Anthropic’s Potential, AI Video Gets Crazy, Market Bubble Approaching?

0:00Anthropic is raising at a new$170 billion valuation. Let's talk about the company and its potential. Plus, OpenAI hits 700 million ChatGPT users. Is AI video actually underhyped? And is the stock market in bubble territory? That's coming up on a Big Technology Podcast Friday edition right after this. Welcome to Big Technology Podcast Friday edition, where we break down the news in our traditional cool-headed and nuanced format. We have a great show for you today. We're going to talk about Anthropix' new massive funding round and big valuation. We'll also cover my interview with Dario Amode this past week and talk a little bit about the takeaways there, where Anthropic is positioned and what the company's promises.

0:40We'll also talk about OpenAI's 700 million chat GPT users, a great section on AI video and whether that format is underhyped, and also the stock market rip-roaring. Microsoft joins NVIDIA as a$4 trillion company. Is it in bubble territory? Joining us, as always, on Fridays to Do It is Ranjan Roy of Margins. Ranjan, great to see you. Welcome back to the show. Good to see you. I missed you last week, but it was nice to listen to the Dario episode on my plane ride back from Tokyo. So excited to talk about this. Okay, great. So on that note, I just want to welcome all of our new subscribers who've come in.

1:14We have a bunch of new people here. Just to give you a rundown of what we do here on Wednesday, we have a big flagship interview with people like Dario. Next week, Amjad Massad, the CEO of Replit, is coming on. And then on Fridays, Ranjan and I show up here and break down all the week's tech news. So we're very, very glad to have you here. All right, Ranjan, I actually thought it would be good to start this week just to talk a little bit about my takeaways after doing a couple months of reporting on Anthropic, and then we can get into their fundraising. So let me just start here. I think that Anthropic is a very impressive company.

1:47The one thing that I kept coming back to when writing the story about Dario and the company is just that you have this competition coming from all sides, competition obviously from OpenAI, but also from Meta, places like Google with DeepMind. And Anthropik has found a way to sort of make its way into this conversation, starting really later than OpenAI and without the resources of the big companies. And I think there was a great quote from Eric Schmidt that I didn't include in my story. I had a conversation with the former Google CEO for this profile of Dario. And he says this, he says, my best description of this is that it is an all out brawl.

2:24It's really a brawl between very well capitalized companies, including my friend Dario's startup. The fact that Dario is in the brawl is extraordinary. And if you ask me what I predicted, if I predicted he'd get there, the answer is no. How would he raise the money? How would he get the partnerships? And somehow he did. And I think it is interesting, despite the fact that Anthropic has 11 billion plus dollars in funding from big tech, that it's been able to compete in this market. What do you think? No, I think I love this all out brawl. I guess I'm not as surprised that Anthropic has been able to kind of compete and raise in this market.

3:00Because again, from a product perspective, we were clawed boys back in the day. Clawed Pro, maybe not subscribing right now, but they made that decision. Claude heads and big boys. Claude heads, big boys. These are important details. I thrive on accuracy here. But I think the most impressive thing that Anthropic has done is actually pivot into where they see opportunity. We've been talking about this the last few weeks. And I'm curious kind of your takeaway after the conversation around Anthropic is making the pivot towards coding, software engineering, going after technical folks. and I think they're strong.

3:42Everything you see about Cloud Code, and this is not me, which is why I'm not using it as much anymore and I can tell, but finding that very large market opportunity and niche and trying to win there rather than trying to do everything, I think they're pretty impressive right now. So I think when you're not as well capitalized as a company like Meta, for instance, you have to make really strategic decisions. And I think speaking with Dario and those around him, I think Anthropik has made a couple of really good decisions in terms of where it's going to compete, really strategic areas in terms of where it wants to build its models and its businesses.

4:17So first of all, I think one interesting thing Dario said was that they are all in on the business use case for two reasons. I think maybe the first one I'll just impute a little bit is that if you're very good at business, you're going to make a lot of money and you need money to run in this type of industry. But the thing that Dario said that was interesting is that if you focus on business use cases, you have an incentive to make your models a lot better. For instance, if you're building a chatbot, you just need to sort of cater to the standard uses. And what he said was basically that if you make your model move from, let's say, undergraduate biology to graduate student biology level, the average chatbot user isn't going to see that, but the average business customer in, let's say, the pharmaceutical industry really will.

4:59And so that incentivizes them to build better models, and it's also good business. And I just found that to be really smart. Well, so it's clear Dario's team model here for new listeners. He is the most hardcore of all on team model. But go ahead. Yeah. For newer listeners, a regular debate between Alex and myself is I still believe the model is important, but the overall product and experience actually is where you see the real differentiation. So that's interesting to me that that is how they're kind of approaching this. Because remember, Claude artifacts predated ChatGPT Canvas. Like they kind of invented that.

5:37So to me, they have innovated on the product side. So it's interesting to me that he's still all in on the model is where this brawl is going to take place. Definitely. And it's also where you direct the model. So I asked him about the coding use case, which, as you mentioned, is an exploding use case for Anthropic. Although we'll see what happens with GPT-5, and we're going to get into that in a bit. But his answer on coding was also really interesting. And that was that, A, if we build great coding tools, all the engineers in Anthropic are going to use them. We're going to get faster as a company.

6:09And B, if you provide a useful AI tool to engineers, they're going to adopt it really fast. And that's proven to be the case. So it's not just the model. It's sort of the way that you train the model and how that outputs in product. And I think that's also a very wise bet for Anthropic that's paying off. Yeah, I mean, I think that's the success of Cursor. Like the whole, you know, epithet that something is a wrapper has always been wrong to me. The Cursor skyrocketed because it just was a better experience. It provided better output relative to the competition at the time. But overall, for software developers, it just was an overall better way to develop and code and engineer.

6:50So I think that, yeah, the two are inextricably linked. But I'm curious, what did you take away in terms of where Anthropic is going? And we're going to talk about the funding in just a moment. Clearly, there's momentum. But what does he really see as the future in your takeaway? I mean, I think that one thing that's clear is that Dario, this sort of does link to the funding, believes that he's the firmest believer in the scaling laws, which is that if you add more compute data and increase the model size, you're going to get predictable exponential results. And so I think that's basically the way that they want to move is they have some near term business interests to get them to a point where they can build bigger models and more efficient models and effectively trying to build a supermodel like I think everybody is.

7:37Like it's one thing that's going to come up. I have M.G. Siegler coming on. We have M.G. on the first Monday of the month. And he writes this great newsletter called Spyglass. And we're going to talk about the fact that all these companies are effectively working towards the same thing. Like call it super intelligence, call it, you know, AGI. Effectively, they're working on scaling up large language models and adding sort of the scaffolding around them to make them useful. So I think that's really where they want to go is they believe that they can build the models best. They want to raise the money and build the biggest and best models.

8:10And then anyone's guess what happens from there. But we've seen these predictions from Dario that he has a belief that there's going to be like real economic value there and also some like potentially scary outcomes. He became somewhat famous for saying that AI in the next couple of years could wipe out 50 % of white collar entry level jobs. I don't agree with that. Maybe that's a little bit of marketing for Anthropic like we talked about. But I really think labor augmentation and labor replacement is going to be where their business is. Well, after the interview, do you feel that was marketing or did you walk away that he truly believes this, is worried about it, is trying to do something about it?

8:49So, yeah, and I'll note it wasn't just the interview. There were 24 plus interviews that I did leading up to this story about him. I do believe that, yeah, he both does really truly believe this. He's seen these scaling laws work in places like Baidu and OpenAI and now at Anthropic. The data that Dario is looking at all points to this continuing to improve. And in fact, like Demis Asabas from DeepMind said, yes, scaling is really helpful, but we're seeing some. Diminishing returns are the words that he uses. It's slowing. And the people that I spoke with at Anthropic, like Jared Kaplan, the chief scientist there, said, no, if scaling is slowing, it's just because you're building it wrong, most probably.

9:33So I really think that they do really believe in this stuff, that this is going to continue on this exponential. I believe that's an earnestly held belief. I also think that it's undeniable that being loud about that is great marketing. Because if you're like the firmest believer in where the technology is going to go and you're talking about like, you know, how it's, you know, potentially like capable of bio, bio weapons. than if you're a pharmaceutical company. You're going to be like, well, I'm talking with some guy. I can't leave these anthropic guys out of the conversation. They're making bioweapons.

10:08I'm just trying to make the next Ozempic here. Exactly. Ozempic Plus. Lose twice the weight in half the time. Yeah, I'm going to use AI for that. I'm in. I'm in. Yeah, so it can be both. I really think it's both. I think everybody around who's been around them, pro or con, thinks that it's both. But I think the big issue, and this is sort of like takeaway number two for me, is that there's going to be an issue with inference. And running these models is very expensive. Many of the startups who I've spoken with have said that they like using Anthropics models, but they're down too often. As the models get bigger, right, because if the scaling laws are a thing, the models are going to get bigger.

10:47They're going to be more expensive to run. And if they're more expensive to run, are they more expensive to use? And if they're more expensive to use, does this industry work? I think that's the big open question. Here's Dario. He says, we make improvements all the time that make the models 50 % more efficient than they were before. We're just at the beginning of optimizing inference. Inference has improved a huge amount from where it was a couple of years ago to where it is now. And I think whether they're able to continue that trend of improving inference and making it more efficient, that's the key question or another key question, shall we say here?

11:20Because that if you're building for the business use case, you have to make your model fit into their ROI calculations. And that's really the bottom line. Yeah, I think that is the more I've been thinking about it. It has to become more of a conversation because right now, again, you know, most of these companies are just bleeding money right now. the economics of it, as you try to make the model more powerful and powerful and saying, that's how you're going to get to the eventual productivity that is promised. But in the meantime, no one has modeled out what this costs a business or even an individual.

11:56We're all, I mean, this is like the mid 2010s when we're all getting free Uber rides. Now we're all just getting, as I was traveling around Asia, I'm sure what I was costing chat GPT in all my searches was not what I was paying for for the$19.95 or whatever it was for Chachi, $20 for Chachi PT+. So I think the economics of the industry, and you had Ed Zitron on a couple of weeks ago, I firmly stand differently than him in terms of, I do believe generative AI and AI is going to completely transform everything. But what that looks like, what it costs, what cost structures look like for people and businesses, I think like this it's certainly not been figured out yet.

12:42Yeah. And by the way, like in the conversation again, just to point back to it, I brought that up to Dario and was like, what's going on? You're going to potentially lose money on your most enthusiastic customers. And he said, well, that's going to change. And then, of course, this week, Anthropic introduced stricter rate limits for cloud code users. So the company is real. And I think all AI companies at this point, they're trying to or they're going to have to navigate the boundaries between like, you know, it's like the opposite of social media. Social media, you want people to be like super engaged and never leave your product.

13:17And with generative AI, because it is expensive to run, you have to be careful about the amount of use you try to sort of incentivize. Yeah, I mean, we've talked about this plenty. Generative AI is not traditional software economics. It's not like essentially zero marginal cost. It's certainly not social media, but not even traditional software. It's a completely different cost structure. It's more industrial, in my opinion, than traditional software, which is actually, I would say, intellectually, one of the more interesting things for me that what the entire world is going to look like in terms of how it leverages generative AI, what these companies are going to look like.

13:56And to me, even for Google, that is actually one of the more interesting parts that the entire business has been built around kind of like fast adoption, slow, like Gmail and Google Workspace in the past was just get it in everyone's hands and start building out more experiences and give them as much usage as possible. Whereas now Gemini is different. And you can see that in the way they're all trying to figure out how to price this stuff. Can I say we have a pretty intense debate going on in our big technology discord about this? There are like two sides of this equation. One side is that just get the usage and all costs will fall to zero because there's so much investment in this space.

14:38And the other is talking about how like, you know, I'm losing money on every product I make. I'm just making that up in volume. So, you know, we will see how that plays out. But I think that's one of the big open questions that I walked away with. Yeah, no, agreed. When venture is involved, that's the eternal debate. Exactly. All right. Let me give one last quick thing. And that is that one of the main things that I wanted to go into this interview and this conversation was trying to investigate whether Anthropics rise in revenue. We all know they've gone from like$1 billion last year. They're projecting$9 billion this year, which we're going to get to in a moment.

15:15I just wanted to know, is the thing that is buoying the revenue, is that all coding or is it broader? And I learned it's much broader. So they are working with companies in industries like travel healthcare, financial services, insurance companies like Pfizer, United Airlines, and AIG to implement this technology within their workflows. And it's not just coding. So I think that the fact that it is broader than coding is a bullish sign for the company. Yeah, I mean, regular listeners will know this to me is the ultimate battleground is actual business implementation and use cases and within the enterprise.

15:55And for all the talk, this is not real yet, especially for the anthropics of the world. So I think they're clearly moving into the space. But to me, I don't know, like they have these use cases. They're starting to build out their teams in these spaces. But on the other hand, like does that decrease focus from the pure software development where they could win? And I think that's the question all these companies are going to have to face. They have to do everything. Again, we're going to talk about the funding in just a second, but they will anyone truly is this winner takes all or will certain competitors, certain people win niches within this space?

16:37That is a great question. So I'm curious what your answer is to that and where you would put Anthropic in sort of the ranking of these companies? I'm a firm believer that no one is going to win it all. The consumer and enterprise are different. That different, you know, like the act of software engineering is different than the act of marketing. And I'm definitely not a God model. One model will win and be able to do everything, do everything well. And that company will also have the best product for all types of use cases and for everyone. So I definitely think that is not going to happen. I mean, we've seen in tech, social media for a long time, Facebook dominated.

17:21Then you start to see some level of competition. But the network effects within something like social media, I think, are very different than the network effects from scaling. Let me ask you this. Is the risk that there are some economically, clearly economically valuable areas of this world and all these big model companies end up directing their attention there and then splitting the market and then just not having the return on investment that they expected? Let me just give coding as an example. Anthropic obviously has the lead in coding. It's been a good business for them. Google just brought the leadership of Winsurf in, apparently in an attempt to get better at AI coding.

18:02GPT-5, which we're going to talk about in a moment, is expected to be much better at coding. If you have these three multi-billion dollar efforts going at the same market, dividing it up, is there a potential risk that no one wins, right? Because if there's not going to be one taking all, is it possible that you just end up getting this spoiler effect where nobody really sees the return they want? I think you just defined free market capitalism and competition, Alex. And I like that. I think that's a good thing. I think by no one wins. This just goes back to the question around what do the economics of this look like eventually.

18:45And to me, Mark Zuckerberg doling out$100 million per engineer, which we talked about last week and said it is justifiable. But I think we start to move away from that arms race mentality and people have to hire sales teams and go to market teams and build good product and prevent churn. And we just get back to the normal way business works. And you started this episode saying, if you're good at business, you make money. And I think if there's ever a takeaway, if you're good at business, you make money. And I think that's what it'll come back to rather than the idea, given the rate of competition, that it will make the idea that any one company is going to be so far ahead purely from a model standpoint that you'll have to win on the other parts of, again, like sales.

19:41Salesforce didn't win cloud early on because it just was the best at cloud. It won cloud because it was just like a powerhouse in the rest of doing business. So I think, again, this goes back to like social, like Facebook, even Google, they created software monopolies solely on incredible software. But these types of businesses have to have the rest of the, like Google wouldn't have, without its advertising model wouldn't have been that interesting. So it's still not, it's still going to require more. That's right. And just as that requirement shows up, we're starting to see the stakes increase again.

20:25So this is from Bloomberg Anthropic Nears funding at$170 billion value. As revenue searches, the investment is going to be, they want to raise as much as$5 billion in a new round. By the way, they just raised most recently in January. They've been in discussions with Iconic Capital to lead the Kantar Investment Authority and Singapore Sovereign Fund about participating. And then the company was generating about$4 billion in annual recurring revenue or annualized recurring revenue earlier this month. But it now expects that revenue could hit$9 billion by the end of the year. This is a new stat from the Bloomberg story.

21:04One thing that stuck out, Dario was like, listen, I am surprised, but we've seen revenue 10x from zero to 100 million, from 100 million to a billion. And from 1 billion, we're now at 4, he said, 4 billion annualized or maybe 4.5. So they're going to have to like seriously, like the run rates are going to have to look like they're in the 20s, I think, at the end of this year, if they're going to hit 9 billion. because they're going to have to make up for those months that they weren't on the$4 billion run rate. I don't know. Maybe it's possible. They're going to get the money to find out. What are they going to do with the money?

21:40That's, again, going back to, is it, I'm so curious, and I know even with 24 interviews and diligent reporting, getting a true answer of how does that investment look like on a proportional level between investment on the model side and investment on the business side, let's say, is an answer that's almost impossible to get. But I don't know. Did you get any sense around that? Oh, yeah. I don't think it's that hard to figure out. I think it's going to go towards infrastructure and getting larger data centers set up. All right, then. You just answered the question. Yeah. I mean, I think that's one of the things that's coming up here and why Mark Zuckerberg has been offering all this money.

22:21It's actually like a pretty smart thing. It's like, all right, well, if I'm spending$100 billion on data centers, I'm just like throwing a number out there. Why can't I spend one tenth of that or one one hundredth of that on talent? Yeah. OK. So then if that's the case, I mean, the assumption there is you're scaling revenue solely on, I mean, virality, essentially, or just like high level brand marketing by saying things like bioweapons, I guess. But to me, I mean, I guess I will say this with a grain of salt because they have shown they're able to scale revenue already with this philosophy and this strategy.

23:00But to me, does it keep going? Or at a certain point, especially at that scale, are you going to start running into the Googles of the world or the hyperscalers more regularly versus you? every individual software engineer is ready to pay you 200 bucks a month on their work credit card versus that's a whole other level of competition. Well, you would imagine it would be harder to 10x every time you 10x just because the law of large numbers comes into play. Like going from 1 billion... Unless you're NVIDIA. Unless you're NVIDIA, in which case that law doesn't really apply. You just substitute Jevons paradox or whatever fun made up economic term you want and you just keep printing money.

23:45I don't know. Getting from 10 to 100 billion is much, much harder. If they get to 10, I will tip my hat to Dario and team. Yes, I will too. And speaking of 10, OpenAI is expected to surpass that this year, actually. So OpenAI hits 12 billion in annualized revenue, breaks 700 million. ChatGPT, weekly active users. This is from Bloomberg. They roughly doubled their revenue in the first seven months of the year, reaching$12 billion in annualized revenue, says OpenAI. And I think there's this big stat. This is a big stat. ChatGPT has 700 million weekly active users. I mean, for a product to come on the market in November 2022 and potentially be on the road to a billion users by, let's say, mid-2026.

24:33That is insane from a company with no footprint beforehand. Yeah, to me, the most impressive part of that is there's no entrenched virality in the product. Like, yes, there's share your conversation, which actually, I saw this post today, and it was really interesting that apparently Google is now indexing shared chat GPT conversations and their searchable conversation for another day perhaps. No, let's talk about that now actually because I found that to be kind of weird and concerning. I mean, maybe because there's also been issues with like Meta's conversations showing up and there's almost nothing weirder than like getting a chance to access people's private conversations or seemingly thinking private conversations with these bots.

25:22People will say the weirdest things to these chatbots talking about their problems, their marriage. And the fact that like, you can, you can, you know, I guess when you hit that share button, is there any clear messaging that this is like sharing to the entire, I mean, you should, you should intuitively know that you're going to share this to the entire internet. Cause if you drop it to somebody else, it's going to show up. But like the idea that this could end up being blasted to, you know, indexable Google is kind of crazy to me. Well, there's two points on that. One, it also just kind of brings me back to I love the brawl as, you know, like Google being like, let's index that stuff, like realizing, oh, well, we'll take some of their information right now and make it available and interesting through our own platform.

26:09But I think, yeah, the other part, so again, like if you create a public share URL, it gets indexed. If you're like sharing the conversation by itself and not creating that URL, it does not. Same with meta. There was like a big brouhaha like a month ago, and it was terrifying. Like I was going through meta AI and seeing some really weird conversations that were being publicly posted in feed. But again, people had met even more so it felt like accidentally hit share. But I think so two parts of that. There's getting to 700 million where virality is not entrenched is incredibly impressive. But this is where still how this stuff lives in our life, especially at the individual and consumer level.