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

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1:05 Bloomberg Audio Studios, Podcasts, Radio News.

1:20 Hello and welcome to another episode of the All Thoughts Podcast. I'm Tracy Alloway and I'm Jill.

1:25 Why isn't thal so Joe?

1:26 When we talk about AI and its impact on jobs and businesses, one of the things we like to do, or one of the prisms through which we like to explore AI is through banks. As So you think about banks, They've got big tech budgets, they're talking to AI companies all the time, they're their clients essentially, so they're deploying a lot of this technology. And then they have this whole array of jobs. Right you have the classic sort of process workers in the back office, You've got the junior analysts who are churning out powerpoints, but you also have bankers in ib who are doing more I guess, relationship driven business. So you have this really good cross section of the sort of white collar jobs that people

2:10 think about when we think about AI disruption.

2:13 Do you remember in the twenty tens when every bank CEO is like, you know, we actually like to think of ourselves as a tech company.

2:19 I remember that was a fun bring in the ping pong tables for the engineers.

2:23 That's right, right, there was a fun little ero. But no, you're absolutely right, And of course you know AI is largely expected, at least until we have much more advanced robotics, expect to affect white collar labor. First, you mentioned the whole range, but there are aspects of when I think about being a banker work in a bank that, to your point, really do feel like relationships and like there's the cliche it's like go out and golf, but I think they do actually golf a lot.

2:48 They think that is part of the business.

2:49 All right, well we'll find out. We have spoken to Marco Argentie at Goldman Sachs before, he's the CTO, about how the bank is actually deploying technology. But today we haven't even more more perfect the perfect, if that's possible. We're going to be speaking, of course, to David Solomon. He's the CEO and chairman of Goldman Sachs, and he just penned an op ed in the New York Times with the headline, I'm the CEO of Goldman Sachs. The AI job apocalypse is overblown. So truly the perfect guest to talk about all of this. David, thanks for coming on all.

3:21 Thoughts, Thank you for having me. I'm glad to be with you guys.

3:23 Congrats on the op ed. You're in the media industry.

3:25 Now, Well, I'm trying not to be in the media industry. But I'm glad I wrote the op ed. By the way, not my title the New York Times story, but I'm I'm glad I wrote.

3:35 The app Why did you write it?

3:36 Well, I wrote the op ed. I haven't written a lot of op eds, I think in my eight years, I've written two. And the last one was back in twenty nineteen, before COVID, and it was around It was around energy where I was trying to talk about the fact that I thought there was going to be real change in the context of the energy supply chain and it was very important that we made investments and things that were greener, and we moved in that direction. But I also stated at the time, and took a little heat for this, very fatally, that oil and gas was going to be a significant part of the energy supply chain for decades to common gold and sacks would be financing fossil fuel companies for a long long time, and

4:09 you know, and looking at the lens now, I think that that it is very important that we have a thoughtful and detailed discussion about the change that's going on, and let's just start, if you don't mind, if I can step back. I am hugely, hugely optimistic about this technology and the impact that this technology can have on large scale enterprises like Goldman Sachs, and the productivity gains that it can create, which I do believe can increase economic growth, create more prosperity, and more impact on our economic system broadly in a very very positive way. I am hugely optimistic, and I think about things in five to ten year time bites like what should we expect to see over the next ten years. That's the way

4:53 I think about things when I make a statement like that. At the same point, I'm extraordinarily cognizant about the fact that it's not going to be a straight line. There's going to be disruption, there are going to be jobs displaced, as there have been with any other technology acceleration over the course of history. And we as an important company and governments also do too play a role in thinking about what's the best way to make this go as well as possible, but with the ultimate goal of having the technology make our society more productive and therefore allow for more economic growth and more participation by everyone. And I was listening to a variety of things that were being said and they didn't really make sense to me,

5:31 and I thought it was important for Golden Sachs to get into the discussion. And so there are things that are always different, but I generally, you know, if you want to talk about kind of fundamental principles that I have after forty some years of doing this, it's never different this time. Meaning I don't think we're going to wake up in a world where nobody works and there has to be universal basic income and we have massive unemployment.

5:55 I just don't think that's the way our economy works. And when people start talking about those things, are postulating about those things, I don't think they're being thoughtful about really looking in a granular way at the labor force and how job creation works in our economy and how technology disruption in the past has changed and shifted the nature or the makeup of labor and the economy in the US.

6:14 So I think to even begin the discussion of like, well AI cause a white collar wipeout, or as you did say in the up ed like some some areas will really change and head comunts will change. But to begin this conversation you have to know, like, well, what is a job? What does someone actually do at their job?

6:33 And so I don't know, maybe this is a chance I'll let you, like butter you up, let you brag about yourself for a little bit. I saw a quote I was doing some prep and you're talking about earlier in your career and going from bear Stearns to Golden you say, and you said, I was a big producer at bear Stearns. I built a lot of relationships there and brought a lot of relationships to the firm.

6:51 What made you good at your job?

6:53 What was like there were a lot of people there bear at the time you eventually became the see of Goldman Sachs. What was it that, like the skill that you've had or that successful people in that role had that made them do their jobs?

7:07 Well, Well, finance has evolved, you know, I started in nineteen eighty four. I recently referred to that as the prehistoric days of finance, when, by the way, I have long flowing hair. You know, it's just a very different world. And so let's just start with the fact that finance was a relatively nascent industry and also had been relatively stagnant for fifteen years, because we really went through a period from the late sixties to the early nineteen eighties where interest rates were going straight up. Yeah, September fifteenth, nineteen eighty two is a very very important day in the history of financial markets because that is the day that the ten year treasury at fifteen point nine percent.

7:50 And it also happens to be it also happens to be a little less than two years before. You know, I landed at the Irving Trust Company at one Wall Street to start my career, and you know, at the time you got trained to do analysis, but the business was very entrepreneurial. There was very little structure and there was so much open running room to go out and participate that young people, especially when you got away from the most white shoe firms, which at the time were Goldman, Sachs and Morgan Stanley, were really encouraged to go make their way. And so I was working at Irving Trust and this was a time when almost everybody in finance went to business school. I was applying a business school in nineteen eighty five and I got a job offer

8:40 to work in the jump bond business at Drexelburnalm, and I decided to take it because it appeared lucrative and my dad jump.

8:48 Bonds were like the only thing taking off basically in finance in the early eighties. They were.

8:53 It was definitely an area of finance that was accelerating, and it was very entrepreneurial. And I said to my dad, this is taking a risk because everybody else is going to business school. And my dad said, go try it for two years. If it doesn't work, you go business school in two years. I mean, it was really it was a pretty good It was a pretty simple piece of advice. But I went to Dressel Burnham. It was very entrepreneurial and the culture there were good things and bad things about the culture at Trexel, and some of the bad things of the reason why in nineteen ninety.

9:19 On February fourteenth, nineteen ninety, Drexel Burnam went out of business, as many other Wall Street firms have in the history of Wall Street. But for the four and a half years that I was there. Basically, I was told, go find a way to build relationships and make money. Go find a way to build you know, I was twenty four years old, Go bring business into the firm. We sat at a desk. I golfed a little bit, but we sat on a desk and we called people and talked to people. And it was a time when it was a time in the world when if you picked up the phone and called someone, you would get them on the phone and you would talk to them. Man, if you were an effective salesperson, you could do a lot of business.

9:55 So to some extent, you were like good at sales, you were good at making that call.

9:59 One of the great exp said, I have this an experience I've talked about a little bit, but I haven't talked about a lot. But a seminal experience in my personal development was the summer after my freshman year in college, I got an internship in a Merrill Lynch office that happened to be the office that was I think it was like tenpen Ploza. It was by Madison Square Garden, and I got the internship because I was my high school girlfriend's father ran that Merrill Lynch office.

10:26 That always helped.

10:27 And he said, why don't you come and do an internship for the summer. And I said what would you do and he said, you'd call on clients. I really had no idea what he was talking about. So I show up at this MARYL. Lynch office and they PLoP me down and they give me a zip code list, okay basically, and it was the zip code was one two eight and one oh one two eight, basically the Upper East side of Manhattan. This is nineteen eighty one. Okay.

10:55 They give me a zip code list, and they say, make a hundred phone calls a day and ask people if they're interested in talking to a Meryl Lynch broker. And during the course of the summer, okay, for eight weeks, I made a hundred phone calls a day. I got five people to talk to a Meryl Lynch broker and we went and had one meeting and opened one account.

11:15 Oh my god, okay.

11:17 It was brutal, brutal. And after the first week I said to my dad, I was like, I don't know that I can do this for the whall summer, and he said, yes you can. You took it on. You got to finish it, and I started thinking about and this is a seminal thing that I'm trying to point to. I started to think about, how am I going to make this more fun? Because it is very difficult to cold call. Now, this was a time when people would answer the telephone. But and I just started making it a game. And but what did it teach me? It taught me to pick up the phone and talk to anybody.

11:49 And when I got to Drexel Burnham, and here there were real financial incentives for picking up the phone and talking to people. I mean, they're they weren't paying me anything, and they just wanted me to do this, said, I was doing it to learn. You put financialists out of the place. I found I could call anybody. I could get people on the phone, I could keep people on the phone, I could go see people. I could relate to people, even though I was very young, and I could bring business into the firm. And very quickly I became good at that. And when I arrived, you know, at bear Stearns after Drexel Burnham went out of business, I very quickly became a very significant producer and a culture that was kind of eat what you kill, and

12:26 it was a great experience. I don't think that's the way. I don't think it was the perfect culture, and you know, culture has evolved, but I do think there's something here and one of the things we're talking about a lot of Goldman I think it's really important. I still think human to human contact matters a lot, and I think one of the great opportunities we have with this technology expansion is to get our young people out with clients, talking to clients, broadening our client footprint. They're incredibly capable.

12:50 They're incredibly capable. This shifted over the last thirty forty years, and it really I don't think it shifted for the better, and now we're going to shift it back, and I think it's a real opportunity.

12:59 Wait, say more about this, because in your off ed you talk about the Stanford data showing like a sixteen percent decline in entry level hiring. So this is something that's happening right now, and presumably a lot of the work that younger analysts at Goldman Sachs do right now could be commoditized through AI. Right if I'm building a PowerPoint presentation, I no longer need like ten analysts to stay up all night to do that, I can just generate it through a platform. So how do you see the role of junior analysts, and then how do you, I guess, train the next generation of banking talent.

13:34 I think that's a really really good question, and I want to get to that, But I just want to comment on one of the things that you said that I think is a really interesting thing for us to think about, because I did quote that statistic, but I think it's important for us to think about and see that statistic for what it is. Okay, because when I graduated from college, it was very, very hard to get a job, but not everybody wanted to get a job, Okay, in the white collar professions that are defined by the sixteen percent. But I'd also argue even today, if you graduate from a liberal arts college and you want to go be a school teacher, Okay, that's not counted in the sixteen percent. Okay, there's not a decline. What they've

14:16 done is they've taken a handful of industries that they're looking at that fit this kind of social narrative of what the right kind of job is when you're coming out of college. Okay, which, by the way, I think is a very faulty lens to look through, and that group is declining by sixteen percent. Okay, but if you want what if you want to go buy what if you graduate from college and you say, you know what, I really think I can do something really cool and entrepreneurial by making the world's best sub sandwich. I'm going to go open a store and start a sub business and try to grow a sub business. And over the next however many decades, you grow a huge sub business.

14:51 Now used to be in the sandwich business.

14:52 Are you in the sandwich business after college?

14:56 That's a nice way of saying I had a job at a deli.

14:59 There are so many there are so many different things you can do. I've got great friends I went to college with. I have one friend that I went to college with that basically graduated from college. He had studied science, you know, physical sciences, and he decided he wanted to be an electrician, and he had his own electrical business in upstate New York, where I went to college. But then ultimately he got pulled into other kinds of businesses where the skills he had developed over ten or twenty years building his electrician business could be put into other things, and his career evolved, And so there's a narrative about jobs and entry level jobs and what I mean, I don't even know what it all means. What I know

15:36 is you want to be a learner through life. You go to school to get educated and to broaden yourself and to meet people. Not everybody should go to a traditional school. There should be lots of different paths. But the goal is to start on the journey of figuring out what you're passionate about, what you enjoy, how you're going to make money, how you're gonna support yourself, how you're going to support hopefully the family that you have.

15:58 And there are lots of different paths. There are lots and lots of from paths.

16:00 Okay, but assume that we're talking about someone who wants to get into gold Midge.

16:06 Yeah, And I don't mean, I don't mean to pontificate that it's a really important, you know thing, because this goes to the op ed and kind of the labor force. There's a lot of the labor force that has nothing to do with what we're talking about. I think that's something that we've got to keep coming back to in the discussion so you know, coming to Goldman at this point in time, we hire we just right now, Okay, we just have twenty five hundred it might be twenty four hundred interns starting. Wow, and in July we have approximately the same number of permanent new hires that are starting.

16:41 The first thing is there a bunch of them that are in quote, client facing jobs and roles. There are a bunch of them that are in operational roles. There are a bunch of them that are in technology and engineering roles. There's a wide wide range of jobs. I mean there's yeah, there are a couple of them that are working in marketing and advertising. I mean there's a wide wide range of jobs. All the experiences are different, all the opportunity sets are different. When I was talking to you about out with clients, I was talking about the people that are in the client facing roles. And one of the things I truly believe and look, I see this. I sat with a group of venture backed founders at dinner in my apartment the other night. The

17:19 average age was like twenty eight. So impressive, so smart. By the way, the people were hiring at Goldman, sacks are so impressive, so smart. They're peers. With these people that are going and starting businesses, they can't go out and talk to clients and have an impact, and so with the technology it makes it more leveraging. I mean, I think you guys saw it because I've used this example of when I started doing a common stock comparison.

17:43 Took six hours. Ye go microfiche, Wall Street Journal, the only source of historical stock prices. Put it on graph paper, take a picture of it. If you really think about that example. What that example is actually saying is if you were a company and you wanted to know where your stock was trading during the day, you had two choices.

18:02 You could call three choices. I guess technically you could call your investment banker and say, hey, where's my stock trading right now? And the fact that we had a quotron in our office, okay, we could tell them. They could they didn't know they didn't have a quotron. Or you could call your stockbroker if you had one, or go outside your office and find a Merrow Inch or an E. F. Hutton or a Dean Winner office on the street and look at the ticker tape and wait until your stock would buy on the ticker tape, okay, or you could wait until the next day and open up the Wall Street Journal and see where your stock traded that day. So we were offering a huge value service by simply having this technological machine that allowed us

18:39 to tell them where their stock was trading. So, if you think about what young people were doing when I started, a lot of what we were doing was taking very primitive technology and giving information to people that were trying to run their businesses, and the pace of everything was very, very slow. We've now, over forty some years, accelerated that enormously, and so the productivity level of all these people's going up, up and up up. We haven't had fewer people. Now maybe this technology is accelerating in our way. We're over time we will actually fundamentally have fewer people. But what I would argue is the real challenge for us is we've got to find ways to apprentice them and teach them a variety of things that they're not going to

19:17 intuitively learn because they don't actually have to work as hard to get the answer. When I had to go to the microfiche and look at the different stocks and see how they were training actually put it on graph paper and absorb the differences and do the math to explain what the percentage compounding differences were. I was learning something that now if you ask for it, you get it instantaneously. You know, has your brain really absorbed what's actually happening? And so the challenge is how do we apprentice and give people the base of knowledge, but how do we also allow these tools to allow them to get out into the world so that they can really have a bigger impact faster. And we don't have the

19:55 answers to this yet, but we're really thinking about it.

20:13 Two sort of short job related questions. First one, you can 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 Definitely.

20:27 Okay, that's by the way.

20:29 I don't think that's going to change. I just you can 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. You know, use it a telephone call to someone is ten times more valuable than a text or an email.

20:48 My daughter says that's an unverified statistic, but I know that's true, and it is if I if I call you personally on the phone, it's gonna have a completely different impact, not if I sent you a text but.

20:58 I don't know your number.

20:58 I would also have to tell David, just as.

21:02 The follow up.

21:02 And this is more of a sort of specific one.

21:04 That's not going away. I mean, I really believe Joe, that's not going to go away.

21:08 Of that mix of new hires, the range of jobs, including engineering jobs including could you identify is there a change different between today and twenty twenty six versus say the pre chat GPT era twenty twenty one. Well in terms of like have you seen the difference yet, just in terms of like the allocations of anything with any hiring.

21:28 Decisions, subtle changes. But you can't look at it in a vacuum. So you said to me, I can be very detailed with yeah. I think, you know, I think with all the stuff it's nuanced. Details matter. If you look over the last ten 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. Okay, there are a variety of things that happened because of the pandemic that bloated or inflated higher across all large enterprises. And so if you if you say, since check GPT, like if you take twenty twenty two, is that was like the high water mark of the bloat.

22:11 This is the problem high water markets.

22:14 The high watermarketlotoris.

22:15 Yeah, historians will be vexed by the confounding variables of twenty twenty two, very long.

22:20 Absolutely, So if you asked me a question, I'm like, okay, twenty twenty two, yes, But that's the wrong starting point because if you look at twenty twenty two, a bunch of what we've done from twenty twenty two to twenty twenty five and now in twenty twenty six was correcting the stupid things that we did in twenty twenty and twenty twenty one. And so I think you've got to look at it through a ten year lens. And what I would say is at this point, if you look at a ten 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 reduced the number of people

23:01 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 you know, I just told you we were running it at twenty five hundred, which by the way, looks similar to what we were running at pre COVID, but lower than the three thousand plus we were running in twenty twenty one. 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.

23:39 I mean, aside from potential headcount reductions and like cost savings, how do you actually measure productivity gains at Goldman?

23:47 Yeah, that's 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. So what we're doing under what I know you guys have read about one GS three point zero. So if we redo our client or boarding anti money laundering KYC processes, and we had a process that had thirty eight hundred people touching it, not one hundred percent of their job touching it, and now we'll have a process with a few hundred people touching it. That's a productivit 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

24:29 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 and investment banking, and the number of investment bankers we have, and the amount of capital we allocate to that business over the last ten years, and you know what, are 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 helping and creating leverage.

25:01 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 and the context of onegs one point zero and two point zero 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 because our you know, you go back when the firm went public, the firm had six billion dollars a capital, I believe, and we had sixteen thousand people something like that order of magnitude. Today we have forty five thousand people, one hundred and ten million dollars of capital.

25:34 The firm is much more productive against producing reasonable returns on that capital than it was twenty seven years ago. I mean, that's clear, but that's a twenty seven year look, not a year to year to year look.

25:45 Here's a question.

25:46 AI works when there's a lot of data pulling together a lot of unstructured data. When I think of a firm like a Goldman Sex 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, and we 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 peopil's heads.

26:27 How do you.

26:27 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.

26:45 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 describe me, I believe than any other, say the other one. I think that we really have for a long time. It's been part of the culture but we really have have a culture of sharing and collaboration. It 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

27:26 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. It wouldn't surprise you Golden Sacks as an extraordinarily amazing data set that we're working very hard on to make as clean impossible. On everything we've ever done from a trading and investment banking perspective over the last forty plus years. We happened to build a system forty years ago called sec dB 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,

28:04 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 kokammi answers. Let 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 McElroy was up by six strokes after two days, and I was like, holy cow, he's probably gonna 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 Nicholas has, but I don't know if there's I can't remember if there's

28:45 anybody else. So I asked one of the models, Hey, how many people have won the Masters twice in a row. And the answer comes back Jack Nicholas and Nick Faldo. So I was like, oh, yeah, Nick Felder didn't. But it didn't say Tiger Woods. So I said to the model. I said the model, hey, I don't think you're right.

29:02 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.

29:26 Are 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 gonna be a lot of garbage in, garbage out, and the models can get better and better and better. But that's gonna be it's gonna 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? And the model said no, no, it's way it works. Now.

30:00 One day. I think it will work that way and a differently, but that's just interesting to me what we are. Here's the third thing. Okay, you were talking about what's inside people's heads. Yeah, I personally believe the answer to this is never. And this is one of the magic, 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. Okay, machines 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

30:42 think this is like a never thing. And so the bridge is, how do you 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 can AI write a script, absolutely, but the first thing is that script.

31:18 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 gonna have that, And so voice matters when you're writing or 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. He's reacting to it emotionally because it's creative.

31:51 It's like relationships. I don't like this. By the way, somebody came in and pitched an investment banking deal and the cis said, you know, there was just something I just didn't like the way that guy talk 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.

32:15 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. Yes, 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 as going to matter, how you spend time with people, how you move.

32:44 All this stuff's not going away.

33:01 All right, So Goldman Sachs Banker should be social maxing. I guess, yeah, that's right, social skill max Well.

33:07 By the way, the most successful people at Goldman Sacks have extraordinary interpersonal skills.

33:13 I believe it. We interviewed Lloyd blank Fine a couple months ago, and Lloyd like, super fun yeah, really funny.

33:22 Yeah, I'm not as funny. I'm really not as funny. I mean he's much funnier than that.

33:26 Well, okay, you mentioned looking up share prices earlier on the quotron machines, and speaking of share price, your stock recently crossed a thousand dollars gold stone 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 Sacks. Is that like the first thing you've look at when you wake up in the morning.

33:48 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 I closed the day before, and it doesn't It generally doesn't change overnight. Look I 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, you know, 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 out of the market.

34:17 Have an absorbtion 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. And by the way, it's not just our stock price, it's actually what happened in the market today.

34:30 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.

34:59 The multiple we'll 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 put it. We had our first investor day in January twenty twenty, 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 sixty five percent. We've grown the earnings of the firm about one hundred and forty one hundred and forty five percent, And what do you know, the stock's reacted really well, and we've gotten a little bit of a better multiple because it's a much bigger, more diverse, durable business. The durable revenature of the business is better,

35:29 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 ten 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 footprinting 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. And so it's been a journey. I mean when I started, the stock was around two hundred, and you know, now the stock's over one thousand. By the way, it could

36:03 go back, but it's not going back to two hundred. But you know, 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.

36:21 So the performance is objectively strong, but you know, no offense. You can see a lot of charts right now in the market that are going straight up into the right.

36:28 So important the important thing, and I know you know this show. The important thing is to look at the relative 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.

36:42 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 maybe your head someone involved in it, Google making an equity raise to continue I that was interesting because there's been a lot of debt financing for 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 chat GPT, it could be wrong? Is your example with tier Woods? Noted when I asked about comparables, like what other big companies did these private raises? They

37:24 are almost all crisis era of Berkshire investments, including one Goldman. But what did you make of that Google doing an equity raise to finance rather than the debt raise.

37:35 Well, there are you know, a couple of things you think about here. But first of all, I know a little bit about this. Yeah, there's some things I could talk about in some things I can't. But I think you know that the firm ran this whole process, and the firm was the only bank that was involved in this for the last five months up into a couple of days ago when other banks were brought in to participate that the firm ran this over the last five months.

37:54 This was Goldman Sachs's deal on the team led by Yasmin Kupal and Kim Posnitt and David Ludwig. You know, it's the equity capital markets business did an extraordinary job. This is one of the largest, if not the largest secondary following equity offering ever and we're ultimately if the Green Shoes exercise, we're going to raise eighty five and ninety up.

38:11 There's just morning from eighty to eighty four point six.

38:14 We upsized it and the Green Shoe, my guess is given the way the stocks trading, will probably be exercised in the coming days until they raised ninety billion dollars. 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. I mean, have some other things coming up at this kind of scale that 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. But it's unprecedented scale, and it's

38:53 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.

39:20 It's one thing, what does it look like this year, but what does it look like over the next five years? How much capital do we need? How much debt? Equity markets are good, 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 is 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 ten years.

39:48 How's that going to change our leverage? What if there was a change in the market multiple okay, and our leverage is up. How are we going to feel about that? And it requires kind of a long term conviction 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, you know, think that through. And Alphabet's the

40:25 first company to step forward. Our team spent a lot of time over the last five months really helping them think through these kinds of issues were I think they were very smart to really think it all through.

40:35 Well, speaking of equity raisings, you got the lead on the SpaceX IPO, so again, congrats on that.

40:41 I amagine our team really really the team on that really extraordinary Dan Dee's can posnate? I mean, just really, Susie Share, really really extraordinary partners of the firm have just done an extraordinary job over over years, I mean over years.

40:56 I imagine this was a very competitive process, right, And you were talking a lot about the importance of relationships earlier, using SpaceX as a concrete example, like what does that relationship actually look like? Is it true that you were sliding into Elon Musk's DMS to pitch yourself, like what is it that you offer to a potential client that other banks can't offer?

41:19 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 twenty 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. But this is a cumulative effort of lots and lots of people over twenty years, and we first as a firm, we first met Elon Musk and the person that first was responsible for covering and was a get names st Bernstein, who was doing a bunch of

42:01 stuff around kind of green energy, and he was had he and his brother had Solar City, and that's that's where we first connected with Elon, and then we took Tesla public. When Tesla went public, sometime around Solar City and Tesla, I first met Elon, and so I've known Elon for more than fifteen years. Dan Dees Stuart Bernstein kind of semi retired from the firm in the early part of the last decade, so let's say twenty twelve twenty thirteen. And Dan Dees, who now runs our global banking 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

42:44 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 his companies, his teams. By the way, in this situation, brit 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

43:31 chance of being asked to provide services. And that's kind of what we do.

43:36 Did you send him a DM?

43:37 So, with respect to the DM, it is unfortunately it's untrue that I pitched Elon via DM about the deal. 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 text on his phone and started direct messaging him when I wanted to, when I wanted.

44:17 To communicate this, I want to start to communicating.

44:22 So I actually I went back, actually and looked at the chain, you know, on my ex count over the last six months, just to make sure I wasn't wrong about this when I saw it in the press, and I said to Tony, I don't think this is true. And I never I never I never asked Elon in a text message about about the I PO. 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.

44:50 So it looks like this year is going to be a year of mega I pos. We had the private confidential filing Fromanthropic, 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 Microsoft's 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

45:28 cap companies in the index, and the public investor will not have caught any of the ride from the five hundredth biggest and the S and P five hundred to the twentieth, et cetera. Does this break capitalism?

45:37 Is this bad for the US?

45:39 Or is this fine?

45:40 Well, I'm going to give you a conclusion first. Okay, 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 and I think it's good for.

45:51 The red headline.

45:52 There it goes your headline.

45:53 I think it's good. I think it's good for the US that we have the biggest.

45:56 Oh, by the way, breaking hot hot headline just moved on the term anthropic said to tap Morgan Stanley Goldman Sex.

46:03 To lead EPIOT.

46:04 This just came out Okay, so there you go. Okay, anyway, keep going.

46:07 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 had fewer public companies today than we had twenty five years ago. Yeah, and this is a long term journey around policy decisions and market structure over a very long period of time.

46:29 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. Right. But it's not fair to say that investors got to participate, you know, and everything, because it's not like there's more access for no one's talking.

46:46 About the nine hundred companies that went to zero that went public of the same year as Microsoft's.

46:50 I mean, that's so. And by the way, that's another thing. Most companies don't survive. So it's 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 one hundred percent of it in the private market and not have a public currency.

47:16 It's just not prudent. And 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 twenty five years ago, I actually ran the equity capital markets business of Golden SAX. That was the job I had earlier in my career in Golden Sex, 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,

47:59 you will run it a different You will run it differently. It is different running a public company and they're 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.

48:19 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 and A, and so I think you're going to see a bunch of these companies go public because they need the capital, because they've reached the scale and they have they have a demand for capital where they need they need the capital.

48:42 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, you know, a five billion dollar market cap company company with an eight hundred million dollar IPO is just it's the discount associated with getting that going has been less attractive to you know, to investors. And part of the reason is is be 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

49:21 a bigger discount in 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 just that's the way the market structures are.

49:48 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 nineteen eighties, have you ever seen anything like this? Does the current time period, I don't know, have a historical analogy for you.

50:16 Sure there are. They're In fact, somebody said to me recently, this is unprecedented. They were talking about ten companies having thirty some percent of thirty some percent of the SMP Yeah, you know, waiting on a market cap base. And I was like, no, it's not a precedent. How about the nineteen twenties, how about the nineteen sixties, how about the late nineteen nineties to two thousand. 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, and I know it's going to create a lot of headlines, but

50:47 I do 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 is a that's a greed thing because they want to participate in their fear of missing out.

51:10 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 and P five hundred, the top ten companies, which by the way, are mid to high thirties market cap and those other three periods, the top ten companies were also in the thirties. And one of the things I have pointed out to people is these top ten companies actually have more earnings, right than the companies did.

51:33 They generate a lot of cash.

51:35 They generate a lot of cash, So that's that's something to observe. But what I should have said is the market multiple, the earnings multiple, and the top ten companies in the SMP. 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 ten companies are trading on forward earnings in the low thirties, okay. In the nineteen ninety late nineties two thousand Internet boom, those companies were trading at more like high forties to fifty. Yeah, okay, you think about Cisco when its market camp was over six hundred billion. So these multiples, yeah, are high, but the growth's pretty good. The earnings are real. Those numbers

52:13 are on the high end of the distribution for sure, but not crazy. The other four ninety, okay, are trading between kind of seventeen to twenty, which, by the way, twenty high side. When you add it all together, it's kind of twenty two times forward. A lot of it's at seventeen. I actually think the seventeen sounds pretty attractive if you think that all these companies are going to be able to use technology. Not all of them will again 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 four ninety I'm talking on average. So

52:54 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 met about the greed versus versus fear. But this could go for quite some time because it's narrow, and on an historical context, it doesn't look like Polaroid at eighty times earnings in the nineteen sixties. It doesn't look like RCA in an infinite amount of time times earnings in the nineteen twenties. So it's I'm not sure.

53:18 As the bottom line, I'm not sure, but there's no question for a narrow group of stocks. The market's really running and we've got a lot of 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 out aside.

53:42 Things can always get crazier. As Joe likes to.

53:44 Say, that's right, all right. You know, like I said, you're going to be involved in the anthropic ipio. Congrats on that. Just between the three of us here, just between the fis between the three of us here, I know you're part of Mythos and Project glass Wing. And there's this cynical take it like, oh they didn't they just released it to a small group because they actually didn't.

54:03 Have enough compute. Whatever have you? What have you seen?

54:06 And is it really like is it keeping your cybersecurity people up at night? Have you fouled a bunch of bugs that you didn't know about?

54:14 Tell us? But here's what I can say publicly, I 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 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 the purpose 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.

54:51 It wouldn't surprise you that just using financial services, for example, is the eight largest banks are significantly ahead on cyber investment in cyber protection over the last decade. Then bank number two thousand that sits in the middle of the country in Arkansas, Okay. 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 well 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

55:33 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. And 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.

56:05 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, when we learn things, making adjustments, and we're going to continue to do that. But 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.

56:35 What I worry about is all the companies that don't have the resources to do it. And it's by the way, it's not just financial infrastructure. Think about energy infrastructure. The biggest utility company is going to be way ahead of you know, local water company in Akron, Ohio, Right, And so everybody's vulnerable, and so we've got to figure out how to help people and bring people along.

56:52 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 AI. Joe, and I know that you're into music. You like to DJ famously. Have you been experimenting with AI generated music?

57:08 Yeah, I mean I've been playing with it. And what I'd say is what I think is 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. Three Where it is, I 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, that's just a little bit of history about music production, because, by the way, thirty or forty years ago, I could never have produced music.

57:36 Now it so happens. I played an instrument when I was in elementary school. On high school, I played the saxophone. I can read music. I understand music theory because I played an instrument for twelve 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 it to four beat, you know.

57:54 So I understand bass music theory. But I've been a rock and roll guy forever. Like I love Bruce Springsteen. I saw my first Bruce Stringsteens show in nineteen seventy eight, The Darkness on the Edge of Town tour, when he wrote that album, and by the way, the albums that came before, at a bunch of them that came after.

58:12 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, and somebody recorded it and it got pressed onto a vinyl album. Okay, A lot of the music that we listened 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.

58:52 And so if you want horns, you can choose from one hundred and fifty different horns. Okay, you don't need fifteen different musicians. Nobody's talked about the difference how technology evolved, and by the way, what it did is because logic pro and able to exist and I'm relatively dysfunctional on the platforms. You know, I can muddle my way around, but I need an expert. Doubt maybe is they can do in three seconds what takes me ten minutes. But 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 basically take out a piano and say this chord sound, this chord progression. Try it on the computer.

59:30 You could say, I want this to be done in horns instead of 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 listened to is produced that way. Okay. Now what you've got is you've got an application that's basically doing that. Okay. And I think there are a couple of big issues that need to be wrestled through with this. The first is these apps are using other people's content in some way, and the artists aren't getting in any way compensated for that. And I think you've got to think about how you're gonna bring the artist community and their ip in the discussion of this overtime.

1:00:15 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. Okay, the stuff I produced, Okay, it's my voice, I said, I liked, I liked 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 get you're gonna get at the moment, certainly mediocrity and as opposed

1:00:58 to really really resting resident stuff.

1:01:01 All right, David Solomon, Clearly you've given the music industry quite a lot of thought. Thank you so much for coming on our thoughts. Really appreciate it.

1:01:09 Well, thank you for having me, guys, and I appreciate, appreciate the conversation. Yeah, that's kind of appreciate you so much. Appreciate it.

1:01:14 Thanks absolutely, We'll do it again, we will, Joe.

1:01:29 That was a lot of fun, A lot of fun, A lot of fun. I kind of surprised how much thought David puts into the music industry, to.

1:01:34 Be honest, Yeah, I know.

1:01:35 I loved I loved 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 was like, well, I 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 and 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 I asked him that question is like, 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.

1:02:15 I kind of wish I had that skill of it more.

1:02:17 Yeah, you can always tell a good all thoughts guest by like how many specific dates? Yeah, data they actually bring up.

1:02:23 But I know a good data point, by the way, just the one. There's one data point. So when in the music question, yeah, and he mentioned having gone to see Bruce Springsteen's Darkness on the Edge of Town tour. That album came out really close to the bottom in the nineteen seventies. 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 twenty ten, so twice that album has been associated with sort of like generational historic lows on them.

1:02:51 That's funny, okay, So okay, Well know the crash is coming when Bruce Springsteen re releases this for the.

1:02:57 The next time, there's gonna be somewhat will be another crash when he re re releases its bottom.

1:03:02 Yeah, the bisignal, all right, all right, important data pointing 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, or whatever you want to call it, seems to be getting more important.

1:03:26 I would actually even say there's another thing. It's absolutely true, and I would say there's twice something else, which is then okay, like everyone gets this sort of like commodified AI, yes, sir, so okay. Then you can infer that the human touch will be more important. But then you add in the fact that the last fifteen years of mobile phones has destroyed so many people's like ability to like make eye contact, they'd probably be even more in the 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 in the air.

1:03:54 All right, so everyone remember to look into each other's eyes when you're speaking with someone and I guess up the phone. Yeah, David's advice.

1:04:02 I also just thought it was really interesting that he thinks we're going to see more public companies doing private equity.

1:04:07 Yeah.

1:04:07 Brings that because I did that alphabet headline, the Google headline that was a big deal and I think called a lot of people by surprise. So the fact that it's like this is the first of multiple he expects, it's a very interesting out trend to.

1:04:21 Watch for sure.

1:04:22 All Right, shall we leave it there?

1:04:23 Yeah, let's leave it there.

1:04:24 This has been another episode of the aud Thoughts podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway.

1:04:29 And I'm Joe Wasenthal. You can follow me at The Stalwart. Follow our producers Carmen Rodriguez at Carmen Ermann, Dash, Ol Bennett at Dashbod, Cale Brooks at Calebrooks, and Kevin Lozano at Kevin Lloyd Lozano and from our Oddlots content. Go to Bloomberg dot com slash odd Loves or have a daily newsletter in all of our episodes and you could shed about all these topics twenty four seven in our discord Discord dot gg slash odd Laws.

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