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Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. Bloomberg Tech is a

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Speaker 1: live from coast to coast with Caroline Hide in New

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Speaker 1: York and v Lo Loow in San Francisco.

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Speaker 2: This is Bloomberg Tech coming up.

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Speaker 3: Taiwan, weihs some of its toughest restrictions yet on AI

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Speaker 3: chip sales to China. Will have the details plus the

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Speaker 3: AIIPO raise. It heats up with Open Ai joining its

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Speaker 3: rivals with plans for a potential public listing later this year.

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Speaker 3: And Apple lays the foundation for the AI era, but

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Speaker 3: how soon will it come? As it hints that the

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Speaker 3: company's upcoming faudaal iPhone is on deck. But first I

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Speaker 3: check on those markets. We're off by eight ten percent.

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Speaker 3: We have been optimistic to start trade and then suddenly

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Speaker 3: we've turned quite a leg lower into negative territory. And

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Speaker 3: it is tech chip stocks in particular the dragoslower, but

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Speaker 3: it's also the key player that is Apple, key player

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Speaker 3: that is in Vidia that drag us down. From our

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Speaker 3: points perspective, I shine light what was happening in terms

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Speaker 3: of hardware. The Philly Semiconductor Index, the socks as we

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Speaker 3: call it, one point eight percent lower on the day

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Speaker 3: after having reprieved some of the Friday sell off. Yesterday's

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Speaker 3: trade Apple off again, the Juggernaut off by two point

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Speaker 3: seven percent. That's important in terms of points. It's important

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Speaker 3: to the overall index, and it drags the S and

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Speaker 3: P five hundred lower as well as one of those

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Speaker 3: some anxiety as to when really we will get Siri

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Speaker 3: AI in our hands. But first we also talk Taiwan

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Speaker 3: and it is weighing some of its toughest restrictions yet

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Speaker 3: on AI chip sales to China, a move we'll bring

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Speaker 3: it closer in line with Washington and mid mounting US

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Speaker 3: concern over technology leakage and national security. For more and

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Speaker 3: what it means for the AI race and the US

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Speaker 3: China tech tensions. We're joined by Blue Meg's global tech editor,

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Speaker 3: Peter Elstrom.

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Speaker 2: Is it significant this move?

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Speaker 4: It's certainly significant. The most sophisticated chips in the world

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Speaker 4: are made in Taiwan by TSMC. Of course, in what

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Speaker 4: we understand from our source is that the Taiwanese government

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Speaker 4: is now weighing these restrictions on making it a crime

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Speaker 4: to export advanced AI chips to China. Now, as you mentioned,

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Speaker 4: this is in line with US restrictions already, where in

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Speaker 4: Nvidia can't sell its most advanced AI chips to China,

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Speaker 4: for example. But why is this important for Taiwan. It

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Speaker 4: is because they hold that place as the manufacturer of

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Speaker 4: these key chips. But also Taiwanese authorities will be able

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Speaker 4: to use more tools to be able to enforce these

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Speaker 4: restrictions within Taiwan. They did detain their first person because

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Speaker 4: of these export restrictions a while ago, but they had

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Speaker 4: to do it because of falsifying documents, not because it's

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Speaker 4: a crime right now to smuggle chips out of the country.

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Speaker 4: So it gives them a few more tools to be

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Speaker 4: able to enforce these restrictions. It's a sign that President

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Speaker 4: LII there in Taiwan is taking a much harder line

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Speaker 4: against China.

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Speaker 3: And what does that mean from relationships between the US

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Speaker 3: and China. What does that mean in terms of Montbelio's

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Speaker 3: conversation coming from the leadership in China against Taiwan.

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Speaker 4: Well, you're alluding to the complex city of the situation,

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Speaker 4: and we just saw President Trump go and visit Shi

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Speaker 4: in China. They talked about these very issues. There was

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Speaker 4: a lot of discussion about many different things, including trade

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Speaker 4: and technology in particular. So it's a moving playing field

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Speaker 4: at this point. And the Trump administration has signaled that

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Speaker 4: it would allow Nvidia to sell the H two hundred chips,

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Speaker 4: for example, into China. China is ensure that it wants that.

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Speaker 4: It's very you know, they also would like to develop

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Speaker 4: their own domestic semiconductor industry. They want to support Huawei

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Speaker 4: and other companies like that that are trying to build

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Speaker 4: in this area. So it's a complicated task. It certainly

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Speaker 4: does mean that there are tensions that remain between the

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Speaker 4: two countries when it comes to these kinds of technologies,

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Speaker 4: and there's not a resolution in the near future.

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Speaker 3: We just saw in fact, China preparing two trillion and

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Speaker 3: one of spending to really focus on its own domestic

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Speaker 3: AI build out, whether that be data centers. In many ways,

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Speaker 3: that's going to be a focus on its own chips.

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Speaker 3: But b to we also got that sort of interesting

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Speaker 3: news that the Pentagon is really once again reamping some

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Speaker 3: of the concerns about Chinese companies, tech companies in their

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Speaker 3: relationship with the military. All of the spells that that

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Speaker 3: antagonism just remains.

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Speaker 4: Yeah, the first story you mentioned is a very important

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Speaker 4: one again a people familiar story that we wrote about

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Speaker 4: how China is weighing this plan to invest two trillion

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Speaker 4: one roughly three hundred billion dollars into data centers in

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Speaker 4: the country. This is kind of the missing piece in

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Speaker 4: the Chinese AI industry at this point, as we saw

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Speaker 4: with deep seak Ali Baba's work with Gwen in particular.

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Speaker 4: They've been quite successful at developing advanced models, but they've

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Speaker 4: made nowhere near the kinds of investments in infrastructure and

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Speaker 4: data centers that we've seen in the US. And now

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Speaker 4: three hundred billion dollars works out to about sixty billion

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Speaker 4: dollars a year over five years. It's not nearly as

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Speaker 4: much as the four hyperscalers are spending. They're aiming for

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Speaker 4: seven hundred and twenty five billion dollars this year, so

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Speaker 4: it's sort of a ten to one ratio. But these

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Speaker 4: data centers are much less expensive in China, and it's

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Speaker 4: a sign that they're going to compete on this infrastructure

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Speaker 4: level as well as the model level, So that's a

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Speaker 4: big step for them.

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Speaker 3: Fascinating play most Peter Elstrom, where the rap of all

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Speaker 3: that is your news.

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Speaker 2: We so appreciate it now as.

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Speaker 3: AI becomes increasingly tied to both geopolitics, but investment strategy

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Speaker 3: messas are looking beyond the initial infrastructure build out potentially

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Speaker 3: and actually applications of AI. Let's discuss that with LATU

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Speaker 3: Alliance spend seen head of thematic equities who sees AI

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Speaker 3: adoption drawning as the focus shifts to long term competitive positioning.

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Speaker 3: So at this moment, just to bring in the US

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Speaker 3: and China perspective, how competitive is the US and the

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Speaker 3: buildout of AI data centers, They're like, how solid is

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Speaker 3: the supply chain if we're worried about US China relationships

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Speaker 3: and what it means for Taiwan.

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Speaker 5: Yes, I think supply chain is important, but if you

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Speaker 5: think about US holistically, I do think a lot of

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Speaker 5: leading edge technology comes out of US. And if you

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Speaker 5: look at the US companies, the tech giants, when you

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Speaker 5: look at the billions and hundreds of billions solid they're spending,

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Speaker 5: they're actually quite strategic about it, and the pace of

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Speaker 5: innovation and the innovation in the architecture itself is actually

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Speaker 5: picking up pretty rapidly. So think about them. They're thinking

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Speaker 5: about the cost protoken holistically, and more and more companies

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Speaker 5: maybe are taking that holistic view and be more vertically

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Speaker 5: integrated and then think about whether it be Google introduces

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Speaker 5: proprietory chips, etc. So they are thinking about different architectures,

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Speaker 5: how to lower the cost protoken, so that set them

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Speaker 5: ahead in terms of competitive advantage. So because all the

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Speaker 5: hyperscalers are all competing in it, and in a way

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Speaker 5: it's an arms race, and that everybody wants to get

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Speaker 5: ahead because that actually goes well for their long term

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Speaker 5: competitive vantage and long term margin. So because the competition

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Speaker 5: is so high that we do think the US at

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Speaker 5: this moment when you look at architecture, certainly US is

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Speaker 5: quite ahead of most people in the world.

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Speaker 3: I think that vertical integration is being so clearly demonstrated

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Speaker 3: by SpaceX at the moment that Elomusk is deciding, yes,

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Speaker 3: I'm a space giant, I'm an AI giant, but also

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Speaker 3: I'm a data center giant, and actually I'm selling some

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Speaker 3: of my compute to the likes of Alphabet and Google

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Speaker 3: or indeed anthropic.

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Speaker 2: Is that the.

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Speaker 3: Way in which you would like to see companies thinking

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Speaker 3: themselves in a more vertically integrated manner, or do you

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Speaker 3: want to see more specific applications of AI is that

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Speaker 3: also attracted.

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Speaker 5: I think it's both. Actually it's at this point of

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Speaker 5: the cycle, it's certainly important to see more applications come out.

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Speaker 5: But if we look back historically, it's actually quite interesting

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Speaker 5: vertical integration and that type of cost atdvantage is very

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Speaker 5: hard to replicate, and in this very compute intensive and

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Speaker 5: capital intensive cycle, I think vertical integration is something that's

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Speaker 5: very interesting to worth that's worth considering from an investment's perspective.

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Speaker 5: But that said, if you look in the past cycle,

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Speaker 5: what happened is we build a massive comp infrastructure and

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Speaker 5: then the entire ecosystem that's capitalized ultimately monetized, and that's

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Speaker 5: created the tech giants as we know today. So it's

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Speaker 5: probably too early to tell, but I certainly think vertical

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Speaker 5: integration seems to be a direction that a lot of

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Speaker 5: these companies are considering and we're watching very closely.

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Speaker 2: It could be quite interesting.

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Speaker 3: Are you feeling comfortable with the capex still of a

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Speaker 3: lot of these large companies and the industry writ large.

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Speaker 5: I think this year we always thought that it was

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Speaker 5: going to be this has to be the year of

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Speaker 5: AI adoption and the fact that token is being utilized

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Speaker 5: and adopted as such, a rapid pace is certainly a

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Speaker 5: good sign that AI is being adopted, it's being used,

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Speaker 5: So that makes us feel better about the amount of

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Speaker 5: capex that's going into it, because ultimately we do want

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Speaker 5: to spend and build a road to somewhere, and seeing

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Speaker 5: the early signs of rapid adoption is certainly very very encouraging.

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Speaker 3: You're all about themes, You're all about long term perspectives

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Speaker 3: and not single names.

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Speaker 2: But at this point, is there going to be better.

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Speaker 3: Entry points to the market? Does it worry you quiv

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Speaker 3: you calls for ants that just how high we are

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Speaker 3: in general trading on big benchmarks, at big private market valuations,

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Speaker 3: big public market valuations.

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Speaker 5: I think that all companies are created equal, and I

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Speaker 5: think we have to look at the company really one

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Speaker 5: by one in terms of we really have to look out.

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Speaker 5: And I think historically when we look back, sometimes the

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Speaker 5: consensus street estimates they get it right the near term,

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Speaker 5: but they miss the long term. And it's the long

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Speaker 5: term that gets revised up and up that ultimately determines

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Speaker 5: how much a stock should be valued today. So in

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Speaker 5: a way, to look out actually allows you to make

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Speaker 5: more money near term. So it's really about long term

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Speaker 5: total addressable market and more importantly, the ability to hold

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Speaker 5: your margin and get the long term profit. That's what

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Speaker 5: ultimately determines whether a stock is valued fairly today.

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Speaker 2: Thanks you, We love having you on the show.

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Speaker 3: Thank you for joining us of Alliance Bernstein there. Meanwhile,

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Speaker 3: coming up, open Ai does indeed join its AI rivals

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Speaker 3: and the race of potential.

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Speaker 2: Go public will have the details on that. S one

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Speaker 2: as a Bloombg Tech.

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Speaker 3: So open Ai has joined the AI rivals with plans

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Speaker 3: for a public listing potentially later this year. The chatchypt

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Speaker 3: make confidentially filed it's S one or the SEC, but

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Speaker 3: it said the timing of an IPO hasn't been decided

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Speaker 3: because there were still things it wants to do as

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Speaker 3: a private company. Bloomberg's AI reporter Shurigafari joins us with

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Speaker 3: a details.

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Speaker 2: So what would those things potentially be?

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Speaker 3: Why make it still unclear if they're going to come

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Speaker 3: as soon as the fall?

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Speaker 6: Yeah, the company said, this is really about optionality for them.

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Speaker 6: Of course, there are a lot of factors when a

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Speaker 6: company's deciding to go public. There's the market, how they

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Speaker 6: stack up to their competitors, So these could all be reasons,

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Speaker 6: right that a company has in mind when they're thinking

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Speaker 6: about the exact timing of going forward with the filing.

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Speaker 3: Forward with the fine, and going forward with the next

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Speaker 3: phase of open AI.

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Speaker 2: I thought it was really interesting the same.

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Speaker 3: Time as we learn that they've filed an S one confidentially,

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Speaker 3: they're also putting out a statement about the control of AI,

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Speaker 3: about aligning it with humanity that was coming from Sam

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Speaker 3: Altman and the chief scientist.

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Speaker 2: What did you make of the blog? That's right?

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Speaker 6: You know, there's been a lot of talk lately in

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Speaker 6: the AI world about the idea of self improving AI.

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Speaker 6: That these AI models are getting so good that researchers

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Speaker 6: at the top labs are actually using them to program.

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Speaker 2: The next model, and.

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Speaker 6: That's caused both excitement but a lot of anxiety. We

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Speaker 6: actually saw Inimthropic last week come out with a blog

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Speaker 6: post even calling for a potential pause if this turns

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Speaker 6: out to really be the case that these models are

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Speaker 6: sort of improving so quickly and getting out of control.

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Speaker 6: So I think, you know, Altman's post is in a

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Speaker 6: way in conversation with that and acknowledging this idea that

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Speaker 6: the AI is starting to automate itself and weighing some

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Speaker 6: of both the opportunities it also risks there.

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Speaker 3: And I think that's so interesting that, of course, again

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Speaker 3: just by outlining that blog post, we're thinking about anthropic

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Speaker 3: timing open AI timing. One puts a blog, the next

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Speaker 3: pet's a blog. One's gone file confidentially the next one has.

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Speaker 3: How much is their anticipation, how much is their worry

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Speaker 3: that they're coming in the same sort of time.

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Speaker 6: It does feel like a race on every level right

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Speaker 6: now between these two sort of top AI firms, both

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Speaker 6: at the technological level, with them releasing a new model

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Speaker 6: sort of neck and neck every few months now even

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Speaker 6: every few weeks, on the sort of ideological level about

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Speaker 6: the direction that they're going to go in balancing the

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Speaker 6: risks and the benefits, as well as just this IPO timeline.

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Speaker 6: So I think it's one of the closest races certainly

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Speaker 6: that I've ever covered in the tech industry, and extremely

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Speaker 6: competitive right now on every level.

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Speaker 3: And you cover it brilliantly, Thank you, Bloomberg Sharing KAfari

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Speaker 3: on all things open ai. And let's stick with that

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Speaker 3: IPO pipeline. The AI names that we've just talked about.

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Speaker 3: If you add in SpaceX, that's three point six trillion

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Speaker 3: dollars a market cap that might be coming to the

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Speaker 3: market in the next few months. But according to Pitchbook research,

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Speaker 3: open ai may end up being the most expensive bet.

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Speaker 3: Harrison roll first is with us senior analyst of Pitchbook's

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Speaker 3: private company coverage joining us. Now, look, we can't see

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Speaker 3: the detail of the revenues and the numbers that's been

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Speaker 3: filed confidentially with the SEC. But you take a great

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Speaker 3: crack at it with an eye on open ai, your

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Speaker 3: late stage company research, and you think that open ai

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Speaker 3: is expensive in some of your frameworks. Can you talk

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Speaker 3: us through at Harrison?

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Speaker 7: Well, yeah, so open aiy has essentially built the most

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Speaker 7: widely used AI product in history, but they rely on

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Speaker 7: so much capital intensive compute that their profits aren't necessarily

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Speaker 7: going to cover their costs. So when looking at open ai,

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Speaker 7: we want to see their Microsoft terms, we want to

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Speaker 7: see how their accounting works. We want to see how

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Speaker 7: their enterprise revenue as a share total and their net

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Speaker 7: revenue retention, the annual compute obligation, and the related party

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Speaker 7: disclosed to really figure out exactly where they stand. As

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Speaker 7: a true business as opposed to the hype that's surrounding them.

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Speaker 7: The framework that I've created, this AI business quality essentially

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Speaker 7: looks at opening eye on five different dimensions. Is revenue quality,

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Speaker 7: computing independence, remote durability, governance, optionality, as well as just

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Speaker 7: capital efficiency. When you look at a company who really

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Speaker 7: doesn't who really has a strong AI mind share, but

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Speaker 7: isn't focusing on the true business qualities that make a

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Speaker 7: business successful in the public markets, it's it's something hard

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Speaker 7: to evaluate right now, and that's why they score the

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Speaker 7: lowest on my scoring system.

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Speaker 2: And four point eight b one of the highest valuations

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Speaker 2: four point.

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Speaker 3: Eight out of ten on aib key AIBQ framework.

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Speaker 2: Now I'm interested in that sort of other.

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Speaker 3: Parties perspective because the Microsoft relationship is one that you

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Speaker 3: drill down on and perhaps some of that revenue sharing

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Speaker 3: is something investors should really be thinking about.

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Speaker 7: Absolutely, the Microsoft share aspect is very unique.

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Speaker 8: By capping how.

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Speaker 7: Much they oh Microsoft, it frees up some sort of revenue. However,

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Speaker 7: it's still unsure about what's going to happen after twenty thirty,

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Speaker 7: and that uncertainty is going to make it very hard

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Speaker 7: for investors to look past twenty thirty and see if

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Speaker 7: they're going to succeed until.

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Speaker 3: Then, can you talk a little bit about what you

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Speaker 3: anticipate for governance structures coming from these companies. We're going

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Speaker 3: to dig into it in a bit at the end

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Speaker 3: of the show about questions people have about SpaceX's governance

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Speaker 3: and the control muscaz how much you're starting to see

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Speaker 3: how much control might be.

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Speaker 2: Had by open Ai.

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Speaker 3: For example, samum and we understand doesn't own any significant

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Speaker 3: portion of equity.

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Speaker 7: No, he's interesting from going from a nonprofit to this

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Speaker 7: just new PBC structures. He's essentially trying to find a

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Speaker 7: way to be the good guy. But at the same

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Speaker 7: time he's already dealt with such backlash from his from

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Speaker 7: the board and other parties involved in other investors where

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Speaker 7: they are even unsure whether or not they want.

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Speaker 8: To deal with this sort of these sort of issues.

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Speaker 7: However, Sam Alvins still finds a way to make it happen,

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Speaker 7: and now people are really relying and betting on his

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Speaker 7: future and his aspirations to bring Open the Eye to.

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Speaker 3: Number one, number one in a race we keep talking about.

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Speaker 3: It is feeling like some sort of race, but it

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Speaker 3: is about mind share. It is about oxygen in the room,

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Speaker 3: but it is about money that's going to be able

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Speaker 3: to be allocated to these companies when they go public.

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Speaker 3: Is there a worry that they file confidentially lost and

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Speaker 3: we're getting SpaceX as soon as this week.

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Speaker 7: I think by filing last actually gives open Ad opportunity

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Speaker 7: to learn from their competitors. Opening I can actually see

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Speaker 7: where Anthropic is going wrong, exactly how they can adjust

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Speaker 7: the gorong.

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Speaker 2: Where are they going wrong?

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Speaker 7: You know, Opening I could be going wrong with their

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Speaker 7: gross margins. They don't really break down exactly the tier

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Speaker 7: and the compute costs associated to it, and we'll really

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Speaker 7: get a sense of the hyperscalar involvement with Opening Eye

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Speaker 7: and just the overall reliance on them to take them

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Speaker 7: to the next step. And then in relation to SpaceX,

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Speaker 7: we're going to get a sliver of the AI aspect

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Speaker 7: from XAI. However, that's not going to tell us enough

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Speaker 7: of what it takes to be a leading frontier AI model.

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Speaker 7: So the public markets are going to be the ones

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Speaker 7: to determine how much it truly costs to run an

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Speaker 7: AI business. And they have SpaceX as a somewhat of

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Speaker 7: a comparison, even though they're they're a space company.

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Speaker 3: Harrison wilfirs a pitch book. Thanks for bringing the analysis.

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Speaker 3: We appreciate it. Coming up, Apple and bails a series

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Speaker 3: of updates at WWDC, but says it isn't able to

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Speaker 3: launch them in the EU due to a standoff with

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Speaker 3: the blocks anti trust watchdock more on that.

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Speaker 2: Next, this is Blomberg Tech.

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Speaker 3: Apple used its Worldwide Developers Conference yesterday to lay the

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Speaker 3: foundation for the AI era, unveiling a range of products

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Speaker 3: including iOS twenty seven SIRIAI. Within that the company still

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Speaker 3: has to overcome, though investor skepticism about this AI strategy.

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Speaker 3: Bloomberg's Mark German joins us now with more details.

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Speaker 2: Look, the skepticism is there.

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Speaker 3: If you're looking at the share price, we're down again.

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Speaker 3: It traded lower yesterday. Is there some anxiety about the

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Speaker 3: pace at which SIRIAI will be unfolded?

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Speaker 2: To us?

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Speaker 8: All?

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Speaker 9: Yeah, thank you for having me. Well, there are concerns

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Speaker 9: about the pace of you. They said that it'll launch

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Speaker 9: in English later this year. But Serie AI is real.

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Speaker 9: If you're on the developer beta. If you're not me,

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Speaker 9: I guess you're able to get off the wait lists

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Speaker 9: and try these new serie features out. I think the

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Speaker 9: response has been mostly positive at this point. As I

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Speaker 9: said before the event, what Apple's doing here is they're

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Speaker 9: going from completely subpar to completely adequate. We're not seeing

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Speaker 9: Wizbang AI features that you're right now seeing from Google,

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Speaker 9: Open Ai and Thropic per se, but you're seeing Siri work.

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Speaker 9: And so Apple was finally able to do was take

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Speaker 9: something that has so much promise for over a decade

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Speaker 9: and finally make it work by recreating their underlying models,

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Speaker 9: using technology from Google Gemini, using some new AI under

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Speaker 9: the hood techniques, and actually presenting users with something they

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Speaker 9: think they're going to be able to use on a

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Speaker 9: daily basis. And so the concerns that should be out

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Speaker 9: there really are what happens to Chat, GPT and Thropic

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Speaker 9: on the Apple platform because a lot of people now

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Speaker 9: are going to have a real LLM built in, and what.

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Speaker 3: Happens to other rivals, maybe even Meta AI. Look, what's

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Speaker 3: interesting is, as we've been speaking, there's been some breaking

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Speaker 3: news that Meta Platform has been ordered by the EU

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Speaker 3: to temporarily help policies that allegedly block AI firms from

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Speaker 3: operating on the WhatsApp messaging service for businesses.

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Speaker 2: This is the EU once.

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Speaker 3: Again basically saying you need to make everything available to

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Speaker 3: all your rivals at all times. This is something Apple's

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Speaker 3: spoken about. They were sort of munslinging with the EU

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Speaker 3: earlier today about whether Siri AI is going to get

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Speaker 3: to the EU users slower and whether it's Apple's fault

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Speaker 3: or the EU's fault.

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Speaker 9: Yeah, I mean, you've seen other features be held back

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Speaker 9: due to the negotiations between Apple and the EU, iPhone

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Speaker 9: mirroring being one of them. There were a few other

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Speaker 9: features on the operating systems last year, apple Intelligence being

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Speaker 9: one of them that eventually expanded to the European Union.

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Speaker 9: So I'm confident this will eventually work out. But yeah,

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Speaker 9: you're seeing a public war of words play out between

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Speaker 9: Apple and the EU right now, and we have to

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Speaker 9: just see who's going to fold first. These are two

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Speaker 9: big entities, two big personalities, and Apple rightfully so does

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Speaker 9: not like the way that the EU is inserting themselves

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Speaker 9: into product development and the way features need to be

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Speaker 9: introduced and implemented, and quite frankly, as a consumer, I'm

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Speaker 9: not in the EU, but I do feel bad for

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Speaker 9: my friends in the EU and my developer friends in

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Speaker 9: the EU who are not able to roll out the

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Speaker 9: newest features to their customers and if they are a customer,

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Speaker 9: not being able to use the newest feature because these

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Speaker 9: rules are in place. So I don't actually think what

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Speaker 9: the EU is doing is a positive at all.

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Speaker 3: Fold first, bring any hint to for foldable phone quickly?

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Speaker 9: Yeah, the foldable phone is coming in September. We've been

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Speaker 9: talking about this for a while in iOS twenty seven

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Speaker 9: is chalk full of hints to this. So really looking

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Speaker 9: forward to this launch. Big deal for Apple, and I

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Speaker 9: think this is going to be a really product. This

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Speaker 9: is one that I've been looking forward to for a

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Speaker 9: while and.

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Speaker 3: The one that you brought us news on for a

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Speaker 3: very long time, always first putting my Mark German.

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Speaker 2: We so appreciate it. Thank you now.

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Speaker 3: Meanwhile, Apple is also expanding its child's safety tools as

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Speaker 3: a governments around the world increasingly clamped down on youth

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Speaker 3: social media usage. No our features unveiled yesterday at WWDC

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Speaker 3: will hand parents much tighter control this full allowing them

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Speaker 3: to better control on devices when kids use the apps,

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Speaker 3: what content they can access, and with whom they can communicate.

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Speaker 2: Now coming up. We'll come back on open ais S.

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Speaker 3: One filing discuss the AI ibo landscape. Nun of Principal

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Speaker 3: Venture Partners. This is Bloomberg Tech. Welcome back to Bloomberg Tech.

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Speaker 3: We are seeing a rollover in stocks. We started trading

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Speaker 3: higher on the day and that optimism has since faded

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Speaker 3: and faded hard for the tech names. In particular, if

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Speaker 3: you look out of the hood of the SP five hundred,

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Speaker 3: it's far healthier and more stocks are in the green.

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Speaker 2: And that's that one hundred they were off by more

440
00:23:02,600 --> 00:23:03,320
Speaker 2: than two percent.

441
00:23:03,440 --> 00:23:06,520
Speaker 3: Is Apple, Micron, Nvidia, AMD, some of the chip hardware

442
00:23:06,560 --> 00:23:09,240
Speaker 3: names that really tug from a points perspective. And this

443
00:23:09,359 --> 00:23:12,200
Speaker 3: is a companies Well Banks and Bank of America for example,

444
00:23:12,359 --> 00:23:14,960
Speaker 3: saying there are too many red flags right now to

445
00:23:15,000 --> 00:23:18,000
Speaker 3: take profits, and people all are doing that. Maybe they're

446
00:23:18,000 --> 00:23:21,840
Speaker 3: getting some dry powder ahead of some massive IPOs. Let's

447
00:23:21,840 --> 00:23:24,280
Speaker 3: take a look at today's big number, three point six

448
00:23:24,880 --> 00:23:25,760
Speaker 3: trillion dollars.

449
00:23:26,040 --> 00:23:27,560
Speaker 2: That's a total market cap and.

450
00:23:27,520 --> 00:23:30,040
Speaker 3: The three big upcoming IPOs if indeed they do come

451
00:23:30,119 --> 00:23:33,760
Speaker 3: open AI getting itself, Optionality and Thropic too. They filed

452
00:23:33,880 --> 00:23:37,040
Speaker 3: confidentially with the SEC but SpaceX that's on deck for

453
00:23:37,080 --> 00:23:40,760
Speaker 3: this week. This is these AI companies are rasing. They're

454
00:23:40,840 --> 00:23:43,280
Speaker 3: raising tens of billions of dollars to buy chips, data

455
00:23:43,280 --> 00:23:49,000
Speaker 3: centers build more advanced AI systems. But look historically megacap IPOs,

456
00:23:49,480 --> 00:23:52,000
Speaker 3: they have a rocky start in the first few months

457
00:23:52,040 --> 00:23:54,359
Speaker 3: a traine look. Stocks often slump in the first year.

458
00:23:54,960 --> 00:23:57,919
Speaker 3: Could these upcoming listings be big enough? That just doesn't

459
00:23:57,920 --> 00:24:01,040
Speaker 3: really apply here. The rules are off discussed of blumagetquitary

460
00:24:01,080 --> 00:24:04,000
Speaker 3: report to common Rhyinikey who's trying to with an unprecedented

461
00:24:04,040 --> 00:24:06,120
Speaker 3: IPO at the end of this week, trying to see

462
00:24:06,400 --> 00:24:08,200
Speaker 3: there's any historical precedent here.

463
00:24:08,560 --> 00:24:11,160
Speaker 2: You go back to some truist found data.

464
00:24:11,320 --> 00:24:17,399
Speaker 3: Thirty mega tech IPOs compared to SpaceX, how have they

465
00:24:17,440 --> 00:24:18,879
Speaker 3: performed in the last fifteen years?

466
00:24:19,320 --> 00:24:22,400
Speaker 10: So the majority of them after one year of trading

467
00:24:22,440 --> 00:24:24,520
Speaker 10: have been down. They've slumped a little bit in that

468
00:24:24,560 --> 00:24:28,240
Speaker 10: first year of trading, but overall the entire group has

469
00:24:28,280 --> 00:24:32,000
Speaker 10: a maximum draw down or sorry, an average draw down

470
00:24:32,000 --> 00:24:34,320
Speaker 10: of fifty five percent in that first year of trading,

471
00:24:34,359 --> 00:24:36,520
Speaker 10: which is really incredible if you think about it. That's

472
00:24:36,680 --> 00:24:39,399
Speaker 10: a huge amount of money one rushing into these stocks

473
00:24:39,440 --> 00:24:42,400
Speaker 10: and then coming out as investors sort of assess all

474
00:24:42,400 --> 00:24:45,480
Speaker 10: the information that they're getting as you know, lockups expire

475
00:24:45,640 --> 00:24:49,359
Speaker 10: and more shares come online. So this it could be different.

476
00:24:49,400 --> 00:24:52,199
Speaker 10: It's such a huge IPO, and we know there's so

477
00:24:52,440 --> 00:24:56,960
Speaker 10: much hype that retail investors are being focused on in

478
00:24:57,200 --> 00:25:00,199
Speaker 10: you know, SpaceX coming to the public market and that

479
00:25:00,240 --> 00:25:02,280
Speaker 10: people are excited they really want to buy into this.

480
00:25:02,400 --> 00:25:04,959
Speaker 10: So we could see something different happen here.

481
00:25:05,000 --> 00:25:06,320
Speaker 2: I mean, maybe there's a silver lining.

482
00:25:06,359 --> 00:25:07,920
Speaker 3: If you end up feeling that you haven't got the

483
00:25:07,960 --> 00:25:10,080
Speaker 3: access that you wanted and you're forced to weight, maybe

484
00:25:10,119 --> 00:25:13,159
Speaker 3: there's a better entry point. Look, we're looking particularly at

485
00:25:13,160 --> 00:25:16,639
Speaker 3: a story of the core Weave founders. They've understandably sold

486
00:25:16,640 --> 00:25:19,080
Speaker 3: two point three billion dollars in stock since the IPO.

487
00:25:19,200 --> 00:25:21,320
Speaker 3: Is that the sort of supply side weight that you

488
00:25:21,400 --> 00:25:23,640
Speaker 3: get on these new company public companies?

489
00:25:23,840 --> 00:25:24,600
Speaker 2: It definitely is.

490
00:25:24,640 --> 00:25:27,840
Speaker 10: And Corewave was really a poster child for extreme volatility

491
00:25:27,880 --> 00:25:29,719
Speaker 10: of the year after its IPO. You know, kind of

492
00:25:29,760 --> 00:25:32,560
Speaker 10: just hit that thresholding in March and it was up

493
00:25:32,600 --> 00:25:34,359
Speaker 10: you know, four hundred percent at one point, and then

494
00:25:34,400 --> 00:25:36,680
Speaker 10: it had a draw down of sixty five percent from

495
00:25:36,680 --> 00:25:39,760
Speaker 10: that point, and we saw Magnetar offload half of its

496
00:25:39,840 --> 00:25:42,879
Speaker 10: position and these insiders sell. I mean, the stock is

497
00:25:42,920 --> 00:25:44,960
Speaker 10: still up more than one hundred and fifty percent from

498
00:25:44,960 --> 00:25:48,240
Speaker 10: its IPO price, but you do see these kinds of pressures.

499
00:25:48,240 --> 00:25:51,480
Speaker 10: They've also had some earnings reports that investors bulked at.

500
00:25:51,560 --> 00:25:55,840
Speaker 10: So all of these catalysts really add up to choppiness

501
00:25:55,880 --> 00:25:58,560
Speaker 10: in the first year as the market kind of assesses

502
00:25:58,600 --> 00:26:01,359
Speaker 10: where the valuation is going to be going forward. And

503
00:26:01,560 --> 00:26:03,320
Speaker 10: I think that's something that people are looking at with

504
00:26:03,359 --> 00:26:06,520
Speaker 10: SpaceX as well. If you look at price to sales,

505
00:26:06,720 --> 00:26:09,840
Speaker 10: it's not profitable yet it's a really high evaluation. That's

506
00:26:09,880 --> 00:26:12,199
Speaker 10: something people have been looking at in the you know,

507
00:26:12,280 --> 00:26:16,240
Speaker 10: AI and the tech in the space space over archingly,

508
00:26:16,400 --> 00:26:19,280
Speaker 10: so investors might want to wait for a better entry point.

509
00:26:19,520 --> 00:26:21,880
Speaker 2: Then, like timelines for everything.

510
00:26:22,080 --> 00:26:24,800
Speaker 3: You shine a light on Tesla for example, and Facebook,

511
00:26:25,119 --> 00:26:27,400
Speaker 3: which of course is now known as Meta. Meta had

512
00:26:27,440 --> 00:26:29,440
Speaker 3: like a really torrid first year, down thirty percent, and

513
00:26:29,480 --> 00:26:31,720
Speaker 3: now it's up fourteen hundred percent to c the IPO.

514
00:26:31,760 --> 00:26:34,000
Speaker 2: And if you look back to Tesla, what up twenty

515
00:26:34,000 --> 00:26:37,000
Speaker 2: five thousand percent? Says Listening exactly.

516
00:26:37,080 --> 00:26:40,240
Speaker 10: So that's kind of the catch twenty two here. You know,

517
00:26:40,320 --> 00:26:41,600
Speaker 10: do you want to try to buy in on the

518
00:26:41,600 --> 00:26:43,800
Speaker 10: first day where you could see a huge pop right

519
00:26:44,000 --> 00:26:46,320
Speaker 10: and then maybe you're buying at a more expensive price,

520
00:26:46,680 --> 00:26:49,040
Speaker 10: or do you want to wait and see what happens

521
00:26:49,359 --> 00:26:53,080
Speaker 10: over Archingly, it seems like if you're a longer term investor,

522
00:26:53,680 --> 00:26:56,640
Speaker 10: the data show that these IPOs do really well.

523
00:26:56,720 --> 00:26:56,880
Speaker 4: Right.

524
00:26:56,920 --> 00:27:01,000
Speaker 10: These stocks have gone up astronomically, So it's just all

525
00:27:01,040 --> 00:27:03,639
Speaker 10: about finding that right entry point, finding that right time,

526
00:27:04,000 --> 00:27:06,320
Speaker 10: that time horizon and when they get.

527
00:27:06,200 --> 00:27:08,680
Speaker 3: In and how much business models evolve, and how much

528
00:27:08,680 --> 00:27:10,640
Speaker 3: we have to understand about these business models as they

529
00:27:10,640 --> 00:27:13,320
Speaker 3: go public. With the most common rhinikey, it's a fantastic story.

530
00:27:13,640 --> 00:27:15,879
Speaker 2: Go read it. Let's discuss this and.

531
00:27:15,800 --> 00:27:19,760
Speaker 3: More now with Songy, you founder managing partner prince All

532
00:27:19,800 --> 00:27:22,359
Speaker 3: Ventures Partners. It's a Silicon Valley based early stage venture

533
00:27:22,359 --> 00:27:25,120
Speaker 3: firm focused on AI native companies. But why you're so interesting,

534
00:27:25,640 --> 00:27:27,840
Speaker 3: song Ya, is also because you serve on the advisory

535
00:27:27,840 --> 00:27:31,120
Speaker 3: Council of the Institute for Human Centered AI at Stanford University.

536
00:27:31,240 --> 00:27:33,400
Speaker 3: You've been an operator at been gaming.

537
00:27:33,080 --> 00:27:34,679
Speaker 2: Companies and tech Sony.

538
00:27:35,280 --> 00:27:37,480
Speaker 3: The business models were about to get our heads wrapped

539
00:27:37,480 --> 00:27:40,760
Speaker 3: around in the public market. Should we be as excited

540
00:27:40,760 --> 00:27:43,000
Speaker 3: about them as we are with SpaceX, with Anthropic, with

541
00:27:43,040 --> 00:27:43,600
Speaker 3: open AI.

542
00:27:44,800 --> 00:27:46,919
Speaker 11: Yeah, I think this is a really tremendous moment. If

543
00:27:46,960 --> 00:27:50,119
Speaker 11: you think about the total market cap that we're talking about,

544
00:27:50,280 --> 00:27:54,119
Speaker 11: it constitutes about ten percent of the NASTAC And we

545
00:27:54,200 --> 00:27:57,680
Speaker 11: are already talk about how concentrated NaSTA market is with

546
00:27:57,920 --> 00:28:02,959
Speaker 11: those like big top ten companies taking about more than

547
00:28:03,000 --> 00:28:06,399
Speaker 11: forty percent of the total market caap. Adding this to

548
00:28:06,640 --> 00:28:09,920
Speaker 11: on top of it make the magnastic even much more

549
00:28:10,119 --> 00:28:14,360
Speaker 11: concentrated and expose the risk of the volatility and kind

550
00:28:14,359 --> 00:28:17,639
Speaker 11: of circular circular risk of the of the technology in

551
00:28:17,680 --> 00:28:18,480
Speaker 11: the market.

552
00:28:18,760 --> 00:28:22,200
Speaker 3: How much is there an anxiety that not only they're

553
00:28:22,200 --> 00:28:25,320
Speaker 3: going to be an outsized waiting in well just passive

554
00:28:25,359 --> 00:28:28,400
Speaker 3: funds more broadly, but they're also all related to.

555
00:28:28,359 --> 00:28:29,440
Speaker 2: One another in some way.

556
00:28:29,600 --> 00:28:32,439
Speaker 3: The fact that anthropics buy and compute of SpaceX, the

557
00:28:32,440 --> 00:28:35,480
Speaker 3: fact that we're starting to see this circular deal making

558
00:28:35,680 --> 00:28:38,040
Speaker 3: come ever more present into the public market.

559
00:28:38,760 --> 00:28:39,160
Speaker 2: That's right.

560
00:28:39,240 --> 00:28:41,280
Speaker 11: I mean, that's that's one of the reasons why people

561
00:28:41,440 --> 00:28:43,160
Speaker 11: kind of point out and there is some kind of

562
00:28:43,160 --> 00:28:48,400
Speaker 11: the bubble element in kind of today's AI market a marketplace.

563
00:28:48,680 --> 00:28:50,800
Speaker 11: And in addition to that, I think It's another thing

564
00:28:50,840 --> 00:28:53,400
Speaker 11: to think about is that technology is kind of at

565
00:28:53,440 --> 00:28:56,600
Speaker 11: its innacent stage. A lot of the technology, I mean,

566
00:28:56,640 --> 00:28:59,840
Speaker 11: this AAIs is a real technology, and it was in

567
00:28:59,880 --> 00:29:03,280
Speaker 11: the phase of tech demonstration that we have seen tremendous potential.

568
00:29:03,680 --> 00:29:06,800
Speaker 11: But it by no means that in terms of engineering

569
00:29:07,720 --> 00:29:10,200
Speaker 11: they need to go into it for optimizing and making

570
00:29:10,280 --> 00:29:12,680
Speaker 11: them bring it down to the right price point and

571
00:29:12,680 --> 00:29:14,560
Speaker 11: et cetera. There's a lot of work to be done.

572
00:29:14,880 --> 00:29:17,680
Speaker 11: So in terms of the kind of technology and infrastructure

573
00:29:17,720 --> 00:29:21,480
Speaker 11: and how it's formed, it's not near. It's kind of

574
00:29:21,520 --> 00:29:23,960
Speaker 11: the end state, and there's a lot of the improvement

575
00:29:24,360 --> 00:29:26,680
Speaker 11: to be done. And I think that the improvement could

576
00:29:26,720 --> 00:29:30,080
Speaker 11: be current big giants or it could be come from

577
00:29:30,120 --> 00:29:33,680
Speaker 11: the other stars they're working on solving the specific problems.

578
00:29:33,880 --> 00:29:36,680
Speaker 11: So there is a lot of innovation too to be.

579
00:29:38,120 --> 00:29:38,520
Speaker 8: Ahead.

580
00:29:38,560 --> 00:29:41,360
Speaker 11: And I think it's a that's an interesting moment because

581
00:29:42,440 --> 00:29:46,240
Speaker 11: another another thing to think about is that this kind

582
00:29:46,240 --> 00:29:50,200
Speaker 11: of the access to the capital and be building this

583
00:29:50,360 --> 00:29:53,520
Speaker 11: capital mode around the company has become part of the

584
00:29:53,560 --> 00:29:56,840
Speaker 11: feature of the of their service and and and their business.

585
00:29:57,200 --> 00:29:58,680
Speaker 11: And I think there's a lot of kind of the

586
00:29:59,160 --> 00:30:03,400
Speaker 11: circle deals that you mentioned, and it's kind of creating

587
00:30:03,440 --> 00:30:06,760
Speaker 11: this the mode against a new entrance, and I think

588
00:30:06,760 --> 00:30:09,840
Speaker 11: that that's kind of one of the reasons why that

589
00:30:09,920 --> 00:30:12,560
Speaker 11: there is a rush into this like IPO and access

590
00:30:12,600 --> 00:30:14,000
Speaker 11: to large sum of capital.

591
00:30:14,320 --> 00:30:16,600
Speaker 3: I mean, you're a previously a member of South Korea's

592
00:30:16,600 --> 00:30:19,480
Speaker 3: Presidential Advisory Council and Science and Technology. I mean, this

593
00:30:19,640 --> 00:30:22,920
Speaker 3: AI exuberance and hype hasn't just been US alone. We've

594
00:30:22,960 --> 00:30:26,920
Speaker 3: seen extraordinary growth of South Korean stocks Skhenex, and they're like,

595
00:30:27,640 --> 00:30:29,680
Speaker 3: is this a global moment of reckoning? Do you think

596
00:30:29,760 --> 00:30:31,640
Speaker 3: that there is a so called bubble and it needs.

597
00:30:31,480 --> 00:30:32,000
Speaker 2: To come down?

598
00:30:33,040 --> 00:30:35,320
Speaker 11: I mean, I think it's an AI is an interesting,

599
00:30:35,760 --> 00:30:40,760
Speaker 11: interesting technology because as soon as we say like artificial intelligence,

600
00:30:41,160 --> 00:30:44,600
Speaker 11: the name is solved, really kind of sparkles imagination of a

601
00:30:44,560 --> 00:30:47,800
Speaker 11: lot of people, and people tend to entthromorphize like what

602
00:30:47,840 --> 00:30:50,720
Speaker 11: AI can do. And I think that also feels into

603
00:30:50,840 --> 00:30:54,280
Speaker 11: this kind of that the hype behavior and like over

604
00:30:54,440 --> 00:31:00,640
Speaker 11: expectation and extrapolating what this technology can do, because I mean,

605
00:31:00,640 --> 00:31:03,760
Speaker 11: I think that because of the global dominance of the

606
00:31:03,840 --> 00:31:07,720
Speaker 11: US tech market tech companies over the past decades, I

607
00:31:07,720 --> 00:31:12,160
Speaker 11: think the growth of this giant AI company is affecting

608
00:31:12,920 --> 00:31:15,880
Speaker 11: the supply chain outside of the US, and like I

609
00:31:15,880 --> 00:31:19,360
Speaker 11: mean conductor companies, infrastrcure companies not just in the US,

610
00:31:19,480 --> 00:31:22,959
Speaker 11: but elsewhere, and I think that's also beeding into the

611
00:31:23,280 --> 00:31:24,480
Speaker 11: other markets. Excitement.

612
00:31:24,760 --> 00:31:27,680
Speaker 3: I mean you see innovation at public level sitting on

613
00:31:27,720 --> 00:31:30,160
Speaker 3: the board of HP. At the private level, when you're

614
00:31:30,200 --> 00:31:33,320
Speaker 3: investing for principal ventures partners, where is exciting and where

615
00:31:33,320 --> 00:31:35,160
Speaker 3: do you think is undervalued right now? If you're going

616
00:31:35,200 --> 00:31:37,160
Speaker 3: to be putting capital to work privately.

617
00:31:37,760 --> 00:31:40,480
Speaker 11: I mean, there's a lot of innovation to be made.

618
00:31:41,280 --> 00:31:44,880
Speaker 11: I think it's so if you think about airline industry, right,

619
00:31:44,880 --> 00:31:47,520
Speaker 11: I mean, I think there are only a small number

620
00:31:47,560 --> 00:31:49,800
Speaker 11: of companies that can make engine, But if you think

621
00:31:49,800 --> 00:31:52,880
Speaker 11: about where all the business happening is taking place, there

622
00:31:52,880 --> 00:31:55,080
Speaker 11: are companies that are making airplanes, that are making kind

623
00:31:55,080 --> 00:31:57,720
Speaker 11: of they're operating airlines, and there are a lot of

624
00:31:58,000 --> 00:32:01,760
Speaker 11: businesses hospital around it. So I think it's a we

625
00:32:01,920 --> 00:32:04,760
Speaker 11: have we have found this like kind of tremendous engine

626
00:32:04,800 --> 00:32:08,640
Speaker 11: technology they can they can that has a potential to

627
00:32:08,640 --> 00:32:12,280
Speaker 11: build whole new businesses and open up the whole new possibilities.

628
00:32:12,480 --> 00:32:14,120
Speaker 11: But like a lot there are a lot of businesses

629
00:32:14,160 --> 00:32:17,520
Speaker 11: and applications to be built on top of that, and

630
00:32:17,720 --> 00:32:21,480
Speaker 11: where the where the more values and there created, where

631
00:32:21,480 --> 00:32:23,680
Speaker 11: the value is going to be captured and held? I

632
00:32:23,680 --> 00:32:25,240
Speaker 11: think it's yet to be determined.

633
00:32:25,880 --> 00:32:29,640
Speaker 3: Fascinating, Songy and you Princeiviple Ventures partners, thank you forking

634
00:32:29,720 --> 00:32:30,680
Speaker 3: us through your thinking.

635
00:32:31,200 --> 00:32:33,560
Speaker 2: We hope to welcome back soon. Meanwhile, Elon Musk has.

636
00:32:33,520 --> 00:32:36,200
Speaker 3: Unveiled a more detailed look at an initial version of

637
00:32:36,200 --> 00:32:39,800
Speaker 3: an AI data center satellite SpaceX plans to build that

638
00:32:39,960 --> 00:32:42,960
Speaker 3: as part of a roughly one million satellite network, but

639
00:32:43,040 --> 00:32:47,360
Speaker 3: we'll do complex computing four AI in Earth orbit in space.

640
00:32:47,920 --> 00:32:51,000
Speaker 3: So during a thirty minute video shared on x must

641
00:32:51,080 --> 00:32:53,479
Speaker 3: really laid out other plans for the future of this company,

642
00:32:53,520 --> 00:32:56,800
Speaker 3: including the continued development of its Starship rocket and joint

643
00:32:56,880 --> 00:33:00,360
Speaker 3: terrified facility with Tesla that aims to manufacture computer chips

644
00:33:00,400 --> 00:33:03,680
Speaker 3: in the United States. Coming up, well, we got more

645
00:33:03,720 --> 00:33:05,400
Speaker 3: on AI and this time it's all about robotics. The

646
00:33:05,440 --> 00:33:08,400
Speaker 3: company Standard Boss just raising two hundred million dollars in

647
00:33:08,440 --> 00:33:11,080
Speaker 3: a new round of funding. It's CEO even Bed's going

648
00:33:11,120 --> 00:33:12,120
Speaker 3: to be joining us next.

649
00:33:12,400 --> 00:33:13,280
Speaker 2: But let's get back.

650
00:33:13,120 --> 00:33:15,760
Speaker 3: To markets, because there's been a huge, like a thousand

651
00:33:15,760 --> 00:33:16,520
Speaker 3: point swing.

652
00:33:16,320 --> 00:33:18,080
Speaker 2: On the NASAK one hundred. Right now I'm.

653
00:33:17,920 --> 00:33:21,440
Speaker 3: Looking at it's going from peak of twenty nine eight

654
00:33:21,520 --> 00:33:24,160
Speaker 3: hundred down to now twenty eight thy eight hundred in

655
00:33:24,200 --> 00:33:26,000
Speaker 3: the course of half an hour or so.

656
00:33:26,120 --> 00:33:26,560
Speaker 2: Is trading.

657
00:33:26,720 --> 00:33:29,000
Speaker 3: We're seeing money being pulled out of chips of hardware,

658
00:33:29,000 --> 00:33:31,240
Speaker 3: in particular of Apple. We're seeing the S and P

659
00:33:31,280 --> 00:33:34,000
Speaker 3: five hundred now down by percentage point, the Semiconductor index

660
00:33:34,040 --> 00:33:36,960
Speaker 3: off by almost four percent. It is a volatile session

661
00:33:37,320 --> 00:33:46,800
Speaker 3: and a volatile few training days is a bluebotech. New

662
00:33:46,880 --> 00:33:49,680
Speaker 3: York based startups Standard Bots has raised two hundred million

663
00:33:49,680 --> 00:33:51,840
Speaker 3: dollars in a new round of funding to scale its

664
00:33:51,880 --> 00:33:53,040
Speaker 3: AI powered robots.

665
00:33:53,200 --> 00:33:55,920
Speaker 2: Now as a company tracks to secure ten percent.

666
00:33:55,720 --> 00:33:59,600
Speaker 3: Actually of all robots deployed in the United States, CEO

667
00:33:59,720 --> 00:34:03,520
Speaker 3: is actively advising Congress I'm banning Chinese competitors over national

668
00:34:03,560 --> 00:34:04,360
Speaker 3: security risks.

669
00:34:04,640 --> 00:34:05,480
Speaker 2: We can talk at all.

670
00:34:05,360 --> 00:34:08,759
Speaker 3: Now a Standbot's co found CEO, Evan Beard, congratulations on

671
00:34:08,800 --> 00:34:11,360
Speaker 3: the race. Let's start their Series C one billion dollar valuation.

672
00:34:11,560 --> 00:34:12,920
Speaker 2: Would you get the two hundred.

673
00:34:12,600 --> 00:34:14,640
Speaker 12: Million for thanks so much, Thanks for having me back.

674
00:34:15,239 --> 00:34:18,760
Speaker 12: So we're using this funding to quadruple our manufacturing footprint.

675
00:34:18,760 --> 00:34:21,400
Speaker 12: We've got a huge backlog of demand. We're growing very

676
00:34:21,440 --> 00:34:23,440
Speaker 12: quickly and to also invest in more R and D.

677
00:34:23,760 --> 00:34:25,080
Speaker 2: So it's going to be in Long Island.

678
00:34:25,160 --> 00:34:27,680
Speaker 3: I understand how much sort of square footage, what sort

679
00:34:27,680 --> 00:34:31,560
Speaker 3: of talent and R and D hardware do you need?

680
00:34:31,840 --> 00:34:33,719
Speaker 12: Yeah, So we have an engineering office in New York

681
00:34:33,719 --> 00:34:36,600
Speaker 12: City and our manufacturing space is seventy thousand square feet.

682
00:34:36,640 --> 00:34:38,400
Speaker 12: It's about an hour outside New York City, but we

683
00:34:38,440 --> 00:34:40,080
Speaker 12: think is the best city on earth, the best place

684
00:34:40,120 --> 00:34:43,040
Speaker 12: to build robotics business and standardbots. Now we believe is

685
00:34:43,040 --> 00:34:47,080
Speaker 12: America's largest AI native industrial robot manufacturer. So and we're

686
00:34:47,120 --> 00:34:47,840
Speaker 12: just getting started.

687
00:34:47,960 --> 00:34:52,640
Speaker 3: And by steal foremost, how many do you already have deployed?

688
00:34:52,920 --> 00:34:54,520
Speaker 2: How many are out there in the wild?

689
00:34:54,560 --> 00:34:57,280
Speaker 3: What makes you such as significant force in robotics already?

690
00:34:57,480 --> 00:34:59,960
Speaker 8: Yeah, well, I could say we have basically in every state.

691
00:35:00,160 --> 00:35:02,319
Speaker 12: We have small and medium businesses using our robot and

692
00:35:02,360 --> 00:35:05,520
Speaker 12: we have iconic companies in aerospace, automotive, oil and gas

693
00:35:05,600 --> 00:35:08,200
Speaker 12: data centers. So really we're working with the full gambit

694
00:35:08,239 --> 00:35:12,920
Speaker 12: of folks that use robots. My favorite customer makes parts for.

695
00:35:12,840 --> 00:35:15,280
Speaker 8: The Long Island Railroad. And the reason I will.

696
00:35:15,360 --> 00:35:17,920
Speaker 2: Pick favorite children, Yeah.

697
00:35:17,200 --> 00:35:19,640
Speaker 12: They were our first customers still a customer after a

698
00:35:19,640 --> 00:35:22,959
Speaker 12: few years. And it's really emblematic if everyone uses our robot,

699
00:35:23,040 --> 00:35:26,040
Speaker 12: which is they're making the things that make America, whether

700
00:35:26,080 --> 00:35:29,359
Speaker 12: it's the infrastructure or the products that we use, so

701
00:35:30,280 --> 00:35:30,960
Speaker 12: the railroad.

702
00:35:31,200 --> 00:35:34,239
Speaker 3: Are they kind of playing using robots and understanding how

703
00:35:34,280 --> 00:35:35,680
Speaker 3: they're going to work with them in the future. Are

704
00:35:35,680 --> 00:35:39,320
Speaker 3: they really giving an awful lot of hard duty work

705
00:35:39,600 --> 00:35:42,239
Speaker 3: to these humanoids? Are they able or arms that you make,

706
00:35:42,280 --> 00:35:44,320
Speaker 3: are they able to hire less for example?

707
00:35:44,400 --> 00:35:46,160
Speaker 12: Yeah, it's a good question, and investors asked that. But

708
00:35:46,200 --> 00:35:48,480
Speaker 12: eighty five percent of our robots are doing production work.

709
00:35:48,560 --> 00:35:51,320
Speaker 12: So these are not pilots, These are not just testing

710
00:35:51,360 --> 00:35:54,400
Speaker 12: things out. These they're actually doing a job. And we

711
00:35:54,440 --> 00:35:56,399
Speaker 12: think of robots as the power tool of the twenty

712
00:35:56,440 --> 00:35:59,160
Speaker 12: first century. So they really enable a worker to do

713
00:35:59,600 --> 00:36:02,040
Speaker 12: much more work before they improve the efficiency of our

714
00:36:02,040 --> 00:36:05,480
Speaker 12: country and our workforce and k The problem that we

715
00:36:05,520 --> 00:36:07,560
Speaker 12: see and what we said to Congress was the United

716
00:36:07,600 --> 00:36:10,000
Speaker 12: States right now is not competitive and manufacturing. If you

717
00:36:10,000 --> 00:36:12,680
Speaker 12: look at the United States against China and other countries,

718
00:36:12,719 --> 00:36:14,359
Speaker 12: it can be five to ten x cheaper to make

719
00:36:14,360 --> 00:36:17,160
Speaker 12: your parts in those countries. And so we think robots

720
00:36:17,200 --> 00:36:19,680
Speaker 12: are this foundational technology that we as a country need

721
00:36:19,719 --> 00:36:22,120
Speaker 12: to be more competitive, to be able to compete and

722
00:36:22,200 --> 00:36:25,000
Speaker 12: to ultimately bring back jobs and bring back our manufacturing base.

723
00:36:25,160 --> 00:36:30,319
Speaker 3: Foundational technology. Now you need the models to be able

724
00:36:30,360 --> 00:36:32,480
Speaker 3: to drive these robots. I'm interested as to what you've done.

725
00:36:32,520 --> 00:36:34,719
Speaker 3: I mean many would say in video in particular, saying

726
00:36:34,719 --> 00:36:36,640
Speaker 3: that we're not quite there yet with physical AI.

727
00:36:36,680 --> 00:36:38,360
Speaker 2: We're going to have this CHATCHYBT moment.

728
00:36:38,440 --> 00:36:41,640
Speaker 3: But how you seeing these models evolving or indeed your

729
00:36:41,680 --> 00:36:43,759
Speaker 3: robot's able to change and diversify.

730
00:36:43,920 --> 00:36:45,879
Speaker 12: Yeah, it's a great question, and it's a reason why

731
00:36:45,920 --> 00:36:48,080
Speaker 12: the US can take a lead in robotics right now.

732
00:36:48,200 --> 00:36:51,080
Speaker 12: And the answer there is we're focused on training robots

733
00:36:51,120 --> 00:36:53,000
Speaker 12: or demonstrations, so you show them what to do. We

734
00:36:53,040 --> 00:36:54,719
Speaker 12: have a handheld device for that and you can just

735
00:36:54,760 --> 00:36:57,120
Speaker 12: perform the task and you don't have to be an expert.

736
00:36:57,360 --> 00:36:59,359
Speaker 12: And what it allows us to do is take an

737
00:36:59,360 --> 00:37:01,759
Speaker 12: average of S worker, a manufacturing worker, and they can

738
00:37:01,800 --> 00:37:04,279
Speaker 12: now program a robot and train an AI model. And

739
00:37:04,320 --> 00:37:06,880
Speaker 12: this allows the robots to handle variability that they couldn't before.

740
00:37:07,080 --> 00:37:08,960
Speaker 12: It allows them to do jobs that you just couldn't

741
00:37:08,960 --> 00:37:10,880
Speaker 12: automate before. Because today's robots.

742
00:37:10,880 --> 00:37:12,920
Speaker 8: Most people don't know. They really just replay motions.

743
00:37:13,080 --> 00:37:15,560
Speaker 12: You program that millimeter by millimeter, and they can play

744
00:37:15,600 --> 00:37:18,320
Speaker 12: through and paint in well that way, but they're so limiting.

745
00:37:18,360 --> 00:37:21,240
Speaker 12: And so this is a fundamental change in what's possible

746
00:37:21,440 --> 00:37:22,960
Speaker 12: and what you can automate with your robots.

747
00:37:23,239 --> 00:37:27,280
Speaker 3: So Evan many would say, well, you're getting people to

748
00:37:27,360 --> 00:37:30,840
Speaker 3: train their replacements. How are those that are working at

749
00:37:30,840 --> 00:37:33,120
Speaker 3: the railroad feeling about helping train these robots?

750
00:37:33,120 --> 00:37:35,320
Speaker 2: Would you see as the future of manufacturing workforce?

751
00:37:35,480 --> 00:37:37,600
Speaker 12: It's a fair question. It's one we think about a lot.

752
00:37:37,640 --> 00:37:39,839
Speaker 12: And my favorite anecdote in this regard is really from

753
00:37:39,920 --> 00:37:42,239
Speaker 12: Milton Freeman, and he visited a job site in the

754
00:37:42,280 --> 00:37:45,160
Speaker 12: seventies and he asked, why aren't they using Earth Moviment equipment.

755
00:37:45,280 --> 00:37:45,640
Speaker 8: It was in a.

756
00:37:45,640 --> 00:37:48,319
Speaker 12: Developing country and they were digging with shovels, and they said, well,

757
00:37:48,360 --> 00:37:51,120
Speaker 12: this is the jobs project. So if we gave them shovels,

758
00:37:51,160 --> 00:37:52,839
Speaker 12: if we gave them Mirth movie equipment, will create way

759
00:37:52,880 --> 00:37:53,560
Speaker 12: fewer jobs.

760
00:37:53,840 --> 00:37:56,160
Speaker 8: And he said, well, why don't you just give them spoons.

761
00:37:56,640 --> 00:37:59,040
Speaker 12: And the point that Milton was making was you earned

762
00:37:59,080 --> 00:38:01,439
Speaker 12: the right to create high paying jobs by creating something

763
00:38:01,440 --> 00:38:03,759
Speaker 12: of economic value, and I think the United States in

764
00:38:03,800 --> 00:38:06,120
Speaker 12: this next transition wants to be on the right side

765
00:38:06,120 --> 00:38:08,359
Speaker 12: of that, and we want to use the tools which

766
00:38:08,400 --> 00:38:09,759
Speaker 12: are in the physical world.

767
00:38:09,760 --> 00:38:10,960
Speaker 8: It's robots, and it's.

768
00:38:11,200 --> 00:38:12,799
Speaker 12: We really view them as this power tool, like a

769
00:38:12,880 --> 00:38:15,120
Speaker 12: drill for workers to be more efficient and be able

770
00:38:15,160 --> 00:38:15,640
Speaker 12: to do more.

771
00:38:15,880 --> 00:38:17,160
Speaker 8: And we want to be on the right.

772
00:38:17,080 --> 00:38:18,680
Speaker 2: Side of that, right side of that.

773
00:38:18,800 --> 00:38:21,000
Speaker 3: With two hundred million dollars to keep on expanding here

774
00:38:21,040 --> 00:38:22,719
Speaker 3: in the state of New York, we appreciate your time,

775
00:38:22,760 --> 00:38:25,239
Speaker 3: Thank you very much. Indeed, standing bots co founder and

776
00:38:25,280 --> 00:38:29,360
Speaker 3: CEO Evan Beard there now. The Mizuho Technology Conference is

777
00:38:29,440 --> 00:38:31,960
Speaker 3: underway here in New York as well, bringing together top

778
00:38:32,000 --> 00:38:35,120
Speaker 3: tech executives industry leaders. Speaking earlier, we've both remained bostic.

779
00:38:35,280 --> 00:38:38,480
Speaker 3: It's not the CEO as I seen Ghazi really weighing

780
00:38:38,520 --> 00:38:41,400
Speaker 3: in on the tightening restrictions targeting China ticulous, and.

781
00:38:42,360 --> 00:38:46,280
Speaker 13: We are assuming China will remain the way it is currently,

782
00:38:46,520 --> 00:38:50,120
Speaker 13: meaning our China business, specific to IP was one of

783
00:38:50,160 --> 00:38:54,520
Speaker 13: our fastest going regions that hit the significant headwinds due

784
00:38:54,560 --> 00:38:58,080
Speaker 13: to all the restrictions. I don't believe these restrictions are

785
00:38:58,120 --> 00:39:01,360
Speaker 13: going to change. If they change fantastic. If not, we

786
00:39:01,440 --> 00:39:05,879
Speaker 13: have plenty of opportunities outside of China to capture the.

787
00:39:05,840 --> 00:39:07,560
Speaker 2: Growth coming up.

788
00:39:07,600 --> 00:39:10,640
Speaker 3: Also in New York, well, the city's controller slams Elon

789
00:39:10,760 --> 00:39:13,720
Speaker 3: Musks near total control of SpaceX ahead of the IPO

790
00:39:14,040 --> 00:39:16,240
Speaker 3: for excluding the company won't be easy for the city's

791
00:39:16,239 --> 00:39:18,919
Speaker 3: pension fund or others will have the details. And look,

792
00:39:18,960 --> 00:39:20,960
Speaker 3: let's get back to these public markets that SpaceX is

793
00:39:21,000 --> 00:39:23,600
Speaker 3: about to enter. They're down. They're down pretty hard. Then

794
00:39:23,600 --> 00:39:25,680
Speaker 3: as that one hundred rolling over one point nine percent.

795
00:39:25,719 --> 00:39:27,719
Speaker 3: We were higher at the start of trade s P

796
00:39:27,760 --> 00:39:29,160
Speaker 3: five hundred or five percentage point.

797
00:39:29,200 --> 00:39:31,520
Speaker 2: We've got Apple, you've got the likes of big tech.

798
00:39:31,600 --> 00:39:33,399
Speaker 3: Tesla's in the red at the moment, we've got Mike

799
00:39:33,440 --> 00:39:35,719
Speaker 3: crumpling down in a points perspective, and that's why we

800
00:39:35,800 --> 00:39:38,320
Speaker 3: mean see the semiconductor index also under pressure.

801
00:39:38,560 --> 00:39:39,439
Speaker 2: This will bely med tech.

802
00:39:50,200 --> 00:39:54,320
Speaker 3: New York City Controller Mark Levine says Elon Musks unprecedented

803
00:39:54,400 --> 00:39:58,400
Speaker 3: control will have over SpaceX serves as a new level

804
00:39:58,400 --> 00:40:01,560
Speaker 3: of disregard for regular shaf holders rights. In an interviewed,

805
00:40:01,960 --> 00:40:04,399
Speaker 3: Lavin said he quote understands that we're in an error

806
00:40:04,400 --> 00:40:07,640
Speaker 3: of founders wanting more control that what Musk is planning

807
00:40:07,640 --> 00:40:10,640
Speaker 3: with SpaceX is way beyond what we've seen.

808
00:40:11,280 --> 00:40:13,920
Speaker 2: This is, of course, in reference to the stipulation that buying.

809
00:40:13,680 --> 00:40:16,920
Speaker 3: Into SpaceX requires accepting a governance structure giving Musk roughly

810
00:40:16,960 --> 00:40:20,160
Speaker 3: eighty percent of voting rights. Ne Megs Olivia Ramunday is

811
00:40:20,239 --> 00:40:23,440
Speaker 3: one of the key reporters that have just gone global

812
00:40:23,480 --> 00:40:25,719
Speaker 3: with this story. And let's start with New York New

813
00:40:25,800 --> 00:40:27,800
Speaker 3: York State as well. There are a lot of people

814
00:40:27,800 --> 00:40:30,359
Speaker 3: managing pension fund money who were worried about this level

815
00:40:30,400 --> 00:40:31,320
Speaker 3: of control.

816
00:40:31,680 --> 00:40:36,680
Speaker 14: Yes, Caroline, absolutely. I think that the controller's main concern

817
00:40:36,920 --> 00:40:40,840
Speaker 14: is about having shareholders' voices be heard when they invest

818
00:40:40,920 --> 00:40:45,080
Speaker 14: in a public company, and to have leadership and executives

819
00:40:45,080 --> 00:40:48,400
Speaker 14: in those companies be held accountable to the concerns that

820
00:40:48,440 --> 00:40:53,520
Speaker 14: their shareholders have around different issues related to the government

821
00:40:53,600 --> 00:40:56,520
Speaker 14: structure of a company. I think what Levine wanted to

822
00:40:56,560 --> 00:40:59,600
Speaker 14: explain to me is that he wants shareholders to still

823
00:40:59,640 --> 00:41:03,520
Speaker 14: be in with their ability to vote in a one vote,

824
00:41:03,520 --> 00:41:04,800
Speaker 14: one share type of structure.

825
00:41:04,920 --> 00:41:06,960
Speaker 2: So is he saying I'm going to boycott it.

826
00:41:07,040 --> 00:41:08,920
Speaker 3: Is he saying I can vote with my feet with

827
00:41:09,000 --> 00:41:10,840
Speaker 3: my money and make an impact, or does he have

828
00:41:10,880 --> 00:41:12,760
Speaker 3: to kind of go along with what is the biggest

829
00:41:12,800 --> 00:41:13,520
Speaker 3: IPO ever.

830
00:41:13,880 --> 00:41:16,120
Speaker 14: That's a great question, and based on my conversation that

831
00:41:16,160 --> 00:41:18,399
Speaker 14: I had with him last week, I do not think

832
00:41:18,440 --> 00:41:21,240
Speaker 14: the goal right now is to divest from the company

833
00:41:21,360 --> 00:41:24,440
Speaker 14: or to exclude any type of exposure. He explained to

834
00:41:24,480 --> 00:41:27,960
Speaker 14: me that with the pension system's own governance structure, that

835
00:41:27,960 --> 00:41:31,480
Speaker 14: would be difficult. They have done sector based in exclusions

836
00:41:31,520 --> 00:41:35,120
Speaker 14: before for the oil and gas industry, but to eliminate

837
00:41:35,239 --> 00:41:38,879
Speaker 14: one company, he said, for their own governance structure, would

838
00:41:38,920 --> 00:41:42,239
Speaker 14: be unprecedented. What he wants to do is he wants

839
00:41:42,280 --> 00:41:45,080
Speaker 14: to engage with Elon Musk. He reached out to Musk

840
00:41:45,200 --> 00:41:47,680
Speaker 14: in a letter co signed by Kelpers and the New

841
00:41:47,800 --> 00:41:51,200
Speaker 14: York State pension funds. They want mus to engage with

842
00:41:51,239 --> 00:41:53,839
Speaker 14: them and to work with them so that they can

843
00:41:53,920 --> 00:41:56,799
Speaker 14: make changes from within, rather than just saying we're not

844
00:41:56,880 --> 00:41:57,920
Speaker 14: going to invest.

845
00:41:58,200 --> 00:41:59,840
Speaker 2: That's far no response.

846
00:42:00,160 --> 00:42:02,200
Speaker 3: This is a global issue there and in some pension

847
00:42:02,200 --> 00:42:04,520
Speaker 3: funds in Europe there actually are saying I don't want

848
00:42:04,560 --> 00:42:05,319
Speaker 3: anything to do with this.

849
00:42:05,680 --> 00:42:09,000
Speaker 14: We've had pension funds and investors in Denmark and the

850
00:42:09,080 --> 00:42:10,839
Speaker 14: UK say that they are going to sit out from

851
00:42:10,840 --> 00:42:14,799
Speaker 14: the IPO. That they will be willing to adjust their

852
00:42:16,680 --> 00:42:19,759
Speaker 14: funds so that they are not exposed to SpaceX. One

853
00:42:20,560 --> 00:42:25,080
Speaker 14: UK focused investor specifically said that they called the governance

854
00:42:25,080 --> 00:42:28,200
Speaker 14: structure catastrophic and that it would not be prudent to

855
00:42:28,680 --> 00:42:31,120
Speaker 14: have their investors exposed to it.

856
00:42:31,600 --> 00:42:32,279
Speaker 2: Fascinating.

857
00:42:32,760 --> 00:42:34,800
Speaker 3: While we can go in a lot into that story

858
00:42:34,840 --> 00:42:37,120
Speaker 3: about some of the reticence and the reasons why Olivia

859
00:42:37,120 --> 00:42:39,520
Speaker 3: and Rounde, I mean, go read her story. It's a

860
00:42:39,560 --> 00:42:42,320
Speaker 3: real deep dive into the governance of this business. Meanwhile,

861
00:42:42,320 --> 00:42:45,120
Speaker 3: we're looking at life pictures of NASA, which is just

862
00:42:45,200 --> 00:42:48,000
Speaker 3: about to introduce its next Artemist crew two months after

863
00:42:48,040 --> 00:42:50,960
Speaker 3: sending astronauts on a record setting lunafly by NASA, says,

864
00:42:51,040 --> 00:42:54,680
Speaker 3: Artemist three launched four astronauts from the Kennedy Space Center

865
00:42:54,760 --> 00:42:55,440
Speaker 3: in Florida.

866
00:42:55,640 --> 00:42:57,960
Speaker 2: Will the Orion spacecraft on the Space.

867
00:42:57,719 --> 00:43:02,840
Speaker 3: Launch System rocket the mission It's gonna last two weeks now,

868
00:43:03,200 --> 00:43:06,560
Speaker 3: that does it? Though, for this edition of Bloomberg Tech,

869
00:43:06,640 --> 00:43:10,560
Speaker 3: as we await that news from Artemis three, we see

870
00:43:10,560 --> 00:43:11,719
Speaker 3: that the market's really taking in turn.

871
00:43:11,719 --> 00:43:13,360
Speaker 2: Look, we're plunging to new loads of the day and.

872
00:43:13,360 --> 00:43:15,600
Speaker 3: As like one hundred off by two point two percent,

873
00:43:15,680 --> 00:43:18,399
Speaker 3: let's call it one thousand point swing. This is as

874
00:43:18,400 --> 00:43:20,600
Speaker 3: you see, really big tech names take the brunt of

875
00:43:20,640 --> 00:43:24,200
Speaker 3: the hit. We've got money coming out, in particular of Apple,

876
00:43:24,600 --> 00:43:27,440
Speaker 3: of Micron, of Tesla. In fact, the SP five hundred

877
00:43:27,480 --> 00:43:30,120
Speaker 3: is off by percent, let's call it. But actually underneath

878
00:43:30,120 --> 00:43:33,240
Speaker 3: the hood is doing rather better. From a cross industry perspective,

879
00:43:33,280 --> 00:43:34,960
Speaker 3: it really is tech in the line of fire. As

880
00:43:34,960 --> 00:43:37,120
Speaker 3: many feel that perhaps we've run too far, too fast.

881
00:43:37,120 --> 00:43:39,120
Speaker 3: There's a lot of volatility in the market and a

882
00:43:39,160 --> 00:43:40,880
Speaker 3: lot of red flags. At the back of America have

883
00:43:41,000 --> 00:43:44,000
Speaker 3: been saying to clients, too many red flags take profits

884
00:43:44,040 --> 00:43:46,680
Speaker 3: while you can the Semiconductor index off by four point

885
00:43:46,680 --> 00:43:49,040
Speaker 3: four percent after we claws back some of Friday sessions

886
00:43:49,040 --> 00:43:50,440
Speaker 3: losses just yesterday.

887
00:43:50,920 --> 00:43:52,719
Speaker 2: Look, you can recap all of this. Don't forget to

888
00:43:52,760 --> 00:43:53,600
Speaker 2: check out the podcast.

889
00:43:53,800 --> 00:43:55,320
Speaker 3: You'll find out on the terminal as well as online

890
00:43:55,320 --> 00:43:56,480
Speaker 3: on Apple, Spotify.

891
00:43:56,120 --> 00:43:58,719
Speaker 2: And iHeart. From New York, this is Bloomberg Tech