerous to publicly release and only shared privately as a part of its own initiative, dubbed Project Glasswing. Still, that didn’t stop at least a few unauthorized parties from getting access.However, OpenAI has so far lacked a similar security product. Like Glasswing, Daybreak isn’t built on just one AI model — OpenAI says “Daybreak brings together the most capable OpenAI models, Codex, and our security partners.”Daybreak also involves specialized cyber models, including GPT-5.5 with Trusted Access for Cyber and GPT-5.5-Cyber, which began rolling out last week. OpenAI also says it’s working with its “industry and government partners” while it prepares to “deploy increasingly more cyber-capable models.”#OpenAI #released #answer #Claude #MythosAI,Anthropic,News,OpenAI,Security,Tech
Tech-news

Daybreak, an AI initiative focused on detecting and patching vulnerabilities before attackers find them. Daybreak uses the Codex Security AI agent that launched in March to create a threat model based on an organization’s code and focus on possible attack paths, validate likely vulnerabilities, and then automate the detection of the higher risk ones.

Its launch comes just over a month after rival Anthropic announced Claude Mythos, a security-focused AI model it claimed was too dangerous to publicly release and only shared privately as a part of its own initiative, dubbed Project Glasswing. Still, that didn’t stop at least a few unauthorized parties from getting access.

However, OpenAI has so far lacked a similar security product. Like Glasswing, Daybreak isn’t built on just one AI model — OpenAI says “Daybreak brings together the most capable OpenAI models, Codex, and our security partners.”

Daybreak also involves specialized cyber models, including GPT-5.5 with Trusted Access for Cyber and GPT-5.5-Cyber, which began rolling out last week. OpenAI also says it’s working with its “industry and government partners” while it prepares to “deploy increasingly more cyber-capable models.”

#OpenAI #released #answer #Claude #MythosAI,Anthropic,News,OpenAI,Security,Tech">OpenAI just released its answer to Claude Mythos

OpenAI is launching Daybreak, an AI initiative focused on detecting and patching vulnerabilities before attackers find them. Daybreak uses the Codex Security AI agent that launched in March to create a threat model based on an organization’s code and focus on possible attack paths, validate likely vulnerabilities, and then automate the detection of the higher risk ones.

Its launch comes just over a month after rival Anthropic announced Claude Mythos, a security-focused AI model it claimed was too dangerous to publicly release and only shared privately as a part of its own initiative, dubbed Project Glasswing. Still, that didn’t stop at least a few unauthorized parties from getting access.

However, OpenAI has so far lacked a similar security product. Like Glasswing, Daybreak isn’t built on just one AI model — OpenAI says “Daybreak brings together the most capable OpenAI models, Codex, and our security partners.”

Daybreak also involves specialized cyber models, including GPT-5.5 with Trusted Access for Cyber and GPT-5.5-Cyber, which began rolling out last week. OpenAI also says it’s working with its “industry and government partners” while it prepares to “deploy increasingly more cyber-capable models.”

#OpenAI #released #answer #Claude #MythosAI,Anthropic,News,OpenAI,Security,Tech

OpenAI is launching Daybreak, an AI initiative focused on detecting and patching vulnerabilities before attackers…

announced a new feature called Trusted Contact, designed to alert a trusted third party if mentions of self-harm are expressed within a conversation. The feature allows an adult ChatGPT user to designate another person as a trusted contact within their account, such as a friend or family member. In cases where a conversation may turn to self-harm, OpenAI will now encourage the user to reach out to that contact. It also sends an automated alert to the contact, encouraging them to check in with the user.

OpenAI has faced a wave of lawsuits from the families of people who have committed suicide after talking with its chatbot. In a number of cases, the families say ChatGPT encouraged their loved one to kill themselves—or even helped them plan it out.

OpenAI currently uses a combination of automation and human review to handle potentially harmful incidents. Certain conversational triggers alert the company’s system to suicidal ideations, which then relay the information to a human safety team. The company claims that every time it receives this kind of notification, the incident is reviewed by a human. “We strive to review these safety notifications in under one hour,” the company says.

If OpenAI’s internal team decides that the situation represents a serious safety risk, ChatGPT proceeds to send the trusted contact an alert—either by email, text message, or an in-app notification. The alert is designed to be brief and to encourage the contact to check in with the person in question. It does not include detailed information about what was being discussed, as a means of protecting the user’s privacy, the company says.

OpenAI introduces new ‘Trusted Contact’ safeguard for cases of possible self-harm | TechCrunch
On Thursday OpenAI announced a new feature called Trusted Contact, designed to alert a trusted third party if mentions of self-harm are expressed within a conversation. The feature allows an adult ChatGPT user to designate another person as a trusted contact within their account, such as a friend or family member. In cases where a conversation may turn to self-harm, OpenAI will now encourage the user to reach out to that contact. It also sends an automated alert to the contact, encouraging them to check in with the user.

OpenAI has faced a wave of lawsuits from the families of people who have committed suicide after talking with its chatbot. In a number of cases, the families say ChatGPT encouraged their loved one to kill themselves—or even helped them plan it out.







OpenAI currently uses a combination of automation and human review to handle potentially harmful incidents. Certain conversational triggers alert the company’s system to suicidal ideations, which then relay the information to a human safety team. The company claims that every time it receives this kind of notification, the incident is reviewed by a human. “We strive to review these safety notifications in under one hour,” the company says. 

If OpenAI’s internal team decides that the situation represents a serious safety risk, ChatGPT proceeds to send the trusted contact an alert—either by email, text message, or an in-app notification. The alert is designed to be brief and to encourage the contact to check in with the person in question. It does not include detailed information about what was being discussed, as a means of protecting the user’s privacy, the company says.  

Image Credits:OpenAI

The Trusted Contact feature follows the safeguards the company introduced last September that gave parents the power to have some oversight of their teens’ accounts, including receiving safety notifications designed to alert the parent if OpenAI’s system believes their child is facing a “serious safety risk.” For some time now, ChatGPT has also included automated alerts to seek professional health services, should a conversation trend toward the topic of self-harm.

Crucially, Trust Contact is optional and, even if the protection is activated on a particular account, any user can have multiple ChatGPT accounts. OpenAI’s parental controls are also optional, presenting a similar limitation.

“Trusted Contact is part of OpenAI’s broader effort to build AI systems that help people during difficult moments,” the company wrote in the announcement post. “We will continue to work with clinicians, researchers, and policymakers to improve how AI systems respond when people may be experiencing distress.”

	
		
		Techcrunch event
		
			
			
									San Francisco, CA
													|
													October 13-15, 2026
							
			
		
	

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#OpenAI #introduces #Trusted #Contact #safeguard #cases #selfharm #TechCrunchAI,ChatGPT,OpenAI
Image Credits:OpenAI

The Trusted Contact feature follows the safeguards the company introduced last September that gave parents the power to have some oversight of their teens’ accounts, including receiving safety notifications designed to alert the parent if OpenAI’s system believes their child is facing a “serious safety risk.” For some time now, ChatGPT has also included automated alerts to seek professional health services, should a conversation trend toward the topic of self-harm.

Crucially, Trust Contact is optional and, even if the protection is activated on a particular account, any user can have multiple ChatGPT accounts. OpenAI’s parental controls are also optional, presenting a similar limitation.

“Trusted Contact is part of OpenAI’s broader effort to build AI systems that help people during difficult moments,” the company wrote in the announcement post. “We will continue to work with clinicians, researchers, and policymakers to improve how AI systems respond when people may be experiencing distress.”

Techcrunch event

San Francisco, CA | October 13-15, 2026

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#OpenAI #introduces #Trusted #Contact #safeguard #cases #selfharm #TechCrunchAI,ChatGPT,OpenAI"> OpenAI introduces new ‘Trusted Contact’ safeguard for cases of possible self-harm | TechCrunch
On Thursday OpenAI announced a new feature called Trusted Contact, designed to alert a trusted third party if mentions of self-harm are expressed within a conversation. The feature allows an adult ChatGPT user to designate another person as a trusted contact within their account, such as a friend or family member. In cases where a conversation may turn to self-harm, OpenAI will now encourage the user to reach out to that contact. It also sends an automated alert to the contact, encouraging them to check in with the user.

OpenAI has faced a wave of lawsuits from the families of people who have committed suicide after talking with its chatbot. In a number of cases, the families say ChatGPT encouraged their loved one to kill themselves—or even helped them plan it out.







OpenAI currently uses a combination of automation and human review to handle potentially harmful incidents. Certain conversational triggers alert the company’s system to suicidal ideations, which then relay the information to a human safety team. The company claims that every time it receives this kind of notification, the incident is reviewed by a human. “We strive to review these safety notifications in under one hour,” the company says. 

If OpenAI’s internal team decides that the situation represents a serious safety risk, ChatGPT proceeds to send the trusted contact an alert—either by email, text message, or an in-app notification. The alert is designed to be brief and to encourage the contact to check in with the person in question. It does not include detailed information about what was being discussed, as a means of protecting the user’s privacy, the company says.  

Image Credits:OpenAI

The Trusted Contact feature follows the safeguards the company introduced last September that gave parents the power to have some oversight of their teens’ accounts, including receiving safety notifications designed to alert the parent if OpenAI’s system believes their child is facing a “serious safety risk.” For some time now, ChatGPT has also included automated alerts to seek professional health services, should a conversation trend toward the topic of self-harm.

Crucially, Trust Contact is optional and, even if the protection is activated on a particular account, any user can have multiple ChatGPT accounts. OpenAI’s parental controls are also optional, presenting a similar limitation.

“Trusted Contact is part of OpenAI’s broader effort to build AI systems that help people during difficult moments,” the company wrote in the announcement post. “We will continue to work with clinicians, researchers, and policymakers to improve how AI systems respond when people may be experiencing distress.”

	
		
		Techcrunch event
		
			
			
									San Francisco, CA
													|
													October 13-15, 2026
							
			
		
	

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#OpenAI #introduces #Trusted #Contact #safeguard #cases #selfharm #TechCrunchAI,ChatGPT,OpenAI
Tech-news

announced a new feature called Trusted Contact, designed to alert a trusted third party if mentions of self-harm are expressed within a conversation. The feature allows an adult ChatGPT user to designate another person as a trusted contact within their account, such as a friend or family member. In cases where a conversation may turn to self-harm, OpenAI will now encourage the user to reach out to that contact. It also sends an automated alert to the contact, encouraging them to check in with the user.

OpenAI has faced a wave of lawsuits from the families of people who have committed suicide after talking with its chatbot. In a number of cases, the families say ChatGPT encouraged their loved one to kill themselves—or even helped them plan it out.

OpenAI currently uses a combination of automation and human review to handle potentially harmful incidents. Certain conversational triggers alert the company’s system to suicidal ideations, which then relay the information to a human safety team. The company claims that every time it receives this kind of notification, the incident is reviewed by a human. “We strive to review these safety notifications in under one hour,” the company says.

If OpenAI’s internal team decides that the situation represents a serious safety risk, ChatGPT proceeds to send the trusted contact an alert—either by email, text message, or an in-app notification. The alert is designed to be brief and to encourage the contact to check in with the person in question. It does not include detailed information about what was being discussed, as a means of protecting the user’s privacy, the company says.

OpenAI introduces new ‘Trusted Contact’ safeguard for cases of possible self-harm | TechCrunch
On Thursday OpenAI announced a new feature called Trusted Contact, designed to alert a trusted third party if mentions of self-harm are expressed within a conversation. The feature allows an adult ChatGPT user to designate another person as a trusted contact within their account, such as a friend or family member. In cases where a conversation may turn to self-harm, OpenAI will now encourage the user to reach out to that contact. It also sends an automated alert to the contact, encouraging them to check in with the user.

OpenAI has faced a wave of lawsuits from the families of people who have committed suicide after talking with its chatbot. In a number of cases, the families say ChatGPT encouraged their loved one to kill themselves—or even helped them plan it out.







OpenAI currently uses a combination of automation and human review to handle potentially harmful incidents. Certain conversational triggers alert the company’s system to suicidal ideations, which then relay the information to a human safety team. The company claims that every time it receives this kind of notification, the incident is reviewed by a human. “We strive to review these safety notifications in under one hour,” the company says. 

If OpenAI’s internal team decides that the situation represents a serious safety risk, ChatGPT proceeds to send the trusted contact an alert—either by email, text message, or an in-app notification. The alert is designed to be brief and to encourage the contact to check in with the person in question. It does not include detailed information about what was being discussed, as a means of protecting the user’s privacy, the company says.  

Image Credits:OpenAI

The Trusted Contact feature follows the safeguards the company introduced last September that gave parents the power to have some oversight of their teens’ accounts, including receiving safety notifications designed to alert the parent if OpenAI’s system believes their child is facing a “serious safety risk.” For some time now, ChatGPT has also included automated alerts to seek professional health services, should a conversation trend toward the topic of self-harm.

Crucially, Trust Contact is optional and, even if the protection is activated on a particular account, any user can have multiple ChatGPT accounts. OpenAI’s parental controls are also optional, presenting a similar limitation.

“Trusted Contact is part of OpenAI’s broader effort to build AI systems that help people during difficult moments,” the company wrote in the announcement post. “We will continue to work with clinicians, researchers, and policymakers to improve how AI systems respond when people may be experiencing distress.”

	
		
		Techcrunch event
		
			
			
									San Francisco, CA
													|
													October 13-15, 2026
							
			
		
	

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#OpenAI #introduces #Trusted #Contact #safeguard #cases #selfharm #TechCrunchAI,ChatGPT,OpenAI
Image Credits:OpenAI

The Trusted Contact feature follows the safeguards the company introduced last September that gave parents the power to have some oversight of their teens’ accounts, including receiving safety notifications designed to alert the parent if OpenAI’s system believes their child is facing a “serious safety risk.” For some time now, ChatGPT has also included automated alerts to seek professional health services, should a conversation trend toward the topic of self-harm.

Crucially, Trust Contact is optional and, even if the protection is activated on a particular account, any user can have multiple ChatGPT accounts. OpenAI’s parental controls are also optional, presenting a similar limitation.

“Trusted Contact is part of OpenAI’s broader effort to build AI systems that help people during difficult moments,” the company wrote in the announcement post. “We will continue to work with clinicians, researchers, and policymakers to improve how AI systems respond when people may be experiencing distress.”

Techcrunch event

San Francisco, CA | October 13-15, 2026

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#OpenAI #introduces #Trusted #Contact #safeguard #cases #selfharm #TechCrunchAI,ChatGPT,OpenAI">OpenAI introduces new ‘Trusted Contact’ safeguard for cases of possible self-harm | TechCrunch

On Thursday OpenAI announced a new feature called Trusted Contact, designed to alert a trusted third party if mentions of self-harm are expressed within a conversation. The feature allows an adult ChatGPT user to designate another person as a trusted contact within their account, such as a friend or family member. In cases where a conversation may turn to self-harm, OpenAI will now encourage the user to reach out to that contact. It also sends an automated alert to the contact, encouraging them to check in with the user.

OpenAI has faced a wave of lawsuits from the families of people who have committed suicide after talking with its chatbot. In a number of cases, the families say ChatGPT encouraged their loved one to kill themselves—or even helped them plan it out.

OpenAI currently uses a combination of automation and human review to handle potentially harmful incidents. Certain conversational triggers alert the company’s system to suicidal ideations, which then relay the information to a human safety team. The company claims that every time it receives this kind of notification, the incident is reviewed by a human. “We strive to review these safety notifications in under one hour,” the company says.

If OpenAI’s internal team decides that the situation represents a serious safety risk, ChatGPT proceeds to send the trusted contact an alert—either by email, text message, or an in-app notification. The alert is designed to be brief and to encourage the contact to check in with the person in question. It does not include detailed information about what was being discussed, as a means of protecting the user’s privacy, the company says.

OpenAI introduces new ‘Trusted Contact’ safeguard for cases of possible self-harm | TechCrunch
On Thursday OpenAI announced a new feature called Trusted Contact, designed to alert a trusted third party if mentions of self-harm are expressed within a conversation. The feature allows an adult ChatGPT user to designate another person as a trusted contact within their account, such as a friend or family member. In cases where a conversation may turn to self-harm, OpenAI will now encourage the user to reach out to that contact. It also sends an automated alert to the contact, encouraging them to check in with the user.

OpenAI has faced a wave of lawsuits from the families of people who have committed suicide after talking with its chatbot. In a number of cases, the families say ChatGPT encouraged their loved one to kill themselves—or even helped them plan it out.







OpenAI currently uses a combination of automation and human review to handle potentially harmful incidents. Certain conversational triggers alert the company’s system to suicidal ideations, which then relay the information to a human safety team. The company claims that every time it receives this kind of notification, the incident is reviewed by a human. “We strive to review these safety notifications in under one hour,” the company says. 

If OpenAI’s internal team decides that the situation represents a serious safety risk, ChatGPT proceeds to send the trusted contact an alert—either by email, text message, or an in-app notification. The alert is designed to be brief and to encourage the contact to check in with the person in question. It does not include detailed information about what was being discussed, as a means of protecting the user’s privacy, the company says.  

Image Credits:OpenAI

The Trusted Contact feature follows the safeguards the company introduced last September that gave parents the power to have some oversight of their teens’ accounts, including receiving safety notifications designed to alert the parent if OpenAI’s system believes their child is facing a “serious safety risk.” For some time now, ChatGPT has also included automated alerts to seek professional health services, should a conversation trend toward the topic of self-harm.

Crucially, Trust Contact is optional and, even if the protection is activated on a particular account, any user can have multiple ChatGPT accounts. OpenAI’s parental controls are also optional, presenting a similar limitation.

“Trusted Contact is part of OpenAI’s broader effort to build AI systems that help people during difficult moments,” the company wrote in the announcement post. “We will continue to work with clinicians, researchers, and policymakers to improve how AI systems respond when people may be experiencing distress.”

	
		
		Techcrunch event
		
			
			
									San Francisco, CA
													|
													October 13-15, 2026
							
			
		
	

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#OpenAI #introduces #Trusted #Contact #safeguard #cases #selfharm #TechCrunchAI,ChatGPT,OpenAI
Image Credits:OpenAI

The Trusted Contact feature follows the safeguards the company introduced last September that gave parents the power to have some oversight of their teens’ accounts, including receiving safety notifications designed to alert the parent if OpenAI’s system believes their child is facing a “serious safety risk.” For some time now, ChatGPT has also included automated alerts to seek professional health services, should a conversation trend toward the topic of self-harm.

Crucially, Trust Contact is optional and, even if the protection is activated on a particular account, any user can have multiple ChatGPT accounts. OpenAI’s parental controls are also optional, presenting a similar limitation.

“Trusted Contact is part of OpenAI’s broader effort to build AI systems that help people during difficult moments,” the company wrote in the announcement post. “We will continue to work with clinicians, researchers, and policymakers to improve how AI systems respond when people may be experiencing distress.”

Techcrunch event

San Francisco, CA | October 13-15, 2026

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#OpenAI #introduces #Trusted #Contact #safeguard #cases #selfharm #TechCrunchAI,ChatGPT,OpenAI

On Thursday OpenAI announced a new feature called Trusted Contact, designed to alert a trusted…

recent New Yorker feature about Altman. Now it’s court testimony.

For a few weird days in 2023, Murati was an interim CEO of OpenAI after Altman was briefly fired (And then OpenAI very briefly picked another CEO, Emmett Shear). Reports from this chaotic time paint a picture of a working relationship between Altman and Murati that came under strain when Murati lost Altman’s trust. Behind-the-scenes accounts say she sent memos to the company’s board of directors and Altman himself, questioning Altman’s managerial abilities, and that his termination soon followed.

On Wednesday, a video deposition from Murati was shown to the court during the Musk v. Altman court proceedings, in which she testified to the truth of this story. A new model was being prepared for release—which the New Yorker says was GPT-4 Turbo—and in her testimony, as described by the Verge, she said Altman told her OpenAI’s legal department, headed at the time by Jason Kwon, said it wasn’t necessary for the OpenAI safety board to review the model.

The person asking questions in the deposition asked, “As you understand it, was Mr. Altman telling the truth when he made that statement to you?”

To which Murati said, “No.” She later explained in her testimony, according to the Verge, “I confirmed that what Jason was saying and what Sam was saying were not the same thing.” She characterized this as a “misalignment” between Altman and Kwon. Kwon is now OpenAI’s chief strategy officer.

According to Reuters, Murati said in her testimony, “My concern was about Sam saying one thing to one person and completely the opposite to another person.” She also reportedly testified that Altman had been “creating chaos.” She described OpenAI at this time as “at catastrophic risk of falling apart,” and said she was “concerned about the company completely blowing up,” according to Reuters.

According to the New Yorker, Murati’s memos to Altman and the board came soon after this interaction, and “Soon afterward, the board made its decision to fire Altman.” Murati was interim CEO for a handful of days, then Shear stepped in for a few days, and then Altman was reinstated, a move Murati publicly supported.

According to Forbes, Murati testified Wednesday that after his return to OpenAI, Altman continued with behaviors that had worried her, including delays around important decisions, and giving inconsistent messages to different coworkers, which she reportedly said created a “very difficult and chaotic environment.”

About ten months after Sam Altman was reinstated as CEO, Murati left, and a few month later, founded her own AI company.

#ExOpenAI #CTO #Mira #Murati #Testifies #Sam #Altman #Allegedly #LyingElon Musk,OpenAI,Sam Altman,Trials"> Ex-OpenAI CTO Mira Murati Testifies About Sam Altman Allegedly Lying to Her
                OpenAI’s former CTO Mira Murati just testified under oath that CEO Sam Altman didn’t tell the truth to her, and that his habits interfered with her ability to do her job. The allegation in question, that Altman lied about safety practices, was already public, having featured heavily in a recent New Yorker feature about Altman. Now it’s court testimony. For a few weird days in 2023, Murati was an interim CEO of OpenAI after Altman was briefly fired (And then OpenAI very briefly picked another CEO, Emmett Shear). Reports from this chaotic time paint a picture of a working relationship between Altman and Murati that came under strain when Murati lost Altman’s trust. Behind-the-scenes accounts say she sent memos to the company’s board of directors and Altman himself, questioning Altman’s managerial abilities, and that his termination soon followed.

 On Wednesday, a video deposition from Murati was shown to the court during the Musk v. Altman court proceedings, in which she testified to the truth of this story. A new model was being prepared for release—which the New Yorker says was GPT-4 Turbo—and in her testimony, as described by the Verge, she said Altman told her OpenAI’s legal department, headed at the time by Jason Kwon, said it wasn’t necessary for the OpenAI safety board to review the model. The person asking questions in the deposition asked, “As you understand it, was Mr. Altman telling the truth when he made that statement to you?”

 To which Murati said, “No.” She later explained in her testimony, according to the Verge, “I confirmed that what Jason was saying and what Sam was saying were not the same thing.” She characterized this as a “misalignment” between Altman and Kwon. Kwon is now OpenAI’s chief strategy officer.

 According to Reuters, Murati said in her testimony, “My concern was about Sam saying one thing to one person and completely the opposite to another person.” She also reportedly testified that Altman had been “creating chaos.” She described OpenAI at this time as “at catastrophic risk of falling apart,” and said she was “concerned about the company completely blowing up,” according to Reuters. According to the New Yorker, Murati’s memos to Altman and the board came soon after this interaction, and “Soon afterward, the board made its decision to fire Altman.” Murati was interim CEO for a handful of days, then Shear stepped in for a few days, and then Altman was reinstated, a move Murati publicly supported.

 According to Forbes, Murati testified Wednesday that after his return to OpenAI, Altman continued with behaviors that had worried her, including delays around important decisions, and giving inconsistent messages to different coworkers, which she reportedly said created a “very difficult and chaotic environment.” About ten months after Sam Altman was reinstated as CEO, Murati left, and a few month later, founded her own AI company.      #ExOpenAI #CTO #Mira #Murati #Testifies #Sam #Altman #Allegedly #LyingElon Musk,OpenAI,Sam Altman,Trials
Tech-news

recent New Yorker feature about Altman. Now it’s court testimony.

For a few weird days in 2023, Murati was an interim CEO of OpenAI after Altman was briefly fired (And then OpenAI very briefly picked another CEO, Emmett Shear). Reports from this chaotic time paint a picture of a working relationship between Altman and Murati that came under strain when Murati lost Altman’s trust. Behind-the-scenes accounts say she sent memos to the company’s board of directors and Altman himself, questioning Altman’s managerial abilities, and that his termination soon followed.

On Wednesday, a video deposition from Murati was shown to the court during the Musk v. Altman court proceedings, in which she testified to the truth of this story. A new model was being prepared for release—which the New Yorker says was GPT-4 Turbo—and in her testimony, as described by the Verge, she said Altman told her OpenAI’s legal department, headed at the time by Jason Kwon, said it wasn’t necessary for the OpenAI safety board to review the model.

The person asking questions in the deposition asked, “As you understand it, was Mr. Altman telling the truth when he made that statement to you?”

To which Murati said, “No.” She later explained in her testimony, according to the Verge, “I confirmed that what Jason was saying and what Sam was saying were not the same thing.” She characterized this as a “misalignment” between Altman and Kwon. Kwon is now OpenAI’s chief strategy officer.

According to Reuters, Murati said in her testimony, “My concern was about Sam saying one thing to one person and completely the opposite to another person.” She also reportedly testified that Altman had been “creating chaos.” She described OpenAI at this time as “at catastrophic risk of falling apart,” and said she was “concerned about the company completely blowing up,” according to Reuters.

According to the New Yorker, Murati’s memos to Altman and the board came soon after this interaction, and “Soon afterward, the board made its decision to fire Altman.” Murati was interim CEO for a handful of days, then Shear stepped in for a few days, and then Altman was reinstated, a move Murati publicly supported.

According to Forbes, Murati testified Wednesday that after his return to OpenAI, Altman continued with behaviors that had worried her, including delays around important decisions, and giving inconsistent messages to different coworkers, which she reportedly said created a “very difficult and chaotic environment.”

About ten months after Sam Altman was reinstated as CEO, Murati left, and a few month later, founded her own AI company.

#ExOpenAI #CTO #Mira #Murati #Testifies #Sam #Altman #Allegedly #LyingElon Musk,OpenAI,Sam Altman,Trials">Ex-OpenAI CTO Mira Murati Testifies About Sam Altman Allegedly Lying to HerEx-OpenAI CTO Mira Murati Testifies About Sam Altman Allegedly Lying to Her
                OpenAI’s former CTO Mira Murati just testified under oath that CEO Sam Altman didn’t tell the truth to her, and that his habits interfered with her ability to do her job. The allegation in question, that Altman lied about safety practices, was already public, having featured heavily in a recent New Yorker feature about Altman. Now it’s court testimony. For a few weird days in 2023, Murati was an interim CEO of OpenAI after Altman was briefly fired (And then OpenAI very briefly picked another CEO, Emmett Shear). Reports from this chaotic time paint a picture of a working relationship between Altman and Murati that came under strain when Murati lost Altman’s trust. Behind-the-scenes accounts say she sent memos to the company’s board of directors and Altman himself, questioning Altman’s managerial abilities, and that his termination soon followed.

 On Wednesday, a video deposition from Murati was shown to the court during the Musk v. Altman court proceedings, in which she testified to the truth of this story. A new model was being prepared for release—which the New Yorker says was GPT-4 Turbo—and in her testimony, as described by the Verge, she said Altman told her OpenAI’s legal department, headed at the time by Jason Kwon, said it wasn’t necessary for the OpenAI safety board to review the model. The person asking questions in the deposition asked, “As you understand it, was Mr. Altman telling the truth when he made that statement to you?”

 To which Murati said, “No.” She later explained in her testimony, according to the Verge, “I confirmed that what Jason was saying and what Sam was saying were not the same thing.” She characterized this as a “misalignment” between Altman and Kwon. Kwon is now OpenAI’s chief strategy officer.

 According to Reuters, Murati said in her testimony, “My concern was about Sam saying one thing to one person and completely the opposite to another person.” She also reportedly testified that Altman had been “creating chaos.” She described OpenAI at this time as “at catastrophic risk of falling apart,” and said she was “concerned about the company completely blowing up,” according to Reuters. According to the New Yorker, Murati’s memos to Altman and the board came soon after this interaction, and “Soon afterward, the board made its decision to fire Altman.” Murati was interim CEO for a handful of days, then Shear stepped in for a few days, and then Altman was reinstated, a move Murati publicly supported.

 According to Forbes, Murati testified Wednesday that after his return to OpenAI, Altman continued with behaviors that had worried her, including delays around important decisions, and giving inconsistent messages to different coworkers, which she reportedly said created a “very difficult and chaotic environment.” About ten months after Sam Altman was reinstated as CEO, Murati left, and a few month later, founded her own AI company.      #ExOpenAI #CTO #Mira #Murati #Testifies #Sam #Altman #Allegedly #LyingElon Musk,OpenAI,Sam Altman,Trials

OpenAI’s former CTO Mira Murati just testified under oath that CEO Sam Altman didn’t tell the truth to her, and that his habits interfered with her ability to do her job. The allegation in question, that Altman lied about safety practices, was already public, having featured heavily in a recent New Yorker feature about Altman. Now it’s court testimony.

For a few weird days in 2023, Murati was an interim CEO of OpenAI after Altman was briefly fired (And then OpenAI very briefly picked another CEO, Emmett Shear). Reports from this chaotic time paint a picture of a working relationship between Altman and Murati that came under strain when Murati lost Altman’s trust. Behind-the-scenes accounts say she sent memos to the company’s board of directors and Altman himself, questioning Altman’s managerial abilities, and that his termination soon followed.

On Wednesday, a video deposition from Murati was shown to the court during the Musk v. Altman court proceedings, in which she testified to the truth of this story. A new model was being prepared for release—which the New Yorker says was GPT-4 Turbo—and in her testimony, as described by the Verge, she said Altman told her OpenAI’s legal department, headed at the time by Jason Kwon, said it wasn’t necessary for the OpenAI safety board to review the model.

The person asking questions in the deposition asked, “As you understand it, was Mr. Altman telling the truth when he made that statement to you?”

To which Murati said, “No.” She later explained in her testimony, according to the Verge, “I confirmed that what Jason was saying and what Sam was saying were not the same thing.” She characterized this as a “misalignment” between Altman and Kwon. Kwon is now OpenAI’s chief strategy officer.

According to Reuters, Murati said in her testimony, “My concern was about Sam saying one thing to one person and completely the opposite to another person.” She also reportedly testified that Altman had been “creating chaos.” She described OpenAI at this time as “at catastrophic risk of falling apart,” and said she was “concerned about the company completely blowing up,” according to Reuters.

According to the New Yorker, Murati’s memos to Altman and the board came soon after this interaction, and “Soon afterward, the board made its decision to fire Altman.” Murati was interim CEO for a handful of days, then Shear stepped in for a few days, and then Altman was reinstated, a move Murati publicly supported.

According to Forbes, Murati testified Wednesday that after his return to OpenAI, Altman continued with behaviors that had worried her, including delays around important decisions, and giving inconsistent messages to different coworkers, which she reportedly said created a “very difficult and chaotic environment.”

About ten months after Sam Altman was reinstated as CEO, Murati left, and a few month later, founded her own AI company.

#ExOpenAI #CTO #Mira #Murati #Testifies #Sam #Altman #Allegedly #LyingElon Musk,OpenAI,Sam Altman,Trials

OpenAI’s former CTO Mira Murati just testified under oath that CEO Sam Altman didn’t tell…

published this week in Science and comes from a research team led by physicians and computer scientists at Harvard Medical School and Beth Israel Deaconess Medical Center. The researchers said they conducted a variety of experiments to measure how OpenAI’s models compared to human physicians.

In one experiment, researchers focused on 76 patients who came into the Beth Israel emergency room, comparing the diagnoses offered by two internal medicine attending physicians to those generated by OpenAI’s o1 and 4o models. These diagnoses were assessed by two other attending physicians, who did not know which ones came from humans and which came from AI.

“At each diagnostic touchpoint, o1 either performed nominally better than or on par with the two attending physicians and 4o,” the study said, adding that the differences “were especially pronounced at the first diagnostic touchpoint (initial ER triage), where there is the least information available about the patient and the most urgency to make the correct decision.”

In Harvard Medical School’s press release about the study, the researchers emphasized that they did not “pre-process the data at all” — the AI models were presented with the same information that was available in the electronic medical records at the time of each diagnosis. 

With that information, the o1 model managed to offer “the exact or very close diagnosis” in 67% of triage cases, compared to one physician who had the exact or close diagnosis 55% of the time, and to the other who hit the mark 50% of the time.

“We tested the AI model against virtually every benchmark, and it eclipsed both prior models and our physician baselines,” said Arjun Manrai, who heads an AI lab at Harvard Medical School and is one of the study’s lead authors, in the press release.

Techcrunch event

San Francisco, CA | October 13-15, 2026

To be clear, the study didn’t claim that AI is ready to make real life-or-death decisions in the emergency room. Instead, it said the findings show an “urgent need for prospective trials to evaluate these technologies in real-world patient care settings.”

The researchers also noted that they only studied how models performed when provided with text-based information, and that “existing studies suggest that current foundation models are more limited in reasoning over nontext inputs.”

Adam Rodman, a Beth Israel doctor who’s also one of the study’s lead authors, warned the Guardian that there’s “no formal framework right now for accountability” around AI diagnoses, and that patients still “want humans to guide them through life or death decisions [and] to guide them through challenging treatment decisions.”

In a post about the study, Kristen Panthagani, an emergency physician, said this is an “an interesting AI study that has led to some very overhyped headlines,” especially since it was comparing AI diagnoses to those from internal medicine physicians, not ER physicians.

“If we’re going to compare AI tools to physicians’ clinical ability, we should start by comparing to physicians who actually practice that specialty,” Panthagani said. “I would not be surprised if a LLM could beat a dermatologist at an neurosurgery board exam, [but] that’s not a particularly helpful thing to know.”

She also argued, “As an ER doctor seeing a patient for a first time, my primary goal is not to guess your ultimate diagnosis. My primary goal is to determine if you have a condition that could kill you.”

This post and headline have been updated to reflect the fact that the diagnoses in the study came from internal medicine attending physicians, and to include commentary from Kristen Panthagani.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#Harvard #study #offered #accurate #emergency #room #diagnoses #human #doctors #TechCrunchbeth israel,harvard medical school,OpenAI"> In Harvard study, AI offered more accurate emergency room diagnoses than two human doctors | TechCrunch
A new study examines how large language models perform in a variety of medical contexts, including real emergency room cases — where at least one model seemed to be more accurate than human doctors.

The study was published this week in Science and comes from a research team led by physicians and computer scientists at Harvard Medical School and Beth Israel Deaconess Medical Center. The researchers said they conducted a variety of experiments to measure how OpenAI’s models compared to human physicians.







In one experiment, researchers focused on 76 patients who came into the Beth Israel emergency room, comparing the diagnoses offered by two internal medicine attending physicians to those generated by OpenAI’s o1 and 4o models. These diagnoses were assessed by two other attending physicians, who did not know which ones came from humans and which came from AI.

“At each diagnostic touchpoint, o1 either performed nominally better than or on par with the two attending physicians and 4o,” the study said, adding that the differences “were especially pronounced at the first diagnostic touchpoint (initial ER triage), where there is the least information available about the patient and the most urgency to make the correct decision.”

In Harvard Medical School’s press release about the study, the researchers emphasized that they did not “pre-process the data at all” — the AI models were presented with the same information that was available in the electronic medical records at the time of each diagnosis. 

With that information, the o1 model managed to offer “the exact or very close diagnosis” in 67% of triage cases, compared to one physician who had the exact or close diagnosis 55% of the time, and to the other who hit the mark 50% of the time.

“We tested the AI model against virtually every benchmark, and it eclipsed both prior models and our physician baselines,” said Arjun Manrai, who heads an AI lab at Harvard Medical School and is one of the study’s lead authors, in the press release.

	
		
		Techcrunch event
		
			
			
									San Francisco, CA
													|
													October 13-15, 2026
							
			
		
	


To be clear, the study didn’t claim that AI is ready to make real life-or-death decisions in the emergency room. Instead, it said the findings show an “urgent need for prospective trials to evaluate these technologies in real-world patient care settings.”

The researchers also noted that they only studied how models performed when provided with text-based information, and that “existing studies suggest that current foundation models are more limited in reasoning over nontext inputs.”

Adam Rodman, a Beth Israel doctor who’s also one of the study’s lead authors, warned the Guardian that there’s “no formal framework right now for accountability” around AI diagnoses, and that patients still “want humans to guide them through life or death decisions [and] to guide them through challenging treatment decisions.”







In a post about the study, Kristen Panthagani, an emergency physician, said this is an “an interesting AI study that has led to some very overhyped headlines,” especially since it was comparing AI diagnoses to those from internal medicine physicians, not ER physicians.

“If we’re going to compare AI tools to physicians’ clinical ability, we should start by comparing to physicians who actually practice that specialty,” Panthagani said. “I would not be surprised if a LLM could beat a dermatologist at an neurosurgery board exam, [but] that’s not a particularly helpful thing to know.”

She also argued, “As an ER doctor seeing a patient for a first time, my primary goal is not to guess your ultimate diagnosis. My primary goal is to determine if you have a condition that could kill you.”

This post and headline have been updated to reflect the fact that the diagnoses in the study came from internal medicine attending physicians, and to include commentary from Kristen Panthagani.
When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Harvard #study #offered #accurate #emergency #room #diagnoses #human #doctors #TechCrunchbeth israel,harvard medical school,OpenAI
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published this week in Science and comes from a research team led by physicians and computer scientists at Harvard Medical School and Beth Israel Deaconess Medical Center. The researchers said they conducted a variety of experiments to measure how OpenAI’s models compared to human physicians.

In one experiment, researchers focused on 76 patients who came into the Beth Israel emergency room, comparing the diagnoses offered by two internal medicine attending physicians to those generated by OpenAI’s o1 and 4o models. These diagnoses were assessed by two other attending physicians, who did not know which ones came from humans and which came from AI.

“At each diagnostic touchpoint, o1 either performed nominally better than or on par with the two attending physicians and 4o,” the study said, adding that the differences “were especially pronounced at the first diagnostic touchpoint (initial ER triage), where there is the least information available about the patient and the most urgency to make the correct decision.”

In Harvard Medical School’s press release about the study, the researchers emphasized that they did not “pre-process the data at all” — the AI models were presented with the same information that was available in the electronic medical records at the time of each diagnosis. 

With that information, the o1 model managed to offer “the exact or very close diagnosis” in 67% of triage cases, compared to one physician who had the exact or close diagnosis 55% of the time, and to the other who hit the mark 50% of the time.

“We tested the AI model against virtually every benchmark, and it eclipsed both prior models and our physician baselines,” said Arjun Manrai, who heads an AI lab at Harvard Medical School and is one of the study’s lead authors, in the press release.

Techcrunch event

San Francisco, CA | October 13-15, 2026

To be clear, the study didn’t claim that AI is ready to make real life-or-death decisions in the emergency room. Instead, it said the findings show an “urgent need for prospective trials to evaluate these technologies in real-world patient care settings.”

The researchers also noted that they only studied how models performed when provided with text-based information, and that “existing studies suggest that current foundation models are more limited in reasoning over nontext inputs.”

Adam Rodman, a Beth Israel doctor who’s also one of the study’s lead authors, warned the Guardian that there’s “no formal framework right now for accountability” around AI diagnoses, and that patients still “want humans to guide them through life or death decisions [and] to guide them through challenging treatment decisions.”

In a post about the study, Kristen Panthagani, an emergency physician, said this is an “an interesting AI study that has led to some very overhyped headlines,” especially since it was comparing AI diagnoses to those from internal medicine physicians, not ER physicians.

“If we’re going to compare AI tools to physicians’ clinical ability, we should start by comparing to physicians who actually practice that specialty,” Panthagani said. “I would not be surprised if a LLM could beat a dermatologist at an neurosurgery board exam, [but] that’s not a particularly helpful thing to know.”

She also argued, “As an ER doctor seeing a patient for a first time, my primary goal is not to guess your ultimate diagnosis. My primary goal is to determine if you have a condition that could kill you.”

This post and headline have been updated to reflect the fact that the diagnoses in the study came from internal medicine attending physicians, and to include commentary from Kristen Panthagani.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#Harvard #study #offered #accurate #emergency #room #diagnoses #human #doctors #TechCrunchbeth israel,harvard medical school,OpenAI">In Harvard study, AI offered more accurate emergency room diagnoses than two human doctors | TechCrunch

A new study examines how large language models perform in a variety of medical contexts, including real emergency room cases — where at least one model seemed to be more accurate than human doctors.

The study was published this week in Science and comes from a research team led by physicians and computer scientists at Harvard Medical School and Beth Israel Deaconess Medical Center. The researchers said they conducted a variety of experiments to measure how OpenAI’s models compared to human physicians.

In one experiment, researchers focused on 76 patients who came into the Beth Israel emergency room, comparing the diagnoses offered by two internal medicine attending physicians to those generated by OpenAI’s o1 and 4o models. These diagnoses were assessed by two other attending physicians, who did not know which ones came from humans and which came from AI.

“At each diagnostic touchpoint, o1 either performed nominally better than or on par with the two attending physicians and 4o,” the study said, adding that the differences “were especially pronounced at the first diagnostic touchpoint (initial ER triage), where there is the least information available about the patient and the most urgency to make the correct decision.”

In Harvard Medical School’s press release about the study, the researchers emphasized that they did not “pre-process the data at all” — the AI models were presented with the same information that was available in the electronic medical records at the time of each diagnosis. 

With that information, the o1 model managed to offer “the exact or very close diagnosis” in 67% of triage cases, compared to one physician who had the exact or close diagnosis 55% of the time, and to the other who hit the mark 50% of the time.

“We tested the AI model against virtually every benchmark, and it eclipsed both prior models and our physician baselines,” said Arjun Manrai, who heads an AI lab at Harvard Medical School and is one of the study’s lead authors, in the press release.

Techcrunch event

San Francisco, CA | October 13-15, 2026

To be clear, the study didn’t claim that AI is ready to make real life-or-death decisions in the emergency room. Instead, it said the findings show an “urgent need for prospective trials to evaluate these technologies in real-world patient care settings.”

The researchers also noted that they only studied how models performed when provided with text-based information, and that “existing studies suggest that current foundation models are more limited in reasoning over nontext inputs.”

Adam Rodman, a Beth Israel doctor who’s also one of the study’s lead authors, warned the Guardian that there’s “no formal framework right now for accountability” around AI diagnoses, and that patients still “want humans to guide them through life or death decisions [and] to guide them through challenging treatment decisions.”

In a post about the study, Kristen Panthagani, an emergency physician, said this is an “an interesting AI study that has led to some very overhyped headlines,” especially since it was comparing AI diagnoses to those from internal medicine physicians, not ER physicians.

“If we’re going to compare AI tools to physicians’ clinical ability, we should start by comparing to physicians who actually practice that specialty,” Panthagani said. “I would not be surprised if a LLM could beat a dermatologist at an neurosurgery board exam, [but] that’s not a particularly helpful thing to know.”

She also argued, “As an ER doctor seeing a patient for a first time, my primary goal is not to guess your ultimate diagnosis. My primary goal is to determine if you have a condition that could kill you.”

This post and headline have been updated to reflect the fact that the diagnoses in the study came from internal medicine attending physicians, and to include commentary from Kristen Panthagani.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#Harvard #study #offered #accurate #emergency #room #diagnoses #human #doctors #TechCrunchbeth israel,harvard medical school,OpenAI

A new study examines how large language models perform in a variety of medical contexts,…

trial in Musk v. Altman comes to a close, one person has emerged as a critical behind-the-scenes manager of communications and egos in OpenAI’s early years: Shivon Zilis.

A longtime employee of Musk and the mother to four of his children, Zilis joined OpenAI as an adviser in 2016. She later served as a director of its nonprofit board from 2020 until 2023 and has worked as an executive at Musk’s other companies, Neuralink and Tesla.

When asked about the nature of his relationship with Zilis in court, Musk offered several answers. At one point, he called her a “chief of staff.” Later, a “close adviser.” At another point, he said “we live together, and she’s the mother of four of my children,” though Zilis said in a deposition that Musk is more of a regular guest and maintains his own residence. Last September, Zilis told OpenAI’s attorneys that she became romantic with Musk around 2016 after she had become an informal adviser to OpenAI. They had their first two children in 2021, she said.

But OpenAI’s lawyers have made the case in witness testimonies and evidence that her most important role, as it pertains to this lawsuit, is being a covert liaison between OpenAI and Musk, even years after he left the nonprofit’s board in February 2018.

“Do you prefer I stay close and friendly to OpenAI to keep info flowing or begin to disassociate? Trust game is about to get tricky so any guidance for how to do right by you is appreciated,” Zilis wrote in a text message to Musk on February 16, 2018, days before OpenAI announced he was leaving the board. Musk responded, “Close and friendly, but we are going to actively try to move three or four people from OpenAI to Tesla. More than that will join over time, but we won’t actively recruit them.”

When asked about this exchange on the witness stand, Musk said he “wanted to know what’s going on.”

In the same text thread, Musk wrote, “There is little chance of OpenAI being a serious force if I focus on Tesla AI.” Zilis reaffirmed him, saying: “There is very low probability of a good future if someone doesn’t slow Demis down,” referring to Demis Hassabis, the leader of Google DeepMind, who Musk has said he didn’t trust to control a superintelligent AI system. “You don’t realize how much you have an ability to influence him directly or otherwise slow him down. I think you know I’m not a malicious person, but in this case it feels fundamentally irresponsible to not find a way to slow or alter his path.”

Roughly two months later, in an email from April 23, 2018, Zilis updated Musk on OpenAI’s fundraising efforts and progress on a project to develop an AI that could play video games. In the same message, she said she had reallocated most of her time away from OpenAI to his other companies, Neuralink and Tesla, but told him, “If you’d prefer I pull more hours back to OpenAI oversight please let me know.”

Almost a year earlier, in the summer of 2017, OpenAI’s cofounders had started negotiating changes to the organization’s corporate structure—Musk wanted control of the company to start out. In an email from August 28, 2017, Zilis wrote to Musk that she had met with OpenAI president Greg Brockman and cofounder Ilya Sutskever to discuss how equity would be divided up in the new company. She summarized points from the meeting, including that Brockman and Sutskever thought one person shouldn’t have unilateral power over AGI, should they develop it. Musk wrote back to Zilis, “This is very annoying. Please encourage them to go start a company. I’ve had enough.”

#Shivon #Zilis #Operated #Elon #Musks #OpenAI #Insidermodel behavior,artificial intelligence,openai,elon musk,sam altman,neuralink,musk v. altman trial"> How Shivon Zilis Operated as Elon Musk’s OpenAI InsiderAs the first week of trial in Musk v. Altman comes to a close, one person has emerged as a critical behind-the-scenes manager of communications and egos in OpenAI’s early years: Shivon Zilis.A longtime employee of Musk and the mother to four of his children, Zilis joined OpenAI as an adviser in 2016. She later served as a director of its nonprofit board from 2020 until 2023 and has worked as an executive at Musk’s other companies, Neuralink and Tesla.When asked about the nature of his relationship with Zilis in court, Musk offered several answers. At one point, he called her a “chief of staff.” Later, a “close adviser.” At another point, he said “we live together, and she’s the mother of four of my children,” though Zilis said in a deposition that Musk is more of a regular guest and maintains his own residence. Last September, Zilis told OpenAI’s attorneys that she became romantic with Musk around 2016 after she had become an informal adviser to OpenAI. They had their first two children in 2021, she said.But OpenAI’s lawyers have made the case in witness testimonies and evidence that her most important role, as it pertains to this lawsuit, is being a covert liaison between OpenAI and Musk, even years after he left the nonprofit’s board in February 2018.“Do you prefer I stay close and friendly to OpenAI to keep info flowing or begin to disassociate? Trust game is about to get tricky so any guidance for how to do right by you is appreciated,” Zilis wrote in a text message to Musk on February 16, 2018, days before OpenAI announced he was leaving the board. Musk responded, “Close and friendly, but we are going to actively try to move three or four people from OpenAI to Tesla. More than that will join over time, but we won’t actively recruit them.”When asked about this exchange on the witness stand, Musk said he “wanted to know what’s going on.”In the same text thread, Musk wrote, “There is little chance of OpenAI being a serious force if I focus on Tesla AI.” Zilis reaffirmed him, saying: “There is very low probability of a good future if someone doesn’t slow Demis down,” referring to Demis Hassabis, the leader of Google DeepMind, who Musk has said he didn’t trust to control a superintelligent AI system. “You don’t realize how much you have an ability to influence him directly or otherwise slow him down. I think you know I’m not a malicious person, but in this case it feels fundamentally irresponsible to not find a way to slow or alter his path.”Roughly two months later, in an email from April 23, 2018, Zilis updated Musk on OpenAI’s fundraising efforts and progress on a project to develop an AI that could play video games. In the same message, she said she had reallocated most of her time away from OpenAI to his other companies, Neuralink and Tesla, but told him, “If you’d prefer I pull more hours back to OpenAI oversight please let me know.”Almost a year earlier, in the summer of 2017, OpenAI’s cofounders had started negotiating changes to the organization’s corporate structure—Musk wanted control of the company to start out. In an email from August 28, 2017, Zilis wrote to Musk that she had met with OpenAI president Greg Brockman and cofounder Ilya Sutskever to discuss how equity would be divided up in the new company. She summarized points from the meeting, including that Brockman and Sutskever thought one person shouldn’t have unilateral power over AGI, should they develop it. Musk wrote back to Zilis, “This is very annoying. Please encourage them to go start a company. I’ve had enough.”#Shivon #Zilis #Operated #Elon #Musks #OpenAI #Insidermodel behavior,artificial intelligence,openai,elon musk,sam altman,neuralink,musk v. altman trial
Tech-news

trial in Musk v. Altman comes to a close, one person has emerged as a critical behind-the-scenes manager of communications and egos in OpenAI’s early years: Shivon Zilis.

A longtime employee of Musk and the mother to four of his children, Zilis joined OpenAI as an adviser in 2016. She later served as a director of its nonprofit board from 2020 until 2023 and has worked as an executive at Musk’s other companies, Neuralink and Tesla.

When asked about the nature of his relationship with Zilis in court, Musk offered several answers. At one point, he called her a “chief of staff.” Later, a “close adviser.” At another point, he said “we live together, and she’s the mother of four of my children,” though Zilis said in a deposition that Musk is more of a regular guest and maintains his own residence. Last September, Zilis told OpenAI’s attorneys that she became romantic with Musk around 2016 after she had become an informal adviser to OpenAI. They had their first two children in 2021, she said.

But OpenAI’s lawyers have made the case in witness testimonies and evidence that her most important role, as it pertains to this lawsuit, is being a covert liaison between OpenAI and Musk, even years after he left the nonprofit’s board in February 2018.

“Do you prefer I stay close and friendly to OpenAI to keep info flowing or begin to disassociate? Trust game is about to get tricky so any guidance for how to do right by you is appreciated,” Zilis wrote in a text message to Musk on February 16, 2018, days before OpenAI announced he was leaving the board. Musk responded, “Close and friendly, but we are going to actively try to move three or four people from OpenAI to Tesla. More than that will join over time, but we won’t actively recruit them.”

When asked about this exchange on the witness stand, Musk said he “wanted to know what’s going on.”

In the same text thread, Musk wrote, “There is little chance of OpenAI being a serious force if I focus on Tesla AI.” Zilis reaffirmed him, saying: “There is very low probability of a good future if someone doesn’t slow Demis down,” referring to Demis Hassabis, the leader of Google DeepMind, who Musk has said he didn’t trust to control a superintelligent AI system. “You don’t realize how much you have an ability to influence him directly or otherwise slow him down. I think you know I’m not a malicious person, but in this case it feels fundamentally irresponsible to not find a way to slow or alter his path.”

Roughly two months later, in an email from April 23, 2018, Zilis updated Musk on OpenAI’s fundraising efforts and progress on a project to develop an AI that could play video games. In the same message, she said she had reallocated most of her time away from OpenAI to his other companies, Neuralink and Tesla, but told him, “If you’d prefer I pull more hours back to OpenAI oversight please let me know.”

Almost a year earlier, in the summer of 2017, OpenAI’s cofounders had started negotiating changes to the organization’s corporate structure—Musk wanted control of the company to start out. In an email from August 28, 2017, Zilis wrote to Musk that she had met with OpenAI president Greg Brockman and cofounder Ilya Sutskever to discuss how equity would be divided up in the new company. She summarized points from the meeting, including that Brockman and Sutskever thought one person shouldn’t have unilateral power over AGI, should they develop it. Musk wrote back to Zilis, “This is very annoying. Please encourage them to go start a company. I’ve had enough.”

#Shivon #Zilis #Operated #Elon #Musks #OpenAI #Insidermodel behavior,artificial intelligence,openai,elon musk,sam altman,neuralink,musk v. altman trial">How Shivon Zilis Operated as Elon Musk’s OpenAI Insider

As the first week of trial in Musk v. Altman comes to a close, one person has emerged as a critical behind-the-scenes manager of communications and egos in OpenAI’s early years: Shivon Zilis.

A longtime employee of Musk and the mother to four of his children, Zilis joined OpenAI as an adviser in 2016. She later served as a director of its nonprofit board from 2020 until 2023 and has worked as an executive at Musk’s other companies, Neuralink and Tesla.

When asked about the nature of his relationship with Zilis in court, Musk offered several answers. At one point, he called her a “chief of staff.” Later, a “close adviser.” At another point, he said “we live together, and she’s the mother of four of my children,” though Zilis said in a deposition that Musk is more of a regular guest and maintains his own residence. Last September, Zilis told OpenAI’s attorneys that she became romantic with Musk around 2016 after she had become an informal adviser to OpenAI. They had their first two children in 2021, she said.

But OpenAI’s lawyers have made the case in witness testimonies and evidence that her most important role, as it pertains to this lawsuit, is being a covert liaison between OpenAI and Musk, even years after he left the nonprofit’s board in February 2018.

“Do you prefer I stay close and friendly to OpenAI to keep info flowing or begin to disassociate? Trust game is about to get tricky so any guidance for how to do right by you is appreciated,” Zilis wrote in a text message to Musk on February 16, 2018, days before OpenAI announced he was leaving the board. Musk responded, “Close and friendly, but we are going to actively try to move three or four people from OpenAI to Tesla. More than that will join over time, but we won’t actively recruit them.”

When asked about this exchange on the witness stand, Musk said he “wanted to know what’s going on.”

In the same text thread, Musk wrote, “There is little chance of OpenAI being a serious force if I focus on Tesla AI.” Zilis reaffirmed him, saying: “There is very low probability of a good future if someone doesn’t slow Demis down,” referring to Demis Hassabis, the leader of Google DeepMind, who Musk has said he didn’t trust to control a superintelligent AI system. “You don’t realize how much you have an ability to influence him directly or otherwise slow him down. I think you know I’m not a malicious person, but in this case it feels fundamentally irresponsible to not find a way to slow or alter his path.”

Roughly two months later, in an email from April 23, 2018, Zilis updated Musk on OpenAI’s fundraising efforts and progress on a project to develop an AI that could play video games. In the same message, she said she had reallocated most of her time away from OpenAI to his other companies, Neuralink and Tesla, but told him, “If you’d prefer I pull more hours back to OpenAI oversight please let me know.”

Almost a year earlier, in the summer of 2017, OpenAI’s cofounders had started negotiating changes to the organization’s corporate structure—Musk wanted control of the company to start out. In an email from August 28, 2017, Zilis wrote to Musk that she had met with OpenAI president Greg Brockman and cofounder Ilya Sutskever to discuss how equity would be divided up in the new company. She summarized points from the meeting, including that Brockman and Sutskever thought one person shouldn’t have unilateral power over AGI, should they develop it. Musk wrote back to Zilis, “This is very annoying. Please encourage them to go start a company. I’ve had enough.”

#Shivon #Zilis #Operated #Elon #Musks #OpenAI #Insidermodel behavior,artificial intelligence,openai,elon musk,sam altman,neuralink,musk v. altman trial

As the first week of trial in Musk v. Altman comes to a close, one…