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

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

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Speaker 1: York and Eva Low in San Francisco.

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Speaker 2: This is Bloomberg Tech coming up. Warner Brothers reopens negotiations

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Speaker 2: with Paramount Skuidance after it proposed or hinted at raising

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Speaker 2: its bid and sweetening other terms of its offer plus

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Speaker 2: renewed selling in several tech giants are weighing on stocks

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Speaker 2: with lingering anxiety over the outlook for AI, and Thrive

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Speaker 2: Capital raises more than ten billion dollars in its largest

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Speaker 2: fund ever, giving the firm an expanded war chest to

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Speaker 2: invest in AI. Welcome to Bloomberg Tech, and this is

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Speaker 2: what markets look like right now. We've carried over the

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Speaker 2: holiday weekend in the US to the same anxiety and

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Speaker 2: we're going to talk later in the program about the

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Speaker 2: contradiction right now hard of the AI trade and as

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Speaker 2: that one hundred off five percentage point chips kind of

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Speaker 2: dragging us down mag seven Bitcoin at sixty seven thousand

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Speaker 2: US dollars per token. Of course, it continues to trade

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Speaker 2: twenty four to seven, but over the weekend, a kind

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Speaker 2: of three day period there was a lot of geopolitical

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Speaker 2: tension driving it. Our top story is Warner Brothers Discovery

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Speaker 2: reopening talks with paramount S Guidars. Netflix has issued them

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Speaker 2: a waiver they can do so. It's a seven day

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Speaker 2: waiver through the February twenty third, by which point they

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Speaker 2: either need to give a.

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Speaker 3: Sweetened, improved bid or something else needs to happen. Let's

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Speaker 3: get the details.

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Speaker 2: Bloombose Lucas share leads our screen time team and coverage

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Speaker 2: of media and entertainment. This is actually a little bit

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Speaker 2: more difficult to understand that then simply negotiations reopening. Talk

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Speaker 2: us through the deadlines, the timeline and what's new Lucas well.

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Speaker 4: The news is obviously that Warner Brothers decided to talk

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Speaker 4: to Paramount. They have not been speaking for a couple

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Speaker 4: of months. Paramount kicked off this wholesale process last year

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Speaker 4: when it kind of sent over an an uninvited to

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Speaker 4: offer basically for all of Warner Brothers Discovery. It then

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Speaker 4: spent a couple of months increasing its offer for every

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Speaker 4: few weeks.

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Speaker 5: Trying to win.

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Speaker 4: It lost the Netflix and Warner Brothers Discovery has spent

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Speaker 4: the last couple of months sort of trashing Paramount. Both

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Speaker 4: sides kind of waging war in public, if you will.

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Speaker 4: But Paramount has gradually increased more and more pressure, addressed

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Speaker 4: more of the board's concerns, and is now at a

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Speaker 4: point where I think Warner Brothers Discovery feels both out

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Speaker 4: of pressure from its shareholders and just because they're sort

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Speaker 4: of tired of this, that they want to engage with

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Speaker 4: Paramount for a week, see what happens, and if they

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Speaker 4: can reach a better deal then obviously you know that

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Speaker 4: the board is going to do its fiduciary.

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Speaker 2: Duty, and we had some reporting about this over the

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Speaker 2: weekend before the formal announcement this morning. Part of this

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Speaker 2: is one of Paramount's bankers signaling to the board that

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Speaker 2: there will be an improved offer, but that they haven't

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Speaker 2: yet made their best offer.

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Speaker 3: What do we know about that?

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Speaker 4: Well, Paramount has been saying for a couple of months

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Speaker 4: that its offer is not last and final, and Warner

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Speaker 4: Brothers Discovery shareholders have been waiting for Paramount to increase

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Speaker 4: the offer from the thirty dollars a share. To your point,

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Speaker 4: some a representative of Paramount's guide Ace had indicated to

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Speaker 4: someone on the board of Directors of Warner Brothers Discovery

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Speaker 4: that they would go up to thirty one dollars a share.

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Speaker 4: My suspicion is that thirty one dollars a share still

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Speaker 4: won't cut it. So the question is Paramount going to

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Speaker 4: go to thirty two, thirty three, thirty four, thirty five,

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Speaker 4: and at what point is that beyond what Netflix is

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Speaker 4: willing to match, because keep in mind that Netflix still

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Speaker 4: has a deal with Warner Brothers Discovery and has the

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Speaker 4: right to match any superior Paramount offer.

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Speaker 3: Netflix has come out with.

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Speaker 2: I think we're talking about this offline, A strong statement,

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Speaker 2: a lengthy statement, just summarize what Netflix's position is here

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Speaker 2: and where they fit into the idea that negotiations now

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Speaker 2: are open for a window of time between Warner Brothers

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Speaker 2: Discovery and Paramount's guidance.

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Speaker 4: Well, some of those sort of public hostilities or disagreements

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Speaker 4: that I referred to earlier, I think, or what Netflix

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Speaker 4: is really seeking to attack with it state.

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Speaker 3: You know, they are getting very tired.

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Speaker 6: Of Paramount saying that Paramount.

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Speaker 4: Has a clearer path to regulatory approval and offers a

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Speaker 4: superior deal. And so Netflix goes through all the reasons

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Speaker 4: why regulators might be concerned about a Paramount deal including

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Speaker 4: some of their international financing and the concentration owning two

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Speaker 4: different movie studios. And that is also a jumping off

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Speaker 4: point for Netflix to argue that the Paramount deal would

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Speaker 4: be worse for Hollywood because Paramount would be a heavily

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Speaker 4: indebted company that would have to cut billions of dollars

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Speaker 4: in costs, whereas Netflix is buying a studio that it

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Speaker 4: doesn't have in house, and so it would preserve most

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Speaker 4: of those jobs.

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Speaker 2: We're just showing the bi Bloomberg Intelligence react, by the way,

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Speaker 2: which is pretty punchy. Netflix should walk away as Warner

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Speaker 2: m and A drama heats up. Maybe we'll get to

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Speaker 2: Githa later in the week. Bloom most Lucas, sure you've

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Speaker 2: led the way on the reporting on this one.

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Speaker 3: Thank you so much. Let's go back to markets.

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Speaker 2: Jitters around the software sector are sending investors in search

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Speaker 2: of safety. Some of the industry's biggest names have lost

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Speaker 2: hundreds of billions of dollars in market value so far

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Speaker 2: this year to spending anxiety. Bank of America's latest fund

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Speaker 2: manager survey shows a record share of investors think companies

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Speaker 2: are overspending. This as the four largest US tech firms

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Speaker 2: project roughly six hundred and fifty billion in combined spending

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Speaker 2: this year. Let's get the latest with Ted Watson bed

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Speaker 2: managing partner. This is the heart of the AI trade

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Speaker 2: right now. The contradiction in AI either AI is going

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Speaker 2: to change the old economy in the new economy or

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Speaker 2: we are in an AI bubble and for lots of

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Speaker 2: people both can't be true at the same time kind

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Speaker 2: of reflected in the trading of recent days.

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Speaker 3: Where do you sit on that dead I.

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Speaker 7: Think if you if you look at the agentic acceleration,

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Speaker 7: this is something you can't ignore in relationship to traditional sets.

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Speaker 7: I mean, the problem with the reason why the IGV

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Speaker 7: is down over twenty two percent year.

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Speaker 6: Of to day.

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Speaker 7: Is people have a real worry on how to model

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Speaker 7: these traditional SaaS companies from a free cash flow perspective,

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Speaker 7: a multiple free cash.

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Speaker 6: And that's the big problem.

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Speaker 7: I think over the weekend two days ago when OpenAI

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Speaker 7: bought open claw, that just gave more credence to the

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Speaker 7: segentic explosion. If you look at some of the token

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Speaker 7: growth that you're seeing, and this is why the cloud

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Speaker 7: titans can't keep up with compute demand is some of

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Speaker 7: the token growth that you're seeing our triple digits month

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Speaker 7: over month. This is not sequential. This is not you

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Speaker 7: over year, this is month over month growth.

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Speaker 2: Can I just jump in there real quick? So I

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Speaker 2: didn't expect you to go to open ai, open claw.

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Speaker 2: That blew up right over the weekend on social media.

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Speaker 2: And what I'm trying to do is understand the story

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Speaker 2: of how public market investors are treating this versus what

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Speaker 2: we see in private markets that clearly is a consolidation

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Speaker 2: of different platforms, right is try and unpick that for me?

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Speaker 7: I think it's it's really a debate between the old

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Speaker 7: and the new. And I think when you when you

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Speaker 7: can't model the old going back to that SaaS assumption

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Speaker 7: on free cash flow multiples and you're looking at this

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Speaker 7: acceleration on a gentic people just are getting out of

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Speaker 7: the way, to be quite honest with you, and they're

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Speaker 7: going to six other sectors that are more infrastructure related.

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Speaker 7: And the feeling is that some of the traditional SaaS

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Speaker 7: companies will have problems going from a traditional SaaS model

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Speaker 7: to a consumption model, which is.

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Speaker 6: All the agent base.

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Speaker 7: And it's a mess. It's an absolute mess. If you're

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Speaker 7: a software investor trying to model these.

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Speaker 2: Companies ted with respects, I don't I don't think you

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Speaker 2: really answer my question, which is, you know, the contradiction

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Speaker 2: of the old and new economy software more recently being impacted.

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Speaker 2: And then are we or are we not in an

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Speaker 2: AI bubble? You mentioned cash flows. One of the introsting

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Speaker 2: pieces of math that people are doing is the capital

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Speaker 2: expenditures commitment of the hyperscalers and its impact on cash

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Speaker 2: flow or proportion of cash flow. Basically cash flow is

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Speaker 2: getting wiped out. How do you feel about that?

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Speaker 7: I think it's a problem X of Google and Meta

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Speaker 7: which have their supporting businesses on the advertising that can

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Speaker 7: actually make up that free cash flow where I get

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Speaker 7: pushbacks names like Amazon and even Microsoft to some degree,

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Speaker 7: to a more limited degree, but if you look at Amazon,

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Speaker 7: I mean they essentially had to lay off a very

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Speaker 7: large component of their white collar employment based to maintain

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Speaker 7: even getting to neutral free cash flows.

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Speaker 6: So it is an issue.

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Speaker 7: One of the things that we are not talking about

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Speaker 7: is memory. And when you have this token, I would

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Speaker 7: say acceleration and you have inference also expanding. We have

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Speaker 7: a huge memory problem and I would almost put it

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Speaker 7: at a crisis level where you're not going to have

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Speaker 7: enough memory to support this compute over the next two years.

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Speaker 6: That's a real issue out there.

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Speaker 2: Next week you can video Ports reports its earnings and

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Speaker 2: it's the biggest beneficiary of the capsule expendensis numbers we

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Speaker 2: talked about. To this point, it has shown massive real

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Speaker 2: top line growth. What would it need to show evidence

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Speaker 2: to carry the rest of the market with it next

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Speaker 2: Wednesday evening.

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Speaker 7: I think number one, they have to they have to

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Speaker 7: assure investors that they don't have a memory problem, which

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Speaker 7: they don't. I mean, Jensen was so far ahead of

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Speaker 7: this memory issue by locking up supply.

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Speaker 6: That's number one.

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Speaker 7: Number two is some of the blackwall numbers as well

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Speaker 7: as transitioning.

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Speaker 6: The timing of Ruben is also very very important.

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Speaker 7: This is a real change an infrastructure on Reuben, and

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Speaker 7: I think anything that they I can assure investors that's

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Speaker 7: on track, and the adoption of Ruben from a system

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Speaker 7: perspective is now cannibalizing any of their business as it

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Speaker 7: relates to for example, Google's TPUs or infant soldiers.

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Speaker 6: They've got to play in both realms.

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Speaker 2: Ted Mortenson of BED, I think you've set us up

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Speaker 2: for a number of weeks to come, thank you very much.

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Speaker 3: Indeed they're coming up.

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Speaker 2: Fords charges ahead with a more affordable next gen EV

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Speaker 2: shares a little softer, but came back after headlines hit

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Speaker 2: We're gonna go under the hood next Sploomberg Tech. Ford

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Speaker 2: may have taken a nineteen point five billion dollar hit

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Speaker 2: to overhaul its EV business last year, but the US

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Speaker 2: car maker is out to prove that it hasn't retreated

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Speaker 2: altogether from electric vehicles. For reveal details of how it's

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Speaker 2: engineering a next gen EV platform to go further on

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Speaker 2: a single charge and still start at thirty thousand US dollies.

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Speaker 3: To do this, the.

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Speaker 2: Company's head of EV's Doug Field, told Bloomberg it had

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Speaker 2: to start with a clean sheet for its organization and

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Speaker 2: design process. Let's get more with bloombergs Keith Norton, who

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Speaker 2: has covered this company inside and out since nineteen eighty five.

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Speaker 2: And it's important to be specific here, right. This was

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Speaker 2: an engineering exercise, the Universal EV. What did they actually

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Speaker 2: do to engineer out cost and stay in the game.

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Speaker 8: Well, as you said, they did it far from Detroit.

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Speaker 8: This was set up in California. It was led by

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Speaker 8: Alan Clark, who's a former Tesla engineer, and they've just

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Speaker 8: they sweat the details. It's like improvement by a thousand cuts.

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Speaker 8: And they've managed to shrink the size of the battery

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Speaker 8: on the CV. The battery is the most expensive component

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Speaker 8: of an electric vehicle, while at the same time extending

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Speaker 8: the range by about fifty miles. That's just one of

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Speaker 8: many engineering gains they made, which is the reason they

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Speaker 8: can field this vehicle at thirty thousand dollars as a

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Speaker 8: starting price, which is twenty thousand dollars below the average

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Speaker 8: price of a new Current America today.

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Speaker 2: We spent about forty five minutes on the phone with

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Speaker 2: Doug Field, which was really interesting exercise.

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Speaker 3: There is a pathway here, right.

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Speaker 2: It starts twenty twenty seven with a pickup truck and

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Speaker 2: they go basically from skunk works to reintegrating back into

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Speaker 2: the might of Ford with distant maybe distant Keith ambitions

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Speaker 2: on L three systems. What's the sort of timeline from

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Speaker 2: here of this UEV platform please.

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Speaker 8: Yeah, not exactly that far distant. They're going to come

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Speaker 8: with the Eyes off the Road Level three semi autonomy

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Speaker 8: in twenty twenty eight, so a year after they launched

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Speaker 8: this vehicle, they'll offer buyers the option of getting this

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Speaker 8: semi autonomous size off the road, hands off the wheel feature.

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Speaker 8: So their point is they can put a feature like

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Speaker 8: that on an inexpensive car in the thirty thousands, which

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Speaker 8: is unusual. Normally those sorts of bands technology features show

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Speaker 8: up first on very high end luxury cars closer to

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Speaker 8: six figures.

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Speaker 6: Right.

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Speaker 2: The approach from Ford thus far has been to electrify

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Speaker 2: the big winners, thinking mocky, thinking f one fifty lightning

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Speaker 2: that that's gone now, right, and the focus is that's

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Speaker 2: gone right, and the focus is China. So put that

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Speaker 2: context out there for us. Why this approach ground up,

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Speaker 2: starting from fresh is the right way to counter that?

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Speaker 2: The cost basis of a Chinese EV company.

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Speaker 8: Right, So the advantage the Chinese have is in price.

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Speaker 8: I mean, there's a Chinese EV in China for ten

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Speaker 8: thousand dollars. Not likely that would come here. But they

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Speaker 8: have a big price advantage even if you make a

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Speaker 8: car ready for the US market. But they also have

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Speaker 8: a technology advantage. They have, you know, cars that are

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Speaker 8: essentially an extension of your of your smartphone smart cars,

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Speaker 8: So you need to compete against them both on price

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Speaker 8: and technology. That's what Ford says it's doing with this

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Speaker 8: because of the approach they've taken. It's not just an

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Speaker 8: affordable vehicle, they say, but it's a desirable vehicle with

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Speaker 8: lots of good features.

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Speaker 2: Bloombers Keith Norton, who again has led the charge on

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Speaker 2: covering this industry and this company for a long time,

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Speaker 2: appreciate it.

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Speaker 3: Let's talk about Apple.

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Speaker 2: It's touting an in person experience event in New York, Shanghai,

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Speaker 2: and London for a March fourth product launch, suggesting a

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Speaker 2: lower key showcase than often held at its Cupatino campus.

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Speaker 2: Let's get out to Bloomberg's Consumer Tech and Apple Managing

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Speaker 2: editor Mark Gumman. There's the event and how they'll do

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Speaker 2: it right. Different to the kind of keynote style format

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Speaker 2: in Coupatino, but it's harder the products. And I think

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Speaker 2: you were on very recently kind of telling us what

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Speaker 2: we should expect from this.

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Speaker 9: Yeah, there's a lot in the pipeline for the first

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Speaker 9: half of this year. I don't think that everything is

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Speaker 9: going to show up at this event. There's just too

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Speaker 9: much stuff for you to have in one showcase. But

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Speaker 9: if you think about why would you need an event.

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Speaker 9: Why would you need an in person experience in three

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Speaker 9: different places London, Shanghai, New York. Right these are as

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Speaker 9: big of multi metropolitan areas in the world as you

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Speaker 9: can get. It means they're launching something pretty significant. So

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Speaker 9: my eyes are on this new low cost MacBook. It'll

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Speaker 9: be in the seven hundred to nine hundred dollars range.

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Speaker 9: It will be their first MacBook powered by an iPhone chip.

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Speaker 9: It'll be slightly smaller than the MacBook Air, but the

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Speaker 9: price point is a really big deal. This has the

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Speaker 9: potential to really overshadow Chromebooks and some of the PCs

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Speaker 9: we're seeing out of the Windows market right now.

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Speaker 3: So this is a really big deal.

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Speaker 9: The other new things that are in the pipeline for

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Speaker 9: the first half of this year new MacBook pros, new

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Speaker 9: MacBook Airs, the iPhone seventeen e, as well as new

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Speaker 9: iPad entry level and iPad Air models. I would think

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Speaker 9: that we would at least get the seventeen e by

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Speaker 9: this event at the latest.

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Speaker 2: I want to say something up for our audience because

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Speaker 2: you put me on the spot the other day. I'm

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Speaker 2: running a MacBook Pro with M four that's my work

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Speaker 2: one at home I've got a twenty twenty macair running

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Speaker 2: in one, and you quite rightly pointed out I should

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Speaker 2: upgrade when they hold these events. How quickly do the

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Speaker 2: new products hit the shelves quickly?

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Speaker 9: When it's a spec bump, they're rolling out within a

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Speaker 9: few days. The longest delay is usually about a week,

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Speaker 9: two weeks maybe maximum, but it's usually pretty quick.

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Speaker 2: Flamous Mark German, who's been on top of the reporting

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Speaker 2: on this well in advance, thank you very much. Coming up,

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Speaker 2: we're going to discuss just how big a market the

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Speaker 2: physical AI space can be.

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Speaker 3: That's where Na over from Berkley's. That's next. This has

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Speaker 3: been bog.

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Speaker 2: Tech, a report from Berkley's projects that by twenty thirty five,

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Speaker 2: physical AI could be a trillion dollar market thanks to

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Speaker 2: advances in brains, brawn and batteries. So where are the

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Speaker 2: investment opportunities along that value chains? I need to tuttle

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Speaker 2: over Barkley's head of thematic if I see see research,

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Speaker 2: and the author of that report joins us now in

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Speaker 2: many ways, so I need to say it's an update.

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Speaker 2: You know you're keeping the research alive. So we have

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Speaker 2: the one trillion addressable market twenty thirty five. But digging

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Speaker 2: down into the notes, actually, autonomous driving is a really

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Speaker 2: big part of this for you.

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Speaker 10: That's right.

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Speaker 11: Our latest research shows that physical AI could really become

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Speaker 11: a trillion dollar market by twenty thirty five. That's ten

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Speaker 11: times higher than where the market is currently valued at.

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Speaker 11: And that trillion dollar estimate spans four key robotics categories,

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Speaker 11: autonomous vehicles, humanoid robots, advanced automation, and drums.

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Speaker 10: And Look, while I have.

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Speaker 11: Really strong conviction that the late twenty twenties and the

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Speaker 11: early twenty thirties will be the decade of the robot

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Speaker 11: I also think that growth and adoption.

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Speaker 10: Will likely come in stages rather than all at once.

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Speaker 11: I can see how autonomous vikos could lead the trend

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Speaker 11: and said the stage, And in fact, nearly half of

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Speaker 11: that estimate of the market growth comes from autonomous vehicles,

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Speaker 11: or in dollar times, that's about five hundred billion dollars

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Speaker 11: by twenty thirty five. I think, also intuitively this makes

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Speaker 11: a lot of sense because autonomous vehicles clearly have a

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Speaker 11: head start.

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Speaker 10: The technology has been around for nearly a decade.

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Speaker 11: Now, the production process is there, it can leverage an

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Speaker 11: existing automotive supply chain, and I think more importantly, the

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Speaker 11: AI models needed for autonomous vehicles can work with a

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Speaker 11: much bigger real world driving data set that's collected from

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Speaker 11: millions of eCos out there, and that's a very different

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Speaker 11: story if you're compared to where humanoid robots are at

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Speaker 11: the moment.

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Speaker 2: So if you follow the arc of what happened with

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Speaker 2: autonomous driving, what needs to happen for humanoid robots for

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Speaker 2: them to make a meaningful contribution to your one trillion

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Speaker 2: dollar forecast for addressable market by twenty thirty five.

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Speaker 11: I think the number one challenge that humanoid it's a

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Speaker 11: phase right.

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Speaker 10: Now is the lack of physical AI data.

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Speaker 11: And that's because when you think about humanoid robots, they

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Speaker 11: really bridge the gap between the cognitive.

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Speaker 10: The digital, and the physical world.

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Speaker 11: And in the physical world, the laws of mechanics and

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Speaker 11: physics apply. A humanoid robot needs precise instructions if it's

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Speaker 11: going to function and perform properly in an unstructured world

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Speaker 11: that is made for humans. Take a simple example such

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Speaker 11: as lifting a box. This is a very simple task

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Speaker 11: for us humans. We have inbuilt dexterity, we have inbuilt intelligence.

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Speaker 11: We know exactly what we have to do. But a

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Speaker 11: humanoid robot needs precise instructions. It needs to know exactly

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Speaker 11: how much force to apply, where to apply that force,

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Speaker 11: and that simple example can get really tricky if something changes,

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Speaker 11: For example, the box is actually heavier than expected, if

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Speaker 11: the surface is slippery, that means that the robot needs

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Speaker 11: a new set of instructions.

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Speaker 10: And the challenge is that there is no dictionary out there.

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Speaker 10: There is no single database that can.

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Speaker 11: Tell us, look for a fifty pounds box, you need

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Speaker 11: this amount of energy, this amount of force. All that

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Speaker 11: needs to be built from scratch in order for the

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Speaker 11: technology to scale and to become more more useful in

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Speaker 11: the real world.

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Speaker 2: In both cases autonomous driving and humanoid robotics, and actually

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Speaker 2: you could extend that to autonomous drone technology as well.

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Speaker 2: There is a great emphasis on China, how far aheaded

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Speaker 2: is in commercializing the technology, but also supply chain dependency.

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Speaker 2: A lot of that supply chain has historically originated from China.

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Speaker 3: How does that show up in your research?

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Speaker 10: So it's clear that China leads.

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Speaker 11: I think it deploys robots on a completely different scale.

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Speaker 11: For example, in twenty twenty five, we estimate that nearly

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Speaker 11: fifteen thousand humanoid robots were deployed worldwide.

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Speaker 10: Eighty five percent of those were installed in China. You

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Speaker 10: get a similar story if you look at other types

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Speaker 10: of robotics technologies like industrial automation.

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Speaker 11: There we're talking about fifty to sixty percent of the

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Speaker 11: units are installed in China. If you compare these figures

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Speaker 11: to what's happening in the US, the numbers.

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Speaker 10: Look very different.

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Speaker 11: Low teams for humanoid robots and even single digits for

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Speaker 11: industrial for industrial.

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Speaker 10: Robots, so the scale is very different.

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Speaker 11: So China has the advantage in terms of technology, also

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Speaker 11: access to raw materials.

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Speaker 10: Take for example, critical minerals, rare earths.

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Speaker 11: You need a lot of those components to build some

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Speaker 11: of these very very specific physical components that go into

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Speaker 11: a robot. So there are different chunks of the supply

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Speaker 11: chain where China can really can really kick in. So

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Speaker 11: all that comes together. But having said that, it's the

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Speaker 11: early stages. I think we are just scratching the surface

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Speaker 11: in terms of what physical AI can do, and I

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Speaker 11: see lots of potential for that adoption to accelerate in

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Speaker 11: other parts of the world.

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Speaker 10: Starting with the US and even potentially in Europe.

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Speaker 3: In a couple of years signs so needs to thutter

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Speaker 3: over of barkleys.

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Speaker 2: It's great to have you back on Bloomberg Tech with

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Speaker 2: your updated research.

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Speaker 3: Thank you.

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Speaker 2: So news crossing the Bloomberg terminal, Palenteer says it has

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Speaker 2: moved its headquarters to Miami, Florida from Denver.

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Speaker 3: They made the announcement.

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Speaker 2: Via a pretty straightforward and simple post on x the

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Speaker 2: social platform. The shares kind of haven't really moved from

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Speaker 2: where they were trading anyway, but an interesting story will

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Speaker 2: continue to track now. Coming up on the show, bitcoin

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Speaker 2: having a tough time after the long weekend. We're going

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Speaker 2: to scuss what's ahead for cryptocurrencies. A lot of focus

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Speaker 2: on geopolitical risk right now.

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Speaker 3: And of course, while it was a US holiday.

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Speaker 2: On Monday, bitcoin trading twenty four to seven around the world.

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Speaker 3: Do you see since Friday? That's what it looked like.

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Speaker 2: Market's actually not as anxious as they were when we

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Speaker 2: woke up. It's halftime. This is Bloomberg Tech. Welcome back

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Speaker 2: to Bloomberg Tech if.

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Speaker 3: You're just joining us.

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Speaker 2: Volatility has gripped Wall Street, particularly when it comes to

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Speaker 2: conversation around the AI trade. Right now, then, as that

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Speaker 2: one hundred is actually just a little bit softer three

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Speaker 2: tenths of percent. The Philadelphia Semiconductor Index or SOCKS was

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Speaker 2: down two percent. We're now off by two tens of

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Speaker 2: one percent. Again, we're seeing volatility in video one of

446
00:23:09,040 --> 00:23:12,320
Speaker 2: those names participating in it. There are some news stories

447
00:23:12,359 --> 00:23:14,080
Speaker 2: that want to pick out while we get the opportunity.

448
00:23:14,119 --> 00:23:18,760
Speaker 2: Gemini Space Station. The cryptoic Stange, founded by the Vinkel

449
00:23:19,359 --> 00:23:24,160
Speaker 2: Twins and iPod a few months ago, is down fourteen

450
00:23:24,200 --> 00:23:26,800
Speaker 2: percent basically in the months that followed the IPO.

451
00:23:27,119 --> 00:23:28,800
Speaker 3: A lot of the C suite has left.

452
00:23:28,960 --> 00:23:32,040
Speaker 2: They confirmed this morning the CFO, chief legal officer, chief

453
00:23:32,040 --> 00:23:35,680
Speaker 2: operating officer all left. That's putting volatility in that name.

454
00:23:35,800 --> 00:23:40,719
Speaker 2: In the crypto adjacent space and generally speaking, cryptocurrencies are

455
00:23:40,720 --> 00:23:44,120
Speaker 2: struggling to find clear direction. After a weekend rally fizzled,

456
00:23:44,480 --> 00:23:48,040
Speaker 2: e raising a small bounce that briefly took Bitcoin close

457
00:23:48,080 --> 00:23:51,000
Speaker 2: to seventy one thousand US dollars per token on Saturday.

458
00:23:51,280 --> 00:23:53,840
Speaker 2: It has been a tough run for crypto, especially with

459
00:23:53,920 --> 00:23:57,960
Speaker 2: Bitcoin posting four straight weeks of losses. There is one

460
00:23:58,000 --> 00:24:00,040
Speaker 2: person who I rely on to help with this, and

461
00:24:00,119 --> 00:24:03,800
Speaker 2: that is Bloomberg's cross at reporter Isabelle Lee. So most

462
00:24:03,840 --> 00:24:07,000
Speaker 2: of America was on a holiday on Monday. In the

463
00:24:07,080 --> 00:24:10,120
Speaker 2: United States, Crypto is a twenty four to seven thing,

464
00:24:10,880 --> 00:24:13,320
Speaker 2: and it's a global thing. But it was interesting to

465
00:24:13,400 --> 00:24:16,040
Speaker 2: kind of track from Friday through to this morning where

466
00:24:16,240 --> 00:24:19,720
Speaker 2: you net out sixty seven thousand US dollars. Partoken and

467
00:24:19,800 --> 00:24:22,119
Speaker 2: the stories on the Bloomberg are about geopolitics.

468
00:24:22,640 --> 00:24:25,360
Speaker 12: Bitcoin never sleeps, but over the weekend and during holidays.

469
00:24:25,440 --> 00:24:28,760
Speaker 12: We must recognize that liquidity is thin. But to your point,

470
00:24:29,000 --> 00:24:31,040
Speaker 12: we've seen four s rate weeks of losses and there

471
00:24:31,080 --> 00:24:32,520
Speaker 12: are just a lot of things going on. We have

472
00:24:32,560 --> 00:24:35,600
Speaker 12: renewed geopolitical tensions when it comes to Iran. FED rate

473
00:24:35,640 --> 00:24:38,879
Speaker 12: cuts are back end focused, especially after last week's inflation report.

474
00:24:39,119 --> 00:24:41,560
Speaker 12: We also have AI concerns on my inbox, as I'm

475
00:24:41,560 --> 00:24:44,359
Speaker 12: sure yours is. It's just full of AI concerns about

476
00:24:44,400 --> 00:24:47,639
Speaker 12: whether this selloff we're seeing will spill over the tech sector.

477
00:24:47,720 --> 00:24:49,680
Speaker 12: So all of that is causing Bitcoin, which is now

478
00:24:49,720 --> 00:24:52,440
Speaker 12: really a risk asset, moving a lot in step with NESDAC.

479
00:24:52,680 --> 00:24:55,120
Speaker 12: It's really edging lowers, so that's what you're seeing. It's

480
00:24:55,119 --> 00:24:58,600
Speaker 12: interesting because we still have the original bitcoin proponents saying

481
00:24:58,600 --> 00:25:00,640
Speaker 12: that this is a haven. This is what you buy

482
00:25:00,640 --> 00:25:03,520
Speaker 12: and comes when it comes to when there's geopolitical tension,

483
00:25:03,720 --> 00:25:06,399
Speaker 12: inflation fears. But for now it's definitely behaving like a

484
00:25:06,440 --> 00:25:06,960
Speaker 12: risk acid.

485
00:25:07,640 --> 00:25:11,000
Speaker 2: Bloomberg's Isabelle Lee with the crypto summary, thank you very much.

486
00:25:11,280 --> 00:25:15,119
Speaker 2: Latest thirteen F filings from Soros Fund Management has revealed

487
00:25:15,119 --> 00:25:18,400
Speaker 2: that it's doubled its steak in Microsoft, jumping from about

488
00:25:18,400 --> 00:25:20,679
Speaker 2: one hundred and two thousand shares to two hundred and

489
00:25:20,680 --> 00:25:23,480
Speaker 2: sixty three thousand shares. Here with the latest of Bloomberg

490
00:25:23,520 --> 00:25:26,199
Speaker 2: Hedge Fun reporter Hemma Palmer, what do we need to

491
00:25:26,200 --> 00:25:27,160
Speaker 2: know here about Soros?

492
00:25:27,520 --> 00:25:30,200
Speaker 13: Right, so when we look at his move here doubling

493
00:25:30,200 --> 00:25:32,480
Speaker 13: his steak in Microsoft, this is a stock that, as

494
00:25:32,480 --> 00:25:34,640
Speaker 13: we now have seen with the beginning of the year,

495
00:25:34,640 --> 00:25:38,560
Speaker 13: has become incredibly volatile, down twenty three percent since the

496
00:25:38,680 --> 00:25:41,639
Speaker 13: end of the third quarter. So you know, these thirteen

497
00:25:41,720 --> 00:25:45,000
Speaker 13: f's today are actually quite insightful because we're seeing positioning

498
00:25:45,280 --> 00:25:48,040
Speaker 13: ahead of what's been a chaotic start to the year.

499
00:25:48,440 --> 00:25:51,119
Speaker 13: So as we can see who made the right best,

500
00:25:51,119 --> 00:25:54,200
Speaker 13: who is probably in pain, the stock's not doing too well.

501
00:25:54,720 --> 00:25:59,560
Speaker 13: Soros also added to Apple, Nvidia, and Amazon, and there's

502
00:25:59,600 --> 00:26:02,280
Speaker 13: been pain interesting board it has.

503
00:26:02,400 --> 00:26:05,240
Speaker 2: It's interesting the thirty and F exercise. Either you start

504
00:26:05,240 --> 00:26:07,480
Speaker 2: with the hedge fund or the fund, or if you're me,

505
00:26:07,560 --> 00:26:09,359
Speaker 2: you kind of look at the change of positions of

506
00:26:09,400 --> 00:26:09,919
Speaker 2: the names.

507
00:26:10,320 --> 00:26:13,760
Speaker 3: University of Texas came up. Why yeah.

508
00:26:13,800 --> 00:26:16,320
Speaker 13: So on the flip side, they actually trimmed their Microsoft

509
00:26:16,400 --> 00:26:20,399
Speaker 13: steak and their Amazon position. They ramped up their Apple holding,

510
00:26:20,440 --> 00:26:24,040
Speaker 13: which has been less painful for them as we look

511
00:26:24,080 --> 00:26:27,000
Speaker 13: at through the end of September. When we look at

512
00:26:27,000 --> 00:26:30,359
Speaker 13: these filings through till now, they do have a large

513
00:26:30,400 --> 00:26:33,880
Speaker 13: portfolio over three hundred positions, so we saw some good

514
00:26:33,920 --> 00:26:37,040
Speaker 13: rotation in that. But the interesting rove there was ramping

515
00:26:37,119 --> 00:26:39,000
Speaker 13: up Apple and also trimming.

516
00:26:38,720 --> 00:26:42,520
Speaker 2: Microsoft, Bloomberg, Semmapana across all the thirty and f's.

517
00:26:42,520 --> 00:26:44,240
Speaker 3: Thank you so much. All right, a lot more to

518
00:26:44,240 --> 00:26:44,840
Speaker 3: come on the show.

519
00:26:44,960 --> 00:26:49,000
Speaker 2: Startup Mesh is out to build the quote largest optical

520
00:26:49,040 --> 00:26:54,119
Speaker 2: manufacturing footprint outside of Asia, lasers, optics, everything AI. That

521
00:26:54,200 --> 00:27:09,119
Speaker 2: conversation's next with a funding raise. This is Bloomberg Tech, Elon, Musk,

522
00:27:09,240 --> 00:27:13,440
Speaker 2: SpaceX and Xai recently merged are competing in a secret

523
00:27:13,520 --> 00:27:18,919
Speaker 2: Pentagon contest to develop voice controlled autonomous drone swarming technology.

524
00:27:19,160 --> 00:27:22,359
Speaker 2: According to sources, it's a one hundred million dollar prize

525
00:27:22,480 --> 00:27:25,280
Speaker 2: that only a handful of companies were selecteds to take

526
00:27:25,320 --> 00:27:28,959
Speaker 2: part in. Here with the story, bloombergs Katrina Manson, this

527
00:27:29,200 --> 00:27:32,360
Speaker 2: was a fascinating read. It's a kind of new domain

528
00:27:32,520 --> 00:27:35,760
Speaker 2: for SPACEXXAI. It's a contest. What do we need to

529
00:27:35,800 --> 00:27:36,120
Speaker 2: know here?

530
00:27:37,280 --> 00:27:39,800
Speaker 14: This is really the frontier of the future of war.

531
00:27:39,880 --> 00:27:43,439
Speaker 14: This is everything that folks like Stop Killer Robots and

532
00:27:43,560 --> 00:27:46,680
Speaker 14: others have been warning about. This is the Pentagon trying

533
00:27:46,760 --> 00:27:50,920
Speaker 14: to experiment with completely new tech that has so far

534
00:27:51,080 --> 00:27:54,320
Speaker 14: been failing its experimental and this is a moment really

535
00:27:54,320 --> 00:27:57,440
Speaker 14: where the AI companies are coming to the fore quite unexpectedly.

536
00:27:57,840 --> 00:28:00,320
Speaker 14: Elon Musk is the very same person who's said that

537
00:28:00,560 --> 00:28:02,560
Speaker 14: he would have nothing to do with new tools for

538
00:28:02,640 --> 00:28:05,520
Speaker 14: killing back in twenty fifteen when he signed onto an

539
00:28:05,560 --> 00:28:10,879
Speaker 14: open letter from AI researchers and roboticists saying we do

540
00:28:10,920 --> 00:28:13,920
Speaker 14: not want autonomous weapons. And now this is the Appentagon

541
00:28:13,960 --> 00:28:16,880
Speaker 14: trying to create autonomous weapons. These are weapons that can

542
00:28:16,960 --> 00:28:21,480
Speaker 14: select and engage targets of their own accord. The contest

543
00:28:21,520 --> 00:28:24,040
Speaker 14: is not explicitly saying they will be doing that, but

544
00:28:24,080 --> 00:28:26,840
Speaker 14: they are saying that drones will be moving around and

545
00:28:26,880 --> 00:28:31,720
Speaker 14: taking commands from voice and turning those into digital instructions.

546
00:28:32,760 --> 00:28:35,840
Speaker 2: I don't know that the price money is necessarily that.

547
00:28:35,920 --> 00:28:39,440
Speaker 2: The main headline for SpaceX right. What you do really

548
00:28:39,480 --> 00:28:42,640
Speaker 2: well in your reporting is explain where the technology's at

549
00:28:42,880 --> 00:28:45,760
Speaker 2: and where you know where various institutions want it to

550
00:28:45,760 --> 00:28:48,920
Speaker 2: get to. So we have drones, but it's this swarming

551
00:28:49,160 --> 00:28:53,280
Speaker 2: idea in the I guess defense use case what needs

552
00:28:53,320 --> 00:28:54,040
Speaker 2: to be cracked.

553
00:28:54,520 --> 00:28:56,480
Speaker 14: I think there are four stages. First, as you say

554
00:28:56,480 --> 00:28:59,440
Speaker 14: there are drones. Everyone's become familiar with drones because of

555
00:28:59,480 --> 00:29:02,800
Speaker 14: the Russian invasion of Ukraine, and Elon Musk himself said

556
00:29:02,800 --> 00:29:05,760
Speaker 14: in twenty twenty four that if there is a major

557
00:29:05,800 --> 00:29:07,880
Speaker 14: power war, it's going to be a drone war. So

558
00:29:07,960 --> 00:29:10,000
Speaker 14: everyone is very focused on what that might look like.

559
00:29:10,120 --> 00:29:12,760
Speaker 14: In the case of a US traina contest over Taiwan,

560
00:29:13,440 --> 00:29:17,360
Speaker 14: people have flown multiple drones together. That's not the same

561
00:29:17,400 --> 00:29:19,520
Speaker 14: as a swarm. A swarm really is where the drones

562
00:29:19,600 --> 00:29:22,680
Speaker 14: talk to each other, they interact with each other, and

563
00:29:22,800 --> 00:29:26,680
Speaker 14: ultimately potentially carry a payload or a weapon and can

564
00:29:26,800 --> 00:29:30,560
Speaker 14: drop that weapon on a target. Weaving in ai to

565
00:29:30,680 --> 00:29:34,560
Speaker 14: do that for targeting, automatic targeting recognition, and in this

566
00:29:34,720 --> 00:29:38,200
Speaker 14: case to take a command from someone giving a voice

567
00:29:38,200 --> 00:29:41,120
Speaker 14: instruction and turn that into a movement or an action

568
00:29:41,840 --> 00:29:44,160
Speaker 14: is relatively uncharted territory.

569
00:29:45,040 --> 00:29:48,160
Speaker 2: I should say that SpaceX and XAI did not respond

570
00:29:48,280 --> 00:29:51,000
Speaker 2: to our request for comment, which is pretty normal procedure

571
00:29:51,040 --> 00:29:51,400
Speaker 2: for them.

572
00:29:51,920 --> 00:29:54,320
Speaker 3: What they are doing is hiring.

573
00:29:53,920 --> 00:29:57,400
Speaker 2: Some interesting roles bikostally, but you know in the classic

574
00:29:57,480 --> 00:29:59,800
Speaker 2: talent pools of Silicon Valley, what areas.

575
00:30:00,600 --> 00:30:02,560
Speaker 14: This is DC in the West Coast, and of course

576
00:30:02,560 --> 00:30:06,600
Speaker 14: SpaceX a long term defense contractor, but never an offensive

577
00:30:06,600 --> 00:30:09,600
Speaker 14: weapons nothing ever so explicit. And XAI, I mean, this

578
00:30:09,720 --> 00:30:12,280
Speaker 14: is grok, this is x We're all going to post

579
00:30:12,320 --> 00:30:15,840
Speaker 14: the story on afterwards. They are now hiring for people

580
00:30:15,960 --> 00:30:19,760
Speaker 14: with clearances and that's a real change. They're looking for

581
00:30:19,800 --> 00:30:23,400
Speaker 14: people with secret clearance and top secret clearance.

582
00:30:24,840 --> 00:30:28,160
Speaker 2: Bloomberg Katrina manson Top Reporting, Thank you very much. There

583
00:30:28,160 --> 00:30:30,120
Speaker 2: are so many other news headlines in the world of tech.

584
00:30:30,360 --> 00:30:33,320
Speaker 2: Time now for Talking Tech and first Start and Propics.

585
00:30:33,360 --> 00:30:36,600
Speaker 2: Talks to extend a contract with the Pentagon are being

586
00:30:36,640 --> 00:30:40,160
Speaker 2: held up over additional protections. The company wants to put

587
00:30:40,200 --> 00:30:43,280
Speaker 2: on its clawed tool and Propic wants to put guardrails

588
00:30:43,320 --> 00:30:46,040
Speaker 2: in place to stop Claude from being used for mass

589
00:30:46,080 --> 00:30:49,760
Speaker 2: surveillance of Americans, or to develop weapons that can be

590
00:30:49,760 --> 00:30:53,520
Speaker 2: deployed without a human involved. According to sources, Depentagon wants

591
00:30:53,520 --> 00:30:55,239
Speaker 2: to be able to use Claude as long as it's

592
00:30:55,320 --> 00:30:59,680
Speaker 2: deployment doesn't break the law. Plus five Capital has raised

593
00:30:59,680 --> 00:31:02,920
Speaker 2: more than ten billion dollars for its largest fund, Yet

594
00:31:02,960 --> 00:31:06,120
Speaker 2: the venture firm founded by Josh Kushner draw far more

595
00:31:06,160 --> 00:31:09,800
Speaker 2: demand than it could accept, turning away billions of dollars

596
00:31:10,000 --> 00:31:13,960
Speaker 2: from prospective investors. The interest underscores the success of several

597
00:31:14,240 --> 00:31:18,800
Speaker 2: of its portfolio companies, including open Ai, SpaceX, and Stripe,

598
00:31:18,880 --> 00:31:21,720
Speaker 2: and sticking with capital, the firm just back to startup

599
00:31:21,760 --> 00:31:25,960
Speaker 2: building optical transceivers that are crucial for data centers. The

600
00:31:26,000 --> 00:31:29,520
Speaker 2: startup is called Mesh Optical Technologies and was founded by

601
00:31:29,560 --> 00:31:32,640
Speaker 2: SpaceX alumni, and it's raised fifty million dollars led by

602
00:31:32,720 --> 00:31:36,880
Speaker 2: Thrive to scale manufacturing of the technology in the United States.

603
00:31:36,920 --> 00:31:40,880
Speaker 2: The company's co founder and CEO, Travis Preshiers, joins US,

604
00:31:40,920 --> 00:31:43,320
Speaker 2: Now this is such an interesting field.

605
00:31:43,640 --> 00:31:44,880
Speaker 3: It's one that Nvidia has.

606
00:31:44,800 --> 00:31:47,800
Speaker 2: Looked at the use of optic optics in GPU is

607
00:31:47,800 --> 00:31:48,840
Speaker 2: also OPU is.

608
00:31:48,800 --> 00:31:49,480
Speaker 3: Being looked at.

609
00:31:49,920 --> 00:31:53,280
Speaker 2: Let's start with what you're offering, the actual technology itself,

610
00:31:53,280 --> 00:31:54,520
Speaker 2: which we wrote about this morning.

611
00:31:55,480 --> 00:31:56,840
Speaker 5: Yeah, thanks for having me on the show.

612
00:31:56,880 --> 00:32:00,440
Speaker 15: And yeah, we're we just announced that our our company,

613
00:32:00,520 --> 00:32:03,920
Speaker 15: Mesh Optical, coming out of Stealth. Here we are standing

614
00:32:03,960 --> 00:32:07,400
Speaker 15: up high volume optical manufacturing of these optical interconnects that

615
00:32:07,440 --> 00:32:11,040
Speaker 15: are used for all GPU clusters. So anytime you hear

616
00:32:11,080 --> 00:32:13,840
Speaker 15: someone talking about a GPU cluster, there's four to five

617
00:32:13,920 --> 00:32:18,720
Speaker 15: of these optical transceivers for every one GPU. And so yeah,

618
00:32:18,760 --> 00:32:21,800
Speaker 15: we're excited to offer our first product as what we

619
00:32:21,840 --> 00:32:24,800
Speaker 15: call a linear pluggable optic and it's at like a

620
00:32:24,840 --> 00:32:28,719
Speaker 15: one point six terabit per second data rate, which is

621
00:32:28,760 --> 00:32:30,280
Speaker 15: like what the state of the art will be in

622
00:32:30,320 --> 00:32:32,800
Speaker 15: the coming years and all these GPU clusters.

623
00:32:33,720 --> 00:32:36,360
Speaker 2: Jere, you were at SpaceX for about five years. You're

624
00:32:36,400 --> 00:32:40,200
Speaker 2: the laser guy right working on the technology stack that

625
00:32:40,280 --> 00:32:45,160
Speaker 2: helps satellites communicate. Essentially your co founders also SpaceX alumni

626
00:32:45,280 --> 00:32:49,440
Speaker 2: in slightly different domains. But how is that transferable to

627
00:32:49,480 --> 00:32:53,880
Speaker 2: what you're doing here in the first instance with the transceivers.

628
00:32:54,560 --> 00:32:56,720
Speaker 15: Yeah, great question, and no, I was super excited to

629
00:32:56,760 --> 00:32:59,200
Speaker 15: have part of a lot of the team that I

630
00:32:59,240 --> 00:33:02,640
Speaker 15: worked with there flying the Starlink laser medice, and we're very.

631
00:33:02,600 --> 00:33:03,680
Speaker 5: Proud of what we did there.

632
00:33:03,720 --> 00:33:08,080
Speaker 15: And you know, I think about the job here every

633
00:33:08,160 --> 00:33:11,320
Speaker 15: day and I feel very similar, about very similar to

634
00:33:11,400 --> 00:33:12,680
Speaker 15: what I was doing at SpaceX.

635
00:33:12,720 --> 00:33:14,760
Speaker 5: And you know, SpaceX, the space Lazer.

636
00:33:14,480 --> 00:33:16,640
Speaker 15: Team was quite small and a very awesome team, and

637
00:33:16,840 --> 00:33:19,200
Speaker 15: we're building the same thing here, a very small, like

638
00:33:19,400 --> 00:33:23,560
Speaker 15: technical oriented team with really talented individuals, and the day

639
00:33:23,560 --> 00:33:24,840
Speaker 15: to day feels very similar.

640
00:33:24,880 --> 00:33:27,440
Speaker 5: We're you know, building standing.

641
00:33:27,120 --> 00:33:31,920
Speaker 15: Up high volume production, trying to deploy as much hardware

642
00:33:31,960 --> 00:33:34,960
Speaker 15: as possible, and co locating the talent right next to

643
00:33:35,000 --> 00:33:39,200
Speaker 15: the manufacturing line, and so yeah, it feels very similar.

644
00:33:40,560 --> 00:33:44,240
Speaker 2: This is about more than the underlying technology, right. This

645
00:33:44,480 --> 00:33:49,560
Speaker 2: is a field where the supply chain is dominated by China,

646
00:33:49,600 --> 00:33:52,680
Speaker 2: and so one of your ambitions is to is to

647
00:33:52,760 --> 00:33:55,800
Speaker 2: exceed that bring capacity to the United States. And you

648
00:33:55,880 --> 00:33:58,920
Speaker 2: put a timeline at twenty twenty seven on that. This

649
00:33:59,040 --> 00:34:01,400
Speaker 2: is a big, sort of big debut funding around. But

650
00:34:01,440 --> 00:34:04,800
Speaker 2: what's the roadmap from here? You're going to need more capital.

651
00:34:05,080 --> 00:34:06,200
Speaker 2: What are your priorities?

652
00:34:07,240 --> 00:34:11,160
Speaker 15: Yeah, our priority is to build as many optical interconnects

653
00:34:11,200 --> 00:34:14,040
Speaker 15: as possible and deploy as many of those as we can.

654
00:34:15,040 --> 00:34:18,680
Speaker 15: So for the immediate term, it's getting to high volume

655
00:34:19,280 --> 00:34:21,560
Speaker 15: of this first device we're making, while at the same

656
00:34:21,600 --> 00:34:25,320
Speaker 15: time planning for our long term ambitions of doing space

657
00:34:25,360 --> 00:34:30,920
Speaker 15: based laser communication and eventually one day propelling spacecraft with photons.

658
00:34:31,719 --> 00:34:36,000
Speaker 2: Right, right, So explain that distinction, right in the first instance,

659
00:34:36,000 --> 00:34:39,400
Speaker 2: who's the customer data center on Earth and then in

660
00:34:39,440 --> 00:34:42,520
Speaker 2: the future there is a distinction on this happening in space.

661
00:34:43,440 --> 00:34:45,480
Speaker 15: Yeah, yeah, So first customer, you know, we've got to

662
00:34:45,520 --> 00:34:48,680
Speaker 15: help the US deploy this compute on the ground as

663
00:34:48,719 --> 00:34:51,480
Speaker 15: fast as possible. And you know, there's a big vulnerability

664
00:34:51,480 --> 00:34:54,120
Speaker 15: in the supply chain with regards to optics and the

665
00:34:54,120 --> 00:34:58,040
Speaker 15: way those optics are assembled and manufactured all overseas, and

666
00:34:58,239 --> 00:35:02,160
Speaker 15: standing up a secure supply chain outside of uh, you know,

667
00:35:02,239 --> 00:35:07,040
Speaker 15: Asia and China specifically, really helps us leverage our product

668
00:35:07,080 --> 00:35:09,400
Speaker 15: into all of these data centers on the ground. And

669
00:35:09,840 --> 00:35:12,400
Speaker 15: when we show how much volume we can do on

670
00:35:12,440 --> 00:35:14,560
Speaker 15: the ground, it's you know, then we have to start

671
00:35:14,600 --> 00:35:17,319
Speaker 15: pushing that volume to space, and we'll be the one

672
00:35:17,360 --> 00:35:18,600
Speaker 15: strategically set up to do that.

673
00:35:19,640 --> 00:35:20,399
Speaker 3: Just real quick.

674
00:35:20,440 --> 00:35:23,279
Speaker 2: On Frive Capital a big day for them and they're

675
00:35:23,360 --> 00:35:26,560
Speaker 2: leading you around. Why is it important that they are

676
00:35:26,600 --> 00:35:27,040
Speaker 2: backing you.

677
00:35:28,160 --> 00:35:31,279
Speaker 15: Yeah, they from the beginning have just been ready to

678
00:35:31,320 --> 00:35:32,080
Speaker 15: go with us.

679
00:35:31,960 --> 00:35:34,759
Speaker 5: And deploy quickly.

680
00:35:34,880 --> 00:35:37,520
Speaker 15: And you know, our goal is to stand up this

681
00:35:37,600 --> 00:35:41,080
Speaker 15: volume production as fast as possible. And they were also

682
00:35:41,120 --> 00:35:43,000
Speaker 15: willing to work as fast as possible with us, and

683
00:35:43,040 --> 00:35:45,680
Speaker 15: we really appreciate appreciate them, like back in the founder

684
00:35:45,800 --> 00:35:47,799
Speaker 15: and also wanting to accelerate.

685
00:35:48,760 --> 00:35:51,080
Speaker 2: From the time that you're at SpaceX. Clearly like the

686
00:35:51,120 --> 00:35:54,200
Speaker 2: bigger vision has changed right now, space based data center

687
00:35:54,800 --> 00:35:57,800
Speaker 2: like that, that's what we're going towards. Do you expect

688
00:35:57,840 --> 00:36:01,040
Speaker 2: to work with your old company and with Elon Musk

689
00:36:01,360 --> 00:36:03,880
Speaker 2: to try and pitch the technology back into them.

690
00:36:04,719 --> 00:36:07,480
Speaker 15: You know, I'd always love to keep working with them

691
00:36:07,520 --> 00:36:11,040
Speaker 15: and help I just want to help connect as much

692
00:36:11,239 --> 00:36:16,200
Speaker 15: compute and send probes to deep space as much as possible,

693
00:36:16,200 --> 00:36:18,000
Speaker 15: and whoever we can work with on.

694
00:36:17,880 --> 00:36:19,560
Speaker 5: That, I'm very excited to do that.

695
00:36:19,719 --> 00:36:23,600
Speaker 15: And you know, connecting everything from the ground to space,

696
00:36:23,880 --> 00:36:26,880
Speaker 15: it's going to need to transition to optical because RF

697
00:36:27,080 --> 00:36:31,440
Speaker 15: reaches a limit and optical photons are much more efficient

698
00:36:31,560 --> 00:36:34,759
Speaker 15: and power efficient and the things the constraints on the

699
00:36:34,760 --> 00:36:37,120
Speaker 15: ground are power, and the constraints in space are also power,

700
00:36:37,160 --> 00:36:39,600
Speaker 15: and so it leads very well for what we're making here.

701
00:36:40,320 --> 00:36:42,160
Speaker 2: We are we're hearing that a lot on the show

702
00:36:42,360 --> 00:36:45,279
Speaker 2: of Late Photons of the Future. Travis Pasheer is co

703
00:36:45,360 --> 00:36:48,480
Speaker 2: founder and CEO of Mesh. Thank you very much. Now,

704
00:36:48,480 --> 00:36:51,840
Speaker 2: coming up, digital talent manager Night raises a new funding

705
00:36:51,920 --> 00:36:54,120
Speaker 2: round as it looks to expand its business.

706
00:36:54,160 --> 00:36:57,280
Speaker 3: We have more on that next. This is Bloomberg Tech.

707
00:37:07,000 --> 00:37:10,319
Speaker 2: Talent management firm Night has raised seventy million dollars to

708
00:37:10,400 --> 00:37:14,560
Speaker 2: expand its business across music, sports, gaming, and live events.

709
00:37:14,920 --> 00:37:18,440
Speaker 2: Knights founder and CEO Reduction joins us. Now this is

710
00:37:18,680 --> 00:37:22,600
Speaker 2: this is digital Hollywood, right and the management of top talent.

711
00:37:23,640 --> 00:37:27,000
Speaker 2: It's interesting to grow through venture. What do you need

712
00:37:27,040 --> 00:37:27,600
Speaker 2: the funds for?

713
00:37:29,000 --> 00:37:30,919
Speaker 16: Yeah, we're going to use it for a few different things.

714
00:37:30,960 --> 00:37:34,440
Speaker 16: I mean, we're primarily focused on talent management here at Night,

715
00:37:34,480 --> 00:37:36,239
Speaker 16: but we do have a venture studio. You know, we've

716
00:37:36,280 --> 00:37:39,680
Speaker 16: gone onto fun things like feastables and tone with Kaisanat,

717
00:37:39,719 --> 00:37:42,360
Speaker 16: and so for us, I think like the thesis was

718
00:37:42,400 --> 00:37:45,560
Speaker 16: always that talent of the future are born on the Internet.

719
00:37:45,760 --> 00:37:47,640
Speaker 16: That is very much still our thought going into the

720
00:37:47,640 --> 00:37:50,120
Speaker 16: future and so we're going to use that to be like,

721
00:37:50,200 --> 00:37:52,440
Speaker 16: what we think is the Internet's media company.

722
00:37:53,960 --> 00:37:57,560
Speaker 2: Which platforms right now are launching careers. I know that

723
00:37:57,560 --> 00:38:00,680
Speaker 2: that is a broad question, but if we talk to

724
00:38:01,200 --> 00:38:05,759
Speaker 2: the giants in broadcasting and streaming, or we talk to YouTube,

725
00:38:06,080 --> 00:38:08,080
Speaker 2: right they would all kind of accept that it is

726
00:38:08,160 --> 00:38:11,640
Speaker 2: a battle for eyeballs, even if they're slightly different mediums.

727
00:38:11,840 --> 00:38:14,759
Speaker 2: So which platform you're seeing launch the people that you

728
00:38:14,800 --> 00:38:15,480
Speaker 2: hope to serve?

729
00:38:16,280 --> 00:38:18,200
Speaker 16: Yeah, I think there's two that stand out to me,

730
00:38:18,360 --> 00:38:21,520
Speaker 16: especially in my industry. YouTube obviously being the first, Like

731
00:38:21,560 --> 00:38:23,560
Speaker 16: we just saw that they announced they have almost thirteen

732
00:38:23,600 --> 00:38:26,760
Speaker 16: percent of connected TV watch time, So they're beating Netflix,

733
00:38:26,760 --> 00:38:28,600
Speaker 16: they're beating Amazon, they're beating HBO.

734
00:38:29,160 --> 00:38:29,360
Speaker 15: You know.

735
00:38:29,600 --> 00:38:32,400
Speaker 16: The next one is TikTok. I think just primarily because

736
00:38:32,440 --> 00:38:35,799
Speaker 16: of the discoverability of content through short form, like it

737
00:38:35,840 --> 00:38:39,880
Speaker 16: doesn't matter if you have ten followers or a million followers,

738
00:38:39,920 --> 00:38:41,799
Speaker 16: Like a good video can get a lot of use

739
00:38:41,840 --> 00:38:42,480
Speaker 16: and go viral.

740
00:38:42,840 --> 00:38:43,800
Speaker 3: And so I think that has.

741
00:38:43,719 --> 00:38:47,960
Speaker 16: Created a lot of careers just because of that top

742
00:38:48,000 --> 00:38:51,080
Speaker 16: of funnel that's created regardless if you have followers or not.

743
00:38:52,320 --> 00:38:54,520
Speaker 2: You you've been at this a while, right, this is

744
00:38:54,760 --> 00:38:58,200
Speaker 2: not as if Night just suddenly came about Overnight's ten

745
00:38:58,280 --> 00:39:01,879
Speaker 2: years of work. I think now at this stage the

746
00:39:01,920 --> 00:39:05,839
Speaker 2: timing of the rays, what was the strategy behind that read.

747
00:39:06,400 --> 00:39:09,440
Speaker 16: Yeah, we've grown very linear over the last ten years,

748
00:39:10,320 --> 00:39:13,040
Speaker 16: you know, through signing different talent through the Venture Studio.

749
00:39:14,080 --> 00:39:16,520
Speaker 16: It felt like a perfect time for us. You know,

750
00:39:16,560 --> 00:39:18,840
Speaker 16: we feel like we've never been more right than we

751
00:39:18,880 --> 00:39:21,960
Speaker 16: are right now in our thesis of Internet native talent

752
00:39:22,280 --> 00:39:25,840
Speaker 16: being the future of celebrities. And so for us, like

753
00:39:25,880 --> 00:39:28,160
Speaker 16: the last ten years, we're all about, like how do

754
00:39:28,160 --> 00:39:30,440
Speaker 16: we educate, how do we continue to represent the biggest

755
00:39:30,480 --> 00:39:32,359
Speaker 16: talent on the Internet. You know, we think the next

756
00:39:32,360 --> 00:39:35,160
Speaker 16: ten years like attention is the currency. You know, we

757
00:39:35,200 --> 00:39:38,360
Speaker 16: think that individuals are more or consumers are more loyal

758
00:39:38,400 --> 00:39:41,440
Speaker 16: to individuals now more than ever. And so as we

759
00:39:41,480 --> 00:39:43,480
Speaker 16: continue this thesis, you know, this is a company that

760
00:39:44,160 --> 00:39:45,840
Speaker 16: hopefully I can run for the rest of my life.

761
00:39:45,920 --> 00:39:48,759
Speaker 16: We'll see, but I think, like, you know, the next

762
00:39:48,760 --> 00:39:50,759
Speaker 16: ten to twenty years, like we still believe in this

763
00:39:50,840 --> 00:39:54,240
Speaker 16: like internet first talent born on the Internet, the future

764
00:39:54,280 --> 00:39:57,960
Speaker 16: state of celebrity is born on the Internet. And so

765
00:39:58,040 --> 00:39:59,680
Speaker 16: it felt like the perfect time for us to make

766
00:39:59,800 --> 00:40:00,600
Speaker 16: a larger move.

767
00:40:01,880 --> 00:40:04,560
Speaker 2: You've done some some m and a for one of

768
00:40:04,560 --> 00:40:07,759
Speaker 2: a better expression. Two thousand and four, Night acquires the

769
00:40:07,840 --> 00:40:09,120
Speaker 2: Roost podcast network.

770
00:40:09,280 --> 00:40:12,040
Speaker 3: Last year Experiential Supply Co.

771
00:40:13,040 --> 00:40:15,400
Speaker 2: Is this kind of the plan now, like the seventy

772
00:40:15,400 --> 00:40:18,279
Speaker 2: million dollars can go towards some interesting properties like that.

773
00:40:18,960 --> 00:40:21,400
Speaker 16: Yeah, we've done those organically off the balance sheet. Like

774
00:40:21,400 --> 00:40:24,319
Speaker 16: we've always been a profit company, you know, We've had

775
00:40:24,360 --> 00:40:27,000
Speaker 16: a successful career, and so we bought the Roost for

776
00:40:27,160 --> 00:40:30,320
Speaker 16: Warner Brothers when they were looking to sell that asset.

777
00:40:30,560 --> 00:40:34,720
Speaker 16: Really like building our media sales apparatus. Acquiring Experiential Supply

778
00:40:34,920 --> 00:40:37,000
Speaker 16: was you know, another thesis that we're going to continue

779
00:40:37,000 --> 00:40:39,600
Speaker 16: to run after. Like we do think the world lives

780
00:40:39,640 --> 00:40:41,480
Speaker 16: on the Internet, and we do think the future state

781
00:40:41,480 --> 00:40:43,640
Speaker 16: of celebrities are born on the Internet. But we also

782
00:40:43,680 --> 00:40:46,520
Speaker 16: think that consumers value in person experiences more than ever

783
00:40:46,520 --> 00:40:49,000
Speaker 16: in the future. We are still bullish on live events

784
00:40:49,440 --> 00:40:52,520
Speaker 16: and experiences for individuals, and so that was a lot

785
00:40:52,520 --> 00:40:55,480
Speaker 16: of bad acquisition. You know, the money will go towards

786
00:40:55,760 --> 00:40:58,120
Speaker 16: you know, buying things that makes sense for the culture

787
00:40:58,160 --> 00:41:00,800
Speaker 16: that we've built here over the last ten years. Businesses

788
00:41:00,840 --> 00:41:03,719
Speaker 16: that we think intersect with the Internet, and so a

789
00:41:03,719 --> 00:41:05,520
Speaker 16: lot of what we're going to look at going forward

790
00:41:05,640 --> 00:41:08,600
Speaker 16: is as things in those categories.

791
00:41:08,880 --> 00:41:12,600
Speaker 2: Read from Night's perspective. How do you think about what's

792
00:41:12,640 --> 00:41:17,160
Speaker 2: happening with Warner Brothers, Discovery, the Netflix part, the Paramount's

793
00:41:17,160 --> 00:41:20,280
Speaker 2: guidance part. You know, does it have some ripple effect

794
00:41:20,320 --> 00:41:23,840
Speaker 2: in your world where the talent's heads get turned about

795
00:41:24,160 --> 00:41:27,400
Speaker 2: the health of industry wide or it's just not a concern.

796
00:41:28,200 --> 00:41:29,000
Speaker 3: No, it does.

797
00:41:29,160 --> 00:41:32,200
Speaker 16: Like I think the issue is just the consolidation of

798
00:41:32,239 --> 00:41:35,440
Speaker 16: all these companies provides less buyers in the ecosystem, and

799
00:41:35,480 --> 00:41:38,319
Speaker 16: so you're seeing a contraction of shows getting sold and

800
00:41:38,360 --> 00:41:41,120
Speaker 16: we've now seen that over the past three to five years.

801
00:41:41,440 --> 00:41:42,840
Speaker 3: I think that's just going to continue.

802
00:41:42,880 --> 00:41:45,600
Speaker 16: I think the consolidation, you know, worries a lot of people,

803
00:41:45,640 --> 00:41:49,000
Speaker 16: Like we are based in Los Angeles, although we aren't

804
00:41:49,000 --> 00:41:52,120
Speaker 16: necessarily traditional Hollywood, you know, we do have shows and

805
00:41:52,120 --> 00:41:54,520
Speaker 16: have sold shows to those streaming services. I think the

806
00:41:54,600 --> 00:41:57,000
Speaker 16: interesting place where we sit as a company is that

807
00:41:58,040 --> 00:42:02,240
Speaker 16: ninety percent of our client roster sees YouTube or being

808
00:42:02,840 --> 00:42:06,080
Speaker 16: a large YouTube or TikTok creator as the endgame for them,

809
00:42:06,320 --> 00:42:09,160
Speaker 16: Like they want to be large Internet personalities. They want

810
00:42:09,200 --> 00:42:12,000
Speaker 16: to control their intellectual property. They want to can control

811
00:42:12,040 --> 00:42:14,840
Speaker 16: their editing and have final cut and final say in

812
00:42:14,920 --> 00:42:18,160
Speaker 16: the product. And so I think it affects us way

813
00:42:18,239 --> 00:42:21,240
Speaker 16: less than it maybe affects the traditional talent management companies

814
00:42:21,480 --> 00:42:26,320
Speaker 16: whose revenue concentration is primarily through entertainment services that's provided

815
00:42:26,320 --> 00:42:29,880
Speaker 16: from a TV network or a Netflix. Where ours, like

816
00:42:29,920 --> 00:42:34,480
Speaker 16: the primary revenue source is YouTube, ad sense, brand sponsorships.

817
00:42:34,520 --> 00:42:37,239
Speaker 16: It's very different, and it's although it does affect us,

818
00:42:37,239 --> 00:42:38,799
Speaker 16: it's on a much smaller scale.

819
00:42:40,440 --> 00:42:42,960
Speaker 2: Reductcher, founder CEO of Night, It's great to have you

820
00:42:42,960 --> 00:42:45,759
Speaker 2: on Bloomberg Tech. Thank you very much. So does it

821
00:42:45,760 --> 00:42:47,360
Speaker 2: for this assition of Bloomberg Tech. What we were just

822
00:42:47,400 --> 00:42:51,279
Speaker 2: discussing right this morning's news that Netflix is issued a

823
00:42:51,280 --> 00:42:54,799
Speaker 2: waiver to Warner Brothers Discovery allowing them to negotiate with

824
00:42:54,840 --> 00:42:58,120
Speaker 2: paramounts guidance. It's seven days through February twenty third, and

825
00:42:58,200 --> 00:43:02,040
Speaker 2: Paramount either has to improve their bit or something happens

826
00:43:02,080 --> 00:43:04,040
Speaker 2: with Netflix, which is a bit softer. They came out

827
00:43:04,040 --> 00:43:07,520
Speaker 2: with a strong statement saying that they feel very confident

828
00:43:07,680 --> 00:43:10,640
Speaker 2: in their existing bid and you can definitely go back

829
00:43:10,680 --> 00:43:13,200
Speaker 2: listen to the conversation looking sure in markets More.

830
00:43:13,120 --> 00:43:15,319
Speaker 3: Broadly, we are seeing volatility.

831
00:43:15,480 --> 00:43:18,320
Speaker 2: We had some serious declines at the index level, the

832
00:43:18,400 --> 00:43:23,160
Speaker 2: NASDAK one hundred, the mag seven names, the Philadelphia Semiconductor Index,

833
00:43:23,320 --> 00:43:26,160
Speaker 2: they were all markedly lower. Now actually the socks is higher,

834
00:43:26,440 --> 00:43:29,440
Speaker 2: but there has been volatility coming with that. Will continue

835
00:43:29,440 --> 00:43:31,840
Speaker 2: to track it. As I said, please recap. We have

836
00:43:31,920 --> 00:43:34,160
Speaker 2: the podcast. You know exactly where to find it on

837
00:43:34,200 --> 00:43:37,800
Speaker 2: the Bloomberg terminal as well as online Apple, Spotify and

838
00:43:37,920 --> 00:43:39,919
Speaker 2: iHeart this is Bloomberg Tech.