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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is alive

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Speaker 1: from coast to coast with Caroline Hyde and New York

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Speaker 1: and Ed Lovelow in San Francisco.

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Speaker 2: This is Bloomberg Tech coming up. Open AI ramps up

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Speaker 2: with more computing capacity from Oracle, expanding the Stargate initiative. Plus,

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Speaker 2: the US House of Representatives is on track to vote

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Speaker 2: on Donald Trump's tax and spending bill.

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Speaker 3: What does that mean for tech?

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Speaker 2: And the Trump administration lifts some export license controls requirements

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Speaker 2: for chip design software sales, specifically for China. Let's get

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Speaker 2: right to financial markets and as that one hundred is

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Speaker 2: pushing once again to fresh record highs strong jobs data

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Speaker 2: for the month of June. Halfway through the show, we're

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Speaker 2: going to go really deep on jobs and then we're

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Speaker 2: going to look at the labor market when it comes

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Speaker 2: to the technology sector. But there are other things happening

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Speaker 2: that are pushing the tech sector in XT markets higher.

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Speaker 2: A lot of it is related to compute capacity. Bloomberg

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Speaker 2: broke a really big story last night, and I want

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Speaker 2: to get right to it.

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Speaker 3: The story's Oracles.

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Speaker 2: On a two day basis, we saw a five percent

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Speaker 2: jump in oracle yesterday. We're pushing a little bit higher

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Speaker 2: again this Thursday. But the deal is open AI expanding

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Speaker 2: the Stargate project, getting more compute capacity in new states

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Speaker 2: and new sites beyond what they've already got in Texas.

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Speaker 2: The person that broke that story Bloomberg's Brody Ford, and he's.

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Speaker 3: With us now.

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Speaker 2: I think we need to get to the details of

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Speaker 2: what you reported, because there was a lot of detail

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Speaker 2: in it, Brody, specifically in terms of gigawatts.

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Speaker 3: The scale of this new capacity.

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Speaker 4: Yeah, we saw earlier in the year, you know, Larry

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Speaker 4: Ellison standing there in the White House talking about we're

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Speaker 4: going to deploy five hundred billion dollars with open AI

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Speaker 4: for data centers. A lot of people doubted that scale. Well,

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Speaker 4: yesterday we broke that they have inked a pretty unprecedented

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Speaker 4: deal four point five giggle watts. The usual rule of

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Speaker 4: thumb is that a gigglewats about a nuclear reactor, and

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Speaker 4: so we're talking about a scale of four and a

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Speaker 4: half worth of nuclear reactors or powering about three and

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Speaker 4: a half million homes. I mean, this is likely the

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Speaker 4: largest cloud deal of all time, and it's gonna be

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Speaker 4: tens of billions of dollars of chips of power. I mean,

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Speaker 4: it's gonna be hard to wrap our head around what

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Speaker 4: this looks like in the build out.

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Speaker 3: Okay, what do we know?

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Speaker 2: What are sources telling us about where these new sites

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Speaker 2: are going to be, what's under consideration? And kind of

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Speaker 2: like how near term this is?

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Speaker 5: Right?

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Speaker 4: So they've narrowed on a handful of data center sites, right,

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Speaker 4: I mean a ten states like Wisconsin or Pennsylvania or Texas.

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Speaker 4: They'll also be expanding the campus they've already built out

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Speaker 4: in Abilene that a lot of us have seen, you know,

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Speaker 4: images of how near term I mean, a lot of

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Speaker 4: this stuff is tough to get off the ground. Oracle

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Speaker 4: earlier this week said that the full ramp would likely

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Speaker 4: not hit into twenty twenty eight, and so it's it's

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Speaker 4: fairly far out, but I would expect to see some

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Speaker 4: of these sites come out and a pretty rapid clip.

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Speaker 4: We don't know exactly which one's gonna move first, but

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Speaker 4: you know, I'm sure we're gonna be starting to get

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Speaker 4: more details trickling out in the coming weeks and months.

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Speaker 3: Let's talk about the Oracle side of this.

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Speaker 2: This is a stop that's now again pushing fresh record

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Speaker 2: highs almost every day. At the moment, it's up forty

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Speaker 2: percent so far in twenty twenty five.

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Speaker 3: This is a big win for Oracle.

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Speaker 2: They are really pushing and changing their position in the

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Speaker 2: landscape of infrastructure and AI cloud computing.

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Speaker 4: Three years ago, if you said Oracle major cloud player,

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Speaker 4: people would make fun of you, definitely, But today that's

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Speaker 4: not the case, right. I mean, they're making I think

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Speaker 4: around ten billion per year in cloud infrastructure. On Monday

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Speaker 4: they said the deal that we connected is this opening

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Speaker 4: I one will be thirty billion per year. I mean

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Speaker 4: that is triple the size of their entire current cloud

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Speaker 4: and so it's huge for revenue. The big question is

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Speaker 4: what it means for margins, And that's kind of the

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Speaker 4: classic with a lot of these AI businesses that they're

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Speaker 4: going to be buying a lot of chips and power

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Speaker 4: and construction, and that's going to constrain their margins. What

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Speaker 4: does that mean for cash flow? That's what investors are

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Speaker 4: asking this morning.

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Speaker 2: Bloomberg's Brody Ford there with the reporting, let's get to

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Speaker 2: the analysis. This expanded deal between Oracle and open Ai.

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Speaker 2: It's also good news for some chip makers. That's according

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Speaker 2: to Bloomberg intelligence, who say the likes of Nvidia and

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Speaker 2: AMD are going to benefit here. Keunjin Sabani offered that

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Speaker 2: note and he joins us. Now inside all of this infrastructure,

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Speaker 2: at the heart of it is the compute, and the

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Speaker 2: compute right now in this market is largely coming from Nvidia,

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Speaker 2: but also to a greater extent increasingly from a AMD.

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Speaker 2: What's the thesis here that you've got congent.

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Speaker 6: Well, two points, As Brady mentioned, Oracle has been really

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Speaker 6: beefing up their spending versus what we thought a year

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Speaker 6: or two ago. Now if you look at the estimates

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Speaker 6: now you're in for twenty five, it is going to

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Speaker 6: be the fastest CSP in terms of capex increases, so

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Speaker 6: definitely increasing the wallet share and becoming a serious buyer

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Speaker 6: of the chips. Second point, it is one of the

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Speaker 6: only hyper scalers or cloud providers among the top five

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Speaker 6: who does not have a custom silicon or an ACIC program.

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Speaker 6: What does that mean is majority of the capex that

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Speaker 6: is is going to spend to bring up this four

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Speaker 6: point five gigle wats of capacity is going to merchant

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Speaker 6: GPU providers, likes and media which it has been buying.

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Speaker 6: Most of GPS from in the past, but also AMD

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Speaker 6: because as they announced, they're ordering about one hundred and

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Speaker 6: thirty k M three point fifty five for the second half,

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Speaker 6: which equates to somewhere between three to four billion dollars

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Speaker 6: of revenue for AMD.

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Speaker 2: Just real quick, con Jen Brody was giving us the

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Speaker 2: reporting on the dollar value of this deal to Oracle, right,

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Speaker 2: it's that thirty billion dollars that we were talking about

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Speaker 2: earlier in the week per year starting in fiscal twenty eight.

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Speaker 2: Are you able to model or do the math on

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Speaker 2: what these kinds of deals and the value of them

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Speaker 2: are to AMD and Video in terms of like number

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Speaker 2: of chips that they will send that way, or kind

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Speaker 2: of the pipeline of business that they're securing through Oracle.

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Speaker 6: To some extent, because there are a lot of assumptions,

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Speaker 6: but what we can map is the gigawards to the

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Speaker 6: chip spending. So rather than the revenue that Oracle will

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Speaker 6: collect the four point five gigabards, assuming that's all brand

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Speaker 6: new data center build out, one gigaward approximately in today's term,

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Speaker 6: equates to sixty billion dollars of capex, which includes everything

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Speaker 6: from chips and hardware. So even if you had to

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Speaker 6: like make take conservative stance and cut it half for chips.

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Speaker 6: That still leaves you for what every gigaward at least

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Speaker 6: thirty billion.

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Speaker 3: Dollars Bloomberg Intelligence is congense.

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Speaker 2: Vanni, there with the analysis, we had the reporting, We

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Speaker 2: got the analysis.

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Speaker 3: Now let's get the market reaction.

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Speaker 2: Janet Murray, head of market analysis at RBC Berandolphin, found

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Speaker 2: it really interesting these big capital projects in infrastructure just

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Speaker 2: keep coming. What does that signal to you about what

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Speaker 2: the market should model for in the coming years ahead?

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Speaker 6: As thanks for having me.

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Speaker 7: I think the significance of this deal is that the

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Speaker 7: demountable computing power is just incestiable. And remember when deep

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Speaker 7: SIK come out, a lot of investors were worries that

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Speaker 7: actually they may not be the need for so much

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Speaker 7: computing power if the modeling is so efficient, But actually

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Speaker 7: that's not true. We see that there is high visibility

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Speaker 7: of the scale of the investment by sovereigns, by hyperscalars

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Speaker 7: and many corporates. So I guess this is really the

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Speaker 7: big conclusion is that the runway still is still very

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Speaker 7: long and the incentive to invest is still very high.

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Speaker 7: So I think the theme of investment in a particularly

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Speaker 7: in semiconductors and cloud which are the AI infrastructure is particalarly.

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Speaker 2: Relevant Janet and Brodie's reporting. He's saying that this expansion

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Speaker 2: between Oracle and Open AI is four point five giggle

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Speaker 2: watt's worth of capacity and in the context of energy,

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Speaker 2: you could power this country at that scale. How do

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Speaker 2: you think about the energy sector and the energy infrastructure

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Speaker 2: requirements that markets are going to have to fund to

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Speaker 2: support these types of data center expansion.

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Speaker 7: Again, I think the utility side energy side of things

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Speaker 7: goes hand in hand with the need for from shooting power,

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Speaker 7: and that's why we have seen our hyperscalar like meta

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Speaker 7: investing in nuclear energy for example. So I think the

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Speaker 7: quest or cheaper, more efficient energy would be there, and

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Speaker 7: I think that is why I think the US warming

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Speaker 7: basically the region that would lead the AI race, because

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Speaker 7: the US is basically self sufficient in the energy production

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Speaker 7: relatively cheaper energy compared to say Europe and for example,

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Speaker 7: the UK. So I guess that's a very important conclusion,

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Speaker 7: is that there is incentive for companies to invest and

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Speaker 7: base their production in the US to access is cheap

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Speaker 7: energy base.

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Speaker 2: Janet, the story this Thursday is treasuries are falling, the

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Speaker 2: dollar is stronger, and equity markets, particularly the technology sector,

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Speaker 2: pushing fresh record highs on the Nasdaq one hundred. Give

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Speaker 2: me your reaction to the jobs data and the coprint

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Speaker 2: that we got this morning.

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Speaker 7: Well, I would say that data is basically goldilots because

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Speaker 7: on one hand, you get better than expected jobs data

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Speaker 7: in general a softening trend, but it's still okay. It's

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Speaker 7: still reflective of a solid labor market. An employment rate

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Speaker 7: is lower, and at the same time, wage growth is

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Speaker 7: actually slower despite a shrinking labor force. So I would

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Speaker 7: say it's a goldilocks, which market clearly likes. And I

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Speaker 7: think the conclusion is that the Federal Reserve really is

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Speaker 7: in urgency to cut raise. But that's fine because I

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Speaker 7: think the markets would prefer the evidence of a strong

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Speaker 7: labor market rather than fretting over the exact timing of

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Speaker 7: the rate cut.

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Speaker 2: I do see some outperformance in technology. Why is that?

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Speaker 2: Why is that? Is it just a waiting issue right

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Speaker 2: now and technology is what this market is or is

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Speaker 2: there something in this economy and the path forward for

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Speaker 2: the Fed that makes this sector more attractive right now?

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Speaker 1: Yeah?

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Speaker 7: I guess there are lots of reasons right. First of all,

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Speaker 7: in terms of earning it's growth profile, technology is still

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Speaker 7: the brightest spot out there, as I mentioned, a clear

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Speaker 7: visibility on AI investment. I think secondly, I think in

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Speaker 7: terms of the productivity gains, I think the tech sector

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Speaker 7: is likely to see or have a lot of those

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Speaker 7: productivity surplus. And of course, I think in terms of

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Speaker 7: the US market, I think the tech sector is where

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Speaker 7: the actionists to access the aif them et cetera, and

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Speaker 7: if we see for example, rape cuss really coming by.

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Speaker 7: I think law barn Yiel's law interest rate also partically

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Speaker 7: benefit those growth areas as well. So really a combination

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Speaker 7: of factors.

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Speaker 2: If you're a technology investor, that was the what you

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Speaker 2: needed to know. Janet Mouri, head of market analysis at

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Speaker 2: RBC BRA and Dolphin, thank you very much. There is

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Speaker 2: a lot more coming up the house pools and all

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Speaker 2: nighter as Republicans race to get a tax bill to

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Speaker 2: President Trump's desk before their July fourth deadline. We're going

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Speaker 2: to live to Washington, DC next and we will have

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Speaker 2: the latest on where things stand.

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Speaker 3: Don't go anywhere. This is Bloomberg Tech.

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Speaker 8: Live, the good life, good name.

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Speaker 3: Welcome back to Bloomberg Tech.

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Speaker 2: You're looking at live pictures from Capitol Hill where House

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Speaker 2: Minority Leader Hakeem Jeffries is delivering a blistering rebuttal of

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Speaker 2: the tax bill that's now going into its sixth hour.

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Speaker 3: Here with the very.

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Speaker 2: Latest, Bloomberg's Tyler Canda out in Washington, DC. What is

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Speaker 2: the latest? What do we expect to happen? What do

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Speaker 2: we need to know?

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Speaker 5: Yeah, hey, Ed, So, the House Democratic Leader Hawking Jeffries

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Speaker 5: has something known as the magic minute, which means that

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Speaker 5: he can speak for however long as he wants, and

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Speaker 5: as you mentioned, he started at four fifty three am Eastern,

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Speaker 5: so we could be in this for the long haul.

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Speaker 5: But it really does feel like they're sort of delaying

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Speaker 5: the inevitable because Republicans a pure poised to pass President

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Speaker 5: Trump's signature legislative Achievement, which would be the one big,

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Speaker 5: beautiful bill. Once Leader Jeffries is done speaking, House Speaker

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Speaker 5: Mike Johnson might take the mic, or they could try

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Speaker 5: to get this done as soon as possible and this

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Speaker 5: would proceed immediately to a vote on finalized passage. Once

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Speaker 5: that happens, we're looking for that magic number of two

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Speaker 5: hundred and seventeen, which means House Speaker Mike Johnson can

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Speaker 5: only afford to lose three votes, but he appears to

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Speaker 5: have it. It seems like Republican leadership was able to

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Speaker 5: flip some of the staunches critics of this bill, those

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Speaker 5: members of the House Freedom Caucus, those Republicans that were

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Speaker 5: pitching themselves as fiscal hawks, and our reporting on the

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Speaker 5: Hill this morning indicates that they did get some sort

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Speaker 5: of concessions and assurances from this White House in order

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Speaker 5: to flip their votes, including one that I know that

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Speaker 5: you pay close attention to, which is when it comes

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Speaker 5: to the phase out of those clean energy tax credits.

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Speaker 5: Ralph Norman told our reporter on the Hill today that

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Speaker 5: one of the assurances that the White House gave them

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Speaker 5: was that there would be strict enforcement when it does

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Speaker 5: come to the phase out, particularly around solar and win

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Speaker 5: tax subsidies. So that's something to look forward and look

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Speaker 5: out to as we try to glean more details on

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Speaker 5: exactly what it took to get these Republicans to flip

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Speaker 5: their vote when it came to the procedural vote.

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Speaker 2: Earlier this morning, tailer technology markets in real time and

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Speaker 2: as that one hundred already pushing fresh record high is

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Speaker 2: now extending its gain in the session to one percent.

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Speaker 2: It is a short week because it is a July

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Speaker 2: fourth holiday this Friday in the United States. There's a

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Speaker 2: lot being made of, like the symbolism of the President

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Speaker 2: signing this bill July and fourth. I heard you speaking

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Speaker 2: with Bloombogs, Matt and Miner about that earlier.

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Speaker 3: Why is that symbolism.

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Speaker 5: There, Well, it really was this self imposed deadline from

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Speaker 5: the administration that they wanted to get this done by

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Speaker 5: July fourth. We are expecting a pretty big signing ceremony

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Speaker 5: either later today or tomorrow, so that President Trump can

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Speaker 5: tout this legislative achievement that they're really hoping we'll pair

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Speaker 5: with some of these potential trade deals frameworks that we

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Speaker 5: could get next week ahead of that July ninth deadline

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Speaker 5: that they have put into effect. Because the administration is

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Speaker 5: really hoping for a few different things to happen here.

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Speaker 5: They want to see a confluence really of economic factors

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Speaker 5: going into the summer so that they can help push

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Speaker 5: ahead when it comes to President Trump's economic agenda. Now,

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Speaker 5: of course they're dealing with criticism. We have the House Speaker,

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Speaker 5: for example, railing against some of the changes when it

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Speaker 5: comes to Medicaid. But this administration is really trying to

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Speaker 5: focus people on this idea of stabilizing the debt to GDP. Yes,

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Speaker 5: this bill is going to add significantly to the national debt,

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Speaker 5: but it is the other policies that they're looking to

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Speaker 5: put into place that ultimately they say will help grow

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Speaker 5: the economy.

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Speaker 2: The national debt pile the big focus of Elon Musk,

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Speaker 2: as we've discussed all week, Bloomberg Tyler Kendall terrific work

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Speaker 2: out in Washington, DC.

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Speaker 3: Thank you very much. Let's get to another big story.

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Speaker 2: The US and China are beginning to implement their recent

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Speaker 2: trade deals, and as part of that, there's some easing

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Speaker 2: of restrictions on critical technologies, including export license requirements for

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Speaker 2: chip design, software sales, particularly in China. Bloomberg's Peter Elstrom,

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Speaker 2: who leads the team in covering Asia tech and European tech,

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Speaker 2: is with us. So what we're talking about is EDA

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Speaker 2: and as of last night, we're hearing from the key players,

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Speaker 2: the key names in the DA space that they're now

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Speaker 2: free to do business in China.

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Speaker 3: What do we need to know?

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Speaker 9: Yeah, that's right. So this is a strange one. It

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Speaker 9: was just in May when we found out from the

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Speaker 9: companies that they were going to have these export restrictions

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Speaker 9: on China. Their EDA software is necessary to be able

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Speaker 9: to design semiconductors. It was also strange the way that

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Speaker 9: it got announced. It was the companies that actually were

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Speaker 9: these new restrictions, it was not the Commerce Department, which

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Speaker 9: is the agency behind that. Again this time it's kind

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Speaker 9: of similar. We had Semens come out first. Cadence Design

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Speaker 9: Systems and Synopsis are also affected here. They came out

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Speaker 9: and then they said it in fact, those restrictions are

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Speaker 9: now being rolled back. They're not going to have the

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Speaker 9: same kind of restrictions on servicing and supporting selling into

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Speaker 9: China to support their customers.

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Speaker 3: So what's going on.

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Speaker 9: Behind the scenes? As you say, the US and China

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Speaker 9: are now in the middle of East trade negotiations. Back

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Speaker 9: in May, China was kind of playing tough. They were

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Speaker 9: not exporting some of the rare earth the minerals that

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Speaker 9: American companies needed. Now that the negotiations are preceding, China

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Speaker 9: struck this tentative agreement to be able to ship those again.

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Speaker 9: In the US and China are coming back to the

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Speaker 9: table and as a result, these companies are going to

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Speaker 9: have a little bit more breathing space. But that's very unusual.

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Speaker 9: You've got export controls, which are typically national security issues

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Speaker 9: now being traded as part of the trade negotiations.

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Speaker 2: We're seeing some of the chip makers push higher, but

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Speaker 2: really the stories around the software name, Cadencenopsis, the two

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Speaker 2: that you mentioned also pushing higher. Will show those in

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Speaker 2: just a second. The modern day cutting edge chip has

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Speaker 2: billions of transistors. Right, No human brain can do the

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Speaker 2: blueprint or designed for that. But there is some concern

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Speaker 2: here that Huawei, in particular, if they are having free

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Speaker 2: access to EDA, that they can use that technology in

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Speaker 2: that software platform to close the gap a little bit,

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Speaker 2: you know, design their own cutting edge chips. Why is

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Speaker 2: America not more concerned about that, Peter, Yeah, that's a.

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Speaker 9: Key issue in the technology race between the two countries.

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Speaker 9: You have the US ahead and a few different key areas.

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Speaker 9: In particular, DA is one of the most important ones.

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Speaker 9: Of course, semiconductor equipment is another one. The Netherlands ASML

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Speaker 9: is by far the leading player. While Way however, has

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Speaker 9: been able to break through some of these barriers. It's

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Speaker 9: become a national champion for China. It's helped try to

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Speaker 9: focus on some of these key bottlenecks that they have.

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Speaker 9: DA is one of the key areas, or if they're

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Speaker 9: able to use these tools, they can step ahead and

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Speaker 9: design some of these chips. They have the surprise the world,

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Speaker 9: i'd say, with some of their advancements and semiconductors, particularly

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Speaker 9: this seven nanometer chip that they used in one of

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Speaker 9: their smartphones in the past. But now they have not

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Speaker 9: been able to make some of the progress, have not

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Speaker 9: been able to move forward quite as quickly. So these

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Speaker 9: tools are going to help them make some of those

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Speaker 9: steps going forward again. That's why it's so surprising that

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Speaker 9: they're trading this away in the negotiations between the US

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Speaker 9: and China.

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Speaker 2: Bloomberg's executive editor for Global Technology, Peter Elstrom, thank you

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Speaker 2: so much. It's time for talking tech, and first up,

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Speaker 2: Deep Seek ramps up hiring. The Chinese AI startup posted

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Speaker 2: ten positions on LinkedIn, indicating it maybe looking to lure

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Speaker 2: talent from outside of its homeland. The listings include three

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Speaker 2: roles focused on general intelligence, with the positions based in

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Speaker 2: Beijing and Han Joe plus ASML and other European semiconductor

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Speaker 2: stocks extended losses. Today, there was a report from Nicky

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Speaker 2: Asia that said Samsung would be delaying its completion of

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Speaker 2: a chip factory in Texas. The report, citing sources, says

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Speaker 2: the delay is due to Samsung struggling to find customers

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Speaker 2: for the plant's output and some news that broke this hour.

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Speaker 2: Core Weaves the first company to receive the latest AI

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Speaker 2: system based on Nvidia's newest chip. Dell delivered the first

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Speaker 2: GB three hundred MVL seventy two.

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Speaker 3: Rack of servers to core Weave and would deploy them.

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Speaker 2: In the US, with core Weave aiming to bring more

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Speaker 2: of the tech online throughout the year. Open AI is

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Speaker 2: one of Corweave's customers and the infrastructural players, saying the

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Speaker 2: new systems will work well for larger, more complex models.

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Speaker 2: That's the reporting, that's the detail. I want to get

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Speaker 2: some more analysis on this. One man deep seeing of

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Speaker 2: Bloomberg Intelligence is with us. There's this like constant tracking

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Speaker 2: of the launch and ramp of Nvidia's latest generation server

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Speaker 2: design that has the latest generation chip and chip combination

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Speaker 2: in it.

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Speaker 3: Col Weave goes first, what do you make of that?

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Speaker 8: Well, when I look at in video's release cycle, they

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Speaker 8: are on a one year rhythm and in between that

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Speaker 8: year now they are launching the black Vell Ultra before

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Speaker 8: the Ruben series comes online. And look, they're almost giving

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Speaker 8: a fifty percent performance upgrade with the black Vel Ultra

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Speaker 8: in terms of token processing. So from that perspective, Corviv

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Speaker 8: having that chip first really gives them a leg up

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Speaker 8: over the hyperscalers, which will also get their in Vidia allocation.

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Speaker 8: But for Corviv, you know they have a backlog of

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Speaker 8: about twenty six billion. To convert that backlock to revenue,

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Speaker 8: you need the most kind of impressive in Vidio chips

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Speaker 8: first and that helps with the faster backlock conversion.

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Speaker 10: So really good news for Corevive, especially on the training front,

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Speaker 10: because a lot of these latest black Ultra chips I

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Speaker 10: believe will be used for training and then the older

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Speaker 10: series will be used for in printing over time.

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Speaker 2: So call we've stock really pushed higher after news came out.

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Speaker 2: I'm also looking at Dell, like, help us understand the

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Speaker 2: Dell component in this ecosystem.

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Speaker 8: Yeah, well, Dell is the one who is making that server,

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Speaker 8: So in Vidia is providing the chip and krviv is

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Speaker 8: really bringing those racks and the servers online to be

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Speaker 8: consumed in a cloud consumption model. But Dell is the

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Speaker 8: one who is actually assembling that server and making sure

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Speaker 8: that it can be delivered to coreviv. So from that perspective,

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Speaker 8: they are part of that supply chain and it's a

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Speaker 8: good thing that they get to, you know, do that

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Speaker 8: for Nvidia before any other server maker like Quanta or

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Speaker 8: you know, any other Chinese OEMs come into play.

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Speaker 2: Very quick, we just have twenty seconds, Mandy, Well, what's

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Speaker 2: the BI big picture thesis right now on how this

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Speaker 2: AI infrastructure build outs going.

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Speaker 8: I mean, Oracle and open Ai really raised up the

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Speaker 8: ante when it comes to you know, their big announcement

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Speaker 8: the thirty billion dollar contract and now this news. So

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Speaker 8: to my mind, you know, the infrastructure supercycle is really

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Speaker 8: playing out and you're seeing that right now.

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Speaker 2: Man, keep seeing Bloomberg Intelligence of BI. Great to have

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Speaker 2: the reaction here on the show.

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Speaker 3: Welcome back to Bloomberg Tech.

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Speaker 2: Let's get right to the markets and I'll start with

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Speaker 2: the technology sector in the acuity market. Right then, a's

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Speaker 2: that one hundred continuing to push fresh record highs. But

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Speaker 2: we got the job's data for June strong labor market,

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Speaker 2: and the story is really clear. Equities pushed higher outperformance

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Speaker 2: in the tech sector, but you also saw treasuries full

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Speaker 2: the dollar strengthen. Take all of that in aggregate. It's

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Speaker 2: really important. This is what the bomb market looks like.

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Speaker 2: I know we go there less often, but there is

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Speaker 2: always a relationship between what's happening in yields and particularly

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Speaker 2: valuations around technology sector. Now, this was the blowout jobs report,

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Speaker 2: and there's any one guy that I want to go

439
00:23:04,480 --> 00:23:07,720
Speaker 2: to on a daylight today, that's Bloomberg's Economics and Policy

440
00:23:07,720 --> 00:23:09,480
Speaker 2: correspondent Michael McKee.

441
00:23:09,600 --> 00:23:11,080
Speaker 3: As you know, I just don't know.

442
00:23:11,240 --> 00:23:14,200
Speaker 2: I don't really understand the granularity of the job's data,

443
00:23:14,240 --> 00:23:17,000
Speaker 2: the revisions, the changes, what is the need to know

444
00:23:17,320 --> 00:23:20,840
Speaker 2: in June, and the kind of explanation for why markets

445
00:23:20,840 --> 00:23:21,920
Speaker 2: reacted the way they did.

446
00:23:22,760 --> 00:23:22,960
Speaker 3: Well.

447
00:23:23,000 --> 00:23:25,680
Speaker 11: The explanation for why markets reacted the way they did

448
00:23:25,800 --> 00:23:29,320
Speaker 11: is fairly simple. The economy seems stronger than it was

449
00:23:29,400 --> 00:23:32,680
Speaker 11: expected to be, and that would suggest that corporate earnings

450
00:23:32,720 --> 00:23:36,120
Speaker 11: can stay strong. But this is a report that looks

451
00:23:36,160 --> 00:23:39,440
Speaker 11: better on the surface than it does underneath. It's not terrible,

452
00:23:39,520 --> 00:23:41,479
Speaker 11: but it's not as great as it looks. We had

453
00:23:42,000 --> 00:23:44,760
Speaker 11: one hundred and forty seven thousand jobs created, and the

454
00:23:44,840 --> 00:23:48,239
Speaker 11: unemployment rate falls to four point one percent. But of

455
00:23:48,280 --> 00:23:51,680
Speaker 11: those one hundred and forty seven thousand jobs, seventy three

456
00:23:51,760 --> 00:23:53,920
Speaker 11: thousand were in government employment.

457
00:23:54,040 --> 00:23:54,760
Speaker 3: Most of that.

458
00:23:54,760 --> 00:23:59,240
Speaker 11: State and local education schools are out in June, so

459
00:23:59,600 --> 00:24:02,720
Speaker 11: there's probably a seasonal adjustment problem with these numbers that

460
00:24:02,760 --> 00:24:06,919
Speaker 11: will cause them to be revised lower. Private payrolls were

461
00:24:07,000 --> 00:24:10,760
Speaker 11: up only seventy four thousand. That's lower than we had

462
00:24:10,840 --> 00:24:14,199
Speaker 11: been seeing, so there is some concern about all this.

463
00:24:14,280 --> 00:24:16,880
Speaker 11: And of course the unemployment rate falls because one hundred

464
00:24:16,920 --> 00:24:18,919
Speaker 11: and thirty thousand people left the labor force, so ed

465
00:24:19,520 --> 00:24:24,040
Speaker 11: not quite as good as anticipated, and of course we

466
00:24:24,080 --> 00:24:26,080
Speaker 11: want to know how they're doing out in.

467
00:24:25,920 --> 00:24:26,959
Speaker 3: Your neck of the woods.

468
00:24:27,320 --> 00:24:31,000
Speaker 11: We lost five thousand jobs in computer manufacturing, another thousand

469
00:24:31,119 --> 00:24:37,080
Speaker 11: in semiconductor manufacturing. Web search portals and hosting lost three

470
00:24:37,200 --> 00:24:40,359
Speaker 11: hundred jobs, so on the tech side not so great either.

471
00:24:41,920 --> 00:24:46,320
Speaker 2: I'm really grateful for that level of detail on the

472
00:24:46,359 --> 00:24:49,479
Speaker 2: tech sect, like we're going to go deep into what

473
00:24:49,520 --> 00:24:51,800
Speaker 2: the environment is right now, particularly in software with our

474
00:24:51,800 --> 00:24:55,040
Speaker 2: next guest, But what I'm seeing on the news cycle

475
00:24:55,240 --> 00:24:57,960
Speaker 2: and timel this morning is very FED related a lot

476
00:24:57,960 --> 00:25:01,080
Speaker 2: of questions directed towards the administration and about what the

477
00:25:01,080 --> 00:25:02,159
Speaker 2: FED should or shouldn't do.

478
00:25:02,280 --> 00:25:06,359
Speaker 11: Why is that, Well, everybody wants lower interest rates because

479
00:25:06,400 --> 00:25:08,919
Speaker 11: of course it's going to mean higher corporate profits. But

480
00:25:09,600 --> 00:25:12,439
Speaker 11: this report pretty much pushes the FED out of that.

481
00:25:12,600 --> 00:25:14,800
Speaker 11: For the July meeting, there was only a couple of

482
00:25:14,800 --> 00:25:18,560
Speaker 11: FED officials who were talking about July. September still stays

483
00:25:18,680 --> 00:25:22,040
Speaker 11: on the calendar as the most likely first month for

484
00:25:22,280 --> 00:25:24,960
Speaker 11: a rate cut. We'll see what happens next week when

485
00:25:25,000 --> 00:25:28,280
Speaker 11: we get the CPI report on the fifteenth. That could

486
00:25:28,320 --> 00:25:32,119
Speaker 11: make a difference to the Fed. But at this point

487
00:25:32,520 --> 00:25:35,159
Speaker 11: it looks like the Fed stays on hold. And of

488
00:25:35,160 --> 00:25:38,879
Speaker 11: course the President will keep tweeting that he doesn't like j.

489
00:25:39,040 --> 00:25:39,280
Speaker 12: Powell.

490
00:25:40,840 --> 00:25:45,400
Speaker 2: Bloomberg's Michael McKee, International Economics and Policy correspondent. It's great

491
00:25:45,400 --> 00:25:47,840
Speaker 2: to have you back on Bloomberg Tech. Let's get right

492
00:25:47,920 --> 00:25:50,399
Speaker 2: to tech and more on the jobs outlook in the sector.

493
00:25:50,880 --> 00:25:55,520
Speaker 2: Eric Wosakowski is the Bespoke Partner's CEO, an absolute specialist

494
00:25:56,080 --> 00:25:59,960
Speaker 2: in executive search, particularly in the fields of SaaS software

495
00:26:00,119 --> 00:26:03,760
Speaker 2: also private equity here in the United States, and I

496
00:26:03,800 --> 00:26:06,200
Speaker 2: want to talk about what that market is like right now,

497
00:26:06,240 --> 00:26:08,359
Speaker 2: particularly at the higher end. There's been so much in

498
00:26:08,400 --> 00:26:12,479
Speaker 2: the news cycle about talent poaching. Frankly, but just on

499
00:26:12,520 --> 00:26:15,199
Speaker 2: the data this morning, was there any read through for

500
00:26:15,280 --> 00:26:18,199
Speaker 2: you that directly correlates to what you're seeing in the

501
00:26:18,240 --> 00:26:19,159
Speaker 2: technology sector?

502
00:26:20,600 --> 00:26:20,679
Speaker 8: Ed?

503
00:26:20,720 --> 00:26:22,520
Speaker 13: Thank you for having me on. I tend to agree

504
00:26:22,520 --> 00:26:25,720
Speaker 13: with Michael. I think the headline news sounds fantastic, but

505
00:26:25,760 --> 00:26:28,160
Speaker 13: I think when you peel back the onion, private sector jobs,

506
00:26:28,200 --> 00:26:34,440
Speaker 13: particularly in tech and innovation, are flat. CEOs today are

507
00:26:35,000 --> 00:26:37,960
Speaker 13: trading on uncertainty in the market, whether it be the

508
00:26:38,000 --> 00:26:41,480
Speaker 13: impact of the tariffs, the geopolitical environment. That said, I

509
00:26:41,520 --> 00:26:44,439
Speaker 13: don't think it's a negative situation because I think what

510
00:26:44,480 --> 00:26:47,720
Speaker 13: we saw yesterday with Microsoft announcing they're cutting more jobs

511
00:26:48,080 --> 00:26:50,920
Speaker 13: is CEOs over the last six months have really tightened

512
00:26:50,960 --> 00:26:55,199
Speaker 13: their belt to see how the market pivots. If we

513
00:26:55,240 --> 00:26:58,160
Speaker 13: get negative implications from tariffs, they're going to be able

514
00:26:58,160 --> 00:27:00,960
Speaker 13: to weather the storm. But I actually think the underpinnings

515
00:27:01,000 --> 00:27:04,000
Speaker 13: here are on a positive economy in the next six

516
00:27:04,080 --> 00:27:06,840
Speaker 13: to twelve months, a strong future, and I think CEOs

517
00:27:06,840 --> 00:27:10,000
Speaker 13: are sitting back with capital to invest. Is they get

518
00:27:10,000 --> 00:27:12,960
Speaker 13: favorable news on tariffs in the geopolitical environments and hopefully

519
00:27:13,000 --> 00:27:13,480
Speaker 13: a rate cut.

520
00:27:15,040 --> 00:27:18,760
Speaker 2: We did hear from the administration, so to speak. This morning,

521
00:27:19,119 --> 00:27:22,000
Speaker 2: Stephen Moran gave an interview to Open Interest, one of

522
00:27:22,040 --> 00:27:25,040
Speaker 2: our earlier shows. He leads the Council of Economic Advisors.

523
00:27:25,240 --> 00:27:26,960
Speaker 2: Let's listen to what he said.

524
00:27:28,359 --> 00:27:31,240
Speaker 14: What we see is an economy that continues to continues

525
00:27:31,280 --> 00:27:34,840
Speaker 14: to defy expectations, continues to define all the doom and

526
00:27:34,840 --> 00:27:36,800
Speaker 14: gloom that's out there, whether it's about the border, or

527
00:27:36,800 --> 00:27:40,159
Speaker 14: immigration or tariffs, just labor market continues to power ahead.

528
00:27:40,240 --> 00:27:43,360
Speaker 14: There were tons of predictions that there'd be a disaster

529
00:27:43,440 --> 00:27:46,200
Speaker 14: of labor market because of the border policies, and nothing

530
00:27:46,240 --> 00:27:48,520
Speaker 14: could be further from the truth. The economy continues to

531
00:27:48,560 --> 00:27:50,560
Speaker 14: create jobs, and if you look at the details of

532
00:27:50,600 --> 00:27:52,639
Speaker 14: the jobs, all of the job gains since the president

533
00:27:52,640 --> 00:27:55,160
Speaker 14: of office are due to native born Americans, and there's

534
00:27:55,160 --> 00:27:57,600
Speaker 14: actually been a decline in foreign born worker which means

535
00:27:57,640 --> 00:27:59,920
Speaker 14: that all of the benefits of the expanding economy are

536
00:28:00,000 --> 00:28:04,240
Speaker 14: recurring to Americans instead of migrants.

537
00:28:05,400 --> 00:28:10,440
Speaker 2: What Stephen outlined, they're seeing in the relationship between policy

538
00:28:10,760 --> 00:28:14,639
Speaker 2: and how it impacts fiscal policy and political policy and

539
00:28:14,680 --> 00:28:17,960
Speaker 2: how it impacts the jobs market. Do you see what

540
00:28:18,000 --> 00:28:21,639
Speaker 2: he explained reflected in software and SATs.

541
00:28:23,240 --> 00:28:25,560
Speaker 13: I don't think it's reflected yet. I think there's an

542
00:28:25,600 --> 00:28:29,600
Speaker 13: opportunity going forward because the largest creator of high paying

543
00:28:29,680 --> 00:28:33,280
Speaker 13: good jobs in the United States is innovation and private equity.

544
00:28:33,320 --> 00:28:34,879
Speaker 13: And I think when we look at the number of

545
00:28:34,960 --> 00:28:38,160
Speaker 13: deals that are done in private equity, the investment that's happening,

546
00:28:38,160 --> 00:28:40,360
Speaker 13: I think we're still in a wait and see mode.

547
00:28:40,480 --> 00:28:42,480
Speaker 13: I think if you look year over year, the number

548
00:28:42,480 --> 00:28:46,719
Speaker 13: of private equity deals is down. That said, in speaking

549
00:28:46,760 --> 00:28:50,200
Speaker 13: with the investment banking firms, their mandate pipelines are full.

550
00:28:50,280 --> 00:28:52,840
Speaker 13: In speaking with our private equity clients, they're reviewing a

551
00:28:52,840 --> 00:28:55,680
Speaker 13: record number of new deals. And I think the next

552
00:28:55,720 --> 00:28:57,560
Speaker 13: six to twelve months, I really think we're going to

553
00:28:57,600 --> 00:29:00,560
Speaker 13: start to see the deal activity pick, which is going

554
00:29:00,600 --> 00:29:02,080
Speaker 13: to fuel investment in jobs.

555
00:29:03,920 --> 00:29:10,280
Speaker 2: So the big story has been mister Mark Zuckerberg, according

556
00:29:10,320 --> 00:29:14,120
Speaker 2: to mister Sam Outman, the CEO of Open Ai, approaching

557
00:29:14,200 --> 00:29:16,800
Speaker 2: talent in the field of AI, but let's call it

558
00:29:16,880 --> 00:29:23,000
Speaker 2: software and offering. According to Sam Outman, pay packages of

559
00:29:23,000 --> 00:29:24,800
Speaker 2: one hundred million US dollars.

560
00:29:25,680 --> 00:29:27,520
Speaker 3: Is that the kind of market that you're seeing.

561
00:29:27,520 --> 00:29:31,840
Speaker 13: This is what you specialize in absolutely, and we're not

562
00:29:31,920 --> 00:29:34,920
Speaker 13: privy to those particular deals. But I think the labor

563
00:29:35,000 --> 00:29:39,560
Speaker 13: market at the high end in software tech SaaS is

564
00:29:39,720 --> 00:29:42,480
Speaker 13: very tight because you don't have that natural flow of

565
00:29:42,520 --> 00:29:46,040
Speaker 13: deals and exits that creates natural term You've got a

566
00:29:46,120 --> 00:29:49,920
Speaker 13: number of assets that are at the ready to transact

567
00:29:49,920 --> 00:29:53,840
Speaker 13: in the next six to eighteen months, and so executives

568
00:29:53,840 --> 00:29:56,240
Speaker 13: today are not reticent to make a move, and so

569
00:29:56,360 --> 00:29:59,840
Speaker 13: that notion of poaching, the notion of having to overpay

570
00:30:00,040 --> 00:30:03,600
Speaker 13: to attract star executives for those open roles you need,

571
00:30:04,280 --> 00:30:09,080
Speaker 13: is absolutely happening. The premium proven executives are at a

572
00:30:09,120 --> 00:30:12,680
Speaker 13: premium right now, and that's why they're demanding outsize pay

573
00:30:13,080 --> 00:30:16,600
Speaker 13: AI is clearly another area that's on the frontier. The

574
00:30:16,600 --> 00:30:20,600
Speaker 13: top executives that are leading way there are demanding outsized

575
00:30:20,600 --> 00:30:21,280
Speaker 13: pay packages.

576
00:30:22,480 --> 00:30:25,840
Speaker 2: Eric just very quickly, how does Bespoke use technology to

577
00:30:25,880 --> 00:30:28,000
Speaker 2: find a solution in that type market.

578
00:30:28,760 --> 00:30:31,080
Speaker 13: So we have, as far as I know, the first

579
00:30:31,120 --> 00:30:36,240
Speaker 13: executive index in executive recruiting. It's focused particularly on the

580
00:30:36,280 --> 00:30:39,880
Speaker 13: software market. We used AI and mL to index six

581
00:30:40,040 --> 00:30:44,240
Speaker 13: hundred and seventy six thousand software executives in North America.

582
00:30:44,600 --> 00:30:49,840
Speaker 13: The technology gives us key indicators on job fits, propensity

583
00:30:49,880 --> 00:30:53,320
Speaker 13: to make a move and the like, and so we,

584
00:30:53,360 --> 00:30:55,479
Speaker 13: as far as I know, are the first and are

585
00:30:55,520 --> 00:30:58,880
Speaker 13: going to continue to push the envelope on technology and recruiting.

586
00:31:00,960 --> 00:31:03,320
Speaker 2: Eric Walzakowski, it's great to have you on the program,

587
00:31:03,440 --> 00:31:06,320
Speaker 2: Bespoke Partner's CEO on this job's Day, but also there's

588
00:31:06,320 --> 00:31:08,920
Speaker 2: so much conversation around what's happening right now in the

589
00:31:08,960 --> 00:31:10,200
Speaker 2: technology jobs market.

590
00:31:10,200 --> 00:31:11,000
Speaker 3: Thank you very much.

591
00:31:11,040 --> 00:31:11,120
Speaker 5: So.

592
00:31:11,240 --> 00:31:14,479
Speaker 2: Coming up, Amy Saper from Uncoort Capital joins us talk

593
00:31:14,520 --> 00:31:18,600
Speaker 2: about the state of seed stage investing and competition to

594
00:31:18,680 --> 00:31:21,040
Speaker 2: get in early. How common a theme has that been

595
00:31:21,040 --> 00:31:23,720
Speaker 2: in recent weeks? Really looking forward to this one. Stay tuned.

596
00:31:23,800 --> 00:31:24,400
Speaker 2: That's next.

597
00:31:24,680 --> 00:31:40,800
Speaker 3: This is Bloomberg Tech. It's time for the VC Spotlight.

598
00:31:41,120 --> 00:31:44,960
Speaker 2: Our next guest is a classically trained singer, backed Michael

599
00:31:45,040 --> 00:31:49,800
Speaker 2: Jackson in one of his music videos and competed across California.

600
00:31:50,040 --> 00:31:52,080
Speaker 2: She's also worked at some of the world's most important

601
00:31:52,120 --> 00:31:56,000
Speaker 2: technology companies, Twitter, Uber, and Stripe, and she's now a

602
00:31:56,040 --> 00:31:59,320
Speaker 2: partner at Uncourt Capital, at one point two billion dollar

603
00:31:59,400 --> 00:32:03,920
Speaker 2: venture firm chasing the biggest potential names in AI. Amy

604
00:32:03,960 --> 00:32:06,880
Speaker 2: Safer joins us here in San Francisco, Welcome to the program.

605
00:32:07,000 --> 00:32:11,520
Speaker 2: Thanks for having me increasingly on this program. At all

606
00:32:11,520 --> 00:32:14,120
Speaker 2: of the dinners I'm going to, there is a big

607
00:32:14,160 --> 00:32:19,360
Speaker 2: battle to get in earlier. Actually, sometimes founders don't really

608
00:32:19,440 --> 00:32:23,800
Speaker 2: have a fully baked idea. And reading your notes and

609
00:32:24,040 --> 00:32:27,000
Speaker 2: the thesis, but also being subscribed to tasting notes on

610
00:32:27,120 --> 00:32:30,280
Speaker 2: Cork's newsletter, that's kind of where the focus.

611
00:32:29,960 --> 00:32:31,480
Speaker 3: Is right now. Absolutely so.

612
00:32:31,560 --> 00:32:35,000
Speaker 15: Here at Kirk we are focused on seed investing, so

613
00:32:35,040 --> 00:32:38,760
Speaker 15: we typically write the first institutional check into a company.

614
00:32:39,040 --> 00:32:42,000
Speaker 15: We are really excited about what we're seeing in AI,

615
00:32:42,480 --> 00:32:46,320
Speaker 15: and we back founders with a deep belief on a

616
00:32:46,440 --> 00:32:49,040
Speaker 15: new customer segment or a new company, and we're trying

617
00:32:49,080 --> 00:32:50,840
Speaker 15: to back the founders that are building the companies that

618
00:32:50,840 --> 00:32:53,280
Speaker 15: are really going to define this next decade, and virtually

619
00:32:53,360 --> 00:32:54,880
Speaker 15: all of those have AI as they're.

620
00:32:54,760 --> 00:32:55,640
Speaker 3: Undercurrent right now.

621
00:32:55,720 --> 00:32:59,240
Speaker 2: What is also true is that the scale of the

622
00:32:59,280 --> 00:33:05,000
Speaker 2: seed round is being redefined. I see seed rounds in

623
00:33:05,040 --> 00:33:08,920
Speaker 2: the high tens of millions, depending on which sort of

624
00:33:08,960 --> 00:33:10,520
Speaker 2: corner of the technology market it is.

625
00:33:10,840 --> 00:33:13,160
Speaker 3: How has that changed things for you? Yeah, absolutely so.

626
00:33:13,200 --> 00:33:15,120
Speaker 15: I think if you look overall of the seed market,

627
00:33:15,160 --> 00:33:18,400
Speaker 15: it is true that rounds are getting larger. I think

628
00:33:18,440 --> 00:33:21,600
Speaker 15: the average in Q one was over three million, up

629
00:33:21,640 --> 00:33:25,680
Speaker 15: from maybe two and a half last year. So the

630
00:33:25,800 --> 00:33:28,360
Speaker 15: large rounds of the tens and twenty millions do make

631
00:33:28,360 --> 00:33:30,800
Speaker 15: the headlines. Those are not the norm of what we're seeing,

632
00:33:30,800 --> 00:33:33,800
Speaker 15: though they do occur. I do think it's true that

633
00:33:33,920 --> 00:33:36,880
Speaker 15: companies and founders are raising a little bit more reflective

634
00:33:37,000 --> 00:33:40,520
Speaker 15: of the increased expectations that the Series A investors are

635
00:33:40,560 --> 00:33:42,400
Speaker 15: placing relative to a couple of years ago.

636
00:33:42,960 --> 00:33:45,640
Speaker 2: There's what you can do in the field of AI,

637
00:33:46,280 --> 00:33:49,280
Speaker 2: and then there's what you can do with AI. What

638
00:33:49,400 --> 00:33:51,320
Speaker 2: is it that you're looking for in a founder right now?

639
00:33:51,400 --> 00:33:56,720
Speaker 2: Like people would say, well, I'm ANAI adjacent company or

640
00:33:56,760 --> 00:34:00,880
Speaker 2: I'm AI we're native, they might just be using AI

641
00:34:01,000 --> 00:34:05,080
Speaker 2: to do something else. They might be not necessarily developing

642
00:34:05,120 --> 00:34:07,080
Speaker 2: a new technology so to speak.

643
00:34:07,240 --> 00:34:10,680
Speaker 15: Yeah, absolutely, so, I think AI is already rapidly shifting

644
00:34:10,719 --> 00:34:12,879
Speaker 15: from being a sector that you might invest in into

645
00:34:13,040 --> 00:34:17,160
Speaker 15: encompassing every startup so whether their core product is AI native,

646
00:34:17,480 --> 00:34:20,160
Speaker 15: and we do have several of those in our portfolio

647
00:34:20,520 --> 00:34:24,239
Speaker 15: IVO for example, in the Legal Contract Review GPT zero

648
00:34:24,360 --> 00:34:27,200
Speaker 15: for copy editing. We also have companies that are selling

649
00:34:27,239 --> 00:34:31,520
Speaker 15: to AI companies so tail scale counts companies like Mistroll

650
00:34:31,560 --> 00:34:33,960
Speaker 15: and Perplexity and others amongst their customers set and are

651
00:34:34,000 --> 00:34:37,840
Speaker 15: emerging as the de facto networking solution for those AI companies.

652
00:34:38,200 --> 00:34:42,200
Speaker 15: So we are focused on companies that are cognizant that

653
00:34:42,440 --> 00:34:44,839
Speaker 15: the market is changing right now, and so whether they

654
00:34:44,840 --> 00:34:46,840
Speaker 15: are building that into their product, whether they're using it

655
00:34:46,880 --> 00:34:49,719
Speaker 15: in their back office to streamline some of their operations,

656
00:34:50,000 --> 00:34:52,520
Speaker 15: or whether they're selling to AI customers, it really is

657
00:34:52,560 --> 00:34:53,319
Speaker 15: everywhere right now.

658
00:34:53,480 --> 00:34:57,839
Speaker 2: I invite you to reflect on your music career, but

659
00:34:57,880 --> 00:35:02,240
Speaker 2: I think largely your career in technology Stripe Uber, Twitter

660
00:35:02,360 --> 00:35:04,880
Speaker 2: now known as X. Are you more of an operator

661
00:35:05,239 --> 00:35:08,400
Speaker 2: than then traditional finance and how are you helping the

662
00:35:08,440 --> 00:35:09,400
Speaker 2: founders that you're backing.

663
00:35:09,600 --> 00:35:09,799
Speaker 16: Yeah.

664
00:35:09,800 --> 00:35:10,320
Speaker 3: Absolutely.

665
00:35:10,360 --> 00:35:13,080
Speaker 15: I leverage my operating career every day, and I will

666
00:35:13,080 --> 00:35:15,240
Speaker 15: say my background is a mix of product, product marketing,

667
00:35:15,320 --> 00:35:18,799
Speaker 15: international expansion. I use the product marketing side far more

668
00:35:18,840 --> 00:35:22,880
Speaker 15: than I thought. I'm particularly attracted to companies and founders

669
00:35:22,920 --> 00:35:26,600
Speaker 15: that are largely technical, building AI enabled applications for engineering,

670
00:35:26,680 --> 00:35:29,040
Speaker 15: product and design teams, and they might not have a

671
00:35:29,080 --> 00:35:31,960
Speaker 15: product marketing or a sales background, and so I help

672
00:35:32,040 --> 00:35:35,719
Speaker 15: them define who's their ideal customer, how do you reach them?

673
00:35:35,840 --> 00:35:37,799
Speaker 15: How do you get your first sets of customers? And

674
00:35:37,800 --> 00:35:40,239
Speaker 15: that's such a critical set of activities to do with

675
00:35:40,280 --> 00:35:40,880
Speaker 15: the seed stage.

676
00:35:41,480 --> 00:35:44,040
Speaker 2: I know a lot of bench capitalists watch this program.

677
00:35:44,080 --> 00:35:46,440
Speaker 2: Many of you are not operators. You have a finance background,

678
00:35:46,480 --> 00:35:49,640
Speaker 2: nothing against any of that, but really interested in the

679
00:35:49,680 --> 00:35:51,160
Speaker 2: operator side of the story.

680
00:35:51,640 --> 00:35:53,759
Speaker 3: Where is it that the founders are struggling right now?

681
00:35:53,800 --> 00:35:56,680
Speaker 2: Like capital is basically commoditized, right, so what is it

682
00:35:56,719 --> 00:35:58,880
Speaker 2: that they say, like we really need your help with

683
00:35:59,560 --> 00:36:03,480
Speaker 2: imminent Is it hiring putting operational staff?

684
00:36:03,560 --> 00:36:04,480
Speaker 3: In absolutely?

685
00:36:04,520 --> 00:36:06,600
Speaker 15: I think it's two main things at the seed stage

686
00:36:06,600 --> 00:36:09,840
Speaker 15: that we focus on. One is really honing on getting

687
00:36:09,840 --> 00:36:12,799
Speaker 15: as specific as possible about who your ideal customer is.

688
00:36:12,880 --> 00:36:15,680
Speaker 15: And that's so critical for the seed stage because you

689
00:36:15,760 --> 00:36:19,400
Speaker 15: have the large horizontal players, the lms that are trying

690
00:36:19,440 --> 00:36:22,240
Speaker 15: to be the horizontal layer for everyone. Where seed stage

691
00:36:22,239 --> 00:36:25,359
Speaker 15: companies and early stage companies can really compete is by

692
00:36:25,360 --> 00:36:30,759
Speaker 15: focusing on a particular customer segment and owning their workflow.

693
00:36:30,400 --> 00:36:31,040
Speaker 3: End to end.

694
00:36:31,400 --> 00:36:33,279
Speaker 15: And so we spend a lot of time there and

695
00:36:33,320 --> 00:36:36,960
Speaker 15: then helping them identify the right talent that they need

696
00:36:37,080 --> 00:36:39,520
Speaker 15: to achieve those milestones and reach those.

697
00:36:39,360 --> 00:36:42,600
Speaker 2: Customers, Amy say pert partner un Court Capital, thank you

698
00:36:42,719 --> 00:36:52,760
Speaker 2: very much for joining us here. Former OpenAI board member

699
00:36:52,760 --> 00:36:56,680
Speaker 2: Helen Toner says Mark Zuckerberg and Meta's lavish spending for

700
00:36:56,800 --> 00:37:00,719
Speaker 2: top AI talent may not guarantee their success. On Bloomberg

701
00:37:00,800 --> 00:37:02,400
Speaker 2: Insight with has Linda I'm in.

702
00:37:03,160 --> 00:37:05,600
Speaker 16: What we're really seeing here with Meta is metas started

703
00:37:05,640 --> 00:37:07,600
Speaker 16: to get a reputation of having a little bit of

704
00:37:07,600 --> 00:37:12,200
Speaker 16: a dysfunctional AI team, not really having its organizational structures

705
00:37:12,200 --> 00:37:14,080
Speaker 16: set up in a way that Billy butts them succeed

706
00:37:14,160 --> 00:37:16,680
Speaker 16: and innovate. And what I think we're seeing here is

707
00:37:17,000 --> 00:37:19,160
Speaker 16: CEO Mark Zuckerberg really stepping in and saying, Wow, we

708
00:37:19,200 --> 00:37:21,120
Speaker 16: have to do something differently. We need a big new push,

709
00:37:21,120 --> 00:37:22,799
Speaker 16: we need a big new effort. The real question is

710
00:37:22,840 --> 00:37:25,200
Speaker 16: can it turn around Meta's fortunes and can it turn

711
00:37:25,239 --> 00:37:27,480
Speaker 16: Meta into a real juggernaut.

712
00:37:29,000 --> 00:37:33,000
Speaker 2: Staying on Meta, the company's Twitter alternative Threads has grown

713
00:37:33,000 --> 00:37:36,080
Speaker 2: to three hundred and fifty million monthly users since his

714
00:37:36,200 --> 00:37:39,200
Speaker 2: debut two years ago. Still, the social media platform is

715
00:37:39,239 --> 00:37:42,880
Speaker 2: continuing to work on finding their own identity among the industry.

716
00:37:43,080 --> 00:37:45,800
Speaker 2: So the subject to today's Tech in Depth newsletter written

717
00:37:46,000 --> 00:37:48,560
Speaker 2: by Bloombers Kirk Wagner. I said Twitter, I of course

718
00:37:48,640 --> 00:37:51,879
Speaker 2: meant X the platform formerly known as Twitter. I don't

719
00:37:51,920 --> 00:37:54,840
Speaker 2: know about Threads. Like when it launched, I used it

720
00:37:54,840 --> 00:37:58,120
Speaker 2: a lot because I like the interaction between Instagram and threads.

721
00:37:58,200 --> 00:38:00,560
Speaker 2: Like one thing I posted there I could take there.

722
00:38:00,880 --> 00:38:03,320
Speaker 2: I don't use it in the same way to share

723
00:38:03,440 --> 00:38:06,360
Speaker 2: news as I do potentially on x or even LinkedIn.

724
00:38:07,280 --> 00:38:09,680
Speaker 2: But it's it's your teching depth newsletter. What's the kind

725
00:38:09,680 --> 00:38:10,760
Speaker 2: of conclusion here.

726
00:38:11,640 --> 00:38:13,400
Speaker 12: Well, I think we're in the same boat, ed, because

727
00:38:13,400 --> 00:38:15,759
Speaker 12: that was sort of my thinking here as we come

728
00:38:15,840 --> 00:38:18,640
Speaker 12: up on the two year anniversary of this product. I

729
00:38:19,600 --> 00:38:22,400
Speaker 12: like threads, I use threads, but I still ask myself,

730
00:38:22,480 --> 00:38:23,839
Speaker 12: what is this thing for?

731
00:38:24,040 --> 00:38:24,200
Speaker 8: Right?

732
00:38:24,280 --> 00:38:28,160
Speaker 12: I think with Twitter, old Twitter, I knew what that was.

733
00:38:28,239 --> 00:38:29,920
Speaker 12: That was the place I went for breaking news. That

734
00:38:30,000 --> 00:38:32,319
Speaker 12: was a place I shared breaking news. That was where

735
00:38:32,360 --> 00:38:35,680
Speaker 12: I assumed that I would get, you know, things that

736
00:38:35,719 --> 00:38:38,880
Speaker 12: are happening right then, right now, right around me. And

737
00:38:38,920 --> 00:38:41,319
Speaker 12: I just don't really feel that from Threads. And part

738
00:38:41,360 --> 00:38:43,400
Speaker 12: of that is that I don't think they leaned into

739
00:38:43,560 --> 00:38:46,800
Speaker 12: politics during this last election cycle, and in my opinion,

740
00:38:46,920 --> 00:38:49,840
Speaker 12: sort of missed an opportunity to plant that flag on

741
00:38:50,200 --> 00:38:53,080
Speaker 12: the news side, and they made a few things changes

742
00:38:53,120 --> 00:38:54,960
Speaker 12: in the last few months that make me think maybe

743
00:38:55,000 --> 00:38:56,759
Speaker 12: they do care more about news and they want to

744
00:38:56,800 --> 00:38:58,960
Speaker 12: move in that direction. But again, two years in, my

745
00:38:59,239 --> 00:39:01,960
Speaker 12: one critique of platform is what do we use it for?

746
00:39:03,040 --> 00:39:03,320
Speaker 8: Well?

747
00:39:03,400 --> 00:39:07,200
Speaker 2: Also, how does meta position it and value it, you know,

748
00:39:07,360 --> 00:39:13,279
Speaker 2: as a platform visa the WhatsApp and Facebook and Instagram

749
00:39:13,280 --> 00:39:14,640
Speaker 2: commercially or otherwise.

750
00:39:16,000 --> 00:39:18,719
Speaker 12: Yeah, I mean I spoke to you know, the executive

751
00:39:18,760 --> 00:39:22,040
Speaker 12: who's running that team, Emily Dalton Smith, earlier this week

752
00:39:22,200 --> 00:39:24,160
Speaker 12: and she said, you know, it's a platform for exchanging

753
00:39:24,160 --> 00:39:27,000
Speaker 12: of ideas, right, It's clearly text. It's very much meant

754
00:39:27,040 --> 00:39:30,680
Speaker 12: to stoke some type of interaction between people in a

755
00:39:30,680 --> 00:39:33,040
Speaker 12: way that even Instagram I think is very much you know,

756
00:39:33,080 --> 00:39:36,239
Speaker 12: you sort of post something and people observe it. Right,

757
00:39:36,239 --> 00:39:39,680
Speaker 12: this is meant to be more back and forth. But again,

758
00:39:39,800 --> 00:39:41,520
Speaker 12: what are you talking about there?

759
00:39:41,600 --> 00:39:41,759
Speaker 8: Right?

760
00:39:41,880 --> 00:39:45,759
Speaker 12: Like people will find their communities, But what makes you

761
00:39:45,880 --> 00:39:48,560
Speaker 12: want to open that app every single day and make

762
00:39:48,600 --> 00:39:51,640
Speaker 12: that a destination for yourself? And that's where I feel like,

763
00:39:51,760 --> 00:39:54,560
Speaker 12: you know, I at least don't know exactly why I'm

764
00:39:54,600 --> 00:39:55,600
Speaker 12: opening threads.

765
00:39:55,280 --> 00:39:55,800
Speaker 3: All the time.

766
00:39:56,040 --> 00:39:58,640
Speaker 12: I hope that it will be because it becomes a

767
00:39:58,640 --> 00:40:00,839
Speaker 12: news source for me down the line. I just don't

768
00:40:00,840 --> 00:40:01,480
Speaker 12: think we're there.

769
00:40:01,400 --> 00:40:05,600
Speaker 2: Yet Bloombos Kurt Wagner, who is also the author of

770
00:40:05,760 --> 00:40:09,840
Speaker 2: Battle for the Bird, the book on Twitter Elon Musk's

771
00:40:09,840 --> 00:40:13,399
Speaker 2: acquisition of Twitter in its transition to X really really

772
00:40:13,480 --> 00:40:15,239
Speaker 2: highly recommend you go read that. That's why I kept

773
00:40:15,239 --> 00:40:17,640
Speaker 2: referring to Twitter. Let's get to another really important piece

774
00:40:17,640 --> 00:40:22,799
Speaker 2: of reporting. Immigration lawyers are advising clients to scrub their

775
00:40:22,840 --> 00:40:28,080
Speaker 2: social media accounts of controversy or politically sensitive topics, warning

776
00:40:28,120 --> 00:40:30,239
Speaker 2: the posts could be used to block their entry to

777
00:40:30,280 --> 00:40:31,560
Speaker 2: the US or.

778
00:40:31,560 --> 00:40:32,960
Speaker 3: As grounds to remove them.

779
00:40:33,520 --> 00:40:37,160
Speaker 2: Bloomberg Cecilia Deannastasio has been reporting this and it's a

780
00:40:37,160 --> 00:40:40,360
Speaker 2: particular segment that we're talking about. It's people who are

781
00:40:40,400 --> 00:40:44,279
Speaker 2: online influence, influencers to a certain extent. What have you

782
00:40:44,360 --> 00:40:45,600
Speaker 2: learned and what's the need to know?

783
00:40:47,120 --> 00:40:50,239
Speaker 17: Sure, so one in five Americans gets their news today

784
00:40:50,239 --> 00:40:53,839
Speaker 17: from influencers. Influencers have a lot of power over what

785
00:40:53,880 --> 00:40:57,080
Speaker 17: people think, especially politically these days, and what we heard

786
00:40:57,239 --> 00:41:02,120
Speaker 17: from immigration lawyers is that just bite influencers status as

787
00:41:02,160 --> 00:41:05,160
Speaker 17: citizens in the US, they are being advised not to

788
00:41:05,239 --> 00:41:08,280
Speaker 17: post on topics that the lawyers are considering hot button

789
00:41:08,360 --> 00:41:10,240
Speaker 17: for fear of potential repercussions.

790
00:41:11,640 --> 00:41:13,520
Speaker 3: So this is potentially severe.

791
00:41:15,840 --> 00:41:20,239
Speaker 2: It's part of a broader backdrop where migration in and

792
00:41:20,280 --> 00:41:22,160
Speaker 2: out of the United States is in focus. We talked

793
00:41:22,160 --> 00:41:25,160
Speaker 2: about it earlier in the Hour in the job sector.

794
00:41:25,800 --> 00:41:29,160
Speaker 2: Are there any sort of examples of where this is

795
00:41:29,160 --> 00:41:30,000
Speaker 2: already happening.

796
00:41:31,440 --> 00:41:35,840
Speaker 17: Sure, we have seen several examples of influencers in the US,

797
00:41:36,040 --> 00:41:38,839
Speaker 17: both people who have been born here, people who emigrated here,

798
00:41:39,000 --> 00:41:43,960
Speaker 17: people who might be undocumented facing repercussions.

799
00:41:43,000 --> 00:41:45,680
Speaker 15: For the way that their speech is viewed by.

800
00:41:45,640 --> 00:41:49,120
Speaker 17: People both close to government and inside of the government.

801
00:41:49,520 --> 00:41:51,400
Speaker 17: One of the examples that we use in our story

802
00:41:51,560 --> 00:41:54,920
Speaker 17: is far left leaning twitch streamer Hassan Piker, who's been

803
00:41:55,000 --> 00:41:59,560
Speaker 17: very outspoken on Palestine. He was detained in questioned when

804
00:41:59,600 --> 00:42:02,720
Speaker 17: he was bring back into the country to Chicago O'Hare,

805
00:42:03,360 --> 00:42:05,400
Speaker 17: and what he told us in an interview was that

806
00:42:05,400 --> 00:42:09,600
Speaker 17: he believes that this was a tactic for people to

807
00:42:09,640 --> 00:42:12,719
Speaker 17: become afraid of sharing their opinions on topics that might

808
00:42:12,719 --> 00:42:14,719
Speaker 17: not align with current governmental positions.

809
00:42:15,520 --> 00:42:18,080
Speaker 2: Cecilia just very quickly. Has there been any reaction to

810
00:42:18,160 --> 00:42:19,560
Speaker 2: our reporting from the government.

811
00:42:21,160 --> 00:42:24,480
Speaker 17: We haven't seen anything yet, but one of the concerns

812
00:42:24,480 --> 00:42:26,840
Speaker 17: that have heard from people who have read the story

813
00:42:27,360 --> 00:42:30,239
Speaker 17: is that today's influencers who speak on politics tend to

814
00:42:30,239 --> 00:42:34,120
Speaker 17: actually be more conservative than left leaning, according to a

815
00:42:34,120 --> 00:42:38,040
Speaker 17: recent pupil and considering some of the concerns around speaking

816
00:42:38,080 --> 00:42:41,440
Speaker 17: about certain topics in certain ways, there are worries that

817
00:42:41,440 --> 00:42:43,320
Speaker 17: that gap might actually widen overtime.

818
00:42:44,160 --> 00:42:47,319
Speaker 2: The HS Assistant Secretary for Public Affairs, Trishop Pacoffin also

819
00:42:47,440 --> 00:42:50,480
Speaker 2: emailing us saying that their officers are following the law,

820
00:42:50,719 --> 00:42:54,160
Speaker 2: not agendas. Really check out that reporting from the team Bloomberg.

821
00:42:54,239 --> 00:42:58,000
Speaker 2: Cecilia Deannastasia, thank you very much. That does it for

822
00:42:58,040 --> 00:43:00,520
Speaker 2: this edition of Bloomberg Tech. It's a show week in

823
00:43:00,560 --> 00:43:03,360
Speaker 2: the United States. There won't be any show this Friday

824
00:43:03,600 --> 00:43:06,080
Speaker 2: because of the July fourth holiday, but this was a

825
00:43:06,120 --> 00:43:07,560
Speaker 2: big show, so much to recap.

826
00:43:07,800 --> 00:43:09,400
Speaker 3: Check out the b Tech podcast.

827
00:43:09,440 --> 00:43:11,280
Speaker 2: You know where to find it on all the Bloomberg

828
00:43:11,320 --> 00:43:16,000
Speaker 2: platforms and online, iHeart, Spotify and on Apple.

829
00:43:16,560 --> 00:43:19,279
Speaker 3: From San Francisco, this is Bloomberg Tech.