OpenAI vs Google, How NVIDIA Spends its $850B Cash Pile, and Musk’s Grok Plans | Nov 24, 2025

0:13Welcome, everyone, to the Informations TI TV. My name is Anita Ramaswamy. I'll be your host this week, filling in for Akash Pasrikta. It is Monday, November 24th. I'm thrilled to bring you today's show. First up, my colleague Theo published a great piece about Elon Musk's recent push to replace X staff with Brock. We'll explain. And we'll dig into a divisive topic, which is what continued AI adoption could mean for job security. Then we'll put Google's Gemini 3.0 model to the test against ChatGPT. One power user will come on to share their experience and talk about the broader chatbot wars. We've also got some tech earnings on deck, so we'll discuss what to know going into quarterly results for Zoom, Zscaler, and Salesforce.

0:58We'll end the show with a great piece from the information's co-executive editor, Martin Peers. Martin and I will be talking about how NVIDIA's fast-growing cash pile is being used and how the company is deploying its capital. It's a big show, so let's dive right in. Exclusive reporting from the information this morning reveals how Elon Musk is making job cuts at X in a larger push to replace employees with XAI's GROC. You'll remember that XAI bought the social media platform back in March, and my colleague Theo Waite wrote a story about the state of play today. He joins me now. Theo, welcome to TITV.

1:33Thanks for having me, Elon. Awesome to have you here, Theo. So what did you learn in the course of your reporting this story? So the most immediate news is that at X, which was merged with XAI earlier this year, there's an effort underway to replace a lot of engineers and remaining human employees with Grok, which is XAI's LLM. And as part of that, you know, there were some layoffs last month of engineers working in trust and safety. It's likely there will probably be some more in the future. And they're all kind of under this Elon mission of automating X, essentially, as much as possible. Right.

2:19So I want to hear a little more about that. I mean, what do you think Elon's goal is in terms of how Grok is going to fit into X after the acquisition? He wants it to run as much as possible. The algorithm, ad targeting, a lot of backend stuff. Like the recent layoffs were of people that worked in engineering for trust and safety. So stuff like detecting spam and, you know, government coordinated influence campaigns, that kind of thing. He basically thinks that you need as few people as possible doing that and as much AI as possible. Got it. And how do these twin brothers that he's hired play into that broader goal yeah so the the central characters in in the story today are these these two guys uh dima and yevkin sabolyev who are basically a they're twins and they're basically a strike force that xai kind of sent into x to uh put grok into everything and to kind of spearhead elon's mission here um they're you know they They report to Elon and they're kind of effectively the top engineers at X, even though Elon is technically the top engineer on paper.

3:29But they, yeah, they're the boss at the moment. Do we know anything else about them? Like, what is their background? What else do we know about where they came from and how they made it to X? Yeah, they're interesting. So they grew up in Ukraine. They both attended this university in Kharkiv, Ukraine, where they studied math at the same time together. And then they moved to Silicon Valley. Dima worked for years at Apple and then briefly joined OpenAI last year before he went to X. And then Yevgen worked at Meta for many years and then joined his brother at Apple briefly and then also came to X or XAI this year.

4:10So they're really interesting. They kind of work in tandem. And my understanding is, you know, there are people at the office that kind of just refer to them as the twins and see them as like one unit rather than two people. Speaking of two units or acting in concert, I mean, it seems like there are some parallels almost between what's going on at X, the social media platform, and XAI. Can you talk a little bit more about the similarities that we're seeing in terms of Elon Musk's approach and how he's choosing to run the two? Yeah, so spiritually there's kind of a similarity between this project at XAI called MacroHard, which is a play on Microsoft.

4:51Um, you know, Elon has kind of talked about a lot, macro hard, having this mission of basically building like a completely AI run software company. And he's argued that like companies that make physical things like, like cars or spaceships are, are easier or sorry, are harder to replace than companies that make software. And a lot of Microsoft's business is, is software. And so Elon says, you know, you can basically just make an AI that can create all the software and run all the software and displace software companies. And so the spirit of Macroheart is like to do that in a lot of different industries with a lot of different software.

5:33At X, it's more narrow, but they both kind of are part of this theme. One of the things I really appreciated, Theo, when I was reading your story was that you included some perspectives from people who were really close to the situation, sounds like employees. What are some of the concerns that you've been hearing about Grok and how Elon Musk plans to integrate it further into his companies? Right. So when you think about XAI's mission of getting Grok to as many people as possible, now that they've acquired X, they obviously have this huge way to essentially force it on people that use X. I mean, I don't know about you, but like, I've never like chosen to interact with with Grok on on X.

6:18And yet I see it all the time. Yeah, exactly. Like I'm not I know some people, you know, at Grok, is this true or something? I don't understand that. But there's there are ways in which it's worked into the UX on X, for example, like, again, another feature I don't use, but I see it. If you're composing a post, you'll have this option to say, like, do you want to generate an image to go along with the post using Grok? And there are all kinds of, you know, other versions of this where it's just kind of stuffed into the interface. And for some people at X, that has kind of been concerning because essentially people that work on X and that work on like the social media side don't have control over Grok, but Grok is generating all this stuff that shows up on X.

7:07So like famously, there was the Grok talking about Mecha Hitler thing a while ago that was frustrating for people on the X side because that was, you know, this output that they couldn't control showing up. And there have been similar issues where, you know, Grok will generate like pornography or adult content or offensive things or copyright, you know, copyright infringing things. And people at X just kind of have no control over that, even though it does impact, you know, the product that they spend all day working on. I mean, it sounds like it's fair to say that there are more than a few snags at this point, but I guess just zooming out, you know, Musk's goal is to make the company more efficient.

7:49I mean, how are you thinking through the possibility of further layoffs, whether they're at his companies or even beyond, just as AI becomes more and more prevalent in the workplace? Yeah, I mean, something that's true of XAI just as much as it's true of other big tech companies is that companies that have been pouring money into AI have to show some kind of result. And right now, that can mean layoffs. I mean, Amazon did big layoffs too. Other companies have done large layoffs after pouring a lot of money into AI. And, you know, I think that sometimes AI can kind of be a pretense to do something companies wanted to do anyway.

8:30It's not like, you know, an Elon Musk led company doing layoffs is, you know, completely new, like that happened when he bought Twitter originally. But to me, like X is a pretty interesting case because these changes become evident so quickly in the product. Like, you know, just think how often you see, you know, new features pop up or your free you feed evolve or spam, you know, get more prevalent and then disappear. Like there are all these changes like that as a user just become evident so much quicker than they do at other companies. So I think like, you know, watching X and XAI will be a pretty interesting like, you know, front kind of a way to see like what what could be coming at other companies in the next few years.

9:17Ultimately, do you think that that vision will work out for Musk? when it comes to making the company more efficient using AI? I mean, it's tempting to say no because there are all these potential problems, but think how many people said they were going to quit Twitter initially and are still on there. It's a very persistent platform with a huge base of users. And I think it's possible he could change a lot more and people would still stick around. That's a really good point, Theo. It was great having you on the show. and I guess only time will tell whether we're going to see more layoffs coming from Musk's companies and beyond.

9:54But really appreciate you joining us today. Thanks, Anita. So it's not just at Elon Musk's companies that workers are keeping the threat of layoffs top of mind. And that's why I want to bring in two guests to talk about the reality of what AI could actually mean for the job market. Joining me next is Gil Luria, head of technology equity research at DA Davidson, and Andrew McAfee, who's principal research scientist at MIT's Sloan School of Management, as well as co-founder of AI startup Work Helix. Gil and Andrew, thanks so much for joining us today. Thanks for having us. So I want to start by setting the scene here a little bit.

10:31US-based employers announced over 150 ,000 job cuts in October. That was up 175 % from the year prior. That's according to a report from Challenger Gray and Christmas. And it's coming at a time when companies are starting to more widely adopt AI. We saw Amazon laid off about 14 ,000 employees back in October, and the company memo that went along with that announcement specifically singled out AI. I mean, Gil, let's start with you. How much of this is truly AI-driven versus a convenient narrative to cut costs? Well, it's both. But to be clear, when we say that a lot of the job losses have to do with AI, a lot of what we're talking about right now is that Amazon, Microsoft, Google, Meta and others have to pay for AI somehow.

11:18And so they're cutting costs in order to keep margins in spite of these massive investments in AI. So in financial terms, we're moving costs from SG &A into CODs. We're moving costs from headcount to compute costs. And that's definitely happening. How many of those people are actually being replaced by AI? That's a whole other question. The framework we're still seeing this is the framework proposed by economist Richard Baldwin that said that we're not going to be replaced by AI. We're going to be replaced by people who use AI better than we knew. Andrew, I want to pose the same question to you.

11:59I mean, what have you been seeing in terms of whether this is really AI replacing labor or if it's just an excuse to cut costs? There are a couple of things going on. One important thing to keep in mind is that outside the hyperscalers that Gil was talking about, at most large enterprises, AI use is still in its infancy. There are a couple hotspots in the organization, software engineering being the most obvious one, but it is really early in the history of deep AI adoption for organizations. So I don't think in a lot of cases their layoffs are because they've automated a ton of work away. The other thing to keep in mind is that the research is not pointing in one direction on this, but there's really intriguing research done by a team, including my co-founder and colleague, Eric Brynjolfsson, that found out that in particular for knowledge work, white collar jobs, and for the youngest entrants to the workforce, the youngest people, the newest entrants to the workforce, that's where we're seeing employment declines compared to the past.

13:03So we could be starting to see AI's impact showing up in hiring of highly exposed professions and new entrants to the workforce. I'm glad you brought up highly exposed professions because I wanted to ask you what you think those are. Yeah. Well, you don't have to rely on me. my other co-founder, Daniel Rock, who's a professor at Wharton and a team at OpenAI, wrote a beautiful paper they published in Science a couple of years ago, where they essentially looked at every task done in the economy, asked, can this be substantially accelerated with AI with no loss in quality, and then rolled that up to the job, the industry, the whatever.

13:39And sure enough, you find that a lot of white collar work is highly exposed to AI, modern AI, and in particular, some kinds of jobs that were not as exposed to previous waves of technology. So again, software engineering is a great example here. Up until very recently, software was lousy at writing software. And just in the era of generative AI, that situation has been turned on its head. So we're seeing these disruptions. We're seeing real innovation here. That's not the same thing as seeing massive technological unemployment in the statistics right now, because we're not. I guess on the flip side, Andrew, I'm wondering if there are any roles that you are seeing that you think will become more valuable as AI takes root?

14:22I think jobs that require real interpersonal skills, motivation, coordination, persuasion, those kinds of jobs become more important. AI is still a lousy, you know, softball coach or middle school teacher or a good upper level manager. So I think caring professions and and professions that require actual deep social interaction and social knowledge, those are likely to become more valuable. Gil, I want to turn it to you and ask what you're noticing from the investor perspective. I mean, are we seeing investors generally rewarding companies that say they're replacing labor with AI and automation for their cost cutting?

15:02Or is Wall Street more focused on AI actually driving revenue growth and top line growth? both are happening uh for sure investors always want their companies to have lower expenses and in fact they're starting to build that into expectations and in the way this is going to play out it will be first at technology companies remember technology companies mostly employ software programmers so they're going to be the first ones to start seeing leverage on those programmers, they'll be able to produce more with the same number of people. So there's a lot of excitement around that. But again, the research Andrew and his colleagues at MIT have done says on the revenue side, it's also going to take a lot longer because these tools are still not necessarily ready for prime time.

15:52The IT technology stack is mostly based on structured data and deterministic outcomes with a lot of data governance. Those are three things that are very hard for AI to do right now. So it's going to take time before the tools get so good that we're generating new revenue. Do you have any examples, Gil, of companies that have effectively used AI to either cut costs or grow their top line that have been rewarded in the market recently? Yeah, absolutely. I mean, if you look at Palantir, Palantir has been able to help many of its clients do that. But it's really early stages. And it's really only Palantir's clients that have been able to do that.

16:36So Palantir comes in and it tells you, look, if you have this mission critical need, instead of hiring up to do that, we'll do it for you. We'll get you that result. You'll have less costs and you'll get an increase to revenue. But so far, it's really just a handful of clients that can afford the tens of millions of dollars that they're paying Palantir. There's not a lot that's going on beyond that. Just zooming out a little bit big picture, even outside of tech, I mean, Andrew, I want to direct this one to you. In the past, we've seen increased labor productivity lead to wage growth. Do you think this is going to be the case with AI and that workers will actually get to share a piece of the gains?

17:16Or do you envision companies capturing most of the value here? Yeah, you and Anita, you bring up this really fundamental fact that we've had previous extraordinarily powerful technologies. They've changed the economy and they have not led to immiseration, to massive technological unemployment or wage declines. There are more workers. They become more affluent. There are differences based on education levels and things like that. But the story about technological innovation is also a story about increased prosperity for people. I expect that to continue, even with something as crazy and powerful as AI.

17:51But you bring up this other important phenomenon that it looks like when we divide up the pie between capital and labor, historically, that division has been pretty consistent. And there's evidence that in recent years, it's been shifting more toward capital. That might continue with AI. It's a thing we've got to keep our eyes on. So to wrap this up, I wanted to ask both of you, I mean, do you expect AI to slow down hiring in tech or do you think we're going to see a rebound as companies sort of figure out how to use this technology and incorporate it in their day-to-day workflows? I think it'll be a change of mix to Andrew's point.

18:28I think we're going to have, it's going to be more challenging. If your job was to read a lot of material and summarize it or to write drafts for somebody else to edit, it's going to be a lot harder to get a job. If you're very good at using AI tools in order to accomplish those types of tasks, you're going to have a very easy time getting a task. So to Andrew's point, then it's much more likely that we're going to have increased productivity and usage than we're going to have mass unemployment from this, but it will push the boundaries. And it's a very important point that he made about the blurring of lines between capital and labor in that what we're talking about now is that labor will be AI generated.

19:13That's the first time where we're really talking about about replacing the tasks and the performance of computing and of thoughtful and generational tasks from labor, from humans to compute. That's going to challenge the economy. But in terms of employment, it goes back to the original point I made. It's going to be people that know how to use AI that are going to do really well. And so you don't think there's necessarily going to be a surge in hiring a year or two from now once AI really takes root in the enterprise skill? I think the labor market should be able to balance out as long as there's not exponential gains in AI.

19:56There is a scenario here. If you believe Mr. Zuckerberg and Mr. Musk and Mr. Altman, we could get to a point where there's an exponential improvement in AI or it becomes self-recursive and we get to a point where AI can do anything any human can do, at least as well as a human, then we're going to be challenged in the workforce. But that's still a small probability. The more likely scenario is that AI is going to continue to drive productivity, will stay at full employment, and those increases to productivity will accrue to both shareholders of companies, as well as to the labor force, because as we get good at AI, we're going to be more productive.

20:40We'll produce more value. We'll be able to get higher wages based on that. Well, I certainly hope you're right about that, Gil. Thank you so much, both of you, for joining me on the show today. It was great to have you here. Thanks for having us. So we are in a moment today where the AI landscape is shifting really fast, and even insiders are feeling the pressure. Last week, the information reported that OpenAI CEO Sam Altman sent a memo to employees warning of rough vibes ahead. That warning came ahead of Google's rollout of its Gemini 3 model, which sparked debate over whether the search giant is actually closing the gap with OpenAI when it comes to its models.

21:18So today, we're bringing on Zach Lloyd. Zach is the founder and CEO of Warp, a platform for software developers using AI. Earlier in his career, Zach was actually the principal engineer for Google Docs. and recently he spent a bunch of time using this Gemini 3.0 model. Zach joins me now to tell us how good the model really is and what kind of threat it could pose to others. Zach, great to have you. Hey, Anita. Great to be here. Thanks for having me on. Zach, I know this is a bit of a loaded question, but Gemini versus GPT, which do you like better? So my company is in the AI coding space, so I can speak mainly to that.

21:57we measure the performance of all of these models as they come out. And as of today, we are at the top of the benchmarks, at least one of the main benchmarks, Warp is, called Terminal Bench. And we're there using primarily Gemini. So I do think Google had a real advance last week. Gemini 3 is a far superior model to Gemini 2.5 Pro. And it's certainly at least comparable, if not maybe a little bit ahead of the pack right now when it comes to using models for agentic development, which is a very important space, obviously. So you'd say it's better than any of the OpenAI models in that regard? At the moment, if you really press me, I think I'm just based off the data here.

22:48and so we're going off what we measure. Our best result on any evals right now has been with Gemini 3. That said, if you look at actual usage within our product, there's probably still more usage for GPT over Gemini. And then historically, actually, the leading models in the coding space have been frame anthropic. So they've been the cloud models. And so at the moment, it's a really interesting situation. I think we have three very, very capable models from Google, OpenAI, and Anthropic, all pretty much sitting in not that different of a spot when it comes to coding capabilities. And what's new is that Google has really made up a bunch of ground.

23:39And would you say that that's specifically in terms of agentic coding? I mean, are there any other sort of workflows that you found that Gemini 3.0 is working better than other models? So I would say across like all sorts of development tasks, so even going beyond coding. So you can have, you know, you can have Gemini doing DevOps tasks. You can have it investigating why your servers are crashing. It's super capable. It's really capable, and we've measured this when it comes to doing sort of like long horizon tasks. And this is one of the ways that these models are improving over time is like you need sort of less and less hands-on keys, human guidance of them.

24:22And Gemini is a very good example of this where it can run for longer and longer time frames. Outside of the coding domain, I don't really feel personally qualified to comment. I watch the news like everyone else. I do think that they are, if there are areas where I see them spiking, it is more in sort of image generation, image recognition. They have a new model, Nano Banana, which is really good. So I do think, like, to me, the headline is like Google is really in the game right now, whereas before it was a little bit more of a two-man show. Yeah. Is that something that surprises you? Because at least to me, it seems like all this chatter about Google has been pretty recent.

25:01I mean, honestly, it shouldn't be surprising. if you look back at the history of LLMs, a lot of the technology originated at Google from Google Engineers. Obviously, the original Transformer paper was from Google. A lot of the original talent that seeded places like OpenAI and Anthropic was Google talent. And Google just is in such a strong position commercially here that they should be able to execute on this. They have incredible amounts of data. They have incredible infrastructure. They are, I think it's overlooked often, but they're one of NVIDIA's only competitors when it comes to actually making, you know, AI chips.

25:42And so, and they have huge amounts of money. So they have, they have everything you need to be really successful. It's to me, it's actually, it's, it's not surprising at all that they have like managed to ship something that is state of the art here. You mentioned that Google makes its own chips. I mean, another piece of the AI stack that it's touching is that it is a cloud provider. And I want to ask you how important you think it is for a model maker to actually be a cloud provider. I mean, does that matter? I think there's an advantage at scale to having the cloud as well. So I think if you look at like the, you know, the sort of value chain in the AI space, You have NVIDIA doing quite well.

26:27Then you have, you know, on top of that, you have whoever is like basically running the data centers and serving the models or doing, you know, doing the training. That's like they take margin. Then there's model providers who take margin. Then there's application layer. And if you can have an integrated version of that, I think you have more control over where you capture value and you have more of an opportunity to optimize by having a fully integrated solution. So I don't know, I'm ex-Google. I know Google executes really well. I think that they have all of the ingredients for being, if not sort of dominant here, at least a major player.

27:10They have one big problem, in my opinion, which is they have this major innovators dilemma situation, which is, I think what has opened the door for chat GPT specifically to really gain a lot of market share is like, I think Google is very cognizant of how do you roll out these AI models without cannibalizing their existing search business. So I think, I think that's like, they have this big structural business challenge, but in terms of like being really well positioned to compete, they're, they're very strong. And do you think Gemini 3.0 and its early success has come as sort of despite that innovator's dilemma?

27:47You know, I'm just speaking to the quality of the model. I think the big question is what do they do with it distribution-wise? How do they roll it into their search properties? How do they roll it out across their apps? So from Warp's position, you know, we use it via an API. We use it through their cloud. it's just like it's unambiguously a great thing for us to have Google ship a great coding model that's competitive with open AIs and Anthropics. It drives prices down for anyone who's building a coding app. So like us or Cursor, it creates options for our users so that our users have choice about which model is going to suit their workflow best.

28:31When it comes to how Google is going to integrate it across the rest of their properties? I'm super curious to see. I don't, I don't know. I think it's only in their interest to obviously have better model technology, but like, will they, how they'll integrate that in search? I have no idea. Obviously, Zach, there's two pieces to this. There's the, you know, the model quality piece, and there's also the business model itself. So I want to kind of press you here a little bit. I mean, let's fast forward to three years from now, right? Of all the frontier models out there, all the companies that are making them, you have OpenAI, Anthropic, Google, I guess Alibaba is in there too.