Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is alive
Speaker 1: from coast to coast with Caroline Hyde in New York
Speaker 1: and Ed Lovelow in sentences, go.
Speaker 2: This is Bloomberg Tech coming up.
Speaker 3: President Trump says he discussed in video's eighty two hundred
Speaker 3: chips with Jijingping.
Speaker 2: Will break down the latest.
Speaker 4: Plus we speak with the CEO of Figma after its
Speaker 4: earnings results, the five fears that AI would disrupt the design.
Speaker 3: Stack, and our conversation with open Ai CFO Sarah Fryer,
Speaker 3: who says the startup may raise more capital after completing
Speaker 3: its recent fundraising round.
Speaker 2: Carry has got the markets.
Speaker 5: I have, let's check in on them.
Speaker 4: We're currently seeing the n AS that one hundred actually
Speaker 4: having its worst day since March the twenty seventh. At
Speaker 4: the moment, edre by one point three percent. Look over
Speaker 4: the course of the week, it's not nearly so ugly.
Speaker 5: We're actually inning down about a tenth percent.
Speaker 4: But on this day it is the chip stocks in particular,
Speaker 4: and I'm looking at Micron on the downside.
Speaker 5: That's a key point drag. You're looking at Invidia as well.
Speaker 4: Look, this is the day in which we digest what
Speaker 4: happened over in Beijing.
Speaker 3: Yes, and that is reflected in semiconductors in part. So
Speaker 3: the Philadelphia Semiconductor Index or SOCKS is the main gauge
Speaker 3: of chip makers, chip equipment makers. It's down almost four percent.
Speaker 3: You have to take into account the astonishing rally in
Speaker 3: chip stocks year to date seventy percent or something prior
Speaker 3: to yesterday's close.
Speaker 2: In video at one point in the session, it's off.
Speaker 3: Session lows was down on track for its biggest decline
Speaker 3: since February. In part, as I say, because the market's digesting,
Speaker 3: what was the net outcome of the meeting between President
Speaker 3: Trump and President G four Invidia And for chips, his
Speaker 3: President Trump talking about in video's eight two hundred chips
Speaker 3: on Air Force one earlier today.
Speaker 2: As you know, Jensen was, there's amazing and the video and.
Speaker 6: He would be a fla.
Speaker 7: You know, they have much higher level than the HQO hundred,
Speaker 7: but the H two hundred is good Chinadja And so yeah.
Speaker 3: President Trump there on Air Force one. Let's get the
Speaker 3: latest with Bloomberg's Tyler Kendall, who joins us once again
Speaker 3: from Beijing.
Speaker 2: Chips in focus for US.
Speaker 3: On Bloomberg Tech Taiwan in focus between the President and
Speaker 3: President g What else do we need to take away
Speaker 3: from this historic meeting?
Speaker 8: Well ed? At this point, we're actually getting some breaking
Speaker 8: news on how China views how this visit went between
Speaker 8: President Trump and Chinese President Jijingping. Chinese state media reporting
Speaker 8: moments ago that China feels that Taiwan is that number
Speaker 8: one issue for US China relations now. President Trump and
Speaker 8: US officials here on the ground maintained that the US
Speaker 8: policy regarding Taiwan has not changed, though the President Trump
Speaker 8: told Fox News earlier today that he would like to
Speaker 8: see tensions cooled down, in his words, between China and Taiwan.
Speaker 8: When pressed about future US weapons sales, the President was
Speaker 8: also noncommittal as Congress waits for him to prove a
Speaker 8: fourteen billion dollar package that's been queued up. That was
Speaker 8: clearly the biggest point of contention amid a summit that
Speaker 8: was rather cordial, and both sides said that they were
Speaker 8: prioritizing stability. But we didn't really get a lot of
Speaker 8: tangibles and deliverables in terms of progress. Right We're still
Speaker 8: waiting on some key details regarding planned commitments. When it
Speaker 8: comes to purchase agreements or new investment deals. Though we
Speaker 8: can confirm that Boeing officials were still here on the
Speaker 8: ground in Beijing over the last few hours meeting with
Speaker 8: Chinese officials and what was considered a positive sign for
Speaker 8: that deal.
Speaker 5: But as you.
Speaker 8: Mentioned, there there was a big expectation that perhaps there
Speaker 8: could be a deal when it came to in Vidia's
Speaker 8: H two hundred chips, as the Nvidia CEO Dnsen Wong
Speaker 8: was a last minute addition to the travel here to Beijing.
Speaker 8: President Trump did confirm that they spoke about the chips,
Speaker 8: but a timately said that China wants to develop their
Speaker 8: own and that's why we hadn't seen any purchases go
Speaker 8: through Ed and Caroline. The President also mentioned that the
Speaker 8: two sides did discuss the future of artificial intelligence and
Speaker 8: where we could see some collaboration in terms of guardrails
Speaker 8: related to the technology.
Speaker 4: For the most Tyler Kendall extraordinary work throughout the past
Speaker 4: few days over in Beijing. We so appreciated. Look, we've
Speaker 4: got to get there. For the broader chip industry perspective,
Speaker 4: what does all of this mean in terms of the
Speaker 4: United States and its ability to drive up manufacturing capacity
Speaker 4: and its workforce right here.
Speaker 5: Sharry List is with us.
Speaker 4: It's a vice president of Global Workforce Development Initiatives at SEMI.
Speaker 4: It's a global industry association connection professionals worldwide across the
Speaker 4: chip and electronics design and manufacturing supply chain.
Speaker 5: It is wonderful, Chary, to have you here with us.
Speaker 5: Thank you so much for having so.
Speaker 4: If we do see tensions rise, and if we do
Speaker 4: focus therefore even more on a manufacturing footprint brought back
Speaker 4: to America where Chips have manufactured their design rather than
Speaker 4: make so reliant on Taiwan, are we able to do it?
Speaker 2: We are?
Speaker 9: I mean, I think I speak on behalf of the
Speaker 9: workforce component involved this. It is one of the bottlenecks
Speaker 9: for this industry in the US, for sure, but there
Speaker 9: are a remarkable set of programs that are being built
Speaker 9: all around the country to meet that need. The Chips
Speaker 9: investments here in the US are launching an incredible growth
Speaker 9: here for us on our soil here in this country,
Speaker 9: and we're going to need another one hundred and fifty
Speaker 9: years one thousand or so people in this work environment.
Speaker 9: So we're building programs all over the.
Speaker 3: Country away from the geopolitics. You know, the news of
Speaker 3: the week highlights just capacity reliance. Right, So the one
Speaker 3: thing that Taiwan's really good at is the brutal economics
Speaker 3: of semiconductor manufacturing, and talent's a key component of that.
Speaker 3: Of course, there's all this plan on paper to build
Speaker 3: more fabs, have more foundry capacity in the United States,
Speaker 3: Do we have the people with the skills to make
Speaker 3: them run and not just make them run, make them
Speaker 3: hum right, brutal economics.
Speaker 9: Yes, I mean I think that's what we're all trying
Speaker 9: to work towards. Absolutely, had we didn't have as many
Speaker 9: programs established in the US anymore because we weren't manufacturing here.
Speaker 9: With the investments that are happening here, programs are launching
Speaker 9: all over the country. In fact, under the Chips investment,
Speaker 9: there's a two hundred million dollar workforce This.
Speaker 2: Is the Chips Act. A result of the Ships actually, sorry.
Speaker 9: As a result of the Chips Act, there is a
Speaker 9: two hundred million dollar investment in workforce through the National
Speaker 9: Science Foundation in concert with the Department of Commerce, to
Speaker 9: invest in building a national infrastructure around workforce development so
Speaker 9: that we can fund regional nodes around the country to
Speaker 9: build what's needed regionally in workforce and how to feed
Speaker 9: that into a national infrastructure.
Speaker 2: Not just jump in ofs.
Speaker 3: I mean Tim Cook very famously said, didn't he that
Speaker 3: China could fill a sports stadium with tooling engineers and
Speaker 3: that type of talent in America would struggle to fill
Speaker 3: a meeting room. What kind of roles are we talking
Speaker 3: about here? Show that you're trying to skill up.
Speaker 9: This nation on Yeah, I mean, I think we need
Speaker 9: everything across the industry, from technicians and operators to fill
Speaker 9: the fabs, to be on the fab floors, to all
Speaker 9: sorts of engineers across electrical engineering, mechanical engineering, chemical engineering,
Speaker 9: to our researchers, our PhDs. We need everybody. We need
Speaker 9: marketing talent, we need finance talent. So I think the
Speaker 9: challenge right now in the US is actually the image
Speaker 9: and awareness of our industry with students. So we do
Speaker 9: a lot of work in the space of getting students
Speaker 9: excited or passionate about this industry or.
Speaker 5: Even to know it.
Speaker 9: Because kids walk around all day every day with their phones,
Speaker 9: the phones, their iPads, their computers were in cars that
Speaker 9: are driven through chips. We are using appliances, everything we
Speaker 9: use all day long, and most people don't know that,
Speaker 9: parents don't all know you know, So it's it's an
Speaker 9: educating of the country. Really.
Speaker 4: Well, it's been so interesting is the method by which
Speaker 4: we start to up our fabrication footprint. Now, in some
Speaker 4: ways it's about leaning into intel, into local plays, but
Speaker 4: a lot of it's been about how drawing TSMC and
Speaker 4: saying please build here in Arizona. How much in the
Speaker 4: past have we relied on sort of TSMC talent coming here.
Speaker 4: Is that a way that's been reskilled and we've learned
Speaker 4: from others, or is it really about teaching them in
Speaker 4: our own.
Speaker 1: Education system, seeing others being brought up through the STEM
Speaker 1: education perspective, rather than learning from talent abroad.
Speaker 9: There's certainly been a mix of both. I think we have,
Speaker 9: of course, relied on talent abroad. As an industry. This
Speaker 9: is a global industry. This is a really intense, intricate,
Speaker 9: complicated industry, and we need talent from everywhere, right, that's clear.
Speaker 9: What we're trying to do now is make sure that
Speaker 9: we can build the workforce in the US with US
Speaker 9: citizens to get US jobs and to fill all of
Speaker 9: these roles. So we are still learning of course, we're
Speaker 9: all learning from each other. We all have different strengths
Speaker 9: across the world, so you know, hopefully we'll be able
Speaker 9: to meet those needs here in the US with all
Speaker 9: the programs that are being established.
Speaker 2: We're out of time.
Speaker 3: But actually Caroen I didn't even think about that, right.
Speaker 3: What did not come out of the meeting again between
Speaker 3: the two presidents probably the issue of visas right and
Speaker 3: talent here in Silicon Valley, San Francisco. How long has
Speaker 3: that been a story, you know, talent from China coming
Speaker 3: to universities, particularly in the world of AI, particularly in
Speaker 3: the world of AI. Shery list is Semi. It's great
Speaker 3: to have you on Bloomberg Tech. Thank you very much. Listen, guys,
Speaker 3: tune in Monday for an exclusive interview with the CEOs
Speaker 3: of Dell and Nvidia. From the sidelines of Dell Technology's world.
Speaker 3: Will be jennying over to Las Vegas for what is
Speaker 3: could not be a more timely conversation. Coming up, Cerebras
Speaker 3: surges in its trading debut, turning summer Silicon Valley's earliest
Speaker 3: backers into billion dollar winners.
Speaker 6: US.
Speaker 2: Next, this is Bloomberg Tech.
Speaker 5: We have got to check in on Cerebras.
Speaker 4: What a debut yesterday extraordinary sixty eight percent higher close
Speaker 4: at one point eighty nine percent. Unsurprisingly, there's been a
Speaker 4: profit taking company today more by some four point eight percent,
Speaker 4: let's call it on the day as we see the
Speaker 4: rest of the industry being under some pressure across the
Speaker 4: AI in chip spectrum because of concerns about really where
Speaker 4: the US China relationship goes. But three of the chip
Speaker 4: makers earliest venture capital backers al cerebra said Benchmark, Eclipse
Speaker 4: Foundation Capital, they're poised to make billions from their bets
Speaker 4: following Cerebras's IPO here for more has been a bouth
Speaker 4: VC and startups reporter Rebecca Times, So how early do
Speaker 4: they back this company and what sort of rewards are
Speaker 4: they going to be able to give LPs?
Speaker 10: Yeah, so two of the are sorry, three of the
Speaker 10: four biggest backers in Cerebras of their biggest outside backers
Speaker 10: came in a decade ago. In twenty sixteen, they invested
Speaker 10: in Cerebras's earliest round on the order of twenty five
Speaker 10: million dollars, and they now stand to make billions of
Speaker 10: dollars each at the IPO. Benchmark is among them inter
Speaker 10: firms with the biggest steak now around eight percent, and
Speaker 10: this would have you know, this was its first hardware
Speaker 10: investment in over a decade at the time, and that
Speaker 10: big swing has really paid off for them in spades. Obviously,
Speaker 10: the stock trading up massively from its IPO price of
Speaker 10: one hundred and eighty five dollars per share rebackgau.
Speaker 3: I don't know if you noticed yesterday, but when Andrew Feldman,
Speaker 3: the Cerebris CEO, was on the show, le Or Susan,
Speaker 3: the CEO of venture firm Eclipse, was hanging over his
Speaker 3: right shoulder every couple of seconds gave a little cheeky
Speaker 3: glance down into the camera lens. Eclipse another firm you know,
Speaker 3: regulars on this show that made a lot of money.
Speaker 7: Here.
Speaker 3: It's really fun reporting on this with you. It's like,
Speaker 3: you know, it's a really important IPO day. Look what
Speaker 3: else do we need to know? And just reflect what
Speaker 3: your week was like covering this blockbuster listing.
Speaker 2: Absolutely so.
Speaker 10: We also learned in the days leading up to the
Speaker 10: IPO that Semikin Doctor Company Arm and its majority backer SoftBank,
Speaker 10: had made an attempt to acquire Cereubris in the weeks
Speaker 10: before it's listing. Those offers were ultimately rebuffed, but there's
Speaker 10: huge competition in this market. There's obviously tons of interest
Speaker 10: in the private markets and now the public markets as well.
Speaker 10: In aichip companies an Area Infrastructure, Eclipse and Foundation Capital,
Speaker 10: one of the other largest free risk backers. This sort
Speaker 10: of hardware, this infrastructure is very much their bread and butter,
Speaker 10: and so they've got, you know, some of the things
Speaker 10: in the pipeline sort of that follow this general theme.
Speaker 10: And certainly there are more investments being made all across
Speaker 10: stages in the private markets, very much in line with
Speaker 10: this theme. So expecting to see much more activity here.
Speaker 3: Invoted for Rebecca Torrance, big week, thank you very much.
Speaker 3: From the excitement around Srebris's debut to the massive AI
Speaker 3: spending that's still ongoing at the hyperscale, is investors increasingly
Speaker 3: focused on whether companies like Alphabet, Meta and Amazon can
Speaker 3: justify the soaring capex with sustained revenue growth. On the
Speaker 3: other side, let's get more on that with Eric Sherid
Speaker 3: and Goldman sax Co Business Unit, leader of the Technology,
Speaker 3: Media and Telecommunications Group in Global Investment Research. Some weeker,
Speaker 3: I mean that's the formula. You look at the hyperscalers,
Speaker 3: you get the capital expenditures number. We get to the
Speaker 3: end of earning season and video reports next Wednesday. Probably
Speaker 3: the largest beneficiary of that capital expendit show. If we're
Speaker 3: being honest, you sit here on a Friday morning, Eric,
Speaker 3: what's your conclusion of the week's news flow and how
Speaker 3: it impacts those bigger names that you cover well.
Speaker 11: I think the main takeaways for us is that we
Speaker 11: remain in an infrastructure led cycle, so CAPEX continues to
Speaker 11: have an upward bias, albeit the bias to the upside
Speaker 11: was more muted this quarter than it was last quarter,
Speaker 11: which we think investors generally received positively. The second element
Speaker 11: would be that the revenue backlogs, or the future revenue
Speaker 11: that could come from this capex is now over nine
Speaker 11: hundred billion dollars combined, spread across both Alphabet and Amazon's
Speaker 11: cloud computing divisions. That is giving investors increased confidence that
Speaker 11: there's revenue that will follow allbeit one, two, three years
Speaker 11: after the capex is spent. And interestingly, the margins in
Speaker 11: these cloud segments also surprised to the upside because non
Speaker 11: AI workloads are accelerating structuring data is accelerating, so therefore
Speaker 11: the long term view of earning a return on a
Speaker 11: larger revenue base gave people more confidence. And that's why
Speaker 11: you've seen Amazon and the Alphabet over the last one
Speaker 11: three months act very very well as stocks as there's
Speaker 11: been a greater appreciation for that.
Speaker 4: I mean, Eric at one point this week we wondered
Speaker 4: if Alphabet was going to eclipse in video as the
Speaker 4: world's most valuable company. And we think about that vertical
Speaker 4: integration that is just helping with this flywheel, the fact
Speaker 4: that they are able to have such prowess when it
Speaker 4: comes to TPU and the amount that they're able to
Speaker 4: begain inefficiencies. And I think if Amazon actually using cerebras
Speaker 4: share stock. More broadly, they've been using Cerebris hardware alongside
Speaker 4: some of their own in house chips. How are you
Speaker 4: seeing this world of benefit from using your own self
Speaker 4: made chips alongside those from others.
Speaker 11: Custom Silicon or TPUs from Alphabet and Amazon, we think
Speaker 11: continues to be one of the most underappreciated narratives in
Speaker 11: the market. Firstly, it continues to drive workloads into these
Speaker 11: cloud ecosystems so they capture more revenue overall. Secondarily, because
Speaker 11: they designed the custom silicon, they garner more of the
Speaker 11: margin by doing it. And the performance of TPUs, while
Speaker 11: not quite where GPUs are on an absolute performance basis,
Speaker 11: if you measure it on price to performance, they're actually
Speaker 11: quite competitive. So this is something where you can go
Speaker 11: to your customers offer a price to performance ratio that
Speaker 11: looks very attractive and they benefit from garnering more revenue
Speaker 11: and more incremental margin. That's another theme that we think
Speaker 11: is gaining in prominence across this landscape.
Speaker 3: Eric, you lead the team at that is covering Amazon
Speaker 3: and Alphabet right, and I'm just saying that's point out
Speaker 3: the obvious. That's your focus, but you must track Anthropic
Speaker 3: so closely. Both companies have significant financial interests in anthropic.
Speaker 3: Both have some kind of competition with Anthropic at the
Speaker 3: model level. In Amazon's case, Bedrock is the marketplace for Claude.
Speaker 3: That's very tangled as a web. How do you untangle it?
Speaker 12: Well?
Speaker 11: I think there's a lot without getting into any one
Speaker 11: company in their relationship with another. I think the world
Speaker 11: overall is becoming more interdependent. When it comes to AI,
Speaker 11: you're going to have foundational model companies that need compute,
Speaker 11: You're going to have hyper scalers that can deliver that compute.
Speaker 11: You increasingly are going to have hyperscalers who are effective
Speaker 11: partners that allow the foundational model companies to come to
Speaker 11: market and connect with enterprises like Goldman Sachs, and there
Speaker 11: is going to be a lot of scale that benefits
Speaker 11: driving incremental growth in this landscape. The truest measure of
Speaker 11: technology computing shifts in my career has been that only
Speaker 11: a handful of companies on both the infrastructure and the
Speaker 11: platform layer earn excess returns on capital. So there's only
Speaker 11: going to be a handful of companies that are enterprise
Speaker 11: platform companies. There's only going to be a handful of
Speaker 11: companies that are consumer platform companies. And if you come
Speaker 11: back to the earlier point that you led with, which
Speaker 11: is the capital need for this entire cycle, there's only
Speaker 11: a handful of companies that have the access to capital
Speaker 11: to be able to build to this. So there is
Speaker 11: going to be an interdependence that comes from just a
Speaker 11: handful of companies that can actually build at this level
Speaker 11: of scale.
Speaker 5: Alek Sheridan fascinating.
Speaker 4: Not having you on the show has always come back
Speaker 4: soon of Goldman sachs.
Speaker 5: Now coming up.
Speaker 4: Tensions rise between Apple and Open Ai. Why the AI
Speaker 4: startup is weighing possible legal action against the iPhone maker.
Speaker 5: This is Blomberg Tech.
Speaker 4: And it's time now for talking tech and first up.
Speaker 4: Samsung management is making a rare eleventh hour visit to
Speaker 4: union leaders to a massive chip factory strike, but the
Speaker 4: world stop memory maker is facing an eighteen day walkout
Speaker 4: that could cost the company seven hundred million dollars a
Speaker 4: day and good stall critical AI chip production. Plus Bill
Speaker 4: Ackman's Pershing Square has taken a new course take in Microsoft,
Speaker 4: with Ackman arguing that the market is unestimating the tech
Speaker 4: chanswer resilience now.
Speaker 5: The move comes as Microsoft.
Speaker 4: Continues its aggressive push into AI, reclaiming its status in
Speaker 4: Agwin's portfolio and Elon Musk's XAI, and is officially entering
Speaker 4: the coding agent race with the launch of grock Build
Speaker 4: in an attempt to catch up with down public explaud
Speaker 4: Musk is racing to close that gap in the developer market.
Speaker 4: It's coding agents become the next multi billion dollar frontier
Speaker 4: in AI.
Speaker 3: Ed Let's chat about Open AI. You sat down with
Speaker 3: CFO Sarah Fryer last night, and she you had the
Speaker 3: opportunity to basically say, good timing. Sam Altman's under away
Speaker 3: in a very big case against Elon Musk. And then
Speaker 3: there's the breaking news last night about Apple and the
Speaker 3: relationship flu part.
Speaker 2: Just reflect on.
Speaker 4: It, I mean an extraordinary not saying planfo.
Speaker 2: Great timing though.
Speaker 4: A joy a bounty of news when you're sitting down
Speaker 4: with a key executive. And Sarah fry is very clear
Speaker 4: about what she needs at the moment. She needs money
Speaker 4: for compute that continues. He has already got more than
Speaker 4: one hundred and twenty billion dollars of it, and she's
Speaker 4: got plenty of optionality.
Speaker 5: We talked about her relationship with Sam Altman.
Speaker 4: She's very What's so interesting is she's saying, Look, if
Speaker 4: you want your CEO and CFO to be, you know,
Speaker 4: always agreeing on absolutely.
Speaker 5: Everything, you're sort of getting her wrong steer. That shouldn't
Speaker 5: be how it works. But they have a really good
Speaker 5: working relationship.
Speaker 4: Look, she was just in California at his ranch on
Speaker 4: the weekend because they're working extra time on things like Compute.
Speaker 5: Here is a close relationship.
Speaker 4: But yes, at times they have to disagree, so that
Speaker 4: was an interesting discussion, particularly when we've had some heman's
Speaker 4: own sort of way in which he presents himself and
Speaker 4: the bill in the business being under the coals and
Speaker 4: under the limelight.
Speaker 5: But I think was notable.
Speaker 4: I asked her about the open Ai and Apple relationship,
Speaker 4: and of course she couldn't comment. But this is a
Speaker 4: company that depends on partnerships to get their technology into
Speaker 4: people's hands.
Speaker 5: Apple is key for.
Speaker 4: The CHATCHBT, but it was meant to be better integrated
Speaker 4: into the overall Apple Intelligence experience.
Speaker 2: We're going to get the detail on that just a set.
Speaker 3: We're going to hear more from Kara's conversation with Sarah
Speaker 3: Fryer later this hour. Stick around for that. Here's the
Speaker 3: details Apple and Open Area's relationship is framed. Open Ai
Speaker 3: is weighing possible legal action against the iPhone maker, arguing
Speaker 3: it hasn't seen the expected benefits from the partnership and
Speaker 3: it's Apple's use of its technology remains limited and hard
Speaker 3: for users. Define let's get out to Bloomberg Senior Tech
Speaker 3: editor Dana Wolman incredibly detailed report from the team. I
Speaker 3: suppose what was that agreement initially?
Speaker 13: So the two companies teamed up and really open Aiyes,
Speaker 13: saw this as an opportunity to, as you said, get
Speaker 13: its product as big of a name as it is
Speaker 13: in front of even more people Apple's huge user base.
Speaker 13: So open Air's technology would be built into Apple's platforms,
Speaker 13: and for a lot of users, especially users who are
Speaker 13: perhaps less tech savvy, it might have been their first
Speaker 13: exposure to open AI's technology and open air. I was
Speaker 13: hoping that this would result in billions of dollars worth
Speaker 13: annually in new subscribers.
Speaker 4: Let's talk about whether or not they have to be
Speaker 4: forced with some legal action to get recompense here, but
Speaker 4: more broadly, it's a time where Apple's own Apple Intelligence
Speaker 4: is not working as they hope, having to depend on
Speaker 4: Google to help build siry.
Speaker 5: More broadly, are they just having to go to more
Speaker 5: players in the ecosystem?
Speaker 13: I'm sorry, can you repeat the question? I don't know
Speaker 13: if I fully heard you.
Speaker 4: How are we thinking about Apple's own dependence on other
Speaker 4: offerings for its own Apple Intelligence that isn't working?
Speaker 13: So Apple is going to be opening up its own
Speaker 13: platforms to other developers as well, which surely is not
Speaker 13: helping with the dynamic with open Ai. It's something that
Speaker 13: Marker mentioned in his report. That said, and this has
Speaker 13: come up in other of Bloomberg Technology's reports as well,
Speaker 13: is that Apple is sort of benefiting from the investment
Speaker 13: that all of these other AI developers have invested over
Speaker 13: the years in AI. Now it's getting to sort of
Speaker 13: integrate this menu of different increasingly advanced tools, as you said,
Speaker 13: as it continues to build out its own much delayed
Speaker 13: product of its own data.
Speaker 4: Wollman, we so appreciate you, thank you for coming on
Speaker 4: regarding open AI and Apple.
Speaker 5: Coming right up, we're discussing AI in another area of Figma.
Speaker 4: It is flipping the script on the AI disruption narrative.
Speaker 4: CEO Dylan Fields joining us next after earnings were a blowout,
Speaker 4: much better than expected, and so much for that disruption
Speaker 4: vis Blue meg Tech. Welcome back to Bloomberg Tech, and
Speaker 4: we've got to focus in on the company Figma. It
Speaker 4: is defying those fears that AI would disrupt the design stack.
Speaker 4: The company has just reported a massive first quarter with
Speaker 4: revenue growth accelerating to forty six percent. It successfully begins
Speaker 4: to monetize new AI features. Joining us now Figma founder
Speaker 4: CEO Dylan Field. Dylan, Look, there has been many many
Speaker 4: a question on software providers about the disruption that will
Speaker 4: come from the likes of large language model frontim makers,
Speaker 4: anthropic being one. What is driving your revenue growth and
Speaker 4: the ability to exceed guidance as well well?
Speaker 14: First of all, thank you for having me and good
Speaker 14: to see you. And yeah, a strong quarter. We had.
Speaker 14: Revenue accelerates forty six percent year every year, and our
Speaker 14: net dour attention for customers that are over ten k
Speaker 14: of ARR is now at one hundred and thirty nine percent.
Speaker 14: And also strong cash flow with non up margin of
Speaker 14: sixteen percent in the quarter in free cash flow of
Speaker 14: twenty seven percent.
Speaker 2: We also raise our guidance. So we're very glad with
Speaker 2: the results.
Speaker 14: And I think in terms of taking a step back
Speaker 14: around what is behind the quarter and also the moment
Speaker 14: you're mentioning as AI commanitizers code, it makes it so
Speaker 14: that code is easier than ever to write, you know,
Speaker 14: the layer above code as that gets commoitized is fine.
Speaker 3: I got an audience question for you on that in
Speaker 3: just a moment. But for me like that, I don't
Speaker 3: know what you would call it, Like the credit caps
Speaker 3: or the way you charge on usage was so fascinating.
Speaker 3: So in March you started charging customers a fee to
Speaker 3: use AI, in particular beyond a certain limit, and the
Speaker 3: response is varied. Right when people hit that cap, many
Speaker 3: were willing to pay for more credits. There was some
Speaker 3: drop off though, like a small group was saying, well,
Speaker 3: if that's the case, I won't use a Figma product anymore.
Speaker 3: Where do you see that netting out?
Speaker 14: Well, we have many products and you're always welcome to
Speaker 14: you know, as a free user use one of our
Speaker 14: free surfaces, or as a paid user of the seat,
Speaker 14: use our.
Speaker 2: Traditional design tool.
Speaker 14: But yes, if you want to use the product we
Speaker 14: have Figma make, we want to use AI features in
Speaker 14: Figma design. What we did was we essentially added some
Speaker 14: number of free credits to paid seats to make sure
Speaker 14: that people had a way to try these features out.
Speaker 14: And then we also made it to that if you
Speaker 14: want to buy additional credits you can, And for a
Speaker 14: long time we actually made it said everything was free.
Speaker 14: But you know that's not exactly the move that us
Speaker 14: do that forever and it does cost real money.
Speaker 2: We also have.
Speaker 14: Thima Weave, and weave is extremely exciting and with weave,
Speaker 14: what you can do is essentially create a workflow, which
Speaker 14: is a note through notebased editing tool where you connect
Speaker 14: up different outputs from models I think images, videos, three
Speaker 14: D models and more, and then you can push them
Speaker 14: through a workflow so that you're able to really mold
Speaker 14: those model outputs like clay. So for example, NBBJ, a
Speaker 14: architecture firm. One of the customers we mentioned Durens Call.
Speaker 14: They used to do these very extensive customer shoots where.
Speaker 2: They would go out to site and they would.
Speaker 14: Really understand what is the different lagging at different times
Speaker 14: and they would then superimpose the three D model of
Speaker 14: the building. And with Thigma weave they can do that
Speaker 14: all in a workflow where they can just really easily
Speaker 14: control all sorts of different parameters and it saves them
Speaker 14: a ton of time and gets better results for the client.
Speaker 14: So that's another one where we also see AA friend
Speaker 14: SCIPT kick in.
Speaker 4: You bring real anecdotal evidence to bear, and the anecdotical
Speaker 4: elevidence we hear is like like if you ever try
Speaker 4: and st wave figma from those that use it when in.
Speaker 5: The workforce, they'll not leave.
Speaker 4: Employees will like march out the building because they so
Speaker 4: love the product.
Speaker 5: But how do you then fight this narrative?
Speaker 4: Then investors just want to sell first, ask questions later,
Speaker 4: and has put your stock under pressure since the IPO.
Speaker 14: I mean, I think we control the inputs and we
Speaker 14: need to deliver for our customers, as simple as that.
Speaker 14: And so we're working very hard always on making sure
Speaker 14: that we're doing the right thing for the long term.
Speaker 14: And I think that the long term is thankfully aligned
Speaker 14: with our strategy. We're in the best position we think
Speaker 14: we are basically can be. And you know, is I
Speaker 14: becoming more important than ever? And I think that one
Speaker 14: area when it comes to maybe the market or the world,
Speaker 14: as we're seeing design go more broad in these companies
Speaker 14: and also be more appreciated as the way that you win,
Speaker 14: but also what you break through a very head of
Speaker 14: information landscape.
Speaker 2: You have to really people what design is.
Speaker 14: It's not just you know, creating something that you know
Speaker 14: you think is beautiful because you know, many people have
Speaker 14: different aesthetics. It's how it works, it's ux, it's forum,
Speaker 14: its function.
Speaker 2: Yeah, and we have.
Speaker 14: To I think, really help people understand the many different
Speaker 14: facets of design and Enfigma, design is not always just
Speaker 14: you know, how it looks, how it works. It's also
Speaker 14: the thinking process out there, and I think in this world, Dyaling, Yes, sorry,
Speaker 14: I don't.
Speaker 2: Mean to cut you off.
Speaker 3: We're running out of time, and I want to get
Speaker 3: that audience question to you because, as you know, I
Speaker 3: think it's really important regular of the show, Ben, how
Speaker 3: do you see inference and token costs affecting your margins
Speaker 3: going forward?
Speaker 2: You kind of alluded to it earlier.
Speaker 14: Yeah, we talked about in our Orange call yesterday and
Speaker 14: how if we see an opportunity to go really big
Speaker 14: and have a ton of growth, we will take it
Speaker 14: and we will push hard. But I think there's a
Speaker 14: short term, there's the long term, and sometimes there's ways
Speaker 14: to push hard on short term and that might create
Speaker 14: downward pressure and margins. But if you're going for a
Speaker 14: massive TAM in the long term, I think that's the
Speaker 14: right move in what our investors should be cheering us
Speaker 14: on to do. And the TAM is very large both
Speaker 14: for design, for sculpting, you know, advertising marketing and breaking
Speaker 14: through noise, and I think that in general, if we're
Speaker 14: able to deliver on that and able to win this
Speaker 14: increasingly competitive landscape which is growing so fast of design
Speaker 14: when it's the new code. I think that puts us
Speaker 14: in an amazing edition for the future. So very excited
Speaker 14: to bringing more people into the design processes. What we're
Speaker 14: seeing with our customers, it's not just designers, it's many
Speaker 14: others as well, but also level them up on design.
Speaker 3: Figmacia didn't feel back on Bloomberg Tech.
Speaker 2: Thank you very much for joining us.
Speaker 3: Now coming up, Figure is putting their humanoid robots out
Speaker 3: the lab and onto the live stream. CEO Brett Adcock
Speaker 3: with us next. This is Bloomberg Tech. Figure says its
Speaker 3: humanoid robots just completed more than twenty four hours of
Speaker 3: continuous package sorting autonomously, a live stream watched by millions
Speaker 3: across YouTube and X three FO three robots worked in shifts, scanning, flipping,
Speaker 3: sorting packages at roughly human speed, all powered by its
Speaker 3: in house AI software running directly on board the robots.
Speaker 3: But that demonstration did spark some skepticism was it real?
Speaker 3: Joining us now, as Brett Adcock founder CEO A Figure,
Speaker 3: that's where we start, you can say, Brett definitively. Over
Speaker 3: the twenty four hours or more, there was no teleoperation.
Speaker 3: A lot of people in the comments, as you know,
Speaker 3: pointed to the idea, and I think we had video
Speaker 3: a bit that the three on shift kept gesturing to
Speaker 3: the head, which is a tailtale sign in robotics of teleoperation.
Speaker 2: Your pledge that there was none.
Speaker 12: There's absolutely no telly operation into this. The robots are
Speaker 12: all operating fully autonomously using an onboard neural network redesign
Speaker 12: called Helix two. Sometimes when the robot takes a turn
Speaker 12: to left to grab packages, it moves its left hand
Speaker 12: out of the way upwards. You'll see this behavior happen
Speaker 12: every single time the robot turns for packages.
Speaker 7: But we've been.
Speaker 12: Running autonomously now for close to fifty hours, the robots
Speaker 12: operating shifts. There's been basically almost no downtime on the belt.
Speaker 12: We've pushed over close to sixty thousand packages and we're
Speaker 12: just going to keep going now and see how far
Speaker 12: this can go.
Speaker 3: So this was live streams, right, and that was one
Speaker 3: reason I really wanted you to come on the program,
Speaker 3: because there's the bit people don't see what's happening behind
Speaker 3: the scenes, like in shift changes, where does the robot go?
Speaker 2: Does it need maintenance?
Speaker 12: For the most part, the robots operate on a four
Speaker 12: hour battery life. After the battery is low, the robot
Speaker 12: messages another robot to come out to take its place.
Speaker 12: The robots didn't do a swap. The robot has just left.
Speaker 12: The conveyor system is going to go charge wirelessly, understand
Speaker 12: while the other robot continues to do work. If there
Speaker 12: are issues, say we have hardware software issues, the robots
Speaker 12: can basically walk off into maintenance and call another robot
Speaker 12: to take its place. The goal is to be able
Speaker 12: to enlistit twenty four to seven operations with basically no
Speaker 12: like no failures on the on the use case itself,
Speaker 12: which we haven't had today. So the robots basically the
Speaker 12: conveyor system has been running twenty four to seven since
Speaker 12: like middle of this week. I think we're now we're
Speaker 12: approaching fifty hours of just full like every single hour
Speaker 12: since since we've launched, the robots have been basically I've
Speaker 12: been doing work now on this line, which.
Speaker 2: I think is like wow, which I think is crazy.
Speaker 12: You know, Figure wants to build like you know, we
Speaker 12: want to build like I robot. You know, we want
Speaker 12: robots everywhere in the world in the commercial market, Like
Speaker 12: this is like the first large step to doing that.
Speaker 4: Okay, So what's harder now robots getting faster or making
Speaker 4: them even more reliable, because at the moment you seem
Speaker 4: to be doing both.
Speaker 12: The robot that you're seeing here is roughly operating around
Speaker 12: human speech just about three seconds of package. That's the
Speaker 12: requirement to operate on this logistics line. So we're at
Speaker 12: like we're at human parity and speed. The goal is
Speaker 12: also to have like ninety percent success rate on the
Speaker 12: bark the package flips for barcode scanning. We're in that
Speaker 12: as well. In that requirement, the robots are also like
Speaker 12: getting extremely reliable. Like part of this whole process of
Speaker 12: running this twenty four to seven with no downtime is
Speaker 12: to show how reliable humanoid robots are. And four years
Speaker 12: ago when I started the company, humanoid robots were falling.
Speaker 12: They were extremely unreliable systems. We've designed the systems and
Speaker 12: engineered this now to a point where the robots are
Speaker 12: I think extremely reliable. I think we're showing that now
Speaker 12: in the live stream to the entire world. The big
Speaker 12: focus for us is is like how do we solve
Speaker 12: for a truly general purpose machine, and then how do
Speaker 12: we manufacture unprecedented volume similar to cell phones? Today, so like,
Speaker 12: so this week back que our manufacturing facility will manufacture
Speaker 12: anywhere between like sixty and seventy humanoid robots just this week, right,
Speaker 12: and we do it right next door on the Figure campus.
Speaker 3: So brat, I want to get into the idea, this
Speaker 3: is full stack. I've been hearing a lot growing speculation
Speaker 3: that open ai could get back into robotics. And you
Speaker 3: have a history white Way, you had a partnership, you
Speaker 3: decided on the software side you could do better yourself.
Speaker 2: You know, what do you make of that?
Speaker 3: That idea that ultimately a big party is going to
Speaker 3: want to own the entire stack that powers the humanoid robot.
Speaker 12: To really do this right, like if we want to
Speaker 12: really build like I robot like the movie, yes, you
Speaker 12: know we basically you have to design the entire hardware
Speaker 12: system almost yourself, like motors like stater rotors, the electromagnetics work, like,
Speaker 12: you have to do all the battery systems work. You
Speaker 12: have to do all the actuator design, sensor design, kinematics
Speaker 12: like structures like which we do all in house now
Speaker 12: here at Figure. We also manufacture the robots, so we're
Speaker 12: like and then we also test them and we do
Speaker 12: all the AI data collection and all the AI and
Speaker 12: neural net training ourselves here in house. So basically, this
Speaker 12: is a full end to end vertically integrated system that
Speaker 12: we now have out doing real use case work that
Speaker 12: humans do, and we can do this at human speeds.
Speaker 12: And we're doing this now for like you know this example,
Speaker 12: most of these shifts run like this eight hours a day.
Speaker 12: We're doing this like twenty four to seven, just to
Speaker 12: show how reliable the systems are and how like mission
Speaker 12: ready these things are to get out at scale. So
Speaker 12: anyway to solve this you have to have like a
Speaker 12: truly vertically integrated approach from top to bottom.
Speaker 4: What about the bottlenecks? View is in our money do
Speaker 4: you want to go public?
Speaker 5: Brat?
Speaker 8: What is?
Speaker 5: What are you needing to get this out?
Speaker 12: More broadly, our largest two bottlenecks are like data for
Speaker 12: pre training, our helix, neural net and UH in manufacturing,
Speaker 12: we're spinning up manufacturing here our manufacturing facilities called BATQ.
Speaker 12: We've we're now doing we're now out of several like
Speaker 12: thousands of run rate annually production that is continuing to
Speaker 12: scale up.
Speaker 5: UH.
Speaker 12: You know, I think UH on the data side, we're
Speaker 12: collecting and training, uh, kind of unprecedented models for like
Speaker 12: our AI stack here internally that we've ever done.
Speaker 7: Uh.
Speaker 12: So I think we're like we're and we have you know,
Speaker 12: we have well over a billion dollars of cash in
Speaker 12: the balance sheet today. So I think from a from
Speaker 12: a financial perspective, we're in a good spot. We're manufacturing
Speaker 12: at pretty much unprecedented volumes for ourselves, and we're we're
Speaker 12: building like next generation AI models that I think are uh,
Speaker 12: to be honest, are just completely mind blowing. And so
Speaker 12: the goal is like the goals to solve the data
Speaker 12: problem and the manufacturing problem, to get humiliar robots out
Speaker 12: of scale.
Speaker 4: And maybe come up with even more names for these
Speaker 4: robots currently getting them from online fans. I think one's
Speaker 4: called Bob and Gary Brett Gadcock. We so appreciate your
Speaker 4: time today, Founder and CEO of Figure.
Speaker 5: Now let's send our attention to Annie Jasse. It was
Speaker 5: once Jeff Bezos's deputy.
Speaker 4: Remember, now five years into his tenure as CEO, Jesse
Speaker 4: is steering the company through some of.
Speaker 5: Its greatest changes. That's the focus of today's big take most.
Speaker 5: Matt Day joins us.
Speaker 4: With more You went to see sort of the new
Speaker 4: real focus point for Annie Jasse. It's data centers, and
Speaker 4: this is a company that is now just scaling so
Speaker 4: much in a vertically integrated manner. Matt, what did you
Speaker 4: learn from visiting the hubs and what it says about Andy?
Speaker 15: But it says that there's just such sprawl to Amazon
Speaker 15: these days. You think you know Amazon from the package
Speaker 15: is showing up at your doorstep. So much of what
Speaker 15: they're spending money on it's data centers. It's a supply
Speaker 15: chain behind data centers. That means chips, that means hardware engineering,
Speaker 15: that means software at the large language model level.
Speaker 2: They're really just all over the place.
Speaker 15: And it's kind of an unfathomable sort of things they
Speaker 15: got going on, and really the sort of single organizational
Speaker 15: principle behind it is Andy at the top of it.
Speaker 15: He's making all these calls on where they got to
Speaker 15: shift money with the comple and stuff out of what
Speaker 15: they're putting into. It's really really an impressive machine.
Speaker 3: So Matt, knowing that he's watching right now and he
Speaker 3: Jesse is glued to Bloomberg Tech.
Speaker 2: There is a good chance that's true.
Speaker 3: What do we learn about him is the Amazon CEO
Speaker 3: versus Jeff Like you and I've talked about this in
Speaker 3: the past, But what's different about him? Does he lean
Speaker 3: hard into the AWS thing?
Speaker 2: You definitely did.
Speaker 15: And if you look at where their bets are today,
Speaker 15: you know a lot of them are, and what can
Speaker 15: Amazon do uniquely and what can they do differently when
Speaker 15: it comes to their core retail business. So they've left
Speaker 15: some opportunities on the table there. That's not the case
Speaker 15: in AI. They want to be everywhere in AI. They
Speaker 15: want to sprinkle AI through all of their product lines,
Speaker 15: and that is where they're spending a ton of their
Speaker 15: their capex right now. So he's definitely brought some of
Speaker 15: that AWS pedigree with him. We've also just learned he
Speaker 15: is he is an extreme detail guy. It's not that
Speaker 15: that was not a Jeff Bezos trade, but for the
Speaker 15: last few years of his leadership at Amazon, Jeff was
Speaker 15: checked out and some of the business. You know, Andy
Speaker 15: hasn't let go of anything since he showed up. He's
Speaker 15: all over the details of this business.
Speaker 3: Blue Most Matt Day with the big take on Andy
Speaker 3: jase Era at AWS and Amazon must coming up arguments
Speaker 3: in the trial between Open AI and Elon Musk wrapped
Speaker 3: up yesterday. We're going to get to the latest and
Speaker 3: some more of the conversation we've been having with open
Speaker 3: Ai the past twenty four hours. This is Bloomberg Tech.
Speaker 4: Opening Eyes chief financial Officer Sir Fran talked about the
Speaker 4: demand the company is seeing and the compute needs it's
Speaker 4: up against. She sat down with me at the Cancello
Speaker 4: Spark summit in Napa.
Speaker 5: Take a listen.
Speaker 16: Compute itself has clearly been a bottleneck. I don't think
Speaker 16: any of us, even Sam and Greg, who I think
Speaker 16: we're incredibly prescient overall, in terms of the need for compute,
Speaker 16: I don't think they could have foreseen just the sheer
Speaker 16: demand that we have right now in twenty twenty six,
Speaker 16: and so that it's the energy that sits behind it.
Speaker 16: We're seeing memory out of Southeast Asia where there's all
Speaker 16: of these chok points in the supply chain, and this
Speaker 16: is why it behooves us to get ahead of that,
Speaker 16: strike those partnerships earlier when people are maybe not seeing
Speaker 16: just the sheer scale.
Speaker 4: Let's talk about partnership and about some of the people
Speaker 4: you just talked about, Quite Brockman and Sam Altman.
Speaker 5: They've had a tough week.
Speaker 4: In terms of being in trial, having their relationships sort
Speaker 4: of cast.
Speaker 5: Into the limelight. What is this like working with Sam?
Speaker 4: There's been some questioning as to how you work alongside him,
Speaker 4: Do you work well?
Speaker 5: Is it a strong bond? Is he trustworthy?
Speaker 8: Is it?
Speaker 4: Seemed to have been grilled by certain lawyers of Elon
Speaker 4: Musk this week.
Speaker 16: So I think mister Musk is very much out to
Speaker 16: just distract, and we are just staying the course, like
Speaker 16: building our technology, putting it into customers' hands, and really
Speaker 16: creating agi for the benefit of humanity. Working with Sam
Speaker 16: is great. We get on incredibly well. I think we
Speaker 16: have a wonderful partnership, super good ying and Yang Sam
Speaker 16: push us.
Speaker 5: He's super curious.
Speaker 16: My job is to take that curiosity and create optionality.
Speaker 16: So just as we talked about whether it's making sure
Speaker 16: we have enough compute, making sure we have the funds
Speaker 16: to do it, makeing sure we build the business strongly.
Speaker 16: And I spend an an ordinate amount of time with customers,
Speaker 16: as does Sam, and we get to compare a lot
Speaker 16: of notes on that front, as well as sometimes our
Speaker 16: nuts on parenting. So it goes the whole gamut frankly Open.
Speaker 3: AI CFO Sarah Fry speaking with Caroline about her relationship
Speaker 3: with the company's CEO, Sam Altman. The relationships and choices
Speaker 3: of open ais founders have been front and center of
Speaker 3: the lawsuit brought by Elon Musk over the charitable status
Speaker 3: of the company. Arguments in the trial wrapped up yesterday.
Speaker 3: Bloombergs Madelin Meckelberg has been there every step of the way,
Speaker 3: and so this is where we're at. Closing arguments we
Speaker 3: wait for. I think jury deliberation Monday give us everything
Speaker 3: that we need to know at this point.
Speaker 6: That's right. I think one thing that we learned from
Speaker 6: closing arguments, it's really relevant to the conversation you just
Speaker 6: had with Sarah, is that this case, for both parties,
Speaker 6: really boils down to credibility. That's the message that they
Speaker 6: left jurors with on Thursday when they had closing arguments.
Speaker 6: Musk's attorneys are trying to cast Sam Altman as someone
Speaker 6: who's deceptive, who's untrustworthy. Meanwhile, lawyers for Open Ai were
Speaker 6: trying to point to the evidence that's been presented so
Speaker 6: far in the case, saying Musk's story doesn't add up
Speaker 6: with what we've seen in the documents, what you've heard
Speaker 6: from witnesses, and so now it's up to the jury
Speaker 6: to decide whose version of events they believe about this
Speaker 6: saga of the formation of open Ai, the dissolution of
Speaker 6: this relationship and the transition into rivalry between Musk and
Speaker 6: Altman that we see playing out today.
Speaker 5: What happens if Musk wins.
Speaker 6: That's a big question. So at this point, the jury
Speaker 6: is going to start deliberating and they're going to issue
Speaker 6: a verdict that's advisory, so it's a non binding recommendation
Speaker 6: to the judge in this case, who's going to have
Speaker 6: the final say on whether or not Musk has enough
Speaker 6: to prove his claims here. And Musk is asking for
Speaker 6: a lot. He's asking for one hundred and thirty four
Speaker 6: billion dollars in d images that he says he's going
Speaker 6: to donate to the Open Ai Foundation. He's asking for
Speaker 6: Altman and Brockman to be removed from their jobs, and
Speaker 6: he's asking for the open Ai come up company that's
Speaker 6: been formed to be transitioned back to a nonprofit. These
Speaker 6: are huge asks. The judge is also going to hear
Speaker 6: arguments on Wednesday about which one of those might be realistic,
Speaker 6: and we're just going to kind of have to wait
Speaker 6: and see how she comes down on the main question
Speaker 6: before we get to that. But the stakes are huge
Speaker 6: and ex essential essentially for open.
Speaker 4: Ai b mags Mann, Mackelberg, fascinating.
Speaker 5: Thank you.
Speaker 4: I mean, we wait with bated breath for the rest
Speaker 4: of the week and what indeed happens in that court case.
Speaker 5: But he'say, there's some.
Speaker 3: Confidence world is part about it is that court case
Speaker 3: happened in the context of the week, all the other
Speaker 3: news flowing. It's almost kind of I don't want to
Speaker 3: say buried, but we do wait for it. It for
Speaker 3: this sedestion of Bloomberg Tech on Monday, speaking with the
Speaker 3: CEOs of Dell and the video two thirty pm Eastern
Speaker 3: eleven thirty m Pacific. If you do not want to
Speaker 3: miss it, check out the pod for the recap. What
Speaker 3: a week this is Bloomberg Tech