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">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
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.
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.
OpenAI’s former CTO Mira Murati just testified under oath that CEO Sam Altman didn’t tell…
![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.
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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](https://i2.wp.com/techcrunch.com/wp-content/uploads/2024/01/GettyImages-104509077.jpg?resize=1200%2C800&ssl=1 "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")
![OpenAI’s existential questions | TechCrunch
OpenAI has been all over the news recently, whether that news is about acquisitions, competition with Anthropic, or bigger debates about AI’s impact on society.
On the latest episode of TechCrunch’s Equity podcast, Kirsten Korosec, Sean O’Kane, and I did our best to round up all the latest OpenAI news. While the company’s latest acquisitions seem to be classic acqui-hires, Sean suggested they also address “two big existential problems that OpenAI is trying to solve right now.”
First, with the team behind personal finance startup Hiro, the company may be hoping to come up with a product that has “more hooks than just a chatbot, and maybe something worth paying more for.” And with new media startup TBPN, OpenAI could be looking to “better shape its image in the public eye, which lately has not been great.”
Read a preview of our conversation, edited for length and clarity below.
Anthony: [We have] two deals that are worth mentioning, one is that OpenAI acquired this personal finance startup called Hiro. And that comes after another deal that was literally announced when we were recording our last episode of Equity, so we didn’t get to talk about it: OpenAI had also acquired TBPN — a business talk show, like a new media company.
And I think both of these deals are pretty small compared to the scale of OpenAI. These are not things that people expect to really change the course of their business or anything like that, but they’re interesting because it suggests that there’s still this [attitude of,] “Let’s try out different things.”
Especially [with] the TBPN deal […] particularly at this time when it feels like OpenAI, from all the reporting we’re reading, is also trying to really refocus on making ChatGPT and its GPT models really competitive in an enterprise context with programmers.
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Is running a tech talk show, should that really be on the to-do list?
Kirsten: No, this should not be on the to-do list. That’s it.
I do want to mention Hiro because to me, that’s an interesting one, because Julie Bort, our venture editor, super talented, she wrote about this and was I think the first to write about it. She dug in a little bit and basically this looks like an acqui-hire. The company is folding. They basically said, “By this date, you won’t be able to access this anymore.”
This is a personal finance startup. And they only launched two years ago. So this absolutely is about getting talent on board. So I’m very curious to see if OpenAI is going to be just absorbing them into the ether at OpenAI, or if they’re actually interested in some sort of personal finance product that they want to work on. To me, it’s not really clear.
Sean: I think you look at both of these as acqui-hires to a certain extent. I mean, the TBPN acquisition, allegedly they are going to retain their editorial independence on the show that they make every day. And all respect to those guys who’ve put that out there and gotten it off the ground so quickly and grown it into what it has become.
I think any person who follows the media should have a healthy dose of skepticism that when you acquire something like that and you put the people who make the show under the org of the public policy people and comms or marketing adjacent people higher up at the company making the acquisition, that you could have good questions about whether or not saying “editorial independence” is enough. It’s not an incantation that just works.
But you know, what’s interesting to me about these two, while they are similar in their acqui-hire-ness, I think they both represent two major problems that OpenAI is facing.
One is Hiro. OpenAI has a very successful product in ChatGPT. As far as whether or not that will actually ever make them enough money to become a sustainable business that’s not raising the largest private rounds in the world, ever, to keep things going, is a big question. And they also seem to be struggling to keep up on the enterprise side of things where the real money seems to be, so bringing in a team like this seems like taking a shot at, “What else can we do?”
The guy who founded Hiro seems to have a serial entrepreneur streak of creating consumer apps, and so this seems to me like a bet on them being able to come up with something else that may have more hooks than just a chatbot, and maybe something worth paying more for.
And then TBPN is an acquisition made to help better represent what the company does and better shape its image in the public eye, which lately has not been great and certainly is under more questions now than just a few weeks ago, because Ronan Farrow just led a report at The New Yorker that dropped suspiciously right around the time that this and a couple other announcements from OpenAI came out last week.
I think those are two big existential problems that OpenAI is trying to solve right now.
Kirsten: So the thing that you didn’t say is, there’s Anthropic kind of looming in — not in the shadows, I mean, they’re very much taking up a lot of space here — but they’re having a lot of success on the enterprise side of things.
It feels like these guys are competitors and they also feel like very different companies in a lot of ways. Anthony, I’m wondering if you see them as direct competition to OpenAI? Or [are they] just finding their stride in enterprise and in a way, these two companies are clearly going to coexist and they’re really not directly competing with each other — maybe on talent, but not necessarily as we initially thought of them?
Anthony: I think they’re directly competing with each other. There’s definitely a scenario where if AI as an industry, as a technology, is as successful as its proponents hope for, they could both be very successful companies, they could just be the one and two. And the success of one does not necessarily mean that the other will just fade into obscurity.
And again, none of this is official, but there’s just been a lot of reporting around how it seems like OpenAI, more than anyone, is obsessed with and upset about Anthropic’s rise.
Our reporter Lucas [Ropek], he did a great piece over the weekend about the HumanX conference, where he was talking to everyone there and they’re sort of like, “Yeah, ChatGPT is fine, too,” but like they were all about Claude Code. And I think that is exactly what OpenAI is worried about.
Because again, in theory, there could be many other opportunities for generative AI, but it feels like the big growth area, the area where the most money is and where they could at least see a path to having a sustainable business in the future, is in these enterprise and coding tools.
#OpenAIs #existential #questions #TechCrunchAnthropic,Equity podcast,OpenAI](https://i2.wp.com/techcrunch.com/wp-content/uploads/2026/03/GettyImages-2266645295.jpg?w=1024&ssl=1 "OpenAI’s existential questions | TechCrunch
OpenAI has been all over the news recently, whether that news is about acquisitions, competition with Anthropic, or bigger debates about AI’s impact on society.
On the latest episode of TechCrunch’s Equity podcast, Kirsten Korosec, Sean O’Kane, and I did our best to round up all the latest OpenAI news. While the company’s latest acquisitions seem to be classic acqui-hires, Sean suggested they also address “two big existential problems that OpenAI is trying to solve right now.”
First, with the team behind personal finance startup Hiro, the company may be hoping to come up with a product that has “more hooks than just a chatbot, and maybe something worth paying more for.” And with new media startup TBPN, OpenAI could be looking to “better shape its image in the public eye, which lately has not been great.”
Read a preview of our conversation, edited for length and clarity below.
Anthony: [We have] two deals that are worth mentioning, one is that OpenAI acquired this personal finance startup called Hiro. And that comes after another deal that was literally announced when we were recording our last episode of Equity, so we didn’t get to talk about it: OpenAI had also acquired TBPN — a business talk show, like a new media company.
And I think both of these deals are pretty small compared to the scale of OpenAI. These are not things that people expect to really change the course of their business or anything like that, but they’re interesting because it suggests that there’s still this [attitude of,] “Let’s try out different things.”
Especially [with] the TBPN deal […] particularly at this time when it feels like OpenAI, from all the reporting we’re reading, is also trying to really refocus on making ChatGPT and its GPT models really competitive in an enterprise context with programmers.
Techcrunch event
San Francisco, CA
|
October 13-15, 2026
Is running a tech talk show, should that really be on the to-do list?
Kirsten: No, this should not be on the to-do list. That’s it.
I do want to mention Hiro because to me, that’s an interesting one, because Julie Bort, our venture editor, super talented, she wrote about this and was I think the first to write about it. She dug in a little bit and basically this looks like an acqui-hire. The company is folding. They basically said, “By this date, you won’t be able to access this anymore.”
This is a personal finance startup. And they only launched two years ago. So this absolutely is about getting talent on board. So I’m very curious to see if OpenAI is going to be just absorbing them into the ether at OpenAI, or if they’re actually interested in some sort of personal finance product that they want to work on. To me, it’s not really clear.
Sean: I think you look at both of these as acqui-hires to a certain extent. I mean, the TBPN acquisition, allegedly they are going to retain their editorial independence on the show that they make every day. And all respect to those guys who’ve put that out there and gotten it off the ground so quickly and grown it into what it has become.
I think any person who follows the media should have a healthy dose of skepticism that when you acquire something like that and you put the people who make the show under the org of the public policy people and comms or marketing adjacent people higher up at the company making the acquisition, that you could have good questions about whether or not saying “editorial independence” is enough. It’s not an incantation that just works.
But you know, what’s interesting to me about these two, while they are similar in their acqui-hire-ness, I think they both represent two major problems that OpenAI is facing.
One is Hiro. OpenAI has a very successful product in ChatGPT. As far as whether or not that will actually ever make them enough money to become a sustainable business that’s not raising the largest private rounds in the world, ever, to keep things going, is a big question. And they also seem to be struggling to keep up on the enterprise side of things where the real money seems to be, so bringing in a team like this seems like taking a shot at, “What else can we do?”
The guy who founded Hiro seems to have a serial entrepreneur streak of creating consumer apps, and so this seems to me like a bet on them being able to come up with something else that may have more hooks than just a chatbot, and maybe something worth paying more for.
And then TBPN is an acquisition made to help better represent what the company does and better shape its image in the public eye, which lately has not been great and certainly is under more questions now than just a few weeks ago, because Ronan Farrow just led a report at The New Yorker that dropped suspiciously right around the time that this and a couple other announcements from OpenAI came out last week.
I think those are two big existential problems that OpenAI is trying to solve right now.
Kirsten: So the thing that you didn’t say is, there’s Anthropic kind of looming in — not in the shadows, I mean, they’re very much taking up a lot of space here — but they’re having a lot of success on the enterprise side of things.
It feels like these guys are competitors and they also feel like very different companies in a lot of ways. Anthony, I’m wondering if you see them as direct competition to OpenAI? Or [are they] just finding their stride in enterprise and in a way, these two companies are clearly going to coexist and they’re really not directly competing with each other — maybe on talent, but not necessarily as we initially thought of them?
Anthony: I think they’re directly competing with each other. There’s definitely a scenario where if AI as an industry, as a technology, is as successful as its proponents hope for, they could both be very successful companies, they could just be the one and two. And the success of one does not necessarily mean that the other will just fade into obscurity.
And again, none of this is official, but there’s just been a lot of reporting around how it seems like OpenAI, more than anyone, is obsessed with and upset about Anthropic’s rise.
Our reporter Lucas [Ropek], he did a great piece over the weekend about the HumanX conference, where he was talking to everyone there and they’re sort of like, “Yeah, ChatGPT is fine, too,” but like they were all about Claude Code. And I think that is exactly what OpenAI is worried about.
Because again, in theory, there could be many other opportunities for generative AI, but it feels like the big growth area, the area where the most money is and where they could at least see a path to having a sustainable business in the future, is in these enterprise and coding tools.
#OpenAIs #existential #questions #TechCrunchAnthropic,Equity podcast,OpenAI")
