The Daily - Inside the A.I. Talent Wars

Episode Date: August 25, 2025

The race to dominate artificial intelligence has become a scramble for talent, with tech companies offering pay packages of $250 million and poaching their competitors’ best employees.Mike Isaac, wh...o covers the tech sector for The Times, explains why all the hype is raising fears that A.I. could become the next big bubble.Guest: Mike Isaac, a New York Times reporter based in the San Francisco Bay Area, covering tech companies and Silicon Valley.Background reading: To navigate the recruitment frenzy, many A.I. researchers have turned to unofficial agents to strategize.Life for workers at Silicon Valley’s biggest tech companies has changed as the behemoth firms have aged into large bureaucracies.For more information on today’s episode, visit nytimes.com/thedaily. Transcripts of each episode will be made available by the next workday. Photo: Photo Illustration by Ihor Lukianenko, via Getty Images Unlock full access to New York Times podcasts and explore everything from politics to pop culture. Subscribe today at nytimes.com/podcasts or on Apple Podcasts and Spotify.

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Starting point is 00:00:00 From the New York Times, I'm Natalie Kittrow-F. This is the Daily. The race to dominate artificial intelligence has become an all-out talent war, with tech companies offering pay packages of a quarter billion dollars and poaching their competitors' best employees. Today, my colleague Mike Isaac on how we, we got here, and why all the hype is raising fears that AI could become the next big bubble. It's Monday, August 25th.
Starting point is 00:00:56 Mike, we are here with you because in the last few weeks, we are here with you because in the last few weeks and months, we've started to see something truly extraordinary happen in the world you cover, which is Silicon Valley. I'm talking about these enormous pay packages, $250 million being handed out left and right to AI talent. And I think at a really basic level, for a lot of us, this has been a moment where we looked up and said, wait, what's going on here? And so I want you to help me understand. Why is this happening? Well, just to reassure. You people here think it's pretty crazy, too. So you're not alone. But I do think it's really a singular moment in Silicon Valley right now where all of the leaders of these big tech companies see
Starting point is 00:01:44 artificial intelligence as the next big thing coming around the corner. And so they've kicked off what I see is kind of an arms race where they're reshaping their companies to figure out how to build the next great AI product. But they've realized that they don't have the type of talent they need. They don't have the type of organizational structures they need. And their solution, for a lot of them, at least, has been to just throw enormous amounts of money at the problem. And what kicked off this AI arms race?
Starting point is 00:02:18 Because it did not seem like it was happening in this really obvious way until pretty recently. So if I had to pick a moment, I think we have the opportunity here to kind of completely reimagine what it means to use a computer. It would be when Open AI made this huge announcement in May through this highly produced video. Johnny is the deepest thinker of anyone I've ever met. And they revealed that they were going to bring on Johnny Ive, the now legendary inventor of the iPhone, iPad, IMAQ, the Mac, the Apple Watch, stuff that we use basically every day.
Starting point is 00:02:57 Right. I have a growing sense that everything I've learned over the last 30 years has led me to this place and to this moment. They announced that they were going to bring him on for $6.4 billion to help develop the next great AI consumer product. Wow. So Donnie Ive is partnering with OpenA.I. So much news from Open AI this week, but $6.5 billion.
Starting point is 00:03:27 It's Open AI, which is the leader in AI development, kind of muscling into the devices game. And it's a really huge deal. It's a ton of money. And everyone across the valley kind of chafed it because they haven't given any details about what this device would actually be. And it's, you know, unclear if it'll work. But I think it planted the idea in a lot of executives' minds at some of these other companies, that, hey, this is now a talent war. And I'm assuming, based on what we know, what they do with all that anxiety is channel it into
Starting point is 00:04:03 spending. They open their wallet. That's right. I mean, the one thing that all of these companies have, especially the big companies, is cash. You know, all of them are doing well financially. But I think the one that really typifies the sort of excessive spending is meta. Okay.
Starting point is 00:04:21 And what does that look like for meta? Tell me about that. Yeah, so back in June, Sam Altman, the CEO of Open AI, decides to go on a podcast that is conveniently hosted by his brother. Look, I've heard that Meta thinks of us as their biggest competitor. And he confirms, yes, meta is aggressively trying to poach people. They started making these, like, giant offers to, you know, a lot of people on our team. You know, like $100 million signing bonuses. And Altman says, Mark Zuckerberg, the chief executive of Meta, had been offering Open AI.
Starting point is 00:04:54 employees like $100 million signing bonuses to come over and work on AI for meta. I'm really happy that at least so far, none of our best people have decided to take them up on that. But Zuckerberg really doesn't get super far at this point because there's a lot of Open AI employees who actually like working at Open AI. They believe in the mission. But then Mark starts to ratchet things up. He decides $100 million is not enough. How about $200 million? How about $250? How about $250? How about we front load half of that offer within the first year? And then you get the rest of it over four years. He goes from, hey, this is crazy to this is generational wealth.
Starting point is 00:05:36 I'm about to offer you someone who may be like a 22-year-old researcher at Open AI. And does that work? I mean, I'm sorry, but $250 million might work on me. Yeah, I mean, like we can talk about, you know, I believe in the mission all day long. And then when someone, you know, backs a dump truck full of money up to your doorstep and says, here you go, it's hard to say no. So he did start getting people. He got someone at Apple who was very important for, you know, more than $200 million.
Starting point is 00:06:06 This is Roaming Ping, the most respected AI researcher and AI executive at Apple. He was basically holding everything together there. He started grabbing people from Google and deep mine. Meta has appointed Jin Gia Zhao, co-creator of Chad GPD and a key contributor to GPD4 as... There were some key open AI hires that he started grabbing and bringing over to Meta. Look, I think they want to assemble the top 50 AI researchers that are out there. But I think a really big moment was when Zuckerberg announced they had purchased a 49% stake in this company called Scale AI, which is essentially a startup that kind of does this data labeling for $14.3 billion.
Starting point is 00:06:54 Whoa. Now, a source gave me more color around incentives as well, saying that this is more about Scale AI founder, Alexander Wang's AI network. And what he did was pay that money to bring over Scales' 28-year-old CEO, Alexander Wang, and a number of his deputies, to head up this new organization that Zuckerberg is calling meta's new Super Intelligence Lab. And Zuckerberg's apparently moving desks in the office so that all of these people can sit right by him.
Starting point is 00:07:32 Okay, so Zuckerberg is figuring it out. It's not just him, though, right? There are other companies that have been getting in on this. Yeah, totally. This is when things get really wild. I think every other company in the Valley starts kind of freaking out and saying, hey, Zuckerberg. is kind of messing up our compensation here. We need to figure out how to start coughing up more money to keep our talent. And, you know, some of these researchers have been there for a while. They certainly aren't getting paid, you know, hundreds of millions of dollars. And so I think what we started seeing is all of the talent kind of congregating together and strategizing for how they could take advantage of the situation.
Starting point is 00:08:11 Hmm. Can I ask, who are, by the way, all these people? What do they do that makes them so valuable to these companies? So the people that are really in high demand these days are folks who are doing kind of niche research called frontier research, which means they've been pursuing far-flung parts of AI research that maybe most researchers are not looking into, and it's a pretty small number of them, are studying what's called. reasoning, which is basically helping to teach a computer to think more like you and me when it's trying to solve problems. And there's just not a lot of people who do this and do this well. You know, I've heard people refer to this as the kind of sportsification of the tech industry. And this is why, right? I mean, typically, you really only hear of athletes getting lured to new companies or teams with this kind of money, you know, like show hey, oh, tiny getting paid hundreds of millions to go play for the Dodgers. And look, we don't chafe at that
Starting point is 00:09:16 when we hear it. I mean, it's crazy money, but at this point, it's sort of normalized, I think. Like, of course, Steph Curry is getting, like, a huge contract. Of course you want to pay LeBron a crazy amount of money because they made these teams, like championship teams, right? That is the analogy that a lot of tech CEOs are making right now. And frankly, a lot of the people inside of these companies, like the rank and file, are starting to see. these folks as superstars. As difference makers. Yeah. I mean, they may not be household names to you or me, but certainly around Silicon
Starting point is 00:09:50 Valley, they have really good reputations. There's even the show that has developed over the past year. It's called TBPN. You're watching TVPN. We started 11 a.m. sharp. It streams five days a week, three hours a day. Speaking of AI research, we have a ton of stories in the AI trade deal. world. Zuckerberg continues to be in a tear. And it's basically a running commentary on the tech
Starting point is 00:10:18 industry, the media industry. Amazing. That kind of treats it like an ESPN sports center type show, but for business. We got a red flag. We got a red flag. Elon Musk and Sam Altman are fighting. Mom and dad are fighting. It's really funny. They do this stuff where if someone goes to meta, they'll spin up a funny graphic that's like traded. Open AI guy becomes chief scientist at Meadows' superintelligence labs and they have fun with it. Apple Inc. is plotting its artificial intelligence. Comeback. Don't call it a comeback. Actually, you can call it a comeback. Yeah, and it sounds like there's a lot of people that are interested in this news and that that is
Starting point is 00:10:58 kind of reflective of how attuned the industry is to these moves at this moment. Very much so. I think, you know, everyone in Silicon Valley. is paying very close attention to who's going where, who's got the next big hire, who's getting paid the craziest salary. And, you know, really just like in sports, everyone is watching to see how these moves or these trades, if you will, is going to affect other companies and see who comes out on top. We'll be right back. Okay, I want to get into those questions of how this money is actually changing things,
Starting point is 00:11:50 how the money is affecting the landscape of AI as you're seeing it. Yeah, so, look, I think we should remember we're literally in the middle of all of this happening right now. You know, this is like a moment in time. All of this stuff is like a wild flurry. of trading people back and forth. These companies are building new things. Everything is up in the air. I do not feel comfortable saying who's going to win the race.
Starting point is 00:12:16 Sure. That said, I think we can still look at the landscape and see where companies are right now. And, you know, who's got a great lead or who's the biggest long shot? And I think that's something that we can still just try to suss out. Yes, let's do that. Give me a power ranking of these companies, as it was. Okay. When I think of this market, I like to think of it in terms of companies creating consumer-facing products. And I say that because while a lot of the rhetoric around AI is about building the next
Starting point is 00:12:53 robot god or this all-seeing, all-knowing AI, a lot of these companies, you know, aside from open AI, haven't been able to do something pretty basic, which is just to convince people to use artificial intelligence in their everyday lives and build a business around that. And so when I think about that metric, I try to break these companies down into three different tiers. There's the bottom tier, companies that are definitely in the mix, but are probably more of like a long shot in this greater race. You have perplexity, which is a startup that creates this Google search-like product. You have Anthropic, which is certainly bigger. They have their own chatbot called Claude, which is used by people and enjoyed, but certainly not as widely
Starting point is 00:13:41 used as some others. And then you have XAI, which is the artificial intelligence wing owned by Elon Musk and kind of grafted on to X, the social network formerly known as Twitter. That has this chatbot called GROC, which, you know, has done some interesting, even impressive things. But when it screws up, It screws up in a big way. There was this moment where it decided it was a Mecca Hitler bot and offended basically everyone at the same time before they had to apologize for it. That's a pretty big error. Yeah, that's not great. And I think it's one of these things where they have the advantages of having Elon Musk and his endless bank account, but they also seem to stumble in a very high profile way.
Starting point is 00:14:30 Yeah, it's interesting that Elon, who's, you know, often seen as out ahead on so many things, does not. seem to be leading the pack on this. So what's tier two? So tier two, I would probably put the more established tech companies. Think Apple, Meta, Google, and these companies have two key advantages, scale and cash. But they have a lot of disadvantages, too. Let's take meta, which we've already established, is behind. a lot of researchers are sort of worried that Mark Zuckerberg doesn't have a clear vision
Starting point is 00:15:09 for what AI will look like at meta. And frankly, they don't want to work on building the next algorithm that keeps you in Instagram or Facebook for longer because it's suggesting better content using AI. That is not exactly what they signed up for when they got into the field. Then, you know, Apple, I think they're weak because, you know, even though they've sold, billions of iPhones at this point, Siri, the AI tool that comes with it, is not even really thought of as an AI tool. It's like a voice assistant that only works half the time and is considered pretty bad in Silicon Valley circles. And even Apple acknowledges Siri is not where it
Starting point is 00:15:52 should be, right? It should be this incredible assistant is what they promised it to be. And it just hasn't been. It hasn't panned out. Because for years, Apple has not really invested in the type of technology that these other companies have. So I would say they have a lot of potential, but they're just not there yet. And Google? Google is interesting. You know, Google has been working on AI arguably the longest of most of these companies. They have made huge advances. They're very mission-oriented. They're likely literally wanted cure cancer. That is huge in helping recruit talent. But I think the AI that most people are familiar with from Google is the little summaries at the top of search results that happen these days. And they've had some, you know,
Starting point is 00:16:42 pretty high-profile stumbles with that summary. There was this moment where they gave a recipe putting glue on pizza, which is like, I don't know about you. That's not something I'm super into, but like, it's not quite Hitler chatbot, but it's pretty bad. I think in the rankings of bad, it's down the ladder a little, but still, like, the entire point of Google is getting you the best search results, and that is clearly not the best. And I think we're now at the top tier, right? Which I assume is the company we've been talking about that everyone's been chasing Open AI. That's right. Open AI really kicked this whole thing off a few years ago. They were the ones that first released the most successful chatbot, millions of people downloaded it overnight,
Starting point is 00:17:29 basically. And to this day, they still have an enormous amount of people using it and continue to grow every single day. But they do have some disadvantages. You know, for one, they're losing enormous amounts of money because it costs a lot of money to keep the successful chatbot running. I think it's, it's one of these things where they're dramatically ahead as far as the number of people using it. But that can change almost overnight sometimes if a company puts out another better product. And yet, there is something remarkable about the fact that this company is so far ahead, right now, at least. And I think it's because the American tech industry is a place where there has been a lot of talk of monopolies. You know, there's these massive
Starting point is 00:18:18 companies that just own so much of the internet. And then you have, this industry that is like the most important thing on earth to many people right now. And there's a company outside of the big ones that's dominant. I mean, this is honestly classic Silicon Valley as a story, right? You may look at Google, meta, Apple. I think these companies are going to be dominating the landscape forever. But like I would have said the same thing about Blockbuster Video 20 years ago. ago, right? Where, of course, I go every Friday night and get a movie and I go home and watch it
Starting point is 00:18:58 on DVD. Yep. And then Netflix comes along and now they're mailing you DVDs. And then a few years later, they're streaming every video to your TV at home. So you don't even have to leave your couch, right? It's a classic idea of the innovator's dilemma. If you're big, if you're dominant, you don't need to worry about creating the next big thing because you can just sort of coast on your laurels and, I don't know, let's milk the sports analogy. You can keep playing defense rather than offense. Yeah. And that leaves you behind when an upstart comes in with something new.
Starting point is 00:19:32 That's exactly right. And all these companies are now kind of on their back foot and trying desperately to catch up to open AI, which, as you said, came out of nowhere and lapped them all. We ranked, well, you ranked these companies based on their relative positions in the race. toward a kind of consumer product, the effort to capture the consumer market. I mean, and the stakes for that, for getting people to use this stuff, seem pretty high given how much we've said
Starting point is 00:20:02 they're spending and investing in this. And it's not just salaries. It's the data centers. It's developing these models in the first place. And so I have to ask, how sustainable is that? I mean, many of these companies are public companies.
Starting point is 00:20:20 They have shareholders. they have investors. How long can this last? Is there a limit? It's a good question. I appreciate you bringing us back down to earth with money because all this stuff is insanely expensive. This is not just billions,
Starting point is 00:20:35 but hundreds of billions of dollars in spending on infrastructure. You know, building data centers is not cheap. Sure. Developing products that maybe people use, maybe they won't is not cheap. It's adding up and it's adding up quickly. I think the,
Starting point is 00:20:50 Companies have been given a lot of latitude for years just because they all basically print money. Google created the perfect internet business model with search ads. Meta has me buying stuff on Instagram incessantly and makes billions every quarter. As long as their businesses have been running smoothly, investors have allowed them to pursue these far-flung ideas that are losing big amounts of money. But I think we're starting to see. the limits of that mentality. In recent weeks, Wall Street has started to get a little shaky on this. They've seen how much this stuff costs to build, and they're starting to ask more questions
Starting point is 00:21:33 saying, hey, can this be an actual business and do people want to use this stuff? Yeah, on that, there has been some talk, right, of whether this might be a bubble, you know, reminiscent of the kind of dot-com bubble in the early 2000s where you had the, this huge amount of internet startups that had these insane valuations and then that bubble popped. Do you see that here? Is that a parallel? No one likes the B word out here. But yeah, I think it's totally, I think it's fair. Look, I mean, there's so much money tied up in this. Every VC firm is spending insane amounts to get into AI companies. There's AI companies built a top of AI companies. Data.
Starting point is 00:22:20 and infrastructure companies that are relying on the success of this stuff, it's kind of like all interconnected and really dependent on each other's success. And I think it's a really fair and important to question whether this stuff is going to even work out, not treat it as an inevitability. What does that mean for the economy? Because so much of our economy is being driven by this huge spending and this massive new industry. If the bubble does go pop, what does that mean for the rest of us? I mean, look, it reminds me of how tied into this we all are. You have to remember,
Starting point is 00:23:03 the big tech stocks often lead the entire market, right? Sometimes the Dow is up and down based on the performance of meta or Google or Apple or whatever. My 401K is probably tied up to this, as is yours, you know? this is kind of woven into our economy, whether we want this version of the future or not. So in a way, we are kind of tied to the success here. The idea that if you choose not to use chat GPT doesn't insulate you from the idea that AI is not going to affect you at all. I think it's more woven into different parts of how the world works than you and I might realize. Right.
Starting point is 00:23:43 It's like even if you personally are not bought in, the entire economy is. So you're on this train. Yep. Welcome aboard. Mike, thank you. Thanks for having me. We'll be right back. Here's what else you need to know today.
Starting point is 00:24:28 After we do this, we'll go to another location and we'll make it safe also. We're going to make our country very safe. We're going to make our cities very, very safe. President Trump said that he planned to target Chicago for his next federal crackdown on crime. Chicago is a mess. You have an incompetent mayor, grossly incompetent. And we'll straighten that one out probably know. That'll be our next one after this.
Starting point is 00:24:51 Trump said the National Guard deployment in D.C. was helping clean up the city and suggested that he was also willing to use active duty troops on city streets. We haven't had to bring in the regular military, which we're willing to do what we have to. But the president may not be able to easily replicate the show of force in D.C. in other major cities. Because D.C. is a federal district, not a state. Trump has more control there than anywhere else. else in the country.
Starting point is 00:25:20 That includes the ability to take control of the local police force. Today's episode was produced by Diana Wynne, Alex Stern, and Carlos Preeto. It was edited by Lexi Dio, Mark George, and Maria Byrne, with help from Michael Benoit, and was engineered by Alyssa Moxley. That's it for the Daily. I'm Natalie Ketrow-F. See you tomorrow.

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