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

Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We cover: 1) Companies are reconsidering their AI spend after token consumption explodes 2) Is this a widespread issue or a big deal made out of a few companies? 3) The bigger problem: only 18% of tokens are spent on things that ship. 4) Are investment decisions being made due to unrestrained tokenmaxxing? 5) The circular investment problem is real 6) A look at the memory chip boom 7) Anthropic passes OpenAI as the world's most valuable startup 8) Robinhood let's your favorite chatbot trade for you 9) Should you connect your gmail to ChatGPT? 10) Would you get your house cleaned for free if the cleaner videotaped it for training data? Join us for the Big Technology AI Summit: https://summit.bigtechnology.com --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Want a discount for Big Technology on Substack + Discord? Here’s 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b Learn more about your ad choices. Visit megaphone.fm/adchoices

• 0:00Speaker 00

  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. This episode is brought to you by Genesis. What does it actually take to put Agentic AI to work across an entire enterprise? I recently spoke with Genesis Chairman and CEO Tony Bates about why orchestration is emerging as a competitive advantage in customer experience, and what companies need to get right in the AI era. Then, I sat down with Adam Mitchell, Head of Enterprise Business Solutions at Voya Financial, to go inside a large-scale Agentic CX transformation,

• 0:43Speaker 00

  including the business decisions, trade-offs, and lessons along the way. You can watch both conversations now on my YouTube channel today. It's never been more challenging to get frontier compute. How do you know where to look, who to trust, or how much to pay? Akash is an open cloud that provides easy access, flexibility, and peace of mind. That's how companies like Razer were able to cut their inference cost by 15 times. Visit akash.network/alex for a free consultation. That's akash.network/alex for a free consultation.

• 1:19Speaker 00

  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 $1 trillion 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 Ranjan Roy of Margins. Ranjul, great to see you.

• 1:59Speaker 01

  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.

• 2:16Speaker 00

  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?

• 2:45Speaker 01

  Ration.

• 2:45Speaker 00

  Let's go with ration. Corporate ration, ration is food, right? All right, I'll start that.

• 2:53Speaker 00

  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. Ranjan, I just want to kick to you. Basically, what we're seeing is story after story of companies

• 3:36Speaker 00

  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 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 where the actual value is much more minimal than what they're seeing? And if that's the case, you know, could this

• 4:19Speaker 00

  all implode or slow down? What's your reaction?

• 4:23Speaker 01

  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

• 5:06Speaker 01

  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 Claude bills.

• 5:50Speaker 01

  Everyone was in the command line, you know, cranking out whatever they wanted in Claude 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, it's kind of making a mockery of, of our industry.

• 6:26Speaker 00

  Well, let's just talk a little bit about the magnitude of this. So this is from Axios going 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 amazing, this 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.

• 7:08Speaker 00

  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, the other examples, you can start to peel away, you know, some of these. So Starbucks, like it had this inventory tool, but it was a, it was a visual intelligence, right? So I think that that was mostly a computer vision tool. With, with Microsoft canceling its

• 7:52Speaker 00

  cloud code licenses, yes, it was financial, but also Microsoft has a competing tool. And so it sort of leaves you with, 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.

• 8:33Speaker 00

  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?

• 9:05Speaker 01

  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 Claude 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 Claude code and no one was monitoring anything and you could not actually see how much you are burning and you're being incentivized in many cases, of course you're going to.

• 9:48Speaker 01

  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 Axios reporting that a 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 that in Meta's AI token leaderboard, one of the employees

• 10:18Speaker 01

  Use 60 trillion tokens, which would be actually be $900 million at today's API prices. So I'm just saying, if you're trying to guess who could it possibly be? There's, there's a pretty finite, you know, the universe of companies that it could actually be. But

• 10:34Speaker 00

  Well, by the way, you know, it's sort of interesting because you can actually take out a number that you might be thinking about, right? You can remove Amazon, you can remove Microsoft, and you can remove Google. And you certainly can remove Apple, right? So it kind of leaves us with Meta.

• 10:47Speaker 01

  You certainly can remove Apple and all that. So I think, but so then you start to think, does that $500 million? Anthropic is getting to count that probably is $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.

• 11:32Speaker 01

  And to me, that, 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 the, 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 so all because a Meta leaderboard or unnamed company leaderboard, someone was just cranking out tokens. Like to me, that's one of the most fascinating and crazy parts. Do you, do you think I'm? Exaggerating the potential downstream effects of these kind of isolated issues?

• 12:16Speaker 01

  Or do you think they are tied together?

• 12:18Speaker 00

  Yes, I do. I do think you're exaggerating the downstream effects. Like, 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 with, for what you will. But even if, you know, you still had accounting tricks, you couldn't fake all of this. In January 2025, it was a billion. May 2025, three billion. June 2025, four billion. August 2025, five billion. October, seven billion.

• 13:02Speaker 00

  December, eight 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...

• 13:18Speaker 01

  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 that, the fact that that was happening, and when you see that curve in terms of their revenue increase, it is real.

• 14:03Speaker 01

  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 Claude Code was a phenomenon. I mean, it was. It was like to truly bring a Gentik-

• 14:27Speaker 00

  It is.

• 14:27Speaker 01

  -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.

• 14:49Speaker 00

  There was a story about this guy that you read this week?

• 14:52Speaker 01

  I'm actually conflating two different stories. One about 20-something Koreans taking out margin loans to buy-

• 14:59Speaker 00

  Memory stock.

• 15:01Speaker 01

  -memory stocks. And also apparently like the Ferrari dealerships have sold out inventory for the next two years in South Korea as well. I've just put those two together in a convenient narrative. I recognize the conflation.

• 15:15Speaker 00

  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, 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-

• 15:56Speaker 00

  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 Intelligence AI, a startup that aggregated data on more than 2,000 companies using AI, using advanced AI for coding.

• 16:39Speaker 00

  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.

• 17:23Speaker 00

  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?

• 17:33Speaker 01

  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,

• 18:15Speaker 01

  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 with any kind of standard business process. That's not 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.

• 18:59Speaker 01

  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 the getting that technical. But like that dramatically would reduce the actual tokens consumed in the 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.

• 19:42Speaker 01

  Because any new experimental technology, that's part of the that's part of the process.

• 19:48Speaker 00

  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 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."

• 20:31Speaker 00

  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, actually real.

• 21:13Speaker 00

  And to me, that's, that, to me, again, is sort of where you could see, if you were going to see like a real pullback, it would be this sort of reckoning of like, "Oh goodness, we're using these bigger models and, you know, we're not seeing the impact that we were hoping for."

• 21:28Speaker 01

  It is Uber, and I guess, I mean, in terms of like dramatic innovation from a company, I-

• 21:36Speaker 00

  Ron, John, they're a tech company. That's what I'm trying to say. If Uber is not seeing the productivity, is Lowe's seeing the productivity?

• 21:44Speaker 01

  Well, okay.

• 21:46Speaker 00

  Home Depot?

• 21:47Speaker 01

  I mean.

• 21:48Speaker 00

  If Uber can't figure it out, are they?

• 21:49Speaker 01

  Home Depot's chatbot's 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 gonna see a pullback and we are gonna 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,

• 22:30Speaker 01

  obviously, you're not gonna see any kind of like concerted progress, ROI, whatever it is. I think like, to me, this just kind of captures the whole thing. The Starbucks one, too. I don't know, like that you'd 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'd mentioned computer vision. It was basically like, you know, taking photos and then trying to analyze those photos. And it like analyzed the milk, the syrup, the sauces and an inventory count. That's a hard problem to do in kind of an unstable environment

• 23:14Speaker 01

  like the real world and in Starbucks of all places, which is a pretty chaotic place often. And the idea that you're gonna solve that versus a 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 gonna see dramatic improvement.

• 23:56Speaker 00

  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 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 coming to grips with how many tokens they're 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

• 24:41Speaker 00

  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 some ways, that could even be like an indication that the technology is working well. What do you think?

• 25:00Speaker 01

  I guess, I mean, but that's exactly what I was saying, that this is all so recent that it's, uh, 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.

• 25:43Speaker 01

  So I don't think, again, anyone who has used these tools, you can just sit there, go down rabbit holes, crank tokens and end up nowhere. Plenty, like.

• 25:54Speaker 01

  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.

• 26:08Speaker 00

  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.

• 26:46Speaker 01

  I support that. I support that.

• 26:50Speaker 00

  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?

• 27:13Speaker 01

  And I will, 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 and imagine that everything is going to be different.

• 27:51Speaker 00

  So for you, so for you, the real problem is the 20% that's being token maxed, assuming my 80/20 breakdown is.

• 27:57Speaker 01

  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.

• 28:23Speaker 00

  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 clouds 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 in Google and

• 29:04Speaker 00

  Anthropic, and also in its own divisions. And then when the, you know, when the 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 Roger, and 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.

• 29:40Speaker 01

  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

• 30:21Speaker 01

  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 of Google, reported 62.6 billion dollars in profit. Google is a cash machine. They always have been. 28.7 billion of that was a paper markup on Anthropic.

• 31:03Speaker 01

  Amazon, 30.3 billion in profit, 16.8 billion, same Anthropic paper gain. So 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.

• 31:45Speaker 01

  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 their investors.

• 31:59Speaker 00

  Let me play devil's advocate here. I mean, all right, let's say you're Google. You have your big investment in Anthropic. You invested it when it was like a billion dollar valuation. Now it's a 900 billion dollar valuation. Why should you not mark the markup in your shares value as profit? That is money that you made.

• 32:21Speaker 01

  No, no, you have to. I mean, you actually have to. Like, so

• 32:25Speaker 00

  Okay.

• 32:26Speaker 01

  I don't think they shouldn't, but it is still, I mean, it's still the case that that is half their, 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.

• 33:09Speaker 01

  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 in 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?

• 33:50Speaker 00

  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

• 34:05Speaker 01

  Yes.

• 34:05Speaker 00

  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 had four, has 49% of its 62, 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.

• 34:45Speaker 01

  Well, not just a curse, but I mean, you take even again, maybe Apple comes out of this just golden that they're the the only ones who like somehow managed to weather by purposefully stay out of it. I think like those that that kind of forward looking spending, and this is all in the next three to five years that everyone is 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

• 35:25Speaker 01

  as everyone has been promising? And again, that 82% like, I think that's why this has caused so many alarms like, 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

• 35:44Speaker 00

  Eighty billion.

• 35:44Speaker 01

  Eighty billion.

• 35:45Speaker 00

  Eighty plus billion.

• 35:46Speaker 01

  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 Dragonneer and Ultimeter 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

• 36:15Speaker 00

  Okay, so 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 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 $1 trillion 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

• 36:59Speaker 00

  $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, you know, sort of secondary or tertiary group of shareholders, those that have had the memory chip stocks very rich while also making like life difficult for anyone who owns a camera and wants a new memory stick because OpenAI has bought it. Your thoughts on this?

• 37:30Speaker 01

  Well, these are my second and third order effects. In that, 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 like, this is something I 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.

• 38:10Speaker 00

  Three, three companies.

• 38:11Speaker 01

  Three companies, sorry, three companies. Like, come on.

• 38:15Speaker 00

  That's bananas. That will fall. It has to fall inevitably, right? I mean, not investment advice, but that has to fall.

• 38:20Speaker 01

  But, 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's adoption? Like, what are you seeing?

• 38:41Speaker 00

  Such a finance question.

• 38:42Speaker 01

  Yeah. What are you like thinking about how companies are going to leverage AI? Are you seeing the ROI from a, like, are business operations improving? It's literally, where do you think the next bottleneck is? Because that's, that is where we are again in the cycle, that the mania is so strong. And everyone missed, if you weren't, if you didn't get in, you missed the memory chip bottleneck. What's going to 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.

• 39:24Speaker 01

  So is that a healthy market? I don't think so.

• 39:28Speaker 00

  No.

• 39:28Speaker 01

  Do you?

• 39:29Speaker 00

  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.

• 39:39Speaker 01

  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

• 39:49Speaker 00

  I thought you were gonna say Ferrari.

• 39:51Speaker 01

  No, no, but that that hard drive.

• 39:53Speaker 00

  You won't be able to get one now for two years.

• 39:54Speaker 01

  But that maybe I'll sell my four terabyte hard drive and then I'm cooking.

• 39:59Speaker 00

  Buy the Ferrari.

• 39:59Speaker 01

  Yeah.

• 40:01Speaker 00

  Soon enough, Ranjan, you might be able to.

• 40:05Speaker 00

  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, Semi Analysis 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's gonna run 1pm 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

• 40:49Speaker 00

  and we'll see you on June 18th. Back right after this. This episode is brought to you by App Point. Everyone's racing to roll out AI right now. Co-pilots, chatbots, agents doing real work. But here's the part nobody loves talking about. All that AI runs on your data and most teams have no single way to see it, secure it, and prove it's under control. That's exactly what App Point does. For 25 years, they've been the trusted layer beneath the world's most demanding data, now extended across your entire AI estate. Your data, your cloud, and the agents acting on your behalf. It's how more than 28,000 organizations deploy AI with confidence. So innovation scales

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• 41:54Speaker 00

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• 42:54Speaker 02

  Now, more than ever, we need someone on our side. But Rob Whitman? Whitman's votes drove up costs, cut Medicaid, and risked 350,000 Virginians' healthcare to pay for tax breaks for himself and his donors. He's not on our side. Shannon Taylor will fight corruption, cut taxes, and bring down costs. This November, vote for Shannon Taylor. She's for us. Paid for by HMP, the House Majority PAC dot com. Not authorized by any candidate or candidate's committee.

• 43:23Speaker 00

  And we're back here on Big Technology Podcast, Friday edition with Rajan Roy of Margins. Rajan, the day has come. Anthropic is bigger than OpenAI. This is from the New York Times. Anthropic tops OpenAI to become the world's most valuable AI startup. On Thursday, Anthropic punctuated its ascent by officially passing OpenAI as the world's highest-flying AI startup. It is going to, it raised $65 billion in financing that values it at $900 billion pre-money. What do you think about this? I mean, is this mostly symbolic? Or is this the day that Anthropic truly has passed OpenAI as the top AI lab?

• 44:03Speaker 01

  I wouldn't count out OpenAI just yet because I wrote about this in 2022, I think probably spring.

• 44:10Speaker 01

  There is the altimeters of the world, the Dragonears 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

• 44:43Speaker 00

  No, that happened?

• 44:45Speaker 01

  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,

• 45:30Speaker 01

  900 billion?

• 45:32Speaker 00

  Yeah. 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, 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 Claude 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, maybe excluding SpaceX, but I wouldn't even say SpaceX is an AI IPO. And so, I don't know, I think that this is

• 46:16Speaker 00

  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, 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.

• 46:44Speaker 01

  I actually, what's even crazier to me is that OpenAI had even raised, what was it? A hundred twenty, hundred twenty-two? One twenty-two. And it only got to eight hundred fifty-two post-money. So like, yeah, they, 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.

• 47:29Speaker 01

  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. Cause 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.

• 47:54Speaker 00

  That's a nice conspiracy. I mean, you're right.

• 47:56Speaker 01

  It's not a conspiracy.

• 47:57Speaker 00

  It's true, fake it till you make it, Silicon Valley style.

• 48:00Speaker 01

  No, no, but it's not a conspiracy. It's like, it is just finance.

• 48:04Speaker 00

  Damn it, that's what's happening.

• 48:06Speaker 01

  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?

• 48:43Speaker 00

  You know, it would really be interesting if they went public and then everybody on Robinhood, which has Claude and ChatGPT controlling their trading, just went full hog into the IPO. Because we have a headline, very interesting headline this week from the Wall Street Journal. Robinhood lets customers use AI to trade stocks and make credit card purchases. Robinhood is launching a new feature that lets customers hand their trading and credit card purchasing decisions to their favorite artificial intelligence tools. Robinhood 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.

• 49:27Speaker 00

  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.

• 49:49Speaker 01

  I mean, this is in the grand scheme of the things and kind of like, this is where we need to go. So thank you, Robinhood, for gentifying 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 as the script should be written, Robinhood kind of like finishing this out is perfect to me.

• 50:33Speaker 00

  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.

• 51:08Speaker 01

  All right, all right. You know what? No, no, no, I'm gonna, okay. I'm gonna come around. I'm gonna 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, I'll give it to you. I think, again, this is again in my, my new grants theory that we just cannot have nice things. This actually makes total sense and I like support the concept of it, but Robin Hood

• 51:47Speaker 01

  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.

• 52:08Speaker 00

  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, will have access to your bank account, will ask if you want a portion, some money towards, you know, giving this, this strategy a try, will 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.

• 52:51Speaker 00

  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.

• 53:03Speaker 01

  No, I think they already are in some ways.

• 53:06Speaker 00

  Yeah.

• 53:06Speaker 01

  And we're seeing the very early stages of it where like more often than not now Claude, but also Gemini have seen ChatGPT not so much. Like it'll go build you an entire interactive experience when you're like, dude, just like, what time is the Spurs, uh, the Spurs Thunder game or something like that? Like here's an entire HTML dashboard and a website that can do this for you. So you're already seeing it try to go above and beyond. And yeah, the more access it has, I can imagine the more it'll try to do. But if it's good, it should do a good job of that and help you anticipate things. But we'll see.

• 53:48Speaker 00

  Yes, will happen. I mean, one interesting thing that I did this week was I was trying to research if I had some like a special number, you know, associated with my business, like, like not an EIN, but like something to, 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.

• 54:18Speaker 01

  Wait, I saw a Gmail connector pop up as well. I totally ignored it, but.

• 54:22Speaker 00

  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.

• 54:29Speaker 01

  Better than Gemini, I'm sure.

• 54:31Speaker 00

  Better than Gemini.

• 54:31Speaker 01

  Gemini and Gmail, yeah. Oh, I should go. I should connect it and ask that my question, what's my first email to my wife?

• 54:39Speaker 00

  I have to say, you should do it. I also did it. And I mean, again, like take the privacy concerns into consideration.

• 54:45Speaker 01

  Which are, I mean, they're pretty.

• 54:49Speaker 00

  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.

• 54:54Speaker 01

  It is.

• 54:55Speaker 00

  It's crazy.

• 54:56Speaker 01

  Giving OpenAI access to my email is still kind of terrifying now that I think about that.

• 55:01Speaker 00

  Yeah, but then it will take the next step for you. Right? And, 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.

• 55:19Speaker 01

  You're clearly. Ready to give up more of your privacy in exchange for services involving AI? Is that the case, Alex?

• 55:30Speaker 00

  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.

• 55:37Speaker 01

  Well, that was more of a segue and a lead in too.

• 55:41Speaker 00

  And therefore.

• 55:45Speaker 00

  Go ahead.

• 55:46Speaker 01

  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?

• 56:02Speaker 00

  Because that's happening right now.

• 56:04Speaker 01

  That is happening right now. There's this AI training startup shift wants to clean your home for free. But they will have 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 like somehow they will, I'm sure they will, scrub all personally identifiable data or anything private.

• 56:41Speaker 00

  Which they won't.

• 56:42Speaker 01

  Which, I mean, the sheer difficulty of that is actually like, I mean, it's, that's a very difficult problem to solve in itself.

• 56:51Speaker 00

  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.

• 57:02Speaker 01

  Wait, wait, wait.

• 57:03Speaker 00

  Every, yeah, all the robot vacuums have that. I mean, I personally wouldn't, but I'm sure people will.

• 57:08Speaker 01

  Hold on, no, no, 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.

• 57:23Speaker 00

  I mean, yeah, you may go to jail for that, but.

• 57:26Speaker 01

  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.

• 57:36Speaker 00

  You gotta think bigger, Ron John. I think that's my advice to you here is you gotta think outside the box.

• 57:43Speaker 01

  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-

• 58:22Speaker 00

  I don't see how you would get more than that.

• 58:24Speaker 01

  Because they don't need to-

• 58:26Speaker 00

  You've been, 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?

• 58:35Speaker 01

  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 over, is it a GoPro?

• 58:48Speaker 00

  Some body cam.

• 58:49Speaker 01

  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?

• 58:58Speaker 00

  Google Street View in the middle of your living room?

• 59:00Speaker 01

  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 at my house.

• 59:14Speaker 00

  So by extension, I should definitely invite the shift guy in for a clean-

• 59:17Speaker 01

  Yeah, at this point, I mean, it's all gone anyways, so you might as well let the shift guy in.

• 59:23Speaker 00

  Yeah. I mean, just on the, on the chat, 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?

• 59:35Speaker 01

  No, no, you don't check every single permission that you're given when you do sign in with Google in detail?

• 59:41Speaker 00

  No.

• 59:41Speaker 01

  No, I'm just joking. Just like when the shift cleaner comes in and I have to sign something.

• 59:48Speaker 00

  Yeah, I'll just sign away, sign away.

• 59:50Speaker 01

  And then go have my intimate act while the shift cleaner is right next to me.

• 59:55Speaker 00

  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, if it's a real person, something. I mean, you know, that's a good question. I don't know. Cause the robot's being watched.

• 1:00:07Speaker 01

  We only have one, we only have one minute left. We only have one minute left. This is a very philosophical debate, but.

• 1:00:14Speaker 00

  Listen, folks, don't, don't do that. Don't. It's a terrible idea for me. I, I just can't get it 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.

• 1:00:30Speaker 01

  Creepy, that creepy Roomba just.

• 1:00:33Speaker 00

  So that's sort of, I don't know. Yeah.

• 1:00:38Speaker 00

  I don't, I don't, I was gonna say, I'll just, I think, let's go, let's have a nice weekend.

• 1:00:42Speaker 01

  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.

• 1:00:49Speaker 00

  All right. Have a great weekend. Big Technology AI Summit, summit bigtechnology.com. I'll be there. Rontan will be there. And thank you again for listening and watching, and we'll see you next time on Big Technology Podcast.

• 1:01:02Speaker 02

  Now, more than ever, we need someone on our side, but Rob Whitman? Whitman's votes drove up costs, cut Medicaid and risked 350,000 Virginians healthcare to pay for tax breaks for himself and his donors. He's not on our side. Shannon Taylor will fight corruption, cut taxes and bring down costs. This November, vote for Shannon Taylor. She's for us. Paid for by HMP, the HouseMajorityPac.com. Not authorized by any candidate or candidate's committee.