Goldman Sachs CEO David Solomon on Running a Bank in the Age of AI

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23:01Tracy Alloway:Two sort of short job-related questions. First one, you can was yes or no. It's like those skills that you had, you were very comfortable picking up the phone and so forth and getting maybe people to answer. Today, is there a role for that person still? That same basic? Definitely. Okay. That's what I figured. By the way, I don't think that's going to change. You guys can go look. I gave a commencement speech at Wharton last month. And one of the lines in the commencement speech was, the phone, the telephone is one of the greatest pieces of technology in the world. Use it. A A telephone call to someone is 10 times more valuable than a text or an email.

23:37My daughter says that's an unverified statistic, but I know that's true. And it is. If I call you personally on the phone, it's going to have a completely different impact than if I sent you a text or an email.

23:46Tracy Alloway:Yeah, but I don't know your number. I'm not going to answer. I would also accept a text from David Solomon. Just as the follow-up, and this is more of a sort of specific right now thing. That's not going away. I mean, I really believe, Joe, that's not going to go away. of that mix of new hires, the range of jobs, including engineering jobs, including, can you identify, is there a change different between today and 2026 versus say the pre-Chat GPT era 2021? In terms of like, have you seen a difference yet just in terms of like the allocations of anything with any hiring decision so far? Subtle changes, but you can't look at it in a vacuum.

24:21So you said to me, I can be very detailed with you. I think with all this stuff, It's nuanced. Details matter. If you look over the last 10 years, I'd say what's happened is the amount of engineering talent we had at the firm grew materially on a relative basis to operational talent or client talent. OK. There are a variety of things that happened because of the pandemic that bloated or inflated hiring across all large enterprises.

24:50Tracy Alloway:And so if you say, since chat GPT, like if you take 2022, that was like the high watermark of the bloat. This is the problem with all these comparisons. The high watermark of the bloat from COVID. Historians will be vexed by the confounding variables of 2022 for a very long time. Absolutely. So if you ask me a question, I'm like, okay, 2022. Yes, but that's the wrong starting point. Because if you look at 2022, a bunch of what we've done from 2022 to 2025, and now in 2026, was correcting the stupid things that we did in 2020 and 2021. And so I think you've got to look at it through a 10-year lens.

25:29And what I would say is at this point, if you look at a 10-year lens, it shifted to more heavily weighted engineering. My guess is that's going to shift differently going forward, given the power of these tools and our ability to code. And you're going to see nuanced changes that probably to some degree reduce the number of people that we start with over the next few years, but probably not what you and I would call dramatically. So I don't want to be predictive because if I throw out a number, here everybody's going to start holding me to the number. But I just told you we were running it at 2 ,500, which by the way, looks similar to what we were running at pre-COVID.

26:11but lower than the 3 ,000 plus we were running in 2021. Okay. My guess is it's going to be in the next three years that will contract a little, but not in a way when you and I would say, wow, this is a huge, huge change. We're still going to hire a lot of people out of school. I mean, aside from potential headcount reductions and like cost savings, how do you actually measure productivity gains at Goldman? That is a great question, Tracy. I can tell you some examples of things we're doing where I know we'll be able to quantify some significant productivity gains, but they're more in the category of remaking operating processes.

26:49So what we're doing under what I know you guys have read about, 1GS 3.0. So if we redo our client onboarding, anti-money laundering, KYC processes, and we had a process that had 3 ,800 people touching it, not 100 % of their job touching it, and now we'll have a process with a few hundred people touching it, that's a productivity. When it's done, I can measure the productivity gain of that process. Okay. That's different than saying to me, okay, you've got a bunch of people who work in investment banking. Okay. How much more productive are they? Now, one measure is I can look at the revenues we have in investment banking and the earnings in investment banking and the number of investment bankers we have and the amount of capital we allocate to that business over the last 10 years.

27:34And you know what? Our people are more productive because we're making on a per person basis, more revenue, more profit on a per person basis. But we definitely are allocating more capital to the business and the capital is helping and creating leverage. But there's no question they have better tools. They can do more. We've found ways for them to do more. We also have collaborative power going on inside the firm in the context of 1GS, 1.0 and 2.0 that are adding to revenue growth, it's very hard to pull it apart. But I think every five years we can directionally say, is it more productive? Yes, it is.

28:11Because you go back, when the firm went public, the firm had$6 billion of capital, I believe, and we had 16 ,000 people, something like that, order of magnitude. Today, we have 45 ,000 people and$110 billion of capital. The firm is much more productive against producing reasonable returns on that capital than it was 27 years ago. I mean, that's clear, but that's a 27-year look, not a year-to-year-to-year look.

28:33Tracy Alloway:Here's a question. AI works when there's a lot of data, pooling together a lot of unstructured data. When I think of a firm like a Goldman Sachs or maybe a law firm, et cetera, there's always a little bit of an, I think, I suspect, an alignment problem where maybe the big producer doesn't want to share all their data with the rest of the firm, doesn't want everything in their head just to be in some big knowledge pool that everyone has access to. You might want to be able to take your book of business to a rival shop every once in a while. That's probably always been the case. But I think it's probably a bigger deal with AI because AI could, in theory, really leverage all of that latent knowledge that exists in a lot of people's heads.

29:15Tracy Alloway:How do you think about getting a firm, wide understanding of what's truly known and understood within many people's heads so that you can really maximize this technology at a time when, again, it might make sense for at least some relationship players to keep a little bit of knowledge inside their own head? Well, it's an insightful question. And I start with the fact that one of the things I'm really proud of about Goldman Sachs is Goldman Sachs is less what you described, I believe, than any other firm. Yeah, let's say the other one. Sure. I think that we really have, for a long time, it's been part of the culture, but we really have a culture of sharing and collaboration.

29:50It is not a star system. People share, share, share. It's just such an ethos at Goldman Sachs that I think we have less of this problem than other organizations have. But what's interesting to me about your question, and it makes me really think about it, is it's something that I deeply believe that you started with, and I'd frame it in three buckets. This technology is incredibly powerful when you have a clean data set. Put these models against a clean data set. It is extraordinary. Like it is mind blowing to me what you can do, the speed with which you can do it, the information that you can accumulate and how powerful that is when you have a clean data set.

30:28It wouldn't surprise you. Goldman Sachs has an extraordinarily amazing data set that we're working very hard on to make as clean and possible on everything we've ever done from a trading and investment banking perspective over the last 40 plus years. We happened to build a system 40 years ago called SECDB that was a trading system. So we have data from all our trading that goes back long before most other firms kept data on this stuff. And so we're working very hard on that. But these tools, extraordinary when you have a clean data set. When you don't have a clean data set and you send them out into the world, you get really, really cockamamie answers.

31:05Let me give you a simple example. Just tell a story from a few weeks ago that was another one of these data points for me and really understanding how this all works. It's pretty simple. I was down at the Masters and Rory McIlroy was up by six strokes after two days. And I was like, holy cow, he's probably going to win twice in a row. How many people have won the Masters twice in a row? I know Tiger Woods has. Okay. I think Jack Nicklaus has, but I don't know if there's, I can't remember if there's anybody else. So I asked one of the models, hey, how many people have won the masters twice in a row?

31:40And the answer comes back, Jack Nicklaus and Nick Faldo. So I was like, oh yeah, Nick Faldo did win. But it didn't say Tiger Woods. So I said to the model, I said to the model, hey, I don't think you're right. Didn't Tiger Woods win the masters two years in a row? Model says, wait one second. Comes back, yes, you're right. Tiger Woods did win the masters twice in a row. Why did you get that wrong? I said to the model. Model comes back, well, I use this source. I did this. I did this source. The bottom line is not a clean data set. not a clean data set. Garbage in, garbage out. Now, human judgment had to look at that and say, no, no, no, I don't think that's right.

32:14Are we going to get to a place where the data sets get better and better and better? Yes. But as long as one of the functions of the model is they go out into the internet and they go out into social media and they go out into the media and they go out into the world, there's going to be a lot of garbage in, garbage out. And the models can get better and better and better. But that's going to be, it's going to be really interesting to see over time how the models get better and better at distinguishing. And one of the things that's interesting is I then asked the model, hey, okay, will you search this differently the next time because wherever you went, got it wrong.

32:46And the model said, no, that's not the way it works. Now, one day I think it will work that way and it will search it differently. But that's just interesting to me about what we are. Here's the third thing, okay? You were talking about what's inside people's heads. I personally believe the answer to this is never. And this is one of the magic things about humanity. This is one of the magic things about creative things. And by the way, part of investment banking and client relationship is creative. It's EQ. It's emotional intelligence around spending time with people, how to connect with people, how to build trust with people.

33:22Machines can be really, really good. Tools can be really, really good. But unless you're in the camp that humanity is not going to be about trust and relationships, I think this is like a never thing. And so the bridge is how to use the tools, okay? And with the tools, leverage more of your humanity and your connectivity in a special way to be more impactful with people. Now, here's an example that I think is an easier example to kind of look at. I have a daughter who's a screenwriter. I've talked to her extensively about this because people talk when somebody writes about their voice. Okay. And one of the reasons why, if you really understand the process of writing a movie, okay, sure.

34:01Can AI write a script? Absolutely. But the first thing is that script, if my daughter's the screenwriter, it is not in her voice unless that model has access to every single thing she's ever written, every single experience she's had in her life, every single emotions he's ever felt, never going to have that. And so voice matters when you're writing, you're doing something creative. Now, here's the thing. She puts her voice on whatever she writes. Now she goes to the studio. The producer says, you know, I don't like this. I don't like that. That's a personal feeling. He's not asking the model to say whether I like it or I don't like it.

34:37He's reacting to it emotionally because it's creative. It's like relationships. I don't like this. By the way, somebody came in and pitched an investment banking deal. And the CEO said, you know, there was just something, I just didn't like the way that guy talked to me. Okay. That's a human emotion. That matters. That's not going to change. And so this concept of getting things out of people's head, what you're really talking about is human intelligence, humanity, EQ. And I think we're going to figure out how to use these models more powerfully. The data sets are going to get cleaner and cleaner.

35:09Yes, maybe we'll expand better into the second and clean up when you go out in the world. But when it comes to the way human beings interact. I actually think this is a superpower that's going to get more valuable and more valuable and more valuable. And it's something we want. I think people should think about. People should try to learn. I think public speaking still matters. I think writing is still going to matter. I think how you communicate and talk to people is going to matter. How you spend time with people, how you build. All this stuff's not going away.

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36:42I'm not as funny. I'm really not as funny. I mean, he's much funnier than I am. Well, OK. You mentioned looking up share prices earlier on the Quotron machines. And speaking of share price, your stock recently crossed$1 ,000. Goldman stock. An all-time high. An all-time high. So congratulations. Thank you very much. On that. My question is, how often do you look at the share price of Goldman Sachs? Is that like the first thing you look at when you wake up in the morning? Well, I don't. It's not the first thing I look at when I wake up in the morning because I looked at it when it closed the day before.

37:12And it generally doesn't change overnight. Look, during the week, I would say I look at the stock price most days during the week, but it depends what I'm doing. If I'm in the office, if it happens to be a day when I'm in the office going from meeting to meeting, and in between meetings, I jump on my desktop and I'm responding to emails or I'm making telephone calls, the screen's up. And I'm looking at our stock price, but I'm looking at a bunch. I'm trying to look at what's going on in the market, have an absorption as to what's going on in the market that day. If it's a day where I'm in a bunch of meetings and I'm on the road, I might not look at the stock price at all, but probably at the end of the day, I'd look and say, hey, what happened today?

37:44And by the way, it's not just our stock price. It's actually what happened in the market today. For me to be effective, I have to be super in touch with what's happening in the market every day. And I spend time on the weekend also catching up on it. You know, from my perspective about our stock price, of course, it's human nature. I'm going to look and see. But what I really care about is kind of year to year to year. And what I really believe deeply, and it's been one of the things our leadership team has really been focused on for the last eight years, is if you grow the earnings of the firm, if you invest in growth in the firm and you grow the earnings of the firm, the stock will do just fine.

38:18The multiple will move around. But if you grow the earnings of the firm, the stock will do just fine. And so we've been focused on investing in the business and growing the earnings of the firm. And we've grown the earnings of the firm material. We had our first investor day in January 2020, and we put out a plan and we've been executing against that plan. And since then, we've grown the revenues of the firm 65-ish percent. We've grown the earnings of the firm about 140 to 145%. And what do you know? The stocks reacted really well. And we've gotten a little bit of a better multiple because it's a much bigger, more diverse, durable business.

38:46The durable revenue nature of the business is better. So we're getting a better multiple on what we're doing. But I'm super excited because I now look ahead for the next five to 10 years. And I look at this technology and our ability to remake operating processes and take the most productive people and have them spend more time with clients and broaden our client footprint in areas like wealth management, et cetera. I'm like, wow, we can really grow the firm. We can really grow the firm and grow the earnings further because we're gonna have more capacity to invest in growth. And so that's super exciting.

39:17And so it's been a journey. I mean, when I started, the stock was around 200. And now the stock's over 1 ,000. By the way, it could go back, but it's not going back to 200. But the stock can back off, the multiple come down, our earnings could slow if we went into a tough economic environment. But fundamentally, the firm is bigger, broader, more diverse, more durable. And I think on a super course for more earnings growth and more performance for our shareholders over the next five years.

39:40Tracy Alloway:So the performance is objectively strong, but no offense, you can see a lot of charts right now in the market that are going straight up and to the right, as you're aware. The important thing, and I know you know this, Joe, the important thing is to look at the relative performance and the relative performance over the time we're talking about is top of the heap. Totally. And we're going to keep driving to try to deliver that. But I got a sort of a capital markets question for you that sort of maybe as a banker, you might have some thoughts on. So connecting it to the AI conversation, what was your thought when you saw, or maybe your headstone involved in it, Google making an equity raise to continue?

40:18Tracy Alloway:I like that was interesting because there's been a lot of debt financing from the big tech companies for the AI build out, which we could have done a whole episode just on that. What do you make of a company that big doing an equity raise at these levels and even doing like a private placement? When I asked you at GPT, and it could be wrong, as your example with Tiger Woods noted, when I asked about comparables, like what other big companies did these private raises? They're almost all crisis era Berkshire investments, including one in Goldman. But what did you make of that, Google doing an equity raise to finance rather than a debt raise?

40:53Well, there are a couple of things. think about here. But first of all, I know a little bit about this. There's some things I can talk about and some things I can't, but I think you know that the firm ran this whole process. The firm was the only bank that was involved in this for the last five months up until a couple of days ago when other banks were brought in to participate. The firm ran this over the last five months. This was Goldman Sachs' deal. And the team led by Yasmin Kupal and Kim Posnett and David Ludwig, you know, as our equity capital markets business, did an extraordinary job. This is one of the largest, if not the largest, secondary follow-on equity offering ever.

41:25And we're ultimately, if the green shoe is exercised, we're going to raise 85 and 90.

41:30Tracy Alloway:It was up this just morning from 80 to 84.6. We upsized it. And the green shoe, my guess is, given the way the stock's trading, will probably be exercised in the coming days. And so they raised$90 billion. And so it's really extraordinary. And by the way, I think one of the interesting things to think about, this is the first concrete, tangible data point on investor demand at this scale. And we have some other things coming up at this kind of scale. And so this is a very important tangible investor data point. And I think one of the things that's very helpful to the firm is sitting in the middle of this, we got a lot of information on how investors are thinking about all this and the others that I think is super, super interesting for us.

42:08But it's unprecedented at scale. And it's reflective of the fact that we now have some of the largest companies in the world that have capital plans over the next five years that are very, very significant. And they can fund a lot of it with debt. But I think you're going to see, and Alphabet is the first one to make this decision, I think you're going to see a bunch of them fund a bunch of it with debt, but also raise more equity because they're starting to think about, okay, what does this look like? It's one thing, what does it look like this year? But what does it look like over the next five years?

42:42How much capital do we need? How much debt? Equity markets are good. Are Our multiples are pretty high, given the way the market's responding at the moment. We've got to think about our leverage going forward. The capital's available. And so the analysis is, and this is not all public, but in specifics, but I'll talk generally, a company has to look and say, not just what's our one, two, or three-year capital plan, what do we think our capital plan is over the next five to 10 years? How's that going to change our leverage? What if there was a change in the market multiple, okay, and our leverage is up?

43:13How are we going to feel about that? and it requires kind of a long-term conviction on what you're doing from a capital deployment standpoint and making the decision as to what makes you more comfortable in kind of the leverage and balance between debt and equity. I think you're going to see more companies issue equity because capital is available and you want to be cautious about this. If you get it wrong, if you totally rely on debt and you get it wrong, you will really regret if you wind up having a downside scenario that's tougher than you expected. So I think you can see more companies think that through And Alphabet's the first company to step forward.

43:45Our team spent a lot of time over the last five months, really, helping them think through these kinds of issues. I think they were very smart to really think it all through. Well, speaking of equity raisings, you got the lead on the SpaceX IPO. So again, congrats on that. Again, our team, really, really the team on that, really, really extraordinary. Dan Dees, Kim Posnett, I mean, just really Susie Schur, really, really extraordinary partners of the firm who have just done an extraordinary job over years. I mean, over years. I imagine this was a very competitive process, right? And you were talking a lot about the importance of relationships earlier.

44:22Using SpaceX as a concrete example, what does that relationship actually look like? Is it true that you were sliding into Elon Musk's DMs to pitch yourself? What is it that you offer to a potential client that other banks can't offer? Well, I mean, there are things that I'm willing to say and try to give you some perspective on it. But the most important point that I could amplify about this is we didn't win this in the last six months. We won this over the last 20 years. Wow. The decision wasn't made. The decision wasn't made until the last six months. And there's a lot of things that the team did over the last six months that contributed to the ultimate result, which, by the way, now we have to execute.

45:08But this is a cumulative effort of lots and lots of people over 20 years. And we first, as a firm, we first met Elon Musk. And the person that first was responsible for covering him was a guy named Stuart Bernstein, who was doing a bunch of stuff around kind of green energy. And he and his brother had SolarCity. And that's where we first connected with Elon. And then we took Tesla public when Tesla went public. Sometime around SolarCity and Tesla, I first met Elon. And so I've known Elon for more than 15 years. Dan Dees, Stuart Bernstein, kind of semi-retired from the firm in the early part of the last decade.

45:45So let's say 2012, 2013. And Dan Dees, who now runs our global banking and markets business, was an investment banker who was just coming back to the US after having been in Asia for a long time. And he was basing out of the West Coast and running our TMT banking business. And he started building a personal relationship with Elon. and Dan has built a really wonderful dialogue with Elon over a long time, but it's not a straight line. And there are times where we're doing things and we're not completely in sync. But at the end of the day, as a firm, we've been long-term committed to Elon, his companies, his teams.

46:21By the way, in this situation, Brett Johnson, the CEO, is a hugely, hugely important guy. And we've had people spending time with him for years and years and years. And that's what our business is. Our business is building trusting relationships over time with people, giving the right advice, taking a long-term view, not being transactional, and trying to earn trust. So when the biggest, most important things happen in the world, we have a better chance of being asked to provide services. And that's kind of what we do. Did you send them a DM? So with respect to the DM, It is, unfortunately, it's untrue that I pitched Elon via DM about the deal.

47:03Okay. But what is true, and this is the way facts get confused, Elon, some point in the last year, stopped taking texts on his phone or emails and started telling people that he knew that if you wanted to get in touch with him, direct message him on X. And so because I have a relationship where I reach out to Elon and we exchange messages about a whole variety of different things. I stopped sending him texts on his phone and started direct messaging him when I wanted to. This is how Joe communicates. This is entirely when Tracy is a warrior when you're running late. So I actually, I went back actually and looked at the chain, you know, in my X count over the last six months just to make sure I wasn't wrong about this when I saw it in the press.

47:49And I said to Tony, I don't think this is true. And I never asked Elon in a text message about the IPO. We focused on his team. We focused on the work that we had to do. And we're really proud and pleased to be leading this. And we're going to do everything we can working with the other banks to get the best result that we can for SpaceX.

48:08Tracy Alloway:So it looks like this year is going to be a year of mega IPOs. We had the private confidential filing from Anthropic. We'll probably get a couple others, et cetera. However, the much bigger story is still generally private capital markets have gotten so liquid that some of these very successful companies, they could, in theory, maybe never go public if they didn't want to. Some people think this is bad for capitalism, that a bunch of big companies are going to come in and that unlike the Microsofts and the Apples and so forth, where the broad public really got to participate, even if you were just an index fund investor, in a lot of the upside, these companies are going to be coming at some of the biggest market cap companies in the index.

48:48Tracy Alloway:And the public investor will not have caught any of the ride from the 500th biggest and the S &P 500 to the 20th, et cetera. Does this break capitalism? Is this bad for the US or is this fine? Well, I'm going to give you a conclusion first and then we can try to dig in a little bit to the details, which I know you guys love to do, but I just start. I don't think this is going to break capitalism. And I think it's good for the US. There goes your headline. I think it's good for the US that we have the biggest, Oh, by the way, breaking hot, hot headline just moved on the terminal. Anthropic said to tap Morgan Stanley, Goldman Sachs to lead IPO.

49:22Tracy Alloway:This just came out. So there you go. OK, anyway, keep going. So I think this is good for the United States to have the biggest, most important companies in the world. When you talk about what's happening, there are a lot of complex things happening about why we have fewer public companies today than we had 25 years ago. And this is a long-term journey around policy decisions and market structure over a very long period of time. The reason that companies like Microsoft went public when they did it the size that they did was there was no capital available to them other than going into the public market.

49:56Right, right. But it's not fair to say that investors got to participate in everything because it's not like there's more access for investors today.

50:04Tracy Alloway:Well, and no one talks about the 900 companies that went to zero that went public in the same year as Microsoft or whatever. And by the way, that's another thing. Most companies don't survive. So it's just not that simple. I do think we've created a regulatory structure and a market structure that really makes it unattractive to go public until you have to. The reason these companies are going public now is because they have to. They have capital needs that are so voracious that it is not prudent for them to try to do 100 % of it in the private market and not have a public currency. It's just not prudent.

50:36And that's why I think you're going to see a bunch of these companies go public, because they actually need the capital. It's interesting. I've advised companies for years. And at one point, 25 years ago, I actually ran the equity capital markets business at Goldman Sachs. That was a job I had early in my career in Goldman Sachs. And I used to say to companies, there are a few reasons to go public. You need the capital. You need the currency. You have to create liquidity for early investors. but all the other stuff that people talk about is really not critical. And you have to recognize that if you're running a company successfully and you don't need those things, when you take it public, you will run it differently.

51:18You will run it differently. It is different running a public company than a private company. There are different pressures. There's a different life cycle of how you have to respond. You will run it differently. And so my advice has always been, wait as long as you possibly can to go public, okay, if you're giving advice to companies. And I think companies have recognized the capital has been available privately at most scale. The liquidity has been available in a variety of different ways at most scale. The currency thing is tricky, but generally speaking with these growth companies, they don't need the currency because they're growing, they're not doing M &A.

51:50And so I think you're going to see a bunch of these companies go public because they need the capital, because they've reached a scale and they have a demand for capital where they need the capital. And I think the current SEC chairman is working on a variety of things that hopefully will take some of the friction out of going public, which will help a little bit. But at the end of the day, given the way markets work and indexation and passive funds and ETFs, a$5 billion market cap company with an$800 million IPO, the discount associated with getting that going has been less attractive to investors.

52:29And part of the reason is public capitals, but private capital has been available without a discount. But that, by the way, that could be a cyclical thing. In other words, we could see periods of time where private capital will have a bigger discount and the public market will be more efficient. And then you'll see more of those companies come to the public market. But I think fundamentally, we're going to operate with fewer public companies and the companies are going to be bigger. I mean, that's the way the market structures of market.

53:20and demand and the future of private capital. Catch exclusive interviews with top newsmakers, plus a live recording of Bloomberg's Odd Lots podcast. Visit bloomberglive.com forward slash invest Hong Kong to learn more. Supporting sponsor Deutsche Bank. Okay, so speaking of capital being available, which is kind of putting it mildly, the markets right now seem kind of crazy to me. And you were at the Economic Club of New York yesterday talking about markets being in more of a greed stage than a fear stage. Based on your Wall Street experience, and again, you mentioned you started in the early 1980s, have you ever seen anything like this?

54:01Does the current time period, I don't know, have a historical analogy for you? Sure. In fact, somebody said to me recently, this is unprecedented. They were talking about 10 companies having 30-some percent of the S &P waiting on a market cap base. And I was like, no, it's not unprecedented. How about the 1920s? How about the 1960s? How about the late 1990s to 2000? I made the comment yesterday at the Economic Club because I was asked about the way the stock market's running. And if you actually look at the whole segment, I said a lot more than that. And I actually said before I said it, I said, look, I'm going to say something.

54:34I know it's going to create a lot of headlines. But I do think it should be said because I do think I'm seeing some of that behavior that I've seen before. And people are worried about missing out on this technology boom, whether it's compute, whether it's storage, whether it's chips, et cetera. And so people are crowding in. And that's a greed thing because they want to participate in their fear of missing out. What I should have said, okay, at that moment was all of that. But then I should have said, but, you know, it's kind of interesting because if you look at the S &P 500. The top 10 companies, which by the way, are mid to high 30s market cap.

55:12In those other three periods, the top 10 companies were also in the 30s. And one of the things I have pointed out to people is these top 10 companies actually have more earnings than the companies did. They generate a lot of cash. They generate a lot of cash. So that's something to observe. But what I should have said is the market multiple, the earnings multiple on the top 10 companies in the S &P, these are approximate numbers. So don't hold them to me directly. I actually looked at this this morning because I thought this would come up. And so hold it as approximate. The top 10 companies are trading on forward earnings in the low 30s.

55:44Okay. In the late 90s, 2000 internet boom, those companies were trading at more like high 40s to 50. Yeah. Okay. You think about Cisco when its market cap was over 600 billion. So these multiples, yeah, are high, but the growth's pretty good. The earnings are real. Those numbers are on the high end of the distribution, for sure, but not crazy. The other 490, okay, are trading between kind of 17 to 20, which by the way, 20 high side, when you add it all together, it's kind of 22 times forward. A lot of it's at 17. I actually think the 17 sounds pretty attractive if you think that all these companies are going to be able to use technology.

56:25Not all of them will execute successfully, but be able to use technology to improve operating processes and create more efficiency and therefore faster earnings growth and more investment in their business. You should see over the next five years improvement in the earnings growth of that other 490. I'm talking on average. So is the market running? Yes. Are people crowding into a handful of stocks because they're fearing of missing out? Yes. That's what I meant about the greed versus fear. But this could go for quite some time because it's narrow. And on a historical context, Next, it doesn't look like Polaroid at 80 times earnings in the 1960s.

57:01It doesn't look like RCA at an infinite amount of time times earnings in the 1920s. So I'm not sure is the bottom line. I'm not sure. But there's no question for a narrow group of stocks, the market's really running. And what's interesting to me is we have a lot of things going on in the macro with the war, with the oil shock, supply chains, inflation getting stickier that are going to have an effect. And, you know, the market may absorb all that differently than it's absorbing it at the moment. At the moment, it's kind of brushing it aside. Things can always get crazier, as Joe likes to say.

57:34Tracy Alloway:That's right. All right. You know, like I said, you're going to be involved in the Anthropic IPO. Congrats on that. Just between the three of us here. Just between the three of us? Just between the three of us here. I know you're part of Mythos and Project Glasswing. And there's this cynical take. It's like, oh, they just released it to a small group because they actually didn't have enough compute, whatever. Have you what have you seen? And is it really like is it keeping your cybersecurity people up at night? Have you found a bunch of bugs that you didn't know about? Tell us. Here's what I can say publicly.

58:05I think it's very important. These models are incredibly powerful. And I think it's very, very important that these companies that are producing these incredibly powerful models work collaboratively with the government and with the private sector to give people opportunities. opportunities to understand what these models can do and to try to continue to secure our critical infrastructure as effectively as we can. Do I think that the process around this was perfect? No, but we're learning as we go. And I think there are a lot of things in the process that have been good and have been helpful. It wouldn't surprise you that just using financial services, for example, is the eight largest banks are significantly ahead on cyber investment and cyber protection over the last decade than bank number 2000 that sits in the middle of the country in Arkansas.

58:55Okay. And the risk in financial services, it doesn't mean that there can't be issues for the biggest banks and the biggest banks need to constantly, constantly, constantly, constantly think about this. We invest a lot in this and we're all over this. That doesn't mean we can't have a problem. We could. But the risk is that a medium-sized bank has a problem and it creates fear in a broader group of medium-sized banks. And you don't have to look that far. If you look at SVB and how SVB had a problem and it created fear in a variety of banks, you could see a cyber attack at a mid-sized bank creating ripples through the banking system, which will be dislocating.

59:33And so I think it's really important that we figure out how to help the broader business community get more invested. And by the way, that's something that's got to happen both by the private sector investing more, but also the government finding ways to help. So, you know, I do think that the administration's executive order to get these models is important. There's got to be coordination between the government and business on this. And I think the process will continue to get better. There are going to be more models. There's going to be more process. And, you know, we've obviously had a team that's learning, looking, you know, we learn things, making adjustments, and we're going to continue to do that.

1:00:09But that's that has been a part of what we do. This might be accelerating a little bit, but it's not that different from what we've been doing for a long time. Just maybe the pace of some of the change on what these models can do is going a little bit faster. And so we've got to be more nimble. And we have the resources to do that. What I worry about is all the companies that don't have the resources to do it. And by the way, it's not just financial infrastructure. Think about energy infrastructure. The biggest utility company is going to be way ahead of the local water company in Akron, Ohio, right?

1:00:36And so everybody's vulnerable. And so we've got to figure out how to help people and bring people along. I want to pivot. I guess we're going to run out of time soon. So I want to pivot slightly to a very important question, which is your own use of AI. Joe and I know that you're into music. You like to DJ famously. Have you been experimenting with AI generated music? Yeah. I mean, I've been playing with it. And what I'd say is what I think's cool about it as someone who's produced a bunch of music, and I want to come back to that because I think there's an important kind of lesson to learn about history in terms of music production to where it is.

1:01:10I think it's super cool. But what it does is it opens up the creative channel to people that would never have an opportunity to produce music. Okay. Well, that's just a little bit of history about music production. Because by the way, 30 or 40 years ago, I could never have produced music. Now it so happens I played an instrument when I was in elementary school, in high school, I played the saxophone. I can read music. I understand music theory because I played an instrument for 12 years. When I was in, you know, out of college, you know, I would call myself a recreational drummer. I mean, I could sit on a drum set and carry a two, four beat.

1:01:43So I understand bass music theory, but I've been a rock and roll guy forever. I love Bruce Springsteen. Okay. I saw my first Bruce Springsteen show in 1978, the Darkness on the Edge of Town tour. When he wrote that album, and by the way, the albums that came before had a bunch of them that came after. He sat in a studio or he sat at a piano or he sat with a guitar. He wrote notes down on paper. He wrote lyrics down on paper. He played around with it. Then he invited human beings into the studio with him that played piano, organ, drums, guitar, horns, saxophone, all different things. And they sat there and they made the music.

1:02:24And somebody recorded it and it got pressed onto a vinyl album. Okay. A lot of the music that we listen to today has been made on a computer on platforms called Logic Pro or Ableton, which is actually how I work to produce the music that I produced. And so if you want horns, you can choose from 150 different horns. Okay. You don't need 15 different musicians. Okay. Nobody's talked about the difference, how technology evolved. And by the way, what it did is because Logic Pro and Ableton exist, and I'm relatively dysfunctional on the platforms, you know, I can muddle my way around, but I need an expert to help me because they can do in three seconds what takes me 10 minutes.

1:03:03But what it allowed is for somebody to say to me, hey, I want this kind of a sound. Okay, I didn't now have to write the musical notes down. Okay, you could basically take out a piano and say this chord sound, this chord progression, try it on the computer. You could say, I want this to be done in horns instead of in a piano, click, it's now horns. And you can basically put a top line together that's very interesting with a computer. A lot of the music that's produced today that we listen to is produced that way. Okay. Now what you've got is you've got an application that's basically doing that.

1:03:41Okay. And I think there are a couple of big issues that need to be wrestled through with this. The first is these AI apps are using other people's content in some way. Right. And the artists aren't getting in any way compensated for that. And I think you've got to think about how you're going to bring the artist community and their IP into the discussion of this over time. And, you know, it's not gotten a lot of attention, but I think it's a very, very important, a very, very important thing that has to be dealt with. And secondly, this goes back to the whole discussion I had about voice when I was talking about my daughter and screenwriting.

1:04:16OK, the stuff I produced. OK, it's my voice. I said, I like I like the way this sounds to me. So do it this way. I like the way this feels, so let's try it this way. Okay, and then you put it out there and you see whether or not anybody likes it. Obviously, the technology allows you to do it faster, but without a human being, really then massaging it and tempering it, okay, I think you're going to get, at the moment, certainly mediocrity, as opposed to really, really interesting, resonant stuff. All right, David Solomon, clearly you've given the music industry quite a lot of thought. Thank you so much for coming on OpLots.

1:04:56Really appreciate it. Well, thank you for having me, guys. And I appreciate the conversation. Yeah, it was fantastic. I appreciate you guys. Thank you so much. Appreciate it. Thanks.

1:05:03Tracy Alloway:Absolutely. We'll do it again. We will.

1:05:17Joe, that was a lot of fun.

1:05:18Tracy Alloway:That was a lot of fun. A lot of fun. I'm kind of surprised how much thought David puts into the music industry, to be honest. No, I loved that you asked that last question, and I liked how thoroughly he answered it. I wasn't sure if that would be the type of thing where he's like, well, you gotta focus on the banking. You know the thing that really – and there's a number of themes within the conversation that are very important to think about. But, I mean, he's really good with dates and names. And as someone who is not good with names specifically and I'm okay with dates, I asked him that question.

1:05:50Tracy Alloway:is like, well, what do you have that like, okay, there are other bankers and you're like a producer. You get some of those. You get that sense, right? Someone who's like that good at like crediting the right people, knows the name, knows the days, knows what they contributed. I kind of wish I had that skill a bit more. Yeah. You can always tell a good All Thoughts guest by like how many specific dates and data points they actually bring up. Wait, I know a good data point, by the way. Just the one. There's one data point. So in the music question, and he mentioned having gone to see Bruce Springsteen's Darkness on the Edge of Town tour.

1:06:23Tracy Alloway:That album came out really close to the bottom in the 1970s. And, but this is why it's interesting because plenty of albums came out. Bruce Springsteen re-released Darkness on the Edge of Town in 2010. So twice that album has been associated with sort of like generational historic lows. Oh, that's funny. Okay. So we'll know the crash is coming when Bruce Springsteen re-releases this for the third time. Well, no, the next time, so there's going to be, at some point there'll be another crash when he re-releases it, that is a buy signal. That's the bottom. That's the buy signal. All right. All right.

1:06:54Important data point here. But no, thinking about the AI job situation, this is a theme that keeps coming up, which is if knowledge is commodified, if knowledge and experience gets commodified on a single platform, then the human interaction, social maxing, looks maxing, whatever you want to call it, seems to be getting more important.

1:07:14Tracy Alloway:I would actually even say there's another thing. It's absolutely true. And I would say there's probably something else, which is that, okay, like everyone gets this sort of like commodified AI answer. So, okay, then you can infer that the human touch will be more important. But then you add in the fact that the last 15 years of mobile phones has destroyed so many people's like ability to like make eye contact, that it probably even more in a premium, even setting aside AI, because the skills are probably just going to get rarer as so many people lose their minds to the phone and the internet. All right.

1:07:44So everyone remember to look into each other's eyes when you're speaking with someone and I guess pick up the phone. Yeah. For David's advice.

1:07:51Tracy Alloway:I also just thought it was really interesting that he thinks we're going to see more public companies doing private equity offerings. Because I did that alphabet headline, the Google headline, that was a big deal. And I think caught a lot of people by surprise. So the fact that it's like this is the first of multiple he expects is a very interesting trend to watch. For sure. All right. Shall we leave it there? Yeah, let's leave it there. This has been another episode of the Odd Thoughts podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway. And I'm Joe Weisenthal. You can follow me at The Stalwart.

1:08:21Tracy Alloway:Follow our producers, Carmen Rodriguez at Carmen Armand, Dashiell Bennett at Dashbot, Kale Brooks at Kale Brooks, and Kevin Lozano at Kevin Lloyd Lozano. And for more Odd Thoughts content, go to Bloomberg.com slash Odd Thoughts where we have a daily newsletter and all of our episodes. And you can chat about all these topics 24-7 in our Discord, discord.gg slash Odd Thoughts. And if you enjoy Odd Lots, if you like it when we talk to the CEOs of big banks, then please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes absolutely ad free.

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1:09:15Thank you.

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