Alex (4:05)

Even look at, you even look at the formatting and yes, this is a post that was written meta.com superintelligence. He didn't even post a thing on Facebook. And it, the if folks, if you haven't seen it, this is what it looks like. It legitimately is like black text on a white background. It looks like the AI researcher websites where they like kind of want to show that they don't really care about branding, even though they really do. And they're like in courier and like blue links and stuff like that. It has exactly that feel and it does have just if you look at the Optics of this. And Mark Zuckerberg knows this very well. It is sort of a, an attempt to position himself as, as a someone who knows what's going on with AI research and B, you know, one of these AI visionaries.

MG Siegler (4:52)

Yeah, this is like the old school version of, you know, when CEOs might write like a Tumblr post back in the day.

Alex (4:58)

Right, exactly.

MG Siegler (4:58)

Because they're being cool and edgy and they're, they're meeting, they're meeting their employee base where they are, rather than.

Alex (5:03)

He should have just written the thing in like entirely lowercase and then he really would have been. Which is the way that Sam Altman writes. Then he really would have been on point.

MG Siegler (5:10)

Or you should have. Yeah. Done a copy and paste of, of having written it in terminal. In a terminal. And then, you know. Yeah. Basically used a screenshot of it.

Alex (5:17)

Yeah. And I know it's like, it's easy to make fun of, but I actually think this is like smart, a smart play. You kind of have to show to these folks that you're speaking their language.

MG Siegler (5:26)

Yeah. I mean, again, I think that he's doing what he feels like he needs to. I think he's been out there, obviously talking to all sorts of people, you know, in terms of who he could potentially bring on board. Some have come on board, many have not. It sounds like, you know, from all the various reports on it. And I think he's probably, you know, using those conversations as inputs in his own head of, like, what's resonating, what's not, what do I need to do differently? What do I need to, you know, how do I need to frame this? And again, I think one of the key things is like, having a cohesive message about what Meta is trying to do, and hopefully one that's different from what the other competitors are trying to do. And I think that that's where this sort of netted out.

Alex (6:07)

So let's get into that message. So he says in it's clear in the coming years, AI will improve all our existing systems and enable the creation and discovery of new things that aren't imaginable today, but is an open question what we will direct Super Intelligence towards. And now here he is. He says super intelligence has the potential to begin a new era of personal empowerment where people will have greater agency to improve the world in the direction they choose. And he says Meta's vision is to bring super intelligence to everyone. This is distinct from others in the industry who, who believe superintelligence should be directed centrally towards automating all valuable work and then humanity will live on a dole of its output. So he's basically saying like, listen, there are others that want to use this technology for automation. We want to give everybody the benefit of being able to use this technology. And there he is setting that, well, let's say unique vision for now, but I'm actually going to question it. But is that, is that the right read on it?

MG Siegler (7:09)

MG I think so, yeah. I mean it's basically like, look, there's all of these other AI companies out there, including Google by the way, which are, you know, saying that they're, that they're closing in on solving. Again, we'll get to the branding but whatever you want to call it AGI or super intelligence and that, that sense that it's though this nebulous term which I think everyone would agree with, right, that, that it can be used for anything. So maybe, maybe it's a problem because no one really knows then what it's actually be used for. And in some cases that's, that's scary to people, to a lot of people. Right. And so what I think Zuckerberg is trying to frame it as like, we're not trying to boil the ocean. We're not going to use this, this technology to do every single thing under the sun. You know, we don't necessarily, you know, focus on enterprise like some of the competitors do. We focus on personal relationships. And so we're going to use, we're going to get to that technology, to this level of technology and we're going to use it for your own personal purposes, to empower you to use it for your own personal purposes. Right. And so it's trying to be again, an empowering message versus some of the others where it maybe sounds a bit, not nefarious but a little bit nebulous and scary in that regard because it can, you know, who knows what it will ultimately be used for. And so again, the framing, I understand, I'm with you. That I'm sort of skeptical about, yeah, that, that necessarily that framing of it. But again, I think from a pure comms perspective, when you're trying to make this, this message to the market, I think that least makes sense.

Alex (8:41)

So now, yeah, I said I have some hesitancy about going fully along with Zuckerberg saying that they're going to be distinct from the other labs in terms of personal empowerment. Because if you look at what ChatGPT is, I mean that seems to me like that's the goal now. Was ChatGPT a demo, maybe, so that they could sell their API. Yes, but has it overtaken that API business at OpenAI? I'm pretty sure it has. So I think that, like all of these chat bots, if the models improve, if we get to, let's call it Super Intelligence or even AGI, every single one of these chatbots are going to have that property, don't you think?

MG Siegler (9:18)

Yeah, the, the thing that immediately popped into my mind when I was reading that is, is along the lines of what you're saying. It's basically like, it reminds me of trying to say that, look, we've built the first personal computer, but it only can be used for personal reasons. Right. It's not going to be used for work. And it's like, silly. A personal computer, a PC, can be used for anything and it should be used for anything. Right? We use it for work, we use it for personal endeavors. And so it's both. And I think that AI, I mean, in my head at least, it's going to play out the same way that, yeah, we'll have tools like ChatGPT and other services and people will use them for both work and, and personal usage. And that's what's happening right now. And so Zuckerberg, trying to sort of narrow this into just one use case, again, it's like, it feels like unnecessarily confining, and I don't think it's going to play out that way.

Alex (10:10)

Right. So I don't think that Meta will necessarily differentiate itself that way, although you can choose the types of features and the types of functionality you want to focus on to make them stronger. For instance, Dario told me on Wednesday that Anthropic chose to focus its energy on making coding better. And that's obviously, you know, worked out for them or that it's actually shown out, shown in, in the product. So Zuckerberg says everyone having a personal super intelligence will help you achieve your goals, create what you want to see in the world, experience any adventure, be a better friend to those you care about, and grow to become the person you aspire to be. I think he leaves out that you'll also, I think, in their vision, will become a friend to that super intelligence in meta products. But I guess that's neither here nor there now, despite the fact that I don't think that they're going to have the stranglehold on this potential product route. Seems to me that this is, if AI continues a pace, all these things are actually going to be the pro. One of the main uses of the technology, like the vision isn't exactly off. I just don't know if they could do it. But the vision sounds like, yep, that might be where we're going.

MG Siegler (11:20)

Yeah. And remember the other side of this, which is like, Zuckerberg must be looking at the market and knowing, like, what advantages do I have? And the one major one, you know, there's a few. Few. One. I think there's a few that he has. But one of the major ones is the fact that they run services, social networks that are used by billions of people. And so if you believe, you know, that this is going to be, as you're saying, like a sliver of what AI is, they have a distribution advantage that others don't in terms of being able to leverage the technology for these sort of more social use cases. And so I think that he's smartly sort of honing in on that. That fact of it.

Alex (12:01)

Yeah, he definitely addresses how this could benefit the Facebook or the meta business model in a pretty direct way. He says if trends continue, then you expect people to spend less time in productivity software and more time creating and connecting. It's like, all right, so if you're able to get your work done in five hours, then maybe you're going to want to post, you know, your AI slop on Facebook. Now that's a little snarky, but it seems like that's where what he's thinking.

MG Siegler (12:26)

Yeah. And then that's sort of using some of the arguments that are out there from Sam Altman and others against them. Right. Where they're saying, like, look, in the future, this technology is going to enable us all to have a lot more leisure time. And Zuckerberg saying, we know what to do with leisure time. Right. That's one of our specialties. And so we're. We're ready for that future and we're going to help enable it and we're going to help sort of fill in that gaps. As an aside, I'm sort of skeptical of, like, the. The idea of, you know, not necessarily productivity gains. I do think that those will happen. But I sort of go to the analogy of like, when a freeway is overcrowded and so they expand it and, you know, you hope like, oh, well, then traffic will free up and instead just more traffic happens. Right. And so I feel like when we use technology to free up time, we're just going to do more work, you know, in different ways with that time. I don't think that everyone's just going to be sitting around, like, wall e You know, watching the videos on our hovercraft things, I do think that, that, you know, that's, that's maybe again playing into what Zuckerberg hopes happens, but I'm not sure it's going to play out that way.

Alex (13:27)

Okay, but then let me ask you this. Obviously Facebook started on the premise of connecting with your friends on the Internet. That's gone well in some ways, but like, really not well in others. And I'm not even talking about meta scandals. I'm talking about the fact that like, there was a clear shift on the social Internet where people stopped caring about what their friends were doing and they just wanted to watch fun stuff. And we went from the friend feed to the for you feed, and we don't really speak to our friends online. Maybe we do in messaging apps. I mean, we do in messaging apps. So I'm curious if you think, and this is kind of more on the weirder side, but what does Facebook become if it, instead of like using the Internet, instead of enabling us to use the Internet to connect with our friends, it like basically helps us replace our friends with AI friends.

MG Siegler (14:20)

Yeah, I mean, in some ways this is, this is a very fundamental debate. Right. And yeah, it dates to sort of the earlier days of social networking. And I do think also, you know, with, with young kids about try to extrapolate how this plays out. It feels like there's a definite sort of downside scenario that you're alluding to where it's. It. It sort of accelerates the trend of, of loneliness, you know, if you want to call, call it that. And, and people sort of being more insular and spending more time with machines, you know, from obviously computers and phones on down to not need to spend time with friends and not need to go outside and not do face to face time because we have all these new tools that sort of make it more fun in some ways, I guess, to interact with people. It's like, you know, is in his ideal world would. And he would never, of course, frame it this way. But again, if you're just trying to extrapolate out what he's sort of suggesting, it's like, is it better to not go outside and play with your friends and instead do, you know, like a game with your friends? It's built by AI, you know, personalized for the two of you in real time. And you know, again, that sounds dystopian. I want to be mindful that, you know, like there's various different ways obviously that, that people will use these technologies and some of them will be incredible and some of them will be good. And I do think it's like, I, I'm not of the mind that social networking and, and even connectivity is, is fully to blame for loneliness epidemic and whatnot. Part of it. But. But I don't think it's, you know, fully to blame for all that. And I do think it can help in some ways. The, the sort of end state though, of that though is, is what you were hitting at earlier where it's like, it's not necessarily another human friend that you're playing with, but instead, you know, an AI friend who's, Who's. Yeah. Just been generated and sort of what that means for your own internal psyche.

Alex (16:17)

Yeah, it could end up being that we become less lonely but more insular, which is not like a trend that you would anticipate, but there was. We had Elaine Borrow on the show. She's an AI researcher and CEO who used to work at Meta in the fair organization. And she brought up this great point where, like, there are social limits to like, what you can do with friends like you. You really can't like, continue to call a friend at like 3am in the morning. You know, if you're working through a problem or, or something like that, you can sort of make unlimited phone calls to AI and that's fine. So, like, humans have limits, AI doesn't. Is that good? You know, not. We don't know yet, but potentially so.

MG Siegler (17:00)

All right, again, I think that there, there's. You can make the both sides argument to this, and I do think that there will be good elements to it, but it. That's. That nuance is way too hard to try to explain in a, in an open letter. Right. As. As is doing here.

Alex (17:17)

Yeah, that's right. He prefers bluntness and he does end with a very blunt mic drop. Meta believes strongly in building personal super intelligence that empowers everyone. We have the resources and the expertise to build the massive infrastructure required and the capability, and we'll deliver new technology to billions of people across our products. I'm excited to focus Meta's efforts towards building this future. So obviously, like, Zuck has had these moments where he's like, said, like video or, you know, VR is the thing we're focused on. He puts all the company's attention and himself on the project. Clearly that is AI. It does seem like this is the recruiting pitch, by the way. It's like, we got the money, we have the expertise, we have the infrastructure. You know, get on board. Because whatever else you're doing is not going to be around for much longer after we're done with this project. And that is sort of the final note that he sends to the public and maybe to those who've spurned him and maybe those who are still considering his offers.

MG Siegler (18:11)

Yeah, but, and I wrote about this a little bit when sort of the news was first coming out after the scale AI acquisition about what they were trying to build with the superintelligence labs. I'm skeptical that it will work. You know, and we, you know, we've talked about that, but I think that there's a little bit of the Lucy pulling the football thing that META has long had both with the public in terms of, yeah, pivot to video. And all the news organizations rush to pivot to video and then Meta. Facebook decides that they want something else for, you know, their algorithms prefer something else when it comes to engagement. And so, you know, they basically have the, the media organizations and do something else. But the same thing is true with both, I think, users and their employee base. Right. Where it's like, yeah, we're going to focus on this thing. And obviously they pivoted the entire company to be around the metaverse. And it's like we're not hearing too much about that these days aside from as it relates to AI. And again, they're, they're sort of doing some hindsight nar narration about how, oh, it was always, you know, a part of the plan and AI, you know, we. Zuckerberg has said in the past. Right. I didn't real. I maybe didn't realize that AI would take off ahead of, you know, the metaverse taking off. We thought it'd be sort of the, the inverse of it, but there was always a plan that the two of them were going to interact together. And so, you know, again, I think that that's the argument made in hindsight. But if anyone who joined Meta for, you know, the metaverse build out and this was going to be the future, like, what are you thinking right now as. As you have colleagues who are getting offered hundreds of millions of dollars potentially to build out AI, I don't think any of the. The Metaverse team is getting those packages right now.

Alex (19:49)

Yeah, you're big sad. I mean, they changed the name of the company to Metaverse or Meta. You're. You've been laboring away on the VR goggles, and some guy who's been working at 2 years on AI at OpenAI just got a hundred million dollars to come over. I mean, I'm sort of being facetious here, but that wouldn't make me happy. Although I sort of think you, you sort of respect the game. Like, if LeBron James comes to your team, you know, you know he's going to make you better. But I, I don't know, it's. It's hard to see all these. LeBron James is coming over and you're still in the Metaverse unit.

MG Siegler (20:27)

So the, the one other thing I would just add to this that I was just reminded of is we often, you know, bring up. Yeah. The meta, the metaverse element of it as, as a easy one to. To mention that Zuck was, you know, obsessed with. And then sort of quickly change focus. But remember, he didn't change focus right away to AI because it obviously took a little bit for it to come around. At first there was the focus, then became, if I remember right, in terms of order, at one point he was highly focused on like encryption and personal one on one conversations versus, you know, he wrote this whole memo to private. Yeah, privacy. Yeah, yeah, yeah. And so that was a focus for a few months, it seems like, because then, then crypto stuff started happening. Right. And they had a whole team that they spun up. That was early on it. And like Kevin Wheel was on that team, if you recall. And there were many other people within META at the time who were on that team who, you know, it seems like they were going to be at the forefront of, you know, a new crypto boom that of course, they were just way too early for, if you want to consider it happening now. And Libra, I think, was. Yeah, the, the name. That's right. Of the product that they were working on. But again, that was a focus for a while until they just totally got rid of that because it was not advantageous to them anymore.

Alex (21:45)

That's right. And so Pivot to privacy was their attempt to capture where the social sharing was going. Like I mentioned earlier that we weren't sharing in the feeds anymore and all sharing was happening in messaging apps. So that was their way of saying that's where it's going and we're going to try to be at the forefront of that. And that, you know, in some ways worked. They have WhatsApp and that is the leading messaging app in the world. So I think there is. I mean, they had obviously bought it years beforehand, but clearly put a lot of product focus there, for better or worse. That obviously also just introduced advertising after promising they would not. So I think there is some merit in running around what. From what seems like on the Outside as chickens without a head, trying to go trend to trend. There are definite stories of big companies in the past who've been like, oh, we're too cool for that next new trend. And then, you know, they're making scanners and copying machines as the world has moved on. So I think that that Meta is, is, looks a little ridiculous for the strategy, but there is some wisdom to it.

MG Siegler (22:53)

Yeah. And you know, I do think that because, and this is a big part of, of Zuckerberg's pitch, right, because they have this fundamental underlying advertising infrastructure across their different social properties. They can take a lot of swings, whereas other companies cannot. Right. And they are, if you remember, like Google used to have, definitely the, the notion thrown at them that they were a one trick pony, right, that they could only ever do search ads, and that was the only business. Now it's still obviously the primary element of the business, but they've done a pretty good job, I think, you know, diversifying in many ways. Right? They have the cloud business, you know, they have Waymo now, which is up and coming. They have all different sorts of, of ways that they can potentially make money. YouTube, that's, that's a different form of advertising, but still it's, you know, a different, a different product line now that they have, that's fully monetized, which is incredible. And Meta still hasn't found that yet. Right. Like they've been trying with, with the Metaverse stuff and selling VR goggles and selling different types of products, but still almost all of it comes from social feed advertising right now. But again, you want to take these swings while you have that in the position of power. And if you believe that that business is going to get disrupted in some way, be it by AI people using other products, people spending more time on YouTube or Netflix and whatnot, you know, you want to get it done while you can. Take all those swings while you can.

Alex (24:31)

Okay, so this entire conversation we've been talking about Meta's super intelligence effort, personal super intelligence. And as with many conversations, we have yet to define it. But that is intentional because we are going to make time to say, what is this word? Why do people keep using it? And what could it possibly mean? And we're going to do that right after this. Hey, everyone, let me tell you about the Hustle Daily Show, a podcast filled with business, tech, news and original stories to keep you in the loop on what's trending. More than 2 million professionals read the Hustle's daily email for its irreverent and informative takes on business and tech news. Now they have a daily podcast called the Hustle Daily show where their team of writers break down the biggest business headlines in 15 minutes or less and explain why you should care about them. So search for the Hustle Daily show and your favorite podcast app, like the one you're using right now. And we're back here on big technology podcast MG Siegler. Monday of first Monday of the month edition. You can find MG's writing@spyglass.org and speaking of the definition of super, super intelligence, MG, you actually have a piece on this, the endless rebranding of AI, basically saying that for a while AI was good enough, then people went to Gen AI, then they started talking about AGI and now AGI isn't enough and now we're talking about super intelligence. What's next? What, what does super intelligence mean? Or is it purely marketing hype?

MG Siegler (26:02)

I mean, this is so obviously the term has been around for a bit. It first really came on my radar, I think actually, when Ilya Sutskever spun out and made his company called Safe Superintelligence. Right. And presumably he did that, obviously he did that on purpose, but presumably he did it also to help differentiate from what OpenAI was doing. Right? They were, at the time, it was, all the talk was the march towards AGI. Famously now they had it baked into their contract with Microsoft, which is still an ongoing dispute, it sounds like. And so, you know, they're deciding like, okay, well, AGI nebulously defined as sort of computers reaching human level intelligence, though some would disagree with that. And then super intelligence is a level above that. Right? It's, it's, it's going beyond what humans are capable of. Again, there are depending on what you read, depending on who you talk to, people disagree about this. No, the part of the problem is no one ever really defined what AGI itself was. And then, you know, going back again as you did like with, with AI itself, it's like that was the all encompassing thing. But then we got all different sorts of like subsections of it because people were, wanted to be more focused on and they thought AI was, was too nebulous a term. And then AGI came along and then AGI was too nebulous a term. And so now super intelligence. And now super intelligence is too nebulous a term because we have personal super intelligence and we have safe super intelligence and we, and Microsoft is working on their own variants of, of super intelligence that they, that they want to talk about. And so it's it's getting a little silly. It feels all. It just is obviously all marketing at this point. And so I, I do feel like that, you know, you gotta at some point pin people down to say, like, what are you actually trying to build? And what, what is the outcome of that going to be?

Alex (27:58)

Yeah, I think we can agree here and this is something that we've been talking about in the first half. It's the same damn thing. It's the same thing. Everyone's building the same thing.

MG Siegler (28:07)

But people would argue with you about that, right? Because they'll say, no, AGI again, is, is sort of human level intelligence. And we have it. We're close to that maybe, but we haven't quite gotten there yet with, you know, all the various math tests and, and the different, you know, tests that they've built to, to prove that. And super safe or, sorry, regular super intelligence is just a level beyond that. Like, there's lots of people who would argue about that and lots of people would word that they're the same exact thing.

Alex (28:31)

I'll stand on the table here and say it's the same thing. I think it's. If there were different techniques, I think this is really what it comes down to. If there are different techniques to build a AGI and super intelligence, I would say, okay, sure, you know, Facebook's building super intelligence over here and OpenAI is stuck building, you know, you know, stale old AGI over there. But they're, they're just training large language models.

MG Siegler (28:55)

Yeah. And it, it's wild that we're trying to define the sort of offshoots of any of them when we haven't defined the first part of it and dating back to the, you know, original sort of definitions of these things. So it's, it's a little bit silly. And that's obviously why I wrote the post. Once I saw that Microsoft, you know, was jumping in the ring as well to try to, to come up with their own individual branding for super intelligence. And then of course, you could see it. So Zuckerberg's new memo that we're talking about, it's titled that. Right. But he started dropping this. The first time I heard him mention this was in an, an interview with Jessica Lesson of the Information, where he just started, like, to casually mention personal super intelligence and it's like, oh, did he, is he just trying to, like, say something offhandedly about how they're, you know, they have a sort of micro focus? But no, he just kept saying it over and over again that they clear we're going to try to make this a branding thing for meta.

Alex (29:56)

Yeah, I mean it's, I think that it's very exciting when the word super is in there. I mean, really.

MG Siegler (30:01)

All right, when are we going to get Ultra Intelligence? And I'm ready for Ultra, Super, Ultra Mega Intelligence. It's going to, it's going to just blow away what we had. Remember when we were talking about AGI?

Alex (30:11)

Forget that we were such losers back then. Now Super Mega Ultra Intelligence, that's where it's at. One interesting thing I saw in your story was that Microsoft cannot actually work on AGI legally. This is what you write. The pesky OpenAI contract says as much, which sheds light on the talking points that Mustafa Suleiman delivered over the past year or so that Microsoft is happy to see the frontier of model work to OpenAI. So maybe this is, maybe this is meaningful that like, well, Microsoft can't build AGI because OpenAI is doing it, but it can work on Super Intelligence because that's not in the contract.

MG Siegler (30:49)

Yeah. And so this I feel like is definitely under. Talked about. It's been reported before, but I feel like now because Open AI and, and Microsoft are maybe in the midst in the heat of, of a new negotiation over the AGI term and, and how that's going to play out for, you know, their relationship going forward. It has come to light again that, yeah, apparently a part of their original contract with, you know, the quote unquote clause in it around AGI was that Microsoft said that they would not, you know, themselves go to work on, go after AGI and working on that. And that in hindsight brings up all sorts of, yeah, interesting points. I think, you know, when you've talked to even Mustafa Suleiman, he's brought up the point of like, yeah, you know, we're happy to let OpenAI work on the, the cutting edge, you know, foundation models and we'll just, we'll sit back and work on sort of more tailored, custom tailored one. When the reality was, yeah, they're, they're technically not allowed to work at the cutting edge if it's going to lead to AGI. Now they could say maybe it wouldn't, but, you know, everyone else would probably disagree with that. And I also think at an even higher level, part of the reason why, I would imagine that you even saw Sam Altman sort of pivot his talking points from AGI to superintelligence at one point in various memos that he's written himself was because of, yeah, the clause in the Microsoft contract. And it was clearly a point of tension, you know, between those two companies. And it's like you've heard Satya Nadella talk on, on, I think on podcast about like the, you know, I think at one point he called it ridiculous, the notion of sort of, that we were close to AGI. Right. Because obviously he's very incentivized for them not to be close to that because it would potentially sever the business terms with, with OpenAI. And so it was almost like, was Sam Altman sort of throwing him a bone by starting to talk about other things other than AGI and rebranding as Super Intelligence? But yeah, the. If the clause is in there originally that Microsoft is not able to work on AGI and now they're, they're happy to have this rebranding too, where Mustafa Suleiman can work on all, all the variants of Safe of superintelligence that he wants to, because it's not AGI.

Alex (32:57)

It sort of brings us to this point that we're talking about how Microsoft and OpenAI are linked and they have these like, weird contractual terms. And you also point out that something that's not talked about enough is just that Big Tech owns so much of this AI moment, even if they go by, you know, different names. So this is the list that you put together. Nvidia own stakes in OpenAI, XAI, Mistral, Perplexity, Cohere, Scale AI. Oh, that's a bunch. I didn't realize they had stakes.

MG Siegler (33:26)

It's even more than that. Those are just like the major ones that I was pulling out. They own so many stakes in everyone.

Alex (33:32)

So Microsoft owns Stakes in OpenAI and Mistral, Apple owns stakes and none of the big AI startups. But, you know, there's potential for, you know, maybe perplexity. Okay, I'm going to let go of that dream at this point. Google owns a stake in Anthropic, Amazon owns a stake in Anthropic, Meta owns stakes in Scale AI and Safe Super Intelligence now, and Oracle owns a stake in Cohere. You say this is a lot of hedging. Does that mean basically that like, if this AI moment takes off, like, Big Tech is just going to be, you know, they're going to be good, whether it happens in a start, whether they build Super Intelligence at home at Meta, or whether they, a startup actually is able to do this?

MG Siegler (34:13)

I mean, obviously, to be clear, they want to do it themselves, right? And they want to capture that full opportunity. But it is, it is interesting to me that this isn't talked about all that often except around, you know, when new fundraises happen. In particular with Anthropic, right, because Amazon and Google own such relative large portions of that company. And famously Anthropic, you know, apparently built into their fundraising documents that those companies can only own up to a certain threshold because they didn't want to be beholden. You know, famously When Dario left OpenAI, there was some talk that he didn't like the Microsoft element getting involved right, with OpenAI and what that was going to, to do to the mission. And so, but yeah, all of these, all the big tech companies, aside from Apple as mentioned, you know, basically have their, their stakes in these different companies and some of them with multiple stakes now because these companies have had to raise so much money. And I do think if you were just to sort of extrapolate out in the ultimate success state of AI and say, say that OpenAI and anthropic and maybe a couple others are, are the next multi trillion dollar companies, if say Microsoft again in the negotiations that they're going through right now, if they end up owning one third of OpenAI and it's one day worth $10 trillion, you know, that's, that's meaningful money to, even to Microsoft, it's already meaningful money to them, you know, because that company is so highly valued. But it's not, you know, it's not more meaningful than a lot of their other sort of core businesses. But again, this is relative early days, if you believe this is early days of AI and these players own these giant stakes, it will end up being a huge, huge element of those companies. And I was reminded of when back in the day when Microsoft invested in Facebook before they went public and people were like up in arms about the deal, thinking it was such a bad deal, like Steve Ballmer was doing another boneheaded thing, ended up being one of the best deals that he ever struck. Certainly, you know, easy of course to say in hindsight, but I think it was a savvy move, you know, because they did it alongside a partnership. I think it was involved with, with ad sales and various other things at the time. Maybe Bing was involved in it as well. It was a long time ago, but, but I do sort of view it through that lens now. Their mistake was selling off that stake in, in Facebook, you know, a little bit after perhaps it went public. Whereas now that would be worth billions and billions of dollars. And again, if Microsoft, if Google, if Amazon hold on to these AI stakes and these companies end up being Worth trillions of dollars. These stakes themselves could be worth trillions of dollars down the road.

Alex (36:52)

Yep. You always got to get Bing involved. That's important. Can't leave Bing out of the equation. But it, you know, it's interesting because it, it really underscores how much money, resources, attention, like we just spoke about how much money and attention Zuckerberg is putting into this. We talked about, of course, like these massive investments. Like when you talk about Google has some of Anthropic, Amazon has some of Anthropic. Actually It's, I think 3 and $8 billion respectively. They own something like you had this in your story, something like 30% or, or more of the company. Actually, Google and Amazon own more of Anthropic than Microsoft owns of Open AI. So it's wild. And I just wonder, I mean, if we go back to like everyone building the same thing, is there a way that these bets pay off? Like, what would it take? So you've spent a lot of time as an investor, what would it take for these bets to pay off? Like, what do we need to see for this money to be money well spent?

MG Siegler (37:53)

So, and just to be clear, yeah, Google and Amazon combined, I believe if my math is correct from all these court documents that I sort of went through, but I believe it's, it's roughly correct that I think them combat those two combined own something just north of 36%, whereas Microsoft again, potentially in this scenario, would own 33 or around that percent of OpenAI if and when they can convert to actually have equity ownership in the company. To answer your question, though, yeah, what would, what would it take? Takes a business model first and foremost. I mean.

Alex (38:27)

Yeah, that'd be nice.

MG Siegler (38:28)

You know, both OpenAI and Anthropic certainly are, it seems like are growing well, you know, on the, from an ARR perspective, you know, their models are obviously slightly different, but they're doing a good job in different markets sort of selling, selling their wares. But it's certainly not enough to turn either one of them profitable at the moment. And so they're gonna need, they're gonna have to do a number, a number of different things. Either they have to keep growing at the incredible growth rates that they've been growing at. And that's, you know, possible up to a certain extent. More likely that they're going to have to add other layers to their business, other stools of their business to figure out how to, to make sort of the money work. I think the main wild card though is much like Google back In the day it might end up being that these companies in the ultimate success state, if they're able to reach it, end up creating sort of new models, and not necessarily new that we've never heard of before, but much like Google and even, you know, meta to some extent, right. They basically created new forms of advertising that ended up being more lucrative than previous forms of advertising because of search, ads because of intent, right. And then with meta because of the feed. And so these are different forms of an old school version of, of monetization. But so what does that look like in the Future version of AI? And you know, OpenAI has famously sort of said, right, that Sam Altman didn't want to go down the path of advertising. And I mean I would chalk that up to, I do think that they will eventually go down that path, but I also chalk that up to the fact that again, I think that if they go down that path and if it's meaningful to them, it will look different than what sort of search advertising has historically looked like. I think there will be a part of that because obviously search is a part of, of chat GBT right now. But I think it just look, it probably has to look different. And again, you ask about what it takes to make these companies ultimately successful. I think it's going to be multi, sort of stools of their business. So not just selling APIs or not just selling access, you know, and premium versions and whatnot of their products. I think that they're going to have to have a lot of different things, including probably devices. Right. Obviously we know OpenAI is working on that. But I do think that there will be different flavors of advertising, newfangled versions of different old business models is what leads to their success with the investor hat on, with the vc hat on. How do you try to model that out? I mean again, you can model out where you think the growth rate is, you know, just of the current business and what that looks like. And I think OpenAI has said in their models that they're going to get to profitability by 2029. Delay again, having had some experience now with, with OpenAI in particular on the investor side, but with other companies just, you know, generic X companies, say those models that are five year, ten year horizon models, those never play out the way that they're modeled out to. Now there can be upside to that. Maybe they play out better in some cases, but they never exactly like it. Right. It's just, it's just to try to paint a picture of how you can get to A space where you could say, be profitable even when you're burning billions and billions of dollars. This is just the extreme version of that with AI, right.

Alex (41:40)

So I spoke with Ravi Matra from Lightspeed for the Dario profile that I wrote and I said, tell me how you thought about this investment and I'm going to get it like just directionally accurate. It's not going to be precise. But he basically is like, well, you know, we took a look at the, the entire pool for like knowledge, labor and then said well, could this just kind of like you know, either augment or replace that?

MG Siegler (42:04)

Yeah.

Alex (42:04)

And he said that's a. Yeah, the market is 15 to 20 trillion dollars. He goes, you work backwards and just say at 60 billion or 100 billion, could you get a venture style return? You absolutely could. Sometimes it's about how you size the markets top down. And then he told me that they put a billion dollar check into anthropic. So it's just fascinating how these, how these, it's, it's so unknown and, and such wild projections to get to the numbers you have to get to.

MG Siegler (42:31)

I'll give you one just example of like, you know, an last generation of, of company that sort of this, this played out at that, you know, that I was a small part of which was, you know, around an Uber investment where it's like you're looking at the market, they back cab market at that point and it's like how do you do what you're talking about basically the TAM analysis, right, the total addressable market. And, and how do you think about that? And with, with Uber back in the day, it always had to be like that there would be something else to it. And you know, there was the notion, I think the early notion of what UberX would become where it, you know, more democratizes the model and it's not just about black cars. But it wasn't fully baked yet, it wasn't rolled out yet. And so you sort of had to buy into this vision of it. It ended up obviously working out that way. But there still were other elements that were key to what they were doing, including things like Uber eats, right, which came along, which you never would have sort of envisioned was, was necessarily a part of it. There was some inkling like, yeah, could they be like the next version of, you know, again, like a democratized FedEx or something like that. Right, because they have all these drivers on the road and you can, you can move parcels around and move different things around and, and, but it's all just theoretical and so yeah, to do like this, these market analysis and figure it out. But it's all very silly to look back upon at the end of the day because no one actually knows, including the companies, right? It almost always goes back to the notion of like build a good product. If people love using it, they're going to continue using it. And that doesn't necessarily mean that you're going to figure out the right model for it, but if you have enough users and you figure out a way to monetize those users, it's going to be a massive opportunity, obviously. And at least the good news for these AI companies, unlike some of the other sort of, if you want to call them, VC subsidized businesses back in the day, they have models that are working, right? Like there were so many different companies even just a few years ago where again, it was VC subsidized, they had no actual models and it was just like, like let's get to scale profit thing, right? And now at the very least we have, you know, money coming in and it's just a matter of are they going to be able to ever slow down the spend that they have to do to train these models in order to get to a scale at which they can actually finally sort of equalize that a bit.

Alex (45:01)

And in that context, how would you analyze the investments in people that they're making? Because think about it this way, something Mantra told me Amazon went public at $400 million. Mark Zuckerberg is handing reportedly billion dollar offers to people.

MG Siegler (45:17)

Yep, yep.

Alex (45:18)

So what would you need to do to get the payoff on that?

MG Siegler (45:24)

This is where I am sympathetic to Zuckerberg's arguments. You know, he's made the argument that basically it's, it essentially boils down to, and I wrote a post about this, that it's all relative, right? Like okay, if you are meta and you're spending whatever it is, $75 billion on CapEx right now per year on this, on infrastructure build out for AI, does it not make sense to spend, you know, some subset of that on the people who can actually make this work? And then it's just, you know, it sort of becomes like this, this, this math equation of like, well, what makes sense. And you could certainly make the argument that to date the human level of investment has been way under index versus what the, again, the CapEx or the, the infrastructure has been. And it's, and it's a weird dynamic, right, for reasons that we were talking about before where he's, he's creating this, this Weird disturbance in the market because it's totally changing, you know, what the historical norms have been in terms of compensation. So you can have people who are, you know, getting paid what the quote unquote normal rate was for an engineer before, which is say hun, in the hundreds of thousands of dollars at one of these tech companies and now you have people getting paid hundreds of millions of dollars potentially to come work on this. And again, trying to be sympathetic to Zuckerberg's position here, if you're needing to catch up in AI, you're spending $75 billion plus a year on infrastructure. The amount that you're spending on people is going to be, even, even with these hundred million dollar contracts is going to be such a small subset of what you're spending on infrastructure. And if they're a key ingredient to making it work, you got to do it right.

Alex (47:04)

And so we've already poured one out to the, you know, poor engineers who are working on the Metaverse. But, you know, part of the title of this episode is Layoffs and payoffs. And what do you make of the fact that, that we're seeing this moment in the tech industry where like literally tens of thousand people, that tens of thousands of people are being laid off as these mega offers come in. It seems like they don't really need to lay off those people from a financial standpoint. So why would they cut so many, I mean, thinking about Microsoft in particular.

MG Siegler (47:35)

Yeah, and because Satya Nadella wrote a memo about this which he released, internal memo, which he released publicly, I'm sure because it was going to leak. And so, so, you know, they, they wanted to, to get ahead of this anyway. But he's basically trying to explain they've done, I think the number is in total now 15,000 people have been laid off from Microsoft over a couple rounds or a few rounds this year. And that's, you know, again, in the same time as we're talking about that they're, that they're spending insane amount of money on CapEx and, and just to hire people like Mustafa Suleiman to come over, you know, and acquiring his company and, and so know, how do you, how do you sort of square that circle? And, and Satya Nadella, you know, basically tried to do it, that calling sort of tried to do it. He called it an enigma, I think of a, of a time and, and that it doesn't make a lot of sense on paper but that basically, you know, we're in this transformational moment with AI yada yada, what everyone Says, But I do think like there's a, there's a number of things going on here, one level deeper, which is one, I do think that we're businesses in general are sort of looking at the landscape and figuring out do they need all of these people, tech companies in particular. Now almost all of them are around 100,000 or more people, you know, on their payroll. And a lot of those people are doing things which, you know, the unfortunate truth is that the, you know, the internal powers that be, the info, the leadership infrastructure probably views them as like, not necessarily they're not bad people, but they're doing stuff that was last year's innovations, right? Or they're, they're doing stuff that they, they might think that AI is able to eventually replace, if not now, but sooner rather than later. I also think that there's a part of it where, look, they know that Wall street at some point is going to get skittish on this Capex spend and especially if the AI revenue isn't, you know, growing in, in concert with it at some point soon. And so I do think that this is a way to throw a bone to Wall street and say like, look, look, even though, you know, it looks like that we're being sort of wild on our spend when it comes to Capex, we are being prudent financially. We're thinking about, you know, how, how we, you know, basically organize the business overall. And, and that includes, you know, letting go of some of the people that we've had previously that we feel like we don't need anymore while we continue to bring on new people that we do feel like we need, you know, from, from the AI perspective and, and building that out. And so the, the weird things of how this plays out, to me it's almost like a microcosm, right, of like the, the overall debate being had about, you know, as I titled my thing, like sort of the haves and have nots.

Alex (50:10)

But it's a great sort of. No, you, you write the have lots and the have not, which I think.

MG Siegler (50:14)

Is just it really, it's above just having, it's having.

Alex (50:17)

Right.

MG Siegler (50:17)

More money than as I, as I put, I think at one point it's basically they're getting offers more money than, than anyone gets offered for any position, including the CEOs of these companies. Maybe there's some star athletes who make, you know, something comparable when you, when you consider their endorsement deals alongside whatever they make in salary. But it's just an incredible, incredible amount of money. And how do you weigh that against. Yeah. These layoffs. And again, it's like, I think of it as like sort of a microcosm of. Yeah, like the, the world in which we live in which, you know, there's the extremes of society with the ultra billionaires while people are struggling, you know, on the ground on a daily basis. And, and the microcosm that. That can be within a company itself. What does that lead to in terms of internal politics and weird inner company dynamics? And I think, you know, that's part of why I think Satya Nadella and others have written that basic memo of like, I think that they're trying to get ahead of that. And also lastly, I would just say because we've seen this a few times now, and I think from. From Andy Jassy and others, they're basically giving the message that, look, you got to incorporate AI into what you do or, or you got to get off board right now because this is coming and this is how we're all going to do business. So do it right now or else you're gone.

Alex (51:30)

Yep, you go full Tale of Two Cities. At the beginning of that piece. It was the best of times, it was the worst of times. I mean, that is the way to start that piece. Okay, so let's end here. AI for writing. It's pretty controversial. I think AI is getting to the point where it's starting to write adequately. Not well, but adequately. I don't use it for writing, but when I read AI written stuff, I no longer have a gag reflex. But you write, I think, something very, very spot on about what it means for our society or our lives. And it's that writing is not just a way to communicate information. It's a way to organize your thoughts. It's a way to think. And so we focus so much on the output of AI writing, but very little on the input. And that's where it's going to hurt if people start relying entirely on these AI tools to convey their thoughts. So kind of take us through your thinking there and talk a little bit about whether you think AI writing is going to be a net positive or negative.

MG Siegler (52:32)

Yeah, this. This came from me just trying to extrapolate out how I would view using AI to write, which I don't like you. I don't right now. And it's like, would I ever. And I was trying to think through, like, yeah, how good is the technology now? And to your point, it seems like, you know, it's getting good enough for a lot of different types of writing. And I've also been thinking a lot about one thing I hate is email, as many people do. But I've long written about my sort of dislike of it. Famous long time ago, 15 years ago, I quit for a long time doing email and I wrote about it in TechCrunch when I, when I wrote there back in the day. And I got a lot of, a lot of flack for that story. But, but I think it also resonated with people because it's like, well, you actually need to do it. And I think we're getting to the point with AI where you probably don't need to do it anymore, right? Like, because you could basically have AI write your emails for you. And then I do think eventually the way that it plays out is that then you have AI reading those emails on the other end and sort of it ends up these bots sort of writing to other bots and then sending you like a to do list of whatever needs. The action items need to be from that. And so I was thinking about it from that perspective. But then I, then I go to, you know, my actual love of writing and sort of what I, what I do and why I love to do it. And I would never use AI to write, say, an article about even AI for me, because that would take away what I, the value I get out of actually writing, which is writing, like many people, it helps me think, it helps me form my own thoughts. And so I do think that that's true of a lot of people, even if they don't necessarily realize it. I think that people who write for a living or write a lot do realize that real element to it. But I think people who don't probably gloss over that fact. But I do think as a society, I would imagine that it plays out in a way where maybe there's some level of writing like email, like the tedious stuff that does get automated away, but the, the sort of, certainly the creative endeavors, but also even just, yeah, like the, the memos that, that help you sort of formulate your own thoughts, those don't go away because it's just about the process. It's just as much about the process of writing as it is about what you put down on paper, what goes on in your head and how you formulate those thoughts.

Alex (54:44)

It does make me wonder about whether, you know, I see the value obviously in writing. But I also know what's happening right now where, like there's these great screenshots that go around Twitter of like, professors scorning their students for like being late on their assignment and ending it with chat gp Ask, ask, Chat GPT. Like, they're copying and pasting it directly out of the chatbot, and those students are going to be like, okay, well, here's the assignment. And then they're going to paste their assignment and it's going to say, ask ChatGPT. So we're just going to be a society, I think, of just people shuffling AI written text back and forth, which like. Like give it. I mean, maybe you're right. Given the amount of tedious stuff that we've been writing in our lives, that might not be the worst thing. But I think there is that risk of the fact that, like, yeah, we're not going to think as deeply about things anymore without writing.

MG Siegler (55:34)

Look, the last thing I would say about that is student cheating is nothing new. It's always existed. Right.

Alex (55:39)

Just began with large language models, calculators.

MG Siegler (55:43)

And everything, you know, before that. And so I think ultimately, you know, that will sort of suss itself out in some way. I do think it's a real issue, obviously, because of how good these LLMs are and how new this, you know, this, this whole wave is right now. And so it's going to take a lot of learning curve to get to the point where we sort of, again, reach an equilibrium of where it, where it makes sense, where it doesn't. But I do think at the end of the day, like, if you're doing something for your own, you know, purposes, be it writing, be it many other different elements of life, like, you're only robbing yourself if you're using, like, a tool, you know, to do it in an automated fashion. So, yeah, for maybe for some writing assignments that you don't want to do, fine. You didn't want to do them, that's fine. But ultimately there's going to be something that you do want to do or that you get value out of that I think that that will work itself out.

Alex (56:35)

I agree completely. All right, folks, the website is spyglass.org MG Siegler joins us the first, first Monday of every month. This is part two of what I hope will be a long series. MG Great to see you again. Thanks for joining.

MG Siegler (56:49)

Thanks so much, Alex. Talk soon.

Alex (56:51)

All right, everybody, thank you for listening. I'm Judd Massad. The CEO of Replit will be on with us on Wednesday to talk about vibe coding. What is it? Will it work in the long run? Is it sustainable? And what will it change? So stay tuned for that and we'll see you next time on Big Technology. Podcast.