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Speaker 1: Bloomberg Audio Studios, podcasts, radio news.

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Speaker 2: We want to go live to the stage in Davos

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Speaker 2: now where Elon Musk is speaking with black Rock CEO.

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Speaker 3: Very think it's an important component of huween what we

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Speaker 3: are and I'm thrilled to have Elon Musk here.

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Speaker 4: He came all the way from California to be here.

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Speaker 4: It's to see all of you. So thank you, Elon.

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Speaker 5: You was welcome. I mean I heard I heard about

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Speaker 5: about the formation of the Peace Summit and I was like,

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Speaker 5: is that is that p I e c uh, you know,

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Speaker 5: a little piece of Greenland, a little Pisa.

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Speaker 4: Thanks, we got one.

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Speaker 5: All we want is peace.

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Speaker 3: Okay, I'm gonna as I said, I'm a pretty proud

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Speaker 3: uh CEO of black Rock since we went public. Uh,

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Speaker 3: the com pounding return of blocklock to our shoulders with

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Speaker 3: twenty one percent. Since Elon took Tesla public, his compounded.

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Speaker 4: Return is forty three percent.

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Speaker 3: This is just another advertisement for everybody, especially for Europeans.

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Speaker 3: This is why more citizens should be investing with growth,

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Speaker 3: investing with your countries. Imagine if a lot of pension

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Speaker 3: funds invested with Elon when Tesla went public and how

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Speaker 3: much we return with the all the pension funds that

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Speaker 3: invested side by side with Elon and the growth, so

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Speaker 3: a spectacular return.

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Speaker 4: There's very few companies.

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Speaker 3: Well, I don't think there's any other company as large

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Speaker 3: as Tesla today that has that compoundent return.

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Speaker 4: So congratulations, I think a good measurement.

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Speaker 5: Well, we have an incredible team a Tesla. That's the reason.

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Speaker 3: So I want to get into there the meaningful component

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Speaker 3: about technology, the possibilities. I want to talk about AI

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Speaker 3: and robotics, energy, space and the progress ultimately coming down

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Speaker 3: to engineering, engineering, discipline, scale execution, and few people, if

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Speaker 3: not anyone, has the experience and the fortitude to confront

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Speaker 3: these issues head on, not just the ideas, but the

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Speaker 3: execution across so many different technology Zelon and that's why

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Speaker 3: I thought it was important for us to have this

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Speaker 3: dialogue here in Davos. So you're presently building on AI,

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Speaker 3: on robotics, on space, on energy all at the same time.

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Speaker 3: When you look across those efforts, what do they have

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Speaker 3: in common from an engineering standpoint, Well, they're.

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Speaker 5: All vertical technology challenges.

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Speaker 4: But the.

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Speaker 5: Overall goal of my companies is to maximize the future

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Speaker 5: of civilization, like basically maximize the probability that civilization has

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Speaker 5: a great future and to expand consciousness beyond Earth. So

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Speaker 5: take SpaceX for example, that SpaceX is about build advancing

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Speaker 5: rocket technology to the point where we can extend life

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Speaker 5: and consciousness beyond Earth, to the Moon, to Mars, eventually

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Speaker 5: to other star systems. And I think we should always

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Speaker 5: view consciousness life as we know it, as as precarious

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Speaker 5: and delicate, because to the best of our knowledge, we

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Speaker 5: don't know if life anywhere else. You know, I'm often

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Speaker 5: asked other aliens among us and I'll say that I

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Speaker 5: am one.

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Speaker 4: But or are you here from the future?

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Speaker 5: They don't believe me, okay, So I think if anyone

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Speaker 5: would know if there are aliens among us, it would

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Speaker 5: be me. And we have nine thousand satellites up there,

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Speaker 5: and not once have we had to maneuver around an

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Speaker 5: alien spaceship. So like, I don't know. The bottom line is,

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Speaker 5: I think we need to assume that life and consciousness

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Speaker 5: is extremely rare and it might only be us. And

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Speaker 5: if that's the case, then we need to do everything

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Speaker 5: possible to ensure that the light of the light of

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Speaker 5: consciousness is not extinguished because we're effectively the way I view,

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Speaker 5: it is the measure, in my mind, is of a

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Speaker 5: tiny candle in a vast darkness, tiny candle of consciousness

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Speaker 5: that could easily go out. And that's why it's important

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Speaker 5: to make life multiplanetary such that if there is a

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Speaker 5: natural disaster or a man made disaster on Earth, that

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Speaker 5: consciousness continues. That's the purpose of SpaceX Tesla is obviously

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Speaker 5: about sustainable technology and and and also at this point

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Speaker 5: we've we've sort of added to our mission sustainable abundance.

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Speaker 5: So with the robotics and AI, this this is really

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Speaker 5: the path to abundance for all. If you say, you know,

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Speaker 5: people often talk about solving global poverty or essentially how

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Speaker 5: do we make give everyone a very high standard of living?

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Speaker 5: I think the only way to do this is AI

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Speaker 5: and robotics, which which doesn't mean that it is without

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Speaker 5: its issues. I mean this, We need to be very

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Speaker 5: careful with AI, We need to be very careful with robotics.

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Speaker 5: We don't want to find ourselves in a James Camera movie. Uh,

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Speaker 5: you know, Terminator. He's great, great movies, love his movies.

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Speaker 5: But we don't want to be a Terminator. Obviously. But

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Speaker 5: if you have ubiquitous AI, that is essentially free or

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Speaker 5: close to it, and ubiquitous robotics, then you will have

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Speaker 5: an an explosion in the global economy, an expansion in

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Speaker 5: the global economy that is truly beyond all precedent.

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Speaker 3: And can that expansion be broad or is it narrow?

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Speaker 3: And how can that be created? How can it broaden

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Speaker 3: the global economy?

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Speaker 5: Yeah, it's I mean, I mean the way to think

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Speaker 5: of it is that if you have a large number

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Speaker 5: of humanoid robots, the economic output is the average productivity

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Speaker 5: per robot times the number of robots. Right, And actually,

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Speaker 5: my prediction is the in the benign scenario of the

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Speaker 5: future that we will the robots will actually make so

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Speaker 5: many robots in AI that they will actually saturate all

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Speaker 5: human needs, I meaning you won't be able to even

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Speaker 5: think of something to ask the robot for at a

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Speaker 5: certain point, like like there will be such an abundance

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Speaker 5: of goods and services because the my prediction is there'll

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Speaker 5: be there'll be more robots than people.

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Speaker 4: So but how do you then have human purpose in

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Speaker 4: that scenario?

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Speaker 5: I mean, you know, there was nothing is perfect, you know,

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Speaker 5: but I mean, I mean, is it is a necessary

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Speaker 5: Like you can't have both, You can't have work that

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Speaker 5: has to be done, uh, and amazing abundance for all

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Speaker 5: because if it's if it's work that has to be done,

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Speaker 5: then then then you and and only some people can

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Speaker 5: do it, then then you you can't have abundance narrow

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Speaker 5: narrow exactly. So but if you if you have billions

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Speaker 5: of humanoid robots, and I think it will be I

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Speaker 5: think I think everyone on Earth is going to have

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Speaker 5: one and going to want one because you're who wouldn't

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Speaker 5: want a robot to you know, assuming it's very safe,

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Speaker 5: watch over your kids, take care of your pet, if

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Speaker 5: you have elderly parents. A lot of friends of mine

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Speaker 5: have said that for elderly parents, it's it's very difficult

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Speaker 5: to take care of them. Yeah, it's expensive, and it's expensive,

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Speaker 5: and they just aren't enough people to take care of

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Speaker 5: the not enough young people to take care of the

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Speaker 5: old people. Right, So if if they if you had

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Speaker 5: a robot that could take care of and protect and

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Speaker 5: elderly parents, I think that would be great. That would

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Speaker 5: be an amazing thing to have and and I think

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Speaker 5: we will have those things. So overall, I'm very optimistic

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Speaker 5: about the future. I think we're headed for a future

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Speaker 5: of amazing abundance, which is very cool and uh and

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Speaker 5: definitely we are in the most interesting time in history.

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Speaker 5: I think there's more a more interesting time in history.

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Speaker 3: Can we can you and I reverse aging in this

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Speaker 3: new history or or are we going to see it?

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Speaker 4: You know, I haven't.

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Speaker 5: I haven't put much time into the aging stuff. I

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Speaker 5: do think it is a very solvable problem that you

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Speaker 5: can do. I think when we find figure out what

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Speaker 5: causes aging, I think we'll find it's incredibly obvious. It's

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Speaker 5: not a subtle thing. The reason I say it's not

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Speaker 5: a subtle thing is because all the cells in your body,

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Speaker 5: you know, with some pretty much age at the same rate.

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Speaker 5: I've never seen someone with with an old left arm

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Speaker 5: and a young right arm ever in my life. So

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Speaker 5: why is that? That means that there must be a

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Speaker 5: synchronizing clock that is synchronizing across thirty five trillion cells

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Speaker 5: in your body. And you know there is some benefit

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Speaker 5: to death by the way, It's like there's there's a

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Speaker 5: reason why we don't actually have a longer lifespan, because

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Speaker 5: if you have, if people do live forever for a

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Speaker 5: very long time, I think there's some risk of an

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Speaker 5: ossification of society of things just getting kind of locked

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Speaker 5: in place, and you know, it just may become stultifying,

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Speaker 5: just not lack vibrancy. But that's said, do I think

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Speaker 5: we'll figure out ways to extend life and and maybe

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Speaker 5: even reverse aging. I think that's highly likely.

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Speaker 3: I'm looking forward to that. Yeah, So in the future

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Speaker 3: that you talk about the AI models, autonomous machines rockets

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Speaker 3: depends on massive increases a compute, massive increases energy expensive energy,

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Speaker 3: manufacturing scale.

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Speaker 4: What are the mottle next to get there?

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Speaker 3: And once again, with all that expenditures, again, how can

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Speaker 3: we make sure that it's broughten not narrow.

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Speaker 5: I just think the natural thing is it's going to

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Speaker 5: be very broad because AI companies will seek as many

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Speaker 5: customers as they possibly can, and the cost of AYE

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Speaker 5: will get is already very low, and it's planeting every year,

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Speaker 5: I mean almost the cost of AI is almost changed,

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Speaker 5: meaningfully changing on a month's month basis.

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Speaker 4: There's open there's open models now everywhere.

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Speaker 5: Yes, very as open models, and the open models only

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Speaker 5: lack there maybe a year behind, right, the private the

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Speaker 5: sort of closed models. So so I think the AI

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Speaker 5: companies will seek as many customers as possible which means

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Speaker 5: they'll see they'll provide AI to the world.

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Speaker 3: But the cost of getting to there, the compute, the chips,

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Speaker 3: the fab the powering that to me, what are the

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Speaker 3: what are the you know, those are a huge limiting factor.

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Speaker 5: I think the limiting factor for AI deployment is fundamentally

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Speaker 5: electrical power.

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Speaker 4: It's just like its energy.

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Speaker 5: Yeah, yeah, I mean we're seeing the rate of AI

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Speaker 5: chip production increase exponentially, but the rate of electricity being

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Speaker 5: vote online is.

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Speaker 4: Year acts.

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Speaker 5: Yeah, it's clear that we're very soon, maybe even later

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Speaker 5: this year, we'll be producing more trips than we can

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Speaker 5: turn on. Except for China. China. China is China's growth

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Speaker 5: and electricity is tremendous.

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Speaker 4: Hundred gigawatts of nuclear as we speak.

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Speaker 5: Actually, solar is the biggest thing in China, So China is.

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Speaker 5: I believe Chinese production capacity on solar is fifteen hundred

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Speaker 5: gigawats a year, and they're deploying over a thousand gigawatts

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Speaker 5: a year of solar. Now, you know, for continuous solar load,

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Speaker 5: you divide that by roughly four or five call it.

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Speaker 5: That's around two hundred and fifty gigawats of steady state power.

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Speaker 5: Paired with batteries, and that's a very big number. That's

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Speaker 5: half of the average power usage in the US. Sous

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Speaker 5: US power usage on average is five hundred gigawats China.

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Speaker 5: Just in solar, just like just in solar, act that

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Speaker 5: can provide steady state power and batteries can do half

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Speaker 5: of the US electricity output fer year just for solar.

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Speaker 5: Solar is by far the biggest source of energy. And

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Speaker 5: actually when you look beyond or even on Earth, but

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Speaker 5: certainly beyond Earth, the Sun rounds up to one hundred

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Speaker 5: percent of all energy. This is an important thing to consider.

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Speaker 5: So the Sun is ninety nine point eight percent of

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Speaker 5: the mass of the Solar system, Jupiter is about point

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Speaker 5: one percent, and everything else is miscellaneous. Now, even if

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Speaker 5: you were to burn Jupiter in a thermino yactor, the

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Speaker 5: amount of energy produced by the Sun would still round

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Speaker 5: up to one hundred percent, because Jupiter is only point

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Speaker 5: one percent. If you teleported teleported three more jupiters into

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Speaker 5: our solar system and burnt three more Jupiters and everything

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Speaker 5: else in the Solar system, the Sun's energy we're still

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Speaker 5: round up to. So it's really all about the Sun,

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Speaker 5: and that's That's why one of the things we'll be

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Speaker 5: doing with SpaceX within a few years is launching solar

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Speaker 5: powered AI satellites because the space is really the source

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Speaker 5: of immense power, and then you don't need to take

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Speaker 5: up any room on Earth. There's so much room in space,

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Speaker 5: and you can scale to enormous I mean, you can

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Speaker 5: scale to I think ultimately hundreds hundreds of terror worts

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Speaker 5: a year.

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Speaker 3: You and I have had these conversations before it. What

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Speaker 3: did you tell the audience what would it take for

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Speaker 3: the United States? And what type of geography would it

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Speaker 3: take to have that solar field to electrify the United States?

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Speaker 3: And then let me ask a question, why aren't we

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Speaker 3: doing it?

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Speaker 5: Yeah? So, I mean, I guess the rough way to

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Speaker 5: think about it is one hundred miles by one hundred

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Speaker 5: miles or one hundred and sixty kilometers by one hundred

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Speaker 5: and sixty kilometers of solar is enough to power the

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Speaker 5: entire United States. So miles one hundred mile areas is

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Speaker 5: I mean that you could take basically a small corner

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Speaker 5: of Utah, Nevada, Nevada, New Mexico. Obviously wouldn't want it

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Speaker 5: all in one place, but it's a very small percentage

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Speaker 5: of the area of the US to generate all of

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Speaker 5: the electricity that the US uses. And the same is

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Speaker 5: true actually, I mean for Europe, you could take a

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Speaker 5: small part. You could take relatively unpopulated areas of say

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Speaker 5: Spain and Sicily and generate all of the electricity power

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Speaker 5: that your needs.

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Speaker 3: So why don't you think that there's a movement towards

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Speaker 3: that here and in the United States?

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Speaker 4: Well, there is, as it is in China.

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Speaker 5: Well, unfortunately in the US the tariff barriers for solar

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Speaker 5: are extremely high, and that makes the economics of deploying

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Speaker 5: solo artificially high because China makes almost all the solar

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Speaker 5: and and that what.

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Speaker 3: Would it take for Europe or the US to build

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Speaker 3: it commercially if it's that scale, Yeah.

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Speaker 5: I think I think. Well I can tell you what

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Speaker 5: we're going to do. You know, SpaceX and Tesla is

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Speaker 5: we're building up large scale solar. So the SpaceX and

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Speaker 5: Tesla teams, both separately are working to build to one

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Speaker 5: hundred gigo what's a year of solar power in the

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Speaker 5: US of manufactured solar power, and that'll probably take a

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Speaker 5: center in about three years. But that's that's these are

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Speaker 5: pretty big numbers, and you know, I encourage others to

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Speaker 5: do the same. We obviously don't control that. You know,

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Speaker 5: your your tariff policy. Uh, but for for for other countries, UH,

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Speaker 5: I would reckon that this China makes solo cells that

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Speaker 5: are incredibly low costs, and I think it would be

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Speaker 5: worth doing a large scale solo.

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Speaker 3: So I know you are You're going to be having

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Speaker 3: a couple of big announcements on robotics and what it

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Speaker 3: can do. I mean, when I went to the factory,

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Speaker 3: you showed me those robots. How quickly you talked about

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Speaker 3: the billions of robots, but how quickly and how quickly

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Speaker 3: can they be deployed in a manufacturing setting. How quickly

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Speaker 3: can they be utilize and be functional and be create

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Speaker 3: that that abundance that you talked about.

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Speaker 5: Well, humanoid robotics will advance very quickly. I think we

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Speaker 5: do have some the Tael's Optimus robots doing simple tasks

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Speaker 5: in the factory, except probably later this year. By the

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Speaker 5: end of this year, I think they will be doing

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Speaker 5: more more complex tasks and still deployed in an industrial environment,

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Speaker 5: and and probably sometime next year. I'd say that by

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Speaker 5: the by the end of next year, I think would

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Speaker 5: be selling humanoid robots to the public. That that's when

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Speaker 5: we are confident that it's very higher liability, very high safety,

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Speaker 5: and the range of functionality is uh is also very high.

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Speaker 5: You can basically ask it to do anything you'd like.

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Speaker 3: You're already seen that in Tesla car. Is the software

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Speaker 3: changes that you're doing and what is it? Every quarter

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Speaker 3: now a software change that upgrades the ability of the

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Speaker 3: robot within the car.

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Speaker 5: Yes, the tails a full self driving software. We update

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Speaker 5: it sometimes once a week and there recently some of

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Speaker 5: the insurance companies have said that it is actually so safe.

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Speaker 5: Where tells a full self driving so safe that uh,

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Speaker 5: they're they're offering customers half price insurance if they if

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Speaker 5: they use tess a full self driving in the car.

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Speaker 3: And that could be monitored by the insurance company, can

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Speaker 3: they Is that part of the agreement?

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Speaker 5: Yeah? But I think self driving cars is essentially a

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Speaker 5: solved problem at this point, right, and test tells us

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Speaker 5: a role out sort of robotaxi service in a few

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Speaker 5: cities and will I be very very widespread by the

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Speaker 5: end of this year within the US, and then we

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Speaker 5: hope to get supervisor for self driving approval in Europe

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Speaker 5: hopefully next.

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Speaker 4: Month really quickly.

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Speaker 5: Yeah, and then maybe a similar timing for China, hopefully.

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Speaker 3: I want to move to space because historically space is

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Speaker 3: very capital and intensive, historically been done by governments of

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Speaker 3: least space.

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Speaker 4: Exchange, the whole model.

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Speaker 3: But we've seen it slow to scale and now I'm

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Speaker 3: starting to see it ramping up.

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Speaker 4: In what you're doing and other things.

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Speaker 3: Talk to us about the reasons, you know, the automation

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Speaker 3: and AI, how it's changing the economics and building and

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Speaker 3: preparing for us in operating in space.

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Speaker 5: Sure. Well, the key brain through that tells that that's

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Speaker 5: the major breakthrough that SpaceX is hoping to achieve this

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Speaker 5: year is full reusability. So no one has ever achieved

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Speaker 5: full reusability of a rocket, which is very important for

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Speaker 5: the cost of access to space. We've achieved partial reusability

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Speaker 5: with Falcon line by landing the boost stage. We've now

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Speaker 5: landed the boost stage over five hundred times, but we

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Speaker 5: don't we have to throw away the upper stage. The

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Speaker 5: uper stage burns up on re entry for Falcon nine,

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Speaker 5: so and that the cost of that is equivalent to

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Speaker 5: a small to medium sized jet. So, but with with

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Speaker 5: Starship which is a giant rocket. It's the largest flying

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Speaker 5: machine ever made, not.

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Speaker 3: The rocket that you're using for the idea of going

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Speaker 3: to Mars, right.

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Speaker 5: Yeah, Mars and the Moon, as well as for high

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Speaker 5: volume satellite stuff. So Starship. Hopefully this year we should

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Speaker 5: prove full reusability for Starship, which will be a profound

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Speaker 5: invention because the cost of access to space will drop

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Speaker 5: by a factor of one hundred when you're chief full reusability.

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Speaker 5: It's the same sort of economic difference that you would

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Speaker 5: expect that between say a reusable aircraft and a non

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Speaker 5: reusable aircraft. Like if you have to throw aircraft away

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Speaker 5: after every flight, that would be a very expensive flight.

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Speaker 5: But if you only have to refuel, then it's the

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Speaker 5: cost of the fuel. And so that's really the fundamental

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Speaker 5: breakthrough that gets the cost of access to space we

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Speaker 5: think below the cost of a freight on aircraft, so

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Speaker 5: you know, under one hundred dollars a pound type of

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Speaker 5: thing easily. So it makes putting large satellites into into

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Speaker 5: space very low, very cheap. And then when you have

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Speaker 5: solar in space, you get five times more effectiveness, maybe

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Speaker 5: even more than that than solar on the ground because

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Speaker 5: it's always sunny cold. Yeah, it's it's it's always well,

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Speaker 5: it's toways sunny. So you don't have a day night

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Speaker 5: cycle or seasonality or weather, and you get about thirty

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Speaker 5: percent more power in space because you don't have atrospheric

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Speaker 5: attenuation of the power. The net effect is solar is

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Speaker 5: five times more. Any given solar panel will do five

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Speaker 5: times more energy in space than on the ground.

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Speaker 3: There's there any capacity in doing that and taking that

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Speaker 3: power and bringing it back to Earth.

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Speaker 4: Is there any way of doing that?

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Speaker 3: Or you're just taking that power and utilizing it for

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Speaker 3: the needs.

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Speaker 4: Like building I data centers in the space.

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Speaker 5: I think the case is it's a no brainer for

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Speaker 5: building AI solar powered AI data centers in space because

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Speaker 5: as you mentioned, it's also very cold in space. If

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Speaker 5: if you're in the shadow, it's very cold in space.

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Speaker 5: There's three degrees Calvin. So you just have your solar

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Speaker 5: panels facing the sun and then a radiator that's like

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Speaker 5: point like pointed away from the sun so it has

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Speaker 5: no sign incidents, and then it's and then it's just cooling.

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Speaker 5: It's a very efficient cooling system. So net effect is

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Speaker 5: that the lowest cost place to put AI will be

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Speaker 5: space and that'll be true within two years, maybe three

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Speaker 5: three of the latest.

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Speaker 3: So looking ten or twenty years out, well, how would

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Speaker 3: you describe success with AI or space technology?

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Speaker 4: And where do you see it is that? Can you?

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Speaker 3: Are you more certain what's going to happen to the

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Speaker 3: next three years or five or ten.

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Speaker 5: I don't know what's going to happen in ten years,

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Speaker 5: but the rate at which AI is progressing, I think

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Speaker 5: we might have AI that is smater than any human

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Speaker 5: by the end of this year. And I'd say no

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Speaker 5: later the next year well, and then probably by twenty

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Speaker 5: thirty or twenty thirty one could five years from now,

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Speaker 5: AI will be smarter than all of humanity collectively.

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Speaker 3: We only have a number of minutes left. But I

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Speaker 3: want to humanize you for a second, so there's no

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Speaker 3: speculation like you're right, pie right, I want to I mean,

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Speaker 3: I would frame this question by you are the most

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Speaker 3: successful entrepreneur industrialists in the twenty first century, maybe beyond.

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Speaker 3: So I want to really get this. You know what

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Speaker 3: inspired you? Who's inspired you? What was a foundation of

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Speaker 3: your curiosity? And and importantly.

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Speaker 4: What was the book? What was it?

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Speaker 3: Was there an aha moment epiphany at any time in

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Speaker 3: your life and career.

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Speaker 5: Well, I mean as a kid, I read a lot

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Speaker 5: of science fiction, sci fi, fantasy books we talked about

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Speaker 5: and uh, comic books.

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Speaker 6: Uh.

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Speaker 5: And I always like technology.

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Speaker 7: Uh.

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Speaker 5: I didn't expect to be where I am today. Seems

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Speaker 5: incredibly implausible, but yeah I was. I was inspired by

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Speaker 5: reading about books about the future, about science fiction and

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Speaker 5: uh and I guess I want to make science fiction

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Speaker 5: not fiction forever. At some point turned science fiction to

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Speaker 5: science fact. And uh, you know, we want to have

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Speaker 5: like Starfleet and star Trek really for for real, like

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Speaker 5: where we actually have giants, spaceships traveling through space, going

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Speaker 5: to other planets, traveling to other star.

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Speaker 3: Systems, beamed up to go back to New York. You know,

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Speaker 3: I'd like to just be beamed back to New York

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Speaker 3: instead of flying.

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Speaker 5: Yeah, star Trek. I guess my my essential what I

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Speaker 5: would call the philosophical philussy of curiosity. I'd like to

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Speaker 5: understand the meaning of life. You know, the is the

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Speaker 5: standard model, is the standard model of physics correct regarding

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Speaker 5: the beginning of life, beginning of existence, and the end

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Speaker 5: of the year verse. What what questions do we not

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Speaker 5: know to ask that we should ask and a I

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Speaker 5: will help us with these things. So I'm just trying

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Speaker 5: to say, how do we get here, what's going on?

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Speaker 5: What's real? Are there aliens? Maybe they are? And if

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Speaker 5: we've got if we've got spaceships that are traveling to

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Speaker 5: other star systems, we may find we may encounter aliens

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Speaker 5: and or may find many long dead alien civilizations. But

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Speaker 5: I'm just, I just I just want to know what's

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Speaker 5: going on. I'm curious about the universe, and that's my philosophy.

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Speaker 3: You see yourself ever going to Mars in your lifetime?

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Speaker 5: Yeah, I mean I would say, like, you know, that's

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Speaker 5: a long commitment.

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Speaker 4: I've been asked, wasn't that three years? Each way?

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Speaker 5: It's six months?

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Speaker 4: Six months? That's all it is.

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Speaker 5: Yeah, six months. But the planets only aligned every two years,

440
00:29:33,640 --> 00:29:37,280
Speaker 5: so uh yeah. I've been asked a few times like

441
00:29:38,160 --> 00:29:40,640
Speaker 5: do I want to, you know, die on Moss And

442
00:29:40,680 --> 00:29:43,360
Speaker 5: I'm like, yes, but just not on impact.

443
00:29:48,440 --> 00:29:51,000
Speaker 3: That's a that's a good answer. Anyway, we're out of time.

444
00:29:51,200 --> 00:29:55,920
Speaker 3: I hopefully everybody enjoyed this. I mean, there's so many

445
00:29:55,960 --> 00:29:59,120
Speaker 3: myths around Elon Muss. I can tell you he's a

446
00:29:59,160 --> 00:30:04,600
Speaker 3: great friend and I constantly learned so much from him,

447
00:30:05,040 --> 00:30:08,920
Speaker 3: and I'm totally inspired by what he's what he has done,

448
00:30:10,880 --> 00:30:14,360
Speaker 3: and then it's been inspired who he is. And I'm

449
00:30:14,400 --> 00:30:17,840
Speaker 3: totally inspired by his vision of the future, and I

450
00:30:17,840 --> 00:30:20,360
Speaker 3: don't think it's such a bad future, and I agree

451
00:30:20,400 --> 00:30:21,280
Speaker 3: with his optimism.

452
00:30:21,360 --> 00:30:22,320
Speaker 4: So Elon, thank you.

453
00:30:22,440 --> 00:30:28,880
Speaker 5: Any last words, Well, I think generally, I think my

454
00:30:28,960 --> 00:30:31,479
Speaker 5: last words would be I would encourage everyone to be

455
00:30:31,880 --> 00:30:36,720
Speaker 5: optimistic and excited about the future good and and generally,

456
00:30:36,800 --> 00:30:40,040
Speaker 5: I think for quality of life, it is actually better

457
00:30:40,080 --> 00:30:43,080
Speaker 5: to err on the side of being an optimist and

458
00:30:43,360 --> 00:30:44,840
Speaker 5: wrong rather than a pessimist.

459
00:30:44,840 --> 00:30:45,320
Speaker 4: And right.

460
00:30:47,080 --> 00:30:56,160
Speaker 8: On that note, this is Bloomberg Tech, and that was

461
00:30:56,360 --> 00:31:00,800
Speaker 8: Elon Musk, the world's richest man, CEO of Tesla's SpaceX,

462
00:31:00,800 --> 00:31:03,480
Speaker 8: alongside black Rock CEO Larry Think They're in.

463
00:31:03,480 --> 00:31:04,960
Speaker 9: Davos and Caroline.

464
00:31:05,240 --> 00:31:08,240
Speaker 8: A lot of this is Elon Musk's talking book Things

465
00:31:08,240 --> 00:31:10,400
Speaker 8: We've heard Before, and I was trying to discern, like

466
00:31:10,600 --> 00:31:13,120
Speaker 8: what's new and what's news. We sent the headline on

467
00:31:13,160 --> 00:31:16,520
Speaker 8: the Bloomberg terminal that Tesla could be selling optimists to

468
00:31:16,560 --> 00:31:19,640
Speaker 8: the public their humanoid robot at the end of next year.

469
00:31:19,880 --> 00:31:22,920
Speaker 8: That seemed to move the shares for Tesla. What else

470
00:31:22,920 --> 00:31:23,960
Speaker 8: caught your ear because there.

471
00:31:23,840 --> 00:31:26,120
Speaker 1: Was a lot Yeah, and I think the idea of

472
00:31:26,440 --> 00:31:31,080
Speaker 1: how much more improved optimists will be, how sophisticated it

473
00:31:31,120 --> 00:31:32,040
Speaker 1: will become, and how.

474
00:31:31,920 --> 00:31:33,880
Speaker 10: Many billions will be out there in the world.

475
00:31:34,080 --> 00:31:36,120
Speaker 1: But more broadly, he also talked about where he is

476
00:31:36,160 --> 00:31:38,680
Speaker 1: in terms of Starship, where he aims in terms of space,

477
00:31:39,000 --> 00:31:41,120
Speaker 1: and the idea that they want to be improving full

478
00:31:41,160 --> 00:31:42,640
Speaker 1: the usability.

479
00:31:42,040 --> 00:31:43,520
Speaker 10: For Starship this year.

480
00:31:43,880 --> 00:31:46,800
Speaker 1: And of course then the favorite talk of most CEOs

481
00:31:46,840 --> 00:31:48,440
Speaker 1: at the moment, if you're in the world of AI,

482
00:31:48,640 --> 00:31:51,320
Speaker 1: is putting AI data centers in space and what that

483
00:31:51,360 --> 00:31:53,320
Speaker 1: means and centers a solar energy There was a lot

484
00:31:53,400 --> 00:31:55,200
Speaker 1: talked about in terms of energy.

485
00:31:55,240 --> 00:31:57,240
Speaker 10: Did that take your interest.

486
00:31:57,000 --> 00:31:59,200
Speaker 1: Because really that seems to be the bottleneck of choice

487
00:31:59,200 --> 00:31:59,720
Speaker 1: at the moment.

488
00:32:00,400 --> 00:32:04,160
Speaker 8: Yeah, you know, TESLA has an energy division, right, and

489
00:32:04,200 --> 00:32:06,760
Speaker 8: so it was obvious that he would kind of talk

490
00:32:06,800 --> 00:32:09,520
Speaker 8: that part up. But this is something in the consciousness

491
00:32:09,560 --> 00:32:13,400
Speaker 8: of the administration. The rest of supply chain. China dominates

492
00:32:13,400 --> 00:32:17,680
Speaker 8: supply of solar energy and whatever SpaceX's long term ambitions

493
00:32:17,680 --> 00:32:21,360
Speaker 8: are for data centers in space. Clearly Larry Think tried

494
00:32:21,360 --> 00:32:23,200
Speaker 8: to get Elon Musk to say, Hey, the US and

495
00:32:23,240 --> 00:32:25,960
Speaker 8: Europe should be doing more. Must didn't really bite, but

496
00:32:26,040 --> 00:32:27,640
Speaker 8: he did go as far to say, well, look, this

497
00:32:27,720 --> 00:32:30,360
Speaker 8: is what Tesla and SpaceX are doing over the next

498
00:32:30,640 --> 00:32:34,520
Speaker 8: two to three years. No brainer to have solar powered

499
00:32:34,880 --> 00:32:37,520
Speaker 8: compute and space, but also ramp up the output of

500
00:32:37,560 --> 00:32:39,640
Speaker 8: cells because if you don't sell them into markets like

501
00:32:39,680 --> 00:32:40,800
Speaker 8: Europe China does.

502
00:32:41,600 --> 00:32:45,720
Speaker 1: Precisely, also talking about how cheaper AI could become. We're

503
00:32:45,720 --> 00:32:47,640
Speaker 1: all thinking about the cost of compute, the cost of

504
00:32:47,720 --> 00:32:50,280
Speaker 1: energy if you put those AI data centers in the

505
00:32:50,280 --> 00:32:52,800
Speaker 1: next two to three years. He's saying more broadly, space

506
00:32:52,880 --> 00:32:55,000
Speaker 1: is the cheapest place to put AI in due to

507
00:32:55,040 --> 00:32:57,000
Speaker 1: three years. It's interesting the FT's just been sending a

508
00:32:57,000 --> 00:32:59,040
Speaker 1: headline talking about in your Must, SpaceX lining up four

509
00:32:59,080 --> 00:32:59,800
Speaker 1: banks from IPO.

510
00:32:59,880 --> 00:33:01,960
Speaker 10: So we're all in on the space story right now.

511
00:33:03,400 --> 00:33:05,320
Speaker 8: And he was asked what inspires you, and he said,

512
00:33:05,320 --> 00:33:07,520
Speaker 8: when he was a kid, he read science fiction books.

513
00:33:07,520 --> 00:33:09,400
Speaker 8: So if you're a kid out there watching and you

514
00:33:09,440 --> 00:33:11,360
Speaker 8: want to be the next Zelond Musk, that's what you've

515
00:33:11,360 --> 00:33:14,080
Speaker 8: got to do. We're also tracking and looking at live

516
00:33:14,120 --> 00:33:17,960
Speaker 8: images of Blue Origin's New Shepherd n S thirty eight

517
00:33:18,040 --> 00:33:21,200
Speaker 8: latest mission. We're on a hold right now. The window

518
00:33:21,240 --> 00:33:24,520
Speaker 8: had been due to open eleven am Eastern time, eight

519
00:33:24,560 --> 00:33:27,640
Speaker 8: am here on the West coast for NS thirty eight.

520
00:33:28,120 --> 00:33:30,520
Speaker 8: By this point, ninety people have gone up on Blue Origin,

521
00:33:30,560 --> 00:33:32,800
Speaker 8: but they're on a hold, a technical hold. We'll keep

522
00:33:32,840 --> 00:33:35,320
Speaker 8: tracking it, but you can watch the launch on live

523
00:33:35,400 --> 00:33:37,760
Speaker 8: go on the Bloomberg terminal carry. There is a lot

524
00:33:37,800 --> 00:33:40,080
Speaker 8: going on in financial markets too, there are.

525
00:33:40,120 --> 00:33:42,720
Speaker 1: And more broadly, we're seeing a bit more optimism come

526
00:33:42,760 --> 00:33:45,920
Speaker 1: to life in the markets. Look the geopolitical angst put

527
00:33:45,960 --> 00:33:49,320
Speaker 1: to one side and the optimism returning about all things AI.

528
00:33:49,440 --> 00:33:51,800
Speaker 1: At one point, we're thinking the narrative is all around

529
00:33:51,960 --> 00:33:54,720
Speaker 1: in video and Jensen Wang being bullish once again on

530
00:33:54,760 --> 00:33:56,800
Speaker 1: the trillion dollars of spending that's going to be going

531
00:33:56,800 --> 00:33:59,760
Speaker 1: into the idea of AI data centers, the need for

532
00:34:00,400 --> 00:34:02,400
Speaker 1: But we've also got earnings on deck later today. This

533
00:34:02,480 --> 00:34:03,960
Speaker 1: is something you're going to be digging into. At the moment,

534
00:34:04,040 --> 00:34:05,920
Speaker 1: lawstacks up six tens percent. But look, we're in the

535
00:34:05,920 --> 00:34:08,440
Speaker 1: green across the board when you're looking at every benchmark

536
00:34:08,480 --> 00:34:09,399
Speaker 1: across the entire world.

537
00:34:09,440 --> 00:34:12,760
Speaker 8: Head I'm taking a look at Intel because Intel posts

538
00:34:12,840 --> 00:34:15,719
Speaker 8: after market and even though the chip maker is still

539
00:34:15,719 --> 00:34:18,640
Speaker 8: in battled. The stock has been on a hell of

540
00:34:18,680 --> 00:34:21,640
Speaker 8: a run of late, you know, on the week up

541
00:34:21,719 --> 00:34:25,120
Speaker 8: almost fifteen percent, on track for its best week I

542
00:34:25,160 --> 00:34:28,359
Speaker 8: think in quite a long time. But right now we're

543
00:34:28,360 --> 00:34:31,120
Speaker 8: treading water. Of course we are, why because we'll wait

544
00:34:31,160 --> 00:34:32,960
Speaker 8: and see actually the meat of what comes out of

545
00:34:33,000 --> 00:34:35,560
Speaker 8: that earnings print again, which is after the market close

546
00:34:36,040 --> 00:34:38,799
Speaker 8: around four pm Eastern time. Carry there are many news

547
00:34:38,800 --> 00:34:39,680
Speaker 8: stories as well.

548
00:34:40,040 --> 00:34:42,319
Speaker 1: There are in the private markets too. And guess what

549
00:34:42,800 --> 00:34:45,319
Speaker 1: open ayes fundraising. We knew that, but the CEO of

550
00:34:45,320 --> 00:34:48,439
Speaker 1: sam Altman has been really busy traveling in the Middle East.

551
00:34:48,680 --> 00:34:51,080
Speaker 1: He's been meeting with top investors in an effort really

552
00:34:51,120 --> 00:34:53,520
Speaker 1: to secure funding from an investment round that could total

553
00:34:53,560 --> 00:34:57,239
Speaker 1: get this fifty billion dollars, it's according to sources in

554
00:34:57,440 --> 00:35:00,239
Speaker 1: meerg suring KAfari joining us to cover the story. I mean,

555
00:35:00,360 --> 00:35:03,040
Speaker 1: the valuations are gargantuan. We're thinking up to eight hundred

556
00:35:03,040 --> 00:35:05,080
Speaker 1: and thirty billion dollars as where it could be. But

557
00:35:05,200 --> 00:35:07,919
Speaker 1: the focus on the Middle East perhaps unsurprising for these

558
00:35:08,120 --> 00:35:09,640
Speaker 1: foundation AI labs.

559
00:35:12,120 --> 00:35:14,120
Speaker 11: That's right, when you think about the pools of capital

560
00:35:14,160 --> 00:35:18,400
Speaker 11: that are required for these kinds of mega fundraising rounds.

561
00:35:18,680 --> 00:35:22,160
Speaker 11: You're tapping beyond the usual network of Silicon Valley vcs

562
00:35:22,680 --> 00:35:25,120
Speaker 11: or even New York finance firms, right, and so that's

563
00:35:25,160 --> 00:35:27,920
Speaker 11: why you see CEOs like zam Altment traveling to places

564
00:35:27,920 --> 00:35:29,960
Speaker 11: like Abu Dhabi to court investors.

565
00:35:31,719 --> 00:35:34,279
Speaker 8: Sharen, you know, we have tried to track this as

566
00:35:34,320 --> 00:35:37,400
Speaker 8: closely as possible. I think one of the things reading

567
00:35:37,440 --> 00:35:40,319
Speaker 8: the report is the detail of what we know about

568
00:35:40,320 --> 00:35:44,000
Speaker 8: how Sam Altman operates, the travel, who he meets with,

569
00:35:44,120 --> 00:35:48,319
Speaker 8: the specific names behind the sovereign wealth funds, and the jurisdictions.

570
00:35:48,320 --> 00:35:49,640
Speaker 9: He's going to give us.

571
00:35:49,560 --> 00:35:51,680
Speaker 8: All the detail you can give us a good insight

572
00:35:51,719 --> 00:35:52,839
Speaker 8: in what he's trying to pull off.

573
00:35:55,320 --> 00:35:56,719
Speaker 11: I mean, if you think about it, this is a

574
00:35:56,760 --> 00:35:59,160
Speaker 11: time when there is great interest in the Middle East

575
00:35:59,160 --> 00:36:02,040
Speaker 11: and other regions tapping into the AI boom. There are

576
00:36:02,080 --> 00:36:05,759
Speaker 11: also other companies fundraising. We know Anthropic is also you know,

577
00:36:06,120 --> 00:36:10,120
Speaker 11: set to finalize around very soon as we've reported, you know,

578
00:36:11,000 --> 00:36:13,919
Speaker 11: SpaceX maybe going IPO, but in the past they've also

579
00:36:14,000 --> 00:36:17,960
Speaker 11: been fundraising. So we have you know, a limited even

580
00:36:18,000 --> 00:36:19,960
Speaker 11: when you get to these larger pools of capital that

581
00:36:20,040 --> 00:36:23,760
Speaker 11: extend beyond the US's ability in terms of ec firms.

582
00:36:23,760 --> 00:36:26,120
Speaker 11: You're still a limit to how much these sovereign wealth

583
00:36:26,120 --> 00:36:29,799
Speaker 11: funds can give. So it requires travel, requires relationships, right,

584
00:36:29,840 --> 00:36:32,720
Speaker 11: It requires going out and actually meeting people, shaking hands

585
00:36:32,719 --> 00:36:33,960
Speaker 11: and hopefully securing a deal.

586
00:36:35,120 --> 00:36:37,840
Speaker 8: This is a big deal what we're hearing right, just

587
00:36:37,840 --> 00:36:40,880
Speaker 8: to recap fifty billion dollar target raise, seven hundred and

588
00:36:40,920 --> 00:36:43,400
Speaker 8: fifty billion to eight hundred and thirty billion dollar valuation.

589
00:36:43,960 --> 00:36:46,239
Speaker 8: A lot of eyes on it, Bloomberg Sheren Gafari leaving

590
00:36:46,280 --> 00:36:48,759
Speaker 8: the team that's been reporting and tracking it.

591
00:36:49,040 --> 00:36:49,360
Speaker 10: Apple.

592
00:36:49,560 --> 00:36:52,280
Speaker 1: It's set to Revampsari later this year, turning the digital

593
00:36:52,280 --> 00:36:55,920
Speaker 1: assistant into the company's first AI chatbot the future is

594
00:36:55,920 --> 00:36:58,400
Speaker 1: set to be integrated into Apple's lineup of iPhones, iPads,

595
00:36:58,440 --> 00:37:02,200
Speaker 1: mac operating systems. Consumer tech editor Mark gum And broke

596
00:37:02,280 --> 00:37:05,520
Speaker 1: the details. You join us now, Mark, It's interesting how

597
00:37:05,560 --> 00:37:08,600
Speaker 1: much they're depending on Google technology potentially on their servers

598
00:37:08,640 --> 00:37:09,160
Speaker 1: as well.

599
00:37:09,480 --> 00:37:10,960
Speaker 10: But this is quite a move to be going to

600
00:37:11,000 --> 00:37:11,960
Speaker 10: the chatbot form.

601
00:37:12,239 --> 00:37:14,640
Speaker 12: This is a blockbuster move for Apple for the last

602
00:37:14,719 --> 00:37:17,600
Speaker 12: several months, even in light of the new sery being

603
00:37:17,640 --> 00:37:19,759
Speaker 12: delayed and not launching on time a year and a

604
00:37:19,760 --> 00:37:22,440
Speaker 12: half ago, Even in light of the box launch and

605
00:37:22,440 --> 00:37:25,920
Speaker 12: the delayed Apple Intelligence. Apple was steadfast and saying that

606
00:37:26,040 --> 00:37:29,480
Speaker 12: it doesn't believe in the chatbot route that OpenAI is taking,

607
00:37:29,480 --> 00:37:33,000
Speaker 12: the chat GPT that Google's taking with Gemini, that Microsoft

608
00:37:33,040 --> 00:37:36,320
Speaker 12: is taken with Copilot. But everyone who's used these chatbots

609
00:37:36,320 --> 00:37:38,400
Speaker 12: to know that this is at the very center of

610
00:37:38,440 --> 00:37:42,360
Speaker 12: the generative AI battleground. Chat GPT is nearing a billion

611
00:37:43,120 --> 00:37:46,800
Speaker 12: monthly active users right It's clearly resonating, and so Apple

612
00:37:46,840 --> 00:37:49,200
Speaker 12: knows it needs to go in this direction, and it's

613
00:37:49,200 --> 00:37:51,880
Speaker 12: doing exactly what it needs to do to make its

614
00:37:51,920 --> 00:37:55,120
Speaker 12: consumers happy and to keep selling its devices and keeping

615
00:37:55,160 --> 00:37:58,640
Speaker 12: its operating system in line with the future. So at

616
00:37:58,680 --> 00:38:01,440
Speaker 12: the end of this year, they're going to Vampserie into

617
00:38:01,480 --> 00:38:03,960
Speaker 12: a chatbot, and it's going to be far more capable

618
00:38:04,000 --> 00:38:07,239
Speaker 12: than what you're seeing from chatbots today, having those features,

619
00:38:07,360 --> 00:38:11,000
Speaker 12: having web search, but also having deep ties into Apple's

620
00:38:11,040 --> 00:38:14,120
Speaker 12: devices allowing you to control specific apps and features.

621
00:38:14,239 --> 00:38:16,440
Speaker 8: It's interesting to see the shares up about nine tens

622
00:38:16,520 --> 00:38:19,360
Speaker 8: percent after the reporting, and when I read the report,

623
00:38:19,800 --> 00:38:23,279
Speaker 8: it's clear Siri will be fundamentally different. But is this

624
00:38:23,360 --> 00:38:26,880
Speaker 8: a direct result mark of that agreement that Apple reached

625
00:38:26,960 --> 00:38:31,080
Speaker 8: with Google for Gemini to underpin this next gen of series.

626
00:38:31,120 --> 00:38:32,600
Speaker 9: That kind of what the unlock has been.

627
00:38:32,840 --> 00:38:34,560
Speaker 12: That has been the unlock for them to bring this

628
00:38:34,640 --> 00:38:37,080
Speaker 12: to market. This is a concept that they've had for

629
00:38:37,120 --> 00:38:40,760
Speaker 12: a while now, using their internal models that they've built

630
00:38:40,800 --> 00:38:43,719
Speaker 12: for Syrian Apple Intelligence a couple of years ago. But

631
00:38:43,960 --> 00:38:45,960
Speaker 12: based on all the delays and based on all the

632
00:38:46,000 --> 00:38:48,920
Speaker 12: issues the companies had, it would have been impossible to

633
00:38:49,000 --> 00:38:52,200
Speaker 12: launch that with their internal models because it just wouldn't

634
00:38:52,200 --> 00:38:54,520
Speaker 12: work well, it would be subpar, and they would have

635
00:38:54,600 --> 00:38:55,760
Speaker 12: crisis round two.

636
00:38:55,600 --> 00:38:56,759
Speaker 5: For their AI strategy.

637
00:38:57,000 --> 00:38:59,560
Speaker 12: So yes, as you said, partnering with Google for Gemini

638
00:38:59,800 --> 00:39:02,799
Speaker 12: has been the unlock to actually bring this to market. Now,

639
00:39:03,040 --> 00:39:05,719
Speaker 12: there are some important details here. There is a new

640
00:39:05,800 --> 00:39:08,440
Speaker 12: version of Serie launching in the coming months in the

641
00:39:08,440 --> 00:39:10,800
Speaker 12: first half of this year, likely around March of April,

642
00:39:11,160 --> 00:39:13,640
Speaker 12: that brings to market features they announced two years ago

643
00:39:13,680 --> 00:39:16,680
Speaker 12: in twenty twenty four at their Developer conference, the assistant

644
00:39:16,680 --> 00:39:19,040
Speaker 12: being able to tap into personal data, being able to

645
00:39:19,040 --> 00:39:22,120
Speaker 12: know what's on your screen, precise control of applications in

646
00:39:22,160 --> 00:39:24,880
Speaker 12: the operating system, and to do that, they're using a

647
00:39:24,920 --> 00:39:29,120
Speaker 12: custom Gemini model that mixes with their internal models, runs

648
00:39:29,120 --> 00:39:30,560
Speaker 12: in the cloud on Apple servers.

649
00:39:30,840 --> 00:39:33,000
Speaker 5: But this chatbot is so powerful.

650
00:39:32,560 --> 00:39:35,120
Speaker 12: And needs to have as much functionality as possible to

651
00:39:35,160 --> 00:39:38,680
Speaker 12: really compete with open ai and what Google Microsoft offered today.

652
00:39:39,000 --> 00:39:39,800
Speaker 4: So what they're.

653
00:39:39,600 --> 00:39:43,920
Speaker 12: Discussing doing is actually running this Gemini model on Google's

654
00:39:43,960 --> 00:39:48,520
Speaker 12: cloud platform services as well as on Google TPUs, which

655
00:39:48,560 --> 00:39:50,799
Speaker 12: is a big sea change for what Apple is doing

656
00:39:50,840 --> 00:39:51,720
Speaker 12: currently with Gemini.

657
00:39:51,960 --> 00:39:55,200
Speaker 8: Yeah, we've talked about the TPU unlock as well. Bluemos

658
00:39:55,280 --> 00:39:58,279
Speaker 8: Mark Gunman backstrong with a big scoop, Thank you very much.

659
00:39:58,480 --> 00:40:01,680
Speaker 8: Let's tend to chips that power ai. Ali Baba is

660
00:40:01,800 --> 00:40:07,040
Speaker 8: preparing to ipo it's chip making tahead. Bloomberg's executive editor

661
00:40:07,120 --> 00:40:09,960
Speaker 8: for Tech leading the Asia, Tmpter Elstrom joins us, Now,

662
00:40:10,320 --> 00:40:12,880
Speaker 8: this is interesting. It's kind of a TUFA. We know

663
00:40:13,160 --> 00:40:16,520
Speaker 8: from our reporting they're planning to ipo this unit, but

664
00:40:16,600 --> 00:40:18,879
Speaker 8: in the interim they're also going to restructure it.

665
00:40:19,080 --> 00:40:19,799
Speaker 9: What do we need to know?

666
00:40:21,400 --> 00:40:22,040
Speaker 4: Yeah, that's right.

667
00:40:22,080 --> 00:40:25,000
Speaker 13: It's a two step process that Ali Baba is looking

668
00:40:25,040 --> 00:40:28,200
Speaker 13: at here. They're going to begin by restructuring the ownership

669
00:40:28,280 --> 00:40:30,920
Speaker 13: of the company, allowing employees to own some of the

670
00:40:30,960 --> 00:40:33,200
Speaker 13: shares here, and then later on they plan on taking

671
00:40:33,239 --> 00:40:36,000
Speaker 13: it public. Now, This is an interesting move by Ali Baba.

672
00:40:36,000 --> 00:40:38,719
Speaker 13: Ali Baba, course is an e commerce company at its core,

673
00:40:39,080 --> 00:40:42,640
Speaker 13: it's been diversifying into a number of different areas, including AI.

674
00:40:42,760 --> 00:40:45,760
Speaker 13: They have one of the leading AI models in China

675
00:40:45,840 --> 00:40:48,440
Speaker 13: with its Gwen platform, and they've been working on this

676
00:40:48,560 --> 00:40:51,080
Speaker 13: chip effort too. It's a bit like Amazon's push into

677
00:40:51,160 --> 00:40:55,080
Speaker 13: being able to develop their own AI chips and Google's

678
00:40:55,120 --> 00:40:58,200
Speaker 13: you talked about the TPUs. It's an interesting strategic move

679
00:40:58,200 --> 00:41:00,560
Speaker 13: by Ali Baba because they're deciding that they do want

680
00:41:00,560 --> 00:41:02,960
Speaker 13: to go ahead and spin off that chip unit. See

681
00:41:02,960 --> 00:41:05,200
Speaker 13: if they can give it some independence, give it some

682
00:41:05,480 --> 00:41:07,520
Speaker 13: give some ownership to the employees so that they have

683
00:41:07,560 --> 00:41:09,880
Speaker 13: a motivation to be able to competitive. But then they

684
00:41:09,880 --> 00:41:11,960
Speaker 13: have a very big market to address here, and they

685
00:41:11,960 --> 00:41:14,640
Speaker 13: have some very significant competitors in China and of course

686
00:41:14,680 --> 00:41:15,440
Speaker 13: beyond shan It too.

687
00:41:15,640 --> 00:41:19,040
Speaker 1: More threats technologies just listed camera con technologies briefly.

688
00:41:19,080 --> 00:41:19,279
Speaker 10: Peter.

689
00:41:19,400 --> 00:41:21,279
Speaker 1: The context of the support from China on.

690
00:41:21,239 --> 00:41:25,600
Speaker 13: This, well, this is a national policy, as we've talked

691
00:41:25,600 --> 00:41:27,959
Speaker 13: about a number of times before the US is cut

692
00:41:28,000 --> 00:41:31,360
Speaker 13: off in Vidia from selling its most advanced chips into China.

693
00:41:31,640 --> 00:41:33,920
Speaker 13: In Beijing, that's seen as a very serious threat. They

694
00:41:33,960 --> 00:41:36,640
Speaker 13: want to have some domestic alternatives to that. So they

695
00:41:36,680 --> 00:41:38,880
Speaker 13: have a number of domestic players that are coming on

696
00:41:38,920 --> 00:41:42,080
Speaker 13: strong wilways leading the way. Camera Con is probably second.

697
00:41:42,080 --> 00:41:44,200
Speaker 13: Camera Con is unknown in the West, really, but it's

698
00:41:44,280 --> 00:41:46,759
Speaker 13: eighty billion dollar company. They're doing quite well. And so

699
00:41:46,840 --> 00:41:49,440
Speaker 13: companies like Ali Baba and more Threads and some of

700
00:41:49,440 --> 00:41:52,400
Speaker 13: the other small players see a golden opportunity here. If

701
00:41:52,440 --> 00:41:55,319
Speaker 13: they can develop the technology for these AI chips, they're

702
00:41:55,320 --> 00:41:57,480
Speaker 13: going to have a very vibrant domestic market.

703
00:41:58,000 --> 00:42:00,840
Speaker 1: I do also looking at doing something similar Peter Elstrom

704
00:42:01,080 --> 00:42:01,720
Speaker 1: great breakdown.

705
00:42:01,760 --> 00:42:02,239
Speaker 10: We thank you.

706
00:42:04,719 --> 00:42:07,480
Speaker 8: The idea that China is behind in AI is a

707
00:42:07,520 --> 00:42:10,520
Speaker 8: fairy tale. Those are the words from Alfa Mench, CEO

708
00:42:10,880 --> 00:42:14,600
Speaker 8: of Miestrow, AI, Europe's only large language model player. He

709
00:42:14,719 --> 00:42:18,480
Speaker 8: spoke with Bloomberg's Gumana Bassecci in Davos, and he also

710
00:42:18,480 --> 00:42:21,680
Speaker 8: weighed in on whether European companies stand to benefit from

711
00:42:21,840 --> 00:42:26,120
Speaker 8: enterprises looking to move away from US providers for geopolitical

712
00:42:26,160 --> 00:42:27,120
Speaker 8: really reasons.

713
00:42:27,160 --> 00:42:27,640
Speaker 9: Listen to this.

714
00:42:30,400 --> 00:42:33,400
Speaker 14: It certainly is a growing topic top of mine in

715
00:42:33,480 --> 00:42:38,080
Speaker 14: the CEO's mind of enterprises that their dependency to single

716
00:42:38,120 --> 00:42:40,960
Speaker 14: providers when it comes to digital services might become a

717
00:42:41,000 --> 00:42:44,360
Speaker 14: problem and is not a great answer to the verlatility

718
00:42:44,440 --> 00:42:46,960
Speaker 14: that we observed in the world. So it's true in Europe,

719
00:42:46,960 --> 00:42:49,120
Speaker 14: but it's also true outside of Europe. It's true in

720
00:42:49,160 --> 00:42:53,520
Speaker 14: the US with Southern accounts, it's true in Canada, it's

721
00:42:53,560 --> 00:42:56,480
Speaker 14: through in the Southeast Asian region where we will create

722
00:42:56,520 --> 00:42:58,879
Speaker 14: a lot as well. So we do see that the

723
00:42:58,880 --> 00:43:01,400
Speaker 14: technology we've built in the differentiation of it, which is

724
00:43:01,880 --> 00:43:04,680
Speaker 14: that you can customize and deploy wherever you want, is

725
00:43:04,719 --> 00:43:08,000
Speaker 14: something that does resonate with the geopolitical events.

726
00:43:08,080 --> 00:43:08,319
Speaker 9: Yeah.

727
00:43:08,400 --> 00:43:11,920
Speaker 7: Well, staying with the geopolitics, one of my colleagues spoke

728
00:43:12,000 --> 00:43:16,360
Speaker 7: to the Anthropics CEO earlier this week and on China.

729
00:43:16,960 --> 00:43:20,319
Speaker 7: He thought that the idea of sending advanced chips there,

730
00:43:20,360 --> 00:43:22,600
Speaker 7: and this is a quote, is crazy and said it's

731
00:43:22,600 --> 00:43:25,040
Speaker 7: a bit like selling nuclear weapons in North Korea.

732
00:43:25,920 --> 00:43:28,759
Speaker 9: What's your view, Well, I.

733
00:43:28,719 --> 00:43:31,200
Speaker 4: Think the I don't think this is true.

734
00:43:31,880 --> 00:43:37,640
Speaker 14: It turns out that China does very well without Nvidia chips.

735
00:43:37,239 --> 00:43:41,239
Speaker 14: We've seen China rise on the open source count and

736
00:43:41,280 --> 00:43:45,920
Speaker 14: we have been at misstyle. Basically the spearhead of open

737
00:43:45,920 --> 00:43:47,560
Speaker 14: source in the West outside.

738
00:43:47,200 --> 00:43:50,080
Speaker 10: Of China is China behind the West.

739
00:43:50,320 --> 00:43:51,840
Speaker 14: China is not behind the West. I think this is

740
00:43:51,880 --> 00:43:54,680
Speaker 14: a this is a itail in the I. They are

741
00:43:54,920 --> 00:43:59,040
Speaker 14: very much at piety and the year ahead is going

742
00:43:59,040 --> 00:44:04,120
Speaker 14: to be extremely interesting. Respect we care about Europe maintaining

743
00:44:04,160 --> 00:44:08,280
Speaker 14: its position, Europe maintaining its ability to train models because

744
00:44:08,280 --> 00:44:11,880
Speaker 14: we don't think that we should rely on open source

745
00:44:12,080 --> 00:44:15,480
Speaker 14: Chinese models in very critical applications. So we need to

746
00:44:15,520 --> 00:44:18,600
Speaker 14: be able to create our own models and to sell

747
00:44:18,640 --> 00:44:21,400
Speaker 14: them to enterprises. So it's going to be very interesting.

748
00:44:21,400 --> 00:44:23,440
Speaker 14: But it's a fairy tale that China is behind.

749
00:44:24,080 --> 00:44:25,759
Speaker 10: Let's talk about your own business. Do you have a

750
00:44:25,800 --> 00:44:26,919
Speaker 10: revenue goal for this year?

751
00:44:27,360 --> 00:44:27,960
Speaker 5: Yeah, we do.

752
00:44:28,360 --> 00:44:30,200
Speaker 14: We should cross a billion by the end of the year.

753
00:44:30,280 --> 00:44:32,759
Speaker 7: Okay, And in terms of CAPEX spending, what are you

754
00:44:32,880 --> 00:44:33,520
Speaker 7: factoring in?

755
00:44:34,320 --> 00:44:37,359
Speaker 14: We are about to do around a billion in cape

756
00:44:37,360 --> 00:44:42,480
Speaker 14: expanding this year on our endevor Mistile compute, which is

757
00:44:43,680 --> 00:44:46,080
Speaker 14: what we've done last year, is to start and build

758
00:44:46,120 --> 00:44:48,080
Speaker 14: our clusters and to feel some of the data centers

759
00:44:48,120 --> 00:44:51,000
Speaker 14: we're renting with these clusters. The idea being that because

760
00:44:51,040 --> 00:44:53,480
Speaker 14: we have the hardware with the software platform, because we

761
00:44:53,520 --> 00:44:55,719
Speaker 14: know how to build the models and the applications on top,

762
00:44:56,040 --> 00:44:56,759
Speaker 14: combining them.

763
00:44:56,680 --> 00:44:58,120
Speaker 10: With the GPUs is a.

764
00:44:58,080 --> 00:45:02,000
Speaker 14: Way to get to that integrated stock aicloud services that

765
00:45:02,080 --> 00:45:06,560
Speaker 14: I compitting with some of the other fully integrated for vetas.

766
00:45:06,960 --> 00:45:10,200
Speaker 1: Misterie CEO Arthur mench there along with Bloomberg's Jamana Bassecci.

767
00:45:10,640 --> 00:45:13,080
Speaker 1: But as we've just heard that, the status of China's

768
00:45:13,080 --> 00:45:17,120
Speaker 1: AI progress has come up repeatedly at Davos yesterday we

769
00:45:17,160 --> 00:45:20,240
Speaker 1: heard Google Deep Mind CEO Demis Hasibus say that China

770
00:45:20,560 --> 00:45:23,400
Speaker 1: was a missed six months behind the West. These comments

771
00:45:23,400 --> 00:45:25,640
Speaker 1: come as politicians have been more focused, of course, some

772
00:45:25,719 --> 00:45:27,920
Speaker 1: tensions between the US and Europe, perhaps from than the

773
00:45:27,920 --> 00:45:30,920
Speaker 1: AI race with China. Let's discuss the airas with China.

774
00:45:31,000 --> 00:45:34,520
Speaker 1: Eliza Tobin, imagining director at Gano Global, your expertise is

775
00:45:34,560 --> 00:45:37,640
Speaker 1: so important you are, and there's a special competitive studies project.

776
00:45:37,640 --> 00:45:39,279
Speaker 10: You were also helping with national.

777
00:45:39,000 --> 00:45:41,480
Speaker 1: Security at the government level and the China director of

778
00:45:41,480 --> 00:45:43,960
Speaker 1: their lizas, so are you on the idea that it's

779
00:45:44,000 --> 00:45:47,480
Speaker 1: a fairy tale that they're behind that actually they are

780
00:45:47,480 --> 00:45:50,000
Speaker 1: in lockstep with the United States in terms of AI

781
00:45:50,080 --> 00:45:51,800
Speaker 1: agility and compute power.

782
00:45:53,480 --> 00:45:56,200
Speaker 15: Well, good morning, Caroline, is great to be on with you. Yes,

783
00:45:56,320 --> 00:45:58,400
Speaker 15: So a couple of things can be true. At the

784
00:45:58,440 --> 00:46:02,560
Speaker 15: same time, China is absolutely going gangbusters in AI on

785
00:46:02,880 --> 00:46:07,120
Speaker 15: innovation at several layers of the stack. You know, they're

786
00:46:07,160 --> 00:46:10,759
Speaker 15: doing amazing things in open source models and applications, and

787
00:46:10,800 --> 00:46:14,680
Speaker 15: of course at the energy level, where America's number one

788
00:46:14,880 --> 00:46:19,960
Speaker 15: advantage still lies is in computing power at scale. I

789
00:46:20,000 --> 00:46:24,080
Speaker 15: think that's widely agreed upon. You know, Jensen Wong in

790
00:46:24,200 --> 00:46:28,920
Speaker 15: his interview at Davos on Fox was acknowledging this when

791
00:46:28,960 --> 00:46:32,960
Speaker 15: he was talking about the demand constraints that he's facing

792
00:46:33,040 --> 00:46:35,920
Speaker 15: and how these this uh, you know, the just growing

793
00:46:35,960 --> 00:46:39,440
Speaker 15: demand for a limited supply of these AI chips is

794
00:46:39,560 --> 00:46:45,360
Speaker 15: actually growing right now. And so that's why it's somewhat ironic.

795
00:46:45,560 --> 00:46:49,520
Speaker 8: And unfortunately let me let me just jump in here, sure, Liz,

796
00:46:49,640 --> 00:46:51,360
Speaker 8: let me jump in. Jensen Wong may have said that

797
00:46:51,440 --> 00:46:53,320
Speaker 8: in that interview, but Jensen Wan has got a vested

798
00:46:53,360 --> 00:46:55,960
Speaker 8: interest to drive the sales of what is the world's

799
00:46:55,960 --> 00:46:59,480
Speaker 8: most valuable company in a market he said is a

800
00:46:59,480 --> 00:47:02,840
Speaker 8: potential fifty billion dollar market. Right What he doesn't address

801
00:47:03,440 --> 00:47:06,279
Speaker 8: is the concern of those that basically don't think the

802
00:47:06,320 --> 00:47:11,799
Speaker 8: balance is right exporting some deprecated technology still being a

803
00:47:11,880 --> 00:47:16,160
Speaker 8: national security risk in part because it allows China to

804
00:47:16,239 --> 00:47:18,480
Speaker 8: catch up, which is the debate of dabos with having

805
00:47:18,840 --> 00:47:20,840
Speaker 8: Have they got that balance right to your mind?

806
00:47:22,280 --> 00:47:25,719
Speaker 15: No, the current policy in the United States doesn't they are.

807
00:47:26,640 --> 00:47:30,600
Speaker 15: The policy to license H two hundred chips to China

808
00:47:31,080 --> 00:47:33,760
Speaker 15: is giving them a lifeline right where they.

809
00:47:33,640 --> 00:47:34,440
Speaker 5: Need it most.

810
00:47:34,600 --> 00:47:37,600
Speaker 15: You know, the compute advantage that the United States has

811
00:47:38,239 --> 00:47:43,280
Speaker 15: was poised to grow exponentially if the controls stay in place.

812
00:47:43,640 --> 00:47:46,480
Speaker 15: But President Trump and Jensen Wong, for the reasons you

813
00:47:46,520 --> 00:47:50,600
Speaker 15: suggest in video, wants a foothold in the China market.

814
00:47:50,719 --> 00:47:54,160
Speaker 15: What's ironic, of course, is that now Shi Jinping is

815
00:47:54,239 --> 00:47:57,560
Speaker 15: waffling about whether he's even going to let his companies

816
00:47:57,600 --> 00:47:59,920
Speaker 15: buy many of these H two hundred chips because he

817
00:48:00,120 --> 00:48:02,239
Speaker 15: wants to make sure that much of the demand is

818
00:48:02,280 --> 00:48:04,040
Speaker 15: going to the domestic chip makers.

819
00:48:05,000 --> 00:48:09,160
Speaker 1: What's interesting is many would say, we need all of

820
00:48:09,239 --> 00:48:12,880
Speaker 1: technology across the world built on underlying US chips, and

821
00:48:12,880 --> 00:48:15,080
Speaker 1: that's the argument to keep them going into China. Liza,

822
00:48:15,120 --> 00:48:16,560
Speaker 1: do you have much credence to that? Are you more

823
00:48:16,640 --> 00:48:20,720
Speaker 1: looking at Representative Brian Mast You're saying basically that Jensen

824
00:48:20,760 --> 00:48:24,040
Speaker 1: Wang has paid you and your paid minions, he says,

825
00:48:24,040 --> 00:48:26,200
Speaker 1: are fighting to sell millions of advans Ai chips to

826
00:48:26,280 --> 00:48:29,200
Speaker 1: Chinese military companies like Alic, Barbar and Tencent.

827
00:48:30,440 --> 00:48:33,280
Speaker 15: Yeah, it's interesting that Jensen Wang is trying to shift

828
00:48:33,280 --> 00:48:37,320
Speaker 15: the narrative away from the military aspects of AI.

829
00:48:37,880 --> 00:48:39,719
Speaker 4: Of course, these chips.

830
00:48:39,440 --> 00:48:43,880
Speaker 15: Are inherently dual use in China has a military civil

831
00:48:43,960 --> 00:48:48,080
Speaker 15: fusion system in place where you can't guarantee that once

832
00:48:48,400 --> 00:48:51,239
Speaker 15: these chips get into China that they won't make them

833
00:48:51,280 --> 00:48:55,680
Speaker 15: available for military use. That's just a fantasy that we

834
00:48:55,719 --> 00:48:58,799
Speaker 15: can sort of control that. And so, but you see

835
00:48:58,800 --> 00:49:03,719
Speaker 15: that thatnarrative of these things potentially being used for military

836
00:49:03,800 --> 00:49:08,000
Speaker 15: or intelligence uses is inconvenient, so and Huang is trying

837
00:49:08,040 --> 00:49:09,279
Speaker 15: to kind of pivot away from that.

838
00:49:10,400 --> 00:49:13,000
Speaker 8: Liza Tobin of Ghano Global, thank you. These are live

839
00:49:13,080 --> 00:49:17,359
Speaker 8: pictures West Texas, Van Horn and Blue Origins Launchpad New

840
00:49:17,360 --> 00:49:18,439
Speaker 8: Shepherd thirty eight.

841
00:49:18,520 --> 00:49:20,520
Speaker 9: Let's listen in. We're braced for lift off.

842
00:49:22,560 --> 00:49:59,560
Speaker 16: Fie for commander Sorry two one zero, Hi.

843
00:49:59,520 --> 00:50:00,000
Speaker 2: Father you.

844
00:50:04,600 --> 00:50:06,880
Speaker 5: Careful person eleven thousand feet.

845
00:50:10,200 --> 00:50:13,440
Speaker 6: All right, New Shepherd of Pets. Take a look on

846
00:50:13,480 --> 00:50:15,080
Speaker 6: your screen on the left hand side of the screen.

847
00:50:15,120 --> 00:50:17,239
Speaker 6: You'll be able to follow along with our telemetry giving

848
00:50:17,239 --> 00:50:20,200
Speaker 6: you altom code and speed, and then on the bottom

849
00:50:20,280 --> 00:50:21,719
Speaker 6: right hand side of the screen you'll be able to

850
00:50:21,719 --> 00:50:31,680
Speaker 6: see how far we are in S thirty eighth flight.

851
00:50:34,120 --> 00:50:38,200
Speaker 8: Okay, you are watching live images of Blue Orangins NS

852
00:50:38,360 --> 00:50:43,799
Speaker 8: thirty eight New Shepherd mission carrying the six latest astronauts

853
00:50:43,840 --> 00:50:47,960
Speaker 8: commercial passengers to just above the Carmen line out of

854
00:50:48,040 --> 00:50:50,799
Speaker 8: Van Horn, West, Texas. We've just hit max Q, the

855
00:50:50,840 --> 00:50:55,680
Speaker 8: moment of maximum aerodynamic pressure or stress on that vehicle.

856
00:50:56,320 --> 00:50:59,279
Speaker 8: The Blue Origin New Shepherd design relies on its own

857
00:50:59,400 --> 00:51:03,920
Speaker 8: B three pm engine, where the propellant is a mix

858
00:51:04,080 --> 00:51:08,400
Speaker 8: of hydrogen and oxygen, the byproduct of which is water.

859
00:51:08,719 --> 00:51:11,280
Speaker 8: For those chemistry nerds of you that are out there

860
00:51:11,520 --> 00:51:14,839
Speaker 8: and Carrow, you know, we cover this because it is

861
00:51:15,080 --> 00:51:18,080
Speaker 8: the evidence of the development of commercial space. You have

862
00:51:18,120 --> 00:51:20,200
Speaker 8: six people on board, some of them have paid for

863
00:51:20,239 --> 00:51:22,799
Speaker 8: the privilege. We don't know how much because they don't

864
00:51:22,880 --> 00:51:26,480
Speaker 8: disclose it, just for sixty seconds of weightlessness in space

865
00:51:26,800 --> 00:51:29,600
Speaker 8: in what Blue Origin says are the biggest windows to

866
00:51:29,640 --> 00:51:30,600
Speaker 8: ever go into space.

867
00:51:31,000 --> 00:51:35,800
Speaker 1: And by now this is almost becoming regular and ninety

868
00:51:35,880 --> 00:51:39,080
Speaker 1: humans above the Carmen line have been flown by Blue Origin.

869
00:51:39,160 --> 00:51:41,160
Speaker 10: Thus fur right, so we're.

870
00:51:41,000 --> 00:51:43,480
Speaker 1: Starting to see the cadence build up and where does

871
00:51:43,480 --> 00:51:46,120
Speaker 1: that push Blue Origin in terms of its next steps

872
00:51:46,120 --> 00:51:47,040
Speaker 1: in commercialization.

873
00:51:48,160 --> 00:51:50,839
Speaker 8: Again, Blue Origin is a multifaceted business. So what you're

874
00:51:50,840 --> 00:51:55,839
Speaker 8: watching on your screen now, as the combined vehicle makes

875
00:51:55,880 --> 00:51:57,600
Speaker 8: its way up to that Carmon line, you have the

876
00:51:57,600 --> 00:51:59,759
Speaker 8: third stage booster and then the caps you're on top.

877
00:52:00,080 --> 00:52:03,360
Speaker 8: This is space tourism essentially, right. They will also argue

878
00:52:03,520 --> 00:52:06,400
Speaker 8: that it provides a zero gravity environment even for sixty

879
00:52:06,440 --> 00:52:10,120
Speaker 8: seconds to do scientific experimentation. But the news last night

880
00:52:10,520 --> 00:52:13,600
Speaker 8: Blue Origin is also working on a starlink competitor, right,

881
00:52:13,920 --> 00:52:18,319
Speaker 8: satellite based and consolation based connectivity. Then they have a

882
00:52:18,320 --> 00:52:20,799
Speaker 8: more powerful rocket, new Glen, which is used for a

883
00:52:20,840 --> 00:52:25,279
Speaker 8: wide range of commercial applications. But putting satellite deployment into

884
00:52:25,280 --> 00:52:28,920
Speaker 8: low Earth orbit, we're about three minutes into this mission.

885
00:52:29,640 --> 00:52:32,200
Speaker 9: We expect that the separation.

886
00:52:31,840 --> 00:52:35,120
Speaker 8: To happen imminently, and then what you have is that

887
00:52:35,280 --> 00:52:39,200
Speaker 8: three minute, thirty seconds mark Carrow. Those six passengers goes

888
00:52:39,239 --> 00:52:41,600
Speaker 8: to the Carmen line, which is the kind of recognized

889
00:52:41,640 --> 00:52:44,920
Speaker 8: boundary of space where they'll get out, undo their seat

890
00:52:44,920 --> 00:52:47,560
Speaker 8: belts and float around looking out of the window. And

891
00:52:47,600 --> 00:52:50,160
Speaker 8: again some of them paid hundreds of thousands. We don't

892
00:52:50,160 --> 00:52:52,359
Speaker 8: have a specific number for the privilege of doing that.

893
00:52:52,719 --> 00:52:54,960
Speaker 1: Yeah, and some of the names might be known to

894
00:52:55,040 --> 00:52:58,560
Speaker 1: many Tim Drexler, for example, but a lot of entrepreneurial names,

895
00:52:58,840 --> 00:53:00,640
Speaker 1: some obstetricians or in there.

896
00:53:00,680 --> 00:53:01,040
Speaker 10: But we've got T.

897
00:53:01,239 --> 00:53:05,080
Speaker 1: Drexel, Lilinda Edwards, Alane Fernanand's, for example, among the six

898
00:53:05,160 --> 00:53:07,239
Speaker 1: that are currently in that capsule.

899
00:53:07,520 --> 00:53:08,759
Speaker 10: And there was a slight delay to it.

900
00:53:08,840 --> 00:53:12,640
Speaker 1: We understand that there wasnown unauthorized personnel and the line

901
00:53:12,680 --> 00:53:14,479
Speaker 1: of the rocket as to why it was pushed back

902
00:53:14,760 --> 00:53:15,440
Speaker 1: that little.

903
00:53:15,239 --> 00:53:16,040
Speaker 10: Bit on the day.

904
00:53:16,440 --> 00:53:19,120
Speaker 1: But talk us through the risks of any of what

905
00:53:19,239 --> 00:53:20,720
Speaker 1: has become standardized practice.

906
00:53:21,440 --> 00:53:26,200
Speaker 8: Every launch that involves human payload, humans on board is

907
00:53:26,239 --> 00:53:29,239
Speaker 8: a risk. The hold on this case, the delay, if

908
00:53:29,280 --> 00:53:33,279
Speaker 8: you like, was because of unauthorized personnel on range, but

909
00:53:33,360 --> 00:53:36,080
Speaker 8: that is a very wide radius. You have to control

910
00:53:36,120 --> 00:53:38,759
Speaker 8: both the eight airspace and on the ground subject to

911
00:53:39,080 --> 00:53:41,719
Speaker 8: itar restrictions because it's a rocket. At the end of

912
00:53:41,719 --> 00:53:43,960
Speaker 8: the day. The view that you're looking at is just

913
00:53:43,960 --> 00:53:46,280
Speaker 8: switch right. So you can see those two white dots

914
00:53:46,280 --> 00:53:48,719
Speaker 8: if you squint and you look very closely, one is

915
00:53:48,760 --> 00:53:52,440
Speaker 8: the capsule and one is the booster there's kind of

916
00:53:52,760 --> 00:53:55,880
Speaker 8: rapidly coming back down to Earth. And what will happen

917
00:53:56,120 --> 00:53:58,320
Speaker 8: very very soon, because we're at the four minutes thirty

918
00:53:58,320 --> 00:54:03,560
Speaker 8: second mark, is those inside the capsule, the six of them,

919
00:54:03,800 --> 00:54:06,480
Speaker 8: will get a one minute warning where they've been through

920
00:54:06,520 --> 00:54:10,560
Speaker 8: this training process where they'll buckle themselves back in, and

921
00:54:10,600 --> 00:54:13,319
Speaker 8: then it's good old fashioned rocket science where the flat

922
00:54:13,360 --> 00:54:17,000
Speaker 8: bottom of the capsule and Earth's gravitational pool brings it

923
00:54:17,280 --> 00:54:19,640
Speaker 8: back down into Earth's atmosphere and we can kind of

924
00:54:19,680 --> 00:54:20,040
Speaker 8: go from that.

925
00:54:20,680 --> 00:54:22,640
Speaker 1: And we can continue this is like a ten minute

926
00:54:22,680 --> 00:54:24,960
Speaker 1: process and we're already as you say, at the halfway

927
00:54:25,000 --> 00:54:27,279
Speaker 1: point ed. We can go to Lolngrush, who helps cover

928
00:54:27,400 --> 00:54:30,560
Speaker 1: all things space across our network and platforms for us,

929
00:54:30,560 --> 00:54:32,919
Speaker 1: and this seems to be going all according to plan

930
00:54:32,960 --> 00:54:35,560
Speaker 1: as we think. But space very much in line of

931
00:54:35,600 --> 00:54:38,760
Speaker 1: sight of investors at the moment, but also of the market.

932
00:54:38,760 --> 00:54:40,000
Speaker 10: Well broadly, we're thinking.

933
00:54:39,760 --> 00:54:42,160
Speaker 1: About Elon Musk's just come off stage over at Davos

934
00:54:42,160 --> 00:54:46,120
Speaker 1: talking about how his reusable giant rocket might be there

935
00:54:46,200 --> 00:54:48,080
Speaker 1: by the end of this year in terms of re usability.

936
00:54:48,960 --> 00:54:52,480
Speaker 17: Yes, that is the ultimate goal of Starship, which they've

937
00:54:52,520 --> 00:54:57,000
Speaker 17: been pursuing for some time for reusability. You know, actually

938
00:54:57,040 --> 00:55:00,319
Speaker 17: the New Shepherd is a fully reusable system, but it

939
00:55:00,320 --> 00:55:02,920
Speaker 17: obviously does not go to orbit, and so Starship is

940
00:55:03,040 --> 00:55:05,640
Speaker 17: really trying to accomplish a feat that no one has

941
00:55:05,680 --> 00:55:08,360
Speaker 17: been able to before. And Elon just said that they

942
00:55:08,440 --> 00:55:12,440
Speaker 17: hope to get to full reusability sometime this year. That

943
00:55:12,480 --> 00:55:14,880
Speaker 17: would be a major accomplishment if they can make it happen.

944
00:55:14,960 --> 00:55:17,040
Speaker 17: And we'll obviously be keeping an eye out on those

945
00:55:17,120 --> 00:55:20,359
Speaker 17: Starship test flights, which are always so fun, but yeah,

946
00:55:20,400 --> 00:55:22,319
Speaker 17: that will be a big moment if they can make

947
00:55:22,320 --> 00:55:22,800
Speaker 17: it happen.

948
00:55:23,840 --> 00:55:26,640
Speaker 8: We got Bloomberg's Lauren Grass, she leads our coverage on space,

949
00:55:26,680 --> 00:55:28,359
Speaker 8: and on the left hand side of your screen, we've

950
00:55:28,360 --> 00:55:32,799
Speaker 8: got the downward camera on the New Shepherd booster as

951
00:55:32,920 --> 00:55:35,560
Speaker 8: it returns down to Earth for about six minutes in Lauren,

952
00:55:35,600 --> 00:55:38,520
Speaker 8: booster descending, and then the capsule when any second will

953
00:55:38,520 --> 00:55:40,759
Speaker 8: start descending by the way, peeking at like four to

954
00:55:40,840 --> 00:55:42,960
Speaker 8: five G on the way around. Karen and I were

955
00:55:42,960 --> 00:55:46,359
Speaker 8: talking about how we carry this right because it's an

956
00:55:46,400 --> 00:55:50,480
Speaker 8: expensive endeavor for space tourism, but Blue origins business as

957
00:55:50,480 --> 00:55:53,680
Speaker 8: we see that that booster coming down is multifaceted what's

958
00:55:53,719 --> 00:55:55,160
Speaker 8: the big priority for Blue right now.

959
00:55:56,080 --> 00:55:58,520
Speaker 17: Well, it actually comes at a really interesting time. They

960
00:55:58,600 --> 00:56:02,600
Speaker 17: just announced the third upcoming flight for their New Glen rocket.

961
00:56:02,719 --> 00:56:06,200
Speaker 17: That's their much larger orbital rocket that they've launched twice

962
00:56:06,239 --> 00:56:10,319
Speaker 17: now and successfully landed on a barge on that second flight. Now,

963
00:56:10,440 --> 00:56:14,040
Speaker 17: New Glen is not fully reusable the second stage, the

964
00:56:14,120 --> 00:56:16,640
Speaker 17: upper portion of the rocket does not come back, but

965
00:56:16,760 --> 00:56:19,880
Speaker 17: they were able to achieve that partial reusability with the

966
00:56:19,920 --> 00:56:22,960
Speaker 17: second flight. So they're really getting into full swing with

967
00:56:23,200 --> 00:56:26,759
Speaker 17: their launch business. And so hopefully just as these new

968
00:56:26,760 --> 00:56:30,160
Speaker 17: Shepherd flights are becoming routine, new Glenn flights will become

969
00:56:30,239 --> 00:56:31,000
Speaker 17: routine as well.

970
00:56:31,560 --> 00:56:34,160
Speaker 1: And we have at this moment the booster landing. Will

971
00:56:34,200 --> 00:56:37,239
Speaker 1: see if they note it successfully it's seven minute, ten

972
00:56:37,360 --> 00:56:40,360
Speaker 1: second mark. It's going to make for a beautiful picture.

973
00:56:40,400 --> 00:56:43,200
Speaker 1: It just took us through the complex nature of a

974
00:56:43,200 --> 00:56:43,960
Speaker 1: boosta landing.

975
00:56:44,760 --> 00:56:48,359
Speaker 8: Well, booster fools three fall through the air using air

976
00:56:48,400 --> 00:56:49,600
Speaker 8: resistance physics.

977
00:56:49,920 --> 00:56:51,200
Speaker 9: Then it ignites that B.

978
00:56:51,400 --> 00:56:55,560
Speaker 8: Three and smoothly touches down a little needle in the

979
00:56:55,600 --> 00:56:58,240
Speaker 8: haystat landing a pin in the middle of the West

980
00:56:58,280 --> 00:56:59,000
Speaker 8: Texas desert.

981
00:56:59,080 --> 00:57:01,120
Speaker 9: Kind of moment character, isn't it?

982
00:57:01,280 --> 00:57:04,239
Speaker 1: Just so there we are boost a touchdown is hit

983
00:57:04,360 --> 00:57:07,800
Speaker 1: at the moment we're t plus seven thirty nine forty

984
00:57:07,880 --> 00:57:11,200
Speaker 1: let's call it capsule reacquired comes at eight minutes, Lauren.

985
00:57:11,600 --> 00:57:15,000
Speaker 1: And all of this is being remind us financed how

986
00:57:15,080 --> 00:57:17,360
Speaker 1: people are obviously paying their way to a certain extent,

987
00:57:17,400 --> 00:57:19,600
Speaker 1: and we don't know exactly who, but this is still

988
00:57:19,680 --> 00:57:24,000
Speaker 1: VC backed very much the endeavor of Amazon founder Jeff Bezos.

989
00:57:24,440 --> 00:57:28,120
Speaker 17: Right, I mean, as you mentioned before, passengers plate pay

990
00:57:28,200 --> 00:57:31,880
Speaker 17: some undisclosed sum to fly on these these flights. But yes,

991
00:57:32,000 --> 00:57:35,600
Speaker 17: I mean Blue Origin is by far very big passion

992
00:57:35,880 --> 00:57:39,680
Speaker 17: of Jeff Bezos, and he has been primarily the funder

993
00:57:39,840 --> 00:57:43,200
Speaker 17: of the endeavor for some time now. Obviously, the goal

994
00:57:43,320 --> 00:57:45,880
Speaker 17: is to move away from that system, to have more

995
00:57:45,920 --> 00:57:49,840
Speaker 17: and more customers, and to eventually become a profitable business.

996
00:57:50,120 --> 00:57:54,560
Speaker 17: You know, that will either that's through satellite contracts, launch contracts.

997
00:57:54,280 --> 00:57:54,840
Speaker 9: Things like that.

998
00:57:55,040 --> 00:57:58,400
Speaker 17: And then also Blue Origin just announced a new mega

999
00:57:58,440 --> 00:58:01,280
Speaker 17: constellation to be a competitor to Starlink, so they have

1000
00:58:01,320 --> 00:58:06,400
Speaker 17: a lot of different revenue streams coming in hopefully soon, Lauren.

1001
00:58:06,440 --> 00:58:08,320
Speaker 8: We just saw the drogue shoots and then the main

1002
00:58:08,400 --> 00:58:13,080
Speaker 8: shoots deploy on the New Shepherd capsule on its way down.

1003
00:58:13,480 --> 00:58:16,720
Speaker 8: Now it's chill, you're just floating and by the time

1004
00:58:16,760 --> 00:58:20,120
Speaker 8: you boost a landing speed like six miles per hour.

1005
00:58:20,280 --> 00:58:22,640
Speaker 8: So we will wait for that over the course of

1006
00:58:22,680 --> 00:58:25,400
Speaker 8: the next two minutes to ensure that the capsule lands safely.

1007
00:58:25,680 --> 00:58:30,000
Speaker 8: You just talked about the business of consolation based satellite.

1008
00:58:30,040 --> 00:58:33,600
Speaker 8: We talked earlier in the conversation about Blue Origins efforts

1009
00:58:33,600 --> 00:58:36,280
Speaker 8: that news last night. We also are trying to keep

1010
00:58:36,280 --> 00:58:38,920
Speaker 8: on top of Elon Musk's appearance at Davos, which you

1011
00:58:38,960 --> 00:58:41,120
Speaker 8: and I were both tuned in for. Right He did

1012
00:58:41,200 --> 00:58:45,000
Speaker 8: talk about starship and some of the broader kind of

1013
00:58:45,120 --> 00:58:48,600
Speaker 8: academic questions around space based data center as best you

1014
00:58:48,640 --> 00:58:50,240
Speaker 8: can just give us a summary of that while we

1015
00:58:50,320 --> 00:58:52,520
Speaker 8: await the Blue Origin capsule touching down.

1016
00:58:53,160 --> 00:58:56,520
Speaker 17: Sure, so, as Elon indicated, he's a very big fan

1017
00:58:56,600 --> 00:59:00,320
Speaker 17: of solar power. One of the justifications for moving data

1018
00:59:00,360 --> 00:59:03,280
Speaker 17: centers into space is depending on where you put them,

1019
00:59:03,480 --> 00:59:06,760
Speaker 17: you can have this constant access to solar power, which,

1020
00:59:06,960 --> 00:59:10,040
Speaker 17: as people who know much about AI and the data

1021
00:59:10,080 --> 00:59:14,160
Speaker 17: center industry here on Earth, power constraints can actually be

1022
00:59:14,200 --> 00:59:18,480
Speaker 17: a huge limiting factor. So moving to space, the likes

1023
00:59:18,520 --> 00:59:21,800
Speaker 17: of Elon and other billionaires, even Jeff Bezos have talked

1024
00:59:21,800 --> 00:59:24,880
Speaker 17: about perhaps, you know, tapping into that solar power to

1025
00:59:24,920 --> 00:59:28,560
Speaker 17: get near constant access to sunlight that can then power

1026
00:59:28,600 --> 00:59:31,800
Speaker 17: these data centers that do all this complex computing.

1027
00:59:32,600 --> 00:59:35,200
Speaker 1: Yeah, we heard Musks saying really in the next two

1028
00:59:35,280 --> 00:59:37,440
Speaker 1: to three years, space is going to be the cheapest

1029
00:59:37,440 --> 00:59:38,280
Speaker 1: place to put AI.

1030
00:59:38,400 --> 00:59:42,880
Speaker 10: And there, look, we have the landing touchdown chill ed

1031
00:59:43,200 --> 00:59:44,880
Speaker 10: as you called it. It looks like quite a lot of

1032
00:59:44,960 --> 00:59:46,120
Speaker 10: dust being blown up.

1033
00:59:48,240 --> 00:59:50,240
Speaker 8: If you're going up at three g's and you're coming

1034
00:59:50,240 --> 00:59:52,440
Speaker 8: down at four to five d's, but the moment you

1035
00:59:52,520 --> 00:59:55,640
Speaker 8: touch the ground is just like a little then that's

1036
00:59:55,640 --> 00:59:57,959
Speaker 8: what I meant by chill. But again we talked about

1037
00:59:57,960 --> 01:00:01,160
Speaker 8: this being routine and sorry to interrupt, Carr. You will

1038
01:00:01,160 --> 01:00:03,840
Speaker 8: wait for confirmation from Blue but as it stands, you know,

1039
01:00:03,880 --> 01:00:05,040
Speaker 8: another successful mission.

1040
01:00:06,000 --> 01:00:07,800
Speaker 10: It is seemingly successful.

1041
01:00:07,800 --> 01:00:10,280
Speaker 1: We'll check in on those succes astronauts as they're known,

1042
01:00:10,320 --> 01:00:13,360
Speaker 1: and what the common line touching and the zero gravity

1043
01:00:13,440 --> 01:00:17,520
Speaker 1: feel was like for each individual. Lauren, We though always

1044
01:00:17,560 --> 01:00:20,400
Speaker 1: come back on Bloomberg to the financing of this and

1045
01:00:20,520 --> 01:00:23,960
Speaker 1: we all wait potentially twenty twenty six an enormous IPO

1046
01:00:24,320 --> 01:00:25,400
Speaker 1: of SpaceX as well.

1047
01:00:25,440 --> 01:00:26,640
Speaker 10: That must be something you're tuned in for.

1048
01:00:27,400 --> 01:00:27,640
Speaker 3: Oh.

1049
01:00:27,760 --> 01:00:28,480
Speaker 4: Absolutely.

1050
01:00:28,560 --> 01:00:31,720
Speaker 17: I think the entire space industry is kind of on.

1051
01:00:31,680 --> 01:00:33,760
Speaker 4: Pins and needles awaiting.

1052
01:00:33,720 --> 01:00:37,400
Speaker 17: How this IPO will play out. And obviously, as we mentioned,

1053
01:00:37,400 --> 01:00:40,400
Speaker 17: one of the big fueling the things fueling the IPO

1054
01:00:40,760 --> 01:00:45,320
Speaker 17: is this concept of raising capital capital for space data centers.

1055
01:00:45,360 --> 01:00:49,280
Speaker 17: So I think it'll have a very sizable impact on

1056
01:00:49,320 --> 01:00:52,720
Speaker 17: the entire space industry, not just SpaceX. I've spoken to

1057
01:00:52,840 --> 01:00:55,800
Speaker 17: a number of experts who think that this will open

1058
01:00:55,840 --> 01:00:58,960
Speaker 17: the door for even more investment in the space industry,

1059
01:00:58,960 --> 01:01:02,040
Speaker 17: which is sometimes cannsidered, very niche. So I think even

1060
01:01:02,120 --> 01:01:05,240
Speaker 17: the competitors of SpaceX are probably pretty excited to see

1061
01:01:05,280 --> 01:01:06,720
Speaker 17: how this plays out.

1062
01:01:07,200 --> 01:01:09,280
Speaker 8: We're going to move away from West Texas, and when

1063
01:01:09,320 --> 01:01:11,120
Speaker 8: Blue Origin confirms all as well, we'll bring it to

1064
01:01:11,120 --> 01:01:13,400
Speaker 8: the audience and go back to Elon Musk at Davos

1065
01:01:13,440 --> 01:01:15,240
Speaker 8: and let's listen to some of what he had to

1066
01:01:15,240 --> 01:01:15,920
Speaker 8: say on stage.

1067
01:01:17,240 --> 01:01:22,440
Speaker 5: Probably sometime next year. I'd say that by the end

1068
01:01:22,440 --> 01:01:27,840
Speaker 5: of next year, I think would be selling humanoid robots

1069
01:01:28,480 --> 01:01:33,080
Speaker 5: to the public. That's when we are confident that it's

1070
01:01:33,200 --> 01:01:36,640
Speaker 5: very higher liability very high safety and the range of

1071
01:01:36,640 --> 01:01:40,440
Speaker 5: functionality is also very high. You can basically ask if

1072
01:01:40,520 --> 01:01:41,440
Speaker 5: to do anything you'd like.

1073
01:01:43,240 --> 01:01:47,440
Speaker 8: Well, that was the timeline prediction that moved markets. Tesla

1074
01:01:47,480 --> 01:01:50,880
Speaker 8: Schees rose when Musk said that Musk often misses his

1075
01:01:50,920 --> 01:01:54,560
Speaker 8: own deadlines in the space context, Lauren, that's your domain,

1076
01:01:54,920 --> 01:01:57,120
Speaker 8: Just real quick, What were the kind of timelines that

1077
01:01:57,160 --> 01:01:59,600
Speaker 8: he gave, if any on that part of his business?

1078
01:02:00,400 --> 01:02:03,520
Speaker 17: Right? So he said, The things that I took note

1079
01:02:03,560 --> 01:02:05,560
Speaker 17: of are the fact that he thinks that space will

1080
01:02:05,600 --> 01:02:08,560
Speaker 17: be the cheapest place for AI data centers to be

1081
01:02:08,720 --> 01:02:11,200
Speaker 17: in the next two to three years. Obviously, I think

1082
01:02:11,280 --> 01:02:14,720
Speaker 17: that might be a very ambitious timeline as well. Jeff

1083
01:02:14,760 --> 01:02:18,439
Speaker 17: Bezos has given a timeline of ten years in order

1084
01:02:18,480 --> 01:02:21,640
Speaker 17: for it to be economically feasible, and I spoke to

1085
01:02:21,640 --> 01:02:24,640
Speaker 17: another expert who mentioned that makes a little bit more sense.

1086
01:02:24,960 --> 01:02:27,439
Speaker 17: And then on the starship front, as we mentioned, he

1087
01:02:27,520 --> 01:02:31,680
Speaker 17: talked about getting to full reusability sometime this year. Again,

1088
01:02:32,000 --> 01:02:34,240
Speaker 17: that's going to be a very big feat if and

1089
01:02:34,280 --> 01:02:36,680
Speaker 17: when they pull it off. I can't say speak to

1090
01:02:36,720 --> 01:02:38,520
Speaker 17: whether or not they will do it this year, but

1091
01:02:38,560 --> 01:02:42,120
Speaker 17: they've obviously been doing these periodic test flights of starship

1092
01:02:42,360 --> 01:02:45,080
Speaker 17: in order to reach that goal, and so either way,

1093
01:02:45,120 --> 01:02:48,240
Speaker 17: it should be very exciting to watch as they incrementally

1094
01:02:48,280 --> 01:02:49,720
Speaker 17: get closer to that development.

1095
01:02:50,200 --> 01:02:52,760
Speaker 1: And Lauren, you'll be along the way for us as always,

1096
01:02:52,800 --> 01:02:55,160
Speaker 1: guiding absolutely show and across platform.

1097
01:02:55,160 --> 01:02:55,840
Speaker 10: Thanks you so much.

1098
01:02:55,880 --> 01:02:59,439
Speaker 1: Blomberg's longrush on all Things space. We're just talking about

1099
01:02:59,440 --> 01:03:01,840
Speaker 1: Elo Musk at Davos. What he said, others have been

1100
01:03:01,880 --> 01:03:05,040
Speaker 1: there too, funny enough. Doc Trace CEO Jill Papelka, and

1101
01:03:05,120 --> 01:03:08,840
Speaker 1: she says that AI has quote democratized cyber attacks and

1102
01:03:08,880 --> 01:03:11,160
Speaker 1: there needs to be a shift towards sophisticated defenses to

1103
01:03:11,160 --> 01:03:14,040
Speaker 1: protect businesses. To play with Brineberg's Francin Laqua on the

1104
01:03:14,040 --> 01:03:16,640
Speaker 1: sidelines of twenty twenty six, Well Economic Forum, take listen.

1105
01:03:19,000 --> 01:03:22,120
Speaker 2: The threats are becoming more sophisticated, they're becoming more complex.

1106
01:03:22,400 --> 01:03:25,160
Speaker 2: And whereas before we might have thought about being attacker

1107
01:03:25,240 --> 01:03:27,560
Speaker 2: centric and trying to predict what the attacker was going

1108
01:03:27,600 --> 01:03:27,919
Speaker 2: to do.

1109
01:03:27,880 --> 01:03:30,040
Speaker 9: Next, that's not what dark Trace has ever.

1110
01:03:29,880 --> 01:03:31,880
Speaker 2: Done, and it's definitely not what we can do moving

1111
01:03:31,920 --> 01:03:36,200
Speaker 2: forward because we can't predict this high velocity, high threat landscape.

1112
01:03:36,280 --> 01:03:39,280
Speaker 2: We know that countries like Japan, for example, they used

1113
01:03:39,280 --> 01:03:41,440
Speaker 2: to have a natural barrier because their language was more

1114
01:03:41,440 --> 01:03:42,840
Speaker 2: complex and people couldn't.

1115
01:03:42,600 --> 01:03:43,080
Speaker 9: Quite get there.

1116
01:03:43,120 --> 01:03:45,360
Speaker 2: You know, the cyber attackers couldn't get their heads around

1117
01:03:45,800 --> 01:03:48,840
Speaker 2: creating an attack in Japanese. But now AI can create

1118
01:03:48,880 --> 01:03:52,520
Speaker 2: those complex, highly sophisticated threats in any language around the world.

1119
01:03:52,720 --> 01:03:55,040
Speaker 2: And so right we're looking at a much higher velocity

1120
01:03:55,040 --> 01:03:55,800
Speaker 2: threat landscape.

1121
01:03:55,880 --> 01:03:59,439
Speaker 18: So is AI and cybersecurity much more sophisticated than even

1122
01:03:59,480 --> 01:04:00,000
Speaker 18: twelve months?

1123
01:04:00,520 --> 01:04:03,600
Speaker 2: Oh, of course it's becoming more and more sophisticated. We

1124
01:04:03,640 --> 01:04:06,200
Speaker 2: have the most amazing minds in Cambridge, people who are

1125
01:04:06,560 --> 01:04:09,360
Speaker 2: linguistics majors, people who have majored in the classics. But

1126
01:04:09,480 --> 01:04:12,280
Speaker 2: now looking at how is this AI challenged for us?

1127
01:04:12,280 --> 01:04:13,760
Speaker 2: How do we protect the world against it?

1128
01:04:13,880 --> 01:04:17,680
Speaker 18: So, after a dark TRACE's acquisition by Thomas Bravo and

1129
01:04:17,720 --> 01:04:20,080
Speaker 18: the shift to operating privately, how has that changed your

1130
01:04:20,120 --> 01:04:21,920
Speaker 18: focus and investment strategy?

1131
01:04:22,080 --> 01:04:24,680
Speaker 2: You know, dark Trace was already changing and so the

1132
01:04:24,880 --> 01:04:27,880
Speaker 2: transition into private equity ownership really was it that big

1133
01:04:27,880 --> 01:04:29,960
Speaker 2: a deal for us? We were continuing on our path

1134
01:04:30,000 --> 01:04:33,080
Speaker 2: of innovating and creating the latest and greatest products. We

1135
01:04:33,080 --> 01:04:36,040
Speaker 2: were also working on scaling our business, so we had

1136
01:04:36,080 --> 01:04:39,440
Speaker 2: become really a seven hundred million dollar startup, and then

1137
01:04:39,480 --> 01:04:41,920
Speaker 2: we needed to ensure that our systems and our processes

1138
01:04:41,960 --> 01:04:44,400
Speaker 2: and our talent acquisition and all the different things that

1139
01:04:45,080 --> 01:04:47,840
Speaker 2: big companies do that we were doing those really well.

1140
01:04:47,960 --> 01:04:51,720
Speaker 18: Also, are the cyber threats coming from government agents or

1141
01:04:51,800 --> 01:04:53,960
Speaker 18: like you know, government entities, or what can you tell

1142
01:04:54,000 --> 01:04:56,200
Speaker 18: us about where the biggest threat is coming from?

1143
01:04:56,280 --> 01:04:59,800
Speaker 2: You know what's interesting is AI has democratized cyber attacks.

1144
01:05:00,000 --> 01:05:02,040
Speaker 2: It's like it's democratize so many other things, and so

1145
01:05:02,480 --> 01:05:04,960
Speaker 2: it doesn't it doesn't really matter where it's coming from.

1146
01:05:04,960 --> 01:05:07,360
Speaker 2: From a dark Trace perspective, we're going to protect you

1147
01:05:07,400 --> 01:05:09,680
Speaker 2: from a nation state actor, just like we're going to

1148
01:05:09,720 --> 01:05:12,680
Speaker 2: protect you from a Western teenager at his garage, you know,

1149
01:05:12,800 --> 01:05:14,800
Speaker 2: having a heyday with AI that day. So it's not

1150
01:05:15,160 --> 01:05:17,560
Speaker 2: it's not so much about being attacker centric. What we

1151
01:05:17,600 --> 01:05:19,160
Speaker 2: do want to think about, though, is how we get

1152
01:05:19,200 --> 01:05:21,800
Speaker 2: every anomaly and how we ensure that we're protecting from this.

1153
01:05:24,200 --> 01:05:27,240
Speaker 8: That was dark Trace CEO Jill Papelco, along with Bloomberg's

1154
01:05:27,240 --> 01:05:30,320
Speaker 8: friend Scene Lacua now coming up, a startup aiming to

1155
01:05:30,360 --> 01:05:34,040
Speaker 8: outperform today's AI accelerators, has attracted one hundred and ten

1156
01:05:34,080 --> 01:05:37,680
Speaker 8: million dollars in Series AID funding. Neurofos CEO Patrick Bowen,

1157
01:05:37,720 --> 01:05:40,480
Speaker 8: an M twelve managing partner Michael Stewart join us.

1158
01:05:40,480 --> 01:05:43,320
Speaker 9: Next. This is Bloomberg Tech.

1159
01:05:48,280 --> 01:05:51,000
Speaker 8: Hei chip startup Neurofoss has closed a one hundred and

1160
01:05:51,040 --> 01:05:54,080
Speaker 8: ten million dollar Series A funding round. The company makes

1161
01:05:54,120 --> 01:05:57,920
Speaker 8: an optical processing unit with over a million micron scale

1162
01:05:58,200 --> 01:06:01,480
Speaker 8: optical elements on a single chain. They rely on light

1163
01:06:01,840 --> 01:06:05,080
Speaker 8: to transmit data. It claims this OPU delivers up to

1164
01:06:05,200 --> 01:06:08,320
Speaker 8: one hundred x of the performance and energy efficiency of

1165
01:06:08,400 --> 01:06:11,520
Speaker 8: current leading GPUs and accelerated cards. Let's get to it,

1166
01:06:11,600 --> 01:06:13,600
Speaker 8: Patrick Burron, you're a FOSS co founder and CEO and

1167
01:06:13,640 --> 01:06:16,840
Speaker 8: Michael Stewart managing partner at M twelve formerly known as

1168
01:06:16,880 --> 01:06:20,560
Speaker 8: Microsoft Venture Fund. Patrick, the devil's in the detail here,

1169
01:06:20,800 --> 01:06:23,760
Speaker 8: the use of light to transmit data instead of electrons.

1170
01:06:23,920 --> 01:06:26,840
Speaker 8: And again I'm not an engineer, but what is this

1171
01:06:26,920 --> 01:06:28,440
Speaker 8: OPU design that you're developing.

1172
01:06:28,760 --> 01:06:31,480
Speaker 19: It's essentially designed to be a drop in replacement for

1173
01:06:31,520 --> 01:06:35,000
Speaker 19: a GPU, but actually runs fifty to one hundred times

1174
01:06:35,160 --> 01:06:38,160
Speaker 19: both faster and with fifty to one hundred times higher

1175
01:06:38,240 --> 01:06:40,840
Speaker 19: row energy. Of use case in the inference use case,

1176
01:06:40,920 --> 01:06:41,480
Speaker 19: not for training.

1177
01:06:41,520 --> 01:06:45,480
Speaker 8: That's right, you're an engineer by trade, by background. But

1178
01:06:45,600 --> 01:06:48,960
Speaker 8: then you go to the dark side Aventure capital, Why

1179
01:06:49,080 --> 01:06:50,960
Speaker 8: back this project? You know you're going to tell me

1180
01:06:51,400 --> 01:06:53,960
Speaker 8: that there's a gap, there's a problem being solved for here.

1181
01:06:54,280 --> 01:06:58,320
Speaker 8: There are lots of inference solutions out there, different technological underpinning,

1182
01:06:58,360 --> 01:07:00,480
Speaker 8: but why this one.

1183
01:07:01,720 --> 01:07:04,240
Speaker 20: Our investment focus is on the data center of the future,

1184
01:07:04,520 --> 01:07:09,000
Speaker 20: and by and large, the industry has committed massive amounts

1185
01:07:09,040 --> 01:07:12,000
Speaker 20: of capital to scaling the technology that we know and understand,

1186
01:07:12,720 --> 01:07:16,520
Speaker 20: and from our investment thesis, our investment aims, we're really

1187
01:07:16,600 --> 01:07:18,880
Speaker 20: looking for what is far beyond the state of the

1188
01:07:18,960 --> 01:07:23,120
Speaker 20: art to disrupt that, particularly towards the end of the decade.

1189
01:07:23,400 --> 01:07:26,440
Speaker 20: And what Patrick and his team have developed is really

1190
01:07:26,920 --> 01:07:29,240
Speaker 20: it's not just a new technique that's cool because it

1191
01:07:29,360 --> 01:07:33,560
Speaker 20: uses light, but it really delivers demonstrable benefits to the

1192
01:07:33,760 --> 01:07:36,600
Speaker 20: energy needed for the compute and in a way that

1193
01:07:36,640 --> 01:07:39,120
Speaker 20: we think could change the game. So that's something we

1194
01:07:39,160 --> 01:07:42,000
Speaker 20: can underwrite as the fund and we think it could

1195
01:07:42,040 --> 01:07:45,200
Speaker 20: impact Microsoft, but also the industry at large.

1196
01:07:45,400 --> 01:07:48,880
Speaker 1: Okay, I'm interested in Patrick on the next set of

1197
01:07:48,960 --> 01:07:51,120
Speaker 1: data centers are meant to be being built in space

1198
01:07:51,240 --> 01:07:51,920
Speaker 1: if you're listening to.

1199
01:07:51,840 --> 01:07:53,400
Speaker 10: Elo mask over at Devils today.

1200
01:07:53,720 --> 01:07:55,640
Speaker 1: I'm interested as to whether that is something that you

1201
01:07:55,920 --> 01:07:59,200
Speaker 1: think is applicable to your technology and how you think

1202
01:07:59,200 --> 01:08:00,920
Speaker 1: they're going to beating what are quite a lot of

1203
01:08:00,920 --> 01:08:04,560
Speaker 1: competitors out there. There's Light Matter, IA Labs, Runovs for example.

1204
01:08:05,640 --> 01:08:06,160
Speaker 4: Yeah.

1205
01:08:06,200 --> 01:08:06,800
Speaker 5: Absolutely.

1206
01:08:06,960 --> 01:08:09,280
Speaker 19: I think the thing is wherever you go, whether it's

1207
01:08:09,320 --> 01:08:14,280
Speaker 19: in space or it's on Earth, AI is fundamentally hardware limited,

1208
01:08:14,440 --> 01:08:16,960
Speaker 19: and the hardware is fundamentally power limited, right, And the

1209
01:08:17,000 --> 01:08:19,240
Speaker 19: move to space is an attempt to try to solve

1210
01:08:19,280 --> 01:08:20,320
Speaker 19: the power consumption part.

1211
01:08:20,240 --> 01:08:20,960
Speaker 5: Of the problem.

1212
01:08:21,320 --> 01:08:24,120
Speaker 19: But wherever you go, even in space, power is still

1213
01:08:24,160 --> 01:08:26,840
Speaker 19: going to be limited, and we're solving that problem at

1214
01:08:26,840 --> 01:08:28,639
Speaker 19: the fundamental physics level.

1215
01:08:29,640 --> 01:08:35,080
Speaker 1: Are you, Michael, seeing the adoption by well those out

1216
01:08:35,120 --> 01:08:37,559
Speaker 1: there at the moment building the data centers for such

1217
01:08:37,720 --> 01:08:41,479
Speaker 1: new interesting technology, because as you say, this could just

1218
01:08:41,520 --> 01:08:44,280
Speaker 1: be replacing dropped in instead of a GPU. How you

1219
01:08:44,360 --> 01:08:46,840
Speaker 1: seeing that revenue process as you back in with this

1220
01:08:46,920 --> 01:08:48,719
Speaker 1: sort of series A funding.

1221
01:08:49,960 --> 01:08:52,800
Speaker 20: Well, in the last couple of weeks, the last couple

1222
01:08:52,840 --> 01:08:56,720
Speaker 20: of months actually, we've seen a completed total breakthrough and

1223
01:08:56,920 --> 01:09:00,320
Speaker 20: the acceptance by the leaders in the end Stry the

1224
01:09:00,360 --> 01:09:05,160
Speaker 20: chip industry to use new hardware to address different parts

1225
01:09:05,160 --> 01:09:08,160
Speaker 20: of the inference workload. And you know, that's the last

1226
01:09:08,160 --> 01:09:13,080
Speaker 20: couple of large licensing and hiring deals that we've seen,

1227
01:09:13,600 --> 01:09:15,640
Speaker 20: and I believe that's the beginning. That's that's kind of

1228
01:09:15,640 --> 01:09:18,639
Speaker 20: like it's like breaking the sound barrier. Need you need

1229
01:09:18,680 --> 01:09:21,800
Speaker 20: those steps to happen on the part of obviously the

1230
01:09:22,200 --> 01:09:25,760
Speaker 20: leaders to pave the way for even more disruptive technology

1231
01:09:25,800 --> 01:09:27,240
Speaker 20: like what Neurofas is developing.

1232
01:09:27,400 --> 01:09:31,400
Speaker 8: You know, this is an industry that is still dominated

1233
01:09:31,439 --> 01:09:34,640
Speaker 8: by the GPU in video, right, but with the specialist

1234
01:09:34,760 --> 01:09:38,759
Speaker 8: inference platforms. You know, the argument that in Vidia makes

1235
01:09:38,840 --> 01:09:42,200
Speaker 8: is that we give five year visibility on our product

1236
01:09:42,280 --> 01:09:45,840
Speaker 8: roadmap and that's why each generation of Silicon that comes out,

1237
01:09:45,880 --> 01:09:48,639
Speaker 8: you just drop it in. How is this more than

1238
01:09:48,680 --> 01:09:50,960
Speaker 8: a lab experiment right now with neurofos and you can

1239
01:09:50,960 --> 01:09:53,559
Speaker 8: convince that that data center that's not yet planned for,

1240
01:09:53,720 --> 01:09:56,400
Speaker 8: let alone build that that's the best viable option.

1241
01:09:56,680 --> 01:09:56,880
Speaker 5: Right.

1242
01:09:57,880 --> 01:10:00,639
Speaker 19: The key is that right now we already have silicon,

1243
01:10:00,800 --> 01:10:02,160
Speaker 19: We have verified solution reel.

1244
01:10:02,640 --> 01:10:03,160
Speaker 5: It is real.

1245
01:10:03,160 --> 01:10:06,000
Speaker 19: We have taped out these chips, we've derisked the fundamental physics.

1246
01:10:06,360 --> 01:10:08,520
Speaker 5: So from here they're Unlike quantum.

1247
01:10:08,280 --> 01:10:10,519
Speaker 19: Computing, where you still need some more physics miracles to

1248
01:10:10,520 --> 01:10:13,080
Speaker 19: make it happen. There are no more physics miracles in

1249
01:10:13,120 --> 01:10:16,120
Speaker 19: our roadmap from here. It is hard engineering, but it

1250
01:10:16,200 --> 01:10:18,360
Speaker 19: is just engineering to get to market. And so we

1251
01:10:18,400 --> 01:10:21,559
Speaker 19: can build a timeline and an engineering schedule that is

1252
01:10:21,640 --> 01:10:23,479
Speaker 19: tractable and actually can deliver on time.

1253
01:10:23,560 --> 01:10:25,880
Speaker 8: You know, I'm just trying to understand how difficult this

1254
01:10:25,960 --> 01:10:28,519
Speaker 8: is going to be. Michael Sarah Brass is doing interesting

1255
01:10:28,640 --> 01:10:32,920
Speaker 8: things different technology Grok. You know, when Nvidia took Grok,

1256
01:10:32,920 --> 01:10:34,320
Speaker 8: they were like, well, they didn't have a place in

1257
01:10:34,360 --> 01:10:37,160
Speaker 8: the world. You seem to think that, actually, the underlying

1258
01:10:37,240 --> 01:10:39,160
Speaker 8: technology g OPU does have a.

1259
01:10:39,080 --> 01:10:41,599
Speaker 9: Place in the world. What evidence would you provide for that.

1260
01:10:42,400 --> 01:10:46,240
Speaker 20: My background is from the semiconductor industry. I got to

1261
01:10:46,240 --> 01:10:48,439
Speaker 20: say I wasn't sold until I visited the lab and

1262
01:10:49,880 --> 01:10:53,320
Speaker 20: Patrick and their team open Kimono showed me the o selloscopes,

1263
01:10:53,360 --> 01:10:56,360
Speaker 20: showed me the test beds. This is something that can

1264
01:10:56,400 --> 01:10:58,560
Speaker 20: not only work on its own, but it could be

1265
01:10:58,600 --> 01:11:01,240
Speaker 20: integrated with other conventional products that are in the server

1266
01:11:01,800 --> 01:11:05,479
Speaker 20: bill of materials. And again that's the piece I can underwrite.

1267
01:11:05,520 --> 01:11:08,200
Speaker 20: We're not really here in this case to look to

1268
01:11:08,240 --> 01:11:13,320
Speaker 20: invest in science. Although I'm a scientist, I at least

1269
01:11:13,360 --> 01:11:16,120
Speaker 20: think we should stand behind the technologies that could change

1270
01:11:16,120 --> 01:11:18,480
Speaker 20: the game for the energy needed for inference compute.

1271
01:11:18,680 --> 01:11:23,880
Speaker 1: Why underwrite Eurofos versus as I said, Li matter I Labs.

1272
01:11:26,120 --> 01:11:28,760
Speaker 20: I don't want to comment on the other companies other

1273
01:11:28,800 --> 01:11:31,600
Speaker 20: than I've known them and I looked at this. I

1274
01:11:31,640 --> 01:11:35,160
Speaker 20: looked at optical compute very seriously five years ago or

1275
01:11:35,160 --> 01:11:38,559
Speaker 20: so for my prior fund. In fact, I met Patrick

1276
01:11:38,600 --> 01:11:41,280
Speaker 20: at that time, and the concept for neurofoss was a

1277
01:11:41,320 --> 01:11:44,880
Speaker 20: little bit early. But I think the market conditions that

1278
01:11:44,920 --> 01:11:49,120
Speaker 20: demand the need for new approaches, combined with, like I said,

1279
01:11:49,160 --> 01:11:52,960
Speaker 20: the signals of leaders to be willing to integrate and

1280
01:11:53,080 --> 01:11:57,200
Speaker 20: use this technology in their platforms that are already commercially successful.

1281
01:11:57,720 --> 01:12:00,880
Speaker 20: This is a moving train toward heteroch unius compute and

1282
01:12:00,920 --> 01:12:04,920
Speaker 20: true disruptive technologies making it to market. What neuropos has

1283
01:12:05,000 --> 01:12:09,280
Speaker 20: that again helped us move forward is something I could

1284
01:12:09,280 --> 01:12:12,280
Speaker 20: see with my eyes that shows that it could work. Now,

1285
01:12:12,280 --> 01:12:14,360
Speaker 20: I'm going to still put the pressure on Patrick to

1286
01:12:14,400 --> 01:12:17,800
Speaker 20: deliver the product on time, which is definitely you know,

1287
01:12:17,840 --> 01:12:19,040
Speaker 20: the job of an entrepreneur.

1288
01:12:19,720 --> 01:12:22,000
Speaker 4: But to his point, it's not a science.

1289
01:12:21,720 --> 01:12:25,240
Speaker 20: Risk question as much anymore as engineering and capital. So

1290
01:12:26,040 --> 01:12:28,160
Speaker 20: once again that's where we can bring.

1291
01:12:27,960 --> 01:12:29,920
Speaker 1: Our fund in and boy is there a need for

1292
01:12:29,960 --> 01:12:32,080
Speaker 1: an unlock on the energy side. Patrick Byne, we thank

1293
01:12:32,120 --> 01:12:34,719
Speaker 1: you so much, CEO of Neurofos and Michael Stewart managing

1294
01:12:34,720 --> 01:12:37,320
Speaker 1: partner an M twelve. Great to have you both on

1295
01:12:37,320 --> 01:12:38,200
Speaker 1: on this funding round.

1296
01:12:40,520 --> 01:12:43,360
Speaker 8: Intel's down half percentage point, but in reality, Carriacs just

1297
01:12:43,400 --> 01:12:45,800
Speaker 8: treading water head of earnings after the bel it's up

1298
01:12:45,840 --> 01:12:49,479
Speaker 8: fifteen percent in a short US week because of the holiday,

1299
01:12:49,680 --> 01:12:52,160
Speaker 8: and it's up like forty six percent year to day.

1300
01:12:52,479 --> 01:12:55,000
Speaker 8: And whatever it tells us about AI, the reality is

1301
01:12:55,080 --> 01:12:58,320
Speaker 8: right now it's bread and butter business. CPUs is in

1302
01:12:58,360 --> 01:13:00,120
Speaker 8: demand and that's really helping it.

1303
01:13:00,640 --> 01:13:01,920
Speaker 10: And the PC side of the business.

1304
01:13:02,040 --> 01:13:04,439
Speaker 1: Many feeling that that's been a growth trajectory for them

1305
01:13:04,479 --> 01:13:07,559
Speaker 1: once again, and we had, of course the discussion around Panther.

1306
01:13:07,400 --> 01:13:09,000
Speaker 10: Lake and what they've been doing in terms of innovation.

1307
01:13:09,080 --> 01:13:10,120
Speaker 10: The key question is going to.

1308
01:13:10,120 --> 01:13:13,479
Speaker 1: Be foundry where is that actually going in terms of

1309
01:13:13,520 --> 01:13:17,080
Speaker 1: clear direction. Revenues are likely to fall for this fiscal

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Speaker 1: quarter that they're reporting on it by six percent. Is

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Speaker 1: only growth come the second half of twenty twenty six, right, Yeah.

1312
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Speaker 8: And probably some updates on lit Bu Tan the CEO,

1313
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Speaker 8: and like what's his relationship like with the president one

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Speaker 8: of his shareholders now the United l States of America.

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Speaker 9: All right, and these are all good.

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Speaker 8: Copies of conversation, but we have had a hell of

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Speaker 8: a run up before the earnings actually hit.

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Speaker 1: Yeah, so maybe a bit of digestion just before they

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Speaker 1: come out. But digest more of this edition of Bloomberg Tech.

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Speaker 10: It's over for now, but end the podcast.

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Speaker 9: Yeah, check out the pod.

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Speaker 8: Astonishing episode to be frank, I mean, lots of recap.

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Speaker 9: You know where to find it.

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Speaker 8: Iheartspotify and on Apple and all all the bloombo platforms.

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Speaker 9: This is Bloomberg Tech.