Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. Bloomberg Tech is live
Speaker 1: from coast to coast with Caroline Hide in New York
Speaker 1: and Eva Low in San Francisco.
Speaker 2: Welcome to a special edition of Bloomberg Tech Live from
Speaker 2: the Bloomberg Tech event in San Francisco and leaders.
Speaker 3: They're from tech, they're from business, and they are gathered
Speaker 3: here to discuss how they can navigate economic, geopolitical uncertainty
Speaker 3: and of course multiply the opportunities in today's landscape.
Speaker 2: So we're going to talk about everything from robots to
Speaker 2: data center costs, the race to reach artificial general intelligence,
Speaker 2: and economic impact.
Speaker 3: But look, let's first of all talk about the markets,
Speaker 3: because look they're down today. Look, we're having our worst
Speaker 3: day on the NAST that one hundred since mid May.
Speaker 3: We've lowered it down to the lowest level since the
Speaker 3: end of May. We're under some pressure, we're bouncing off
Speaker 3: of our lows, are off by eighteen percent. But there's
Speaker 3: some anxiety and then that perhaps the market's run up
Speaker 3: too far too fast, particularly ships.
Speaker 2: Yeah, so this is a story about Broadcom and Broadcom's
Speaker 2: earnings and basically they said that in the current period
Speaker 2: they will book, sixteen billion dollars of sales in the
Speaker 2: custom silicon group that we're talking TPUs, we're talking a six.
Speaker 2: The street went into this with very high expectations. Seventeen
Speaker 2: point two billion dollars. That's a big drop right on Broadcom,
Speaker 2: the biggest drop I think since.
Speaker 4: January of twenty twenty five.
Speaker 2: So let's talk about it, because, hey, right place, right time,
Speaker 2: we're gonna have a big conversation today, Bloomberg Global Tech
Speaker 2: Executive Editor Tom Giles, Right place, right time.
Speaker 5: Thank you for having me.
Speaker 2: Yeah, thank you for being here, and later to say
Speaker 2: you will have a conversation with Broadcom CEO pock Ten.
Speaker 6: That's right, the man of the hour, the man whose
Speaker 6: results are moving global markets and not in the in
Speaker 6: the right way. The wait, he hopes, Probably you're if
Speaker 6: you're a ball right. The point here is, as you said,
Speaker 6: there was an expectation for revenue forecast for the current
Speaker 6: quarter at about seventeen point two billion. You come in
Speaker 6: at sixteen billion dollars. Still a pretty impressive number. Let's
Speaker 6: be fair. The demand is there, nobody's worried about things
Speaker 6: dropping off a cliff. But if you this stock is
Speaker 6: priced for perfection, In the run up to these earnings,
Speaker 6: that company added two hundred and seventy billion dollars in
Speaker 6: market capitalization. That is just another reminder of how much
Speaker 6: people are anticipating and expecting this demand to continue. Chips
Speaker 6: are a very cyclical industry. I was on yesterday last night,
Speaker 6: we had cerebra Ceo. We're going to listen to him
Speaker 6: in a little bit. I asked him, you know, are
Speaker 6: basically are we in a bubble? People are concerned about
Speaker 6: the sustainability of this rally, People are concerned about the
Speaker 6: sustainability of demand. His point is we're in the opposite
Speaker 6: of a bubble. We cannot keep up with demand, particularly
Speaker 6: in the hardware space. And I think that that is
Speaker 6: the message that howked han And is trying to bring across.
Speaker 6: We will definitely be asking him, did we miss something?
Speaker 6: Is there a nuance here? What do we need to
Speaker 6: know about your outlook going forward?
Speaker 7: Yeah?
Speaker 6: One thing that reading research this morning, including from Rosenblat,
Speaker 6: my friends at Rosenblatt, we're talking about how now we
Speaker 6: have even greater visibility. He talked about how we have
Speaker 6: visibility into twenty twenty eight, much further out than just
Speaker 6: three months ago. He said, I didn't have that visibility.
Speaker 6: I have it now and he's still sending bullish signs.
Speaker 6: So I think in the longer term, the market is
Speaker 6: going to be encouraged by that kind of visibility further
Speaker 6: and further out.
Speaker 8: And that's on the AI Infrastructure Playbook.
Speaker 3: And it's all because we're using jennitor AI so much more.
Speaker 8: Who are using it through the likes of Anthropic, the
Speaker 8: like of op Ai, the likes of groqu Ai.
Speaker 3: If you're looking over at SpaceX, these companies are about
Speaker 3: to go public and we have the anthropic leader here
Speaker 3: speaking as.
Speaker 6: Well, one of the co founders, Daniella Amaday. She's the president,
Speaker 6: the brother of the CEO. We're excuse me, sister of
Speaker 6: the CECO. We're going to be asking her about what
Speaker 6: it's like to have just gone out with your with
Speaker 6: your secret filing, your confidential filing. What do we have
Speaker 6: to look forward to with this this IPO, one of
Speaker 6: the biggest ever.
Speaker 2: I just want to set the scene for the Bloombo
Speaker 2: tech audience fit. Anthropic literally filed confidentially for an IPO Monday.
Speaker 4: Am I getting that right?
Speaker 2: The world's been wild an illusion last night SpaceX s
Speaker 2: one A the amended filing. They priced the IPO one
Speaker 2: hundred and thirty five dollars a share seek Thrace seventy
Speaker 2: five billion almost one point eight trillion dollar valuation, which
Speaker 2: we were right about. By the way, must tweeted that
Speaker 2: it was false. You remember, Tommy, you edited the story.
Speaker 8: I mean, just wipe that.
Speaker 2: Today's event is astonishing, right, It is astonishing that Daniel
Speaker 2: amoday will be on stage, that we have investors here
Speaker 2: who are across the cap tables of all three companies, Anthropic,
Speaker 2: Open Air SpaceX. We're going to learn something. I mean,
Speaker 2: this is a difficult environment to try and cover.
Speaker 6: Yeah, I think one of the big questions right now
Speaker 6: is this horse race between open AI and Anthropic. And
Speaker 6: open AI had really captured the world's imagination for years,
Speaker 6: since November, that faithful day November twenty twenty two, seen
Speaker 6: as the leader, seen as the one to beat. In
Speaker 6: the last six months, roughly, we've seen Anthropic ascent changed.
Speaker 6: We've seen them capturing people's imagination, whether it's through Mythos,
Speaker 6: their cybersecurity tool that everybody wants to get their hands on,
Speaker 6: that everybody is afraid of but also wants to learn
Speaker 6: how to use and learn from. Right they have They
Speaker 6: got out ahead of open Ai with the confidential filing,
Speaker 6: and they have been shown sending the message to the
Speaker 6: world that we have captured the business market in a
Speaker 6: way that open Ai has it. Now, I've talked to
Speaker 6: some people and they have said, don't count open Ai out.
Speaker 4: This is a horse race.
Speaker 6: Today Anthropic is seen as a head. Tomorrow it's going
Speaker 6: to be you know, they're going to really least a
Speaker 6: new version of chat GPT and it's going to maybe
Speaker 6: blow your mind, and they're going to be seen as
Speaker 6: a sendate and it's this back and forth and we're
Speaker 6: going to see that play out in real time with
Speaker 6: two potentially back to back trillion dollar IPOs.
Speaker 3: And we can play it out in real time with
Speaker 3: a member from Altimito who's backing all three of these courses.
Speaker 8: In terms of the venture.
Speaker 1: Capital space, talk about hedging your bets and get at
Speaker 1: nice hedge behind us as we hedge our bets.
Speaker 8: Tom Charles, we so appreciate.
Speaker 7: You being with us, Thanks very much.
Speaker 3: And look, it's his event that we're here and at
Speaker 3: the moment alongside Emily Chang. And look, stay with it
Speaker 3: because Blueleg Tech later today has a roll con President CEOs.
Speaker 3: We're just talking about hot Tang. What a time to
Speaker 3: be joining this blue leg tech conference. But also coming up,
Speaker 3: we've got the perfect person to be discussing some of
Speaker 3: those market valuations in the private space. CEO Data bricks
Speaker 3: as is the private company as reaching sky high valuations?
Speaker 8: Is it also thinking of a mega tech idea?
Speaker 2: Yeah, you're a CEO. You're reading the yes ones right
Speaker 2: and thinking what do I do? Could this be a
Speaker 2: sign of an AI bubble? Tom mentioned it? No, According
Speaker 2: to Cerebra CEO Andrew Fellman, he sat down with Tom
Speaker 2: last night.
Speaker 7: This is.
Speaker 9: What is unusual about it I right now is the
Speaker 9: builders are so far behind the demand it's absurd. We
Speaker 9: have a backlog of more than twenty five billion dollars
Speaker 9: of demand that there are none of us, not us,
Speaker 9: not AMD, not a video that can keep up with
Speaker 9: the demand that your employees are driving. And that's sort
Speaker 9: of in a lot of ways, the opposite of a bubble.
Speaker 3: Welcome back to our Bloomberg Tech special and look, maybe
Speaker 3: no surprise for anyone, I think so, But an AI
Speaker 3: bubble compute needs sas apocalypse. Some of the key themes
Speaker 3: that will be debated here today at the Bloomberg Tech event.
Speaker 3: Our next go, Well, you can talk about all of them,
Speaker 3: isn't the center. Ali Godzia is with us, the CEO
Speaker 3: and co founder of Data Breaks, one of the.
Speaker 8: Most valuable private companies.
Speaker 3: That has yet to file confidentially with the SEC as
Speaker 3: far as we know. We're going to hold back on
Speaker 3: IPO chat for a minute and ask you about whether
Speaker 3: this moment of all of these companies looking to access
Speaker 3: capital in the public markets, is that an anxiety if
Speaker 3: you could there be oxygen sucked out of Roumans some
Speaker 3: ways to back some companies such as yourselves.
Speaker 10: Well, we're private company, so private invests. They're soon not
Speaker 10: going to have all these companies to deploy their capital on,
Speaker 10: and so there's going to be a lot of capital
Speaker 10: available in private markets. So no, that's not going to
Speaker 10: be a problem with offer us.
Speaker 4: Allie.
Speaker 2: I'm really interested in what life's like for you right
Speaker 2: now as the CEO of a company of Data Breaks
Speaker 2: is evaluation, but also, like you know, I don't mean
Speaker 2: this is sort of flippantly like okay, great big private valuation.
Speaker 2: The company's growing incredibly fast, you know, revenue run rate
Speaker 2: Caro set up at the top everything that's happening in
Speaker 2: software right now. What is it that you are dealing
Speaker 2: with most often? What is it that you are sort
Speaker 2: of I don't know, waking up and going okay, wow,
Speaker 2: this is this is today.
Speaker 5: Yeah.
Speaker 10: My view is that we're in a very special moment
Speaker 10: because I'm a contrarian. I believe we actually already have AGI,
Speaker 10: artificial general intelligence already arrived.
Speaker 4: We already have what's your evidence? Yeah?
Speaker 10: I ask groups all the time. I ask this question.
Speaker 10: I ask how many of you believe we have AGI?
Speaker 10: And roughly ten percent of their audience usually raises their hands.
Speaker 10: Then I ask, how many of you think that the
Speaker 10: AIS that you use, the frontier models are smarter than
Speaker 10: most of the people you work with most of the time.
Speaker 10: And ninety percent of any crowd I've done this like
Speaker 10: twenty thirty times raised their hands. Okay, so it's already
Speaker 10: really plenty smart. We don't need AI to get smarter.
Speaker 10: It just is lacking context. If you could capture all
Speaker 10: the context of all the conversations we're having and everything
Speaker 10: that's happening in.
Speaker 4: The processes data bricks, that's exactly.
Speaker 5: If you could feed that to the AI.
Speaker 10: They already could be extremely productive, but no one's really.
Speaker 5: Focused on that problem.
Speaker 10: Everybody's focused on super intelligence and can we like continue
Speaker 10: the scaling laws And the problem is if we just
Speaker 10: could have that context, we.
Speaker 5: Would have huge breakthrough.
Speaker 10: So that's what database is focused on, you know, that's
Speaker 10: our only focus is how do we infuse that data
Speaker 10: context into this product we have called Genie, which then
Speaker 10: can help answer and automated questions. I think this is
Speaker 10: the most important question that people should focus on right now.
Speaker 8: And we've got plenty of new products.
Speaker 3: Like as you're getting ever higher valuations, you're backing it
Speaker 3: up with new offerings. I think about lik Base, I
Speaker 3: think about some of the M and a that you've
Speaker 3: been doing in the market to beef up the product offerings.
Speaker 3: What's hitting home at the moment?
Speaker 8: Where are the customers demanding of you?
Speaker 10: Yeah, as you said, like base is, you know, it's
Speaker 10: everyone wants these databases. People are not paying attention to databases.
Speaker 10: Everybody's paying attention to software is being commoditized because AI
Speaker 10: can produce software. But what they don't think about is
Speaker 10: that all software needs a database. It's a fact. You
Speaker 10: cannot have a piece of software and it's not using
Speaker 10: a database and Linke Base is really really really tailoring
Speaker 10: to those agents. So you know, firstas product group uses
Speaker 10: like base and their using they put all their KPIs
Speaker 10: in it, and that way the agents can actually start
Speaker 10: answering questions on all the KPIs that they have because
Speaker 10: you know, everybody's using agent stuff or.
Speaker 7: Is everyone using an agent now?
Speaker 8: Is adoption? Is productive activity there?
Speaker 7: Yeah?
Speaker 5: Okay, so that depends.
Speaker 10: So back to that context question, if we could just
Speaker 10: get the data to the agents. People are using agents,
Speaker 10: but they're not using it in its full potential. Maybe
Speaker 10: we've like tapped into one percent of it because it's
Speaker 10: not like autonomous agents are running around, you know, working
Speaker 10: together collaborating with humans and you know, so that's not
Speaker 10: happening yet. Why is that Because they don't have the context.
Speaker 10: So we have to infuse that context into them. So
Speaker 10: giving you another example, noval Artisk, you know they make Ouzempic,
Speaker 10: you know, big customer that actually leverages Genie and they're
Speaker 10: able to infuse a lot of the all the trials
Speaker 10: that they run, they infuse it to the AIS and
Speaker 10: now you can ask questions from the AIS about you know,
Speaker 10: how's that obesity study going. And they were able to
Speaker 10: shorten the time it takes to understand these studies using
Speaker 10: gene and agents from you know, weeks down to a
Speaker 10: few minutes.
Speaker 5: So it is happening. But we're just at the.
Speaker 2: Case study is real, right, and I'm not questioning whether
Speaker 2: it is. But that then jensen Han's equation of more compute,
Speaker 2: more tokens, more revenues, it means that that should put
Speaker 2: them on a trajectory to more profitability.
Speaker 4: Right to many people, it's really simple.
Speaker 2: The other thing that Gentleman outlined at the beginning of
Speaker 2: this week computext Yes, was that it's complete nonsense that
Speaker 2: software is in trouble because his thesis is that the
Speaker 2: agents themselves become the ultimate users of that software. I've
Speaker 2: been finding that concept very hard to understand. You probably
Speaker 2: are in a place where you can evaluate it early,
Speaker 2: aren't you.
Speaker 10: Yeah, So I think that's going to spot on with
Speaker 10: both of those. You know, we actually did the calculation.
Speaker 10: We think in the next nine months, but let's say
Speaker 10: you're around one year or two years, we're going to
Speaker 10: have more software being written than in all history of mankind.
Speaker 5: You know, no matter how you back into it. This
Speaker 5: kind of checks out.
Speaker 10: Okay, with so much software being written, there's going to
Speaker 10: be so much demand for all the other things. Like
Speaker 10: this isn't the ecosystem around software. We happen to do
Speaker 10: lake Base, which is a database, and you know we're
Speaker 10: seeing huge amounts in these database, but there are other
Speaker 10: ones around software.
Speaker 5: So yes, it's this is just continued.
Speaker 3: And therefore I go back to how we started this conversation.
Speaker 3: As you keep on scaling, as you keep driving innovation,
Speaker 3: do you need more private capital?
Speaker 8: Would you look to go for public capital at this moment?
Speaker 10: Yeah, I mean we are always interested and we're always
Speaker 10: talking to investors, and you know, I'm sure we're going
Speaker 10: to do more of that. We will also be a
Speaker 10: public company.
Speaker 2: I just think, but why also, why, like if the
Speaker 2: private markets will keep going with you?
Speaker 4: Yeah, what's your impetus figuring?
Speaker 10: Yeah, because you know, at our scale, you know, I
Speaker 10: think we raised twenty billion dollars. At these scales, we're
Speaker 10: almost trying to create a market transaction mechanism for our employees,
Speaker 10: which you know, it's ten thousand right now, but if
Speaker 10: you take all of them, the prior employees, it's probably
Speaker 10: fourteen thousand or so, you know, So there is a
Speaker 10: thing that can do that. It's called the public markets.
Speaker 10: So I just think this is a terrible year for
Speaker 10: you know, to go public. We're going to just so
Speaker 10: much happened super quickly. How closely did you read the
Speaker 10: space excess one and how closely will you track an
Speaker 10: anthropic IPO to evaluate the future market that you want
Speaker 10: to go into. Yeah, look, we're not really trying to
Speaker 10: time the market. We're trying to really win the market
Speaker 10: in the long run. That's really our progress.
Speaker 5: So I did not go through the S one filing
Speaker 5: one by word.
Speaker 7: It's got other things to do.
Speaker 2: Yep, Ali goes the CEO data breaks a busy guy
Speaker 2: back on Bloomberg Tech.
Speaker 4: Thank you very much.
Speaker 2: We're live from the Bloomberg Tech event, where one of
Speaker 2: the biggest questions facing investors but also founders alike is
Speaker 2: what comes next IPO market, the AI boom, how it's
Speaker 2: reshaping technologies landscape? Joining us right now is a poor Bagarawil,
Speaker 2: partner at L Timater Capital. L Timater, Let me just
Speaker 2: set the scene right so I also understand the context
Speaker 2: view of the world we're in right now is crazy
Speaker 2: and thropic just fold confidentially ultimately leads that round. I
Speaker 2: get that there's a limit to what you can say
Speaker 2: about that, but you're also on the cap table of
Speaker 2: open ai SpaceX. This isn't also about IPOs in isolation.
Speaker 2: Alphabet came out and upsized an eighty four billion dollar
Speaker 2: now equity offering. So actually my question to you right
Speaker 2: now is what is the capital market telling you about
Speaker 2: the state of the world. Is that a good place
Speaker 2: to start, Like, that's a great basis, sir. Thank you
Speaker 2: for having me at Caroline. It's lovely to be here.
Speaker 11: You know, I think at the highest level, I think
Speaker 11: you nailed it. It's like we ai has gone from
Speaker 11: being a technology product cycle to one of the largest
Speaker 11: capital formation cycles. Right on one side, you've got the
Speaker 11: pigs and shovels. You know, this is the compute, memory, optics, networking.
Speaker 11: You go down the list they are selling these products
Speaker 11: to to let's call them the minors.
Speaker 4: These are the labs.
Speaker 11: Google just raised eighty four billion dollars opening eye. It's
Speaker 11: a historicallye one hundred and twenty two billion anthropic of course,
Speaker 11: and you know, you look at the same week and
Speaker 11: video just announce an eighty billion dollar stock buyback program
Speaker 11: ske High next same thing, eight billion dollars of stock
Speaker 11: retired with more dividends coming.
Speaker 2: Those are like sort of contradictions in the function of
Speaker 2: the market.
Speaker 4: They're opposite.
Speaker 11: It's and that's the line that I wanted to highlight.
Speaker 11: On one side, you've got the folks who are helping
Speaker 11: you scale AI. These are receiving the capex, the others
Speaker 11: who are spending the capex.
Speaker 4: And I think that's the line that's.
Speaker 11: The biggest mental bottle I want to leave the folks with,
Speaker 11: which is, as you look at these businesses, are you
Speaker 11: on the side of receiving the capex, which would be
Speaker 11: the compute layer, of the energy layer, the memory layer
Speaker 11: of the networking layer, or are you on the side
Speaker 11: of spending. And I think that's the biggest divide in
Speaker 11: AI right now.
Speaker 3: But at the moment, we have seen rocket ship when
Speaker 3: it comes to AI infrastructure and those who've been receiving
Speaker 3: all the capital expenditure, and then people just so desirous
Speaker 3: to help fund those that are going to be out
Speaker 3: there and raising it. Whether it be open AI, whether
Speaker 3: it be SpaceX, whether it be anthropic, whether it be
Speaker 3: Google alphabet. Is there enough room for all of these
Speaker 3: large language model There's always been this argument that will
Speaker 3: be commoditized when you're sat thinking about being in Rock
Speaker 3: AI and SpaceX and at the same time Open AI
Speaker 3: and a topic should you be.
Speaker 11: You know, I think there's this narrative of companies doing
Speaker 11: a binary thing. Oh, you're the consumer AI company, or
Speaker 11: you're the enterprise AI company, you're the space AI company.
Speaker 11: I think I think the reality is a lot more multifaceted.
Speaker 4: Right, Let's take Opening I for example.
Speaker 11: I think the product, the company's mission is getting AI
Speaker 11: to the market holistically across consumer. You've got just under
Speaker 11: a billion users on chat GPT. On enterprise they've now
Speaker 11: got five million codex users. That was doing really well.
Speaker 11: And then a long series, you know, long tail of
Speaker 11: other bets with hardware, with robotics, with obviously the frontier
Speaker 11: enterprise offering SpaceX, which is you know, the two largest
Speaker 11: markets on the planet Space ANTII, and so I think
Speaker 11: the selling compute and now they're selling compute elon web services.
Speaker 2: Can actually as you about that, you know that there's
Speaker 2: so many directions we could go. But the space business
Speaker 2: of launch and Starlink two trillion in the TAM Get
Speaker 2: it Enterprise AI. You've kind of answered that, but stealthily
Speaker 2: in there they are.
Speaker 4: Becoming a hyperscaler.
Speaker 2: Right, if you think about the ethropic arrangement, they're almost
Speaker 2: hedging by saying in the interim, we're really good at
Speaker 2: building data center.
Speaker 11: Well, I think I think I would say it's a Switzerland, right,
Speaker 11: it's a Switzerland approach.
Speaker 4: You know, for a long time the first person to
Speaker 4: say that to me.
Speaker 11: So for the longest time we were holding re breath
Speaker 11: for hey, that you did this deal with Cursor, and
Speaker 11: the big question was, well, a lot of Cursor revenues
Speaker 11: come from the great anthropic models. Then they got entropic
Speaker 11: on the platform. Then obviously they're building their own models.
Speaker 11: And so I think of the XAI business as the
Speaker 11: Switzerland business. We're now selling compute, we will sell models,
Speaker 11: we'll have a coding product, we'll have other products down
Speaker 11: the line on consumer, et cetera. And again it's a
Speaker 11: holistic approach, and that's why the TAM is so large.
Speaker 3: Look, we love in the media and more broadly to
Speaker 3: be putting anthropic and open AI in.
Speaker 8: Some race against each other. But do you have as
Speaker 8: a private market investor.
Speaker 3: Any pause that maybe there isn't going to be the
Speaker 3: demand for this rule of public offerings, then in many
Speaker 3: ways it's going to be liquidity to your ultimism.
Speaker 11: Look, I think for the longest time, we've had a
Speaker 11: large part of the market waiting finding ways to get
Speaker 11: access to the biggest super cycle in AI right now,
Speaker 11: and I think that that moment has arrived.
Speaker 5: IPOs are cyclical, as we know.
Speaker 11: You know, the last big cycle was four or five
Speaker 11: years ago in twenty twenty one, and based on everything
Speaker 11: we know, there's a lot of demand for these products
Speaker 11: as they go out in terms of the demand for
Speaker 11: the capabilities. Look, I think in December last year we
Speaker 11: crossed a level of capability with coding models in Opus
Speaker 11: four five that has pushed it to the next frontier
Speaker 11: on consumer as everybody's already experienced and then yet to
Speaker 11: be proven as robotics manufacturing the hardware device that I
Speaker 11: open the Eye is working on, and others more to come.
Speaker 11: And I think more participation is better for us.
Speaker 2: You are, you're teaching at Stamford, and you've kindly invited
Speaker 2: me to come and check out a class, and I will,
Speaker 2: and one of the questions that you pose in a
Speaker 2: series of like guest speakers, right, you know everyone in
Speaker 2: industry and your fellow investors on the cap table. You
Speaker 2: asked them like, what's one idea or long one idea?
Speaker 2: You're sure I explain that, But why do you think
Speaker 2: that's a useful mechanism for understanding the world?
Speaker 5: Well, I like to hold the speakers to what they say.
Speaker 11: I'm going to ask them the question next year and
Speaker 11: have a scorecard of what happened to their long short picks.
Speaker 11: It's my favorite game to play with founders. I learn
Speaker 11: a lot as as founders pick their most optimistic idea,
Speaker 11: they're their most bearish idea.
Speaker 4: And I'll give you the theme.
Speaker 8: You know.
Speaker 11: The theme in this class was more than half of
Speaker 11: the speakers were long the let's call them the fix
Speaker 11: and shovels providers compute most common theme. Energy was the
Speaker 11: second most common theme that is ultimately the bottleneck at scale.
Speaker 11: The most common theme on the short side was was
Speaker 11: folks who are not innovating, incumbents were not innovating.
Speaker 5: You know, it's a fun time and.
Speaker 7: Cos are you short.
Speaker 8: Or what are you not looking at? In a startup space?
Speaker 3: As you're thinking about a wall of liquidity coming to altimiter,
Speaker 3: what would you not like to invest in very quickly.
Speaker 11: Well, I'm an optimist by trade, by profession, in my blood,
Speaker 11: so I'm very optimisticing on a lot of things going on.
Speaker 11: I think the simple mental model that I have is
Speaker 11: if there's a business that gets hurt by the scaling laws,
Speaker 11: it's one of the scaling laws. The scaling laws are
Speaker 11: if you provide more compute, more resources, more data, more algorithms,
Speaker 11: intelligence goes higher. If you're a business that is hurt
Speaker 11: by this empirical observation that intelligence is going to go up,
Speaker 11: that's a tough place to be because we believe intelligence
Speaker 11: is going to go up a lot of all.
Speaker 3: If we could speak to you for hours, it's so
Speaker 3: great to have you here at Bloomberg Tech. Above of alcohol, forces,
Speaker 3: of altimeter capital, fascinating conversation.
Speaker 4: With Welcome back to a special edition of Bloomberg Tech.
Speaker 2: We're live from the Bloomberg Tech event in San Francisco
Speaker 2: on Ed Ludlow.
Speaker 4: That's Caroline Hyde.
Speaker 7: I'm here.
Speaker 3: It's beautiful, but look what's not beautiful is a market
Speaker 3: a little bit today. Let's take a look at today's
Speaker 3: big number three hundred billion dollars head that is roughly
Speaker 3: how much market value we've just lost the Broadcast couch
Speaker 3: after the shares plunged today following the company's earned his
Speaker 3: release last night. Look, we were covering it live for
Speaker 3: us last night and it was a sharp drop. And
Speaker 3: it comes as the company's AI chip sales Beforecast just
Speaker 3: missed Wall streets really lofty expectations as while not raising
Speaker 3: long term AI revenue targets either that the stock fell
Speaker 3: by as much as you can see, well, four five
Speaker 3: forteen percent. We were down as much as fifteen percent
Speaker 3: the worst days of January twenty twenty five.
Speaker 8: But Hot Tan, he's speaking of this evently.
Speaker 2: Yeah, and you know he is going to try and
Speaker 2: give something longer term. But this was about incredibly high
Speaker 2: expectations of what's happening in the AI infrastructure build out cycle.
Speaker 4: Let's get to the software space.
Speaker 2: OCTOR delivered a very strong start for the year by
Speaker 2: beating first for expectations last week, but then raised its
Speaker 2: full year guidance basically across the board, joining us to
Speaker 2: discuss basically a platform shift that's happening, but also emerging
Speaker 2: threats from AI is octor CEO co founder Todd McKinnon.
Speaker 2: You know it was so interesting because you know, at
Speaker 2: the end of the day, numbers and numbers, and you
Speaker 2: had the confidence to raise on the outlook.
Speaker 4: There must be a reason why.
Speaker 2: You know, earlier in the show we're talking with Data
Speaker 2: Bricks and Ali Goodsey about how real.
Speaker 4: Is at the deployment of agents.
Speaker 12: You must know the answers to that act was founded
Speaker 12: in the shift of cloud computing and this new shift
Speaker 12: we're in, the shift to AI and AI agents is
Speaker 12: bigger than anything since the Internet, possibly bigger. And so
Speaker 12: what actor's benefiting from is all this change and all
Speaker 12: this technological evolution. It makes identity even more important than ever.
Speaker 12: Are these applicats, all these services, and then you layer
Speaker 12: on top of that a new product cycle for OCTA.
Speaker 12: The new product cycle is OCTA for AI agents. So
Speaker 12: we have a product that is the identity layer, the
Speaker 12: connectivity for all these AI agents in the enterprise. It's
Speaker 12: a powerful combination that's driving the business on all fronts.
Speaker 3: What makes your offering unique different from other peers? There
Speaker 3: are there many want to be the governance rules, the
Speaker 3: protection layer.
Speaker 7: For this port.
Speaker 12: I think it may surprise you. But it's the focus.
Speaker 12: We're focusing on the connections, the connections between AI agents
Speaker 12: and all the databases and data sources and applications they
Speaker 12: need to be most effective, and that connectivity that is
Speaker 12: very important to the functionality of the agents. But it's
Speaker 12: also something that's very risky from a security perspective. Yeah,
Speaker 12: the more you connect to your agents, the more risk
Speaker 12: of information leaking, the agent going rogue and you having
Speaker 12: to shut it down quickly. So that connectivity and we
Speaker 12: have a blueprint for the industry to how to connect
Speaker 12: those agents securely, and that's really resonating with customers.
Speaker 2: Earlier this week, somebody called Jensen Wang when on stage
Speaker 2: and in front of it camera and said that the
Speaker 2: narrative around software is complete nonsense, and he made the
Speaker 2: argument that for legacy software, agents will become the end users,
Speaker 2: and there are more agents than people in the world,
Speaker 2: and your stock, like everyone else is in your space,
Speaker 2: went absolutely bananas.
Speaker 4: Be honest with me, God, is.
Speaker 2: That helpful to have Gensen Wong Way in like that
Speaker 2: or would you just wish you didn't?
Speaker 12: Well, if you zoom out and look what's happening. I
Speaker 12: mentioned earlier the transition of the cloud fifteen years ago.
Speaker 12: The transition to AI is similar in that every layer
Speaker 12: of the stack is being reimagined and reinvented, from the
Speaker 12: hardware layer, to the infrastructure layer, to the platform layer,
Speaker 12: to the development tool layer, to the application layer. And
Speaker 12: so every vendor has an important priority to make sure
Speaker 12: they reinvent themselves with these agentic capabilities and these capabilities
Speaker 12: of automation. But this one is actually different. There's a
Speaker 12: new layer on top of all this. And this new layer,
Speaker 12: which is not hasn't happened in previous generations of technology change.
Speaker 12: There's a new layer, and that's the layer of digital work.
Speaker 12: It's a whole new category, a whole new opportunity that
Speaker 12: everyone's going after in addition to reinventing themselves in their
Speaker 12: own business. And that's I talked about this two pronged
Speaker 12: drivers of our business. We have the reinvention and the
Speaker 12: reprioritization of identity, and this new layer for automated digital work,
Speaker 12: which are octafer AI agents, is powering and playing right into.
Speaker 3: What does it mean for your own workforce, for your
Speaker 3: own human capital?
Speaker 8: Are you're needing as much of it?
Speaker 12: They have to be more effective and more productive, and
Speaker 12: the tools are there to do that, whether it's clog
Speaker 12: code or whether it's the latest marketing tool or support tool.
Speaker 12: They have to be more effective and they have to
Speaker 12: deliver value.
Speaker 8: Keeps the same amount of people working.
Speaker 4: Well.
Speaker 12: This is where I disagree with a lot of people.
Speaker 12: I think in five years Octa is going to have
Speaker 12: far more software engineers that we have now, and you
Speaker 12: want them to be reproducting, you want them to be
Speaker 12: generating tokens. And that's because it's a little bit of
Speaker 12: a trick answer, because the reason we'll have more is
Speaker 12: not because they won't be more efficient. It's because there's
Speaker 12: just so much more capability to build. There's so much
Speaker 12: demand for software, and there's so much power of the automation.
Speaker 7: We're very excited about this.
Speaker 2: So the Bloombo tech audience is in industry, it is sophisticated,
Speaker 2: but lots of people this is so abstract.
Speaker 4: Still.
Speaker 2: The thing that I always get frustrated with with an
Speaker 2: agent is that I just want it to act. So
Speaker 2: if you take this as a random case study, but
Speaker 2: like my flight gets canceled, I have to phone a
Speaker 2: human still, even within Bloomberg, try and.
Speaker 4: Get that resolved.
Speaker 2: But there is a world that you're pitching where they
Speaker 2: have access to my credit card, the flight information.
Speaker 4: It just happened.
Speaker 12: These are the connections I'm talking about the connections of
Speaker 12: the data that has to be secure.
Speaker 2: What is the barrier in the world right now? You know,
Speaker 2: Corporate America, companies around the planet, that is preventing this
Speaker 2: just happening.
Speaker 12: The barrier is people thinking about models, and we herald
Speaker 12: model advancements. The reality is is that the models are
Speaker 12: out of capability now, far surpassed in our ability to
Speaker 12: simply connect the systems together and get practical argentic applications built.
Speaker 12: But that's great because there's a lot of smart people
Speaker 12: in the world working on connecting them, and we're focused
Speaker 12: on making sure they're connected securely.
Speaker 4: And that's why the future is very.
Speaker 2: That's what I meant though, like are we worried about
Speaker 2: how secure that potential transaction is or not?
Speaker 5: We have to be always worried about security.
Speaker 12: You're connecting sensitive data and automating it in new ways
Speaker 12: and there's always risk in that, and that's why I
Speaker 12: think our solutions are resonating so much, just as practical
Speaker 12: focus on we want things to be more automated. We
Speaker 12: want these agents to have more capability. They need more data.
Speaker 12: How do we pragmatically do that in a secure and
Speaker 12: manageable way. And that's what oktafer Ai agents does.
Speaker 8: And so this talk of SaaS pocalypse, I.
Speaker 12: Think it's completely over bloom. It's completely over bloom. I
Speaker 12: think there will be SaaS companies that don't embed these
Speaker 12: capabilities in their offerings. Just like in the revolution and
Speaker 12: the move to the cloud, there were companies that were
Speaker 12: left behind and became legacy vendors and Resolve bought up
Speaker 12: by Oracle. That'll happen too, but there all also be
Speaker 12: mini vendors that make the transition and thrive in the future.
Speaker 3: And that's why you're proving it up to CEO co
Speaker 3: found and Tom McKinnon. It's great to have it here
Speaker 3: at Bloomberg Tech. The live event in San Francisco, and
Speaker 3: coming up we have the personification of the San Francisco economy.
Speaker 3: We've got the San Francisco for Bed president Mary Daily
Speaker 3: joining us live. We're going to discuss AI's economic impact
Speaker 3: on the people, on the productivity, the risks that are
Speaker 3: getting perhaps overlooked god Rails.
Speaker 8: Maybe needed this is BLUEBG Tech.
Speaker 3: We are live from the Bloomberg Tech event in the
Speaker 3: heart of San Francisco, and look, the debate is rich
Speaker 3: around AI's economic disruption.
Speaker 8: Is it growing more intense?
Speaker 3: Some see the technology that can unlock enormous gains and
Speaker 3: productivity and growth, but others that they warn of disruption,
Speaker 3: of unintended consequences. And we want to try and understand
Speaker 3: the sort of messy middle of all of this with
Speaker 3: Mary Daily, President of Federal Reserve.
Speaker 8: Bank of San Francisco.
Speaker 3: Mary Daily, extraordinary the data that you now have to
Speaker 3: lean upon, trying to understand what's fact, what's fiction, what's utopia,
Speaker 3: what sensation? Who do you go to field field dates
Speaker 3: on whether productivity is working.
Speaker 13: I thought of the businesses who were using the technology,
Speaker 13: because you can always encounter enthusiasts or doom sayers, but
Speaker 13: it's really the people in the middle, as you said,
Speaker 13: who are using that technology thinking about it, and I've
Speaker 13: seen tremendous interest in it it last year and now
Speaker 13: I'm seeing tremendous investment in it, thinking about how do
Speaker 13: they train their workforces to be AI ready, how do
Speaker 13: they think about what AI can do, not just in
Speaker 13: the back office but.
Speaker 7: In the front of a house of operations.
Speaker 13: And we're seeing this in small businesses, medium and large,
Speaker 13: in global companies and more regional ones, and importantly in
Speaker 13: everything from agriculture to machining and building things to services.
Speaker 13: And I think that's really the place we haven't seen
Speaker 13: widespread productivity gains yet. The ROI is still to be developed,
Speaker 13: but I'm definitely seeing the enthusiasm and it's picked up
Speaker 13: tremendously in the last year.
Speaker 2: We haven't seen the productivity gains yet. You know, you're
Speaker 2: being very clear on that. As you remember, I asked
Speaker 2: you over and over again for an hour, please show
Speaker 2: me the productivity gains. But in the economic data, whichever
Speaker 2: set of data you want to look at, do you
Speaker 2: see an impact from AI negative or positive?
Speaker 7: It's really hard to take.
Speaker 13: We have had productivity growth that's been outside of the
Speaker 13: historical norm, and I think that's a positive for the
Speaker 13: US economy.
Speaker 7: Everyone wants to say that's AI.
Speaker 13: What I think of it is as sure, it's possible
Speaker 13: that businesses are looking for cost savings and they hire
Speaker 13: fewer workers than they do just as much because they're
Speaker 13: using an LA assistant to help. But we just haven't
Speaker 13: heard from businesses that they're seeing transformative ongoing productivity gains
Speaker 13: yet and they want to always underscore yet. And so
Speaker 13: then I said, well, what's the timeframe and they said
Speaker 13: next year, year after. Because what we know is it
Speaker 13: isn't just about getting a model and using it for
Speaker 13: things or an agent. It's about transforming your business processes
Speaker 13: so that you really take advantage of things we don't
Speaker 13: even think about today, what can be done differently that
Speaker 13: we'll transform the economy. So you can definitely find a
Speaker 13: single business or sectors who are using it and seeing
Speaker 13: the gains, but we haven't seen that across the economy
Speaker 13: going forward.
Speaker 7: But I'm pretty bullish. I see the possibilities.
Speaker 13: And I'm hearing more and more that people are seeing
Speaker 13: early rewards and really recognizing that next year is the
Speaker 13: litmus test.
Speaker 3: But this is an interesting kind of phrase today, putting
Speaker 3: aside the slight dip in the market, the exuberance that
Speaker 3: we have seen in financial markets to want to back
Speaker 3: these companies, and we're about to get more public companies coming,
Speaker 3: more liquidity.
Speaker 7: More money.
Speaker 3: Is that in and of itself a financial stability issue.
Speaker 8: You worried about the market's rioting.
Speaker 11: So high.
Speaker 13: You remember, you know who's doing most of this investment,
Speaker 13: the mag seven who's really there. This is actually something
Speaker 13: they can do and fund, and their enthusiasm is real.
Speaker 13: They see what's possible. But I don't think that we
Speaker 13: should think, oh, there's financial stability concerns just because the
Speaker 13: market's gone up. It could go up or down as
Speaker 13: it has in the past, but a financial stability issue
Speaker 13: would mean it's spread to the banks, it's spread to
Speaker 13: consumers or businesses. Right now, I'm not seeing evidence of that.
Speaker 13: We keep our eye on it for absolute sure, But
Speaker 13: what I am seeing is that companies other than the
Speaker 13: technology enthusiasts, companies outside of technology, are using AI to
Speaker 13: think about how to do their business better in real ways.
Speaker 13: I mean, I was just meeting with some machine machines
Speaker 13: for a living, that's what they do, and they're thinking about,
Speaker 13: how do I scan in fifty years of plans of
Speaker 13: these machines I've built for companies and then use those
Speaker 13: plans in a model to generate innovative new ideas of
Speaker 13: things I can sell that will be faster, better, cheaper
Speaker 13: than things I've sold before. We toured a robotics company
Speaker 13: that builds things that help manufacturers do better in terms
Speaker 13: of shipping and distribution. These are real things that do
Speaker 13: have a capacity to change the economy. So that's why
Speaker 13: that's the underlying part of my bull ish It has
Speaker 13: less to do about the investments that tech companies are
Speaker 13: making and more about the investments that everyday regular companies
Speaker 13: that make things and provide services.
Speaker 7: The things they're.
Speaker 2: Doing president daily inflation is still the biggest risk.
Speaker 4: And you know those are not my words.
Speaker 2: We heard it, you know, all week long at the
Speaker 2: Bloomberg Credit Forum, for example. One of the things that
Speaker 2: you and I have discussed in the past is is
Speaker 2: the massive CAPEX commitment build out of data center in
Speaker 2: conjunction with a bottleneck in some core areas like memory
Speaker 2: inflationary or is it disinflationary? You know, that's the thesis
Speaker 2: that like a utility of pgene would argue disinflationary because
Speaker 2: the big guys are buying and aggregate. I still don't
Speaker 2: understand where we are with that.
Speaker 13: It's a timing issue in my judgment that you know,
Speaker 13: in the beginning of course, when companies want to invest
Speaker 13: in big construction projects a lot of electro electricity demand,
Speaker 13: then the companies that are providing those things or areas
Speaker 13: that are providing those things are going to see competition
Speaker 13: for the limited amount of services they have. But what
Speaker 13: they're building creates the infrastructure. The data centers create the infrastructure.
Speaker 7: Or if the big.
Speaker 13: Guys come in as you just said and help with
Speaker 13: electrical plants that help with electricity generation, that eventually can
Speaker 13: help with the prices of those things.
Speaker 4: Don't hear it now, but you just have to think.
Speaker 7: About the timing.
Speaker 13: And one of the things is really important in policy
Speaker 13: making is that we not assume we know. We actually
Speaker 13: look for the evidence of what are we seeing in
Speaker 13: prices today, what are we seeing in what is the
Speaker 13: forecast of prices tomorrow? And then how do we think
Speaker 13: about policy. So right now I'm focused on you know,
Speaker 13: other energy prices, oil prices, and food prices are driving
Speaker 13: up inflation. What we do know that down the road
Speaker 13: these things could maybe compete for services and costs and
Speaker 13: raise costs, but we haven't seen real evidence that that's
Speaker 13: the limiting factor. The limiting factor seems it's hard to
Speaker 13: get generators, it's hard to get the infrastructure equipment you need,
Speaker 13: and so you see the big tech companies thinking about
Speaker 13: solutions they can provide for themselves.
Speaker 3: The infrationary data must be fascinating here in San Francisco.
Speaker 3: When I think about all these companies potentially going competent, well,
Speaker 3: that means to the employee base, well, that means that
Speaker 3: your health price and the ability to be.
Speaker 8: Able to buy yet more readA state here. What it
Speaker 8: means for the cost of labor as well. Is there an.
Speaker 13: Infrasery pressure that you're seeing in San Francisis I've lived through.
Speaker 13: So I moved to San Francisco in nineteen ninety six
Speaker 13: and then that we have the dot com and I
Speaker 13: know what it feels like to not be able to
Speaker 13: rent a place that's affordable because the people who are
Speaker 13: making milliony more orders of magnitude. And I was in
Speaker 13: a position where that's manageable. But that's what's happening, is
Speaker 13: people feel like they're getting crowded out because other things
Speaker 13: are happening. But that's more about the supply of housing
Speaker 13: than it is about the demand for housing. We want
Speaker 13: people to come and invest in this community. We want
Speaker 13: the city to thrive. We want regional activity and employment
Speaker 13: to grow. But as you said, you know, the more
Speaker 13: interest people have in living in a place. If you
Speaker 13: have limited supply of housing, then you're going to have
Speaker 13: a run up. So those are the things that not
Speaker 13: the FED, but other policymakers, other federal policies makers, and
Speaker 13: local policy makers like the mayor are working on. But
Speaker 13: it looks very you know, you'd see the elements of
Speaker 13: nineteen ninety six already here, where there's productivity, growth, there's enthusiasm,
Speaker 13: et cetera.
Speaker 8: But the data bubble, is there a risk that we're
Speaker 8: in not saying, you know, the.
Speaker 13: Dot com was very different than the AI boom, and
Speaker 13: so I just want to you know, there's a lot
Speaker 13: there that's already being put into businesses and it's very pervasive.
Speaker 7: It's not just the dot com.
Speaker 13: So I don't jump to the conclusion that if it
Speaker 13: has similarities to the nineties, it's going to be the.
Speaker 2: Nine Well, if I may presented, you went out and
Speaker 2: did some of the most important work in that era
Speaker 2: of how the advent of the internet would change the economy. Look,
Speaker 2: so you've kind of established where we sit right now.
Speaker 2: Inflation continues to rise, how like or unlikely would that
Speaker 2: make a rate cut in twenty twenty six? How do
Speaker 2: you tie the two together from this juncture onward.
Speaker 13: You know, I think one of the questions I get
Speaker 13: asked regularly is what's the path.
Speaker 7: For the rates going forward?
Speaker 13: Yeah, And the answer I give, because this is how
Speaker 13: I really think we have to think about it, is
Speaker 13: we don't know how the economy is going to play out.
Speaker 13: We have, as we've been talking about, this tremendous possibility
Speaker 13: with Ai, but we have the same time the war
Speaker 13: in Iran, that is with an uncertain end, which has
Speaker 13: pushed oil prices up and fertilizer prices which have filtered
Speaker 13: into food prices. And right now those are fairly contained.
Speaker 13: And if you look at the futures market for oil,
Speaker 13: it's eighty dollars a barrel by the end of the year.
Speaker 13: But you know, we have to think about that, and
Speaker 13: so right now policy is in a good place. We
Speaker 13: are prepared to respond either way whatever the economy brings.
Speaker 7: But I think give a.
Speaker 13: More forward guidance about what's possible could be misguiding in
Speaker 13: the end, because we just have to wait for the
Speaker 13: economy revolve. Everybody wants to resolve the uncertainty today, but
Speaker 13: I think that's a mistake because it will close off
Speaker 13: our mind about what we really have to look at
Speaker 13: the inflation risk possibility, but also the possibility of the
Speaker 13: war end. Oil prices come back down and we're back
Speaker 13: to the underlying dynamics which some of the positives of
Speaker 13: AI we've been talking about.
Speaker 3: Can I ask you about the labor market as well,
Speaker 3: because you've tried to bring this transparency of how you're
Speaker 3: thinking about things with your blog, for example, and one
Speaker 3: of the really interesting ones that I was reading and
Speaker 3: capture my attention was the idea that we've got zero
Speaker 3: labor growth now immigrations changed the way in which demographics change.
Speaker 3: Are you feeling like we've seen some improvement, some resilience
Speaker 3: in the labor.
Speaker 8: Market again, and will that hold?
Speaker 4: Has it firmed?
Speaker 7: Yeah, you know, I.
Speaker 13: Think that's too early to stay firmed. I think we're
Speaker 13: you know, there's always statistical air, so you can bounce
Speaker 13: around from month to month. But if you you know,
Speaker 13: I was one of the people who policymakers who were
Speaker 13: a little worried about the labor market at the end
Speaker 13: of last year were very supportive of the cuts we
Speaker 13: took to stabilize conditions there.
Speaker 7: So relative to that point.
Speaker 13: I think this is we've really stabilized, and I'm starting
Speaker 13: to see businesses feel a little more cautiously optimistic, which
Speaker 13: we'll feed through to hiring. But they're not being you know,
Speaker 13: they're not just running out.
Speaker 7: To hire people. They are right, I can get an agent.
Speaker 13: They're interrogating how much AI can do for them before
Speaker 13: they hire. And you know, regularly we talk to our
Speaker 13: businesses and they say, we don't want to hire a
Speaker 13: bunch of people. Find out AI can do certain things,
Speaker 13: and we did a different set of skills, so we
Speaker 13: want to wait. We want to be patient on our
Speaker 13: hiring and make sure we're not over hiring, because you know,
Speaker 13: if you ever go through a period of time where
Speaker 13: a business has to lay workers off, it's a painful
Speaker 13: experience for the workers and for them. And so they
Speaker 13: just don't want to get overly confident only to find
Speaker 13: out they have to make adjustments.
Speaker 7: So that caution will be with us for a bit.
Speaker 2: We are live on Bloomberg Television and Bloomberg Radio. We're
Speaker 2: in San Francisco and we're at the Bloomberg Tech event
Speaker 2: and we're speaking with San Francisco that Marry Daily reset
Speaker 2: a little bit. But if I may it's the first
Speaker 2: opportunity we've had to ask you. Have you spoken to
Speaker 2: Chairman wa Wash about how he sees the FED evolving
Speaker 2: about changes to the institution and if you may fold
Speaker 2: in the context of your district San Francisco Fed. Yes,
Speaker 2: much more than that and your role going forward.
Speaker 7: Sure, absolutely so.
Speaker 13: You know, I think what we really want when any
Speaker 13: new chair comes in, and what we want from all
Speaker 13: of our leaders of FEDERALI serve banks and all of
Speaker 13: our governors, is that you're thinking constantly about how can
Speaker 13: the FED be better? How can it better shave the
Speaker 13: American people? How can we do our work more efficiently,
Speaker 13: more effectively, and more resiliently. You know, ultimately everything we
Speaker 13: talk about is put between two bookends. We are fiduciary
Speaker 13: stewarts of public trust, which means we better have services
Speaker 13: that people can depend on and we better work hard
Speaker 13: to achieve our goals. And we're fiduciary stewards of public funds,
Speaker 13: which is we are very careful.
Speaker 7: About how we spend taxpayer dollars.
Speaker 13: So with those two things in mind, you know, I
Speaker 13: mentioned I joined the FED back in the nineties. So
Speaker 13: I joined the FED in the nineties and we had
Speaker 13: check processing. Remember checks, we had check processing.
Speaker 8: I stopped the right legs.
Speaker 7: Everywhere, everywhere in the everywhere.
Speaker 13: We had a location, we had people who process checks.
Speaker 13: But then check demand started to fall, and so we
Speaker 13: consolidated those activities into a few locations. And that level
Speaker 13: of modernizing, constantly thinking about how can you do better?
Speaker 7: Is what I see now.
Speaker 4: So what is the chair's equivalent of that?
Speaker 7: Well, just joined.
Speaker 13: So I'm going to give him the right time he
Speaker 13: has to announce that. He's talked about making sure he's
Speaker 13: holding onto that tradition, and he comes in with a
Speaker 13: lot of ideas. But you know what I've heard him
Speaker 13: say again and again, which I really appreciate because all
Speaker 13: he's the fifth chair I've worked with.
Speaker 7: All of the chairs I've worked with have the same
Speaker 7: basic compass.
Speaker 13: It is to do our best work for the American
Speaker 13: people and work with all the individuals who are earnestly
Speaker 13: doing their work in the FED to do it well.
Speaker 3: And I see that in chair worsh that earnest work
Speaker 3: within the FED. How much of that is being multignized
Speaker 3: to use adult AI.
Speaker 8: How hard or easy is it at the moment when
Speaker 8: you're such a regulated the institution in and of yourself.
Speaker 13: Well, we're careful like all regulated institutions, and importantly like
Speaker 13: all businesses. Businesses, and when I talk to businesses, the
Speaker 13: last thing they want to do is a huge risk
Speaker 13: that destroy their shareholders. They're the value of their company.
Speaker 13: The same is true for us. Good fiduciary stewarts of
Speaker 13: public trust and good fiduciary stuarts of public funds, which
Speaker 13: means we're always driving to adopt new technology to do
Speaker 13: our work more efficiently, but we recognize we have to
Speaker 13: do that safely. You know, people want to know they
Speaker 13: can get their money when they need it. They want
Speaker 13: to know that the banks are well supervised. They want
Speaker 13: to know that Montarry policy is not made by machines.
Speaker 7: It's made by people making judgments not.
Speaker 13: Only about models and rules, but also about the lived
Speaker 13: experiences of people across our country.
Speaker 2: Very quickly, before the show ends, what are you seeing
Speaker 2: in credit? That's a big story for us in how.
Speaker 4: Data centers are financed. For some it's very worrying.
Speaker 13: Well, you know, we're watching that carefully. I watched that carefully.
Speaker 13: What we do see is that there's a lot of
Speaker 13: there's those companies investing a lot of their own resources
Speaker 13: in those So it's something to keep our eye on.
Speaker 13: But at this point, you know, again, if you stack
Speaker 13: rank the things that are worrying today, I'd say getting
Speaker 13: inflation back to target, getting Americans the relief they deserve
Speaker 13: that we've been working on for quite a while.
Speaker 7: That's my number one priority.
Speaker 4: I'm Francisco President, Mary Daddy.
Speaker 2: You've been very generous of your time, and we always
Speaker 2: cover such a broad spectrum of topics. Really grateful to
Speaker 2: have you here with us in San Francisco at the
Speaker 2: bloombo Tech event.
Speaker 3: Yeah, what an event it has been, What an event
Speaker 3: it continues to do.
Speaker 8: We're just getting started, and I know that does there's
Speaker 8: addition to Bloomberg.
Speaker 4: Tech for the TV show. Yeah, but you've.
Speaker 8: Got to stay tuned.
Speaker 3: The rest of Bloomberg Tech event today has some phenomenal conversation.
Speaker 4: Just coming up.
Speaker 3: I'm lucky enough to be speaking again with the San
Speaker 3: Francisco Fed Chair of course, Mary Day.
Speaker 8: But you look for the lineup that what we've got
Speaker 8: coming up.
Speaker 2: Yeah, and I'm going to be speaking to Trey Stevens,
Speaker 2: partner at Founders Fun, chairman of Andreil but Founder's Fund
Speaker 2: is a high single digit percent stakeholder of SpaceX. Don't
Speaker 2: forget SpaceX's IPO pricing June eleven.
Speaker 4: Yeah, that's a big deal.
Speaker 2: Recap the show, a lot of really great conversations on
Speaker 2: the podcast. You guys know where it's at online, Spotify, iHeart,
Speaker 2: and Apple and all the Bloomberg platforms as well.
Speaker 4: Stay tuned. This is Bloomberg Tech.