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- [00:00]
Alex
Let's talk about what's on Nvidia's roadmap after its GTC bonanza and whether the company's right that the AI buildout is just beginning. Plus, we'll dive into the state of OpenAI and a reshuffling at the top of Apple's Siri project. That's coming up with the Information's Executive editor, Amir Efradi, right after this.
- [00:19]
Amir Efrati
Forward thinkers know that when people thrive, organizations thrive. This is the future of work. This is Workday, the AI platform that elevates humans. From LinkedIn News, I'm Jessi Hempel, host of the hello Monday Podcast. Start your week with the hello Monday Podcast. We'll navigate career pivots. We'll learn where happiness fits in. Listen to hello Monday with me, Jessi Hempel on the LinkedIn podcast network or wherever you get your podcasts.
- [00:52]
Alex
Welcome to Big Technology Podcast Friday Edition where we break down the news in our traditional cool headed and nuanced format. Boy, are you in for a treat today because Amir Efradi, the co executive editor of the Information and the author on many stories that we read on the Friday show is joining us to break down the news on our Friday show. Ranjan Roy is out today. He'll be back next week. Meanwhile, we have a great show for you. We're going to talk about Nvidia's new AI roadmap, the state of OpenAI based off of a lot of Amir's reporting. And then also one more week we'll talk about a shuffling atop the Siri organization and Apple and whether the company will ever right the ship there. So great to have you on the show, Amir.
- [01:32]
Amir Efrati
Thanks Alex. Great to be here.
- [01:34]
Alex
Great to have you. I've been, I think I've been in your inbox for how long? A year maybe, trying to get you on. So I'm really happy to have you here. Like I said, we cite your stories all the time and I'm going to ask you so many open AI questions. Hopefully we'll get to the last story.
- [01:48]
Amir Efrati
Cool. I think I was in your inbox for a while too, waiting, waiting back. But yeah, very excited to get going.
- [01:55]
Alex
I will take that as true. All right, so let's talk a little bit about the GTC news from this week. We're going to get into the actual Nvidia roadmap in a minute, but I just want to talk about the broader analysis here because the main message from Jensen Huang, of course he was going to talk about the new chips they have, but basically his message was, we're just beginning to see the build out around AI and stay tuned because Nvidia has a lot to offer as we move into reasoning and as we get bigger and broader adoption of AI. So I'm going to quickly read the take from Dylan Patel at Semianalysis. And Dylan, by the way, is going to be on the show in the coming weeks, so stay tuned for that. His take is this. AI model progress has accelerated tremendously and in the last six months models have improved more than in previous six months. The trend will continue because three scaling laws are stacked together and working in tandems. Pre training scaling, post training scaling and inference time scaling and gtc. This year is all about addressing the new scaling paradigms. Basically he says that we're just seeing bigger and better models. And last year's mantra was the more you buy, the more you save. And this year's slogan is the more you save, the more you buy. I think what Dylan is saying there is basically that we are all now entering an era where AI chips are much more efficient and if you save a lot, you'll be able to do much more and then therefore you will be able to buy more Nvidia chips because adoption is going to be through the roof. Amir, I'm curious how you react to that.
- [03:26]
Amir Efrati
Well, I think when you talk about Nvidia, what you're really talking about is a handful of major cloud providers and within that, and sometimes separate from that, big companies, like big users, I should say, of Nvidia's chips, meaning OpenAI, you know, anthropic XI and, and Metta. And that's, that's mainly it. And so the question then becomes who else is going to, is going to want these chips? So we've got the Blackwell series that's just starting to roll out and it's a, you know, big improvement on the Hopper series that was in such, such high demand two years ago. You could not, you know, get enough. Two years ago there was a huge shortage as everyone clamored for, for those. And you know, we're in, in somewhat of a similar situation where a lot of very big companies want these chips. The companies that are developing AI, but not that many others are, are similarly going to want it. And it's interesting because a couple of weeks ago, in the last Nvidia earnings call, Jensen talked about this shift over time. He predicted that a lot of businesses, just regular businesses, not necessarily technology companies or software companies, are going to be adopting Nvidia's AI chips over time. That's his, that's his sort of roadmap and he said that that kind of follows other technology waves that came before and that may very well be true. I think the question is how much time before we get to something like that. And you know, at the moment that that's pretty unclear. And so the, you know, the cloud providers that we talk to at Nvidia's GTC event were basically saying that yeah, there's not much interest in Blackwell chips on the part of companies that aren't really big major AI developers themselves. And, and you know, that just raises some questions. I don't think that will necessarily change Nvidia's sales. They're like sold out and they're going to be sold out because like I said, you've got this mad, mad rush and mad competition on like the frontier model side. But, but yeah, I don't think it's, it's as straightforward as, as, as Dylan is making it out to be in the sense that, you know, there's still a lot of technical challenges that the major AI labs are trying to, to figure out. So I think there are definitely unanswered questions about how to make models that, you know, generalize and that are good at many different things at once. And so yeah, I don't think we fully know we know the future, but Nvidia is going to be fine for a while, that's for sure.
- [06:18]
Alex
So can you give an example of a company that is not among the major cloud companies that would potentially buy a bunch of Blackwell chips? I guess for, to set up their own. Would that be to set up their own data centers for inference? Or what is, what exactly would this group of companies look like?
- [06:33]
Amir Efrati
And this is why the earnings call was so interesting. I think he brought up an example of an automaker that would want to have AI chips on premises and again, we're just not there. So there are definitely automakers that use hopper chips for various reasons as many big businesses have been trying out either building their own internal apps or trying to launch AI features in their customer facing apps. But, but yeah, I think they're just still sorting through that and that, that takes time. It especially takes time if you're, if you're talking about, you know, reducing hallucinations and just protecting people's data and making sure things don't leak and all that. That just takes corporate America time. And so I don't think anyone is really clamoring for these Blackwell chips except for the really big AI developers themselves. And to some extent Nvidia itself, that's, that's what's so, so interesting. And we keep learning more, you know, about how Nvidia itself is actually one of the biggest customers of its own chips, both for internal purposes and also because they have their own cloud service that they may or may not want to supercharge. But they certainly spend a ton of money, billions of dollars, renting back their own chips, which is something people don't talk about a lot.
- [07:57]
Alex
Yeah. And I guess we'll cover a bit when we get to coreweave. But in the meantime, I want to continue to advance Dylan's argument because I think this is the argument that Nvidia and the rest of the AI industry would make. That's basically that the chips are getting much more powerful and more efficient and the models are getting more efficient. And as you get more efficient, you can unlock some new novel applications beyond maybe just putting the cars. Putting chips in cars. This is what Dylan writes. The inference efficiencies delivered in Nvidia's roadmaps on the hardware and software side unlock reasoning and agents in the cost effective deployment of models and other transformational enterprise applications, allowing widespread proliferation and deployment. A classic example of Jevons paradox. Or as Jensen would say it, the more you buy, the more you make. So do you buy this?
- [08:51]
Amir Efrati
Maybe in the long run there could be a period of uncertainty in between that. I don't know that it's a straight line. And I guess another way to look at this is another way to look at this is how many companies are generating revenue from generative AI? Not that many, definitely. Many companies are using it to cut costs and cut some costs and that's great, or automate customer service and so on. But in terms of companies that are actually selling generative AI, it's really, it's really very few. You could probably count it on two hands. Who, who actually has a significant amount of like application revenue or model revenue. So I think that just raises an interesting question about, you know, about the trajectory of adoption and what most companies can or cannot do with models. Even though they're getting more efficient now, these things can change quickly. And the Deep Seq revolution is still just beginning. So there's a lot of reasons to be excited. Like deepseek is still proliferating. It really like opened up a lot of people's eyes, to your point and to Dylan's point. So we'll see in the coming months, like what it enables because people are still testing and experimenting and playing around with it. But yeah, I think there's still unanswered questions about the exact trajectory that we're on beyond, you know, OpenAI, anthropic XAI meta and these big kind of spenders on the chips and these big companies that do have the ability to make revenue from providing this technology.
- [10:36]
Alex
You know, Amir, this is clarifying something for me because Jensen did spend a good chunk of the keynote trying to make the case that the AI build out is just beginning. This is from analyst Gene Munster. About a third of the two hour plus keynote Jensen spent making the case that we're still in the early, early in the AI build out. Investors are still skeptical given that Nvidia trades at 20 times earnings per share. I buy it. So I think what you're saying is going to be the big question around generative AI in the next couple months, maybe years, which is, are we at the beginning of the build out and is this going to extend beyond the companies that you just named the OpenAI's, the anthropics, et cetera? Or is this kind of where the AI revolution, so to speak, nets out, where it just kind of ends with a couple of chatbots and maybe some better enterprise efficiencies?
- [11:27]
Amir Efrati
Yeah, no, I'm not ready to make a bear case on this and certainly progress is occurring quite rapidly on a number of fronts, including on the coding side, as you've covered and you know very well. But yeah, I think we're still in this phase where we're waiting to see who else can generate meaningful revenue from products that are powered by generative AI. Um, so I'm not saying it's not going to happen. I'm, I'm just saying it, it maybe takes a little bit of time and.
- [12:00]
Alex
Maybe that's why we're hearing so much about robotics, because if they're able to unlock robotics with like an LLM for the physical world, then the opportunity becomes even more massive. And it's funny because I was on CNBC right as GTC was getting started and they're like, what are you expecting? And I say, well, listen, I'm expecting them to make the, a big case for humanoid robotics. And that's going to lead to artificial intelligence, General artificial intelligence. And there was a little bit of a mention of it at the beginning, at the end, from Jensen, but it actually came after the keynote in sort of the side stages that we got more announcements from Nvidia on robotics. A lot of people like Jan Lecuna, who was on the show on Wednesday, make the case that you basically need to Understand the world as it is and you're never going to get to human level intelligence just with text. And it was interesting as I read your recap of what was happening within the company, what was happening within GTC that you made robotics kind of like a big part of your first sentence. This is from your story and the information. Nvidia on Tuesday unveiled a slew of new software for robotics, including a simulator it made with Disney and Google's help during its annual conference for software and hardware developers. The announcements aim to catalyze the development of robots with software powered by Nvidia's artificial intelligence chips. So I'm curious if you think that's the way to read it, that this is what they see as the next big growth area and how real you think the robotics push is for I would say Nvidia, but also the broader tech industry?
- [13:34]
Amir Efrati
Yeah, it's definitely real and I think what, what really catalyzed it was Elon Musk and, and Optimus, to be honest, he really is a force of gravity, if you will. And I think that definitely caught the attention of OpenAI, which started its own, restarted its own robotics efforts as a result and many others. So there is a reason to take it seriously. But it involves such a difficult thing to pull off and also involves all kinds of components and motors and all sorts of things that, that you have to get right. And I don't want to say that this, that we're sort of like where self driving cars were 10 years ago, but in 10 years ago a lot of people were like, oh, self driving cars are right around the corner. And, and actually because it involves the physical world, because it is physical AI, because people's safety matters and we have had, you know, at least one or two deaths associated with, with self driving cars, which is really not that bad. It just took a very long time to get to where we are where you know, Waymo is outside my office every day. So I, it's very exciting, the robotic space, but will probably take a lot longer than you think. And whatever demos you're seeing figure AI, just take this with a huge grain of salt. One, one other thing that we just wrote in summary on the robotics announcements from GTC is that these were mostly incremental announcements. And yeah, the like little Star wars robot that they trotted out. I forget what it's called, DBX or something. Very cute. That one was probably remote controlled it seemed but, but yeah, I just, I wouldn't, I wouldn't hold your breath. I think there's A lot of good reasons to be excited. There's a lot of reasons why investors are putting money into this. But I, it's probably a, a 10, 10, you know, 10 year kind of bet definitely.
- [15:37]
Alex
And you see in Jensen's openings or one of his opening slides, he has this like exponential curve and it go starts from perception AI moves to generative AI, then to agentic AI and then physical AI. And Jan comments Jensen at gtc, the future of AI is physical AI. I couldn't agree more. Obviously. So I, I think we're just gonna, this is just gonna be a narrative that we're just gonna hear a lot more about. Especially as that question that we asked in the beginning. How what stage of the build out are we is. As long as that's unclear, we're gonna see more of this. It might be a look, look over here type of thing, but. Yeah. What do you think about it, Amir?
- [16:14]
Amir Efrati
Well, just to, just to round out the physical AI part. So I remember at, I think it was CES in must have been 2017 or 2018, Jensen was basically saying we're making self driving cars with Mercedes and we're making this and that. I think he even had like a, a prototype self driving car based on Nvidia's own software. You know, that was definitely way too far ahead of where things actually were and that's, that's part of his job. I'm not saying that that's a reason to doubt what he's saying, but I think we have some past precedent for this when it comes to physical AI on the non physical AI on the digital AI front. Look, OpenAI and Meta and Google are definitely very serious about massive build outs. XAI too. So you have, you know, at least four, five, six companies with a lot of resources that are still completely and totally committed to the idea that bigger is better. The, the funny thing about that is that, you know, similar to self driving cars, it could be that the rate of improvement does not continue in some exponential way and it could be more logarithmic or you know, it could just be, you know, you put more into it and you get, you know, a little more efficient over time. But I don't know that we're, I don't know that it's obvious that it's going to be some exponential curve. I think a lot of these folks, especially the, the dyed in the wool, you know, AGI kind of researchers definitely envision a time of like self, you know, improving AI, right? And again they are 100 religiously committed to the idea that they're very close on that. I just, I, I don't know that we have a ton of evidence for that yet. But, but everything that's happening is great and I, I'm, I'm a huge fan of all these investments. So, you know. Yeah, keep, go, go for it guys.
- [18:22]
Alex
Keep at it. Okay, before we move on, just very quickly about the chip roadmap itself, we don't have to spend a lot of time on this, but we should at least note it. This is again from your story. The company gave some glimpses of its upcoming AI chips, Blackwell Ultra, due out later this year, Veer Rubin chips coming out next year. And then the next generation is going to be named after another scientist, Richard Feynman. So any like, high level thoughts about what these, you know, generational improvements of chips enable companies to do? Is it just like slightly more powerful chip to train your AI models on? Like, how should we think about them at the moment?
- [18:59]
Amir Efrati
Yeah, that's pretty much it. I think. As we saw with Blackwell, there are inevitably going to be delays as Nvidia continues to really try to accelerate their rate of releases. It's just really hard to pull off, especially when it's like a different architecture or like a totally different die configuration which they're going to be trying to do. So it's very complex to pull off with all their partners and with TSMC in particular. So there's definitely a lot of like nervousness and hand wringing about like how long it's going to take to perfect these next versions. And then for the companies that ordered a ton of Blackwells, you know, the, the Microsoft's of the world and Google's and so on, they're, they're, you know, pretty stressed just like hearing about these new chips because they haven't even figured out the Blackwell chips and how they're going to make those work. And that's still like a tbd. We have not had the rollout of Blackwell and that's going to be a very massive undertaking on the part of the data center companies or the cloud providers that are going to implement them.
- [20:08]
Alex
Yeah, it was one of those things. When I heard about this, the Rubin chips that are set to come out next year, I was like, wait, so many people haven't even gotten the Blackwell chips. They can actually, what are they going to do? Are they going to just double up on orders or skip the Blackwell hardware is tough. It's not like software. There can be delays, it can be messes and you have to sort of adjust from there. Not.
- [20:28]
Amir Efrati
I'm glad you brought that up because adjustments happen all the time and these customers do put their orders off and say, actually don't give me the B2 hundreds, I'll wait for the GB3 hundreds or whatever. It's taking you too long to do this. We'll just wait for the next one. So there is a lot of that negotiation happening. And what's interesting about next year is that it's going to be a very, very important year in chips because that is the year when TSMC is going to launch its kind of next generation chip making process. You've got all kinds of companies that have been making huge investments and planning for that moment because they want to launch their own AI chip. OpenAI is definitely on that list and there are others. We know bytedance has been trying pretty hard. We've got Meta. I don't know how big or serious their effort is, but it definitely exists. You've got efforts from Amazon certainly that are very much worth paying attention to and we wrote about this week and they're practically willing to lose money to get customers to use these things. These are the Trainium chips that directly compete with Nvidia and are offered through Amazon Web Services. And so, yeah, you just have a lot of things converging on next year and yeah, that's going to be pretty exciting to see.
- [21:59]
Alex
Right. And so let's just take one of those and kind of talk a little bit about it. You mentioned that Amazon is willing to effectively lose money on its Trainium chips. This is from your story. Amazon uncuts Nvidia with aggressive AI chip discounts. One longtime AWS cloud customer said the company recently pitched them on renting servers powered by Trainium, which is Amazon's chip that would give them the same computer computing Power as Nvidia's H100 chips at 25% of the price. Does that type of stuff. I mean, we know that all these companies are building their own chips. Is that stuff shake up the market? I know you said we might have to wait till next year to figure that out, but what do you anticipate the impact of that being.
- [22:40]
Amir Efrati
Yeah, it definitely could have some, some impact. I think it's a little too early to tell, but we just know how serious they are about it. Because Nvidia, you know, nobody likes to deal with a monopoly and you know, or a company that has dominant share because they then ask their customers to buy other things, whether it's networking equipment or, or other parts that those customers may or may not want to buy. And that was a huge source of tension last year between Nvidia and Microsoft in particular and some others that we reported on. And it's actually part of the government investigation into Nvidia that is underway. So I think everyone respects Nvidia and Jensen. Unbelievable job, kind of seeing into the future and building for it and hats off, but they want to do what they can to, to be less reliant on them. And actually the one company that, that also was very thoughtful to, in getting ahead of things is Google. Google, which we haven't talked about and their Tensor processing units are, are something that you, you know, it's fair to say is a bit of a competitive advantage for them because they have been less reliant on Nvidia and this is how they develop their AI, although they don't have an infinite amount of TPUs. And so one of the reasons they had to merge their two AI groups, DeepMind and Brain, in 2023 is because they just didn't have enough TPUs to build large language models. So it's not, it doesn't solve all their problems. They are a major Nvidia customer as well. But the TPU chips are a force to be reckoned with. I know that they have their own plans to try to get customers, their cloud customers, I should say to use these TPUs so that it's not just Google using. I don't think that there are a lot of customers clamoring for that other than maybe Apple which has a lot of former Google engineers, but they're going to give that a shot too. So yeah, these are going to be really, really interesting efforts because these, these alternative AI chips are supposed to end up being pretty good. Now Dylan Patel might tell you that Nvidia is just so far ahead of everyone else and nobody is going to, is going to catch them. And that's an, it's an open question. And Nvidia has all these advantages, of course. Um, but I, I just wouldn't discount the seriousness of some of these other companies. And then it raises the question of, you know, exactly how much computing power are you going to need? And if, you know, if OpenAI or, or Google or Amazon, if they just make, you know, a lot of less powerful chips, does that make up for the power shortfall? You know, if they are good efficient chips, you know, is that going to be enough? So that's another question worth we're thinking about and asking Dylan about.
- [25:43]
Alex
Okay, that's fascinating. Let's keep poking at the Nvidia thesis, because it's fun to do it. So there's this company, Core Weave, which is pretty interesting if I have it right. What it does is it stacks up on GPUs and rents them out. And Nvidia has a large investment in it. It's planning to ipo. So you have this story that I think Corey Weinberg wrote this week and information about the projections for coreweave. The early projections, as it shared with private investors last fall, was that its revenue would quadruple to 8 billion and the cash burn would shrink to 4 billion. Instead, what's happening is revenue is going to be 4.6 billion. Cash burn is going to be 6 billion. Oh, 6 billion last year, and it's going to rise from 6 billion last year to 15 billion this year. So instead of doubling revenue or quadrupling revenue and shrinking losses, it is going to grow its revenue, but its losses are going to be incredible. And I'm curious, some people have taken this as a sign that basically it's all over for generative AI. So can you help us sort through the fact and the fiction of what's going on with Core?
- [26:55]
Amir Efrati
Well, at a high level, what's going on with Core Weave is when you present financial projections as a private company, there's a lot more leeway than when you present financial projections as a public company. So that's, that's really the main point there. When it comes to Core Weave itself, it is a success story. There's no doubt about that. And they were kind of right place, right time and moved very quickly. They were bitcoin mining enablers, and so they were big Nvidia customers to begin with. And then Nvidia saw an opportunity very smartly to again diversify its customer base. And it knows and doesn't like dealing with these cloud providers because they're trying to develop their own chips that compete with Nvidia's. So they're like, let's help Core Weave. Let's help and a bunch of other smaller data center and cloud providers and give them allocation of these really in demand hopper chips so that they can get revenue. And what ended up happening is again, because most of the chip customers, Nvidia chip customers are huge companies like OpenAI or these huge users like OpenAI, Microsoft and a few others. Core Weave's business ended up being mainly renting out these chips to Microsoft and a few others.
- [28:27]
Alex
Good work if you can get it.
- [28:28]
Amir Efrati
Yeah. Instead of Microsoft getting these chips directly, they had to go to Core Weave to get them. So I'm not being cynical about it, but Core Weave is basically a pawn in Nvidia's master plan. That being said, it really sounds like there is a place for them in the market because as a smaller company, as a startup that's really focused on AI computing, they're just able to move a lot faster than some of these big cloud providers and in setting up data centers. And so speed is really their forte. And it's really as just like physical AI, anything hardware related, as you pointed out, is really, really hard. You know, atoms are much harder than bits. And so a lot of the big cloud providers, even Microsoft, they really struggle, they really struggle to move quickly in the data center world. Core Weave doesn't have the same issues. They don't have a huge broad base of customers that they have to cater to. They only have a few customers they have to cater to. They can move a lot faster for all sorts of reasons. So there is a place in the market for Core Weave. I think it's just a matter of what is the proper valuation and, you know, can they, can they raise money to continue their build out over time? That I think those are, those are really the questions. It's more of a question of like, how much do you value this, this asset? As long as they continue to be strategic to Nvidia, they'll be okay.
- [29:57]
Alex
All right, I'm here. But on that point, they still have less revenue than expected, right? They were expecting, what were they expecting? 8 billion? They're only getting 4.6 billion. So is that a sign that the demand for their, for these services is lessening? Explain that.
- [30:13]
Amir Efrati
I don't think so. No, I don't think so. I think these are lumpy things and it's a matter, you know, they've had this issue before in 2023 when they were trying to expand very quickly and they couldn't. So they were mainly kind of real estate constrained more than anything else. So I wouldn't, I wouldn't read too much into that. One thing that. Oh, good.
- [30:39]
Alex
I was just going to say sometimes it's a supply issue, sometimes it's a demand issue. And it seems like it's a supply issue here, not a demand issue.
- [30:46]
Amir Efrati
Yeah, in this case, definitely a supply issue. One interesting thing that I don't know that they've disclosed this, but I remember in 2023 and it really stood out to us and it ended up being true. They, you know, they were telling investors a couple of years ago that the Nvidia chips that they were getting these Hopper chips, they would be able to monetize those for six years. That sounded like a really long time to us. And especially because you know, be like, oh, they're going to be two more generations of chips after that. But it's interesting that prediction, even though it's only been a couple of years, it seems to be right because even the ampere chips, which is the prior generation before Hopper, they're still in use today. OpenAI still uses them. So I think they definitely, you know, if that continues to hold, then it's not as if they are buying these fast, fast depreciating assets. These are assets that can hold their value for, for some time anyway. So that's, that's a little bit of good news for them.
- [31:56]
Alex
Okay, Amir, so you mentioned OpenAI and you are the co executive editor of the Information, but you also do a lot of reporting and I think that among reporters there's few that know OpenAI better than you. So I think that like as we go through this conversation about where Gen AI is heading, what the state of Nvidia is, we really need to talk about where OpenAI is going. So I'm just going to ask an open ended question for you. I mean, what is the State, State of OpenAI today? Very curious to hear what you think.
- [32:24]
Amir Efrati
The state of OpenAI today. How to, how to start? There are a few different vectors you could take. I guess the easiest one to Talk about is ChatGPT and that is a runaway hit. I mean, you know, it is a strong brand. It's growing like a weed. Dare I say it's like Google 20 years ago and that is worth a lot of money. And I don't want to say that it completely replaces Google, but it, it definitely could replace some of Google, but it also just enables a whole slew of queries and commercial opportunities. I mean, my wife is actually the chatbot evangelist in my household and has nothing to do with me. She's already, she's using ChatGPT in more creative ways than I could ever think of. This is not necessarily a creative example, but it's an important one. She asked it to do a bunch of research on skincare products because she I guess wasn't happy with hers, wanted a new stock and it came up with a bunch of different answers based on her parameters. And she is loving it. She bought everything it recommended and she's loving it. And she's so happy. She's like, can you tell I'm glowing and all that? And I'm like, yes, yes, of course you are. So that just gives you an example of the kinds of things that it can do, even if it's not eating into commercial stuff right now. So I don't know, I don't know how you discount that. Like, that is, that is an amazing kind of rocket ship. And I'm not seeing Google, you know, catching up to that. Certainly not their standalone Gemini chatbot. So the question is, can they get these same types of queries within this main search product? I don't know. They're trying a bunch of stuff. It's hard to do because they don't want to destroy their cash cow. But that's an incredible thing. You know, Meta is trying to shoehorn its chatbot into all these social apps that you have on your phone. I don't know exactly if that makes total sense or it only makes sense in some cases. But it's definitely not leading to the kinds of queries that I think you're seeing on ChatGPT, a lot of which are actually kind of coding related. Right. It's like the original, you know, really robust kind of coding assistant. That is a big reason why it's such a financial juggernaut in addition to being like a consumer juggernaut through its ability to, to charge subscriptions to a lot of professionals. So that's one side of OpenAI and there's a lot of reasons for them to be excited. Then there is the like, talent side, which is still pretty good despite a lot of their talent losses. I would say though, that, you know, it's, it's usually, you know, talent change, talent kind of personnel moves and the impact they have sometimes takes a little bit of time to play out. And so Mira Moradi, who was the CTO and abruptly left last, last fall, that's the one that's been the most concerning to people at OpenAI and to Sam Altman because she's been able to land some, you know, some good folks from, from the research team.
- [35:46]
Alex
She recruited just like everybody from the live streams, like the top echelon, just like all now working at thinking machines.
- [35:53]
Amir Efrati
Yeah, yeah. And you know, it definitely, you know, one of the, one of the ways, you know it's becoming A problem for OpenAI is when they send one of their biggest investors in to give a seminar to the employees telling them all the reasons they shouldn't go to a startup and how rare it is to have a great financial outcome that would be better than, than what they would get by staying at OpenAI. Yeah.
- [36:21]
Alex
So can you talk about that. You had that story. It's very interesting. Josh Kushner went in and was like, if you join a startup and you get 1% and it IPO or sells for a billion, don't think you're getting $10 million. It's like a hilarious. I've never heard of a meeting like this.
- [36:36]
Amir Efrati
Yeah. And what's interesting about it is it may be generally true what Kushner was telling people, but because these people are so rare and so unique and you know, it's like some of these folks are worth like $10 million right now, you know, in terms of the offers, the job offers that they would get. And it's not unlike the self driving car phenomenon from 10 years ago. Very similar. There are just so few people who had any expertise in developing the core kind of underlying software that they could get these kinds of offers and valuations and so on if they left these big companies to start their own thing or join a startup. So we do have this interesting dynamic. Mira is definitely trying to make it worth people's while to join her, you know, by giving them, by giving them equity that is very, very cheap and could be very valuable, at least on paper very soon. So she's not an idiot. She knows, she knows what money talks, what people need to be able to come out of OpenAI given that it is a rocket ship. So we don't need to go too far on this because there is still some great talent density at OpenAI. And I don't think it's easy to say that they're completely decimated or anything like that, but these are things.
- [38:04]
Alex
Before we move on, can I ask you one mirror question? I mean, what is she building? Because is she just going to try to build the same thing as OpenAI or. I could not understand for the life of me what she was trying to do when I read the launch post. So maybe you have some thought on this.
- [38:18]
Amir Efrati
Well, there are some things that are just harder to talk about if we're trying to report on them or break news on them. But no, I don't think it's going to be the same. And I think in some cases they're just trying to bring really smart people together to come up with a plan. Once they have those smart people. Right, it's like a roadmap. Well, they call it a lab. Right? It's a lab. So the purpose of a lab is to do experiments and then figure out what to do. Now there are plenty of commercial opportunities if you want to like be a consultancy and Say, hey, we just came out of OpenAI, we know what to do. You know, you can go to aerospace company or you could go to, you know, any business under the sun and offer your services and they'll, they'll probably take it. Or you can go to some of OpenAI's customers and try to say like, hey, we will do bespoke stuff for you as you help us learn what products are going to be great in the market. Right.
- [39:12]
Alex
That's ruthless.
- [39:13]
Amir Efrati
I mean, we'll see, you know, we'll see. You mentioned Deep Seq earlier and yeah, I think one thing that those clearly enable is just a lot more experimentation and a lot more, you know, of kind of building on top of these things to kind of get some approximation of the state of the art OpenAI or anthropic models without having to buy those OpenAI or anthropic models. So, yeah, they definitely have some options, but I don't know.
- [39:39]
Alex
Okay, I want to ask you one more OpenAI question before we go to Apple and Apple Intelligence. There was a fascinating information story that you guys put together about the apps at the other end of the agentic AI that OpenAI is building and how they feel about the fact that they're, you know, effectively going to be disintermediated by AI. And I think this is like the first few examples we've seen of companies telling the AI companies, hey, wait a second, we don't just want to be like an endpoint effectively in your master chatbot system. And you have some details of a meeting between DoorDash and OpenAI last fall, where I love the question that DoorDash asked OpenAI. They said, well, what happens if you take operator to the logical limit and what happens if only AI bots rather than people visit the DoorDash site? One thing that they talk about is how they have ads on their site and now instead of people seeing the ads, it would be robots. But to me, I think the greater concern that we're going to see from companies like DoorDash and others is as this AI gets more advanced and can surf the web, why do you need the DoorDash? For instance, maybe if your bot can now just log onto a restaurant webpage and order delivery. I mean, of course you still need the dasher, I suppose, but okay, that's a robot now. What does DoorDash exist for? And so there's been this kind of discussion around this stuff about do we live in a world without apps as AI gets better. And I think in this story, you're starting to see that the apps are starting to think about that as well. Now maybe that's extreme, like if you take it to its logical limit. But in the meantime, there could be some serious consequences to companies that end up in this, you know, AI ecosystem. Maybe the same way that app companies found themselves sort of, you know, by the leash in the Apple App Store. But this might be even worse because they control everything. So what do you think, Amir?
- [41:38]
Amir Efrati
Yeah, we're still really, really early in this. You mentioned Operator. This like web using web browser using AI that's out there and OpenAI is trying to get other developers now to make similar products. We don't know where that's going. I still think the opportunity with that kind of technology is more in the enterprise app world when you are trying to like use different enterprise apps at the same time. And maybe you have this AI that can like help you work with all these things together, transfer data from one place to another and so on. But the consumer kind of uses of these web browsing agents are kind of the things that the companies that have made these agents have talked about. So OpenAI and Anthropic and Google to some extent. And yeah, I think that retailers in particular are going, huh, Well, I guess we sort of need to see where this is going and to get ahead of it and to see if we need to block these things because they'll eat our lunch, no pun intended, in Doordash's case. So Yeah, I think OpenAI, like every technology company or any company wants to be the front end of the world. It wants to be the conduit through which everything happens. That's sort of what, what these companies end up, end up desiring at the end of the day. And already, as I mentioned with the ChatGPT example and my wife, OpenAI already has a product that's starting to, you know, impact commerce. So all the retailers and publishers, website publishers and other folks, they already have to sort of contend with that and think about that because, you know, just like when Google was coming up, people are going to need and want this referral traffic and they're going to want to, you know, if not game the system, they'll want to make sure that they're getting as much traffic and as many customers as possible once consumers like change their habits and start experiencing the web in a, in a new way. Same thing happened with social, obviously, and, and these things kind of ebb and flow over time. But that's sort of the starting point here. These, like web using agents I'm still not totally seeing it when it comes to consumer uses, but it's quite early and I'll definitely take it seriously. But I think that you've already seen Reddit block some of these things from traversing its site, so it's not a stretch to think that, that others will. And, you know, from the perspective of OpenAI and the companies are creating these, these agents that basically can, like, take actions on your behalf or do things that are a little bit more complex than just, like, reading and regurgitating something, they can actually do a transaction. They're. They think that this is the future. They think that, you know, you're just going to tell your AI, I want to, you know, I want to buy this kind of meal, or I'm hungry for this and just go do it for me and have it show up at my door. Right. Or, you know, I want this kind of information, like, tell me what happened in the. And, you know, set it. Set it and let it go and we'll do it. So they sort of see it as part of this vision of, like, so much more being automated. I think if you talk to, like, the Walmarts and Amazons of the world, they'll say, yeah, for, for some things it makes sense to, to automate purchases, but, like, not for a lot of other things. Like if you're going to plan a party and if you, like, have taste and you care about the details, like, you're not going to leave that to an AI. Right? At least not right now. So these things are early, these things are buggy. But there's clearly going to be tension between retailers and AI companies, just like there has already been tension between news publishers or content publishers and AI firms. And that is going to continue. There's already a lot of bad blood there, and that will continue.
- [45:51]
Alex
Yeah, I just think this is going to be a huge story moving forward, and we're just seeing the beginnings of it. So it was nice to see that you guys had some coverage inside a meeting where this is being discussed. We're here with Amir Efrati. He's the co executive editor of the Information. We have to talk about Apple drama, and we'll do that right after this.
- [46:10]
Amir Efrati
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- [46:36]
Alex
Race the sails.
- [46:37]
Amir Efrati
Race the sails. Captain, an unidentified ship is approaching.
- [46:41]
Alex
Over.
- [46:42]
Amir Efrati
Roger, wait.
- [46:43]
Alex
Is that an enterprise sailor solution?
- [46:46]
Amir Efrati
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- [47:04]
Alex
And we're back here with Amir Efradi, the co executive editor at the Information, talking all about the world of AI and what would a discussion about artificial intelligence be in March 2025 without a discussion of what the heck is going on at Apple? More drama at Apple. We've done two straight episodes leading with the Apple story. Figured this week we would take a break. So let's conclude with what's going on at Apple because it does seem like the urgency is high and we haven't seen firings yet. But we are seeing a reshuffling. This is from Bloomberg. Apple shuffles AI executives ranks and bid to Turn around Siri Chief Executive Officer Tim Cook has lost confidence in the ability of AI head John Giandrea to execute on product development. So he's moving over another top executive to help Vision Pro creator Mike Rockwell. Rockwell is going to report to software chief Craig Federe removing Siri completely from Giandrea's command. I think there was an MG Siegler tweet about this where he just kept on repeating, resist the urge to make a joke about the Vision Pro ahead taking over Apple Intelligence because we all know the Vision Pro hasn't done well, but at least they shipped that product in the way that they said they would, whereas Apple Intelligence has been a disaster. I don't personally think that this leadership change is going to make a difference because to me, the inability to build something good with Apple Intelligence and Siri, like I've been saying on the show for the past couple weeks, is a culture thing. And by putting Mike Rockwell in charge, you're not going to change the culture of Apple, which is something that really needs to change, something that needs to be less secretive and more collaborative, like I wrote about in Big Technology this week, to be able to build AI. But maybe, maybe this will, like light a fire under their butts. It's hard to really think that this is going to make a big difference, but I'm curious what you think, Amir.
- [49:00]
Amir Efrati
Yeah, you made an excellent point. And I think a couple of years ago as this was starting, Apple was trying to be a little bit more transparent in its research arm in terms of talking about the large language model related research they were doing. But yeah, I don't, I don't think they've, they've carried that too much further. And to your point, you know, it is, it is not easy to attract AI talent to every place and, and I think it's been very strange to see their struggles here because they, they have had a long time to do this now. It does, it does start with the person who's in charge. And one, one thing that is interesting about John Jan Andrea is that he really wasn't like a big fan or a big believer in large language models. And I think it took him a long time to kind of get, get fully on board and you know, they, they were sort of running into this situation where at WWDC last year they're actually promoting their ChatGPT, right, and OpenAI as, as being a leader here in this kind of foundational technology. Now I don't know that they've actually pushed that much traffic to, to OpenAI and you know, kind of provided their, their users with, with a lot of chatgpt action. And I, I think there's just this like inherent problem with, with privacy and, and data or like I think for a long time their whole mission was to put Siri all on device or as much on device as possible. Right. And really have it not, not need to talk to any servers. And so then it's like, okay, are we entering a totally different era where you actually do need server access? Because that's where the AI chips are that need to process whatever. I, um, so it's, it's honestly, it's been really strange to see, to see this. It's been really strange to see them have struggles with some of the features that they've been trying to launch and having to delay a lot of these things. But, but I think it's a combination of leadership being very slow on LLMs and being slow on ramping up investment in talent and then, and then yeah, some of the like inherent structural, organizational and kind of structural constraints that you pointed out, plus the, you know, how incongruent these LLMs or LLM services tend to be with the idea of like hyper privacy, hyper, you know, data localization and things like that. So yeah, it's a combination of factors, but very strange. The whole thing has been really odd.
- [51:39]
Alex
It's weird. I'll tell you one of the most interesting contradictions about the AI moment right now. You need to be big to play. We know that. Right. Like the companies that are at the lead are the ones that have the most money. But the advances have been made by the smaller, more nimble companies. OpenAI was an upstart built ChatGPT Deepseek hedge fund with a bunch of GPUs built Deepseek R1. You just can't have big company attitude if you're doing this stuff because you don't want to cut people off from new information. You need to be experimental, you need to be nimble and be ready to try the cutting edge and not have to go through processes. And it just seems like that's plaguing Apple in a big way. And Google's had that, but has gotten over it. But Apple has not gotten out of it and it's going to be hard for them to do.
- [52:26]
Amir Efrati
Can we just point out that, you know, when Siri launched, hats off to them because yes, it had its limitations, but it was a cultural moment definitely in the west and in the US and it was an earthquake inside of Google for sure. It really freaked everyone out there because Apple had done something that just captured people's imagination. And I think it's just incredible. It's been like 10, 12, 13 years since the launch of Siri and the improvements to Siri have just been so lackluster. It was interesting though that in all of this it definitely took some time for accountability to set in. And I think you had one big signal that there was a shakeup coming, was Kim Verath, who's there like software taskmaster, went into the Apple intelligence kind of section of the company and the Siri folks and was really brought in to figure out what to do on the product side and help people get on track back. And then you know, Mark Gurman at Bloomberg, who's done a great job reporting on all this, then reported on kind of mea culpa by Robbie Walker, who joined quite a long time ago to work on Siri that sort of like took the fall for, for some of the problems. This was sort of an internal mea culpa. And then I have to say Gurman's report yesterday on this, this change with Rockwell and Gianna Drea, we had heard about this earlier this week. We're working on reporting on this as well. But the fact, you know, to be able to print in publication a sentence like Tim Cook has lost confidence in John Dean. Andrea, that is not something you write lightly. And you have to imagine, and I'll keep this vague, but you have to imagine that there is a reason why Gurman was able to write those words just in the way that he wrote them. But yeah, it's really, really quite a shift over there. But it's definitely logical given all the problems they have and how far behind they are. But they still have an opportunity. Nobody has really just knocked it out of the park on voice and voice AI. It's definitely happening. It's definitely coming. I know Elon obviously is trying with the Grok app and I forget what he calls the voice assistant. I think it has a different name than Grok. But Google has a. You know, Google definitely has options here with their Android platform. So Apple can still do amazing things that are very, very useful if they kind of make Siri innovative again. So I wouldn't like totally count them out in every way, but man, this has been such a weird saga.
- [55:27]
Alex
Not something you expect from Apple. Okay, so we have a Discord chat for our paid big technology subscribers. It's real fun. And the Discord's been buzzing all week about someone saying, I think it was Mac rumors calling this the Windows Vista moment for Apple. Do you think that's fair?
- [55:45]
Amir Efrati
You're asking me to tell you whether Apple is going to be languishing for a decade? Um, that, that is difficult to do. Um, yeah, I don't, I don't want to stick my neck out on that. Uh, yeah, I really don't. But I, and I don't have the Apple intelligence features. I'm very happy with my iPhone, really one of the greatest purchases I've, I've ever made. And so it's, it's hard to feel too, too down on them. And you know, one, one thing that I've actually been thinking more about than, you know, lately is the upcoming kind of Google antitrust penalty trial and what that could mean for, for Apple. I think that's really the big deal. If, if for some reason the government is going to be able to prevent Google from paying Apple $20 billion a year for search referral traffic through Safari, which preloads the Google search service, then, then it's worse than the Windows Vista situation. It's like, you know, they get cut, cut down in size. So I don't know whether or not the market has priced in that possibility or exactly what the government is going to be able to, to do. And what, yeah, what Tim Cook has up, up his sleeve to, to kind of deal with that, but that's a very pressing short term concern for them to lose those profits.
- [57:20]
Alex
Oh yeah. All right, Amir, thank you for coming on. Can you share where people want to find where people can find your and your team's reporting and how they can subscribe to the information.
- [57:30]
Amir Efrati
Sure. It's just theinformation.com I'm on X Amir and Amir@theinformation.com is my email if you ever want to reach out. But yeah, we focus on stories that tell you things, hopefully that you didn't know before. That's the bar we try to meet every time we try to get inside all the companies that people care about. And, yeah, we take AI quite seriously. We have a newsletter that is insanely popular and insanely full of great reporting called AI Agenda, run by Steph Palazzolo. So we definitely encourage people to check that out, too.
- [58:06]
Alex
And I will just second all of this and say thank you for writing so many great stories that we're able to cite here on the Friday show and for coming on the show yourself. So thanks for coming on, Amir.
- [58:15]
Amir Efrati
Thank you very, very much. I'm so glad we could do it.
- [58:17]
Alex
Me, too. All right, everybody, thank you for listening. We'll be back on Wednesday with another flagship interview. And on Friday, Ranjan Roy will be back to break down the week's news. We'll see you next time on Big Technology Podcast.