Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is alive
Speaker 1: from coast to coast with Caroline Hide in New York
Speaker 1: and Eva Low in Sent Francisco.
Speaker 2: This is Bloomberg Tech coming up. The US combust Department
Speaker 2: moves closer to allowing Nvidia to sell its h two
Speaker 2: hundred AI chips to China.
Speaker 3: Plus robotics startup Skilled Ai just closed a one point
Speaker 3: four billion dollar funding round, tripling its valuation in seven months.
Speaker 4: We'll discuss with the CEO Depact PAPAC.
Speaker 2: And Netflix is working to revise its bid for Warner
Speaker 2: Brothers Discovery, shifting to an all cash offer.
Speaker 3: As you see though those names in the red and
Speaker 3: in general the market on the downside, we still got
Speaker 3: geopolitical anxiety, We've still got earnings coming thick and fast,
Speaker 3: and we've still got and as that one hundred off
Speaker 3: by one and a half percent, not so in the
Speaker 3: world of come on to a search for safety a
Speaker 3: bid as the dollar falls. We see two point eight
Speaker 3: percent higher on the bitcoin rally, so maybe a bit
Speaker 3: of catch up with digital gold where we see spot
Speaker 3: gold and a new record high up seven tens percent.
Speaker 3: Copper all important commodity to our world of AI and
Speaker 3: data center zed we ran a new record high on
Speaker 3: an interday basis. We're up five tens percent just coming
Speaker 3: off of that high on the day. But en it's
Speaker 3: notable and shift of this year.
Speaker 2: Right, rules and requirements are changing in the world of
Speaker 2: AI chips. The US Commerce Department out with clarification which
Speaker 2: impacts in video and it's H two hundred that it
Speaker 2: wants to shift to China, but also impacts AMD as well.
Speaker 2: AMD has been trading all over the place this morning,
Speaker 2: at one point notably higher in the session, but in
Speaker 2: Vidia markedly down now trading at its lowest level in
Speaker 2: around a month. What are these new rules and what
Speaker 2: do they mean and why is this significant? Bloomberg Senior
Speaker 2: Tech editor Mike Shepherd joins us out of DC lay
Speaker 2: out the new rules and requirements for US. But what
Speaker 2: we're saying in the Bloomberg story is this marks a
Speaker 2: significant moment for the companies in their efforts to set
Speaker 2: into China.
Speaker 5: Why well, this is a small but critical bureaucratic step
Speaker 5: that paves the way for Nvidia and and D to
Speaker 5: be able to sell H two hundred incomparable AI chips
Speaker 5: to China. What it does is it now says that
Speaker 5: the US government will review requests for export licenses on
Speaker 5: a case by case basis and move away from the
Speaker 5: past policy of a presumption of denial of any such
Speaker 5: request and that had in the past been really an
Speaker 5: effective export ban. Now these companies can't be there expecting
Speaker 5: a rubber stamp for their requests. The US government is
Speaker 5: laying out some pretty specific requirements. One that the companies
Speaker 5: must show that the exports to China will not create
Speaker 5: a supply shortage here. This is addressing, in a way,
Speaker 5: some of the concerns that lawmakers here in Washington have
Speaker 5: been raising with attempts to pass their own version of
Speaker 5: export controls. Two, they must show that any manufacturing done
Speaker 5: for China must not displace any production capacity intended for
Speaker 5: US customers here. And three, the companies must implement strict
Speaker 5: know your Customer procedures to ensure that these chips and
Speaker 5: the related technology don't get out to unauthorized users.
Speaker 3: It's interesting, Mike, that we are seeing Nvidia down on
Speaker 3: the day AIMD. Do we get any sense of how
Speaker 3: many they might be able to ship, Because it's not
Speaker 3: without its intricacies as you say fifty percent of the
Speaker 3: overall made in the US.
Speaker 5: Well, it is the question of the moment surrounding this
Speaker 5: rule just how this cap that it lays out would function.
Speaker 5: The rule says that the exports to China can go
Speaker 5: more than no more than fifty percent of total product
Speaker 5: here in the US. But does that mean H two
Speaker 5: hundreds produced from this day going forward. If that's the case,
Speaker 5: it would not be a very big set and it
Speaker 5: would mean a far smaller number of exports to China,
Speaker 5: and that would certainly not go anywhere near meeting the
Speaker 5: huge demand that Jensen Wang has said that he is
Speaker 5: getting from Chinese customers. And we have reported that Ali
Speaker 5: Baba and Bite the Answer interested in buying as many
Speaker 5: as two hundred thousand chips each. Now, if we are
Speaker 5: talking about all the H two hundreds produce over all time,
Speaker 5: that would be a much bigger universe and that would
Speaker 5: be a much happier outcome for Nvidia, AMD and their investors.
Speaker 5: So we will have to see exactly how that is interpreted.
Speaker 6: If that gets spelled out.
Speaker 5: Another big question Caro is answered, how quickly the government
Speaker 5: can move to actually process these export requests. Because we
Speaker 5: have been hearing over the past year and longer that
Speaker 5: they are simply running into capacity problems in the bureaucracy
Speaker 5: at commerce and being able to turn these around.
Speaker 3: Bottlenecks throughout the world of AI. Mike Sheperd, thanks so much.
Speaker 3: Let's stick with what this means for Nvidia and more
Speaker 3: broadly for semiconductors. Beth Kennick's with us IO fun lead
Speaker 3: tech analyst. So, is this a fifty billion dollar annual
Speaker 3: revenue opportunity?
Speaker 4: Is China that for Nvidia?
Speaker 7: Hey, Caroline jensen Wok has stated it's a fifty billion
Speaker 7: per year annual opportunity. When we left off, it was
Speaker 7: about five billion a quarter. That's twenty five billion, so
Speaker 7: somewhere between twenty five billion and fifty billion, which really
Speaker 7: means that as we look into analyst estimates, they are
Speaker 7: probably too low. And that has been something from the
Speaker 7: very beginning that we have found Alpha in is that
Speaker 7: analysts are really struggling to wrap their head around the
Speaker 7: opportunity of Nvidia. And now here comes back the aged
Speaker 7: two hundreds, and where my firm is very focused is
Speaker 7: calendar year twenty twenty seven. If you look at these estimates,
Speaker 7: they are too low, as it is let alone if
Speaker 7: China revenue resumes.
Speaker 3: What's really interesting, though, is China's response to all of this.
Speaker 4: You say it's too low.
Speaker 3: How much might be the revenue for Nvidia in China.
Speaker 4: But at the same time we understand.
Speaker 3: That deep seats driving new models with seeing them use
Speaker 3: what they have in the different method that maybe Ali
Speaker 3: Barbara and why do you don't need those two hundred
Speaker 3: thousand that they've already put off efforts and offers in
Speaker 3: for what do you make of the way in which
Speaker 3: China is going to pivot to domestic chips?
Speaker 7: I would argue that right now the number I had
Speaker 7: was about two million, h two hundreds and there's only
Speaker 7: about seven hundred thousand available, which means that once again
Speaker 7: in videos oversubscribed. I have been asked before, who is
Speaker 7: the next in Vidia to something like Huawei, you know,
Speaker 7: is it Google's TPUs? And the answer is the next
Speaker 7: in Vidia is in video. They are extremely hard to disrupt,
Speaker 7: and that goes for China or even United States competitors BEV.
Speaker 2: Taking into account that the news story that Mike Shephard
Speaker 2: just brought us, Jensen Wong told us at CS that
Speaker 2: the five hundred billion dollar forecast for five fiscal quarters.
Speaker 2: It includes this one for Blackwell Rubin could get bigger
Speaker 2: because they could factor into H two hundred sales in
Speaker 2: twenty six. I know twenty seven to a year, but
Speaker 2: if you model for that little update that the Jensen
Speaker 2: one gave.
Speaker 7: Yes, so right now the analyst estimates did actually catch up.
Speaker 7: They're about three to twenty billion this calendar year. Let's
Speaker 7: just go with twenty twenty six. I want to really
Speaker 7: emphasize that its next calendar year that we're going to
Speaker 7: start to see analyst estimates too low. That is where
Speaker 7: the alpha is at right now, and it only takes
Speaker 7: one or two quarters for us to really see Nvidia's
Speaker 7: price movement from all of the all of the momentum
Speaker 7: we're seeing not only from Blackwell Ultra, but then we've
Speaker 7: got Vera Rubin second half of this year. Now we
Speaker 7: have the H two hundreds coming back. Where that falls
Speaker 7: specifically in what quarter matters less to me, and what
Speaker 7: matters more is that those analyst estimates are far too low.
Speaker 2: Bes The big story in global markets this morning is
Speaker 2: a blistering rally in metals, particularly copper copper, as S
Speaker 2: and P Global wrote January eight foundational to the expanding
Speaker 2: electricity supply that will power the data center build out,
Speaker 2: and it's now a big growth area in that market.
Speaker 2: How worried are you about that copper in the supply
Speaker 2: chain and how it relates to the power needs of
Speaker 2: the data centers that Nvidia's chips go into.
Speaker 7: These are excellent questions, and across the board resources when
Speaker 7: it comes to this data center expansion are extremely stretched,
Speaker 7: especially anything that supports the electrical grids, such as copper.
Speaker 7: What I would really emphasize is those alternative sources of
Speaker 7: energy is a great way to position going into twenty
Speaker 7: twenty six. One thing to my firm has dug up
Speaker 7: is that in order for us to get to VERA,
Speaker 7: Ruben and then Reuben Ultra power has to precede that
Speaker 7: we have to really get this power to these data
Speaker 7: centers before those systems can really ship in volume and
Speaker 7: be installed. Things like net gas, even solid oxide fuel cells,
Speaker 7: those that do not need great dependency on the electrical
Speaker 7: grid is a wonderful way to position, and copper surging
Speaker 7: today is a reminder of that.
Speaker 4: What's interesting is we've hit in video.
Speaker 3: We're talking about the supply chain therein we're also getting
Speaker 3: the idea that CPUs.
Speaker 4: As well at s US as well.
Speaker 3: And you just think about the moves that we've seen
Speaker 3: yesterday today in Intel, I mean, where do you think
Speaker 3: the glutts or the bottlenecks are really going to be
Speaker 3: hitting hard?
Speaker 4: We are?
Speaker 3: I mean, analysts keep Bank saying Intel and AMDA basically
Speaker 3: sold out for twenty twenty six on the CPU service
Speaker 3: side exactly.
Speaker 7: And what's even more interesting is that AMD was up
Speaker 7: more or last year than Nvidia, and they are such
Speaker 7: a strong CPU player as well as Intel. There are
Speaker 7: many bottlenecks. Caroline networking is another one that comes to mind.
Speaker 7: Of course, energy we just spoke about. Just keep in
Speaker 7: mind that it's not just GPUs, but there's almost an
Speaker 7: equal amount of money being spent on all of the components,
Speaker 7: all of the networking, all of the power, and we
Speaker 7: are no longer compute constraint, We're no longer GPU constraint.
Speaker 7: It really is becoming a power problem and a networking
Speaker 7: problem that needs to be solved, especially as we move
Speaker 7: into the inference market, which is only going to require
Speaker 7: more memory, more bandwidth, less latency, and more and more energy.
Speaker 2: Beth do AMD and Intel just accept that it's the
Speaker 2: CPU market where they can do battle and just let
Speaker 2: the accelertor market go to Nvidia and other specialists.
Speaker 4: No, I do not believe that will be the outcome.
Speaker 7: I think AMD is a strong contender, a strong number two,
Speaker 7: especially in the second half of this year. They've really
Speaker 7: been preparing to bring the rack scale architecture to market,
Speaker 7: which is called Helios and ED what was I've covered
Speaker 7: AMD very thoroughly and we could get into the specs
Speaker 7: all day long.
Speaker 4: But open AI giving them.
Speaker 7: That six gigawad deal is a massive nod. I mean
Speaker 7: that is a big nod that AMD is a contender
Speaker 7: from the leading R and D firm.
Speaker 2: Helios, AMD's first rack scale solution, but then in the
Speaker 2: world's first two nanimeter chip inside, which they talked up
Speaker 2: in our interview last week. Be f Kindig the IO Fund.
Speaker 2: Great to have you back on Bloomberg Tech. Thank you
Speaker 2: very much. Now coming up, anger grows over sexually explicit,
Speaker 2: non consensual AI generated images on x We have the latest.
Speaker 6: This is Bloomberg Tech.
Speaker 3: The Supreme Court still hasn't ruled on challenges to President
Speaker 3: Trump's tariffs, leaving the world to wait until at least
Speaker 3: next week to learn the fate of visits signature economic
Speaker 3: policy from a massurveillance. Co host Amriy Horden joins us
Speaker 3: right here for more. So we delay once again, and
Speaker 3: that timing could be awkward. It could be awkward. So
Speaker 3: Supreme Court punts it once again.
Speaker 8: They do not come out with the decision on whether
Speaker 8: or not the majority of Actually a lot of this
Speaker 8: terriphone venue we're bringing in into the United States, more
Speaker 8: than seventies percent, is tethered to the president using aiber flexible,
Speaker 8: a blunt tool that he has used since he came
Speaker 8: back into office. And why it could be so awkward
Speaker 8: is because the President will be in Davos next week
Speaker 8: and he's going to be meeting with global leaders, the
Speaker 8: world elite. Last year he joined on remote really Lambasstard,
Speaker 8: the global elite. And at this point, potentially we could
Speaker 8: get the decision next Tuesday or Wednesday, because that's when the.
Speaker 4: Justices will be meeting again.
Speaker 8: That's when potentially we can get the decision and he
Speaker 8: could potentially be facing a Supreme Court saying you cannot
Speaker 8: use that legal authority while he's talking to all these
Speaker 8: countries that he already did trade deals with.
Speaker 2: Bloomberg zamree, Howden, thank you very much. Another top story,
Speaker 2: the US Senate unanimously passed a bill allowing victims of
Speaker 2: sexually explicit AI images to sue the creators of that content.
Speaker 2: The move is in response to growing public anger after
Speaker 2: Bloomberg reported the Lelon musk x has become a top
Speaker 2: site for generating pictures of people who have been non
Speaker 2: consensually undressed by a must post it on x that
Speaker 2: he wasn't aware of any naked underage images generated by Grock.
Speaker 2: That's Xai's generative AI tool. Let's bring in Bloomberg's Emily Burnbaum,
Speaker 2: who covers corporate lobbying government. The Defiance Act confers on
Speaker 2: American citizens a civil right to sue, take that information
Speaker 2: and give the rest of the details. Because that's the
Speaker 2: bit that's new here.
Speaker 9: Yes, that's exactly what it does. It essentially empowers victims
Speaker 9: of this non consensual deep fake technology, people who have
Speaker 9: been non consensually undressed by this AI tool, and it
Speaker 9: allows them to sue the people responsible for posting that.
Speaker 9: And it's a companion to a bill, to a bill
Speaker 9: that was signed into law last year by President Trump
Speaker 9: that creates criminal penalties for distributing that kind of content.
Speaker 3: Ah, it didn't go through the House last time, the
Speaker 3: Defiance Act, whereas take Down did, And why would this
Speaker 3: time be any different?
Speaker 4: Is the pushback becoming enough.
Speaker 3: Because thus far, all we've really seen is the Department
Speaker 3: of Defense put groquai within its military system instead of
Speaker 3: pushing back on this being something that Grocco X needs
Speaker 3: to camp down in some way, that's true.
Speaker 9: There definitely is more of an appetite in Congress to
Speaker 9: pass this legislation. There have been six new co sponsors
Speaker 9: that have come on board since the beginning of the year.
Speaker 9: I think that the issue of non consensual AI generated
Speaker 9: images has become so vivid to lawmakers. Many of them,
Speaker 9: like Alexandria Ocasio Cortez, are themselves the victims of this.
Speaker 9: So I think the appetite has really broadened this year.
Speaker 2: Emily, where does the company X and the platform X
Speaker 2: fit into this in a citizen's right to sue and
Speaker 2: those that distribute the content.
Speaker 9: So the Defiance Act, which passed the Sunate this week,
Speaker 9: that probably would not impact GROC, that impacts the people
Speaker 9: who are responsible for distributing the images. But there is
Speaker 9: a lot of conversation right now about whether the Take
Speaker 9: It Down Act would empower Attorney's General to sue Grock
Speaker 9: Xai Elon Musk over some level of responsibility for you know,
Speaker 9: thousands of these images proliferating every hour.
Speaker 4: So far, no Attorney's.
Speaker 9: General have taken that up, but it's definitely under serious consideration.
Speaker 3: Certainly something that maybe Malaysia has been putting forward about
Speaker 3: whether or not it's Xai's responsibility in some way. Blueing
Speaker 3: Magzemine van Bound, fantastic reporting, thank you very much. Indeed,
Speaker 3: not coming up. ABMB has a new chief technology officer.
Speaker 3: We'll hear about his plans for the short term mental
Speaker 3: company that's next is.
Speaker 4: A body meg Tech.
Speaker 10: I'm extremely excited, like Brian said, to bring craft to
Speaker 10: the art of deploying AI first features and products. So
Speaker 10: I hope to be able to surprise the world with
Speaker 10: really beautiful features that they're going to love using every day.
Speaker 2: That was Airbnb's new CTO, Armadal Dala, weighing in on
Speaker 2: the short term rental platforms AI efforts. Let's get more
Speaker 2: wherever and Latterly Lung, who spoke with our Dala and
Speaker 2: Airbnb CEO Brian Chesky. I think an interesting base start
Speaker 2: is what is Airbnb trying to solve for here by
Speaker 2: bringing in a new CTO. What is it they want
Speaker 2: to change about the platform.
Speaker 11: So after a few years of sort of working on
Speaker 11: the plumbing of Airmb's app, like vamping the app, they
Speaker 11: are ready to take it forward, adding AI across the app,
Speaker 11: including customer service with which they did last year, and
Speaker 11: now they're going to do more with search as well,
Speaker 11: like letting people discover listings and also cross markets who
Speaker 11: have their new services like tours and experiences going forward.
Speaker 3: And I think you sort of put that exact question
Speaker 3: to Brancheski himself. Let's just take a listen to how
Speaker 3: he responded as to why they're pivoting and focusing all
Speaker 3: in on AI at this moment, and take a listen.
Speaker 12: We are at the beginning of this incredibly exciting technological
Speaker 12: transformation with AI. It's going to be a journey. And
Speaker 12: I couldn't be more excited about Ahmed because he's one
Speaker 12: of the leading AI experts in the world, but he
Speaker 12: also brings a sense of craft Airbnb, something we're really
Speaker 12: known for. And I think what you're going to see
Speaker 12: in Airbnb is not only AI search, but a very
Speaker 12: personalized AI experience where I think we're going to bring
Speaker 12: great design sensibility into the experience of Airbnb.
Speaker 3: Let's talk a little bit about how they're talking of
Speaker 3: the narrative of change because they've said farewell to the
Speaker 3: previous CTO who's there for about seven years, and brought
Speaker 3: in this expert from Meta. So who do they say
Speaker 3: you farewell to and why is this Meta executed the
Speaker 3: best place?
Speaker 11: So Aribalo, the previous CTO came in during our time
Speaker 11: when Airbnb was going through hypergrowth. There was seven more
Speaker 11: than seven years ago. And now Airbnb is sort of,
Speaker 11: as Cheskey said, going through a technological revolution of you
Speaker 11: know lms and chat agents, and now Airbnb sort of
Speaker 11: wants to use sort of the unique data they have
Speaker 11: on the platform to differentiate itself from other you know,
Speaker 11: chatbots to provide better recommendations to customers on their platform.
Speaker 2: Abnb the company who stock growse about three percent last year,
Speaker 2: down a couple of percent so far this year.
Speaker 6: And Cheski was one of those.
Speaker 2: People that was the early vocal behind founder mode it.
Speaker 2: What's the health of Airbnb right now. Is this them
Speaker 2: saying we've got to do something to re accelerate.
Speaker 11: Yeah, Brian was not satisfied with the below ten percent
Speaker 11: growth rate we've seen last year, and so he's been
Speaker 11: very active in wanting to pilot more businesses for this year.
Speaker 11: They're piloting boutique hotels and server cities, and they're trying
Speaker 11: to add grocery delivery for people to pre stock their
Speaker 11: kitchens before or are they check in. So they're trying
Speaker 11: to get their growth free BACKRUP as sort of the
Speaker 11: core rental service for chors.
Speaker 4: Now.
Speaker 3: So you've also got a story about how the chief
Speaker 3: information officer has departed after the CTO shakeup.
Speaker 4: Is there more executive leadership changes to come?
Speaker 11: Yeah, so there would be. They're still looking for the
Speaker 11: new CIO. We can expect that to come in in
Speaker 11: the months in the year ahead.
Speaker 3: Most Natalie Lung, thank you very much. Indeed, let's turn
Speaker 3: out attention to entertainment now. Netflix is working to revise
Speaker 3: it's been for Warner Brothers Discovery, potentially shifting to an
Speaker 3: all cash offer, according to sources. Now the moves aimed
Speaker 3: at speeding up a deal that lookers face pushback from
Speaker 3: Washington and competition from rival, bit of Paramounts guidance for more, Let's.
Speaker 4: Get to the new most.
Speaker 3: Lucas Shaw, who covers media and entertainment, hit this story
Speaker 3: hard and Lucas, I mean the all cash narrative. Why
Speaker 3: is that important? Why would that be the winning formula
Speaker 3: for Netflix?
Speaker 13: Because investors like cash now versus stock, and that's that
Speaker 13: they could sell later.
Speaker 11: Right.
Speaker 13: One of the knocks against the Netflix deal as perpetuated
Speaker 13: at least by by Paramounts guidance. The rival bidder has
Speaker 13: been that Paramount's deal is all cash, and that Netflix
Speaker 13: deal contains you know, between four and five dollars a.
Speaker 6: Share of stock.
Speaker 13: Now, Netflix stock is pretty valuable, something that you think
Speaker 13: people would want to have, but most people would rather
Speaker 13: just take the cash now and get paid. And so
Speaker 13: that I think Netflix hopes will accelerate on many fronts.
Speaker 11: It.
Speaker 13: You know, it'll assuage any shareholder concerns about their bid
Speaker 13: and also eliminate any potential complexities as they continue to
Speaker 13: negotiate and pursue it.
Speaker 2: Lucas, when we were reporting this out, you know, the
Speaker 2: Netflix response and the tit for tat, you know, Paramounts
Speaker 2: suing earlier this week and nominated our It's to the board.
Speaker 2: Do you get the sense that Netflix think this will work,
Speaker 2: that they now are back in sort of the lead
Speaker 2: in a tight race for the assets.
Speaker 6: Well, I don't.
Speaker 13: I think if you were to talk to the people
Speaker 13: at Netflix, they've never felt they were out of the lead,
Speaker 13: right know, they are obviously facing a stiff challenge from Paramount,
Speaker 13: but they're the ones who have an approved deal, and
Speaker 13: they have yet to see kind of some they have
Speaker 13: yet to see shareholders say and masks we don't want
Speaker 13: the Netflix deal. They have yet to see the federal
Speaker 13: government say we're going to block this deal. There are
Speaker 13: certainly some kind of blinking yellow lights, but I don't
Speaker 13: think they've they've seen anything yet that that gives makes
Speaker 13: them too concerned. They seem still pretty confident that they'll
Speaker 13: get this.
Speaker 3: Done and in a week January twenty first, that's when
Speaker 3: the tend to offer for certainly the Paramount Skuydance side
Speaker 3: of the equation runs out, right. I mean, do you
Speaker 3: get any signal for investors that they were tool interested
Speaker 3: in that side?
Speaker 13: You know, investors have been split some of the big
Speaker 13: investor investment funds, you know, they don't say anything, but
Speaker 13: we have spoken with a number of the major shareholders
Speaker 13: and I'd say their reactions range from we prefer Netflix,
Speaker 13: do we prefer Paramount, And then a lot of people
Speaker 13: in the middle are basically saying, you know, tie right
Speaker 13: now goes to the winner, which is Netflix. But we
Speaker 13: hope Slash expect that Paramount will increase its offer, which
Speaker 13: Lucas is a pretty clear Paramount move.
Speaker 2: Just very quickly remind us of the state of play.
Speaker 2: The difference between the two bids.
Speaker 13: Well, Netflix's bid is for just the studio and streaming service,
Speaker 13: so Warner Brothers and HBO. Paramount's bid is for the
Speaker 13: whole company, so that includes all the cable networks like CNNT, N,
Speaker 13: T TBS and the like.
Speaker 2: Bloombos Lucas Shaw, who leads the team at screen time,
Speaker 2: that has led the way on reporting this story.
Speaker 6: Thank you so much. Now coming up on Bloomberg.
Speaker 2: Tech, robotics startup Skilled Ai just closed a one point
Speaker 2: four billion dollar funding round, a big valuation, tripling.
Speaker 6: From a year. This is next. This is Bloomberg Tech.
Speaker 4: Welcome back to Bloomberg Tech. Let's check in on the
Speaker 4: markets that are under pressure.
Speaker 3: Look we've got a wall of warriors to come to
Speaker 3: the earning season geopolitical risks, and we see some dragged
Speaker 3: down and big tech. We're off by one point few
Speaker 3: percent on the NASDAK. In fact, two straight days of
Speaker 3: losses on the SMP. We're coming off of record highs
Speaker 3: in video, of course, confronting that news that maybe EAH
Speaker 3: two hundreds could be getting closer to exporting to China.
Speaker 3: But at the moment we're under pressure. It's one of
Speaker 3: the key drags on the downside. Bitcoin though, of three
Speaker 3: point four percent. We're seeing maybe a bit of love
Speaker 3: for digital gold, not just gold, silver and copper. We're
Speaker 3: also seeing maybe some shorts getting squeezed out. Move on,
Speaker 3: have a look at what's happening in individual stocks. I'm
Speaker 3: trying to light on Honeywell, look, we're at one point
Speaker 3: eight percent. Maybe an asset that it controls quantinum could
Speaker 3: be looking for an IPO. We're an understanding that they're
Speaker 3: potentially filing for an IPO with the SEC. We know
Speaker 3: that this last valuation was about eleven billion dollars Z
Speaker 3: We've got other key strategics and videos in their GP
Speaker 3: Morgans in there as well, so all eyes on quantum
Speaker 3: computing as we look towards twenty twenty six.
Speaker 4: What are you looking at?
Speaker 6: Yeah, we also have a big deal in private markets.
Speaker 2: Robotic startup Skilled Ai has just closed a one point
Speaker 2: four billion dollar funding around the valuation more than fourteen
Speaker 2: billion dollars and that's for a company only founded in
Speaker 2: twenty twenty three. Skilled is aiming to stand out in
Speaker 2: what's a crowded field by building an AI powered robotic brain.
Speaker 2: The goal is to develop a system that can adapt
Speaker 2: across environments and form factors and crucially learn from its
Speaker 2: own mistakes. Joining us to discuss a Skilled co founder
Speaker 2: and CEO, Deepak Pathak, It's great to have you on
Speaker 2: Bloomberg Tech. What's interesting. Let's start with the round. It's
Speaker 2: not just the volume, it's not just the valuation. Some
Speaker 2: of the strategics that are backing you in Nvidia, others
Speaker 2: in consumer electronics, Samsung LG and in the software sector
Speaker 2: as well. What are they recognizing is your core competence?
Speaker 6: Do you think so?
Speaker 14: If you're thinking about the robotics today is one of
Speaker 14: the oldest areas in technology. In EI was big for robotics.
Speaker 14: We have seen amazing they're more robotics for the last
Speaker 14: seventy years, not four or five years, seventy years. But
Speaker 14: we are robots around us. And this is what people
Speaker 14: often get wrong. When you think of robots in your mind,
Speaker 14: you imagine hardware like that comes to a point in
Speaker 14: your mind first, because that's how Hollywood has primed us.
Speaker 14: But the main thing in behind that not having robots
Speaker 14: around us today is the brain is missing. And if
Speaker 14: you have the brain for robots, you can really enable
Speaker 14: them around in variety of areas. We active applications, and
Speaker 14: that's what exactly SCARED is doing. We are building what
Speaker 14: we call only bodied brain, any robot, any task one brain.
Speaker 6: I'm interested in how you're building it.
Speaker 2: The limitation that a lot of people are talking about
Speaker 2: right now is real world data and training. There are
Speaker 2: different approaches digital twins, trying to simulate physics in digital worlds.
Speaker 2: This is very much what in video is focused on,
Speaker 2: right is that the approach you've taken simulated or synthetic data.
Speaker 14: So I think I will draw analogy to lllms like Jagpity,
Speaker 14: like models like if you see open a head Jadgepitty,
Speaker 14: And soon after many companies had their own LM models,
Speaker 14: and the reason for that is data exist on the
Speaker 14: Internet for language or vision, but robotics there is no
Speaker 14: Internet of robotics today. So what we do is we
Speaker 14: look for alternate sources. One such source is human videos.
Speaker 14: We look at how humans operate in their scenarios in
Speaker 14: your kchareen in while working in factories, and combine that
Speaker 14: with training come simulation, which companies like Nvidia invest a
Speaker 14: lot on, like omni.
Speaker 4: Verse and all those.
Speaker 14: So these two things watching people and then practicing in simulation.
Speaker 14: That's how we combine and scale these models to large scale.
Speaker 4: Your software can be put within the GPU.
Speaker 3: And what's interesting is you're already going from what we
Speaker 3: understand zero to tens of millions of dollars deepak in
Speaker 3: revenue just a few months in twenty twenty five.
Speaker 4: Where's that revenue coming from? Who is using your software already?
Speaker 14: Yep, So this is the revenue has mostly been from
Speaker 14: the price applications. And the idea is in like instead
Speaker 14: of instead of going for our end goal is a
Speaker 14: consumer homelike applications. But right now, since it's just a
Speaker 14: beginning of the field, we are taking this model and
Speaker 14: we are deploying it in variety of applications, like we
Speaker 14: are deploying robots in sectors like point to point delivery applications,
Speaker 14: security applications, data centers, and manufacturing and warehouse so the
Speaker 14: revenue is coming from most of these applications.
Speaker 3: You're born out of academia and you're still professor kind
Speaker 3: of emlan. But what's interesting is you're not without some
Speaker 3: competition out there. I think about physical intelligence for example,
Speaker 3: you're all trying to intend to get robots to become
Speaker 3: intelligent and situationally aware. Do you think you can take
Speaker 3: on Are you worried about competition?
Speaker 14: Well, competition is always good and turns out like the
Speaker 14: AI community born from very small circles. So they're all
Speaker 14: our friends and colleagues from earlier. But what's unique about
Speaker 14: what we are building is this only bodied brain, like
Speaker 14: any robot, any task one brain. Now, if you really
Speaker 14: think deeply about this, it sounds absurd, like a humanoid
Speaker 14: robot with a human like body, a dog robot and
Speaker 14: they share the same brain. And that's what you see
Speaker 14: in the reserves we release.
Speaker 6: The difference in approach is fascinating.
Speaker 2: It is a crowded failed you know, Burnt from one
Speaker 2: X was on the show yesterday. They have a world
Speaker 2: model that essentially allows NEO to carry out a task.
Speaker 2: It's it's never seen before and that largely you know,
Speaker 2: I'm not an engineer, right, but what you have in
Speaker 2: common is VLN. Those are the inputs distinguish your approach
Speaker 2: to one X's as an example.
Speaker 14: So in our case, the robot learns by watching people.
Speaker 14: Right now, imagine I have to pick up this cup
Speaker 14: in front of mee do I have to exactly imagine?
Speaker 14: So scary By the way, watching me you learned when
Speaker 14: you were a kid. You learned by watching your periods.
Speaker 14: You learn watching others. Now, if you think about how
Speaker 14: you how you operate. Every time you pick up a cup,
Speaker 14: do you imagine in your head a picture of cup
Speaker 14: and then putting your finger in the handle, And no,
Speaker 14: it's all mushed in like somehow it's consciousness inside your
Speaker 14: body and then you imagine in some abstract space and
Speaker 14: then do it. And that is the main idea here.
Speaker 14: That's how we do it. But just ted being said,
Speaker 14: watching alone is not enough because if it was enough,
Speaker 14: I could play like Federer, keep watching his games all day.
Speaker 14: And that's where practice comes into play now. Practicing in
Speaker 14: the real world in the making mistakes is expensive, and
Speaker 14: that's where become mind simulation. So videos alone is not enough.
Speaker 14: Same alone is not enough. But put them together and
Speaker 14: boom you have a magic recipe to really figure out
Speaker 14: how to scale robotics.
Speaker 3: Magic recipe that values are forteen billion dollars as far
Speaker 3: Deepak Pathact co found a CEO skilled AI. Thanks so
Speaker 3: much for joining us today coming out more funn around news.
Speaker 3: Excel partner Sarah Dlston joins us to talk about her
Speaker 3: latest investment in AI security startup debt First.
Speaker 4: There's somebody meg tech.
Speaker 2: Security startup debt First, has closed a forty million dollars
Speaker 2: Series A funding round. The company uses AI to identify
Speaker 2: and harden software vulnerabilities.
Speaker 6: The round led by Excel.
Speaker 2: Joining us to discuss Excel partner Sarah Wilson Debt First.
Speaker 2: This was a big theme actually at AWS reinvent the
Speaker 2: idea that particularly sort of swarm based agents can go
Speaker 2: on the offense, not just defense. So it's a sensible
Speaker 2: place to start with. Why you made the investment in
Speaker 2: general security intelligence is what can it do that existing
Speaker 2: app SEC and other sort of static analysis tools just can't.
Speaker 15: I think the main thing is performance and speed and
Speaker 15: the ratio of signal to noise. So I think what
Speaker 15: we have to realize in this moment is, as we're
Speaker 15: all so excited about how AI is making it possible
Speaker 15: to ship software so much more quickly, that same AI
Speaker 15: tool is being used by the bad guys to ship
Speaker 15: attacks more quickly. And so the historical ratio of signal
Speaker 15: to noise just won't stand in the current era. And
Speaker 15: so the security platform that Debt first has made is
Speaker 15: AI native. And what they are doing is continuously agentically
Speaker 15: scanning a company's code. They're looking at its architecture, they're
Speaker 15: looking at its business logic, and they're finding verified vulnerabilities
Speaker 15: eight times more than the previous best in class. And
Speaker 15: I think the key there is verified vulnerability is they're
Speaker 15: not raving their hands about things that aren't really a problem.
Speaker 15: They're finding real problems, and then they're also serving up
Speaker 15: a solution. You can press one button and say fix it,
Speaker 15: and folks are doing that.
Speaker 2: In mass I was looking at the round. It's a
Speaker 2: sizable series A. You know, in the last couple of
Speaker 2: years the market has been somewhat distorted depending on the
Speaker 2: company's type.
Speaker 6: But what you just said eight times invest in class.
Speaker 2: How critical is a data point like that to you
Speaker 2: when you decide do I want to be in this
Speaker 2: round a tool or not evidence?
Speaker 15: It's really critical, and I think, particularly in the case
Speaker 15: of security, there's just a societal imperative that we get
Speaker 15: this right. And I think Excel We've been investing for
Speaker 15: forty three years. Throughout that time, security has been a
Speaker 15: key category of investment for US folks like CrowdStrike or netscope,
Speaker 15: that IPO just last year, and what we've seen is
Speaker 15: in these major innovation transitions, these major you know, cycles
Speaker 15: of transition, the security apparatus has to be replaced.
Speaker 4: It has to evolve to that new era.
Speaker 15: And that's why we're so excited about companies like Depth first.
Speaker 15: But you're exactly right, you know, it has to work.
Speaker 15: It's imperative that it works, and so those stats are
Speaker 15: really important. They're important to the CISOs, they're important to
Speaker 15: the fortune fifty that are evaluating these companies. And so
Speaker 15: if we're gonna, you know, put ourselves in our funds
Speaker 15: behind a company, it's imperative that we believe that the
Speaker 15: thing works and not just not just today, but that
Speaker 15: you have the team that can drive over this next
Speaker 15: era of transition, that you have the talent that can
Speaker 15: sort of weather this moment.
Speaker 3: The talent is Hanley Soltofta, and you're seeing Palo Alto Networks.
Speaker 3: Even so it's now he's in big acquisitions in the space,
Speaker 3: trying to get ahead of the cyber risks around AI.
Speaker 4: Do you think that this is a long term bet?
Speaker 4: Will this company go public or do you think it
Speaker 4: will be an M and A story.
Speaker 15: You know, I think this is absolutely a long term bet.
Speaker 15: That is always our you know, our focus when we
Speaker 15: do our investing, and I think that this is a
Speaker 15: team that's really uniquely qualified to go that distance. So
Speaker 15: this is technical leaders from companies like Data Bricks, from
Speaker 15: Google DeepMind, from fair These are folks who have built
Speaker 15: you know, large durable companies and confronted these security problems.
Speaker 4: At an incredible scale.
Speaker 15: But mirroring that cyber experience with the AI experience, very
Speaker 15: few people have had sort of the experience of building.
Speaker 4: At a place like Google.
Speaker 15: Deep Mind and can now apply that to this context.
Speaker 15: So it's a really interdisciplinary team, a highly technical team
Speaker 15: that we believe is very unique in their ability to
Speaker 15: tackle this problem.
Speaker 3: Sarah, you a head of strategy Partnerships at fair So
Speaker 3: when you're thinking about who are the talent you want
Speaker 3: to go for, is it your own network you need
Speaker 3: upon Is it that you're hearing these companies being born
Speaker 3: out of these big deep minds even before they're a
Speaker 3: really created. How you tapping into a really early stage
Speaker 3: business that needs financing?
Speaker 4: Yeah, I think it's all of the above.
Speaker 15: And then you know, we hope to spend a lot
Speaker 15: of time with folks during the early days when they're
Speaker 15: really you know, considering starting a company or the early
Speaker 15: definition of the company. You know, our goal is to
Speaker 15: be along the journey for decades, right the generational companies
Speaker 15: that are going to solve these security problems will last
Speaker 15: that long, and so we do we try and find
Speaker 15: them early. And it can be through a lot of things,
Speaker 15: but certainly one of the greatest signals is when we
Speaker 15: see incredibly talented people that we know to be excellent
Speaker 15: aggregating around an opportunity.
Speaker 4: And I think what really emerged.
Speaker 15: About this team is that they're incredibly motivated by this mission.
Speaker 15: And if you look around all of our critical systems
Speaker 15: in society are powered by software. Software that people can
Speaker 15: write increasingly quickly with AI, and the other dimension that's
Speaker 15: changing is increasingly we're giving this software more autonomy, we're
Speaker 15: giving it more access, we're giving it the ability to reason,
Speaker 15: and that's really exciting, but it's also something that would
Speaker 15: be concerning if those things aren't secure. We just watch
Speaker 15: your segment talking about the robots, right. We want to
Speaker 15: make sure if we're getting these devices access to our homes,
Speaker 15: to our businesses, that they're secure. And I think that
Speaker 15: that is a is a belief that's shared by the
Speaker 15: Depth First team that they this is sort of an
Speaker 15: imperative for society that we get this right, that we
Speaker 15: ensure that all of this new AI generated code that's
Speaker 15: being shipped at increasing rates is all secure.
Speaker 3: What's being shipped by a load of your portfolio companies Cursor,
Speaker 3: Lovable and Thrope among some of the bets over Accel.
Speaker 3: We really appreciate your time, Accel partner Sarah Itttleston. Now
Speaker 3: coming up Spotify, f co, CEOs my Face are host
Speaker 3: of challenges more the Audio Giants plans next.
Speaker 4: That's a blue bag.
Speaker 2: Tech Salesforce is looking to bolster AI capabilities for Slack users.
Speaker 2: The company is releasing an upgraded slack bot that uses
Speaker 2: anthropics claud model, joining us to discuss Rob Seaman's Slack
Speaker 2: interim CEO and Chief Products Office. You know, I have
Speaker 2: not yet got access to this, this updated slack bot,
Speaker 2: but as a Slack user, very interested to see where
Speaker 2: this goes.
Speaker 6: Rob.
Speaker 2: The general idea, right was that Mark Bennioff, the parent
Speaker 2: company CEO, was using chat GPT and you guys are like,
Speaker 2: we want to have an internal tool.
Speaker 6: So has it worked? What is he using it for?
Speaker 6: What are you using it for? Absolutely? So one.
Speaker 16: I can't wait for you to try it. So we're
Speaker 16: using it internally. Marcus certainly using it. I'm using it.
Speaker 16: I'll give you a few examples of how I use it.
Speaker 16: I used it recently. I just said, hey, go find
Speaker 16: the most recent all hands deck that we're working on.
Speaker 16: One of the things that we do is actually introduce
Speaker 16: every single new hire every month, and I said, tell
Speaker 16: me how to pronounce the names of all the new hires,
Speaker 16: and that goes off and finds the presentation without me
Speaker 16: saying reads the presentation figures out where the new hires are,
Speaker 16: loops through all of them, and figures out their highest
Speaker 16: probability nationality and tells me how to pronounce them. I
Speaker 16: don't have to go bug people to figure that out.
Speaker 16: It's awesome and it saves me time.
Speaker 6: In the first instance.
Speaker 2: It is underpinned by Anthropics Claude, Right, and you're going
Speaker 2: to tell me, well, this is interim and we're going
Speaker 2: to look at all kinds of different model options.
Speaker 6: We're model agnostic.
Speaker 2: But it is an interesting and the latest example of
Speaker 2: how Claude helps people in the enterprise get to market quick.
Speaker 6: You know what was your experience of that, rob.
Speaker 16: The biggest thing for us was being able to take
Speaker 16: an m pick it up and set it down in
Speaker 16: our infrastructure in a way that our customer's data never
Speaker 16: left our security boundary and wasn't used for the training
Speaker 16: of the model. And that's what we got with Anthropic
Speaker 16: and Claude. And on top of that, we've done a
Speaker 16: bunch of sophisticated prompt and context engineering that makes slack
Speaker 16: bot deeply personal and a deeply personal agent to every
Speaker 16: single person that uses it.
Speaker 4: Well, but how are you thinking about security?
Speaker 16: Oh, I mean, it's a paramount for us. It's been
Speaker 16: something that's been the very very top of our priorities
Speaker 16: since the foundation of slack and so one slack bot
Speaker 16: is a personal agent. It needs to be deeply trusted
Speaker 16: by the user, but also trusted by the enterprise. And
Speaker 16: so what we do is the user, the slack bot
Speaker 16: is acting on behalf of the user, so it can
Speaker 16: access the information that a user can their direct messages,
Speaker 16: their private channels, and the public channels within a particular
Speaker 16: slack instance.
Speaker 6: And as I.
Speaker 16: Mentioned before, from a company perspective, you can rest assured
Speaker 16: that your data is not being used to train the model,
Speaker 16: nor is it leaving the security boundary. So it's all
Speaker 16: adhering to your existing security policies and slack this.
Speaker 4: Is all about return on AI investment.
Speaker 3: It's all about making it clear to me, to you,
Speaker 3: to the users that the stuff saves you time makes
Speaker 3: more productive.
Speaker 4: How are you measuring that role.
Speaker 16: We don't measure individual productivity, but we do measure the
Speaker 16: usage of slack bots. So we measure the penetration, so
Speaker 16: the number of users that actually use slack bot over
Speaker 16: the number of users that have access to it, but
Speaker 16: at week over week retention and then message intensity, and
Speaker 16: that allows us to approximate the value that's being created,
Speaker 16: and the week over week retention force slackbot is higher
Speaker 16: than any other feature we've ever had, and slack and
Speaker 16: the message intensity keeps growing, and to us, that's a
Speaker 16: quantitative signal of qualitative value that's being derived from our
Speaker 16: users for time savings, but also we're seeing through our
Speaker 16: qualitative surveys people use this for brainstorming and creative pursuits
Speaker 16: that we didn't even expect.
Speaker 3: Rob Seman, Slack intro CEO, and great speaking with you
Speaker 3: about slack bot.
Speaker 4: We'll see how it catches on.
Speaker 3: Meanwhile, let's take a look at shares of Spotify right
Speaker 3: now and indeed over the start of the year well
Speaker 3: off by nine percent. That's, of course, when the new
Speaker 3: co CEOs have joined the company. Gusta Sworderstrom Alex Norstrom
Speaker 3: took over as from the Spotify founder Daniel Eck. Now
Speaker 3: they've both been out the business for a long time,
Speaker 3: but Eck himself.
Speaker 4: Grew the platform from money suck to.
Speaker 3: One of the most powerful businesses in the music industry,
Speaker 3: and the new CEOs have to steer that powerful ship
Speaker 3: around some pretty tough headwinds AI angry creators, user fatigue
Speaker 3: to turn around that share drop and most actually Commen
Speaker 3: has been writing about all of this by the Audio
Speaker 3: GI's leadership transition.
Speaker 4: It's in BusinessWeek and there are a lot of headwinds.
Speaker 4: What is front and center for them?
Speaker 3: How are they're taking on the algos and the AI story.
Speaker 17: They're coming up with a lot of different products that
Speaker 17: they're hoping will kind of buy them some time and
Speaker 17: also maybe address some of what users want to do. So,
Speaker 17: for example, they're integrating Spotify into jack shipt. They've made
Speaker 17: a partnership with Meta on its glasses.
Speaker 4: They are letting you.
Speaker 17: Enter prompts to get a playlist in return, using even
Speaker 17: like online contexts so that you can get the top
Speaker 17: rated albums of the year from Pitchfork or something like that.
Speaker 17: So they really want to give people both this personalization,
Speaker 17: more options showing up where people are. Podcasts are coming
Speaker 17: to Netflix. They're really trying to meet people where they
Speaker 17: are rather than forcing them to just come to Spotify.
Speaker 2: YouTube not a new issue, but the biggest in front
Speaker 2: of them. It seems like, you know, it's very detailed
Speaker 2: in the BusinessWeek story. This competition for eyeballs and YouTube
Speaker 2: is the thing on both of those CEO's deaths right
Speaker 2: now Acshually.
Speaker 17: Yes, YouTube, Spotify has moved into video. One of the
Speaker 17: scoops from our story is that they're now actually focusing
Speaker 17: on fitness content. So as a result of them pushing
Speaker 17: into video podcasts, creators who we see on YouTube that
Speaker 17: actually put out guided workouts have started uploading their content
Speaker 17: to Spotify, and Spotify is seeing that.
Speaker 4: People really enjoy that content.
Speaker 17: So instead of just using playlists to soundtrack their runs,
Speaker 17: they're actually watching yoga on Spotify, for example. So this
Speaker 17: is an area they're pretty excited about and seemed to
Speaker 17: be investing in.
Speaker 4: We know a lot about Daniellek.
Speaker 3: We've sort of grown up alongside him as he's taken
Speaker 3: this European success story global.
Speaker 4: What do we know about the co CEOs?
Speaker 17: Who are they? Well, their descents, what are they about?
Speaker 17: So both of them are Swedish. Alex is of half
Speaker 17: Chinese half Swedish descent. His mother was a single mother,
Speaker 17: Sharan a Chinese restaurant. Growing up, he's really kind of
Speaker 17: the culture guy. He gets a playlist regularly that keeps
Speaker 17: him on top of trends. It seems like he's really
Speaker 17: sort of a social person who's doing all these partnership
Speaker 17: deals with the labels and audiobooks and such. Gustave formerly
Speaker 17: really focused on product now co CEO also Swedish. He
Speaker 17: sold a startup to Yahoo back in two thousand and six.
Speaker 17: He did a stint in the Swedish military, and he's
Speaker 17: really tech philosophy focused.
Speaker 4: He was really excited about a book.
Speaker 17: He read from the inventor of quantum computing, so he
Speaker 17: really gets.
Speaker 4: Deep on that.
Speaker 17: And supposedly the two of them together are really like
Speaker 17: a yin and yang.
Speaker 4: They go well together.
Speaker 17: A fun tidbit, Nordstrom means north stream, Soderstrom means south stream,
Speaker 17: so it's written at the universe.
Speaker 4: I guess.
Speaker 2: This really is a must read on Bloomberg online or
Speaker 2: in a magazine coming to you very soon in BusinessWeek.
Speaker 2: Bloomberg's actually come and with the deep dive in Spotify.
Speaker 2: Thank you very much, Caro. That does it for another
Speaker 2: edition of Bloomberg. Tech markets still continuing to start the
Speaker 2: year pretty.
Speaker 4: Hot, pretty hot.
Speaker 3: Well, we're under pressure if you're not a big tech
Speaker 3: they're hot if you're looking at commodities. And that too
Speaker 3: is an AI story. I mean, the joke of twenty
Speaker 3: twenty two and onwards. Everything's an AI story, don't forget
Speaker 3: to check out or all of them.
Speaker 4: On our podcast.
Speaker 3: Find on The Terminal, as well as online on Apple,
Speaker 3: on Spotify, and on iHeart as a Bloomberg