Pro-Worker AI

**Nathaniel Whittemore** (0:00)
Today on The AI Daily Brief, Pro-Worker AI. Before that in the headlines, Meta delays its next AI model. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
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It appears that Meta has had another setback as their latest frontier model gets delayed. The New York Times reports that Meta's new model, codenamed Avocado, has been delayed until at least May. We last heard about the model's progress in January when CTO Andrew Bosworth told Reuters it had been delivered for internal testing. He said at the time that the model was, quote, very good, but warned that there's still a lot of work to be done in the reinforcement learning process. More recently, there's been reports that Meta has set up a new applied AI division that reports to Bosworth rather than AI CEO Alexander Wang. Rumors followed that Zuckerberg was done with Wang, although those rumors were strenuously denied. Now, the reporting states that Avocado Performance has fallen short of the latest models from Rivals, and this month's planned rollout has been delayed. The report mentioned a shortfall in reasoning, coding, and writing from internal benchmarks. In other words, basically every major category for modern LLMs. Reportedly, the model outperformed Gemini 2.5, but wasn't a match for Gemini 3 Now, part of the issue could be the long development cycle. Meta has been working on this model for almost nine months, and the goalposts of model performance have shifted dramatically during that time. Meta put an optimistic spin on the issue, issuing a statement which said, Our next model will be good, but more importantly, show the rapid trajectory we're on, and then we'll steadily push the frontier over the course of the year as we continue to release new models. We're excited for people to see what we've been cooking very soon. And yet that doesn't exactly comport with reports that Meta leadership is even considering licensing Gemini to power their products as a stopgap solution. That said, researchers are said to be excited about the next model after avocado, codenamed watermelon. Now, ultimately, I certainly think that making people wait for a model that's actually good is way better than releasing a model that no one is impressed with. But the model battle for Meta remains distinctly uphill. Ethan Malik summed up a bit of the industry sentiment when he tweeted, Both XAI and Meta seem to be falling behind, based on the Grok 4.2 benchmarks in this reporting. Frontier AI models are really a three-way race at this point. Speaking of XAI, it seems like there are big moves afoot in that organization. First of all, they grabbed a pair of senior leaders from Cursor in a bid to catch up on coding. Sources speaking with the information said that Andrew Milich and Jason Ginsburg have joined XAI and will report directly to Elon Musk. The pair worked as heads of product for engineering at Cursor. Now the move comes as Elon acknowledges that XAI is behind on coding. During a conference appearance on Wednesday, Musk admitted the problem but said he expects XAI to catch up and exceed our competitors, his words, by the middle of the year. Meanwhile, XAI co-founders keep heading for the exits. Business Insider reports that Zhihang Dai left the company earlier this week, and Guorong Zhang has told colleagues he plans to leave in the coming days. For those keeping track at home, that's another two departures to make a total of six co-founders leaving this year. Only three of the twelve co-founders remain at the company, and one of them is Elon Musk himself. Now there's been speculation that some of these co-founders exited after projects they led fell short of Elon's expectations. For example, Zhang led Grok Code, and Toby Paulin, who departed at the end of February, was in charge of the maligned MacroHard project which we discussed on Thursday's show. Musk of course is known as a difficult person to work for, and hinted that this is a controlled demolition rather than a leadership collapse. He posted on Thursday, XAI was not built right the first time around, so is being rebuilt from the foundations up. Same thing happened with Tesla. Speaking of Cursor, that company is seeking new funding at a massive $50 billion valuation. Bloomberg reports that Cursor is in talks for a new funding round that would almost double their valuation. Cursor's last round in November brought in $2.3 billion at a $29.3 billion valuation. Now remember, this is a company that doubled their revenue to $2 billion since they last raised funds. But what's significant about this is that if they really are raising at a $50 billion valuation, that suggests that they are trying to compete for the long haul, rather than thinking about trying to shack up with one of the leading model labs. Now that choice isn't a shock given how CEO Michael Truell is positioning the company. Employees were told in an all-hands in January that for Cursor, it is, in his words, wartime. That means a product overhaul to focus on automated coding tools, as well as an ambitious project to train their own state-of-the-art models to reduce their dependency on the other labs. In Labland, the information reports that Anthropic is in talks with Blackstone and other PE firms to launch an AI consulting venture. The venture would be a dedicated consulting firm to sell Anthropic's tech to corporate customers. Alas, apparently, Anthropic's ongoing conflict with the Pentagon has put the talks on the backburner. Sources said that Blackstone leaders, including CEO Stephen Schwarzman, are concerned about announcing a partnership while Anthropic is mired in conflict with the administration. The genesis of the deal was apparently Blackstone seeking Anthropic's help to deliver consulting services to their hundreds of portfolio companies. Blackstone also discussed a similar plan with OpenAI, according to sources familiar with the talks. Ultimately, what all of these stories get to is the fact that enterprises are lagging and it's going to take just a huge amount of time on task and actual human bodies to do the internal implementation that's actually needed. I predict you are going to see massive expansions in the forward deployed engineering departments of these firms, partnerships with all the existing consulting firms, new venture spin-ups like this, all at once and more. Next up, an interesting statistic from a new survey from the American Medical Association. The survey found that 81% of doctors now use AI in their profession. Leading use cases include keeping up with medical research, generating discharge instructions, and documenting appointments. The AMA first gathered this data in 2023 and have found that usage has more than doubled since then. Said AMA CEO John White, AI has quickly become part of everyday medical practice. Physicians see real promise in its ability to support clinical decisions and cut down on administrative burden. Notably, the AMA has adopted augmented intelligence as their term for AI, hammering home the point that technology isn't supposed to replace human judgment. And indeed, when you dig into the data, that seems to be how it's playing out. The leading use cases of AI in medicine are all about summarizing information and aiding with administrative work. Assistive diagnosis was the only use case that comes close to the actual practice of medicine and only 17% of doctors said they were using AI in this way. Finally today, some new comments from Sam Altman, speaking at a BlackRock conference on Wednesday. While intelligence too cheap to meter might be the end goal, for now, Sam Altman is very distinctly in the business of selling tokens. Speaking at the conference, he said, Fundamentally, our business is going to look like selling tokens. We see a future where intelligence is a utility like electricity or water, and people buy it from us on a meter. In the full quote, Altman said the goal is still to make abundant cheap intelligence widely available. However, he explored the idea that skyrocketing demand could mean high prices or rationing. That's particularly relevant, given that token-heavy agentic use cases are coming online, as energy issues are picking up steam. Now, speaking on AGI, Altman said the term has lost all meaning. Instead, he's watching for two major milestones. First, the threshold when the majority of the world's intelligence is inside of data centers. Acknowledging huge error bars in the prediction, he said this could happen by 2028 And the second marker is the moment when leading scientists, CEOs, and political leaders can no longer do their jobs without AI. Altman commented, More and more these jobs will be supervising a bunch of AI. That threshold of when you really wouldn't want to be doing your job without heavy reliance on AI might take a little bit longer, but probably not a lot longer. I don't know man, that pretty much describes my job already, but here we are. Altman also addressed the numerous concerns around AI adoption, commenting, data centers are getting blamed for electricity price hikes. And almost every company that does layoffs is blaming AI whether or not it really is about AI. Altman argued that one of the biggest problems to be faced in the coming years is a rapid shift in how capitalism works. First, he noted that the entire structure of capitalism is designed to manage scarcity. If AI delivers true abundance, then society will need to rapidly adjust to a new paradigm. In the more immediate term, he noted that AI is disrupting the balance between labor and capital that keeps society functioning. He added, I am not a long-term jobs doomer. I think we will figure out new things to do. But I think the next few years are going to be a painful adjustment. And indeed, that is exactly the topic of our next segment. So, with that, we will close the headlines and move on to the main episode.