Warning Signs For The AI Boom, Anthropic Passes OpenAI, Robinhood’s AI Trading

Is the AI boom in trouble as costs pile up and productivity questions emerge? Anthropic is now the largest AI startup passing OpenAI, and Robinhood will let your chatbot trade for you. That's coming up on a big technology podcast Friday edition right after this. I'm just back from ServiceNow's Knowledge 2026 in Las Vegas. And the conversations I had there are ones you're going to want to hear. I sat down with their president and CPO, Amit Zavari, on the platform strategy powering enterprise AI, chief people and AI enablement officer, Jackie Canny, and chief digital information officer, Kelly Romack, on what AI really means for the workforce. The technical leaders behind ServiceNow's NVIDIA partnership on shipping AI at scale and Ulta Beauty on deploying ServiceNow's technology across 1,300 stores. If you want to know where enterprise AI is actually headed, not the hype, but the real story, you can find these videos on my YouTube channel. Search Alex Kantrowitz on YouTube. Depending on who you ask, between 80 and 95% of enterprise AI projects fail. To get AI to work for you, you don't need more tokens. You need better people. Abord pairs powerful proprietary tools with senior engineers who've seen it all. That combination means your project doesn't stall, doesn't drift, and doesn't fall. It ships. Whether you're a startup that needs to get to market or an enterprise with complex legacy challenges, Abord delivers exactly what your business needs fast. Abord is your partner for AI transformation. Visit Abord.com and let's build something together. 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 the warning signs for the AI boom as companies start to question all the tokens they're spending on things that may or may not be shipping. We're also going to discuss Anthropic passing OpenAI as the world's largest AI startup. They're coming in close to a trillion dollars in their latest fundraise announced this week. And also Robinhood is going to let you basically have your trading delegated to a chatbot. Is that a good idea? We'll cover it all. Joining us as always on Fridays to do it is Ronjon Roy of Margins. Ronjon, great to see you. Good to see you, Alex. We cannot have nice things. As we get into today, I am talking about AI and token maxing. It's just a reminder that we can, none of us can ever have nice things that are just given to us. Okay. Well, we definitely, this is definitely a topic that will require a level of nuance that I don't think is being communicated in the headlines. So in the first half today, we'll do our best to at least tackle this with a degree of depth that I don't think has been shown in the conversation yet. Okay, here's the story. This is from the Wall Street Journal capturing it all. Corporate America is starting to ration, ration? Ration? Ration, let's go with ration. Ration, ration is food, right? All right, I'll start that again. Corporate America is starting to ration AI as costs skyrocket. Use of artificial intelligence by big companies is exploding, and the soaring cost has some of them pumping the brakes in a way that could complicate AI's triumphal march across the economy. Some enterprises have hit their annual token budget in just three months or reported seeing their AI spending bills double or triple. Now corporate leaders are scrambling to bring down expenses by finding ways to ration AI use in their organizations, steer workers towards cheaper homegrown tools, and help them hone their skills to improve returns. Ronjon, I just want to kick to you. Basically, what we're seeing is story after story of companies. That could include Uber, it could include Meta, it could include Microsoft, DoorDash, that have talked about the spending of tokens has gotten way out of hand, right? Just the people are using these things to either get on the top of leaderboards or they're using high-throughput models to do stupid tasks, and it's just burning lots of money based off of it. And I think underlying all this is a question of, wow, you know, the revenue in this industry has run up really quickly. Is it all a mirage? Is it basically a bunch of idiots token maxing to get to the top of leaderboards where the actual value is much more minimal than what they're seeing? And if that's the case, you know, could this all implode or slow down? What's your reaction? This is why I started this episode, Alex, saying we cannot have nice things because agentic AI, listeners know, is something I truly believe in and have seen the power of and get to work with every single day. But token leaderboards, token maxing at companies like Amazon and Meta already were making me feel a little uncomfortable. Then when you couple that with how that incentivized soaring annualized recurring revenue, which led to more funding rounds and gets us into the situation we're in right now. I think at least I'm happy that it's being recognized, but I'm also unhappy with how quickly everyone is just kind of, the pendulum is swinging dramatically the other way. And now suddenly everyone is saying AI has no value and no one has seen anything happening and this is all a mirage. So I think to kind of just start on the conversation of token leaderboards and what happened. Even last week, I was saying this. And again, for listeners, I work at a company writer focused on enterprise AI and have had a front row seat to all of this. What we were talking about last week, the last six months were this period of kind of unfettered experimentation. And now we're seeing that kind of come to the headlines. And I've been saying this for a while now, actually, that no one was checking their actual cloud bills. Everyone was in the command line, you know, cranking out whatever they wanted in cloud code and then codex. And now everyone's recognizing that, oh, wait, maybe that's not how it should work. And I think it's a good thing. I think this was going to happen at some point. People should recognize there is a cost to all of this. And that's fine. That's okay. You need to be thoughtful about how you build with AI. But I do think it's so much stupidity is coming out right now that it's kind of making a mockery of our industry. Well, let's just talk a little bit about the magnitude of this. So this is from Axios going a level deeper. It's talked about how Microsoft canceled most of its cloud code licenses and part over costs. Uber's COO said AI costs are getting harder to justify. You also have Starbucks, which had an AI program that users worked for automating inventory that it shut down. And there is an AI consultant that said, one of their clients, this is the amazing stat really made the rounds. An AI consultant said one of their clients recently spent a half a billion dollars in a single month after failing to put usage limits on cloud licenses for employees. Here's my question. I'm trying to figure out whether like this thing, this notion of runaway token costs is the exception or it's the rule. I mean, I imagine this half a billion dollars spent is first of all, like unnamed. So would have liked to have gotten a name on that, although I understand why it's tough for someone to put a name on such a claim like that. But when you look at some of the other examples, you can start to peel away some of these. So Starbucks, like it had this inventory tool, but it was a visual intelligence, right? So I think that that was mostly a computer vision tool. With Microsoft canceling its cloud licenses, yes, it was financial, but also Microsoft has a competing tool. And so that sort of leaves you with Uber and an unnamed source. So I don't want to say that this isn't happening. Clearly it is, but I think I'd like to see a little bit more smoke to start to extrapolate to the entire industry, you know, being on fire as opposed to what we've seen so far. And I think there is this notion that like, if you get one of these stories, it just blows up. And, you know, remember, we've talked a little bit about how attitudes against AI are, you know, very negative right now. And in this type of environment, a story like this just kind of booms around the internet because it starts to do some confirming of the preferences that people have for this stuff to go away. I'm just saying that for the examples that we see, at least in regards to how prevalent this is, even though I've heard of many stories of companies with leaderboards, I would certainly, you know, apply at least a tiny bit of skepticism here in terms of this being a widespread problem. Your thoughts? I think it is both. I think, and again, I see firsthand. I build things that I get to see work. But this is also true and correct, I do believe. And I think let's take these one by one. But again, overall, the idea that there has been a lot of wasteful spending specifically with cloud code. And I think that's like the main culprit. And that's what's coming up here because when you gave engineers unfettered access to cloud code and no one was monitoring anything and you could not actually see how much you were burning, and you were being incentivized in many cases, of course, you're going to. That's like that's the entire system that you're setting up. But I think let's take them one by one. Obviously, the the Axios reporting that the consultant said that one of their clients recently spent half a billion dollars, $500 million in a single month because they didn't put usage on limits. Now, my favorite part of this is like, there's not a lot of companies where that can happen and fly under the radar. There was also reporting So it kind of leaves us with meta. You certainly can remove Apple on all that. So I think, but so then you start to think, does that $500 million? Anthropic is getting to count that probably as $6 billion in run rate. So as their run rate is increasing these dramatic levels. And like, to me, that's one whole side of this conversation that is terrifying and is problematic, is the extrapolation of these kind of like big, but still, you know, like isolated issues has been extrapolated into ARR and now fundraising. And we're going to get into Anthropic's fundraising this week. So I think that's a huge issue. And to me that it is crazy, the kind of like second and third order effects that one example like that can actually have in terms of fundraising. And suddenly it's like the butterfly effect where suddenly a 27 year old Korean is taking out a margin loan to buy more SanDisk stock on the local stock market and then buying a Ferrari. And there's reporting that like Ferraris are being sold all because a meta leaderboard or unnamed company leaderboard someone was just cranking out tokens. Like that to me, that's one of the most fascinating and crazy parts. Do you think I'm exaggerating the potential downstream effects of these kinds of isolated issues or do you think they are tied together? Yes, I do. I do think you're exaggerating the downstream effects. Like there, there's a specific problem. I mean, I did title this episode Warning Signs for the AI Boom for a reason. And I'm going to get into the specific reason in a moment. But and you know, there could be, and we're going to also talk a little bit about the weird creative accounting and circular deals in a moment. But when you think about the revenue of Anthropic, it's gone, and this is the annualized revenue. So take that as it with, for what you will. But even if, you know, you still had accounting tricks that you couldn't fake all of this. In January 2025, it was a billion. May 2025, $3 billion. June 2025, $4 billion. August 2025, $5 billion. October $7 billion. December $8 to $10 billion. This year, February 2026, $14 billion. March 2026, $19 billion. April $30 billion. May $47 billion. So again, like, even if you were to discount like that, let's say that $500 million use. It's not just that $500 million. Like there are moments in these cycles that you don't forget. And about a month ago, I think I had talked about this on the show a month ago, two separate instances with fairly high level technology folks that I'm speaking with, they are bragging about how much they're spending on Claude. Bragging. Like you don't hear people bragging about those kind of, like you're bragging about operating expenses is not something that's typical in business. And the fact that that was happening, and when you see that curve in terms of their revenue increase, it is real. It is like actual, I mean, it's not truly annualized revenue or annual revenue. It's ARR. But it's coming from somewhere. And basically people with every IT team in the, every large company was given, and Claudeco was a phenomenon. I mean, it was, it was like, to truly bring agentic to the world, like it was and it is. But how that got reflected into actual like numbers was, I do think this directly reflects. And then the downstream, the 27-year-old Korean taking out a margin loan to buy stock and then buying a Ferrari, I still think is directly correlated. There's a story about this guy that you read this week. I'm actually conflating two different stories. One about 20-something Koreans taking out margin loans to buy memory stocks and also apparently like the Ferrari dealerships have sold out inventory for the next two years in South Korea as well. I just put those two together in a convenient narrative. I recognize the conflation. Okay, well, at least we're honest about it. All right. So, so here's what, here's the kind of the punchline that I'm getting to. To me, if there's there, you know, I don't think the token maxing stuff is the rule. Like, I don't think we're seeing $47 billion of ARR that's just being wasted because people want to rise leaderboards or people want to brag to their friends how much they're spending. I would say that probably accounts for a percent of what's happening, but not all of it. Here's where I'm actually concerned. And I, and I will caveat this by saying, I do believe in the underlying technology. I think, you know, it's making good progress. We've all seen it make progress. Right. But in order for this to continue, it's going to have to show actual productive use. And let's say it's 20% token maxing. The other 80% of people being cautious and trying to be productive with it, you know, within reason, not just trying to burn tokens for a burning token sake. They're going to have to see a return on their investment. This is from that Wall Street Journal story that we read at the beginning. For companies using advanced AI coding tools, only 18% of spending on tokens is translating into shipped coding products that reach real users. According to Entelligence AI, a startup that aggregated data on more than 2000 companies using AI, using advanced AI for coding. So here's where my concern really comes in. You know, let's say you're talking about the 80% that's not token maxing. And by the way, I think that's a low number. I think it's probably higher than that. Of people trying to actually use these tokens to accomplish things. 82% of that use is not translating into shipped products that reach real users. And that, to me, is the issue. Now, it was bound to happen that in this moment where there's going to be some frothy spending because of the potential that you are going to see some waste. But when 82% is wasted, that to me is the bigger concern than the leaderboards and the token maxing. And that's where I think we're going to start to see, you know, if we see a real reckoning with the generative AI boom, it's going to come in that area in particular. And that, to me, is a flashing red warning sign. Your thoughts? Okay, I'll give you that is more of a concern. The token maxing is kind of funny, sad, but I agree. It's not, it's still isolated. And this is the bigger issue. Where I, even though, again, in this conversation, all of this I have found very problematic. And I think there's like just the hype and the scale with which everyone has kind of like chased things during this cycle has terrified me. This is an example where this is new technology. And if, again, why I started this episode with We Can't Have Nice Things, if everyone was allowed to simply start building, understand what's working, not be overly pressured, spend some money, see, like, you know, take what works and then build more on that. Because like when you say 82%, what should happen, this is only four to six months old, call it. So that 18%, then you reinvest in whatever kind of work is being done there. And it's actually any kind of standard business process that's not in an unreasonable path. We see it ourselves. Again, like the reason I truly believe we can get there is like even things that I have built with our customers, we see like, okay, you start with one process and it's like taking X number of tokens. And then, oh wait, instead of using a giant CSV file as context in the agentic workflow, let's turn it into a JSON. Actually, let's chunk it into multiple different JSONs and only call, like getting that technical. But like that dramatically would reduce the actual tokens consumed by 70, 80% in a process. So like, this is the stuff you should be doing. This is stuff we are working on and trying to do, but then all of this hype around it makes it makes it incredibly difficult. So I think like I do agree that's probably even more real, that 82% is wasted, but I think in any normal business cycle, that would be fine because any new experimental technology, that's part of the, that's part of the process. Right. And I think this is definitely happening across the board. And it brings me to this like story in Business Insider that Uber's COO says it's getting harder to justify the money spent on AI. This, the chief operations officer of Uber, Andrew McDonald, said that based on talks with Uber's senior engineering leaders, that higher token usage did not translate into proportional increase in useful customer consumer features. That link is not there yet, right? He said, I think maybe implicitly there is more getting shipped, but it's very hard to draw a line between one of those stats. And okay, we're now actually producing 25% more useful consumer features. There was a pretty interesting reaction to this online. I think that like the AI critics, you know, pushed it out there being like, see, it's all bullshit. And then the AI boosters like pushed it out there and said, honestly, embarrassing for Uber. And this is a skill issue, not a technology issue. But I would just kind of draw it right down the line here, which is that if this is a problem that's happening for Uber, it's a problem happening for many other companies, right? If Uber can't figure this out, then you would imagine that that line again about the 82% of tokens being wasted isn't just some like AI consulting firm, you know, sort of pulling a number out of its butt. It's something that's actually real. And to me, that's, that to Uber is not seeing the productivity. Is Lowe's seeing the productivity? Well, okay. Home Depot? I mean... If Uber can't figure it out, are they? Home Depot's chatbot is actually pretty good. If you use, I think it's called like the orange apron. I was kind of stress testing it, but that's a separate thing. I think we're going to see a pullback and we are going to recognize, but structurally, I mean, this is the thing. Structurally, when you go to your entire engineering team and say, go use as much as you can of this when there's no clear direction, and this is over a four month period. It's over a four, I mean, in the grand scheme of things, that's not a ton of time. And if things aren't being done strategically and everyone is just kind of doing whatever they can, obviously you're not going to see any kind of like, you know, like concerted progress, ROI, whatever it is. I think like, to me, this just kind of captures a whole thing. The Starbucks one too. I don't know, like that we've mentioned before from the reporting. This was such a perfect example. Like everyone's like, oh, they're scrapping AI. New CEO came in in September 2024, wanted to do an AI kind of press release. You had mentioned computer vision. It was basically like, you know, taking photos and then trying to analyze those photos and it like analyze the milk, the syrup, the sauces and an inventory count. That's a hard problem to do in kind of an unstable environment like the real world in Starbucks of all places, which is a pretty chaotic place often. And the idea that you're going to solve that versus demand planning, inventory forecasting, like these are pretty advanced AI fields. And like, I mean, there's many, many companies out there. There's many, but so this gets, that one to me does get cherry picked as it's a press release type thing. They take on a really, really complex problem. And of course it doesn't work. I feel the Uber stuff feels similarly where it's just like, use a lot of AI. And then of course, in four months, you're not going to see dramatic improvement. One more bit of nuance here that I think we should share. You know, you remember when the Uber, there was somebody from Uber that said like, oh, we, we blew through our entire 2026 token budget, you know, in like two months or three months and everyone went crazy over that. And that's sort of one of the things that we're seeing here is like, you know, executives are, are coming to grips with how many tokens are spending. Well, Simon Wilson had like a pretty interesting perspective on this. He goes, some of the most widely cited of these stories appear quite overblown to me, given that Claude code really only got good in November. It's entirely unsurprising that a budget set in 2025 may have failed to predict demand for that tool in 2026. I think that's a good point, right? That we all know that in November, December is where these models took a leap and became much more useful for things like autonomous coding. And so we should expect to see many more stories of, you know, companies hitting their budget, their token budgets, uh, early and trying to figure out what to do. But in, in some ways that could even be like an indication that the technology is working well. What do you think? I guess, I mean, but that's exactly what I was saying, that this is all so recent that it's like, it's clear to me that trying to get any like long-term learning from just three to four months, this exactly like I think is, is not correct, but, but I do think that, I don't think that actually shows that there is value. I think it just shows, I mean, these are, I think these are all great tools. And as we said, like, I think it requires learning. It's going to require like completely changing organizations and the way they work. That's going to take time and it's not going to get fixed in four months. So I don't think, again, anyone who's used these tools, you can just sit there, go down rabbit holes, crank tokens and end up nowhere. Plenty. Like, and we've all tried to build some random app that doesn't really go anywhere and it's fine. But if you're both pressured to do that and like that's being done at a large scale, we're seeing the results. I guess there is this kind of third way here, which is that these tools are actually quite useful, but engineers have figured out a way to just kind of set their jobs on autopilot and kind of hang out and build the same features that they were tasked. So the tokens are doing their job. The engineers are gaming the system. The higher ups aren't seeing any productivity. And everything can sort of be explained as like the engineer has hacked their way through the system with this brilliant new technology, which I wouldn't be completely surprised by, you know, to learn that that was the real story. I support that. I support that. Okay, so bottom line from this segment, I'll speak for myself. To me, you know, the core thing to read from this story is basically the 82%. AI has got to not waste 82% of the tokens in order for this boom to continue. And that to me is the real warning sign here. Those type of numbers. If it doesn't figure that out, there's going to be some serious problems. Your thoughts? I will push back that that 82% actually, I believe, could be a reasonable thing in any early stage of like a pretty dramatic new technology. And I'm saying like the world changed in November 2025 and it's like that 82% is okay. If it's a reasonable thing, it's if it's still thought of as, let's experiment, let's learn, not let's just plow money into it, which is what people did and imagine that everything is going to be different. So for you, so for you, the real problem is the 20% that's being token maxed, assuming my 80-20 breakdown is accurate. No, no, no. The real problem for me is we can't have nice things, that if everyone just approached this in a nice, responsible way and just built and just learned and took what wasn't working and discarded it and took what was working and then invested and doubled down on that, like any other thing, we would be okay. But it's, as we get into the next few segments, we're not okay. Yeah. And I think that this is something that we need to get into as well, which is that the financing still looks a little wonky here for AI. And I think there was a long discussion of the circular financing and that kind of went on pause for a while. And we've seen these amazing cloud revenue numbers over the past few quarters with Google and Microsoft and Amazon all booking insane profits from their cloud's divisions. But at the same time, they've also, all of them have invested in AI labs, Microsoft in OpenAI and Amazon in OpenAI and Anthropic, you know, tens of billions of dollars and Google and Anthropic and also in its own divisions. And then when the, you know, when these startups spend these massive amounts on the computing that sort of has been tied to the deal, you know, the computing from their funders, it gets booked as revenue and then they show profits. And then, you know, the cycle moves about again. So, Rajan, you brought this up to me in our, in our text messages this week. Just would love for you to comment about it for a moment and talk to us a little bit about why you think this is a potential warning sign for AI. Well, I think, again, going back to why we can't have nice things, you can't build responsibly and take a deep breath because of this insane like infrastructure that's been built around circular funding. And I, it reminded me, I was trying to find, I think it was almost 18 months ago on the show, we were talking about, it was like one of the early stage, I mean, and it was still 6 billion at the time, but where it was explicit that a lot of this is in cloud credits. So I think it was Amazon first going into Anthropic and us kind of half joking, like, oh, I bet you, it's just all AWS credits and that's a, and they're going to call it funding. But now as the numbers have gotten bigger, I mean, Microsoft invested $13 billion in OpenAI. A lot of that was just spent back into Microsoft. They recognize it as Azure revenue. Then they also recognize a paper markup in OpenAI as well. Like every one of these, I didn't, the scale kind of shocked me because I saw these numbers that last quarter, Alphabet, parent company Google, reported $62.6 billion in profit. Google is a cash machine. They always have been. $28.7 billion of that was a paper markup on Anthropic. Amazon, $30.3 billion in profit, $16.8 billion, same Anthropic paper gain. So like, again, we all know this. NVIDIA put in $100 billion into OpenAI. OpenAI is going to then be committed to buying NVIDIA chips. Like overall, everyone has known this. It's like right, there's been reporting all along the way, but we haven't really, really worried about what does that mean? And I think we're starting to get to the point of actually start, what happens if there's a slight downturn? It's like the reflexive nature of all this money that's moving in a circle is terrifying. And again, like that's why we talked about this last week. I think everyone is rushing to go to IPO so this will just be in the hands of retail investors as opposed to these companies and After nearly half of their overall profit. So I think like, that's a, I'm not saying this is like an unethical thing in any way. I think, I guess, if we're going to say anything unethical, it's not even unethical. I think, like, I don't think there's like a cabal of tech executives sitting around talking about how can we juice our overall valuations and then build this circular financing system. Actually, what's fascinating to me is I think this really is like a good example. It's still such a small circle of people. Like, in the grand scheme of things, it's in the hundreds of people maximum across all of these companies that are kind of at the forefront of this, the poster children for this. And probably in relatively similar conversations and social circles and conferences and sitting at the same tables at industry dinners or the Trump White House, what have you. You know, like, so you can feel how the conversation in that group thing can kick in. And then suddenly, if the guy over there is tossing in an investment that actually goes right back to them in cloud credits, why wouldn't you do it? Right. Well, you get that, but then you also have this promise of future spending, right? So it's not just like Microsoft putting money into OpenAI and then OpenAI putting it into Microsoft. It's Microsoft putting money into OpenAI and then OpenAI promising to, you know, to basically buy computing services from a Microsoft or an Amazon. I mean, think about this. This is, again, from a tweet that you shared. Microsoft has 49% of its $627 billion future backlog tied to OpenAI. Oracle has 54% of its $553 billion pipeline depending on OpenAI alone. There's no guarantee that OpenAI is going to come in and actually spend that money. So when you look at the financial health of these companies, I don't know, you know, the AI could be a blessing, but also this dependence on an OpenAI could also be a curse. Well, not just a curse, but, I mean, you take even, again, maybe Apple comes out of this just golden that they're the only ones who, like, somehow managed to, whether by purposefully stay out of it. I think, like, that kind of forward-looking spending, and this is all in the next three to five years that everyone has kind of, like, built these contracts. It all assumes an end demand from the rest of the world outside this small group of companies. And, like, are they going to be interested? Is it going to work as magically as everyone has been promising? And, again, that 82%, like, I think that's why this has caused so many alarms. And then also, I mean, one of the other interesting things to me is, and we can get into the IPOs, but I think, what was SpaceX's estimated fundraise? It's like $86 billion. $80 billion. $80 plus billion. It's between, I think I saw, like, Josh Brown on CNBC called it, like, three asteroids coming to hit the Earth. Like, the amount of capital that's going to be required from the rest of the world outside of sovereign wealth money and Dragonier and Altimeter and whoever else, like, to actually fund these three IPOs. Like, where is that money coming from other than the South Korean 27-year-old taking out the margin loan for his Ferrari? Let's talk about that, though, because this is fascinating, by the way. So, very briefly, we should cover this. I mean, it's not just these handful of companies anymore. This boom is spreading to the memory chip companies. It's from the Wall Street Journal. AI has made memory chips more valuable than oil. Memory is now worth more than oil. Staying that way will depend on how much the notoriously volatile chip industry can make recent changes stick. The world's three largest memory chip makers, Samsung Electronics, SK Hynix, and Micron Technology, now carry market capitalizations of more than a trillion dollars each. That's 22% above the combined market cap of the world's three most valuable oil companies, even with Saudi Aramco weighing in at its own nearly $1.8 trillion. I mean, just talk a little bit about this boom in memory chips, right? It just seems like the AI companies are buying up all they can get. And they've made a sort of secondary or tertiary group of shareholders, those that have had the memory chip stocks, very rich, while also making life difficult for anyone who owns a camera and wants a new memory stick because OpenAI has bought it. Your thoughts on this? Well, these are my second and third order effects. That $500 million on the token maxing leaderboard earlier, here's where we ended up. This is what I'm saying. It's like, again, the idea that the more, and this is something I have thought about for a while. And I mean, as AI produces more data and content and stuff that needs to be stored, it was always inevitable that memory would be more important. But to see two companies reach market capitalizations of more than a trillion dollars, Three, three companies. Three companies, sorry, three companies. Like, come on, come on. That's bananas. That will fall. It has to fall inevitably, right? I mean, not investment advice, but that has to fall. But this is where I had friends, like in the investment community, the question they keep asking me, it's funny, like, again, I work in enterprise AI. They ask me, what is the next bottleneck? Like, that's the conversation is not, oh, you know, like how is adoption? Like, what are you seeing? Such a finance question. Yeah, what are you thinking about how companies are gonna leverage AI? Are you seeing the ROI from a, like our business operations improving? It's literally, where do you think the next bottleneck is? Because that is where we are again in the cycle. That the mania is so strong and everyone missed, if you didn't get in, you missed the memory chip bottleneck. What's gonna be the next? I mean, is it like, it's like cooling for data centers and stuff like that. Like there's all these kind of like really minute or niche areas that serve the entire value chain. And everyone is trying to look up the next one because they've seen what's happened. So is that a healthy market? I don't think so. No. Do you? But on the other hand, like maybe there's real economic forces there. Like maybe you actually do need all these memory chips to make this work. I don't know. I'm just glad I got a four terabyte hard drive like last fall when I was trying to export all my Google photos, but never successfully did because they make it a real pain. But I'm glad. I thought you were gonna say Ferrari. No, no, but that hard drive. You won't be able to get one now for two years. So that. Maybe I'll sell my four terabyte hard drive and then I'm cooking. Buy the Ferrari. Soon enough, Ranjan, you might be able to. All right, let's go to break. But before we go to break, good news. Ranjan is going to be joining us in person for the Big Technology AI Summit in San Francisco on June 18th. We have just a few tickets left. So if you have any interest in joining me, Ranjan, OpenAI President Greg Brockman, SemiAnalysis President and CEO Dylan Patel, Aaron Levy from Box, and Arvind Srinivas from Perplexity, Lauren Good from Wired. It's gonna be a great day. Definitely should join us. The day is gonna run 1 p.m. till 5. And then we'll have a wine reception with some food on the roof. So it's really coming together nicely. Just a few tickets left. Hope that you will join us there. So just go to summit.bigtechnology.com and we'll see you on June 18th. 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I wouldn't count out OpenAI just yet because I wrote about this in 2022, I think, probably spring. There is the altimeters of the world, the dragoneers of the world, Sequoia as well. Like a lot of the late-stage financing game of pre-IPO doing one last round essentially is a signal to the market of this is the value. Worked very well for a while back in 2021 and 2022. I think that's what's happening here very clearly. And again, it's like, I mean, do you remember the days when the valuation associated with the fundraising round was actually a highly guarded secret? Back in the 2015, I think even like 2017, 18, it wasn't a reported thing. It was like reporters would have to like dig to get valuations. You hid that on purpose from like a competitive standpoint. And so like, I mean, we saw this a lot. I think that's what's happening here. I mean, you have this incredible growth and then you want to get out to market and you want to signal to the market, here is where we believe the market, the valuation is. So when you go to IPO that you can actually try to actually kind of get that pricing like anchored to this because now in the conversation, the anchor is, what is it? 900 billion. Yeah. I mean, I think, so just to sort of zoom out a bit, I mean, I do think this is a remarkable moment for Anthropic, which a year ago, there was, I mean, they were, their last valuation was like 350 billion, a year ago, if you would have told us that they were going to be worth more than OpenAI at this point, I think we would have been stunned. And it's largely come on the back of cloud code. So they're clearly the hottest company in AI right now. They do have this sort of straight shot to being the most successful IPO of the bunch. And I mean, it may be excluding SpaceX, but I wouldn't even say SpaceX is an AI IPO. And so I don't know. I think that this is an important milestone and it just shows how locked in a battle OpenAI and Anthropic are right now. I mean, OpenAI really needs to respond with this codex super app and Google, my goodness. I mean, it doesn't really seem to be factoring. I mean, obviously they are with the, with the cloud business and that cloud business is growing, but not in this sort of autonomous coder in the way that OpenAI and Anthropic have really rode recently. I actually, what's even crazier to me is that OpenAI had even raised, what was it? 120, 122, 122 and only got to 852 post-money. So like, yeah, they got some work to do. However, I don't know. I'm just waiting for the S1s. Like SpaceX. Yes, SpaceX. To their credit, the S1 came out. It was, and we talked about this in length at length last week. It was almost shockingly not good. And still everyone is just, it's 1.8 trillion. It's that, that is, see again, the value of anchoring. It's a way, it's one of those like, you know, like mental principles or whatever it is, like the anchoring effect. Just say it, just say it over and over and everyone assumes right now, Anthropic, 900 billion. That's the valuation because the same people have been investing in it the whole way through and are the ones poised to cash out if people believe that are saying that it is, it is so. That's a nice conspiracy. I mean, you're right. It's not a conspiracy. It's like, it's true. Fake it till you make it Silicon Valley style. No, no, but it's not a conspiracy. It's like, it is just finance. Damn it. That's what's happening. No, no, it's just, no, no, it's just finance. Like, why wouldn't you do it? Why, like what possible reason would you not, if you set the valuation, because that's typically a higher valuation is supposed to be against investors, right? Like you're going to fight for the lower valuation. So you have more of the company. But in this case, you have every incentive in the world to juice the valuation because that means that it gets anchored there and then you go out at a higher value. Like then you realize that at the expense of the retail market. So why wouldn't you? You know, it would really be interesting if they went public and then everybody on Robin hood, which has Claude and ChatGPT controlling their trading, just went full hog into the IPO because we had a headline, very interesting headline this week from the Wall Street Journal. Robin hood lets customers use AI to trade stocks and make credit card purchases. Robin hood is launching a new feature that lets customers hand their trading and credit card purchasing decisions to their favorite artificial intelligence tools. Robin hood users can link an AI agent like Anthropic's Claude or the coding agent Cursor to separate, to a separate dedicated investment account. There, the agent can access the dedicated funds and place trades as directed. For instance, for example, users might instruct their agents to root out risks created by being overly concentrated in one part of the market or monitor a basket of promising semiconductor stocks. Notably, you cannot trade options this way yet. Operative word, yet. Ranjan, I'm sure you love this. I mean, this is in the grand scheme of things and the kind of like, this is where we need to go. So thank you, Robin hood for agentifying trading for all of your millions of customers so that they will somehow end up with SpaceX in their portfolio because it's the only way this story can go. And I think I'm actually, I don't know, I'm happy about this. Not, not truly happy, but like from a pure narrative standpoint and a, as the script should be written, Robin hood kind of like finishing this out is perfect to me. Can I make an argument in favor? I mean, I wouldn't put your entire portfolio in this thing, but to give it a few hundred dollars and say, can you sort of come up with a strategy based on these principles and go out and trade for me? And it can like, I mean, 95% of day traders lose, but what if you sort of had an AI day trader that was going out and in sort of synthesizing so much more information than you possibly could and paying attention to the second by second and minute by minute shifts. Maybe that could work. I don't know if that's something you trade on your behalf. Okay. No, no, no. I'm going to, okay. I'm going to come around. I'm going to come around and say, I do think there is, I agree, like actually probably an agent should be able to trade better than a human, like an everyday person who's not like really focused on this, actually setting some parameters and letting it go. I'll give it to you. I think again, this is again in my, my new grand theory that we just cannot have nice things. This actually makes total sense and I like support the concept of it, but Robin hood releasing it at this moment. I just, it's, I can't see a good outcome of this, but in theory, it makes sense. And maybe this is the way investing. I mean, this is what like the betterments of the world and more of the kind of like algorithmic wealth planning. We're supposed to do. And it's just the next generation of that, I guess. Yeah. I mean, my hot take on this and I wrote about this in big technology today is that everything is going to go this direction and it's not going to wait until you get to Robin hood. The second you start researching stocks in ChatGPT, we're going to get to a place where ChatGPT or Claude will offer to build a strategy for you. We'll have access to your bank account and we'll ask if you want to portion some money towards, you know, giving this, this strategy a try. We'll come back to you and be like, here's how it's going. Do you want to invest more? And I think similarly with everything that you chat with these bots about, they are going to just try to intuit what your next move is. They don't want you to go to the Robin hood. They want you to stay, you know, within their chat experience and let their computer use bots and agents go out and finish the rest for you. That's my perspective. No, I, I think they already are in some ways and we're seeing the very early stages of it where like, uh, more often than not now Claude, but also Gemini, I've seen ChatGPT, not so much The week was I was trying to research if I had some like special number, you know, associated with my business, like not an EIN, but like something to that nature or to that degree. And I asked ChatGPT, hey, do I have something like this? Like, would a company like mine have something like this? And it goes, well, I don't know, but you might have the answer in your Gmail. Why don't you connect your Gmail? And it popped a Gmail connector in the chat. Wait, I saw a Gmail connector pop up as well. I totally ignored it, but... Oh, I said yes. I said yes. And then it went in, it found my incorporation documents, and it said, nope, you don't have this. Better than Gemini, I'm sure. Better than Gemini. Gemini and Gmail, yeah. Oh, I should connect it and ask that my question, what's my first email to my wife, which is Gemini. I just say, you should do it. I also did it, and I mean, again, like, take the privacy concerns into consideration. Which are, I mean, pretty uh... But I was like, oh, how much did I pay for this flight? And it like went into my Gmail and it got the ticket price. It is crazy. So then imagine not taking the next... Giving the OpenAI access to my email is still kind of terrifying now that I think about it, though. Yeah, but then it will take the next step for you, right? And, you know how sometimes it will draft an email in ChatGPT? Once you connect that Gmail, it's only a matter of, like, let me draft this in Gmail. All right, forget about drafting it in Gmail. How about I go and send this to you, you know? And then it comes back to you with the responses. This is just the way that this is going. You're clearly ready to give up more of your privacy in exchange for services involving AI. Is that the case, Alex? I mean, I just think, yeah, it's sort of, it's effectively my duty to test this out and come back to our listeners and readers. Well, that was more of a segue and a lead-in to... And therefore... Go ahead. Would you be willing to allow a stranger into your house to clean your house in exchange for them recording that entire cleaning session and providing that real-world data to an AI company? Because that's happening right now. That is happening right now. There's this AI training startup Shift wants to clean your home for free, but they will record cleaners as they scrub, vacuum, dust, tidy, wash, and use that footage to train robots. So it will be an actual human coming. They'll clean your apartment for free. And in exchange, they get to get all that data and use it to train robots. And now they, as part of this announcement, they indicate that somehow they will, I'm sure they will, scrub all personally identifiable data or anything private. Which they won't. Which, I mean, come on. There's no way they're going to do that. The sheer difficulty of that is actually like, I mean, that's a very difficult problem to solve in itself. You know there's going to be a headline, like in two years from now, apartment free apartment cleaning AI startup stores videos of people engaged in intimate acts as they were cleaning rooms. Wait, wait, wait. Yeah, all the robot vacuums have that. I mean, I personally wouldn't, but I'm sure people will. No, no, but wait, wait, wait. Hold on, hold on. But that would assume this is an actual human coming into your apartment with a camera. If you are still having an intimate act during this person cleaning your house, that's on you, my man. That's on you. I mean, yeah, you may go to jail for that, but. That's totally on you. I'm just talking about if you have like some like contracts laying out that are getting scanned or something. You've got to think bigger, Ronjan. I think that's my advice to you here is you've got to think outside the box. So, so one thing I'll say, I actually tweeted, is this real? And the founder had actually responded, yes, we've already served some over the last few weeks and globally over 10,000 contributors collected their skill demonstrations. I found this very fascinating because he calls them skill demonstrations, the house cleaning, because it's an actual human going and demonstrating a skill like vacuuming to a camera, which already was just, I don't know, fascinating in itself. But I also realized that probably means you only get one cleaning, right? Because after that. I don't see how you would get more than that. Because they don't need to. The skill has been demonstrated in your space. Wait, would you, we're running out of time. Would you, would you do this? Like, are you tempted to allow them to come in and clean your place? I am tempted from purely, like, I just want to see the person who comes into my house. I just want to like, do they have a camera on their back? Is it like, is it a GoPro? It's a body cam. Is it like, is it a rig? Is it a rig of cameras? Is it like one of those like virtual reality motion capture suits? I don't know. Like Google Street View in the middle of your living room. I'm more curious about that. I would like to talk to them. I still am a little on, it's less the data privacy. I'm more concerned about you giving ChatGPT your Gmail than this random shift guy showing up in my house. So by extension, I should definitely invite the shift guy in for a cleaning. Yeah, at this point, I mean, it's all gone anyways, so you might as well let the shift guy in. Yeah. I mean, just on the, on the ChatGPT, I mean, ChatGPT has my email. Google has my email. Every tech company has my email. You know how many places I've signed in with Google? You know, it's like, okay, what's another one? No, no, you don't check every single permission that you're given when you do sign in with Google in detail. No, I don't. I'm just joking. Just like when the shift cleaner comes in and I have to sign something, sign away. Sign away. And then go have my intimate act while the shift cleaner is right next to me. I highly discourage any of the, there's varying forms of illegality actually involved in that. I mean, if it's a robot, that's one thing. If it's a real person, something. I mean, you know, that's a good question. I don't know because the robot's being watched. We only have one minute left. This is a very philosophical debate, but. Listen, folks, don't do that. Don't. It's a terrible idea for me. I just can't get out of my head with the Roombas. The Roombas were taking pictures of all these intimate acts. And I just found that astonishing that people were reviewing them and posting them in their slacks and stuff like that though. That creepy Roomba just. So that sort of, I don't know. Yeah. I don't, I was going to say something. I'll just, let's go. Let's have a nice weekend. I think it's time to, I think it's time to, it's a beautiful weekend out in New York. Have a great weekend. All right. Have a great weekend. Big technology, AI summit, summit.bigtechnology.com. I'll be there. Ronjan will be there. And thank you again for listening and watching. And we'll see you next time on Big Technology Podcast. Most people don't realize how much their personal information is being bought and sold every day. 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