Speaker 1: From Marhard where Innovation, money and power Collie in Silicon Valley, NBN.
Speaker 2: This is Bloomberg Technology with Caroline Hyde and Ed Ludlove.
Speaker 3: I'm Carolin Hyde and Bloomberg's word lad Quarters in New York,
Speaker 3: and I'm Ed Lovelow in San Francisco.
Speaker 4: This is Bloomberg Technology.
Speaker 3: Ed caution consumes investors as were a torrent of tech earnings.
Speaker 5: This week, we discuss what to watch.
Speaker 4: But artificial intelligence momentum. We speak to the CEO of
Speaker 4: Runway on generative AI powered video and we're joined by
Speaker 4: the executive leading fidelities charge into AI and machine learning.
Speaker 3: Meanwhile, legal headaches to blue check chaos. What on earth
Speaker 3: is going on at Twitter? The latest is all coming up.
Speaker 4: It is a big week where earnings are in focus.
Speaker 4: You look at this sort of long list of megacat
Speaker 4: names that are coming. We start with Microsoft, then Alphabet,
Speaker 4: the parent company of Google Meta, and then we work
Speaker 4: through to May fourth in a couple of weeks time
Speaker 4: or next week. For Apple. Things are getting very serious
Speaker 4: because across the S and P five hundred information technology subsector,
Speaker 4: we expect a pretty big drop when it comes to
Speaker 4: earning's character.
Speaker 3: Yeah, we're expecting the biggest drop in tech profits since
Speaker 3: two thousand and nine. Let's dig in to the key
Speaker 3: company's got to keep an eye on none of them
Speaker 3: and Mart Mahiney you know him, of course, senior managing
Speaker 3: director of Internet Research over at Evercore ISI and we
Speaker 3: wait with bated breath to the likes of Alphabet, some
Speaker 3: of the big heavyweights that really shine and light on
Speaker 3: how much companies are willing to spend on advertising and
Speaker 3: drive these sorts of companies forward.
Speaker 6: Mark, That's right, Caroline, So yeah, we're going to get
Speaker 6: a lot of I think there are three things we
Speaker 6: want to alter that it and all the noise we're
Speaker 6: going to get the signal we're going to get this week.
Speaker 6: Let's try to focus on three things. What are these
Speaker 6: companies telling us about the state of the economy. Is
Speaker 6: our advertising retail trends, cloud enterprise spend trends. Are they
Speaker 6: still deteriorating or improving from where we were in the
Speaker 6: December quarter? Our best guess is that trends are stabilizing
Speaker 6: to softening, not recovering yet. The second thing is costs.
Speaker 6: That's the new sheriff in town, if you will. All
Speaker 6: of these companies across tech have announced some sort of
Speaker 6: riffs reduction in forces over the last three six nine months.
Speaker 6: I mean, it's a dramatic change in the mentality of
Speaker 6: Silicon Valley and of tech broadly. So is there more
Speaker 6: to come? And what does it actually mean in terms
Speaker 6: of the bottom line? How successful are these companies defending
Speaker 6: their free cash flow and earnings? And then the third
Speaker 6: thing is on the positive side, is AI generative AI.
Speaker 6: You already teased it out a little bit, and I
Speaker 6: imagine that every tech company is going to mention AI
Speaker 6: and somebody should start a counter right now. How many
Speaker 6: times AI is mentioned in the in the earnings transcripts
Speaker 6: over the next of course, of the next couple of weeks.
Speaker 4: But it's going to be high.
Speaker 6: But for a reason too, we're at a bit of
Speaker 6: a tipping point because for a lot of reasons, but
Speaker 6: you know, chat GPT really brought AI home to most
Speaker 6: people about what the power is of these models even
Speaker 6: though they've been deployed for a while. But the increase
Speaker 6: in compute capacity really allows kind of a step level
Speaker 6: increase in the applications to the deployments of AI. So
Speaker 6: talk about it. We want these companies to talk about
Speaker 6: how well positioned they are and what their deployment ideas are.
Speaker 4: Mark, let's go back to that sheriff in town being
Speaker 4: cost control. You know, probably the one point of commonality
Speaker 4: between those names is that they have done layoffs and
Speaker 4: other cost reduction action and how it shows up. I
Speaker 4: find Meta to be really interesting in that respect because
Speaker 4: the top line growth might not be there, but I
Speaker 4: think we're expecting a sequential improvement in margins, right because
Speaker 4: of the actions that they've taken.
Speaker 2: I think that's right.
Speaker 6: I just think of these companies, probably the one that's
Speaker 6: been most aggressive in taking out costs so far, maybe
Speaker 6: surprisingly it is Meta, and I think these other companies,
Speaker 6: I think the market. I think investors want Google to
Speaker 6: do more with their cost structure, that's probably, and then
Speaker 6: I think market once and investors want Amazon to do
Speaker 6: more too. I don't know about Microsoft. Investors may be
Speaker 6: comfortable with where they are now, but yeah, I think
Speaker 6: at the whole, investors kind.
Speaker 4: Of want a little bit more.
Speaker 6: Look, we overbuilt, we over hired because we overextrapolated from
Speaker 6: COVID demand trends, but also because we're going into a
Speaker 6: softening demand environment. You know, households are going to have
Speaker 6: to tighten our belts and solo companies. So I think
Speaker 6: there's gonna be an expectation or at least a hope.
Speaker 6: This question is whether it's going to be realized that
Speaker 6: we're going to hear more on the cost front from companies.
Speaker 6: I think we will from Meta, I'm not sure we
Speaker 6: will from Google, and I think we will from Amazon,
Speaker 6: but you know, it's hard to know.
Speaker 3: The three big beasts that you analyze Mark Amazon also
Speaker 3: will shine a light, as you said so rightly, on
Speaker 3: how willing companies are to invest in things like cloud.
Speaker 3: At the moment, AWS a big profit juggernaut for them,
Speaker 3: but also for alphabet who are hoping to break even
Speaker 3: in some way on that. What do you expect for
Speaker 3: how much companies are showing resilience and needing compute power
Speaker 3: right now?
Speaker 6: Well, we're decelerating. I think cloud demand is going down.
Speaker 6: It shot up during part of the COVID crisis. It's
Speaker 6: been a super hot, high priority level area for enterprise
Speaker 6: spend for the better part of five, six, seven years,
Speaker 6: but it's slowed down and we're through what we're going
Speaker 6: through what's called an optimization cycle, where companies are going
Speaker 6: to you know, when the renewals are coming up, they're
Speaker 6: demanding better, a bigger discounts, or more capacity for the
Speaker 6: same price. That's clearly happening in the market. That means
Speaker 6: that these revenue growth rates that Microsoft is going to
Speaker 6: report with a zer, a, Google Cloud, and AWS are
Speaker 6: going to report, they're all going to show a slow down.
Speaker 6: And the question we have is just how low will it go?
Speaker 6: And I think we hope that the trough is kind
Speaker 6: of the June quarter, and we think with Amazon with
Speaker 6: AWS you're going to have like a single digit percent
Speaker 6: growth and AWS revenue. I mean, that's kind of shocking
Speaker 6: if you go back two years, nobody would have expected
Speaker 6: that to happen, But that's probably what's going to happen.
Speaker 6: And then the question is how quickly does it base
Speaker 6: from there and start reaccelerating. We think it will base,
Speaker 6: We think it will reaccelerate. We just don't really know
Speaker 6: just how quickly it will. So that's that's going to
Speaker 6: be an overhang on the stock mark.
Speaker 4: If we do get some upside surprise across this kind
Speaker 4: of pretty broad range of names, where do you think
Speaker 4: it will be.
Speaker 6: I think it's probably going to come on the margin side.
Speaker 6: Ed I think it's probably going to come on the
Speaker 6: cost side, because that's what these companies can control. It
Speaker 6: can't do much about demand trends in a softening macro environment.
Speaker 6: So I'd be really surprised if we had positive, you know,
Speaker 6: material upwards revisions on cloud enterprise spend, or on retail
Speaker 6: spend or on advertising spend. I mean, I hope we
Speaker 6: get them, but as a bull on these stocks, but
Speaker 6: I don't.
Speaker 4: I think that's.
Speaker 6: Highly highly unlikely and what we should so I think
Speaker 6: there'll be positive news on the margins. We should all
Speaker 6: be just watching out for the chance that if we
Speaker 6: go into a hard landing in the second half of
Speaker 6: this year. I don't think that's modeled in. It may
Speaker 6: be priced in, but I don't think it's modeled into
Speaker 6: these companies. So that's what we're you know, Like I
Speaker 6: do worry like fund valuation wise, I think there's upside
Speaker 6: to be stock because they were so de risk last year.
Speaker 6: But estimates wise, I think the first half the year
Speaker 6: estimates are fine, a little bit of an upwards bias
Speaker 6: because of cost cutting, But I just worry about the
Speaker 6: demand tens if we have a hard landing estimates may
Speaker 6: need to come down in the back half of the year,
Speaker 6: So I don't know if that's more cautious than you
Speaker 6: wanted to hear it. That's kind of how we come out.
Speaker 3: And what's interesting about timing this year for this quarter.
Speaker 3: It used to be that Snap was the bell weather
Speaker 3: for where we would expect Alphabet and Meta to go,
Speaker 3: but they're actually behind those two ones in terms of
Speaker 3: timing this year.
Speaker 4: Yeah, you're right, we showed the calendar earlier. Mark. It's
Speaker 4: just the cadence of the week gets bigger and bigger
Speaker 4: and bigger. But we don't have an early sense apart
Speaker 4: from Tesla that's reported on broadly where we sit in
Speaker 4: this market.
Speaker 6: You're right, Carolina, Then you're right, and it's odd the
Speaker 6: way you set it up. Caroline, you're right that the
Speaker 6: market took Snap as a bell weather, but come on,
Speaker 6: it's tiny compared to these other companies, and they haven't
Speaker 6: executed nearly as well, so they've really been a false
Speaker 6: false indicator most quarters, I would argue, So I think
Speaker 6: it's better for the market that they report later because
Speaker 6: it's just noise that comes out of them. You and
Speaker 6: I don't mean I don't mean that disrespectfully. I just
Speaker 6: think that they're less of a read through into the
Speaker 6: larger and larger players. That's what I really meant to
Speaker 6: say in a respectful way. Whereas Google is going to
Speaker 6: give you a really good view on what's happening to
Speaker 6: overall advertising trends. Google is GDP advertising, so and I
Speaker 6: think they're going to talk about trends that are softening,
Speaker 6: not deterior and dramatically, but are modestly deteriorating. And I
Speaker 6: think we should be prepared for that. I think it's
Speaker 6: going to be a really reasonable read through, certainly sizable.
Speaker 6: It's the single largest advertising data point you can get worldwide.
Speaker 6: Pay attention to Google.
Speaker 3: Mamahini well said, and pay attention to all of those
Speaker 3: AI headlines that come out of them as well. Av
Speaker 3: Aquo II, we thank you as always for joining.
Speaker 5: Us a ed.
Speaker 2: Yeah.
Speaker 4: Look, layoffs were a common theme of that conversation. Let's
Speaker 4: take a look at Disney, which began its second round
Speaker 4: of job cuts today, part of its broader push to
Speaker 4: eliminate about seven thousand jobs this year. The company says
Speaker 4: that by Thursday, around four four thousand jobs will have
Speaker 4: been cut. The cut stretch from Disney's headquarters in Burbank,
Speaker 4: California to the ESPN Sports network over in Connecticut. Now
Speaker 4: coming up, Bitcoin hit new records after each of its
Speaker 4: previous harvings. Now cryptoanalysts are projecting for a new high
Speaker 4: when the process takes place next year. We have more
Speaker 4: and how this will push the price of the digital
Speaker 4: token quick check and the shares of First Republic higher
Speaker 4: seven percent due out of earnings after the bell later today,
Speaker 4: have really keen eye on deposit flows still going the
Speaker 4: health of that bank long term, bringing the details.
Speaker 7: This is bloombow.
Speaker 3: So crypto taking a bit of a breathe over the
Speaker 3: last few trading days, but analysts through actually saying Bitcoin
Speaker 3: in particular, it's rebound, just the start of the rally
Speaker 3: that will take the coin past fifty thousand dollars next year,
Speaker 3: all because of what is the process known as halving,
Speaker 3: that's basically curbing the amount of tokens that miners receive
Speaker 3: as a reward for their work. Mike mccloin seeing in
Speaker 3: macro strutches and bringing back intelligence joins us. Now with
Speaker 3: more and this so called harving, we're anticipating what happens
Speaker 3: in about April of next year.
Speaker 8: Well, Hi, Caroline, it makes me put on my trader's
Speaker 8: hat versus my investor's hat. The having, i think is
Speaker 8: the key part of bitcoin's definable diminishing supply, which is
Speaker 8: unique to all common is the theater is kind of
Speaker 8: like that, just less more difficult to measure. But with
Speaker 8: increasing the demand and adoption of price must up over
Speaker 8: time that it's a known known. The thing I'm worried
Speaker 8: about right now is this bigger unknown of the world
Speaker 8: tilting towards the recession, risk assets kind of tilting downward,
Speaker 8: and the FED still tightening. In bitcoin and in cryptos
Speaker 8: among the riskiest of acts. So I'm worried that we're
Speaker 8: more likely to have peaked around thirty have some pressure
Speaker 8: for a while, particularly if we see more in the
Speaker 8: screen we're seeing today with the stock market going lower
Speaker 8: and NASDA kind trickling down below that thirteen thousand level.
Speaker 4: Mike, let's go back to basics a little bit. A
Speaker 4: harving or harthening as it's otherwise known, reducing the amount
Speaker 4: of tokens that bitcoin minors get as a reward for
Speaker 4: their work. What is the link between that activity and
Speaker 4: the anticipation of the price of bitcoin going higher. What
Speaker 4: are the mechanics behind that.
Speaker 1: So right now the most you can we can produce
Speaker 1: on a daily basis of bitcoin mine is nine hundred
Speaker 1: coins a day. Before that was eighteen hundred before the
Speaker 1: last having, So you get the next having that's going
Speaker 1: to cut it back to four hundred and fifty coins
Speaker 1: a day. It's by code, and then four years from
Speaker 1: now it's going to do it again. That's just the
Speaker 1: beauty of the code. It has to go down the
Speaker 1: supply decline.
Speaker 9: So right now the total supply is running around two percent,
Speaker 9: so right around the historical measure of goal. A year
Speaker 9: from now it's going to drop below one percent because
Speaker 9: it's just definable diminishing. And that's the beauty of it.
Speaker 9: All those miners are fighting for more and more. But
Speaker 9: it's a unique thing about what bitcoin does. No other
Speaker 9: commodity does that. You can say prices go up, supply
Speaker 9: comes on tip. Particularly with gold it does too, but
Speaker 9: most notably learned that when crude all last year. But
Speaker 9: what's happening now is people are anticipating now it's going
Speaker 9: to just do what it did in the past. And
Speaker 9: I think the thing that's different this time, ed is
Speaker 9: bitcoin was born out of the last great financial crisis
Speaker 9: in that recession. I think this one's going to define it,
Speaker 9: but it's going to be its first recession, and I
Speaker 9: think it's the first time we might see that the
Speaker 9: S and B five hundred drop more than twenty percent
Speaker 9: into a recession, which should pull all risk acids lower.
Speaker 9: So I think i'll end with this one thing you
Speaker 9: saw today was a little bit off topic, but similar
Speaker 9: as record shorts and ten year thirty year in bond futures,
Speaker 9: might be indicative of gold continued toll performing, Bitcoin being
Speaker 9: pushed a little to the waistside.
Speaker 4: All right, Mike mcglom Bloomberg Intelligence on a roll out
Speaker 4: of Miami. Thank you. Meanwhile, Caroline, don't know if you
Speaker 4: saw this one. Franklin Templeton says it's money market fund
Speaker 4: used to record share ownership on a blockchain, is seeing
Speaker 4: inflows specifically from crypto related firms. The fund's total assets
Speaker 4: increased to around two hundred and seventy million dollars. This
Speaker 4: is a fund that invests in US government securities, does
Speaker 4: not hold crypto assets, but it's who's putting the money in.
Speaker 3: Yeah, because remember a lot of at the moment, these
Speaker 3: overall crypto investors or crypto related companies, they've just lost
Speaker 3: a load of their financial infrastructure with some of the
Speaker 3: bank's silver gate. We think, of course Signature Bank coming
Speaker 3: out of the market. They want safer places to put
Speaker 3: their money. Of course, you kind of have to be
Speaker 3: banked to get into a money market fund, even if
Speaker 3: it's Franklin Templeton. But I suppose it is no surprise
Speaker 3: that if you're going to look for a money market
Speaker 3: fund to gain you exposure, safe exposure overall, you're likely
Speaker 3: to go to one that's at least in some way
Speaker 3: in your line of sight and liking. And of course
Speaker 3: the Franklin on shae US government money funds they're going
Speaker 3: to like that. There's sort of play there, isn't there,
Speaker 3: And at the moment it's off likely to be on
Speaker 3: chain without Benji coin.
Speaker 4: We saw the vcs do it, and now we're seeing
Speaker 4: the industry itself do it with their own money. Let's
Speaker 4: continue talking with the crypto market. Sunny Singers here with
Speaker 4: more insights. The CEO of CS Labs twenty one in
Speaker 4: stealth mode, but also of course a well known person
Speaker 4: in this industry. Let's go straight actually to the harving
Speaker 4: or the harvining. What do you make of that?
Speaker 2: Yeah, it happens everything years.
Speaker 4: You're a believer in the logic behind it.
Speaker 10: Yes, it makes sure like central governments can keep producing
Speaker 10: new currency, which creates inflation. Bitcoin was created the other
Speaker 10: way to reduce the supply, which makes it more deflation area.
Speaker 10: So it's a great mechanism they built into the system,
Speaker 10: and it happens every four years, and it's scheduled to
Speaker 10: happen next April twenty seventh, round rough with that date,
Speaker 10: and so right around a year from now, and you're
Speaker 10: gonna start seeing a lot of media frenzy start happening.
Speaker 10: Six months to you know, rout and that should start happening,
Speaker 10: and then you start seeing the price run up a
Speaker 10: little bit.
Speaker 3: Look, it's funny to overall think about how much we've
Speaker 3: seen this torrid time within crypto, whether it's actually the
Speaker 3: likes of Bitcoin eighth sort of taking up a lot
Speaker 3: of the oxygen in the room when it comes to
Speaker 3: allocation at the moment, or at least.
Speaker 5: Where the rallies have been.
Speaker 3: Then there's also the question we were just talking about
Speaker 3: the fact that a lot of crypto players find themselves
Speaker 3: without the banking infrastructure that were used to the signatures,
Speaker 3: the silver banks or the overall silver gates as well.
Speaker 5: How difficult is it in the crypto space for you?
Speaker 2: It's very bad.
Speaker 10: So my company we just raised a four million dollar
Speaker 10: seed around. We did it in forty five days, which
Speaker 10: is great from an all starting of crypto investors as
Speaker 10: all autritional investors, But the mood has definitely changed. The
Speaker 10: banking regulations have become increasingly hard. Getting banks is increasingly hard.
Speaker 10: Everything that could go wrong has gone wrong for the
Speaker 10: crypto industry. And yet the price of bitcoin has rallied
Speaker 10: from sixteen thousand to almost thirty thousand in the last
Speaker 10: six months, which is pretty remarkable, and I wouldn't be
Speaker 10: surprised if bitcoin hits forty thousand this year.
Speaker 4: Can I just jump in on that seed stage? Just
Speaker 4: broadly speaking, how difficult was that following the collapse of
Speaker 4: Silicon Valley Bank? For how long you would negotiate around
Speaker 4: But you're basically taking a crypto proposition to investors who
Speaker 4: are a bit more cautious than perhaps they previously were
Speaker 4: in that industry.
Speaker 10: Yes, it was much harder and we wanted to get
Speaker 10: a mix of crypto investors as well as silicon value investors.
Speaker 2: And the silicon value investors.
Speaker 10: Might have loved the idea, but they're no longer doing
Speaker 10: crypto investing anymore. A while of teams said they're now
Speaker 10: doing AI and pivot, so it's much more difficult that way,
Speaker 10: and they would rarely to wire our money the day
Speaker 10: before SVB had the issues, and we're going to SVB
Speaker 10: two as we did away that three weeks too. So again,
Speaker 10: everything that could go wrong has gone wrong in the
Speaker 10: crypto space for the last year, I would.
Speaker 3: Say, and that's not even talking about some of the
Speaker 3: overall regulatory headwinds that still everyone is very worried about
Speaker 3: when it comes to how people are going to analyze
Speaker 3: the SEC is going to look.
Speaker 5: At some of these crypto assets.
Speaker 3: All these headlines you see Gemini thinking of a non
Speaker 3: US based derivative platform. We know that other key players
Speaker 3: are looking at licenses, crypto licensings in Bermuda. How tempting
Speaker 3: is it to take whatever you're building out of the
Speaker 3: United States.
Speaker 10: Yeah, and again companies that coin based Gemini, my previous company,
Speaker 10: bit pay. We try to play by the rules. Work
Speaker 10: with the SEC. We all got in New York bit licenses.
Speaker 10: We're trying to do it the right way. Fighting the
Speaker 10: SEC is now really getting a little harder to work with,
Speaker 10: and they keep changing their mind on things and becoming
Speaker 10: like coin based of Gema. It's trying to keep growing
Speaker 10: during Crypto Winner, it's hard for them to get full
Speaker 10: clarity on what to do.
Speaker 2: That's why they're looking offshore.
Speaker 10: And again ftxus FTX, which went out of business, was
Speaker 10: created because it compan called bit mechs random issues. And
Speaker 10: now with FTX gone, there's really a void in the
Speaker 10: international trading markets that's going to buyans instead, and companies
Speaker 10: like Gemini and coinbas see a big opportunity if they
Speaker 10: can get this derivers market and things like that that
Speaker 10: Bias has been focusing on.
Speaker 4: All right, Thanks to Sonny Saying CEO of cs Labs
Speaker 4: twenty one, which I hope to hit more about. Twitter's
Speaker 4: legal battles over its mass layoffs. Last Full continue to grow,
Speaker 4: with two more formal workers filing class action complaints at
Speaker 4: about two thousand Index employees pursuing claims in individual arbitration.
Speaker 4: Let's bring in Bloomberg. Sarah Fryar for more two thousand,
Speaker 4: making claims. It's quite a big chunk of the workforce
Speaker 4: that was laid off.
Speaker 11: And it's all in individual arbitration and mass arbitration, which
Speaker 11: often when companies put the arbitration clauses into contracts to
Speaker 11: expect that they'll be able to get things done quietly
Speaker 11: behind the scenes. In this case, I don't think that's
Speaker 11: going to work. I think it's going to become a
Speaker 11: very arduous and expensive process for Twitter.
Speaker 3: Meanwhile, there's been several people completely well many people completely
Speaker 3: baffled by what's happening at Twitter in general, particularly around
Speaker 3: who's got those blue check.
Speaker 5: Marks who doesn't. It feels as though there's a lot
Speaker 5: of chaos there at the moment.
Speaker 3: I just want to listen into what Ron Reynolds had
Speaker 3: to say last week about the service to take a listen.
Speaker 12: Sarah, I don't know. I mean, I see they all
Speaker 12: have sort of different footprints. I mean, Twitter has is
Speaker 12: now and has always been a piping high dumpster fire
Speaker 12: of trash, and it is it can be a very
Speaker 12: difficult place, but it's also a place that there can
Speaker 12: also be incredible good.
Speaker 3: When you have words to say like that, are we
Speaker 3: unsurprised that with twenty one million followers, his Blue Legacy
Speaker 3: check mark isn't being paid by Ela Musk.
Speaker 11: I think that we're actually seeing the check mark return
Speaker 11: to a lot of accounts in particular that have been
Speaker 11: critical of Musk is almost applying that brand to them
Speaker 11: as a punishment, which seems like a strange a strange
Speaker 11: reward slash punishment. If you want people to buy a
Speaker 11: blue check, using it against your enemies is not the
Speaker 11: strategy I would pick, but hey, Musk has he works
Speaker 11: in mysterious ways. I think we're also seeing the check
Speaker 11: reappear among the accounts of you know, rather popular accounts
Speaker 11: with more than a million followers, including some accounts of
Speaker 11: people who don't exist or who have since died from
Speaker 11: before the checks were rolled out. So it is all
Speaker 11: getting a whole lot more confusing, And I think that
Speaker 11: it just means the Twitter Blue experiment nobody knows what
Speaker 11: it's for. Nobody knows all.
Speaker 4: Right, Bloomberg Surah for I thank you. Cara would point
Speaker 4: out in Ryan Reynolds's case, in particular, he is using
Speaker 4: Twitter right. Think about the reaction video he shared film
Speaker 4: by Paul Rudd after his football team Rexham got promoted.
Speaker 3: Millions of people saw that particular clips, several clips.
Speaker 5: What a story They've got to make another documentary out
Speaker 5: of it.
Speaker 13: Ed.
Speaker 4: Yeah, and by the way, my mum was born in Wrexham,
Speaker 4: so I was cheering from AFAR.
Speaker 3: Welcome back to bloombag Technology. I'm Carolin Hide in New York.
Speaker 4: And Imed Ludlow in San Francisco. Carrige. We get a
Speaker 4: quick check on the markets and where we're training in
Speaker 4: the technology sector, and that's that one hundred softer by
Speaker 4: about seven tens percent. Tesla kind of a big drag
Speaker 4: on that index from a points perspective. Underperformance as well
Speaker 4: in the chip space semiconductors and the socks off by
Speaker 4: nine tens percent short end of the curve. That is interesting.
Speaker 4: You see the two year off by about three basis
Speaker 4: points four point one four percent, and as we said,
Speaker 4: we kind of cooled it on Bitcoin twenty seven three
Speaker 4: hundred dollars or so per token. There's a few specific
Speaker 4: movers that we're looking at in the markets as well
Speaker 4: when it comes to big tech names, actually tech names
Speaker 4: large and small. Mister director, if you change up the
Speaker 4: board Tesla, as I said to the downside, a pretty
Speaker 4: big drag. Microsoft also markedly lower off by two percent
Speaker 4: ahead of earnings coming this week. Amazon also softer C
Speaker 4: three AI, an AI name that has been downgraded, not
Speaker 4: for anything reasons to do with artificial intelligence, Caro, simply
Speaker 4: to do with macro and fundamentals. And you wonder now
Speaker 4: how much this market is getting a bit more realistic,
Speaker 4: some of the momentum on the publicly traded AI names
Speaker 4: at least kind of being taken out. Should we move on.
Speaker 4: Here's what some of our guests on the show have
Speaker 4: had to say about the rise of generative AI in
Speaker 4: that space, both but for the sort of investing standpoint,
Speaker 4: but also let's have a little thing about research too.
Speaker 4: Have a listen.
Speaker 14: Some of the best opportunities are are sitting right in
Speaker 14: front of us.
Speaker 15: AI I believe will be the third largest compute revolution
Speaker 15: that we've seen in our generation.
Speaker 4: So we think the biggest opportunity and the safest place
Speaker 4: to deploy these type of technology is inside the enterprise itself.
Speaker 6: We'll see more of that AI to go into traditional
Speaker 6: industries and helping them move faster and be more efficient.
Speaker 5: AI is global, it's not something local. It's not a fan.
Speaker 5: It's going to be here and it is affecting all
Speaker 5: of us.
Speaker 4: This space is emerging so fast.
Speaker 16: Frankly, it's very hard at track.
Speaker 4: Even from an investment perspective.
Speaker 15: There's never like one very obvious clear answer when you're
Speaker 15: getting into the weeds of how this technology can affect people.
Speaker 15: I'm a huge fan of making sure that the government
Speaker 15: authorities work closely with the industry.
Speaker 3: Well, we've got yet more insight, this time from a
Speaker 3: heavy backe see backed player in the space already making things,
Speaker 3: creating things in the real world.
Speaker 5: Chris valence Uler is with our.
Speaker 3: CEO of the applied AI research company Runway. Basically, you're
Speaker 3: all about human creativity, you're about films. We've already seen
Speaker 3: what your own AI generalor AI being used within everything everywhere,
Speaker 3: all at once.
Speaker 5: How is it being used in a way that that surprises.
Speaker 16: You many ways.
Speaker 14: We started to see things that we're just literally impossible
Speaker 14: to do for now being possible with these technologies. I
Speaker 14: think we're still very early to understand the full creative
Speaker 14: potential of everything that will come. But yeah, you have
Speaker 14: thoughts like everything about all once using Runway to added
Speaker 14: some scenes in there, you have musicians and artists taking
Speaker 14: like really the technology to the next level, which we
Speaker 14: think it's really the right thing to do, which is
Speaker 14: start experimenting and exploring more with these capacities.
Speaker 12: You have.
Speaker 3: Of course all of this excitement euphoria, there's also a
Speaker 3: lot of nerves, particularly around people who worry that their
Speaker 3: own are their own imaging is being used to train
Speaker 3: Aiyes on, how are you squaring that circle?
Speaker 5: Because it's a difficult one to navigate.
Speaker 14: Yeah, I know, and we've always thought about that in
Speaker 14: a very particular, interesting different way. I come from on
Speaker 14: our distant background, and so I have deep empathy for
Speaker 14: those arties and those creatives who are asking themselves what's
Speaker 14: going to happen next with this technology?
Speaker 16: I think, I think to remind ourselves is that we're.
Speaker 14: Still very early, and what we need to do is
Speaker 14: open the conversation to have more people come in and
Speaker 14: understand how you're going to start leveraging this technology in
Speaker 14: your art practice. I think that for me is really important,
Speaker 14: and I'm something we practicing runway kind of like from
Speaker 14: the very beginning.
Speaker 4: Chris, your Gentoo system is still on a witless basis, right,
Speaker 4: I know a lot of folks that I've spoken to
Speaker 4: about this way are keen to get access. But the
Speaker 4: reality is, you know, text to video it generates about
Speaker 4: three seconds, and I wondered how much you're emphasizing the
Speaker 4: kind of early stage that this is In three seconds.
Speaker 4: Not a lot of contents generate using the tool.
Speaker 16: I agree three seconds is not enough.
Speaker 14: We already have fifteen second like long support Engen, you're
Speaker 14: working towards including and adding more to that. I think
Speaker 14: the reason we released with three seconds is we have
Speaker 14: to make sure that more people can get their hands
Speaker 14: on the research, on the product, on this new way
Speaker 14: of creating.
Speaker 16: Content and really have thousands of people using it, and
Speaker 16: so the amount of.
Speaker 14: Feedback we've gotten to improve the quality of the model
Speaker 14: the experience as well. I think text to videos one
Speaker 14: of many modes of using Gen two actually has eight
Speaker 14: different modes. Today release the mobile app for the first
Speaker 14: time ever, you can try Gen one actually on your iPhone,
Speaker 14: and so there's so many things yet to be explored
Speaker 14: and discovered here that for us really just making sure
Speaker 14: that we could put it in the hands of more
Speaker 14: creatives out there.
Speaker 4: I was listening to Noam Shazir, the CEO of character
Speaker 4: Ai on the No Prize podcast the other day, and
Speaker 4: he faces a similar debate, Right, how do you onboard
Speaker 4: users and grow the user base and then in the
Speaker 4: future monetize And I wonder how that equation looks for
Speaker 4: you as well, the focus on kind of making money
Speaker 4: or just grow the number of users and investing in
Speaker 4: the infrastructure needed to support it.
Speaker 14: I think it's important that remember that we're very early
Speaker 14: on the journey of both value capture and one of
Speaker 14: the station industry wide, and so making sure that you
Speaker 14: work with as many people and as many companies as
Speaker 14: you can will help you on tab possible value captures.
Speaker 14: I think overall, where we're starting to digest the initial
Speaker 14: stages of that and for us is really making sure
Speaker 14: that we're going to keep building the research and the
Speaker 14: foundational effort to build better models and more safe models
Speaker 14: every time.
Speaker 4: Hey Caro, I think back to when Sonia Juang of
Speaker 4: Sequoia is on the show a Venture Capitalist explaining why
Speaker 4: she sees potential here, you know, think about one's ability
Speaker 4: to dream up anything and use the generative tool to
Speaker 4: just create your own video. That's where the vcs seemed
Speaker 4: to be wanting to put their money.
Speaker 3: To augment humanity, not to come against it at the moment.
Speaker 3: But Chris, I turned to you and think about how
Speaker 3: enthusiastics certain vcs have been around you. I think a
Speaker 3: CO two Lux Capital for Lie's. You've got a lot
Speaker 3: of money come in your direction. Are you turning it away?
Speaker 3: Are you thinking about raising funds opportunistically?
Speaker 14: So we started Runway like four or five years ago,
Speaker 14: I mean working on jogging models and creative tools for
Speaker 14: the last eight years or so. When we started, it
Speaker 14: was hard. Jenneyvi I wasn't really a thing, and people
Speaker 14: told us we were crazy, Like Jenndyvi, I was never
Speaker 14: going to be a thing.
Speaker 5: Really, I did as little as four years.
Speaker 16: Yeah, four years. I will be broiled at Chris. This
Speaker 16: is not a thing.
Speaker 14: JENNEYV is not a market And so the one thing
Speaker 14: that I think has changed now is I don't have
Speaker 14: to convince more people that this is worth paying attention to.
Speaker 14: That's that's for sure. But we're very fortunate to be
Speaker 14: able to work with investors that believed in that very
Speaker 14: early on, where perhaps they're wandering as much proof points
Speaker 14: and it's a long term bad. But I go back
Speaker 14: to the mentioned before, it's still.
Speaker 4: Very early, and a lot of one need to be
Speaker 4: built around.
Speaker 14: The industry at large is still yet to be built,
Speaker 14: and so there's a lot of opportunities for more investors
Speaker 14: to invest in more kind of likes in you can't
Speaker 14: really speak about like fundraising, but I think the industry
Speaker 14: at large will will continue to grow very very.
Speaker 4: Fast, all right, Chris Balezuela, see a runway. Good to
Speaker 4: see David Cumming on the show. Keep us updated. Now
Speaker 4: when this one physics teacher isn't in the middle of
Speaker 4: a physics lesson, he's in the middle of building one
Speaker 4: of the world's biggest free AI training data sets. His
Speaker 4: Bloomberg Zaggie Cantrell with.
Speaker 17: More Luranza's time DAI one came out and I was
Speaker 17: instantly wow, Wow, this is so extremely powerful, Like now
Speaker 17: we can draw images from text and this will change everything.
Speaker 17: And I instantly understood that if this is like centralized
Speaker 17: to one, two or three companies, this will have really
Speaker 17: bad effects for society.
Speaker 18: We've taught for months about the benefits and pitfalls of
Speaker 18: artificial intelligence, but what we talked a lot less about
Speaker 18: is that these AI products are built on decades of
Speaker 18: data from across the Internet. One data set, which has
Speaker 18: been used to train image generators Stable Diffusion and Google's
Speaker 18: Imagen is called.
Speaker 4: Lion five B.
Speaker 18: Lion five B was created by a team of hobbyists,
Speaker 18: including a high school student in London and a high
Speaker 18: school teacher in Hamburg. Lyon is built on open source data.
Speaker 18: It scrapes public images from across the web and anyone
Speaker 18: can see what's in it. Stability AI, the company behind
Speaker 18: Stable Diffusion, is now seeking a four billion dollar valuation
Speaker 18: thanks in a large part to the free data from Lyon.
Speaker 17: I think it's really important for this technology, the models
Speaker 17: we train, the data sets we produce to stay openly accessible.
Speaker 18: But after discovering that their work was used to train
Speaker 18: Stable Diffusion, artists are now suing Stability. Lyon is cited
Speaker 18: in these suits, but not as a defendant. It's still
Speaker 18: an open question if these artists work, or any images
Speaker 18: that are publicly available online a fair game for these
Speaker 18: data sets. An answer may come soon with the European
Speaker 18: Union's AI Act, a government's first ever serious effort to
Speaker 18: regulate our ti official intelligence.
Speaker 4: If you want society to embrace technology and to trust technology,
Speaker 4: you need to have that social contract with society.
Speaker 18: The generative AI boom has also generated calls to ensure
Speaker 18: that companies disclose what images train their machines. Models like Openaies,
Speaker 18: Daly Too, and chat GBT, for example, have not really
Speaker 18: shared any details about their databases. While such regulation could
Speaker 18: be a win for artists and creators, advocates for open
Speaker 18: source data sets believe over regulation will only benefit big
Speaker 18: tech in the long run.
Speaker 17: If we try to slow things down and over regulate,
Speaker 17: there's a big danger that in the end a few
Speaker 17: big corporate players can afford to fulfill all formal requirements,
Speaker 17: and in the end this technology and all data that
Speaker 17: flows through it, will it be monopolized or at least
Speaker 17: highly centralized.
Speaker 16: And I see this as the real danger.
Speaker 18: As AI data sets and the rules around them are
Speaker 18: being developed in tandem, the question remains how closely should
Speaker 18: we regulate what goes into them?
Speaker 4: That was the latest from Bloomberg Zaggie count out of Germany. Now,
Speaker 4: the CEO of NBC Universal is leaving after admitting to
Speaker 4: an inappropriate relationship with an employee. In a statement after
Speaker 4: an investigation, Jeff Shell said he deeply regrets the incident.
Speaker 4: He served as CEO since January twenty twenty and worked
Speaker 4: at NBC Universal parent Comcast for almost two decades. A
Speaker 4: replacement has not yet been announced.
Speaker 3: Caroline and just sticking with media, just check out the
Speaker 3: market capitalization hit to Fox today. Seven hundred million dollars
Speaker 3: has been lost as it's down four percent.
Speaker 5: Why but as parting ways with Taker, Carlson.
Speaker 3: Seems to be the real catalyst of the news, it's
Speaker 3: most popular primetime host we know, also the source of
Speaker 3: repeated controversy over his statements and everything from election fairness
Speaker 3: to LGBTQ rights. We currently see also plenty more news
Speaker 3: coming from the medial world.
Speaker 5: We're going to dig into that in a little bit.
Speaker 5: But meanwhile, coming up, we're going to dig in more to.
Speaker 3: Artificial intelligence, of course, and its impact on wealth management.
Speaker 3: We're going to be joined by Sarah Hoffman, vice president
Speaker 3: of AI Machine Learning Research at Fidelity Investments.
Speaker 5: That's next, listen Bloomberg.
Speaker 4: Time now for the VC roundup. Aerodyne Group, a Malaysian
Speaker 4: drone services company, has picked City Group for a funding
Speaker 4: round ahead of its planned IPO. According to sources, the
Speaker 4: startup seeking to raise up to two hundred million dollars
Speaker 4: and aims to make its first close in midyear, ahead
Speaker 4: of an IPO in twenty twenty four or five. And
Speaker 4: Schroeder's a shareholder in the UK financial technology company Revolute,
Speaker 4: has cut the value of its stake by forty six percent.
Speaker 4: This is the second right down to hit the company
Speaker 4: after the fintech's firms auditors raised questions on its twenty
Speaker 4: twenty one revenue.
Speaker 3: Caroline and we're going to stick a bit on the
Speaker 3: world of fintech, but we're going to focus in on
Speaker 3: the impact of artificial intelligence on it because we've talked
Speaker 3: about perhaps how AI is affecting yours and my life
Speaker 3: in general generative AI, but what about wealth management in particular.
Speaker 3: We've got a bit of an optimist in the house,
Speaker 3: Sarah Hoffman, and vice president of AI and Machine learning
Speaker 3: research over at Fidelity Investments, And really what takes us
Speaker 3: about some of your thoughts in AI and wealth management.
Speaker 3: There is the way in which you think chat, GBT
Speaker 3: or those sorts of large language models could assist with
Speaker 3: upgrading our approach to financial literacy.
Speaker 5: How do you see that happening?
Speaker 13: Yeah, so obviously the financial world has become so complicated
Speaker 13: and would really want more people to be able to
Speaker 13: access and under stand finances and one thing that I
Speaker 13: could see happening with generative AI. I mean, we've been
Speaker 13: talking about per personalization for so long, but this technology
Speaker 13: really takes personalization to the next level when it comes
Speaker 13: to any type of education, but specifically financial literacy, which
Speaker 13: is so complicated. You can ask this technology, you know,
Speaker 13: explain this to me as though I'm a fourth grader,
Speaker 13: Or if you're somebody who's very into sports, you could say,
Speaker 13: explain this to me with a sports metaphor we can
Speaker 13: all really learn in our own way now, which is
Speaker 13: super powerful.
Speaker 3: Yeah, I've already been doing it to explain it to
Speaker 3: my five year old I'm interested in those serah As
Speaker 3: to how much information you talk about personalization, how much
Speaker 3: are people willing to share their own financial information and
Speaker 3: asking for examples and advice?
Speaker 5: Shall we say it by chat ChiPT? How right is
Speaker 5: that to do it at the moment as well?
Speaker 13: Right now, I would not recommend using it for advice,
Speaker 13: but I do believe this could be great before you
Speaker 13: meet with a financial representative. So if a customer could
Speaker 13: really learn on their own before that meeting, and even
Speaker 13: the financial representative could use these tools before the meeting,
Speaker 13: I think we can have a much better, more informed
Speaker 13: discussion with better questions where even though I think the
Speaker 13: human is still essential, everybody's gaining and coming in a
Speaker 13: better place.
Speaker 4: Sarah, I'm interested in you and what you're up to
Speaker 4: at Fidelity. Give me a typical day in the life
Speaker 4: of Sarah Hoffman working in the field of machine learning
Speaker 4: and AI.
Speaker 13: But at Fidelity, I focus specifically on what's coming with
Speaker 13: technology over the next five years. Fidelity is a company
Speaker 13: that really wants to make sure we are ready for
Speaker 13: what's coming across our business units, and so at Fidelity
Speaker 13: we focus specifically on building the next generation digital platform.
Speaker 13: I'll also focusing on the human element of the industry,
Speaker 13: which we believe is very important, and so my role
Speaker 13: specifically is really making sure we are aware of the
Speaker 13: trends that are coming.
Speaker 4: Would you say that you work closely more internally with
Speaker 4: your technology teams or how close are you also working
Speaker 4: with the investment teams to basically say, look, this is
Speaker 4: a tool that we could use and here's how we
Speaker 4: might potentially use it.
Speaker 2: Yeah.
Speaker 13: So I write research papers and give presentations and talks
Speaker 13: and have dialogue across the company across roles and for
Speaker 13: both of these types of roles.
Speaker 3: And how much so is everybody chat GIPT to help
Speaker 3: write those research papers now.
Speaker 13: Sarah, I've tried, I would right now. One of the
Speaker 13: main issues with tools like chat GPT is that they
Speaker 13: really don't have current information, so you can't really rely
Speaker 13: on it for if you're looking for trends or anything
Speaker 13: that's it doesn't understand or know about what's happening right now.
Speaker 13: But it's still useful for if you're trying to figure
Speaker 13: out a nice structure or even brainstorming. You know, how
Speaker 13: can generative AI be useful in wealth management? It's a
Speaker 13: useful brainstorming tool, but because it doesn't know today, I
Speaker 13: wouldn't recommend it to trust it blindly. One nice thing
Speaker 13: I would add about using it for brainstorming is that
Speaker 13: today it could produce things that you cannot trust. And
Speaker 13: when it comes to brainstorming and trying to find a
Speaker 13: novel insight, it doesn't actually matter if you can't verify
Speaker 13: the results, as long as it helps you think more
Speaker 13: creatively and think differently. So to me, brainstorming is actually
Speaker 13: a perfect use case for these tools.
Speaker 4: Sarah.
Speaker 3: It was interesting we just had Chris Valenzuela on who's
Speaker 3: the CEO of Runway, thinking about generative AI and the
Speaker 3: world of creation and particularly in images. But he said
Speaker 3: when four or five years ago he was speaking to
Speaker 3: vcs and they were like.
Speaker 5: Generative AI is not a thing. It's not going to
Speaker 5: be thing.
Speaker 3: Did you, as someone who has to look at what's
Speaker 3: the trend in four or five years, see this coming?
Speaker 5: So I saw this coming.
Speaker 13: I would save me personally with GPT three, the previous
Speaker 13: version of chat GPT which was released in twenty twenty,
Speaker 13: it was so much better than and your generative AI
Speaker 13: existed before, but this was so much better than anything
Speaker 13: we had seen before that you know that I and
Speaker 13: many others were, you know, looking at you know, how can,
Speaker 13: what can?
Speaker 5: What does this mean?
Speaker 13: Basically, the conversations that started in November with everybody else
Speaker 13: really started back in twenty twenty, twenty twenty one with
Speaker 13: GPT three. For those of us in the AI world.
Speaker 3: Sarah Hoffmann me thank you for audio advice and was
Speaker 3: back to them. Vice president of AI and Machine Learning
Speaker 3: Research every Fidelity Investments, there is quite the whirlwind. Immediate
Speaker 3: departures today from Tucker Carlson departing Fox News immediately sending
Speaker 3: Fox shares plunging, as we've already seen in the showdown
Speaker 3: six hundred million dollars in terms of market cap.
Speaker 5: We've also seen CNN star anchor Don Lemon.
Speaker 3: Leaving after being under intense scrutiny following remarks all went
Speaker 3: back in February about women and aging. Let's break all
Speaker 3: of this down. I Meg's Felix Chillette extraordinary. Let's start
Speaker 3: with Tucker Carlson. How much is this linked to settlements
Speaker 3: with voting systems in the life.
Speaker 19: I think it's definitely fallout from the dominion settlement. Rupert
Speaker 19: Murdoch in the past has shown that during times of
Speaker 19: controversy he's totally willing to get rid of talent. And
Speaker 19: if you think back to the phone hacking scandal, closing
Speaker 19: News of the World, getting rid of writers reporters left
Speaker 19: and right, I think you know Murdoch has always felt
Speaker 19: confident that he can replace the talent, even if it's
Speaker 19: someone like Tucker Carlson, who's currently the top rated primetime
Speaker 19: host for Fox News. You think back of when Fox
Speaker 19: News got rid of Glenn Beck reread events, Meg and Kelly,
Speaker 19: they're always this question, Oh, how are they going to recover?
Speaker 19: And yet whoever they plug into those time slots always
Speaker 19: seem to do quite well.
Speaker 4: Felix, our colleagues at Bloomberg Intelligence have a react out
Speaker 4: at pointing out Fox News two point two billion dollars
Speaker 4: of EBIT DARR or seventy percent of profits. You can
Speaker 4: see why there's that market reaction. CNN Don Lemon, what
Speaker 4: do we know?
Speaker 19: Don Lemon has been, you know, going from one controversy
Speaker 19: to the next for the last couple of months. They
Speaker 19: brought him back after he made these comments about Nicki
Speaker 19: Haley that upset people. You know, the problem with Don
Speaker 19: Lemon is not only is the generating negative headlines for CNN,
Speaker 19: but also the ratings have been lousy. So combine those
Speaker 19: two things. Chris Lick, who's overseeing CNN now for Warner
Speaker 19: Brothers Discovery, has been under a lot of pressure. You know,
Speaker 19: ratings have been way down ever since Donald Trump left
Speaker 19: office for CNN, and so the fact that they would
Speaker 19: make this switch, it almost seems surprising to me that
Speaker 19: they haven't done this previously.
Speaker 3: Felix Jalet with the inside track and what is a
Speaker 3: whirlwinder headlines we'll let him get back to his analysis
Speaker 3: of reporting.
Speaker 5: We thank you so much.
Speaker 3: Meanwhile, Oh, quite an extraordinary start to a Monday, and Ed,
Speaker 3: I thank you for rolling with my rather horse voice.
Speaker 3: I wasn't at partying, I'm afraid to say.
Speaker 5: But that does it for this edition of Bloomberg Technology.
Speaker 3: Tune in tomorrow for our gear up the coverage, your
Speaker 3: coverage of RSA cybersecurity conference over in San Francisco.
Speaker 5: We got the eighteen t COO among many more.
Speaker 4: Yeah. Look, huge weeks of earnings, just megacap names coming left,
Speaker 4: right and center. If you want to recap, don't forget.
Speaker 4: We have the podcast on Bloomberg or other platforms where
Speaker 4: you get your podcasts. So much to think on. This
Speaker 4: is Bloomberg