The 50 Most Influential People in Tech, Fed Raises Rates, AI Adoption Has Stalled

0:13Welcome, everyone, to The Information's TITV. My name is Akash Pasricha. It is Thursday, September 17th. Today on the show, we're going to be talking about what the Fed raising rates means for the AI sector. We're then going to hear about Bridgewater co-CIO Greg Jensen's view on AI regulation. My colleague, Dakin Campbell, spoke with him, and we're going to unpack that conversation. We're also bringing on Menlo Ventures to discuss some new data they've collected on consumer AI. We're going to close out the show with a conversation about the informations newly released of the 50 most influential people in the tech sector.

0:50It's going to be a great show, so let's get right on into it. the fed raised interest rates yesterday it has been three years since that has happened it looks like there will be another hike later on this year that will certainly impact the ai sector as debt has become so crucial to the build out i want to bring on paul meeks head of technology research at freedom capital markets for a conversation paul welcome back to the show great to have you here good to see you cash okay so first in three years more to come we've got this AI build-out going on in the background. How do you think that this is going to affect the AI story?

1:27It's a clear negative, but dampened somewhat by the fact that everybody sees it coming. Because you can take a look at Fed funds futures contracts and know what percentage probability, which is awfully high when rates hikes are coming or when rates fall on the other end of the cycle. But it's going to really hurt things in two ways. The first way is the obvious problem, which is all these AI infrastructure builders are aggressively borrowing money because they have to fund these huge builds. You know, cumulatively, by the end of the day, when we get through all this AI infrastructure building, we're going to cumulatively have spent several trillion dollars.

2:10And so most of these companies, the NeoClouds, the AI co-location companies, they are subprime credit rated. And so this is not good. But there's going to be other ways around that. Now, the offset is… What are the ways around that? Well, the key is this. The offset is that recently, because demand is so voracious and there's still not enough supply, and actually the gap is getting worse and worse, they are getting a much better pricing on their deals. So much higher, two or three X what they were getting a year or two ago, revenue per megawatt. So their P &L should improve so they can pay off your higher interest expense.

2:59So that's the offset, nothing really mechanical. The other way that we get dinged is, you know, all these companies have cash flows that are estimated so far out in the future that just on a valuation basis for an equity analyst like me, rising interest rates equals rising discount rate for these cash flows really hammers the stock valuations. So one, through higher borrowing costs. Two, just damns the valuations with a higher discount rate. So how do you think the AI companies change their strategy in an environment like this? I mean, pricing is one thing, I hear you. Do they temper their ambitions at all?

3:46I'm thinking about the CFOs of all. I mean, and by the way, we should say, it's not like they haven't modeled this stuff in. I mean, like you said, this is stuff they've been expecting, but I wonder how you might see the dialogue from these companies change on earnings calls, guidance. I'm talking about the public companies, right? We'll talk about the private companies in a second here. What are you expecting there? So one of the things that they've even started to emphasize in this last round of Corleek calls is the inflection in the adjusted EBITDA margin or even EBIT margin for some companies where they're starting to see as you turn on the capacity, usually there's a couple weeks between what they call active power and revenue generation, that the inflection in the margins are so strong and actually shows you a business that's attractive to finance.

4:47And so they really have to show, hey, it's not just bringing on contracted capacity and over time converting that to revenues. Obviously, that's really important. But the fact that as they scale these businesses, they get to adjusted EBITDA margins 60, 70, 80 % in some cases, which people turn around and say, wow, I'm cool with financing this business because it looks like it's going to be a good one. So you're talking about like what Oracle that - We haven't seen that uptick yet, but we're starting to see it, the inflection in the margins. And so are you talking about sort of, you know, Oracle's earnings?

5:23I mean, they talked a lot about the ways that they were moderating their costs and keeping margins somewhat afloat with the prepayments and the... Yeah, I'm talking about the NeoClouds and the AI Colos, of which, for example, Oracle and the rest of the hyperscales would be customers. Out of the five major hyperscalers, including Oracle, Oracle seems to be the only one that's too far out on its skis with burning through its free cash flow. I mean, the others, you think about it, and this is different than those who financed the internet bubble back in the late 90s, early 2000s. Those were a lot of really crappy companies that should not have gone public.

6:04But the 90 % to date of the AI infrastructure building has been with four or five of these hyperscalers that have very strong balance sheets, all investment grade, even if they bleed some free cash flow. over time, people should be very comfortable with their balance sheets and their financial wherewithal. And what are you expecting for CapEx? Looking ahead, the growth rates that we've seen, do you expect them to continue at that or do you expect them to temper? I expect them to temper a little bit, but I expect CapEx from the hyperscalers, and now we're getting into enterprises also doing these deals directly, not through the hyperscalers.

6:48I expect it to go fast and furious at least through 28, maybe through the end of the decade. And you can expect 60, 70, 80 % increases per annum. But I don't think we're going to be shrinking either. I think we have robust growth for several years. And I used to say 28. Now I'm comfortable saying end of decade. Right. And the rate environment won't affect that. Well, it depends if we have two rate increases here in this cycle and then done. If we end up having a slew of them, of course, part of it has to do with the price of oil, which drives inflation. And of course, it has to do with what's happening with the US and Iran.

7:33But as of now, I am a little bit worried, but not too worried about two increases in rates with one already behind us this week. Right. Let me ask you a question about the private companies, the labs. I mean, one thought that I was having this morning was if you're a public company and you're investment grade, you can show to investors that, hey, here's what our financials are looking like. That's the premise on which they can choose to take your debt or not. do they have an advantage at all over the private companies right now insofar as how they can fundraise in this uh new rate environment or is it still is it the same story i'm basically asking are the private companies at a disadvantage here in an environment of of rates going up i would say that the smaller incognito private companies maybe but when you think about some of the uh goliaths you know these two trillion dollar market cap aspiring companies you know spacex anthropic open ai they are so large and they are so carefully scrutinized and if they like it or not maybe it's not a press release maybe it's a leak we know their financials because they're essentially in the public domain so i think for those guys and those are the ones that really move the needle.

9:02Don't think it's necessarily a disadvantage. In some aspects of their business, might be attributes compared to public companies. Because when you're a public company, every 90 days, you have to come to the altar. Kind of sucks. Yeah. Well, what about the venture capital sector? What do you think this means for, and you're in the business of investing in bigger companies, but what do you think happens to that landscape? Well, I think the AI infrastructure build, and hopefully followed by AI monetization will be a strong and durable theme. And that should really trump, maybe no pun or pun intended, the pushback that you might get from higher rates.

9:44Now, remember, my view is rates will be up another 25 basis points before Christmas. And then hopefully we're steady state. All bets would be off if we continue this cycle pretty far into 2027. Paul, can I ask you a question about a different headline? We saw last night that OpenAI disclosed six new concerning incidents with their models. This is the whole question of rogue agents continuing to reverberate through the sector. What's your reaction to this? I mean, certainly as an investor, how are you viewing this? I think a lot of it is marketing spin, positioning ahead of IPOs. You know, for a while, Amode over at Anthropic wanted to be seen as the AI good guy.

10:39Remember months ago, they pushed back on the Department of Defense saying, hey, you're not going to be able to use our technology for surveilling Americans or anybody else for that matter. And then that was Jeff DePosso's with Sam Altman over at OpenAI. And he was the bad guy. I went to court and got really messy with Elon Musk. And so I will tell you that I watch it. Of course, I'm concerned about it. Of course, I think we need to have at least some sort of guardrails on AI development, not just domestically, but globally. But part of it is the race between Anthropic and OpenAI to go public. Anthropic positioning itself as the good guy.

11:19open AI, not happy that they're being perceived as the bad guy. And so they make some of these mea culpas and try to get ahead of the bad PR. So I think part of it is smoke and mirrors and IPO positioning. Right. Well, Paul, I want to thank you for coming on. That is Paul Meeks, head of technology research at Freedom Capital Markets here on TITV. many people are calling out for and against regulation in ai our colleague dakin campbell spoke with greg jensen co-chief investment officer at bridgewater associates one of the world's largest hedge funds about what he thought i want to bring on dakin to talk about that conversation dakin welcome to the show it's great to have you back Thanks.

12:07I love being here. It was a great interview. I encourage everyone to read the full transcript on our website. But I do want to talk to you a little bit about your takeaways from it. Set the stage for us a little bit. I mean, Greg Jensen, for those people who don't follow the finance role as closely, who is he and why did you ultimately want to talk to him about AI? Sure. So as you said in your lead-in, Greg Jensen is the co-chief investment officer of Bridgewater Associates. It's one of the biggest and most famous hedge funds in the world. Greg has been there for 30 years now, so he knows, lives and breathes Bridgewater.

12:46He's also been thinking about AI since at least 2012, he told me. And he was an early investor and open AI. And I believe Anthropic paid its payroll the first week it was a company with a check that he wrote to them. So he's not just a lion in the investing landscape, but also somebody who's been following AI for a very long time. And we'll go through the interview step by step here, but what was the most surprising thing that he told you in the conversation? so greg has written an op-ed in the new york times he has given other uh interviews but i guess i was not prepared and talking about this but i was not prepared for the degree to which he wants the big ai labs and the ai industry to be regulated you know bridgewater as one of the world's most successful hedge funds uh the people who live there who work there are capitalists i I would say, with a capital C.

13:51And so it's not often that you sit down with somebody who has benefited so much from capitalism and sort of lived and breathed it to be calling for heavy regulation of an industry. That's just not a common message. What was he suggesting specifically? Yeah, so he really wants the AI labs to be regulated. He wants anybody that is controlling a significant amount of compute, which he threw out a number, 5%, to be regulated. he wants that to be a cap too, 5 % or something like that to be a cap. He made the point that OpenAI and Anthropic in the next couple of years are going to control between 35 % and 50 % of the world's compute resources.

14:48He would also like any models that are deployed in the U.S. ecosystem, as he put it, to be regulated, to be tested and overseen. So he's sort of laid out a pretty extensive regulatory regime that he would like to see. And was he drawing a parallel here to, I mean, banks and this idea of systemically important financial institutions? I mean, is that sort of the model that he was trying to apply? Yes, that is another thing. I should mentioned that as well. He does want the big compute owners to be regulated like banks. You know, honestly, we didn't get into it too much. But, you know, as viewers may know, the big banks are regulated quite heavily by the Federal Reserve and other regulators because they have so much control of largely of deposits, of consumer deposits.

15:48And so he was laying out a or suggesting that maybe a similarly large and extensive regulatory mechanism or regime should be directed at the large compute owners. So not just the AI labs, but others that have large compute resources. I'm trying to think about this critically here, how the AI labs themselves would feel about this type of regulation specifically, because they've obviously said, you know, we agree that we should pace the frontier, things should go slower, there should be an independent review body to keep things safe. I mean, they certainly have not said anything to the effect of cap our growth or, you know, put a cap on how much compute we get.

16:38So my assumption here is just that they would be very against this, unless I'm missing any angles here that you thought about after? No, that's my assumption as well. It did occur to me as I was talking to him what the big labs would think about one of their first investors coming out and publicly calling for them to be regulated in this way. I mean, over the years, I've talked to lots of bankers. They don't like being regulated as much as they are, almost to a single banker. So I can't imagine if you're not regulated like that, that you would have any enthusiasm for stepping into that kind of a regime.

17:23So why do you think then he is calling for this? Someone who, as you said, has benefited tremendously from being a capitalist the last 30 years. I mean, why is this an inflection point, do you think, in his mind? Yeah, that's a good question. We didn't get into it a ton, but from all that I can tell and all that I've read of other interviews he's given, he feels strongly about this. He feels AI is at a place where if it is not regulated, it can do the real damage. One of the things he told me that I found surprising, one of Bridgewater's models cheated on a test that they gave to it. So he has seen his models go or at least a single model go rogue in his own lab environment.

18:16So and because he's such a because he was such an early investor, he's having conversations with folks at the big labs and hearing about their concerns and hearing about sort of the fear that certainly some of them have. So it feels like we are like he believes that we are an inflection point. um you know there may be some other alternative motives i i haven't uh thought about that or or sort of uh played that out on the chessboard well no but i mean look it's it's always interesting to see how uh people's perspectives not necessarily change because we haven't been in this ai moment before but again people surprise you in all sorts of ways so you know it's kind of interesting to think about why they think what they do you know you talked about um one of bridge modern bridge Bridgewater's models cheating, which was surprising.

19:11You also talked to him about enterprise data security and Bridgewater using these models and whether or not he has any concerns about the models training on their proprietary data. What was his response to that? Yeah, I was surprised by that. I asked him what their infrastructure setup looked like and how they were thinking about their own compute resources. And he told me that they rent all of it, honestly, and that a lot of it is held in the cloud and that they actually do some training on other people's compute and on other people's servers. So, you know, he made the point to me that 15, 20 years ago when AWS was first becoming, first establishing the cloud business, Bridgewater had a long conversation with them about getting around intellectual property and getting comfort with putting their intellectual property into the cloud.

20:13So he didn't seem all that, you know, flexed about it, to be honest. You know, on the other hand, we've seen other hedge funds, certainly Jane Street and others, you know, securing their own compute, building their own or renting out their own data centers. So, you know, his willingness to use the clouds and to simply rent his compute, I thought was pretty interesting. Right. Well, it's a great interview. Like I said, I encourage everyone to check it out. He also has some comments on the AI trade itself, which I will let listeners read for themselves. That is Dakin Campbell, our AI finance reporter here at The Information.

20:59Menlo Ventures released a new report on the state of consumer AI. There are some interesting findings in that study. It was a canvas of about 5 ,000 people. I want to bring on Amy Wu Martin, a partner at Menlo. She was one of the authors of the report. Amy, welcome to the show. It's great to have you here. Thanks so much for having me on. So I want to ask you about some of these findings that you guys put together here. I mean, the first line in the report is kind of interesting. It reads, consumer AI adoption hardly grew, even as spending tripled. But the share of US adults using AI rose only by three percentage points.

21:39And this was, I think, 61 % to 64%. Yeah, we were surprised by some of the findings. What do you think is behind that? I think the numbers show that, you know, obviously people are using AI, but people who are not using AI aren't using it. You know, there's like a very deeply entrenched space of holdouts. You know, people who are deeply distrustful, they worry about their privacy, They quite frankly prefer to talk to a human. It's about a third of Americans right now. And that has not moved very much in the last year. But if you think about what has moved, so let's say the two thirds of people who do use AI.

22:17Last year, when we surveyed consumers, only about 3 % of AI users actually paid for AI. And now it's about half of people pay for it. And so it's a pretty remarkable actually change in the market, just in, I think, a little different ways than even we thought. Right. And I mean, you know, you sort of allude to this in the report. It very much is a story right now of the power users dominating the spending. It's not just the proportion of people who are paying. It really seems to be a small core of people that are carrying a lot of the expenditures. That's right. I think it's around like 40 % of people are paying for, it accounts for about 60 % of spend.

22:59And I'm sure that, you know, as you get to like what is the 80th percentile, 90th percentile. It's even more extreme. I mean, I think consumer oftentimes follows a power law and, you know, we see that here as well. It's kind of interesting if we look at, you know, if you look at the power users are also using agents. Among people who have tried using agents, I think over 90 % of them have paid. And so, you know, you really have, you see this like wide spectrum of power users that are using it. And there are a lot, as we see, you know, these are people who are using AI for over two hours a day, you know, on things helping them with writing, creative research, et cetera.

23:39And then, you know, other people who don't. And if we look at the profile of people who are using AI, powered users, a lot of times they're a bit older. They use AI both in the workforce and at home. they are a lot of times their parents, you know, who are very time poor, but cash rich and are willing to pay to save their time. Right. Now you talked about agents and, you know, I was looking at some of the numbers too. So 64 % of people use AI, but 24 % of AI users use agents. And so, I mean, if you put those two numbers together, you get to about 15 % of people, period, regularly use agents, which is a pretty small proportion.

24:26And yet, one of the predictions that you guys make in the report is that 2027 is going to be the year where AI agents really become mainstream in terms of their use. So I'm thinking about, you know, I don't know. I have to be honest. So 15 % of everyone is using agents. I mean, I don't know that I think 2027 is going to be the year of takeoff. And I know we've got instinct and muse, but walk me through a bit of your analysis here. Why did you guys have so much conviction here? We've been waiting for a tipping point in consumer AI use for a while. Consumer adoption has historically always lagged enterprise, Right.

25:10Enterprise executives, they're constantly experimenting. It doesn't have to necessarily work, although right now I think they're looking very hard at ROI. Consumers won't use anything that they're not getting, you know, they're not saving time, money on making their lives better by probably like order of magnitude. Right. They're notoriously maybe they are experimenting with things, including agents. But if they're really going to retain, it's going to actually have to change their life for the better. and so we think that the technology, the models essentially and their capability between memory and also execution and being able to string together on multiple tasks, rate of error has finally dropped to a point where you do have this moment and I think that's why you see so much attention around products like Muse, which is right now the number two most downloaded app in the world.

25:57Great job Meta on that launch. Of course, Instinct in town. that people, I mean, my friends not in tech are using these products and experimenting with them. So I think that we've reached a tipping point from an investor perspective. I think that there have been very few consumer founders in the last few years. It hasn't been cool. You know, it's been really hard to make money. And now I think there's a moment, there's status associated with consumer tech now. I think we'll see a lot more. Every consumer investor is the most passionate people you'll meet, really, because consumer always goes through the cycle of consumer is dead, consumer is back, consumer is, you know.

26:40We go through a cycle, but really, it's been a desert for several years in consumer tech, I think. If you think about it, there's only a couple of products in consumer AI tech. It's basically OpenAI. It's been Suno. So, you know, now it's instinct and we can say talent is still B2B. But yeah, I think we're about to have a wave. Yeah. Let me ask you one more data point here. So you guys talked about how AI use varies by income. And so 77 % of consumers and households earning$100 ,000 or more use AI. but it's only 56 % for those households earning under 50 ,000. How do we, I mean, this is, I guess, more of a sociological question, I guess, that I'm asking.

27:32You know, I'm sort of trying to think about the ways that social media expanded the demographics that it became commonplace with. Why do you think that finding was the case? and how do you think we eventually get to the point where everyone of all income levels is using ai as frequently yeah i think if it's it's a socioeconomic thing it's also an age thing because definitely younger people are used are more likely to be power power users and certainly more likely to be making money using ai right now and so um you know i i think that they're the fact that you have to pay for it is one thing. I think that's much tougher for lower-income families.

28:15Also, there's a problem of just time. Do they have time to be experimenting? But I do think that if there's a push around from an education learning perspective to get more workers in the workforce trained on these next-gen tools, they're going to be at a disadvantage in terms of employment. And so, yeah, I think a lot of AI tool adoption starts in the workplace. and so you see a lot of white collar workers getting exposed to them and then bringing them to the home. It's interesting actually about 50 % of our AI users who pay actually are paying it out of pocket and so it's not that they're we found that it's not that they're employers that are paying for all these tools but I think a lot of the usage probably starts there and so although although we I mean we do know that I mean the usage starts at work but But as you said, it ends up being that people even quietly use these AI tools without their companies knowing.

29:10That's true. That's true. A lot of enterprise is a lot of tools. Yeah. I mean, we've had people on the show saying, we monitor things very closely. And I'm like, I got to tell you, I don't know that you're monitoring well enough because people still need to be used. Don't ask, don't tell, even if there's official policies. Right, right. Okay. So let's bring this to sort of the news of today then. I mean, we saw OpenAI has disclosed six new concerning incidents. There's this whole discourse of AI ending the world. I mean, now, I mean, how do you think that affects adoption? I mean, certainly there are going to be people that say, I don't want to use AI because I'm afraid of it taking my data or the risks that it posed do you not think that's going to have an impact i think you've already been seeing the impact right i mean this is where it's like about a third of americans have still not used ai and um and uh priced in basically it's baked in it's already priced in it's baked in yeah we saw that even last year we see that this year uh and so yeah and i saw that report um come out i was i have a 10 month old so of course i i am worried about what will you know what will my child sort of grow up into?

30:28I think that there needs to be guardrails. To be honest, I'm more worried. It's like really great that OpenAI is disclosing a lot of this and Anthropic is as well. But I don't think that the open source companies necessarily are, particularly in China. And so, you know, I think that alignment is important. Right. Great. Well, Amy, I want to thank you for coming on. That is Amy Wu Martin, a partner at Menlo Ventures here on TIT. It is a big day here at The Information. We released our new list of the 50 most influential people in tech. It is not just a snapshot of influence today. It also spotlights people that our newsroom believe will shape the tech industry in the years to come.

31:16It is very comprehensive. Most of our newsroom contributed reporting in some way to this list. But our weekend reporter, Jemima McAvoy, was one of the leads alongside our editor-in-chief, Jessica Lesson. I want to bring on Jemima for a conversation about her biggest takeaways. Jemima, welcome back. It's great to have you. Thanks, Akash. So you decided to put this list together. I mean, you could have picked anyone. How did you even decide? What was the methodology here? Yeah, it was definitely a daunting task. The first thing we had to do was figure out how we're going to define influence. We made a big distinction between someone who has power and someone who has influence.

31:57The CEO of a big company could be powerful, but that doesn't mean that people listen to him or her. So a question we kept asking ourselves throughout was, like, would other tech leaders pick up the phone for this person if they called? And so that was a guiding force. And then the second thing was we didn't want to just define or figure out the influential people today. We wanted to figure out the influential people moving forward. So the other key part of our methodology was, will these people continue to be influential over the next decade? So a big part of this was drawing from the expertise and reporting of our newsroom, who are among the foremost experts of the industries and companies that they cover.