Speaker 1: From the heart of where innovation, money and power collide
Speaker 1: in Silicon Valley and beyond. This is Bloomberg Technology with
Speaker 1: Caroline Hyde and Ed Ludlow.
Speaker 2: Live from New York. I'm Caroline Hyde Man.
Speaker 3: I'm Jim Steinbeck in San Francisco. This is Bloomberg Technology
Speaker 3: Coming up.
Speaker 2: Alphabet is set to acquire cloud security firm Whiz for
Speaker 2: thirty two billion dollars in cash. The acquisition is Alphabet's
Speaker 2: largest to date. Plus all eyes on Invidios CEO Jensen
Speaker 2: Wang is set to take the stage in a few
Speaker 2: hours as investors seek clarity on Blackwell Ultra and the
Speaker 2: next AI chip breakthrough, and Chinese car Make is a
Speaker 2: gaining market share globally. This is BYD's souls. On the
Speaker 2: news of its five minute charging system, Alphabet off by
Speaker 2: more than three percent market fools, but also after a
Speaker 2: huge acquisition is announced. It's biggest ever and it's going
Speaker 2: to be leaning into cloud security with the help of Wiz.
Speaker 2: This is just a five year old company, tim and
Speaker 2: it's back by VCS. It's going to be a bit
Speaker 2: of a payday if they can get it secured by
Speaker 2: twenty twenty six. But phenomenal Ride for these group of
Speaker 2: full founders who built once before and sold out to
Speaker 2: Microsoft back in twenty fifteen. This time it's Google's chance.
Speaker 3: He had incredible track record and incredible what they've done
Speaker 3: in five years. From more on Google's Whiz acquisition, Bloombergs
Speaker 3: Katie Roof joins us. Now, Katie, you've been following this
Speaker 3: for the last ten months. Wiz spurned the offer of
Speaker 3: twenty three billion dollars over the summer, apart from the
Speaker 3: additional nine billion dollars. What changed, that's right?
Speaker 4: Well, yes, obviously they had nine billion more reasons to
Speaker 4: say yes. But also one thing that's changed is the
Speaker 4: regulatory environment and at least the perception that it will
Speaker 4: be better under this regulatory environment. Yes, we've been following
Speaker 4: this for ten months. We started to hear rumors and
Speaker 4: even two months before they leaked last year. The talks
Speaker 4: first began at RSA, this big security convention last year,
Speaker 4: so it's been going on for a while.
Speaker 2: What's so interesting, Yes, ar ours have increased significantly after
Speaker 2: the last eight months, we understand, and that vindicates the
Speaker 2: price point. But for a thirty two billion dollar price
Speaker 2: tag and a company that's going to remain independent there's
Speaker 2: actually still going to be multi cloud provision. It's not
Speaker 2: just going to be selling into Alphabet customers. When it
Speaker 2: comes to cloud, it's still going to be servicing aw
Speaker 2: West and as you it's a pretty phenomenal deal.
Speaker 4: Absolutely, it's definitely a phenomenal deal for Whiz. But you know,
Speaker 4: it just shows how threatened Google feels right now about
Speaker 4: security and how you know, worried they are about competing
Speaker 4: with Microsoft and Amazon growing AI related security threats, and
Speaker 4: you know they're willing to pay the price. And granted,
Speaker 4: you know, Google can easily afford this. It's a high
Speaker 4: number for Wiz, but you know, these trillion dollar companies
Speaker 4: can can make these multi you know, billion dollar deals
Speaker 4: happen quite easily.
Speaker 3: Does it move the needle with competition in the cloud
Speaker 3: space as we just talked about, you have AWS number one,
Speaker 3: you have Microsoft Azure number two. Google Cloud is in
Speaker 3: third place? Can it compete now that it has or
Speaker 3: if the Whiz deal goes through?
Speaker 4: I mean that will be the question that remains to
Speaker 4: be seen. But you know, certainly that's their goal here.
Speaker 4: They really are hoping that you know, look, Whiz that's
Speaker 4: only been around just a few years, quickly gained the
Speaker 4: significant percentage of the fortune one hundred customers, and you
Speaker 4: know they want to be able to sell this as
Speaker 4: part of their offerings, you know, certainly, you know, as
Speaker 4: Caroline noted, it can still work with the competitors, but
Speaker 4: Google clearly has this on their team right now. I'm
Speaker 4: sure Whiz will you know, maybe continue to work with
Speaker 4: them and innovate, you know, under the umbrella of Google.
Speaker 2: What's interesting is they could have fundraised in the private
Speaker 2: market still, they could have ide an IPO, but they've
Speaker 2: gone this particular route. Who wins out? Remind us of
Speaker 2: the vcs that have bat this from day one.
Speaker 4: Sure, so you've got Index, You've got Sequoia, You've got Cyberstarts,
Speaker 4: which is a hot Israeli security firm. Those are all
Speaker 4: on the board. You also have Insight partners on the
Speaker 4: board as well. But they've also been backed by Green
Speaker 4: Oaks and light Speed and Injrecing and they have such
Speaker 4: a long list of you know, top tiers Silicon Valley
Speaker 4: investors that were throwing money at this thing. It was
Speaker 4: practically born a unicorn, was it was so highly valued
Speaker 4: when it first launched several years ago, and so there
Speaker 4: have been big believers in this company for a while.
Speaker 4: They felt like, you know, just you know, hit the
Speaker 4: ground running.
Speaker 2: Katie move, thanks so much on all angles on Wiz
Speaker 2: and Google. Meanwhile, we turn our attention to win Video
Speaker 2: the Global Artificial Intelligence Conferences upon us GtC expect you
Speaker 2: to give developers and investors insight into the company's future
Speaker 2: AI chip plans as well as of course we're awaiting
Speaker 2: CEO Jensen Huang's keynote speech, Let's bringing Bloomberg Intelligence is
Speaker 2: Man Deep Sing look earnings. Jensen couldn't quite get the
Speaker 2: investor base to get excited about the new scaling law,
Speaker 2: which is reasoning models. What is he going to be
Speaker 2: able to convince us this time?
Speaker 5: Well, I assume the focus will be on AI agents
Speaker 5: and inferencing, given the market has clearly made that pivot
Speaker 5: post Deep Seek. Everyone is focused more on you know,
Speaker 5: reasoning and inference time scaling. And even though we are
Speaker 5: talking about scaling laws, I mean, it's fair to say
Speaker 5: everyone isn't very excited about pre training anymore. Where you
Speaker 5: are spending you know, ten billion dollars upfront and training
Speaker 5: just the next version of your model. So I would
Speaker 5: assume Jensen will try and convey that, you know, reasoning
Speaker 5: models do require a lot of GPUs, and in video
Speaker 5: GPUs are still the most popular when it comes to
Speaker 5: inference time reasoning. But clearly, you know, Google spending thirty
Speaker 5: two billion dollars on an acquisition takes away some of
Speaker 5: that capex they could have spent acquiring and GPUs. So
Speaker 5: you have to remember four customers contribute forty five percent
Speaker 5: of Nvidia's revenue. Now, if they're doing more deals and
Speaker 5: deals of this magnitude, that will play into the KPEX
Speaker 5: expectations for next year.
Speaker 3: So Mandip is that your view that reasoning that inference
Speaker 3: still does use as much compute as training these llms.
Speaker 5: So it changes the nature of compute. Remember you know
Speaker 5: when you were training models with bigger clusters as Grock three,
Speaker 5: did you know with two hundred thousand GPUs you required
Speaker 5: those all as a cluster. Now, if you're doing more
Speaker 5: inference time reasoning, you don't require one data center with
Speaker 5: you know, giant cluster. You can have it distributed for
Speaker 5: latency purposes. And that's where you know, if you are
Speaker 5: a hyperscaler, you are looking at different options a different
Speaker 5: custom A six because these AI agents are performing different tasks.
Speaker 5: It's not all text based chat pots. It could be
Speaker 5: you know, audio based image generation. So some ACX solutions
Speaker 5: could work. And Broadcom did talk about, you know, adding
Speaker 5: four new customers when it comes to their ACIX. So
Speaker 5: clearly there are a lot of moving parts when it
Speaker 5: comes to inferencing. But that's what I think Jensen would
Speaker 5: focus on during his keynote.
Speaker 2: It is interesting actually reports today of how much Amazon
Speaker 2: is thinking about the price point of its homegrown chips
Speaker 2: at the moment and where it can serve an inference
Speaker 2: and inferentia. But when you've got that sort of level
Speaker 2: of competition, they have to keep saying we've got the
Speaker 2: next thing. We've got the next thing, So talk about
Speaker 2: the next thing. We've got Blackwell Ultra and then the
Speaker 2: next iteration of the AI chip.
Speaker 5: I mean, look, in Vidia's value proposition is they can
Speaker 5: do so much more with one chip in terms of
Speaker 5: power efficiency and the compute they give versus the alternative.
Speaker 5: So Amazon may have a chip, but it's not the
Speaker 5: same price power performance that in Video is giving you
Speaker 5: with one chip. And that's their value proposition that you
Speaker 5: have the Kuda layer when it comes to you know,
Speaker 5: the cluster that you're running on for in Vidia. So
Speaker 5: all the standardization does make a difference. But hyperscalers worry
Speaker 5: about you know, costs not there what they're paying this year,
Speaker 5: but five years down line, ten years down line, so
Speaker 5: they're thinking long term, and you want to move away
Speaker 5: from Nvidia given the size of you know, the investments,
Speaker 5: say I'm making with the compute right now.
Speaker 3: That was Bloomberg Intelligence is at Mandeep Sing joining us
Speaker 3: in New York. Mande thanks so much. Well, let's talk
Speaker 3: more about what investors will be looking for from GtC
Speaker 3: and Jensen Wong's keynote later today. We're joined by Daniel Pilling,
Speaker 3: portfolio manager and a senior research analyst at Sans Capital. Daniel,
Speaker 3: good to see you. What do you want to hear
Speaker 3: from Jensen today that will convince you, that will convince
Speaker 3: other investors that earnings growth and indeed growth of the
Speaker 3: company has not peaked.
Speaker 6: Good morning, Yes, So I think, first of all, I
Speaker 6: agree with the reasoning pop process and the inference spright.
Speaker 6: So in France is becoming much more compute intensive. It
Speaker 6: can be up to one hundred two thousand times more
Speaker 6: compute intensive. In Vidia is the biggest player in that
Speaker 6: by far, and you know the hoote would be a
Speaker 6: Jensen will share some of his long term strategy, a
Speaker 6: sort of how does he capture and continue to gain
Speaker 6: market share with any imprints. Now, the second thing though
Speaker 6: I would say, is I actually think that the training
Speaker 6: the scaling laws within training are not entirely dead yet
Speaker 6: either both in pre training and post training. And my
Speaker 6: guess would be that their company, I in Vidia, will
Speaker 6: confirm that as well. Now this year we're going to
Speaker 6: see the big black ball clusters scaling. That's going to
Speaker 6: be a ten x improvement versus lausity for sure. And
Speaker 6: the secondly, also we have this reinforcement learning without humans
Speaker 6: in the loop that deep Seek has shown that seems
Speaker 6: to describe another scaling law in post training, and as
Speaker 6: far as we can see, that has driven a lot
Speaker 6: of a ton of them training demat and which you
Speaker 6: can see actually frankly on GitHub and hugging space in
Speaker 6: terms of the number of deep Seek models. And then
Speaker 6: the three and the third thing, if I may say,
Speaker 6: there's going to be a lot of talk about physical
Speaker 6: AI that's going through its s curve as we speak.
Speaker 6: You can see that in Weimo right in San Francisco
Speaker 6: there twenty percent market share, and I think there's going
Speaker 6: to be a lot of talk about agents, but frankly,
Speaker 6: that's a little bit further out. It's nice if they
Speaker 6: talk about that, but I think it's more important to
Speaker 6: talk about inference, scaling and trading.
Speaker 2: Skilling, really interesting points. He's often paid lip service to
Speaker 2: Elon Musk and Tesla, for example, maybe a bit with Memo.
Speaker 2: Maybe in the future of robotics as well, Daniel, I'm
Speaker 2: interested in the rampant pace at which now we see
Speaker 2: Jensen put out new products. We're going to hear a
Speaker 2: lot about Blackwell Ultra the next iteration. We're also going
Speaker 2: to hear about Rubin I'm sure, which is in the
Speaker 2: next AI breakthrough. Can they really develop at this pace
Speaker 2: because we saw the sort of supply chain hiccups with
Speaker 2: back Well as it rolled out.
Speaker 6: Yes, So I think the answer is yes. And I'll
Speaker 6: tell you why. They have the best people. They are
Speaker 6: the most people's folkusing those product, and they have the
Speaker 6: biggest R and D fools, and they have the most
Speaker 6: capacity to Taiwan Seti And I think the interesting counter
Speaker 6: question to this, though, is to say, can the others
Speaker 6: even follow? Right? So for example, big hyperscalers, they all
Speaker 6: try to develop their own ship. They're trying to do
Speaker 6: this with a partner. They're not doing it all alone,
Speaker 6: which means that they're trying to optimize the system by themselves.
Speaker 6: And video is optimizing the systems by themselves, whereas the
Speaker 6: others are doing with partners, which is going to make
Speaker 6: it much, much, much more difficult to compete in a video.
Speaker 6: So I think the answer is yes, and I think
Speaker 6: that crais a lot of competitive differentiation versus anybody else.
Speaker 3: Daniel, you mentioned physical AI, and I'm curious what you
Speaker 3: think is the realistic form factor when it comes to
Speaker 3: physical AI and just how far out we are from that.
Speaker 6: Yeah, so we thought about this a lot as well.
Speaker 6: So it's clear that the big, big, big physical AI
Speaker 6: revenue growth driver in the next one to two years
Speaker 6: is going to be self driving at leastent not in
Speaker 6: our opinion. Why because you can see it in San
Speaker 6: Francisco ready. The experience is amazing when you drive away
Speaker 6: old people. They have twenty percent market share. They're moving
Speaker 6: to many other cities and this is just the beginning, right,
Speaker 6: They have a tiny, tiny market Shante with total milage.
Speaker 6: Now the humanoids they're pretty interesting as well, but arguably
Speaker 6: a little bit further away. So in our opinion, is
Speaker 6: going to be self driving vehicles within big cities the
Speaker 6: next one to two years. That should drive a massive
Speaker 6: explosion in terms of influence. The van which benefits in video,
Speaker 6: but many many other players on the supply Machaine as well.
Speaker 2: Daniel, how far away is quantum because we actually heard
Speaker 2: as sort of a long time rage maybe up to
Speaker 2: two decades coming from Jensen, but now he's actually sitting
Speaker 2: on a panel around quantum and trying to make it
Speaker 2: a quantum day.
Speaker 6: Yes, so we think quantum computing is sort of maybe
Speaker 6: in the eighties in terms of where semiconductors work like
Speaker 6: at that time here right, So it's a long time out.
Speaker 6: The reason for that is, first of all, there's no
Speaker 6: Kuda equivalent as of today at pcent for quantum computing,
Speaker 6: so you can't actually really use it easily. And secondly,
Speaker 6: the scaling of the cubas has proven to be quite
Speaker 6: difficult now, so it's at least ten to fifteen twenty
Speaker 6: years out in terms of a use case potentially, And
Speaker 6: I would actually argue if in Video plays their cards well,
Speaker 6: then quantum computing could be one of the parts of
Speaker 6: utation they offer in the very very long term, alongside
Speaker 6: the GPUs, CPUs and whatever else the PU You might
Speaker 6: have a.
Speaker 2: We want to thank you, Daniel Pelling, always fascinating catching
Speaker 2: up with your portfolio manager and senior research analyst at
Speaker 2: Sam's Capital. Meanwhile, we have some breaking news for you,
Speaker 2: because of course the phone call has begun. Russian President
Speaker 2: Vladimir Putin and Donald Trump have been speaking on the
Speaker 2: phone today. We understand that the White House confirmed talk
Speaker 2: started at ten am Eastern time. Discussions are said to
Speaker 2: be related, of course, to the end of the war
Speaker 2: with Ukraine, a key objective being a thirty day truce
Speaker 2: with Kiev. As already we understand Kiev has accepted. That
Speaker 2: will bring you any more breaking news on that.
Speaker 3: Well, let's take a look at some China tech names,
Speaker 3: starting with the ride hailing app d d Global. Think
Speaker 3: of it as China's answer to Uber. It did swing
Speaker 3: back to a quarterly loss and it's a blow to
Speaker 3: the company that's exploring a Hong Kong listing this year.
Speaker 3: You can see shares on the day lower by about
Speaker 3: three percent. Dedi has had an inconsistent recovery since that
Speaker 3: regulatory crackdown a few years ago. That was when it
Speaker 3: was delisted from the New York Stock Exchange. They lost
Speaker 3: much of its market value. This after Beijing cracked down
Speaker 3: on data sharing practices among big tech companies, and Shallomi
Speaker 3: shares are higher right now. Revenue in the fourth quarter
Speaker 3: beat the average general's estimate. The company CEO also said
Speaker 3: it's delivered two hundred thousand vehicles and its race its
Speaker 3: target this year from three hundred thousand to three hundred
Speaker 3: and fifty thousand vehicles. Shares hire right now by about
Speaker 3: three point three percent, Caroline.
Speaker 2: Isn't that extraordinary that we know that Shaomi first got
Speaker 2: into the EV market only in the summer of last year,
Speaker 2: and now they're pumping out two hundred thousand and likely
Speaker 2: to increase it to three hundred and fifty, all the
Speaker 2: while that we're seeing just the Chinese EV sector go
Speaker 2: from strength to strength. Also in innovation, I mean, what
Speaker 2: did you make of BYD's pop today?
Speaker 3: Yeah, I mean it's pretty incredible. Five minute charging. I
Speaker 3: mean that's really what led to that pop today, And
Speaker 3: if you think about it from the perspective of somebody
Speaker 3: who has an EV and maybe has range anxiety. That
Speaker 3: is a game changer. If it takes just the same
Speaker 3: amount of time for you to charge your vehicle as
Speaker 3: it does to go to a gas station, then boom.
Speaker 3: That's kind of the golden goose when it comes to
Speaker 3: this tech caroline.
Speaker 2: But not everyone can get access to those coolden goose,
Speaker 2: or at least those eggs, because that European countries can
Speaker 2: buy the Hanel or the tang L, the latest that's
Speaker 2: going to be coming from BYD with this new electric
Speaker 2: charging technology, but not in the US. And let's just
Speaker 2: talk about that, because of course President Trump is hoping
Speaker 2: his tarifts are actually going to continue to combat cheaper
Speaker 2: Chinese cars and stop them mentoring the US market. Already
Speaker 2: you can't access BYD, for example, but outside of the US,
Speaker 2: Chinese automakers have really established a global presence. It's today's
Speaker 2: big take story. He discusses one of the authors of
Speaker 2: the piece, Chester Dawson, And let's just take BYD for
Speaker 2: as a case study here. Chester, they have just come
Speaker 2: from behind to end up being well basically the world's
Speaker 2: biggest EV maker, and they're doing it by accessing the
Speaker 2: emerging markets, not of course.
Speaker 7: The US, that's right, Yeah, I mean it is somewhat unusual.
Speaker 7: You know, typically when you have a fast rising new
Speaker 7: entrant in the automotive business, the first thing they want
Speaker 7: to do is get to the US because it's one
Speaker 7: of the richest and biggest markets around the world. But
Speaker 7: as you mentioned, you know, it's been kind of core
Speaker 7: to US economic policy and national security policy to start,
Speaker 7: you know, drawing up that drawbridge and protecting manufacture of cars.
Speaker 7: You know, obviously the Detroit Three, but also companies like
Speaker 7: Toyota that make a lot of cars in the US
Speaker 7: are not facing that competition. But as you say, technology
Speaker 7: doesn't stand still, and they're introducing some pretty impressive new developments.
Speaker 7: They're going to show up in places like maybe Johannesburg
Speaker 7: and you know, Bangkok before they get to the US.
Speaker 3: Do they ever get to the US? I mean, Chester
Speaker 3: people love these vehicles. Ford CEO Jim Farley a few
Speaker 3: months ago was quoted as really loving the Shallmi vehicle
Speaker 3: that he had been driving. That was a sort of
Speaker 3: big news in the US auto world. People love these cars.
Speaker 3: What do they love about them?
Speaker 7: Well, I think the one thing they love is the price.
Speaker 7: I mean they're very competitive, which is not to say
Speaker 7: they're I mean they're cheap in terms of the price,
Speaker 7: but they're not junk. They come with some pretty impressive
Speaker 7: features and creature comforts. You know, as you noted at
Speaker 7: the outset. You know Shaomi, which used to make cell
Speaker 7: phones kind of like you know, the Apple on the iPhone,
Speaker 7: but in China they quickly moved into cars and you know,
Speaker 7: they're now projected to be making seven times what Rivian,
Speaker 7: a US electronic electric vehicle startup, wants to make, and
Speaker 7: that's in large part due to the fact that you know,
Speaker 7: they're very user friendly. So yeah, it's it's no surprise.
Speaker 7: They're good price and pretty good quality as well.
Speaker 3: Bluemberg's Chester, Dawson, Chester. Always good to see you, Thanks
Speaker 3: so much for joining us. Coming up, we're going to
Speaker 3: look at Google's impact in the health sector, all with AI.
Speaker 3: This is Bloomberg. Google is expanding its health related AI
Speaker 3: summaries and search to improve its influence in the health sector.
Speaker 3: Answers will now cover thousands more health topics and expand
Speaker 3: more countries and languages. The company is also adding a
Speaker 3: separate feature in search called what People Suggest, which it
Speaker 3: said aims to provide users with information from people with
Speaker 3: similar lived medical experiences.
Speaker 2: Here on tim Yeah. Google also said it has been
Speaker 2: updating a new AI system to help researchers speed up
Speaker 2: the scientific en biomedical discoveries. For example Google's AI Coscientist tool.
Speaker 2: It's an AI system meant to act basically as a
Speaker 2: virtual collaborator for buy my scientists. I actually got to
Speaker 2: sit down with Ane Lisa Polowski, founder and principal investigator
Speaker 2: for the Accelerated Science Biochemistry and Molecular Biology Lab over
Speaker 2: at Google. I asked her to walk us through what
Speaker 2: this looks like. Take a listen.
Speaker 8: The idea is we've built a system that works together
Speaker 8: with scientists. So, for instance, if it's a Friday afternoon,
Speaker 8: I'm in my lab. I have all these ideas I
Speaker 8: want to explore, but I have my two kids at home,
Speaker 8: and so I can actually plug in a research goal
Speaker 8: into the system, check the ideas it's creating and the
Speaker 8: evolution over time, and by Monday morning, I have a
Speaker 8: bunch of different approaches I can use for my research.
Speaker 2: Ultimately, there's been much said a Lisa about how JENATAI
Speaker 2: can bring fruits to bear when it comes to healthcare,
Speaker 2: when it comes to research, when it comes to tackling disease,
Speaker 2: Is this the reality that you're currently thinking can be
Speaker 2: the help with a co scientist an AI coscientist.
Speaker 8: We're at the early stages of the project. So in
Speaker 8: our paper we show these three examples. So we've seen
Speaker 8: that there is evidence in this direction and we're looking
Speaker 8: forward to leaning in more and showing more keep abilities
Speaker 8: as we extend this work.
Speaker 2: Has there been any friction or should I say just
Speaker 2: reticence by the scientific community to allow models to juke
Speaker 2: it out on their areas of focus over a weekend
Speaker 2: while they sort of down tools.
Speaker 8: There can be skepticism, but as a scientist, skepticism is good, right.
Speaker 8: It encourages that we push ourselves, that we create a
Speaker 8: system that's useful and something that's impactful for the community.
Speaker 2: How have you stress tested it? For many the limitations
Speaker 2: degenerative AI and for agents is well the fact that
Speaker 2: they do sometimes get things wrong. When have you seen
Speaker 2: that occur? And how have you managed to cab to
Speaker 2: balance it right?
Speaker 8: So no large language model is perfect, but we try
Speaker 8: to supplement this with novelty and checkness reviews. We both
Speaker 8: use the literature that's available and web search. We add
Speaker 8: in tools and databases, and we're learning to extend our
Speaker 8: work into knowledge crafts and other strategies where we can
Speaker 8: improve and refine on our techniques. The other thing is
Speaker 8: we're looking to the community for feedback, so we created
Speaker 8: a Trusted Tester program and we welcome and open those
Speaker 8: different idea approaches to how we can improve AA coos.
Speaker 2: Scientists, Google research analyst and scientist and Alisa Pawski. They're
Speaker 2: ahead of the key Google Health event in New York
Speaker 2: coming up in Vidio's GtC has investors focused on the
Speaker 2: AI outlook. Locks Capital's Grace is fruders with us and
Speaker 2: to join to talk all about the startups and where
Speaker 2: she's finding opportunities for the technology. This is Blue Meg Technology.
Speaker 2: Welcome back to Blue Meg Technology. I'm Caroline Hide in
Speaker 2: New York, Man.
Speaker 3: I'm Tim Stanovek in San Francisco.
Speaker 2: Quick check on these markets, Tim, because risk off at
Speaker 2: the moment, many reasons for investors to be anxious. You've
Speaker 2: got the FED later today. What do tariffs actually mean
Speaker 2: for the US economy? What does Middle East and instability
Speaker 2: once again mean in terms of a flight to Haven's
Speaker 2: golds that are record but the nasdaqc's off by one
Speaker 2: point eight percent. We're seeing Bitcoin another key risk, ASSEID
Speaker 2: No Choice off by two point five percent. We're only
Speaker 2: at eighty one thousand. Now move on some of the
Speaker 2: individual names that have tried to keep above water but fail.
Speaker 2: Nvidia is one of the key point strikes on the day.
Speaker 2: Even as we look ahead to GtC and the keynote
Speaker 2: coming of course from Jensen Huang at one pm Eastern time.
Speaker 2: Can he reinject optimism into the need for his GPUs
Speaker 2: for inference as well as training. I'm looking at alphabet
Speaker 2: making a big purchase thirty two billion dollars for Whiz
Speaker 2: down three and a half percent, as indeed the entire
Speaker 2: market sinks. I'm looking at Meta though off by almost
Speaker 2: five percent. This was the one magnificent seven name that
Speaker 2: actually was in the green for the year, not anymore
Speaker 2: when out the lowest since November the twenty nine to ten.
Speaker 3: Well, let's see what Katherine and runey Vera has to say.
Speaker 3: She's stone X's group Chief Market Strategies and she joins us. Now, Catherine,
Speaker 3: you saw what Caroline was talking about there with Tech
Speaker 3: under pressure, the Nasdaq one hundred and only eight of
Speaker 3: the one hundred socks in the green right. Now, what's
Speaker 3: your outlook for the sector?
Speaker 9: Well, it depends on what happens with rates. This is
Speaker 9: a very rate sensitive sector.
Speaker 10: So with treasury yields high three and a half two,
Speaker 10: sorry for four thirty to fifty, that squeezes long duration
Speaker 10: growth stocks, and that's unwinding some of these more crowded trades.
Speaker 9: I think that's probably one of the biggest drivers of
Speaker 9: Tech's moved to the downside. Then, of course we have
Speaker 9: any type of broad market correction, given that TECH is
Speaker 9: about thirty percent of the SMP's market cap, if it
Speaker 9: is vulnerable as well to any risk off trade which
Speaker 9: could be precipitated by trade tensions or anything of the like.
Speaker 9: I think it's also entering a mature phase so that
Speaker 9: anything AI related no longer gets this immediate bump up.
Speaker 9: But now the market is starting to be more discerning
Speaker 9: and more aware of massive capital spending and the potential
Speaker 9: for less capital spending going forward, especially with the introduction
Speaker 9: of lower cost chips and competition.
Speaker 2: Within a video though for example, let's just use that
Speaker 2: as the pin up now trading at twenty five times
Speaker 2: future earnings. A lot of floth has come out of
Speaker 2: the valuations. At what point do we start to get
Speaker 2: dip buying, do you think, Catherine.
Speaker 9: I suspect we soon will. A ten percent correction is something,
Speaker 9: but it certainly doesn't unwind the frothiness that we've seen
Speaker 9: in the run up for AI stocks in general over
Speaker 9: the past several years. And I'll add one point, which
Speaker 9: I think is that what you're seeing is a resetting
Speaker 9: of value expectations and a move out of tech and
Speaker 9: into second derivative AI plays such as industrials and even energy.
Speaker 9: You're seeing financials catching a bit. My top pick for
Speaker 9: this year is healthcare, and the reason for that is
Speaker 9: both because it's defensive, so it's a nice hedge of
Speaker 9: your bets, but also because it was the worst performing
Speaker 9: sector last year. And if effectively we do get a
Speaker 9: purchase of the dip and a resumption to the upside
Speaker 9: of the S and P by year end, then my
Speaker 9: suspicion is that the most beaten up sector from last
Speaker 9: year will become one of the better performing sectors as
Speaker 9: those value investors come in.
Speaker 2: I mean, even right thus far, this year, healthcare has
Speaker 2: been the winning formula and financials text languishing near the bottom.
Speaker 2: I use another case study in Tesla because last year,
Speaker 2: since the election results, Tesla didn't trade off fundamentals, it
Speaker 2: traded on vibes and an association with the White House.
Speaker 2: When we go back to vibes again, if ever, I
Speaker 2: mean does it? Is it a case in point and
Speaker 2: once yields stopped, we do start to see the upside
Speaker 2: and risk hunger just returns like that or are we
Speaker 2: in a totally different paradigm right now?
Speaker 9: I think you make a really good point. I think
Speaker 9: the vibe shift now is less focused on inflation and
Speaker 9: the FED and it's more focused on tariff. So we
Speaker 9: have to ask ourselves the biggest component of the S
Speaker 9: and P how vulnerable is it to tariff's and is
Speaker 9: this tariff fear a real threat to economic growth? And
Speaker 9: what we did was we looked back at President Trump
Speaker 9: one point zero and.
Speaker 11: Even the Federal Reserve came out with a recent analysis
Speaker 11: quantifying caroline the impact of core PCE from Donald Trump
Speaker 11: one point oh twenty seventeen, twenty eighteen to twenty nineteen tariffs,
Speaker 11: and they quantified it at zero point five percentage points
Speaker 11: addition to core PCE.
Speaker 9: Now, the impact on final goods back then was a
Speaker 9: one year effect before it rolled off, and then we
Speaker 9: saw intermediate goods have a longer lasting impact to the
Speaker 9: upside on prices. This time is slightly different because supply
Speaker 9: chains have already adjusted, so that means that new tariffs
Speaker 9: would hit margins and earnings rather than spark inflation. So
Speaker 9: my concern is that, you know, additional tariffs will directly
Speaker 9: impact market sentiment and that will bring additional downside to tech.
Speaker 9: So my call has paid off pretty well, which is
Speaker 9: stay long tech, buyputs on tech now that trade is
Speaker 9: looking really awesome. I put it in when tech was
Speaker 9: at all time highs, but now what we see is
Speaker 9: that put volumes are at all time record highs. So
Speaker 9: now it's expensive to do, but it has been it
Speaker 9: has proven to be a very good.
Speaker 8: Trade, Catherine.
Speaker 3: Up to now, we've seen the main beneficiaries of the
Speaker 3: AI boom be the chip makers and the hyper scalers.
Speaker 3: Right to what extent are we seeing other companies and
Speaker 3: other sectors within the S and P five hundred for example,
Speaker 3: adopt this technology and has it hit their margins?
Speaker 9: Yet Yeah, you're right, and this has been a kind
Speaker 9: of a buzzword more than wholesale adoption, and the market
Speaker 9: is looking for results at this point, so enough talking,
Speaker 9: and we want to see deployment, not only deployment, but
Speaker 9: full execution and earnings. So there's been massive investments in
Speaker 9: this space. I think at this point, as I said before,
Speaker 9: I think it's we're in a mature face. We want
Speaker 9: to look for second order effects, so second order investment
Speaker 9: opportunities that are indirect beneficiaries or perhaps the second wave
Speaker 9: beneficiaries of this large scale, massive capex in AI. Last year,
Speaker 9: I recommended utilities. Utilities was one of the top performing
Speaker 9: sectors last year, and my recommendation was because it's, you know,
Speaker 9: second derivative to AI. Now, I think we need to
Speaker 9: be looking at data center operators, cloud infrastructure, medical, real estate, financials.
Speaker 9: I think there are second order effects. That's where the
Speaker 9: bang is for the coming for coming years in a
Speaker 9: structural way.
Speaker 3: Which sector do you think will take advantage of it
Speaker 3: the most?
Speaker 9: Well, I still like healthcare. I think there's going to
Speaker 9: be a lot of deployment of AI in the in
Speaker 9: the sector, and I like it one for that reason.
Speaker 9: And two also because it's a nice defensive sector. So
Speaker 9: that's going to be my top pick for this year,
Speaker 9: just as utilities was last year. So they're nice because
Speaker 9: they're both defensive and they could potentially benefit from additional upside.
Speaker 2: Katherin Rooney Vera of stone X Group. Always great to
Speaker 2: catch up. Thank you, Tim Well, So I'm now for
Speaker 2: talking tech.
Speaker 3: Starting into space. Two NASA astronauts our returning home in
Speaker 3: a SpaceX craft after being stuck in orbit for nine months.
Speaker 3: The astronauts undocked from the International Space Station last night
Speaker 3: and are expected to splash down off the Florida coast
Speaker 3: later today, where they will undergo medical checks and be
Speaker 3: reunited with their families. Plus Apple lost it fed at
Speaker 3: Germany's top civil court to overturn a regulator's decision to
Speaker 3: put it under tighter antitrust scrutiny alongside other US tech giants.
Speaker 3: The court cited apples a vertically integrated products and services,
Speaker 3: it's importance for third party access to markets, and its
Speaker 3: potential to harm competition as reasons for the decision. And
Speaker 3: Cognition Ai, the developer of an AI powered coding assistant,
Speaker 3: has raised hundreds of millions of dollars at evaluation close
Speaker 3: to four billion dollars. That's, according to sources, around doubles
Speaker 3: the previous valuation of the startup, which released its generative
Speaker 3: AI coding tool a year ago.
Speaker 2: Caroline, let's stick more on general to AI, THEAI sector,
Speaker 2: Written Large and VC Spotlight. Chray Isford is with us
Speaker 2: panner at Lux Capital, focusing on emerging opportunities in artificial intelligence.
Speaker 2: You're based here in New York and you're on the
Speaker 2: board or focus in and helping with the investments in
Speaker 2: certain pinups. I think of Runway and I think of
Speaker 2: together AI for example. How are we seeing the application
Speaker 2: there AI starting to return real value because at the
Speaker 2: moment everyone has been so focused on the foundational and
Speaker 2: the infrastructure layer. Are we starting to read rewards?
Speaker 12: For the last few years, we've really seen enterprises focusing
Speaker 12: on foundational AI. Now we're seeing that shift, as you say,
Speaker 12: to the applications applications of AI and doubling down into
Speaker 12: the twenty twenty five year year of the agents. Actually,
Speaker 12: we've been talking a lot about AI agents in enterprise production.
Speaker 12: We just talked about where are we actually seeing that impact.
Speaker 12: We're seeing it across our portfolio in really three main areas,
Speaker 12: one encoding, two in customer support, and three in sales.
Speaker 12: And I'll give you one quick example on that. On
Speaker 12: the real ROI and impact we're seeing. There's a company
Speaker 12: called niven Agi. They're an AI agent for customer support.
Speaker 12: They are seeing real enterprise impact, integrating with those legacy
Speaker 12: systems and working with public companies to actually solve these
Speaker 12: tickets in a fraction of the time, at a fraction
Speaker 12: of the cost, driving that real value.
Speaker 2: What's interesting is we just had Daniel Pilling Sance Capital
Speaker 2: on who's an investor in someone Nvidia. His theory is
Speaker 2: actually sort of physical AI, which I know you've also
Speaker 2: invested in. The physical AI is actually in many ways
Speaker 2: closer than a agentic AI in terms of the real rewards.
Speaker 2: What do you make of that sort of time frame
Speaker 2: and when we start to see more bountiful effects of agentic.
Speaker 12: AI, Well, it depends how you define AA agents. Then
Speaker 12: that's actually part of the confusion, right, everyone has their
Speaker 12: own definition, right for my purposes, For engineers I talk
Speaker 12: to across our portfolio, it's really an autonomous system where
Speaker 12: an LM is directing its own actions across a series
Speaker 12: of steps, and these agents are getting better and better
Speaker 12: or not really seeing that truly verifiable loop in fields
Speaker 12: that are not kind of coding customer support sales. It's
Speaker 12: because in fact, they're actually difficult to integrate with right
Speaker 12: And that's kind of a funny kind of the irony
Speaker 12: in the space right now. If you look at the
Speaker 12: physical world, we've seen text and image highly repeatable, highly
Speaker 12: verifiable tasks, whether it's in the sciences or whether it's
Speaker 12: in math. But as you start to get to these
Speaker 12: proprietary data trops I'm talking robotics, I'm talking warehouses, I'm
Speaker 12: talking data and manufacturing, where you have to tap into
Speaker 12: this proprietary workflow of data, even for a biologist or chemists,
Speaker 12: and you have to not just get that data, but
Speaker 12: also integrate it with the workflow. That's where we're seeing
Speaker 12: really exciting advancements. But it's still early from seeing that
Speaker 12: real enterprise ROI grace.
Speaker 3: It does seem like the opportunities that you just spoke
Speaker 3: about are really all enterprise focused. Really, you know, thinking
Speaker 3: about it B to B, what does it look like
Speaker 3: for consumers if this technology is adopted on a wide scale.
Speaker 12: Well, I'll give a simple example on that. You know,
Speaker 12: I tried to piog a flight from New York to
Speaker 12: San Francisco using open a eyes operator a few weeks ago.
Speaker 12: Simple tasks in theory, sure of flight lots of us do.
Speaker 12: In reality, it's pretty complex. You know, you need to
Speaker 12: get the right airline, you need to get the right airport,
Speaker 12: you need to get the right time, and all my preferences.
Speaker 12: And so that's a common issue we're seeing. These AI
Speaker 12: agents are complex systems with compound I need errors. So
Speaker 12: even if there's one little error like not getting access
Speaker 12: to that one criteria, it compounds across that fifty steps
Speaker 12: in the agentic system. So from a consumer experience perspective,
Speaker 12: it can be pretty frustrating when you don't book that
Speaker 12: flight exactly the way you want it.
Speaker 3: Are you seeing crowding out come from big companies right now?
Speaker 3: You have the hyper scaler's valued at multi trillion dollars?
Speaker 3: Is there an opportunity for small companies to come in
Speaker 3: and actually provide solutions and complement these hyper scalers complement
Speaker 3: these large chip companies most definitely.
Speaker 12: In fact, we're seeing it across our own portfolio. I'll
Speaker 12: give another example. They are called together AI. They're an
Speaker 12: open source AI cloud. They actually help you run and
Speaker 12: productize these fantastic open source models, and you can use
Speaker 12: them not using a cloud provider in tandem or working
Speaker 12: in tandem with your own existing suite of tools. And
Speaker 12: so you're seeing the emergence of this new AI infrastructure stack,
Speaker 12: which is still nascent but exciting, where you're using these
Speaker 12: cheaper chips, you're actually using these open source and even
Speaker 12: smaller models to achieve that same outcome.
Speaker 2: We're looking at your portfolio companies and some of them
Speaker 2: have international flavors and certainly hugging face I think a
Speaker 2: climb over there running that business to in Sikana AI
Speaker 2: as well Tokyo based. At this moment where we're almost
Speaker 2: putting up this race of China versus the US, what
Speaker 2: are the talent pools are you looking to for AI
Speaker 2: expertise and excellence?
Speaker 12: Well, AI expertise is everywhere, and I think if you
Speaker 12: focus on China for a second, right, China has fantastic
Speaker 12: engineers and researchers, and I think Deep Seek was a
Speaker 12: lot of a wake up call for the US whe
Speaker 12: were saying, wow, you know whatever you thought deep Sea
Speaker 12: cost to train it was a true feat of hardware
Speaker 12: efficiency and engineering efficiency, and I actually think that's a
Speaker 12: blueprint we're going to see us internationally, So not just
Speaker 12: in Japan with companies like Sicana AI using those smaller
Speaker 12: agent based models, also in France with companies like Mistral
Speaker 12: building really really strong AI open source models as well.
Speaker 12: But how do you actually leverage and do more with less?
Speaker 12: How do you use less compute? How do you actually
Speaker 12: use more efficient chips in fact cheaper chips and actually
Speaker 12: have a more effe AI infrastructure stack using that open
Speaker 12: source technology grace here.
Speaker 3: In the US to change an administration not even two
Speaker 3: months ago. I'm curious about how you view the landscape
Speaker 3: differently now that somebody like David Sachs, for example, whom
Speaker 3: Caroline and Jackie spoke to just a couple of weeks ago,
Speaker 3: is in the position as ais are. Do you see
Speaker 3: a difference in the landscape here.
Speaker 12: I think it's early to know, but we're really seeing
Speaker 12: a huge excitement for the AI industry and really the
Speaker 12: industry being invigorated. Right we just talked about deepseek as
Speaker 12: that being a wake up call to invest more heavily
Speaker 12: in engineering startups in awesome AI startups who are building
Speaker 12: right here on US soil and who are actually leveraging
Speaker 12: this open source and transparent innovation to ultimately create really
Speaker 12: exciting applications. I'm really excited for new AI applications in
Speaker 12: some of those physical AI areas we talked about earlier.
Speaker 12: So robotics, space, defense, and manufacturing all have those proprietary
Speaker 12: data sources and that unique workflow you need to understand
Speaker 12: the workflow of a defense contractor if you're actually building
Speaker 12: a fantastic application. So that mix of kind of public
Speaker 12: and private is something that's really exciting.
Speaker 3: Melox Capitals Grace Isford, Grace, thanks so much for joining us.
Speaker 3: Do appreciate it well. Coming out a lawsuit alleges that
Speaker 3: Google and the startup character Ai are to blame for
Speaker 3: the death of a fourteen year old boy. Who will
Speaker 3: discuss the claims and the implications for Silicon Valley. This
Speaker 3: is Bloomberg. In February of last year, fourteen year old
Speaker 3: Sewell Setzer took his own life. His mother blames the
Speaker 3: chatbot he spent months messaging with. Now she issuing character Ai.
Speaker 3: It's the company behind the bot and Google, which has
Speaker 3: a partnership with the startup. Let's bring in Bloomberg's Malathi Nayak.
Speaker 3: She joins us here in San Francisco, Malafi. This is
Speaker 3: just a heart wrenching story. We're going to get to
Speaker 3: the legal implications in just a minute, but what happened here.
Speaker 13: So this is a story about a young boy who
Speaker 13: began using this chatpot technology and he got romantically involved
Speaker 13: with the chat pot that he created himself, sort of
Speaker 13: inspired by a character from Game of Thrones, and he
Speaker 13: got really sort of caught up in this chatbot. You know.
Speaker 13: His mother says that he began to sort of withdraw
Speaker 13: from his friends, was having trouble at school, you know.
Speaker 13: After a few months, and at some point the parents
Speaker 13: decided to confiscate his phone, and while looking for the phone,
Speaker 13: he happened to find his stepfather's gun, which was hidden
Speaker 13: in their home in compliance with Florida law where the
Speaker 13: family lived, and he sort of, you know, Goddess phone,
Speaker 13: had this last conversation where he was talking about sort
Speaker 13: of coming home to this chat pot and then he
Speaker 13: you know, he just sort of took the gun to
Speaker 13: his head and shot himself. So it's a tragic story,
Speaker 13: and there is a lawsuit now which the mother has
Speaker 13: filed against Character Ai, which created this chat pot technology,
Speaker 13: as well as Google, which has an interesting sort of
Speaker 13: deal with this AI startup, and it sort of brings
Speaker 13: into question these sort of new deal structures in AI
Speaker 13: where companies technology companies are not really buying these startups outright,
Speaker 13: but they are instead of buying the assets, they're sort
Speaker 13: of investing in these technologies in a very sort of
Speaker 13: unusual way where they're hiring the talent and they're just
Speaker 13: licensing the technology. So there's no real full blown acquisition here.
Speaker 13: And it's possible that, yeah, it's possible that these deals
Speaker 13: were sort of structured this way because last year with
Speaker 13: the Biden administration, we saw a crackdown and mergers and
Speaker 13: acquisitions where you know, big companies were not allowed to
Speaker 13: scoop up their smaller rivals. So it's possible that these
Speaker 13: deals were structured that way. But it's sort of interesting
Speaker 13: that the lawsuit sort of brings these deals into the
Speaker 13: spotlight and sort of questions the legality of the sort
Speaker 13: of relationship between these big dear companies and these smaller
Speaker 13: startups right multi.
Speaker 2: Garcia's lawyers say in the complaint that Google in particular
Speaker 2: contributed financial resources, personnel, intellectual property, and AI technology to
Speaker 2: the design and development of character AI's chatbots. We must
Speaker 2: be clear that both Google and of course character Ai
Speaker 2: dispute any responsibility in terms. They have come back and
Speaker 2: certainly stated that Google and character ai are completely separate
Speaker 2: and unrelated companies, so says Google. What has been the response?
Speaker 2: When do we see it play out? Briefly?
Speaker 13: So in a few months, we'll have a hearing on
Speaker 13: the motion to dismiss where Google and a character ai are.
Speaker 13: We'll try to convince the Florida Fredrikrourt to actually throw
Speaker 13: out this case and sort of so that it won't
Speaker 13: proceed further. So we'll see that play out in a
Speaker 13: few months. But we've seen what Google and character I
Speaker 13: have said. They've said they're separate companies, that they're not
Speaker 13: related to each other. And Google says that it's sort
Speaker 13: of involvement as an investor, as the mother calls it,
Speaker 13: or through a cloud services partnership, that bet that they
Speaker 13: both had or the fact that they had this deal
Speaker 13: doesn't sort of, you know, implicate it in any way
Speaker 13: or sort of is sort of tenuously connected to the
Speaker 13: harm that was caused here, and in a lot of
Speaker 13: these cases, yes, as we've seen with say Autopilot and
Speaker 13: Tesla too, it's very hard to sort of, you know,
Speaker 13: connect the harm to the technology. So you know, this
Speaker 13: whole question about who's to blame here is sort of
Speaker 13: a big one and still sort of unraveling in courts
Speaker 13: when it comes to different technologies. And in this case,
Speaker 13: you know, AI is coming to the forefront in terms
Speaker 13: of these new up and coming AI technologies that are
Speaker 13: getting really popular. And you know who is to blame
Speaker 13: when things go wrong? And you know, when there are
Speaker 13: unexpected turns like this one, blame.
Speaker 2: Magis malt nayak. It's a story that people must go
Speaker 2: and read. We thank you so much. Sticking with all
Speaker 2: things AI and Vidia CEO Johnsen Wang is set to
Speaker 2: deliver his keynote addressed in just a few hours time
Speaker 2: at GtC. What can we expect when most common ranicky
Speaker 2: is here and well the shares are selling off in anticipation,
Speaker 2: So what can you do to study people's nerves?
Speaker 14: Yeah, so what people are really looking for here is
Speaker 14: some near term visibility and optimism in what Invidia has coming.
Speaker 14: So some of the biggest things that they're looking for
Speaker 14: are comments on Blackwell Ultra, which is expected in the
Speaker 14: second half of the year, rubin other updates in next
Speaker 14: gen GPUs. I think the other thing that people are
Speaker 14: really looking for from Jensen is countering the bear case here,
Speaker 14: which was really sparked by deep Seek earlier this year,
Speaker 14: and that is really just saying that you know, there
Speaker 14: won't be a cyclical downturn in spending from these big
Speaker 14: AI companies, that they don't have too much AI compute
Speaker 14: going right now, and that Invidia will still be sort
Speaker 14: of the top of mind, you know, chip maker place
Speaker 14: that they're buying for you know, much time to come.
Speaker 2: Have we seen any dip buying ahead of this, you know.
Speaker 14: Dip buying and Invidia has been really interesting this year.
Speaker 14: Usually we see people rushing back in so quickly to
Speaker 14: buy the dip, and this year we've seen investors really
Speaker 14: let the stock draw down much more than it has
Speaker 14: in the past. So, I mean it's down for the
Speaker 14: last two days that you know, is after having a
Speaker 14: big sell off, So we really haven't seen a ton
Speaker 14: of diffying two.
Speaker 2: Point eight trillion dollar company only come in Ryanikey, thank
Speaker 2: you so much for joining us. That does it from
Speaker 2: this edition of Blueberg Technology. Don't forget to check out
Speaker 2: our podcast. You can find it on the terminal as
Speaker 2: well as online on Apple, Spotify, and iHeart This is
Speaker 2: Bluemberg Technology