SpaceX, Tesla, Meta Headline Week's Big Tech Earnings

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0:09 This is Bloomberg Businessweek Daily. Reporting from the magazine that helps global leaders stay ahead. With insight on the people, companies, and trends shaping today's complex economy. Plus, global business, finance, and tech news as it happens. The Bloomberg Businessweek Daily Podcast. With Carol Masser and Tim Stenebeck.

0:32 This rebound in chip makers booming the stock market as dip buyers emerged on bets that the AI investment boom will continue to support solid earnings. Following a sell-off in one of Wall Street's most crowded bets, we did see a gauge of chip giants climbing, as we said. The NASDAQ 100 is higher. Keep in mind, we'll also get some insight into that AI investment boom thanks to meta platforms providing earnings along with Tesla, also SpaceX, and then there's more to come. Here to kind of set us off for the week, is Mandeep Singh. He's Global Head of Tech Research at Bloomberg Intelligence. He's here in our Bloomberg Interactive Brokers Studio. Last week was tough for the AI trade. CoreWeave, just in general, it just felt like

1:11 such a pushback. The semiconductors, we get Meta, SpaceX, Tesla. How important are these to you in terms of getting another read on what's going on in the AI boom?

1:21 I mean, I consider SpaceX to be a hyperscaler along with Meta. And so SpaceX to me is really interesting given the backdrop of Starlink situation and what's going on with them.

1:34 And obviously, they won't comment much, but.

1:37 I expect on the analyst call, you would see questions around Starlink and then what it means for the cloud segment growth. Because in the end, They need more customers. They need that cloud segment to ramp up. And the expectations are quite high because the company guided to $ 100 billion in ARR by the end of the year.

2:01 And they're nowhere close.

2:02 Where are they right now?

2:03 They are closer to a $ 25 billion, $ 30 billion revenue run rate. So even if you extrapolate the ARR. they're nowhere close to that $ 100 billion mark. And so that's where the expectations are high. And you want to see them talk about customer growth, which they have. I mean, Anthropic and Google, but they need more than two customers.

2:23 Yeah, and I mean, this is just their second public quarterly earnings report. So do you feel like there's going to be any sense of understanding, I should say, or maybe do you think investors may be a little bit easier on them as they're just kind of getting out? Or you mentioned the bar being high.

2:39 Talk about that.

2:40 I mean, I think overall, the sentiment going into the print is I've been hearing a lot about Starlink.

2:47 It's not very clear what happened.

2:49 And look, that is the more established part of the business. And if they can't win business outside the US, that's going to become a problem, whether it's Starlink or the cloud side of the equation. So something to keep an eye on in terms of how they guide. And I feel they've been quite aggressive with their guidance. So in the end, it comes down to the commentary around the expectations for 2027. And then how does the market react around CapEx? Because we have seen what's gone with CoreWeave.

3:21 I mean, SpaceX is incredibly levered as well. So if the market is not liking the high leverage for these neoclouds, I don't think SpaceX gets a pass either.

3:33 Yeah, I mean, debt is debt, and it's a pretty start to look at the ad. I'm looking at the equity side. SpaceX shares are down about 27% from that high just after the IPO. All right, so we're watching that one very closely. What about meta and how That fits into the AI trade because it feels like all of a sudden they're like, wow, look at what you like MetaViews and everything that they're doing. And they've gotten a lot of attention.

3:55 I do.

3:56 But with that being said, now that they have a frontier model to show for all the CapEx that they have done so far. the monetization question still looms. And, you know, if they're talking about raising CapEx for 2027, which I think they will, given they feel emboldened by the fact that they have a frontier model now, then the debt question starts to come even for someone like Meta.

4:19 Because now it's not about financing everything through your operating cash flow.

4:24 You have to issue debt.

4:25 And yes, Meta is investment grade and they don't have any debt concerns.

4:29 Like the Corvibs.

4:31 But at the same time, you know, the bar is getting higher in terms of showing that monetization.

4:37 Why is it all of a sudden getting higher? Like it just does feel like we've been kind of building to this, but it does feel like we're kind of at a point.

4:43 The cost of capital has gone up.

4:45 Look at where we were at the start of the year and where we are now with treasury yields. And so everything has gone up in terms of, you know, what you have to pay to get any debt.

4:55 You know, it's interesting because I feel like if you flashback just about six months ago, it was a lot of enthusiasm about the AI spend. So do you think it really is that cost of capital that's really changed the narrative in a sense, or is it also a combination of something else?

5:09 And the revenue that these companies have to show. So we know the Frontier Labs have grown their revenue fivefold from the start of the year to where we are now. But even with Anthropic, they had stellar growth for the first nine months. Well, now we are starting to see maybe that monthly ARR growth is slowing down. So when you are in that sort of situation where, again, the growth numbers are great for the overall year, but then people are parsing through what's going on recently.

5:38 And why is it slowing down?

5:40 Is it because of open rate models or token pricing coming down? So it impacts the ROI and what these companies have to show for all the capex that they are doing.

5:50 Mandy, Dan Ives is going to join us after you, after a break. He does write this week a validation moment for AI. And he kind of, some of what you said, he says three of the names at the center of the AI revolution reporting. He says we're going to know whether or not Meta can begin to monetize Muse on top of the Ad Engine, whether SpaceX can show Starlink's cash funding, an AI business that is starting to pay for itself, and whether Tesla can move from autonomy from optionality to to a fleet. Do you kind of agree with most of this?

6:23 I mean, I feel this earning season, you will see the cloud hyperscalers. And I feel I won't put meta in that basket. So it's really your Amazon, Microsoft, and Google. They will shine because their cloud business will show a sequential acceleration.

6:40 You know, the earnings will reflect that.

6:42 Is that because it's not just AI that's part of that business? Is that part of it?

6:46 So they are benefiting more from the infrastructure demand. So they are running the workloads that are needed for OpenAI and Anthropic. So even though Anthropic is facing pressure from token pricing going down, they still need to run their workloads on Amazon and Google infrastructure and they're not cutting their prices. So in the end, I feel because AI demand and usage has gone up, that will show up in the hyperscale cloud earnings. And so they will have a nice acceleration. I expect all the clouds to do well.

7:22 But then I think the lab side seems to be incrementally slowing down because of open source pressure. These guys are insulated from that.

7:30 That's real.

7:30 Yes.

7:31 I'm curious, which of the hyperscalers do you think the earnings report is most consequential this season? Do you think it's going to be a bit of a digest of all of them together? Or is there one that you think might be the most sensitive?

7:44 I mean, with Google, there's always pressure on them because everyone feels their search business is under threat from OpenAI and now Muse and all that. So there's always that risk associated with Google, but they come out with great numbers. So I feel from that perspective, Google is always the one which is under the radar, but they've come out and beat their numbers every time.

8:10 You know, it's funny that you say, oh, the open source. Like, it does feel like we had the CEO and co-founder of Perplexity on and talking about doing just that in terms of open source and thinking that's the best way to go in terms of users and possibly people who might want to do something wrong, just have it open to everybody. But increasingly, there's more and more... newer names that are coming into this, and it changes the dynamics.

8:34 It does.

8:34 Or it can.

8:35 Look, I think you still need compute.

8:37 If there's one thing we know about AI, is AI needs a lot of compute, and companies, even the labs, haven't been able to optimize that.

8:46 But it's still not a guarantee for the neoclouds, right?

8:48 Not a guarantee for the neoclouds because of their financing structure.

8:52 So, you know, that's the surprising part.

8:54 CoreWeave has shown that negative sentiment despite the GPU rental prices going up. So you would think that should be favorable dynamic for them. Right. But it's just the financing structure and all the commitments they have. And that's why, you know, they had that pressure last week.

9:14 Stay with us. More from Bloomberg Businessweek Daily coming up after this.

9:26 As we start to get a gut check on the AI spend, the AI narrative, the valuations, a lot of big tech players starting to report earnings this week and then in the next few weeks. Our next guest is out with a research note calling this week a validation moment for AI. Let's get to it. Good to have back with us on Bloomberg, Dan Ives. He's partner and senior managing director at Yorkville Ives & Company. There's also the Dan Ives Wedbush AI Evolution ETF, which has some $ 885 million in assets, up more than 20% year-to-date. And then there is the just-launched $ 200 million publicly listed closed-end investment fund called Ives Ultra AI Opportunities. It invests in private VC-backed AI companies. He's always a busy man, but

10:06 he always finds time for us. Dan, good to have you back.

10:09 You're out there in New Jersey. Yeah.

10:11 How are you?

10:11 Good.

10:13 No, look, it's obviously been.

10:16 It's been exciting but turbulent last few weeks. We were in Korea last week trying to get a better sense in terms of memory and what demand looks like there. But look, it all comes down to this week and next week in terms of earnings. I mean, that's, I think, ultimately what the street needs to see in terms of the hyperscalers and big tech.

10:35 What did you, though, glean from your time in Korea? Obviously, an important point. We've seen their markets under extreme pressure, and there's a lot of names, obviously, that play into the semiconductor space that seemed to be pretty vulnerable last week, as were U.S.

10:50 Semiconductors.

10:51 But what did you glean from what you saw and heard?

10:55 Yeah, no doubt nervousness, but demand supply 13 to 1 for memory chips. So I just, look, as me and you, and we've talked about in the show, you know, over the years, like we're going to go through these narratives, go back to SAS apocalypse earlier this year. You look what's happening here. I'm not saying that there's validity.

11:15 Of course, there's validity.

11:16 In terms of some of the nervousness, what we saw with CoreWeave and the bonds and CDS spreads.

11:22 But the reality, this.

11:25 Acceleration is happening in terms of demand on chips, hyperscalers, use cases.

11:30 And that's what I think earning season is going to show.

11:33 And yeah, just how important is this week in terms of just restoring confidence really in the AI trade?

11:39 I think it's very important because in the vacuum, when you don't have numbers, you could have different narratives, different reports, And I think that sort of could dictate sometimes. And I think, look, it gets investors off their game because there is nervousness. We're going into the midterms. There's always a lot of volatility around this period of time. But at the end of the day, it comes down to fundamentals.

12:05 What does demand look like on chips? What are enterprises doing relative to the hyperscalers? And what do use cases look like? Palantir, Snowflake, ServiceNow, so many others. And that That is what will dictate if stocks go high. And I still believe we're in year three of a 10 to 12 year build out.

12:25 What do you then, you know, what does it mean if we're in year three of a 10 year build out, Dan, and you've got, you know, N scale, we had a headline cross N scale, anthropic and talks for a $ 45 billion cloud computing deal. So basically N scale would be selling computing power to anthropic. and this deal could be worth $ 45 billion. What's interesting is, and it could be finalized in the coming days, according to our Bailey Lipschultz, Dena Bass, and Brody Ford, But it comes after we just had a story about how Nscale's valuation is being questioned, this $ 30 billion valuation, investors against the backdrop and concerns about AI, especially the neoclouds, that maybe it's worth about half of that. So do you have a feeling on

13:09 neoclouds versus maybe the hyperscalers in terms of their security and their role longer term?

13:16 Yeah, I think hyperscalers, they're in a total different world relative to not just their balance sheet. And then you look at the enterprises in terms of where they sit, how they're positioned in terms of these strategic build outs, as well as on the data center build out. And that's why I think Microsoft, Amazon, Google continue to be interested.

13:35 a different stratosphere. Oracle is a good example of trying to be a hyperscaler, but there's pain with that, right?

13:42 When you take on the debt and they've had a cut cost.

13:46 When you go down with CoreWeave Nebius, those are going to be the sort of champions relative to what we see on Neoclouds.

13:54 But I think you have to separate it out. And look, in the game of musical chairs, will there be some without a chair? Of course not. But I think relative to where we are today, it's so early. And if you look at the demand and you look at ultimately capacity and where it's going to go, even if you haircut some of the data centers that don't ultimately get billed out, I still think streets underestimate numbers massively over the next one, two years.

14:20 Can I just ask you, are you invested in N-scale?

14:25 So we just raised, so that $ 200.

14:28 Million was just raised. We haven't made an investment yet. From the IPA.

14:32 Do you want to? Or can you tell us?

14:35 Exactly. But look, the whole reason we did that, it was to give investors around the world the ability to have a public equity, then invest in private AI, private AI leader companies that are out there. Because so many are private, and it shouldn't just be a handful of people in Silicon Valley.

14:57 That could own those names. That's the whole goal of the IVAI.

15:00 So a name like Nscale is what you would want in that fund?

15:03 I mean, that's a good example of ones, whether it's Anderol, whether it's OpenAI, whether it's FigureAI. I mean, there's so many great private companies. We are in an innovation boom. But the problem is that if you look at it just, and we always talk about with the bears, and I get the debate, and so many smart investors that obviously are on the other side of this, but it all comes down to execution building out the fourth industrial revolution.

15:31 As this happens, that will prove it out.

15:33 And just like the last few years, it will show this is more of a white knuckle moment than a time to panic.

15:40 Dan, what would you actually need to see in these earnings to make you less bullish on the AI trade?

15:44 Yeah, it's a great question.

15:47 If we saw CapEx that starts to take foot off the pedal, if we started to see demand rise, deals that we thought were going to happen on the software, on the hyperscaler side.

15:59 Not happening. So I think that to me is the key.

16:02 And I could just tell you from our checks, combined with what we see is going to happen in earnings season, like for every dollar in cap backs from big tech, there's a five to six dollar multiplier we estimate across the rest of tech. And that speaks to why this is just, we're talking about a generational theme. to the three to four trillion that's going to be spent over the coming years.

16:26 You know, and I know we've been talking a little bit. You mentioned CoreWeave. We've been talking about the debt. It felt like there was a time, though, where investors, or rather, excuse me, companies could really just take on any amount of debt. We could talk about the AI spend, and it felt as though they were rewarded for it. But now we're seeing a bit of a shift here in the market where you are seeing a lot more scrutiny.

16:44 Can you talk to us just about the burden of proof that we're now expecting, essentially, out of these big tech firms?

16:50 Yeah, I think.

16:51 Yeah, I think part of it is just what we see with bonds and then just with yield.

16:55 So there's just more pressure. Two is as you get to a little more.

16:59 Maturity on the trade, investors are trying to understand like, okay, what does capacity look like? Like who's at risk? Who's not at risk? Like what, what does GPU capacity look like? What does backlog look like? So I think as we go into the next phase of, Investors start to get more of their sea legs to understand who they're going to bet on and maybe who they're going to bet against.

17:23 That's also why, like, if you go back to maybe where this was one, two years ago, it's a, we're in a different phase of the market.

17:29 But I think that's a great.

17:30 Thing because the data centers are getting built. The use case are getting built. Look at Apple, look at meta. Look at Tesla, look at SpaceX, physical AI. Like now we're going to the next phases. And not everyone's a winner, but you'll better be able to discern who the winners are from the losers.

17:49 So what has to be a loser? Maybe it's in this earnings season. What company is a loser that you're like, ooh, okay, maybe this is a sign of something that could go wrong? What company in particular?

18:02 I mean, on large cap, we've been more cautious on Oracles. Now, Oracle's not good. They're a phenomenal company. And you think about the OpenAI $ 300 billion deal. The reason we're just more cautious on that is that when you have to cut muscle, cut your core to build out the data centers, the business gets hurt. And it's hard for some of the stock to work in that period because they're trying to be a hyperscaler. SpaceX, they're trying to be a hyperscaler.

18:32 And that's why I think ultimately they're going to need Tesla as part of it. You see what they're doing in NVIDIA. But who stands in a different league is Microsoft, Amazon, Google, because.

18:41 They're already there.

18:46 Stay with us. More from Bloomberg Businessweek Daily coming up after this.

18:57 Yes, it is Carol Master along with Isabel Lee in for Tim Stenevek on this Monday. We're going to go from New York to Vegas because underway in Las Vegas is Money 2020. It's a conference that describes itself as a content sales and networking platform for the global money ecosystem. We know there's so much going on right now. They focus on what's next across the world of payments, fintech, and financial services, something I feel like you talk a lot about. Definitely.

19:21 I actually have been to one of these conferences, and you meet all sorts of people.

19:25 It's actually fun.

19:25 You meet financial advisors, portfolio managers, and the intersection of all of this, right?

19:31 We should go.

19:32 Well, we're going to go there now because right now with us is the CEO and co-founder of the AI search company, Perplexity. He is Arvind Srinivas and he does join us from Money 2020 underway in Vegas. Also with us is the host of Bloomberg Tech on Bloomberg TV, Ed Ludlow. He's out there in our San Francisco bureau. Arvind, I want to kick it off with you. Your panel tomorrow speaks to us in a big way when it gets to what's going on in financial services and how AI is rewriting it. So I am curious, what does it mean in the real world when we talk about this, or you've got something that's entitled this, and what does it mean for perplexity or another agent what it could actually do for the financial world. Because I will say,

20:14 being at something like FutureProof out in Huntington Beach recently in California, there was a lot of talk about the role of agents when it comes to the financial world.

20:23 A lot of people think of agents as just consuming data that exists on your financial services. Like Plaid is a great connector that aggregates a lot of different data in one single platform. The key difference on perplexity is perplexity is an accuracy product. Whether you think of it as a search product or an agent product, it doesn't matter.

20:45 We are super focused on being the most accurate AI out there. And there is this benchmark called FinSearch.com built by ByteDance and Columbia Business School on which perplexity is.

20:56 A state of the art.

20:58 Finance is a vertical on which accuracy is stable stakes. And perplexity is the best at accuracy because perplexity focuses on search. and focuses a lot on making sure that the agents that power your financial research are grounded in accurate real-time data, as well as your personal data, with a clear auditability trail to where all that data comes from.

21:22 So that is the key differentiation to.

21:24 What happens on perplexity computer. And we've been working with Plaid for many months now, and the usage has been skyrocketing. People who are using the Plaid Connector are using it to begin with to track their spend, but over time, they basically use it as their personal CFO.

21:43 In your own personal life, you're the CEO.

21:45 Perplexity becomes your CFO for tracking all your personal finance spend, figuring out your investment strategy, how to construct your portfolio, how to make sense of what's happening in the world affects your portfolio, how to rebalance it. And so it starts from basic things like where am I spending a lot and help me get to a certain budget of spend per month or what are subscriptions I'm wasting my money on to actually building a portfolio and crafting a retirement strategy all the way there.

22:14 Aravind, I appreciate the emphasis on accuracy. And there's a distinction, right, in a world where an agent is AI that can take action as opposed to just a recommendation. Could you talk a little bit about the kind of technical challenge of that? How the model can decide when it's right to make an independent and autonomous action decision, and when it still needs to be referred back to the user for a check?

22:39 At this point in time, we are only offering read-only agents. So perplexity computer can only do read-only actions on data it ingests from Plaid, or the data it ingests from Morningstar or PitchBook, or fact set, so we believe that agents are still not quite there to actually go and make investments on your behalf or place trades on your behalf.

23:03 And you have to be very precise on what you want it to do. We've of course integrated Coinbase and public and all these APIs for the genic trading. But the way people actually use these agents is not to actually go build a bot that trades on your behalf, but actually make sense of what's happening in the world and help you decide what trades to place. That's where we are today.

23:27 And we really.

23:28 Believe that accuracy is the only way you gain the user trust. You need to first gain the user trust for them to make decisions on what to place trades on or what investments to buy on using your tool. before they start trusting your tool to actually go do that on your own behalf.

23:44 Arabin, a big news headline in the past week is that you are open sourcing space, basically the security system that you sandbox agents in, right? So the agent stays within space while it runs code, works on files. Why did you take that step?

24:02 We want to support the ecosystem. We started building the sandbox platform to serve ourselves. If we relied on a third-party provider to run our sandboxes, we'd be spending an additional $ 50.

24:14 Million a year or something at the scale of traffic we serve.

24:17 So it made all sense for us to build our own platform and to optimize it to be secure because you're often reading about how agents are going rogue, escaping sandboxes, doing all sorts of arbitrary things they were not intended to do.

24:31 Our attackers can gain control into.

24:32 The sandbox on which all your credentials are running and they could use it in malicious ways. So we wanted to first make sure it saves us a lot of money and it's very secure for our users, it's secure for our company. And we decided that it's in our best interest to open source it because it attracts a lot more eyes on it. And that way we can make it even more secure and even more robust and even more scalable, as well as optimize it for multiple different chips.

25:02 So x86 is the default CPU.

25:04 On which all these sandboxes are running right now. But specialized CPUs are being built for hosting sandboxes.

25:11 So that's another big focus for us.

25:14 Ed, you're still with us, but that semaphore report, I want to bring you into it. I guess one of the questions is you're wondering why are they doing this, right? What was the reason in terms of opening this up? What was it that they were maybe trying to prevent?

25:31 So there's the distinction of the risk of an open weight model and then the environment that an agent runs in. So why there's a lot of emphasis in the news cycle right now, you saw it today from the federal government saying that they won't allow civilian agencies to use DeepSeek, is that with an open weight model, it can be downloaded in its entirety, right? It can be run on your computer that's sitting on your desk and you can modify it. That takes it outside of the safe environment that the designer of that model puts into its own servers.

26:00 And then on, you know, open sourcing it, it's also supporting people that want to have access to AI at an affordable level.

26:06 I want to just follow up on the Semaphore report you were just talking about with our Ed Ludlow. You know, why was this necessary to do? And I'm just curious, is there a bad thing that you're trying to prevent an autonomous agent from doing?

26:22 The best way to build safe systems is to make it open source.

26:26 It's been true.

26:26 Your Android phones are running a version of Linux, which is open source. All our code is being hosted on GitHub, which is based on open source. And so a lot of the deep learning libraries are built on PyTorch, which is open source. And these are all safe and secure systems on which our world is running already today. And so we think that sandboxes should be viewed in the same way. Instead of talking in abstract terms, like agents going rogue, why don't we actually just open source the platform and the underlying code base and give attackers and defenders the same code base so that everybody can figure out what are all the various attack vectors and build the defenses for it.

27:11 That's exactly what we did. We first had space.

27:14 We asked a bunch of frontier models to go figure out ways to escape the sandbox, even though we were you know, make sure that as far as the network level, that's not possible. And we will figure out all the various ways in which they can do that and build the defenses into the Sandbox and open source it. And after a few iterations, you're going to end up with a very secure platform for.

27:35 Hosting agent run times.

27:37 And this way, the fact that it's open source means it benefits the whole ecosystem. Every new cloud can take it and run Sandbox.

27:44 Inference, right?

27:47 AI inference, Arvind, is expensive, and you're giving away security software. What's the part of your business that actually becomes more profitable as you scale, and what happens if the model costs don't fall as fast?

27:57 We continually post-train open-weight models and serve them on our own products, and so we're the model-neutral layer for AI.

28:07 We are able to.

28:08 Charge a markup on all the tokens we serve over the inference cost because we deliver real value to the user. It's about the work that gets done. It's not about which model gets used. So that's the position of an orchestrator. Tokens are going to grow like multifold, but the spend per token is not going to grow the same level.

28:27 So the one who orchestrates all the best models to get the work done for the user is going to be able to charge a markup on what it actually costs to serve the models. And whatever it costs to serve the models should also go down as you start post-training more cost efficient models. So you get margins on both sides, and that's the way to actually become profitable.

28:48 Hey, listen, we just have about 30, 40 seconds. What is Perplexity becoming? It started as an AI answer search engine. It's increasingly about agents and doing work. Just got about 40 seconds, 35 seconds. What is it that you guys are becoming? Just quickly.

29:04 Perplexity is the place where work gets done in a model-neutral way. So you don't have to think about which model is needed for what task. You come to Perplexity, you get all the different models. We route across these different models. and get your job done. We're the most accurate AI out there.

29:19 And forgive me, yes or no, is an IPO in your near future? Just quickly.

29:23 We'll see. We'll see.

29:29 Stay with us. More from Bloomberg Businessweek Daily coming up after this.

29:41 Carol Master along with Nora Melinda here in our Bloomberg Interactive Brokers studio. Nora in for Tim on this Monday. Hey, we want to talk a little bit about Warren Buffett, Chairman Emeritus of Berkshire Hathaway, worth a mere $ 150 billion according to the Bloomberg Billionaires Index. Not the richest, but it's a lot of money, no doubt. And for a long time, the world pretty much knew what he was going to do with his fortune, but that did change.

30:05 And now the fate of one of the world's greatest fortunes will be decided by three very different siblings living three very different lives who didn't expect to be or necessarily even want to be the ones doing the deciding. So let's get to this story. With us, the two reporters who put this story together, Sophie Alexander, she is wealth reporter, and Alex Rajabandari, he is US insurance reporter, both at Bloomberg News and both in our Bloomberg Interactive Broker Studio. Killer story, congratulations. I want to throw it out to both of you first. What did it take to report this out? Because these are tough people to find information about. I mean, there's a lot out there, but it's still tricky.

30:45 Yeah, luckily we got great access to the three siblings. First we visited Peter, or I should say first we visited Howard, who's the middle child, in Decatur, Illinois, where he has a farm and police training complex. And then we flew out to New York, where we visited Peter up in Kingston, New York. And then later we visited Susie in Omaha, where of course the family is from.

31:08 Was it hard to get them to agree? Howard's been out there, I feel like, a lot, certainly talking to Bloomberg over the years in a big way, but was it hard to kind of ultimately get them all to agree?

31:19 I think once we got to speak to one and they spoke to their siblings about how we wanted to approach it and how we wanted to document what they were doing and it's something that hasn't been done really in a comprehensive way before, then that was locked in.

31:34 And how long did all of this take to come together?

31:37 We started reporting in June, right? We visited Illinois and New York. That was in July. And then, you know, the whole writing and fact-checking and doing everything to make sure that it's all together.

31:50 I have to say, it's a fun story to play with on the Bloomberg. Some great pictures, some great graphics. So, Sophie, let's take a step back because for a long time, first of all, Bill Gates and Warren Buffett were buddies. They took train rides together. They did a lot of stuff together. The assumption was that it would go To the Gates Foundation, right? So talk to us about the backdrop of where we thought Warren Buffett's money was all going to go.

32:13 Yeah, so Warren has been at this project since 2006. That's when he first said that he was going to give away the majority of his fortune. And back then, he had decided that most of it was going to go to the Gateses.

32:25 The Gates Foundation.

32:26 And that continued for two decades until this July when he decided that he wasn't going to give to the foundation anymore. And it actually sort of changed a little bit as well in 2024 when he just had decided that after he died, the remainder of his wealth would go to a trust for his three children to decide to do.

32:49 What to do with.

32:50 Is there any insight onto why that shift may have happened, especially given the fact that, you know, he spent decades saying that he wanted to give virtually his entire fortune away. And then, you know, his three children suddenly end up responsible for figuring out what happens to all of it.

33:04 I mean, I think part of it is just the fact that he hasn't been able to come anywhere close to doing it. When he first made that promise in 2006, he was worth $ 44 billion. Since then, he's given away more than $ 70 billion. And again, he's still worth $ 150 billion. It's just the work is going to go on for a long time.

33:24 Alex, come on in. We've got a chart to talk about his wealth distribution. And we see the $ 150 billion. For those on radio who can't see it, but the bulk of the pie chart is that $ 150 billion that has to be given away. There's $ 4 billion that went to Peter Buffett, about almost $ 50 to the Gates Foundation, right?

33:44 Another $ 4 to Howard Buffett, $ 11. 5 to the Family Foundation, and another $ 4 to Susie Buffett. So that gives you an idea. But the bulk of his money is given away. Tell us about these three very different siblings.

33:57 Right.

33:58 And first of all, are they comfortable doing this, or do they feel a lot of pressure?

34:02 Sure.

34:02 There is a variety of.

34:06 Feelings they have towards this responsibility.

34:08 I would say Susie, the eldest child, she feels a responsibility to her parents to do that right, and she's been talking about it with us.

34:22 Howard is very excited. He has a lot of ideas.

34:25 He says he wants to revisit a list of ideas he wants to finance with all the money that's going to come his way. Peter has more reservations. He does think that it's not really natural for anyone to have that much money to distribute in the first place. And look, all of them, they found out about this pretty late in their lives. I mean, they had careers, they had lives on their own. And in 1999, their parents set up their foundations for them to kind of make them, you know, make them start giving away money through philanthropy.

34:57 Then in 2006, that pledge happened. That was a big change for them. It became a big part of their lives. And that was like a full-time job still. And they're in their late 60s and early 70s. So they're going to work at it for the rest of their lives. But they've got to get moving.

35:11 Right.

35:12 So ramping up donations is going to have to go up, even from Buffett's side, because he wants to give it all away in the next years. to them while he remains alive. But if he passes away, everything's going to be to them and they're going to have to, if they want to give everything during their own lifetimes, they're going to have to, to bake up.

35:29 Yeah.

35:30 Wow.

35:30 And I know that it's, there's essentially this idea that they have to agree unanimously on where it goes. Is there any sort of understanding as to how this is supposed to work? Are there any differences in regards to, you know, potentially, Who wants to put money where?

35:45 Rock, paper, scissors.

35:46 Is that going to come in at any time?

35:49 I have two siblings, so I can only imagine.

35:51 So that's the plan for what happens after Warren dies. And they haven't really discussed it yet. They don't know what they're going to do. We asked them about this, whether they were going to just continue on with the current path, which is giving most of the money to the family foundation, the Susan Thompson Buffett Foundation. and then smaller amounts to each of the kids' foundations? Or are you guys just going to pool it all together and tackle something big with a bigger pot of money?

36:17 They don't know.

36:18 But it's interesting. I love how you start the story and you talk about meeting Howard and there's Ozzy Osbourne playing right in the background. You talk about Peter and he's been making, converting old furniture, an old furniture factory into a souped up community space. This speaks to Such different, it sounds like, different critters. And then there's Susie, and she's been doing things like early education centers, after-school programs, a science museum. So how are they approaching it in terms of bringing, is it important to them to bring in their preferences, or do they think about what their father wants?

36:58 Yes.

36:59 I don't think their father wants really anything or has voiced anything in that regard. He says, and he's openly repeated, that he has never looked at their 990s. He gives them a free reign for their donations. I would say they have different approaches to philanthropy. They all cater to different causes. One thing that stood as a common thread between all of them is that they don't really want to make big, checks the way Mackenzie Scott would do, and I think Sophie can speak more about this, but, like, they would rather focus on, like, key causes, trusted allies, but, like, a closer relationship with the grantees.

37:40 Sophie, that's a really good point. Mackenzie, she's just kind of changed the way people give away money, right? She just kind of shoots from the hip and it seems to go. But, you know, you give a large gift. You can change a nonprofit like no other. So it's interesting how they're thinking about it.

37:56 Yeah, absolutely.

37:57 I mean, a lot of Mackenzie Scott's gifts have just transformed the game for nonprofits, a lot of small nonprofits that aren't used to this amount of money. And so a lot of them have been able to set up endowments so that they don't have to worry about every year making sure they're getting enough checks. And this is not something that appeals to the Buffett kids. Susie and Peter both talked about how they don't like the idea of giving too large of a gift to a small nonprofit for fear that it'll overwhelm them. And Susie doesn't like the idea that, you know, if I endow a nonprofit, I might like them today, but I don't like them in the future, and I can't control that.

38:35 You know, this is all really interesting. I'm curious, you know, have they now potentially had folks reaching out to them, anyone saying, hey, you know, throw some our way?

38:45 Well, yeah, over the past years, it became clear that all the pledge money will go their way. They've seen a dramatic pickup in outreach from, Don't profits from all over the place, all over the planet. Yeah, they've all echoed the same sentiment.

39:00 Is that overwhelming?

39:02 I mean, they run on skeleton crews, right? They still have very small teams and they want to keep it that way to remain lean. But, you know, Susie's staff, including her, is 12 people. I think Peter has 28 people. Howard maybe a bit more in the 20s or 30s.

39:20 Peter's 24, I think, and Howard's 28. But yeah, small crews for the amount of money they're dealing with.

39:25 What about what their parents, though, taught them? And you say none of them really planned for all of this. Warren and Susan propelled their grown children to philanthropic work in a real way in 1999. But I do think about what we learned from our parents. We have a keen sense of what was important to them. So if you have an impact on maybe what they do, versus their own priorities?

39:50 I think that the influence of both their father and their mother runs a strong course through each of the children, and they've talked about this themselves. People who work for Susie talked about how she's like a perfect blend of her parents. And their mother was an activist. She was a civil rights activist and a women's reproductive rights activist.

40:10 And these are some causes that the kids still care about today, especially Peter.

40:17 And I see Peter saying, I don't think anyone should have billions of dollars at their disposal. It's just not natural. Is he alone in that thinking? Is there one sibling that maybe kind of pushes the others ahead? I know my older sister's like that. Curious.

40:31 I would say he's the only one to voice it that way.

40:34 He told us that a few years ago when he realized all the money was going to go to them, he told his father that he didn't want any part in it. His father said, I wouldn't either. And it His wish wasn't honored. So definitely he stands out in that way among his siblings. The other ones are, they realize it's a big responsibility, but they show some enthusiasm for it.

40:59 This is the Bloomberg Businessweek Daily Podcast. Available on Apple, Spotify, and anywhere else you get your podcasts. Listen live weekday afternoons from 2 to 5 p.m. Eastern on Bloomberg.com, the iHeartRadio app, TuneIn, and the Bloomberg Business app. You can also watch us live every weekday on YouTube and always on the Bloomberg Terminal.