Speaker 1: Bloomberg Audio Studios, podcasts, radio news. This is Bloomberg Intelligence
Speaker 1: with Alex Steel and Paul Sweeney.
Speaker 2: The real app performance has been in US corporate high yield.
Speaker 3: Are the companies lean enough? Have they trimmed all the fats?
Speaker 2: The semiconductor business is a really cyclical.
Speaker 1: Business, breaking market headlines and corporate news from across the globe.
Speaker 3: Do investors like the M and A that we've seen?
Speaker 2: These are two big time blue chip companies.
Speaker 3: Window between the peak and cunt changing super fast.
Speaker 1: Bloomberg Intelligence with Alex Steel and Paul Sweeney on Bloomberg Radio.
Speaker 2: On Today's Boomberg Intelligence Show, we dig inside the big
Speaker 2: business stories impacting Wall Street and the global markets.
Speaker 3: Each and every week we provide in depth research and
Speaker 3: data on some of the two thousand companies and one
Speaker 3: hundred and thirty industries our analysts cover worldwide.
Speaker 2: Today, we'll look at a big deal in the M
Speaker 2: and A space that will create a mortgage behemoth.
Speaker 3: Plus we're going to discuss the rising costs of food
Speaker 3: and wow that's effecting the consumer.
Speaker 2: But first we begin with research. Bloomberg Intelligence recently put
Speaker 2: out on ten companies to watch for in the second
Speaker 2: quarter of twenty twenty five and for more on this.
Speaker 3: Liz Paul and I were joined by Tim Craig, head
Speaker 3: Bloomberg Intelligence Global Chief Content Officer.
Speaker 2: We first asked him to give us a broad scope
Speaker 2: of the company he's looking at.
Speaker 4: So just as a reminder, these are all based off
Speaker 4: of focus ideas, which for us in Bloomberg Intelligence are
Speaker 4: high conviction out of consensus views where we see catalysts
Speaker 4: ahead that can actually change the market's mindset around these companies.
Speaker 4: So you've talked about the weight on consumer sentiment and
Speaker 4: things along those lines. Well, Dollar Rama, which is a
Speaker 4: dollar store up in Canada has yeah, exactly, They're going
Speaker 4: to face slower wage growth, higher inflation. We've not seen
Speaker 4: estimate cuts yet for Dollar Rama, like we've seen a
Speaker 4: dollar Tree and dollar stores and whatnot. We think that's coming.
Speaker 4: Another one that is interesting if you want to throw
Speaker 4: on as well the whole tariff concept is PDD. You
Speaker 4: might not have heard of this, but this is one
Speaker 4: of the big Chinese companies that trade tech companies that
Speaker 4: trades in New York. They own Timu, which is that
Speaker 4: ultra low priced e commerce platform in the States. There's
Speaker 4: their bigger platform is one in China, they're going to
Speaker 4: have constraints on what they can bring in at the
Speaker 4: right price, and they're also investing pretty heavily outside the
Speaker 4: US to grow their non US platform beyond China. So
Speaker 4: again we think that there's estimate cuts there to come.
Speaker 2: Hey, Tim, One of the more looking at this list,
Speaker 2: one of the more controversial calls, I think is Tesla.
Speaker 2: Steve Manner, the analyst for Bloomberg Intelligence covering the auto business,
Speaker 2: he's pretty positive on Tesla here despite the stock price
Speaker 2: in there. I guess the concern about Elon Muskin is focus.
Speaker 4: Yeah, you know, you could throw this in with tariffs,
Speaker 4: with policy, et cetera, and clearly it's taken a shellacking
Speaker 4: from a stock price perspective. We see two things going
Speaker 4: on here. Number One, there's been a lot of talk
Speaker 4: about how their sales have been disappointing as of Leyden.
Speaker 4: Is that because of politics, We think, frankly it's because
Speaker 4: of the model transition with the new Model Y coming out,
Speaker 4: orders even in China have been good, and we would
Speaker 4: expect to see sales to pick up as we proceed
Speaker 4: through the second quarter and on ind to midyear. You've
Speaker 4: also got a really underappreciated battery storage business that is
Speaker 4: also starting to ramp up. So we see two catalysts
Speaker 4: here to play out that people aren't focused on because
Speaker 4: of all the other noise.
Speaker 3: And here's one for Paul here Cracker Barrel, Oh yeah,
Speaker 3: is on your list again. I've never been.
Speaker 2: Now, Tim, he lives in London.
Speaker 4: You go to New.
Speaker 3: York City, man like, I don't know what I'm going
Speaker 3: to see.
Speaker 2: Tim grew up in southwest Virginia. He knows.
Speaker 3: I mean I'll eat it. If you buy it and
Speaker 3: eat it, I mean give it to me, I'll eat it.
Speaker 3: Let's put it that way, all right, talk to us about.
Speaker 4: Really good I've crack. Cracker Barrel falls into the restructuring
Speaker 4: reorganization bucket. And there's another one on the list as
Speaker 4: well that actually may be good for you, Alex. I'll
Speaker 4: come back to But cracker Barrel three years of estimate cuts.
Speaker 4: There's next to no buys on this on this stock.
Speaker 4: And from an underlying business perspective, they've made some wholesale revamps,
Speaker 4: the menu, their approach to service. Uh, they're remodeling stores,
Speaker 4: and we think that there's an inflection to come from
Speaker 4: the standpoint of earnings trends. Notwithstanding the economy, this one's
Speaker 4: already been beaten down, and we think that there's an
Speaker 4: up decided to come Carrying's the other one carrying? Yeah?
Speaker 4: So again three years of estimate cuts, you think who
Speaker 4: is carrying? Well, their biggest label is Gucci. There you go,
Speaker 4: Alex and if.
Speaker 3: I only discount him, let's be clear.
Speaker 4: Yeah, So new CEO at Gucci, a new head designer
Speaker 4: at Gucci. We think there's a rejuvenation at hand, and
Speaker 4: it's not in the estimates.
Speaker 2: So again, Tim, let's just step back a little bit.
Speaker 2: European markets really performing well, certainly relative to the US market.
Speaker 2: What are your clients saying here?
Speaker 4: So I think there are a couple of things coalescing. Three.
Speaker 4: In fact, you take tariffs and all the concern that's
Speaker 4: going on. You take deep seek and that raising the
Speaker 4: specter of g Is there a different dynamic in the
Speaker 4: world of tech that's been driving US markets and US exceptionalism.
Speaker 4: And then you have a big European defense initiative and
Speaker 4: imperative with Germany coming out with what people around here
Speaker 4: are calling the Bazooka. And you add these together, there's
Speaker 4: a growth idea developing in Europe. There's concern about what's
Speaker 4: going on in the US. And if you look at
Speaker 4: our economists, they see as much of a hit on
Speaker 4: US growth and inflation as they see it anywhere outside
Speaker 4: of Mexico and Canada. So you know, all of that
Speaker 4: weighs on the US and Europe is an alternative, and
Speaker 4: obviously we've talked a lot about how it's valued relative
Speaker 4: to the States. I think that creates a money flow issue,
Speaker 4: a money flow opportunity, just like it does for China.
Speaker 5: All right.
Speaker 3: Thanks to Tim Craig had Bloomberg Intelligence, a global Chief
Speaker 3: Content Officer, Each week we look at research from Bloomberg
Speaker 3: n EF previously known as New Energy Finance. They're the
Speaker 3: team at Bloomberg that tracks and analyzes the energy transition
Speaker 3: from commodities to power, transport, industries, building, and ag sectors.
Speaker 3: This week we looked at the growing enthusiasm for nuclear
Speaker 3: power for more.
Speaker 2: Guest hosts Isabelle Lee and I were joined by Chris Gaddomski,
Speaker 2: Bloomberg and EF lead nuclear analysts. We first to ask
Speaker 2: Chris what his thoughts are on nuclear power as a
Speaker 2: source to fuel AI expansion.
Speaker 6: It's a great technology for supplying clean, carbon free twenty
Speaker 6: four to seven base load power. However, there's a mismatch
Speaker 6: between the demand for the electricity. Data centers say they
Speaker 6: would like to have the electricity right away tomorrow, if
Speaker 6: not sooner, and any new nuclear capacity in the US
Speaker 6: is not going to come online until after twenty thirty.
Speaker 6: I mean you may have one or two outliers come
Speaker 6: on beforehand, but before you have a reliable demonstration of
Speaker 6: the technology. Because these are all new technologies being built,
Speaker 6: we'll be looking for after twenty thirty, So possibly we
Speaker 6: could miss the first wave of advanced reactor contribution to
Speaker 6: the AI developments.
Speaker 5: Why is nuclear construction in the West barely budgeting, whereas,
Speaker 5: in for instance, Asia Pacific region it's booming.
Speaker 6: There's two big reasons for that. One, the price at
Speaker 6: which the Chinese, for example, can build a nuclear power
Speaker 6: plant is much lower than we can in the US,
Speaker 6: and that's the function the fact that China right now
Speaker 6: is building twenty eight nuclear power plants. We have built
Speaker 6: two in the last ten or fifteen years, and so
Speaker 6: they will build six nuclear power plants at the same site,
Speaker 6: and the construction team moves from one reactor to the
Speaker 6: next reactor to the next reactive reactor h reactor subsequently
Speaker 6: costs less than the first. So to China to build
Speaker 6: reactors for maybe one fifth to one quarter of what
Speaker 6: the US can build, it makes sense for them to
Speaker 6: build a lot of nuclear power plants. We've lost the
Speaker 6: x tease and the desire to build a lot of
Speaker 6: large nuclear power plants. To cite some advantages and significant
Speaker 6: benefits to the technology, talk to.
Speaker 2: Us about small modular reactors. Is that a solution.
Speaker 6: Yeah, it is a solution because the not dynamic has
Speaker 6: has has changed in the past. We've seen let's build
Speaker 6: large reactors to get economies of scale in size. The
Speaker 6: conversations talk, well, let's build a lot of small reactors
Speaker 6: and get down the learning curve as quickly as we can.
Speaker 6: So there are only two small modi reactors operating modern
Speaker 6: ones operating in the world, one in China, one in Russia.
Speaker 6: China is building another one. Russia is planning to build
Speaker 6: another one, but they haven't yet broken ground on that.
Speaker 6: So it's a technology that presents a lot less risk
Speaker 6: to the utility or the hyperscaler who is buying it.
Speaker 6: There's no big deployment risk. There is technology risk because
Speaker 6: these are all first of a kind, and so with
Speaker 6: the first of a kind project, especially in the nucle
Speaker 6: power business, there's a lot of uncertainty with regards to
Speaker 6: schedule and cost, and so people are thinking about this.
Speaker 6: A lot of the utilities of are making plans to
Speaker 6: go forward. The US and Canada the UK are leading
Speaker 6: the effort, and so it's going to take some time
Speaker 6: before those first reactors, small, major reactors, and advanced reactors
Speaker 6: across the finish line.
Speaker 5: We know that new nuclear projects are coming online slower,
Speaker 5: But do you think this administration will change that or
Speaker 5: is it going to be status quo.
Speaker 6: The Trump administration in its first time first term was
Speaker 6: very very pro developing uranium the equivalent of drill baby
Speaker 6: drill from the uranium sector, and to a certain extent
Speaker 6: that uranium has bounced back up. The current administration now
Speaker 6: is favorable towards nuclear. Chris Wright, the Secretary of Energy,
Speaker 6: has a pedigree from Berkeley and MIT to the leading
Speaker 6: academic institutions regarding nuclear, and I think that they are
Speaker 6: very pro nuclear. However, the big question is how much
Speaker 6: government funding will be used to support nuclear reactor construction.
Speaker 6: That's something that we're still working out and trying to
Speaker 6: understand Chris.
Speaker 2: I finished the first season of the TV show Landman,
Speaker 2: so I now consider myself an expert in the oil
Speaker 2: and gas business, and I think my takeaway is, you know,
Speaker 2: listening to energy providers and energy users, we're going to
Speaker 2: need everything. We're going to need fossil fuels, We're gonna
Speaker 2: need the wind, We're going to need solar, all that
Speaker 2: kind of stuff. Maybe nuclear. How do you think about that?
Speaker 6: Yeah, my take is that we certainly do need nuclear.
Speaker 6: If you look on a geopolitical basis, you have China
Speaker 6: building twenty eight reactors, large reactors. Also, as soon as
Speaker 6: it passes are post twenty third, they'll have more nuclear
Speaker 6: power plants operating than we do. The Russians are very,
Speaker 6: very aggressively building nuclear power plants not only in Russia
Speaker 6: but in Middle East and establishing one hundred year relations
Speaker 6: with that, and I think that has caused a lot
Speaker 6: of concern for the US government saying, hey, listen, we
Speaker 6: need to sort of offer a viable alternative option for
Speaker 6: new nuclear in the years ahead. And I think it's
Speaker 6: a very very solid ambition. Biden dedministration called for two
Speaker 6: hundred gigawats of extra nuclear capacity. That's tripling what we
Speaker 6: have right now, and so there is a tremendous need
Speaker 6: for it, and I think there has a place. It's
Speaker 6: not a solution for all the problems, but it works
Speaker 6: very well for many types of applications.
Speaker 2: Our thanks to Chris Gadomski, Bloomberg and EF lead nuclear analyst.
Speaker 3: All right, coming up, we're going to break down the
Speaker 3: future of AI empowering data centers.
Speaker 2: You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in
Speaker 2: depth research and data on two thousand companies and one
Speaker 2: hundred and thirty industries. You can access Bloomberg Intelligence via
Speaker 2: bi go in the terminal Paul Sweeney and.
Speaker 3: I'm Alex Steele, and this is Bloomberg.
Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live
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Speaker 3: We move now to the M and A space.
Speaker 2: This week we heard that the online mortgage provider Rocket
Speaker 2: is acquiring mister Cooper Group, the country's largest mortgage servicer it's.
Speaker 3: An all stock deal valued about nine point four billion dollars,
Speaker 3: and this will create a mortgage behemoth that handles one
Speaker 3: in every six mortgages in the US.
Speaker 2: For more, guest host Isabelle Lee and I were joined
Speaker 2: by Page Smith, Bloomberg News consumer finance reporter. We first
Speaker 2: asked Page to explain the latest deal and what mister
Speaker 2: Cooper is.
Speaker 7: Mister Cooper is more is best known, I would say,
Speaker 7: in the mortgage servicing side of things, So it's sort
Speaker 7: of after the fact, you've got your mortgage, but who
Speaker 7: were you actually interacting with, you know, gears down the line,
Speaker 7: it's actually going to be mister Cooper. But this is
Speaker 7: a big deal for Rocket because they've kind of they've
Speaker 7: been trying to position themselves as sort of a one
Speaker 7: stop shop for consumers finance offerings, so think credit cards
Speaker 7: in addition to your mortgage and you know, now theoretically
Speaker 7: your mortgage servicing rights. So it's it's a pretty big
Speaker 7: deal for this company based in Detroit. Dan Gilbert a
Speaker 7: pretty prominent person in the finance yep, pretty big in
Speaker 7: sports as well. But nine point four billion dollars, it's
Speaker 7: a big deal for these folks.
Speaker 5: We have Rocket also striking a deal to acquire Redfin,
Speaker 5: which is a real estate brokerage. How will that build
Speaker 5: into this one or if they're even connected at all.
Speaker 7: Certainly it's it is basically sort of from a sort
Speaker 7: of a nose to nose to toe, if you will,
Speaker 7: of the home buying experience. Everything will sort of be
Speaker 7: under this Rocket umbrella. It you know Redfinn as you
Speaker 7: as I think a lot of folks will you know
Speaker 7: quite well, is this platform for buying and selling homes
Speaker 7: and it would be sort of a starting point for
Speaker 7: the home buying journey. Rocket is well known for originating,
Speaker 7: getting or creating mortgages, and now mister Cooper is well
Speaker 7: known for sort of the servicing of mortgages. So it's
Speaker 7: it is kind of from start to finish of the
Speaker 7: home buying process.
Speaker 2: Theoretically, they got a lot of debt on their bouncy
Speaker 2: because I being a former banker, I don't look at
Speaker 2: stock market values. I look at enterprise value to include
Speaker 2: the debt. It's eighteen point five billion dollars because that's
Speaker 2: what you get paid on. You get paid on enterprise
Speaker 2: a so that is a big, big number there. Talk
Speaker 2: to us about the mortgage business. I mean, is it
Speaker 2: doesn't seem like there's a lot of deals happening in
Speaker 2: the business.
Speaker 7: Well, I mean, I think we can look at interest rates.
Speaker 7: It's certainly been a tough time for home buyers and sellers,
Speaker 7: and that also weighs on these home on these home lenders.
Speaker 7: It's a tough time for folks who kind of have
Speaker 7: put their eggs all in one basket, which is the
Speaker 7: home lending business. But that's kind of what Rocket has
Speaker 7: been aiming to do, is to really branch out and
Speaker 7: diversify their business so they're not so interest rate reliant
Speaker 7: or exposed rather which they have been in the past.
Speaker 7: And frankly that's showed up in their earnings over the
Speaker 7: past couple of years. So I chatted with CEO U
Speaker 7: and Krishna over the summer. Actually we did kind of
Speaker 7: a deeper dive into Rocket and the company, and one
Speaker 7: thing that he told me then was that artificial intelligence
Speaker 7: is actually a big bet that they're making to really
Speaker 7: try to boost the business and make that home buying
Speaker 7: process truly as smooth as possible for the customers, to
Speaker 7: kind of amp up their offerings and we'll see how
Speaker 7: it works out. With for them in the end, But
Speaker 7: so far numbers look pretty good.
Speaker 5: What's this deal expected? Were you hearing chatter before? Did
Speaker 5: it's completely shock you?
Speaker 7: I was not hearing chatter before, and it seems like
Speaker 7: the market is responding in kind of an interesting way.
Speaker 7: But we're going to continue to follow the story and
Speaker 7: see how this kind of fits into the broader rockets.
Speaker 2: Who do they compete against? Do they compete against the
Speaker 2: banks that make the loans or the banks that make
Speaker 2: the loans usually just syndicate them away, right.
Speaker 7: Well, I kind of take a different take on that
Speaker 7: since I cover consumer and finance kind of broadly. I
Speaker 7: think of folks who are kind of trying to be
Speaker 7: that one one stop shop for consumer the consumer finance experience.
Speaker 7: So for me, I think of you know, so FI
Speaker 7: technologies for example, that is like a they have a
Speaker 7: lot of lending opportunities for consumers, but they do a
Speaker 7: heck of a lot of other business as well. Robinhood
Speaker 7: even coming at it from the investing side of things
Speaker 7: now offering banking products for folks, That's kind of how
Speaker 7: I think about it in terms of competitors. But that's
Speaker 7: just from a fintech consumer finance perspective when it comes
Speaker 7: to home lenders. You know, other big folks in the space,
Speaker 7: the space. I was just looking at some data by
Speaker 7: Inside Mortgage Finance that placed United Wholesale Mortgagees number one,
Speaker 7: Pennymac is number two, and Rocket as number three.
Speaker 2: Penny Mac is what I use. Anything that rings a bell? Okay,
Speaker 2: Dan Gilbert just for what it's worth. Kids on the
Speaker 2: rich top list of Bloomberg all the wealthy people, he
Speaker 2: comes in at number sixty two. Well they're not bad.
Speaker 2: Net worth of twenty eight point seven billion dollars up
Speaker 2: two point six billion.
Speaker 8: Year to date.
Speaker 7: Yeah, he's a force in Detroit. I would say some
Speaker 7: of our colleagues out of the Detroit Bureau did a
Speaker 7: great story on him last year. If you're interested in
Speaker 7: the terminal, All.
Speaker 3: Right, thanks to Paige Smith, Bloomberg News Consumer Finance Reporter,
Speaker 3: we move next to the artificial intelligence sector.
Speaker 2: Guest host Normal Linda and I were joined by John Lynn,
Speaker 2: chief business officer at Equinox.
Speaker 3: Equinex is the largest global data center provider and is
Speaker 3: listed on the Nasdaq Stock Exchange under the ticker symbol.
Speaker 4: E q i X.
Speaker 2: John lenn joined to discuss the future of AI empowering
Speaker 2: data centers, and I began the conversation by asking John
Speaker 2: to explain what Equinox does.
Speaker 8: We're really the fundamental digital infrastructure provider of the world,
Speaker 8: building two hundred and sixty eight data centers across seventy
Speaker 8: four market If you're the guys, we are the guys
Speaker 8: building and connecting all of these cloud provide and enterprises,
Speaker 8: making all of that data available for AI.
Speaker 9: And it's really interesting because I was just speaking with
Speaker 9: him during the break saying that I cover US real
Speaker 9: estate stocks, I cover real estate investment trusts, and that's
Speaker 9: exactly what falls in that patch. This is my guy.
Speaker 9: So wonderful to have this conversation. But I think that
Speaker 9: there's often people don't really when you think about data centers,
Speaker 9: they don't often think about the people that are actually
Speaker 9: providing the real estate for data centers. So can you
Speaker 9: talk a little bit about how equinics differs from maybe
Speaker 9: for thinking about a data center itself, but more or
Speaker 9: less the fact that you guys are acquiring properties and
Speaker 9: doing it that way.
Speaker 8: Yeah, you can think about it as full scope development,
Speaker 8: where I mean we're going from raw land getting their
Speaker 8: entitlements and then building the entire data center and then
Speaker 8: operating that for perpetuity essentially. And our focus is around
Speaker 8: making sure we're getting as many customers as possible into
Speaker 8: the facilities and really interconnecting their data flows together, which
Speaker 8: is pretty unique in the data center space, which has
Speaker 8: also been a great opportunity for us to participate in
Speaker 8: the AI growth.
Speaker 2: What are you guys seeing here? What are you seeing
Speaker 2: from your client and the people you talk to about
Speaker 2: kind of their needs going forward? Because right now, I
Speaker 2: think in the marketplace, if you look at like Nvidious
Speaker 2: stock and some of the other stocks that trade around
Speaker 2: the AI theme, twenty twenty five has not been a
Speaker 2: good year, after obviously phenomenal extraordinary growth in twenty three
Speaker 2: twenty four, maybe before that. How are you viewing the
Speaker 2: growth here in AI and from your end of the business,
Speaker 2: the real estate side.
Speaker 8: Yeah, First, I'd just say, you know, AI is a
Speaker 8: portion of the demand for data centers, but data center
Speaker 8: as a whole are powering everything that everybody is doing,
Speaker 8: right like listening to this broadcast, you know, ordering food
Speaker 8: for lunch, you know, trading, trading on the exchange, et cetera.
Speaker 8: I mean, you need computers for everything nowadays, and that's
Speaker 8: still continuing. I think, you know, digital transformation is not
Speaker 8: in the early stages anymore, but we're far from done,
Speaker 8: and so that is just the secular driver that will continue.
Speaker 8: From the eye landscape, I'd say obviously a huge amount
Speaker 8: of interest and excitement and I think the it caught
Speaker 8: the imagination of everyone, and I'd say, right now what
Speaker 8: we're seeing is like exciting use cases that are really
Speaker 8: providing durable value, right. And I think it's still early
Speaker 8: stages for many of that across the general business landscape,
Speaker 8: but that's what gets me fundamentally excited. You look at
Speaker 8: a company like a Bristol Meyers squib a customer of ours.
Speaker 8: They're doing drug discovery using videogpus and like being able
Speaker 8: to increase and accelerate their time to therapeutics. That's fundamentally
Speaker 8: going to improve like human life, right, and I think
Speaker 8: that there's so many different aspects that AI can improve
Speaker 8: based on that.
Speaker 9: So run us through some of your biggest customers, who
Speaker 9: do you all work with.
Speaker 8: Certainly the cloud providers are some of our top customers.
Speaker 8: We've got over two thousand different network providers as well.
Speaker 8: The Genesis of the company was really around how do
Speaker 8: we help the Internet scale? And that ended up being, well,
Speaker 8: how do we help the globes telecommunications and data flows scale.
Speaker 8: And so when you think about all of the cloud providers,
Speaker 8: how do they connect to the end customers, that's through
Speaker 8: our facilities. And then as we've built that landscape, we've
Speaker 8: ended up basically becoming the place where enterprises put their
Speaker 8: most trusted assets. When you think about then, whether they
Speaker 8: have some workloads that are in the public cloud, well,
Speaker 8: they're going to have some that are going to have
Speaker 8: ownership and control of themselves. When they put those in
Speaker 8: our facilities, it lets them glue that infrastructure together and
Speaker 8: become like one super powerful environment.
Speaker 2: And folks, Equinics is a publicly traded company. Eqix is
Speaker 2: the ticker. It's got a market cap of eighty one
Speaker 2: billion dollars. And if you want some research on it
Speaker 2: and you're on the Bloomberg terminal, Jeffrey Langbaum was my
Speaker 2: reat analyst. He covers eqix. You can go big and
Speaker 2: that's where you find the research on Equinox. John talk
Speaker 2: to us about the global formfront and we know you
Speaker 2: guys are global here, where are you seeing growth stronger
Speaker 2: growth versus weaker growth.
Speaker 8: Yeah, I'd say across the landscape, there's still quite a
Speaker 8: bit of demand for data center activity. You know, we're
Speaker 8: particularly excited about some of the emerging markets Southeast Asia
Speaker 8: for instance. It's certainly growing quite a bit. But you know,
Speaker 8: based off of a lot of the recent Surgeon AI
Speaker 8: and kind of the use cases set up for that,
Speaker 8: just a tremendous amount of growth in the US over
Speaker 8: the course of the last two years.
Speaker 9: So, I mean, when we think about your creditors in
Speaker 9: this broader landscape, there's obviously digital realty trust when we're
Speaker 9: thinking about publicly traded routes here in the data center space,
Speaker 9: and if you look over the past five years, we
Speaker 9: have equinic shares that have risen forty percent, but that's
Speaker 9: compared to digital realty that's risen about eleven percent. What
Speaker 9: do you think that you all are doing differently than
Speaker 9: your competitors.
Speaker 8: I think one, it's our focus around really driving diversity
Speaker 8: of customer and like kind of having an ecosystem that
Speaker 8: we've built around the value that we're doing, and so
Speaker 8: that's incredibly important for us. Like for the AI trade,
Speaker 8: for instance, we're focusing not just on capturing some of
Speaker 8: these large training footprints, but really, how do we make
Speaker 8: sure we're getting all of these AI players and exposing
Speaker 8: them to the rest of our customer base and really,
Speaker 8: again that fuel becomes additional growth across our entire portfolio.
Speaker 2: Do you develop and build data centers or do you
Speaker 2: just buy existing we develop and build? Where are you
Speaker 2: developing and building these days? And if you say Texas.
Speaker 8: Or Florida, Well, we're building all around the world. I
Speaker 8: think we've got sixty eight current like major construction projects
Speaker 8: across it. Yeah, so it's we're very active.
Speaker 2: Wow, how about it?
Speaker 9: It's really it's a big company in this. I mean, yeah,
Speaker 9: people think about you guys have to come to my path.
Speaker 8: It's a beautiful space.
Speaker 9: So what is your you know, what are your thoughts
Speaker 9: for people who are saying that, you know, the tech
Speaker 9: rally has run too far? You know, maybe we have
Speaker 9: CAPEC spend that's just you know, bloated. There's so much
Speaker 9: spending in this space. Is this a place to be
Speaker 9: investing right now? When we think about AI and places
Speaker 9: of that.
Speaker 8: Regard, I think the long term trend around this is
Speaker 8: going to be inevitable, right, I think it's certainly we're
Speaker 8: creating durable value, not just for you know, kind of
Speaker 8: the planet and all of our customers, but but for shareholders.
Speaker 8: I think the the amount of investment in the space,
Speaker 8: and like the numbers are candidly like eyewatering right now.
Speaker 8: And so but a lot of that I think is
Speaker 8: just capital accumulation rather than deployment. And you know, compared
Speaker 8: to a lot of other markets in the real estate side,
Speaker 8: it's actually a little hard to kind of overbuild just
Speaker 8: because there's so many natural like limiters in terms of
Speaker 8: the way we want to scale, from utility power availability,
Speaker 8: to supply chain to you know kind of just the
Speaker 8: amount of trades you need to be able to build
Speaker 8: and operate these facilities. And so I think that that
Speaker 8: helps kind of provide more rationality than you know, in
Speaker 8: some some real estate markets where you know, you can
Speaker 8: throw up a shell pretty easily, you can you can
Speaker 8: kind of just like convert and overbuild. In this case,
Speaker 8: it's a very long development cycle, and so I think
Speaker 8: you'll you'll see kind of some self metering there.
Speaker 2: Our thanks to John Lynn, chief business officer Equinics.
Speaker 3: Coming up in the program, we're going to break down
Speaker 3: the rising cost of food and how that's affecting the consumer.
Speaker 2: You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in
Speaker 2: depth research and data on two thousand companies and one
Speaker 2: hundred and thirty industries. You can access Bloomberg Intelligence via
Speaker 2: b I go on the terminal. I'm Paul Sweeney and.
Speaker 3: Am Alex Steele, and this is Bloomberg.
Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch the program
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Speaker 2: We turned out to the restaurant industry this week. Guess
Speaker 2: so was normal? Lindon I were joined by Michael Halen,
Speaker 2: Bloomberg Intelligence senior restaurant and food service analysts.
Speaker 3: He joined to discuss the rise and costs of food
Speaker 3: and how that's affecting the consumer.
Speaker 2: First asked Michael to break down his most recent research
Speaker 2: on restaurant spending.
Speaker 10: Restaurant space is unique. We were in a restaurant recession
Speaker 10: last year. Higher prices, Yeah, higher prices really kind of
Speaker 10: you know, the you know, the low income consumer kind
Speaker 10: of pushed back against higher prices.
Speaker 4: Right.
Speaker 10: QUSR has been raising their prices since twenty twenty. The
Speaker 10: rest of the restaurant industry has been raising prices since
Speaker 10: twenty twenty one. So last year was kind of that
Speaker 10: restaurant recession. This year, you know, we see you know,
Speaker 10: higher income consumers with a better balance sheet. Right, Crypto's
Speaker 10: up significantly. Home prices are still rising, right, and so
Speaker 10: you know, for that reason, we think that this is
Speaker 10: going to be a better year. And we still think
Speaker 10: so in the data that we've seen and from a
Speaker 10: lot of the CEOs that we've spoken to. The weakness
Speaker 10: in February was broad based, and to me that's less concerning.
Speaker 10: I would be more concerned if they said, listen, low
Speaker 10: income consumer pulled back even harder, the middle income consumer
Speaker 10: started to pull back harder, that would be more concerning
Speaker 10: to me. Broad Based tells me that, well, it was
Speaker 10: really cold. We got snow all over the country, including Sarasota, right,
Speaker 10: and New Orleans. It was the coldest January in thirteen
Speaker 10: years or so, right, and the flu was really bad.
Speaker 10: So for me, it really seems that people were just
Speaker 10: sick of the weather and sitting on the couch waiting
Speaker 10: for things to open up. We have some weekly data
Speaker 10: for early March, and data got better.
Speaker 9: So what data are you looking at when it comes
Speaker 9: to consumer health? I know you said there's some that
Speaker 9: you don't really pay as much attention to.
Speaker 6: Yeah.
Speaker 10: For the restaurant stuff, we use black box intelligence. We
Speaker 10: get very good industry level and sub segment level seems
Speaker 10: source sales traffic and check data. When I'm looking at
Speaker 10: the consumer, you know, it's kind of dated right now
Speaker 10: because it comes out quarterly, But I'm looking very closely
Speaker 10: at credit card balances and so credit card balances, credit
Speaker 10: card delinquencies, autal on delinquencies. They are still rising, but
Speaker 10: at a much lower slower pace than they were early
Speaker 10: last year, so it's a rate of change improvement. We're
Speaker 10: also looking at CPI declining, real income's rising, and savings
Speaker 10: rates rising, right, and so to me, those are all
Speaker 10: good things for the low income consumer, right, So yeah,
Speaker 10: we're not so concerned about that that consumer sentiment data.
Speaker 2: How about terraffs, How does that impact the average restaurant
Speaker 2: if they're buying food and that type of stuff.
Speaker 10: Yeah, Listen, if you're a mom and pop shop and
Speaker 10: you're importing you know, Italian or Japanese items, stuff like that,
Speaker 10: it could hurt.
Speaker 4: Right.
Speaker 10: For most our chains, they're sourcing a very large majority
Speaker 10: of their products in the United States. You know, Chipotle
Speaker 10: was one everyone was worried about their saying, it's gonna
Speaker 10: be like thirty basis points impact to their food.
Speaker 2: So the block prices aren't going to go crazy.
Speaker 10: Yeah, it's gonna be like thirty basis points for the
Speaker 10: Alvocado prices, right, And they've for years they've been you know,
Speaker 10: expanding beyond Mexico in terms of sourcing. One of the
Speaker 10: companies that we cover that has probably the most exposure
Speaker 10: overseas is Darden. They said they actually import about twenty
Speaker 10: percent of their items. Part of that is they have
Speaker 10: an Italian chain, right, but also it's just cheaper for them,
Speaker 10: and so they're working on sourcing domestically and in other
Speaker 10: places to try to ease some of that pain. So
Speaker 10: even though it's a twenty percent number, it can be
Speaker 10: much lower than that, So the restaurants aren't going to
Speaker 10: be impacted that harshly.
Speaker 9: How are consumers adjusting to the price increases. Are people
Speaker 9: just saying, Hey, I want to go out, I want
Speaker 9: to eat, so I'm just going to pay more even
Speaker 9: sell or are they a bit more resistant?
Speaker 2: If so, witch groups, it's a case shaped recovery, right.
Speaker 10: And so chains like Chilis, I mean, they just posted
Speaker 10: a thirty percent comp in the United States over a
Speaker 10: five percent comp. We've never seen that before for a
Speaker 10: chain that's been around as long as But they're bringing
Speaker 10: in younger consumers, wealthier consumers that are willing to spend, right.
Speaker 10: And so the top slant of the K, people with money,
Speaker 10: they're doing just fine, and they're still spending at restaurants, right.
Speaker 10: It's the people on the bottom slant of the K.
Speaker 10: It's these chains that are catering to low income consumers, right,
Speaker 10: that are getting that pushback. Either they're you know, going
Speaker 10: to restaurants less frequently, they're doing more shopping at the
Speaker 10: grocery store, or and when they do go to the restaurants,
Speaker 10: oftentimes they're ordering off the menu, or they're ordering less drinks, apptizers,
Speaker 10: desserts and stuff like that.
Speaker 2: Hey, Mike, how about labor real quick? Thirty seconds, bus boys, dishwashers,
Speaker 2: migrant labor migrant labors cut off here is that can
Speaker 2: be a problem for some of these restaurants.
Speaker 10: Well, it's a concern for the restaurant and industry in general.
Speaker 10: Most of our companies are compliant, they are right, and
Speaker 10: so they're not really too worried about it.
Speaker 2: Our thanks to Michael Halen, Bloomberg Intelligence scene restaurant and
Speaker 2: food service analyst.
Speaker 3: This week, Bloomberg Intelligence hosted its fourth Generative Artificial Intelligence
Speaker 3: Conference and there were some great lineups in terms of
Speaker 3: how you apply and mag jen AI for more.
Speaker 2: Alex and I were joined by Julie Choice, CMO of
Speaker 2: Sarah Bros. We first to ask Julie where she thinks
Speaker 2: we are with the changing views of AI.
Speaker 11: Well, I think that AI is really kind of hitting
Speaker 11: the mainstream more. I think that you know, chatchipt surfaced
Speaker 11: at the end of was that twenty two? I mean technically,
Speaker 11: I think the first model came out in twenty twenty two,
Speaker 11: and it's been almost two and a half years since then,
Speaker 11: and chatchipt has found its way into so much of
Speaker 11: our lives, and so people are more comfortable with AI, right,
Speaker 11: and so now I think we're just shifting into okay,
Speaker 11: AI can be a part of my life. But it's
Speaker 11: still early days.
Speaker 3: So where do you sit then, in the in the
Speaker 3: pyramid for AI?
Speaker 11: So we are Cerebras makes this beautiful chip which is
Speaker 11: basically AI infrastructure. We are the equivalent of Nvidia, so
Speaker 11: in video GPUs, it's just an alternative type of processor
Speaker 11: for AI. So we are the underlying compute that's powering
Speaker 11: the training and running of models like CHET GPT.
Speaker 2: I guess one of the questions now is people are
Speaker 2: trying to just get a better handle on what the
Speaker 2: compute needs are going forward. Gensen Wong at Nvidia remains
Speaker 2: extraordinary bullish about that, and he has been, you know,
Speaker 2: the voice of AI for many investors for the past
Speaker 2: couple of years. Where do you think we are in
Speaker 2: that compute need?
Speaker 11: Oh my goodness, I completely agree with Jensen Hang. I've
Speaker 11: been following Jensen kind of unofficially as a mentor. I
Speaker 11: find him to be an incredibly inspiring leader. I agree.
Speaker 11: I think that the compute needs for AI are ever
Speaker 11: increasing now with models like GPT four O which and
Speaker 11: the whole one series. These are like these reasoning models. Right.
Speaker 11: I'm here in New York to go to the generative
Speaker 11: AI scaling event that Bloomberg is hosting, and it's all
Speaker 11: about this like inference time. Compute. Inference time requires a
Speaker 11: tremendous amount of compute, and so we're still just scratching
Speaker 11: the surface of how much compute is really needed for
Speaker 11: this extra level of intelligence.
Speaker 3: And do you play in the inference and the LM
Speaker 3: space like the training and the usage you do both?
Speaker 4: Yes?
Speaker 11: Okay, yes, so cerebversus in both training and inference.
Speaker 3: What is has demand for your products changed at all
Speaker 3: since deep Seed came out in terms of pricing or
Speaker 3: in terms of demand.
Speaker 11: Yeah, I mean deep Seak happened in January and it
Speaker 11: was such a big moment for the industry and we
Speaker 11: immediately within forty eight hours of the news that big day,
Speaker 11: we added deep Seek to our catalog of models. And
Speaker 11: so what we do is we offer Lama models, Deep
Speaker 11: Seek models, and other kinds of models to the developer
Speaker 11: community right in our cloud. And our differentiation from GPUs
Speaker 11: is that we're like twenty to seventy times faster in
Speaker 11: terms of like that response time when you put in
Speaker 11: a query. Our responses are about twenty to seventy times
Speaker 11: faster because of the architecture being bigger, So deep Seek
Speaker 11: really created this moment of developers coming at us saying,
Speaker 11: oh my god, you guys have the fastest deep Seek.
Speaker 11: We want to you know, we want we want that,
Speaker 11: we want to see what that can do. And that's
Speaker 11: led to a lot of prototyping. But what we do
Speaker 11: see is that when it comes to developers that are
Speaker 11: building AI businesses, there's a lot more usage of Lama.
Speaker 11: So Meta Lama is probably still the most popular open
Speaker 11: source AI model that is downloaded at least from the
Speaker 11: Cerebraus cloud. And then we have customers like Perplexity and
Speaker 11: mistral Alpha Sense based here in New York that are
Speaker 11: kind of serving their adapted Lama models as well as
Speaker 11: their own custom models.
Speaker 2: So the deep Seak issue for the industry was, Hey,
Speaker 2: here's this Chinese company coming out with an AI solution
Speaker 2: at a much lower cost. Is that good or bad
Speaker 2: or neither good or bad for the AI evolution?
Speaker 7: Oh?
Speaker 11: I think it's very good because deep Seek was a
Speaker 11: state of the art model when it came out. It's
Speaker 11: still one of the best models in the world, especially
Speaker 11: I think with their at V three. And what it
Speaker 11: proves is that when you can open source this level
Speaker 11: of intelligence, You're bringing down the cost to developers and
Speaker 11: it increases developer creativity. And so one of the things
Speaker 11: that Cerebras is super passionate about is providing developers with
Speaker 11: the best models open source or custom you know, fastest
Speaker 11: at the best price. And so we were just very
Speaker 11: excited when Deepseak open sourced, and clearly like the developers
Speaker 11: were very excited as well. It was definitely kind of
Speaker 11: an inflection moment.
Speaker 3: In terms of what you're most excited about right now, Like,
Speaker 3: what's the coolest use case you've seen when it comes
Speaker 3: to training and when it comes to in fronts.
Speaker 11: Fantastic question. So for training, I'm going to bring up
Speaker 11: a healthcare use case. So one of our favorite partners,
Speaker 11: and you know, we shouldn't have favorites, but I really
Speaker 11: appreciate the work that Mayo Clinic has done in Cerebras.
Speaker 11: They have been able to train world leading foundation model
Speaker 11: using genomic data, and the point of their genomic model
Speaker 11: is to help patients of rheumatoid arthritis. I have a
Speaker 11: family member who's been struggling with this terrible disease for
Speaker 11: a decade, and this AI model can help her find
Speaker 11: the medicine that actually works much more quickly. I didn't
Speaker 11: realize that actually rheumatoid arthritis generally forty percent fail rate
Speaker 11: in terms of aligning the right medicine to the patient.
Speaker 11: And so really proud of the work that the mail
Speaker 11: Clinic team has done in partnership with Cerebris, training that
Speaker 11: model super fast on our chip, releasing it in probably
Speaker 11: less than nine months of development time. Wow on the
Speaker 11: training side. On the inference side, I'm very excited to
Speaker 11: be working with companies like Perplexity as well as Mistral.
Speaker 11: These are some very very AI forward companies leading the
Speaker 11: way in terms of disruptive search experiences for consumers and
Speaker 11: amazing chat assistance, especially in Europe, and we're powering their
Speaker 11: super fast results.
Speaker 2: Your company, are you seeing any impacts of just the
Speaker 2: uncertainty surrounding how this TWERFF policy will evolve? Is it
Speaker 2: and your customers saying, you know, we're just going to
Speaker 2: wait a little bit before we place an order or
Speaker 2: something like that.
Speaker 11: No, Actually, it's really all systems go Okay. Our customers
Speaker 11: want the fastest inference speeds, they want the smartest models
Speaker 11: in their applications. We're not waiting to find out. There's
Speaker 11: no time to wait. We have to deliver the fastest
Speaker 11: compute to the best Custos commers in the world.
Speaker 3: Our thanks to Julie Choi, CMO of Sarah Bross.
Speaker 1: This is the Bloomberg Intelligence Podcast, available on Apple, Spotify,
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