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

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

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Speaker 1: York and v lovel in San Francisco.

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Speaker 2: This is Bloomberg Tech coming up.

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Speaker 3: Mike Cron and Eske Heinez joined the one trillion dollar

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Speaker 3: market Cap Club All about the Memory Plus.

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Speaker 4: Taiwanese prosecutors suspect three individuals of smuggling in video chips

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Speaker 4: to China through Japan.

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Speaker 2: And we speak.

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Speaker 1: Bloomberg Tech is a live from coast to coast with

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Speaker 1: Caroline Hide in New York and V lovel in San Francisco.

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Speaker 2: This is Bloomberg Tech coming up.

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Speaker 3: Mike Cron and Eske Heinez joined the one trillion dollar

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Speaker 3: market Cap Club All about the Memory Plus.

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Speaker 4: Taiwanese prosecutors expect three individuals of smuggling in video chips

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Speaker 4: to China through.

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Speaker 3: Japan, and we speak with the x price founder and

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Speaker 3: early SpaceX investor Peter Demandis's SpaceX celebrates a major starship milestone.

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Speaker 4: And meanwhile, we still think about what space is doing

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Speaker 4: to the public markets, but more broadly, the public markets

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Speaker 4: just taking.

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Speaker 5: A bit of a breather.

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Speaker 4: Today we're looking at what howpillion terms of semiconductors in particular,

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Speaker 4: it has been a fiery ride hire In the last

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Speaker 4: five training days, we'd added thirteen percent of this benchmark.

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Speaker 4: Today we pulled back a little bit, but there are

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Speaker 4: notable players within the chip sector that you've got to

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Speaker 4: keep your eyes trained on. It's all about the power

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Speaker 4: the muscle of high bandwidth memory, and of course it's

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Speaker 4: sent Micron storing. We're still holding onto the day's games

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Speaker 4: rock three tens of percent, but it was all about

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Speaker 4: yesterday's market moves and those that happened in Asia as

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Speaker 4: well ed.

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Speaker 3: That brings us to today's big number one trillion dollars

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Speaker 3: in climbing memoryship giants s k Heinex and Micron have

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Speaker 3: now joined the one trillion dollar market cap club and

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Speaker 3: see continued momentum is investors pile into some of the

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Speaker 3: companies the powering the AI boom. Let's get more with

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Speaker 3: Bloomberg Equities reporter Ryan Vacelica. It's been a number of

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Speaker 3: days now where we've been trying to look at what's happening. Ryan,

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Speaker 3: with the memory names of particular, Micron was the case

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Speaker 3: study because of that ubs note which you can remind

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Speaker 3: us of, but generally speaking, what is happening across memory,

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Speaker 3: not just in US markets, but of course in Korean

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Speaker 3: markets as well well.

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Speaker 6: There's been a huge and growing appreciation of how central

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Speaker 6: high bandwidth memory is to the overall AI infrastructure build out.

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Speaker 6: These companies have seen absolutely massive demand and absolutely massive growth.

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Speaker 6: I think Micron's revenue nearly tripled last quarter, which was

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Speaker 6: I think the fastest piece of growth going back to

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Speaker 6: I think the nineteen nineties. So absolutely just staggering levels

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Speaker 6: demand for these types of chips, all of which are

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Speaker 6: being used in the AI infrastructure, and that is really

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Speaker 6: translating in a pretty direct way to the stock prices.

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Speaker 6: I think Micron is up more than seventy percent in

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Speaker 6: May by itself, which is the biggest one month jump

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Speaker 6: since December nineteen eighty seven. Just to give you a

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Speaker 6: sense of just how quickly these stocks are moving.

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Speaker 4: Up, let's look at about sk Heinex how much it

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Speaker 4: moved up in the May number as well. They've almost

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Speaker 4: moved in lockstep, both of them up seventy percent in

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Speaker 4: the month of May. Sk high Inex Micron both at

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Speaker 4: more than two hundred percent so far year to date,

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Speaker 4: but what's notable is both of them are posting quarterly

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Speaker 4: revenue increases of.

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Speaker 5: More than two hundred percent.

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Speaker 4: So in many ways, Ammas out there seemed to be saying, look,

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Speaker 4: these are still actually fundamentally cheap.

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Speaker 6: Yeah, the levels of growth that these companies are seeing

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Speaker 6: is absolutely astronomical. And I can also add in sand Disk,

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Speaker 6: Western Digital, Seagate, all the memory in storage space are

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Speaker 6: just seeing absolutely huge demand. The evaluation picture is a

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Speaker 6: little bit tricky though. In fact, we have a story

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Speaker 6: coming out tomorrow, but I'll give you a sneak preview.

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Speaker 6: Micron multiple is trading under ten right now, ten times

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Speaker 6: forward earnings. That is extremely low, especially for company growing

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Speaker 6: this quickly. However, because memory has historically been quite cyclical,

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Speaker 6: there are some concerns that this low multiple might be

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Speaker 6: an indication of peak earnings. I've actually had someone say

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Speaker 6: to me that he would feel more comfortable if Micron

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Speaker 6: was really expensive right now, because I would indicate maybe

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Speaker 6: a trough level in earnings that are about to go ahead,

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Speaker 6: leading the stock up with it. So right now you

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Speaker 6: can certainly say that Micron is inexpensive. The question is

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Speaker 6: is AI changing the cyclical nature of memory overall? That

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Speaker 6: we are in some kind of new paradigm where maybe

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Speaker 6: Micron actually is as cheap as it looks, and this

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Speaker 6: isn't some kind of contrarian warning light.

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Speaker 3: I'll answer that Ryan, Yes, because in high bandwidth memory

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Speaker 3: and the design of the SEC the chiplet, it's directly

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Speaker 3: embedded into the GPU.

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Speaker 2: And what's so crazy about all of this.

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Speaker 3: We're talking a lot about supply constraints, a shortage of GPUs,

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Speaker 3: but it's not because of the GPU die. It's not

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Speaker 3: because in video can't get enough of them necessarily. It's

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Speaker 3: the corresponding high bandwidth memories. Not there unpack what UBS

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Speaker 3: said in its note about that, particularly on the valuation.

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Speaker 3: It said, one reason with doubling our price target is

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Speaker 3: we think that people will start to appreciate that.

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Speaker 6: Yeah, so UBS came out, I think that actually tripled

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Speaker 6: their price target. I think the estmate was that this

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Speaker 6: would eventually be a one point eight trillion dollar company.

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Speaker 6: So even though we've seen some huge gains in the stocks,

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Speaker 6: UBS expects the upside. It sees a lot more additional

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Speaker 6: upside from here. What it said was that Micron really

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Speaker 6: deserves to have a multiple that's on par with Nvidia,

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Speaker 6: and I think it said it was looking for maybe

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Speaker 6: fifteen times estimated earnings, whereasas historically it gave it a

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Speaker 6: five times estimated earnings multiple. So they are saying that

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Speaker 6: Micron should be worth three times what it used to

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Speaker 6: consider a fair valuation for the stock. That is a

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Speaker 6: really significant change here, and it really is causing people

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Speaker 6: to reevaluate. How should we be valuating these companies, How

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Speaker 6: should we be considering the nature of the market, the

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Speaker 6: nature of this demand, and what is that mean for

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Speaker 6: growth going forward? Right now it's up in the air,

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Speaker 6: But so far people seem extremely optimistic and extremely positive.

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Speaker 4: Well broadly, we're seeing at the moment ry not a

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Speaker 4: single cell rating on either of these stocks. Despite that

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Speaker 4: more than two hundred percent crescendo so far this year.

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Speaker 5: We appreciate you.

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Speaker 4: As investors are pushing memory chants like Skhinex, like Microntu

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Speaker 4: record valuations. The race for advanced semiconductors also raises new

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Speaker 4: concerns of export controls. So Taiwanese prosecutors suspect three individuals

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Speaker 4: smuggled Nvidia AI chips to China through Japan. So, according

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Speaker 4: to sources, some more we go to Blomboth Senior Tech

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Speaker 4: editor Mike Sheppard to join us. This is once again

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Speaker 4: about super micro computer. This is about servers that are

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Speaker 4: somehow winding their way to China.

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Speaker 2: Well, that's right.

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Speaker 7: These three individuals are suspected of having falsified documents indicating

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Speaker 7: that the final destination for these devices was Japan, when

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Speaker 7: in fact, according to authorities, the ultimate buyer was in China.

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Speaker 2: So place.

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Speaker 7: Now, authorities managed to seize about fifty of these servers

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Speaker 7: before they were actually shipped, but it looks like at

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Speaker 7: least one shipment got through according to the reporting by

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Speaker 7: our colleagues Mackenzie Hawkins and Debbie Wu, who have been

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Speaker 7: all over this story from the start. Now, Caro, the

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Speaker 7: twist in this case is Japan. When we have been

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Speaker 7: reporting on and talking about some of the other chip

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Speaker 7: smuggling cases involving in Nvidia's hardware and products, they've typically

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Speaker 7: gone through some of the Southeast Asian economies like Thailand

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Speaker 7: and Singapore, and we haven't seen Japan really factor into this.

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Speaker 7: Japan has actually seen it's more of a place where

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Speaker 7: Chinese companies can rent computing power legally. It's a practice

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Speaker 7: that falls within the bounds permissible bounds of US export

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Speaker 7: controls through data centers in Japan, Chinese companies can simply

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Speaker 7: access all that AI compute simply by paying a rental

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Speaker 7: fee chev real quick.

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Speaker 3: Nvidia didn't respond to a requests for comment on this story.

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Speaker 3: But Jensenmong is Taiwan right now, and I believe somebody

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Speaker 3: asked him broadly about this issue very quick.

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Speaker 7: What did he say, Well, he was asked over the

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Speaker 7: weekend after those three individuals were detained whether super Micro

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Speaker 7: needed to do more to rein in some of the

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Speaker 7: concerns about chip smuggling, and he said, look, they need

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Speaker 7: to perhaps tighten up the ship when it comes to

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Speaker 7: compliance and oversight of their customers. And this is a

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Speaker 7: rare thing for the Nvidia CEO to say about one

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Speaker 7: of the company's partners, super Micro, and neither company, of course,

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Speaker 7: it's important to note, has been accused of any wrongdoing

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Speaker 7: in these or other cases. But they insisted that their

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Speaker 7: compliance is up up to par and that they are

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Speaker 7: doing more to strengthen it in the wake of the

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Speaker 7: charges that were filed against one of its co founders

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Speaker 7: earlier this year.

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Speaker 4: An unfolding story one you're all across. We so appreciate it.

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Speaker 4: Bloomberg's Mike Shephard. There, Look, we can continue to talk

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Speaker 4: to your politics and how it impacts the market, and

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Speaker 4: we continue to talk about US tech stocks that are

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Speaker 4: holding onto me and record highs with a whole lot

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Speaker 4: of enthusiasm for the AI trade.

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Speaker 5: But there's some pressure out of that.

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Speaker 4: Let's talk about it when that's Tegna CEO se I

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Speaker 4: have left Tegna Investments and just pivoting back to how

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Speaker 4: we started a story that Micron and sk Heinex and

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Speaker 4: now in the trillon dollar club that we're still seeing

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Speaker 4: AI infrastructure bottlenecks. Nancy, Is this just continuing to feed

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Speaker 4: your optimism around the sector.

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Speaker 8: Yeah, I mean, Carolyn, we're we're ready for a correction

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Speaker 8: because we get one about once a year, and this

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Speaker 8: has been pretty frothy. But when you go back and

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Speaker 8: look when there's been an eight week run like this,

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Speaker 8: historically stocks are up over twelve around twelve percent a

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Speaker 8: year later, and that's Bespoke's work, not mine.

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Speaker 9: So I think you have to be you have to

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Speaker 9: be nimble.

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Speaker 8: And you know, we added to Micron at three sixty

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Speaker 8: six just a few months ago and felt late and

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Speaker 8: of course we weren't, at least not for the moment.

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Speaker 8: What you have to do is be diligent about trimming

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Speaker 8: things back, and that is what we've been doing, you know,

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Speaker 8: taking some gains, sitting and waiting, reallocating to names that

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Speaker 8: we think, you know, will continue to benefit. But yeah,

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Speaker 8: this is a productivity driven ball market.

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Speaker 9: I think it will continue for some time.

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Speaker 8: We will probably get a correction that will be yet

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Speaker 8: another opportunity like deep Seek was, like the first quarter

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Speaker 8: of this year was. But you want to stick with

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Speaker 8: the high quality names and you want it. You don't

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Speaker 8: want to chase the latest because the hedge funds are

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Speaker 8: going to pivot here pretty quickly, and we saw that

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Speaker 8: from hardware to software and now back to hardware.

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Speaker 3: Nancy, I'm going to show you a chart, and for

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Speaker 3: those that listen to Bloomberg Tech as a podcast, it's

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Speaker 3: a squiggly line that shows a very sharp up with trajectory.

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Speaker 3: From the end of March to present day. We've gone

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Speaker 3: from about twenty two five hundred points to almost thirty thousand. Yes,

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Speaker 3: if you tell anyone I quoted points on the I'll

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Speaker 3: deny it. You just said that you're ready for a

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Speaker 3: correction in the Micron story was about ubs almost tripling

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Speaker 3: its price target.

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Speaker 2: How are you going to play Micron in a correction environment?

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Speaker 9: Yeah, I mean we are going to be trimming it

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Speaker 9: here shortly and we will likely add back to it.

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Speaker 8: Beware of people that tell you, you know, old tech

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Speaker 8: is dead or software is dead, because these companies find ways.

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Speaker 8: I understand this is more of a demand issue, but

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Speaker 8: they do find ways to pivot, and so I think

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Speaker 8: what you want to be doing is taking some gains

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Speaker 8: when you can and then looking for opportunities when the

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Speaker 8: market pulls back. We called for a bottom on April fourth.

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Speaker 8: I mean, that's not really our business, but we did.

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Speaker 8: We were a little bit late, but that is how

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Speaker 8: this market has been moving. And so it's quickly and

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Speaker 8: it's rapid, and it's violent to the upside.

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Speaker 2: And so don't.

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Speaker 8: Confuse that with you know, being a genius, because what

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Speaker 8: the market giveth, it will also take it the way.

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Speaker 9: So you just want to remain nimble.

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Speaker 4: Remaining nimble and thinking about what your long term bet

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Speaker 4: saw Like Nancy, you always bring us our twelve best

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Speaker 4: ideas portfolio, and within that is some software is service

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Speaker 4: now for example, and boy of those names been beaten up,

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Speaker 4: but they have clawed their way back from some of

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Speaker 4: the bottoms.

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Speaker 5: But tonight we get we get it called salesforce numbers.

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Speaker 4: Will that fundamentally show that these AI related disruptible names

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Speaker 4: can hang on in there?

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Speaker 9: I think so, Caroline. It's an important report to be sure.

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Speaker 8: And you know what we've done is we've within our

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Speaker 8: twelve best We have a six for twenty six that's

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Speaker 8: up forty percent this year and includes names like CrowdStrike.

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Speaker 8: Last year we had service Now in that five for

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Speaker 8: twenty five and it did abysmally, but the portfolio is

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Speaker 8: still outperformed. So that is what you have to think about,

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Speaker 8: is that the right name is Microsoft going to be

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Speaker 8: a winner?

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Speaker 2: I think so.

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Speaker 9: I'm more concerned about Salesforce, which we don't own.

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Speaker 8: We exited Adobe for obvious reasons a while back, and

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Speaker 8: I think that's what you have to consider who will win.

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Speaker 8: And I do think if you own the platform, you'll

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Speaker 8: be a beneficiary of AI. And I do think service

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Speaker 8: now is well positioned, despite how difficult of a name

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Speaker 8: it has been to own s.

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Speaker 3: We're in this period now where we've gone through earning season,

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Speaker 3: including through in video, So we're not now fixed on

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Speaker 3: the Kapex figures. Maybe we still are in videos set

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Speaker 3: its piece what happens in this interim period, like what

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Speaker 3: is the catalyst in either direction for the market.

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Speaker 9: That's the right question ed. I think that is why

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Speaker 9: we think we may be right for a correction.

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Speaker 8: What will happen is we will turn our attention the

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Speaker 8: market's fickle, and then we'll start focusing on the Fed.

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Speaker 8: We'll go back to is Horn moves open and there

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Speaker 8: will be hand ringing, and I think that will drive

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Speaker 8: the narrative because it's too early for the midterms. So

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Speaker 8: we are putting in place some protection for our clients

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Speaker 8: and it may be money not well spent if the

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Speaker 8: market continues to accelerate, but it never does go straight up,

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Speaker 8: So I think.

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Speaker 9: You want to pay attention to FED speak.

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Speaker 8: I hope there's less of it as we move forward

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Speaker 8: from here. I mean that is a promise that Kevin

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Speaker 8: worsh made, and let the FED do their job and

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Speaker 8: then and there will also be on inflation watch, which

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Speaker 8: which I think is actually not the bigger problem that

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Speaker 8: we face from an economic standpoint.

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Speaker 9: But there are many who disagree.

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Speaker 5: With me on that what about it wrong.

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Speaker 8: Yeah, I mean I think I think that's problematic on

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Speaker 8: so many levels. But you know, we're getting all the

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Speaker 8: peace talk, but we haven't seen a lot of progress.

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Speaker 8: So I think for most investors the question is when

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Speaker 8: does when do the straits of straight of horror moves open.

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Speaker 9: When that happens, then I think you'll see a melt up.

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Speaker 8: But until then you'll see a lot of hand ringing

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Speaker 8: and that you know, that is what markets do, and

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Speaker 8: that is what the algos and the hedge funds exacts

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Speaker 8: in the near term. So volatility, remember, friend of long

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Speaker 8: term investor, use it to your advantage.

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Speaker 9: Because earnings growth has been amazing. We've also seen guidance raised.

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Speaker 8: We've been steadfast in the tech trade for the last

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Speaker 8: three years while many wrote it off. So we're pretty

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Speaker 8: happy with you know, the way our portfolios have performed

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Speaker 8: as a result of that.

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Speaker 3: Nancy Tegler of Laffetango Investments back on v tech, Thank

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Speaker 3: you very much. Now coming up, we're going to speak

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Speaker 3: with the X Prize founder Peter Demandez as SpaceX celebrates

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Speaker 3: a major starship milestone.

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Speaker 2: This is blombog Tech.

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Speaker 3: SpaceX's latest successful starship launch marks a major milestone for

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Speaker 3: the company's next generation rocket program and a critical step

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Speaker 3: towards the longtime growth strategy that was laid out in

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Speaker 3: its recent IPO filing. Also crucial elon Musk, the S

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Speaker 3: one made it absolutely clear with an outsized pay package,

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Speaker 3: majority voting control for the CEO bloemeg intelligence writing. The

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Speaker 3: document highlights some significant governance concerns that still might be

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Speaker 3: overshadowed by investor's fear of missing out. FOMO on the

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Speaker 3: biggest IPO ever here to talk about it. The importance

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Speaker 3: of Starship Musk the perspective of an early SpaceX investor.

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Speaker 3: Peter diamandis founder of X Prize, and we're trying again.

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Speaker 3: You're on the show Friday, and we had to cut

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Speaker 3: our conversation short. But then on Friday night, Starship twelve

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Speaker 3: Flight Test Mission V three. Your reaction to it, to

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Speaker 3: how that went.

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Speaker 10: Well, Listen the fact that it was a brand new vehicle,

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Speaker 10: brand new engines, the most advanced engineering ever built by humans.

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Speaker 10: It was incredible success. You know what people, if do

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Speaker 10: you realize, is that you can't test a rocket a

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Speaker 10: little bit at a time. You have to test the

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Speaker 10: entire system and the fact that the launch took off

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Speaker 10: with its version three of its engines and the entire

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Speaker 10: vehicle the largest, most powerful engineering system ever launched by humans.

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Speaker 2: It was great.

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Speaker 10: We're going to see Starship making incremental flights, getting better

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Speaker 10: and better until the time where the entire vehicle is refliable,

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Speaker 10: refuelable on orbit and becomes a platform to go to

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Speaker 10: the Moon, go to Mars, go beyond.

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Speaker 3: Why Starship is also its capability and payload to orbit

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Speaker 3: for first starlink and then orbital data center. I wrote

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Speaker 3: at the beginning of the week about how clear the

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Speaker 3: S one was about the limitation of SpaceX's current access

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Speaker 3: to compute and how much it's going to need in

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Speaker 3: the future. You then had an exchange with Elon Musk

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Speaker 3: I think in the last twenty four hours, right or

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Speaker 3: forty eight hours about that exact issue. What was the

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Speaker 3: point you were trying to relate to Elon there?

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Speaker 10: The point is that he's not just built This is

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Speaker 10: not just a rocket company, right, This is a vertically

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Speaker 10: integrated satellite network, global broadband, sovereign communications, AI, compute and

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Speaker 10: ultimately off planet infrastructure. You know, he is building a

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Speaker 10: hyperscaler Uh, not just an AI system, So his ability

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Speaker 10: to succeed as a company goes beyond just the you know,

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Speaker 10: groc is an AI system. He's providing the infrastructure for

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Speaker 10: a large number of the frontier labs out there. You know,

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Speaker 10: And what people need to realize about this company is

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Speaker 10: it's the It isn't just a little bit ahead of

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Speaker 10: the entire launch industry on planet Earth. It's orders of

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Speaker 10: magnitude ahead beyond anything else, and everything we hold a

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Speaker 10: value on Earth, metals, minerals, energy, real estate is in

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Speaker 10: near infinite quantities in space, and so what we're buying

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Speaker 10: is the next you know, the global economy, you know,

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Speaker 10: two dot oh and three dot O. As we look

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Speaker 10: at into SpaceX.

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Speaker 4: Go global, Peter, because I know you can, and we're

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Speaker 4: please that you do. There's a lot of hand ringing

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Speaker 4: and almost people feeling that every turn, the US uses

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Speaker 4: China as the excuse as to why we need less regulation,

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Speaker 4: why we need to go full throttle, why we need

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Speaker 4: to win quote unquote how much you seeing a space

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Speaker 4: race US China and how much a SpaceX managed to

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Speaker 4: dominate their visa v not just US competition, you.

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Speaker 10: Know, we humans love competition and it drives us forward.

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Speaker 10: And so if you think about this, you know, it

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Speaker 10: is the US versus the Soviets and the Russians in

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Speaker 10: the you know, fifty years ago, we're doing that same

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Speaker 10: thing again, but this time it's beyond just a political race.

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Speaker 10: It's an economic race.

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Speaker 2: Again.

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Speaker 10: We're building out huge revenue engines as we're going forward,

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Speaker 10: whether it's going to be mining the Moon for resources

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Speaker 10: or mining the asteroids for resources. We're also going to

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Speaker 10: be building out a level of global compute infrastructure in

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Speaker 10: Earth orbit. And again, no one was talking about this

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Speaker 10: a year ago, and today every major hyperscaler is we

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Speaker 10: see anthropic buying into XAIS or space XAIS data centers

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Speaker 10: on Earth. But they're also going to need that's going

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Speaker 10: to be given for morbit.

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Speaker 4: Look, you're a man who's driven by trying to solve

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Speaker 4: the world's most pressing problems. You're also a man who

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Speaker 4: happened to have got into SpaceX and Google and other

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Speaker 4: key companies very early.

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Speaker 5: Well at this moment where people.

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Speaker 4: Are questioning how it helps them, how is this being

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Speaker 4: democratized in some way? How are we solving the world's

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Speaker 4: greatest problems for everyone, not just the few? Peter, How

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Speaker 4: are you thinking about that, particularly when we look at

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Speaker 4: a listing of a company that is already so valuable.

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Speaker 5: Is that much left on the table in terms.

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Speaker 4: Of democratization and buying of shares by retail investors?

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Speaker 10: Sure, so let's hit the point you made first about

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Speaker 10: solving the world's biggest problems. The single most powerful thing

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Speaker 10: we humans have is our intelligence. We're about to see

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Speaker 10: human intelligence increased by not just ten or one hundredfold,

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Speaker 10: a millionfold, a billionfold, right, It's the ability for us

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Speaker 10: to discover breakthroughs across physics and chemistry and biology, material sciences.

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Speaker 10: All of these things are going to be driven by

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Speaker 10: the use of these AI systems, And so I don't

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Speaker 10: think people understand how rapidly the economy is going to

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Speaker 10: grow on the back of AI. We're going to be

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Speaker 10: solving aging as a fundamental right. What is it worth

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Speaker 10: if you can add thirty healthy years and then those

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Speaker 10: extra thirty healthy years on your life by you the

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Speaker 10: next fifty healthy years or one hundred healthy years, what

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Speaker 10: is that worth? Individuals? When we get to room superconducting,

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Speaker 10: when we get to new ways of growing food, you know,

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Speaker 10: twice as fast, five times faster, healthier, we're heading towards

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Speaker 10: a world of abundance across everything, food, water, energy, healthcare, education,

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Speaker 10: all of these elements. You know, when I interviewed Elon

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Speaker 10: on my Moonshots podcast at the beginning of this year

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Speaker 10: and then again in March, what he talked about, and

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Speaker 10: I believe this is we're going to see double and

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Speaker 10: then triple digit GDP growth. And this is happening not

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Speaker 10: because we're working harder or we humans are smarter. It's

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Speaker 10: on the back of AI and humanoid robotics. One of

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Speaker 10: the things he said was that we're entering a world

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Speaker 10: where AI and robots are going to create so much,

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Speaker 10: so much products, so much availability that we could not

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Speaker 10: want enough. Now, this sounds like, you know, a techno

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Speaker 10: utopian vision, but we have to realize that all of

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Speaker 10: the progress that we've seen in humanity, we're living lives

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Speaker 10: today that are godlike. Compare it to our parents and grandparents.

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Speaker 3: Yes, let me jump into you just said thank you

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Speaker 3: for vote January six for Elon at length and then

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Speaker 3: again in March, and what you just said about robots.

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Speaker 3: There is broad speculation right now about the prospect of

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Speaker 3: a post IPO SpaceX merging with Tesla on January thirtieth.

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Speaker 2: January thirty, if I.

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Speaker 3: Reported they'd held talks prior to the Xai transaction, you

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Speaker 3: say one hundred percent. I mean, what are you learning

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Speaker 3: from those two conversations? What do you know about how real?

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Speaker 2: That is? Why it makes sense.

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Speaker 10: It makes sense because it consolidates Elon's control. Today as

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Speaker 10: reporting the IPO in the S one, you know, there's

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00:23:35,160 --> 00:23:37,679
Speaker 10: super voting rights that he has and of course is

439
00:23:37,720 --> 00:23:43,160
Speaker 10: inside owners. I think it's like, you know, eighty plus

440
00:23:43,200 --> 00:23:47,320
Speaker 10: percent voting control. He doesn't have that in Tessla, and

441
00:23:47,359 --> 00:23:49,800
Speaker 10: by combining the companies, I think he'll have that. He'll

442
00:23:49,800 --> 00:23:54,160
Speaker 10: have the ability to operate across all of this infrastructure

443
00:23:54,440 --> 00:23:59,800
Speaker 10: and you know the a fleet of cybercabs, all of

444
00:23:59,800 --> 00:24:04,720
Speaker 10: it Tesla vehicles out there that have compute capability on them,

445
00:24:04,800 --> 00:24:08,200
Speaker 10: have power on them as well. We're creating a global

446
00:24:08,200 --> 00:24:13,000
Speaker 10: infrastructure on the ground, in space. So it just consolidates control.

447
00:24:13,119 --> 00:24:15,880
Speaker 10: It makes his ability to implement his vision a lot

448
00:24:15,920 --> 00:24:18,840
Speaker 10: more efficient. So you know, I put it as not

449
00:24:18,920 --> 00:24:21,080
Speaker 10: a matter of if and only a matter of when

450
00:24:21,080 --> 00:24:23,840
Speaker 10: those two companies come together. And also because there are

451
00:24:23,920 --> 00:24:27,000
Speaker 10: valued public companies, you can make that merger happen a

452
00:24:27,080 --> 00:24:30,960
Speaker 10: lot easier than if you're combining private companies and arguing

453
00:24:30,960 --> 00:24:31,720
Speaker 10: about valuation.

454
00:24:33,160 --> 00:24:36,840
Speaker 4: Peter jmnis X Prize founder, fascinating to have some time

455
00:24:36,880 --> 00:24:39,320
Speaker 4: with you and the vision of where spaces goes and

456
00:24:39,359 --> 00:24:39,960
Speaker 4: long win Tesla.

457
00:24:40,000 --> 00:24:40,720
Speaker 5: We appreciate it.

458
00:24:40,800 --> 00:24:42,600
Speaker 4: Now coming up, we're going to be joined by the

459
00:24:42,600 --> 00:24:46,320
Speaker 4: CEO of Cognition and discussing the AI startup's latest fundraise

460
00:24:46,480 --> 00:24:49,959
Speaker 4: to power the first AI software engineer as they call it,

461
00:24:50,000 --> 00:24:53,440
Speaker 4: Devon or many devans. There's a cracking, big valuation on

462
00:24:53,480 --> 00:24:56,000
Speaker 4: the back of this. I'm excited about that conversation coming

463
00:24:56,080 --> 00:24:58,159
Speaker 4: up next with San Francisco and New York and with

464
00:24:58,240 --> 00:25:00,800
Speaker 4: stocks under pressure in the broader tech ecosystem.

465
00:25:00,880 --> 00:25:01,800
Speaker 5: This is blombg Tech.

466
00:25:31,040 --> 00:25:33,640
Speaker 4: Welcome back to Bloomberg Tech, and we pull back from

467
00:25:33,680 --> 00:25:35,959
Speaker 4: some of our record highs today we turn our attention

468
00:25:36,000 --> 00:25:38,360
Speaker 4: to what's happening with the Middle East. Will there be

469
00:25:38,400 --> 00:25:40,320
Speaker 4: some sort of piece still between the US and Iran?

470
00:25:40,320 --> 00:25:43,560
Speaker 4: There are conflicting we'll move music around it in newsflow,

471
00:25:43,840 --> 00:25:46,640
Speaker 4: and the market just sells off a little bit in that.

472
00:25:46,520 --> 00:25:47,080
Speaker 5: I have a storm.

473
00:25:47,080 --> 00:25:48,919
Speaker 4: We're currently off by four ten percent on the nastat

474
00:25:48,920 --> 00:25:51,080
Speaker 4: one hundred coming off of yesterday's record high. We're looking

475
00:25:51,080 --> 00:25:54,080
Speaker 4: at the semiconductors, particularly under pressure video and the like,

476
00:25:54,200 --> 00:25:55,920
Speaker 4: yanking it down too and a half percent, but remember

477
00:25:55,960 --> 00:25:58,560
Speaker 4: it's up thirteen percent prior to this on a five.

478
00:25:58,400 --> 00:26:01,040
Speaker 5: Day winning streak. So we take a but we don't

479
00:26:01,119 --> 00:26:01,720
Speaker 5: take a pause.

480
00:26:01,880 --> 00:26:04,960
Speaker 4: One key name, Micron, is still managing to cling into

481
00:26:04,960 --> 00:26:07,240
Speaker 4: the green RUPs seven tenths of a percent. This is

482
00:26:07,280 --> 00:26:08,960
Speaker 4: as they hit a trillion dollar figure.

483
00:26:09,080 --> 00:26:09,159
Speaker 7: Ed.

484
00:26:09,280 --> 00:26:11,200
Speaker 4: This is as we start to see the real focus

485
00:26:11,359 --> 00:26:14,400
Speaker 4: on high bandwidth memory that saw also sk Heinex run

486
00:26:14,480 --> 00:26:14,960
Speaker 4: up so far.

487
00:26:16,000 --> 00:26:19,159
Speaker 3: Let's get back to today's big number, one trillion dollars

488
00:26:19,200 --> 00:26:22,120
Speaker 3: in climbing. That's the market cap memory chip giants sk

489
00:26:22,200 --> 00:26:25,240
Speaker 3: Heenez and Micron have reached and his carriages outline.

490
00:26:25,240 --> 00:26:26,919
Speaker 2: Micron still has momentum.

491
00:26:27,119 --> 00:26:31,000
Speaker 3: Investors are piling into companies that are powering the AI boom.

492
00:26:31,200 --> 00:26:33,760
Speaker 3: Let's get more Micron and sk Heiniez Boombozi and King,

493
00:26:33,760 --> 00:26:35,679
Speaker 3: who leads our coverage of semiconductors.

494
00:26:35,880 --> 00:26:36,560
Speaker 2: You are so funny.

495
00:26:36,600 --> 00:26:38,480
Speaker 3: You and I go to all these conferences and speak

496
00:26:38,520 --> 00:26:41,879
Speaker 3: to all these people in industry, and if you do

497
00:26:41,960 --> 00:26:44,160
Speaker 3: it from their perspective, none of this is a surprise,

498
00:26:44,720 --> 00:26:47,160
Speaker 3: like as Jensen one would put it at c Ovin VideA,

499
00:26:47,280 --> 00:26:50,160
Speaker 3: he was trying to convince the memory makers years ago

500
00:26:50,560 --> 00:26:53,480
Speaker 3: that this would happen. Now Here we are why do

501
00:26:53,520 --> 00:26:55,000
Speaker 3: we need so much high bandwidth memory?

502
00:26:55,119 --> 00:26:57,520
Speaker 11: Yeah, I mean, if you look at the forward estimates

503
00:26:57,520 --> 00:27:00,320
Speaker 11: for this company, Wall Street is bought in to this

504
00:27:00,480 --> 00:27:04,480
Speaker 11: massive sense of we need so much more equipment. There's

505
00:27:04,520 --> 00:27:07,280
Speaker 11: going to be trillions of dollars of spending happening on this,

506
00:27:07,720 --> 00:27:11,680
Speaker 11: and memory is an absolutely fundamental base layer of the technology.

507
00:27:11,960 --> 00:27:14,879
Speaker 11: If you believe that the industry and the economy is

508
00:27:14,960 --> 00:27:18,080
Speaker 11: changing to the extent that people like Jensen we are

509
00:27:18,119 --> 00:27:19,119
Speaker 11: saying it will.

510
00:27:19,359 --> 00:27:22,560
Speaker 4: And it seems like there's stereotypical oligopoly here. There's like

511
00:27:22,600 --> 00:27:25,119
Speaker 4: three key players that are rushing to try and for

512
00:27:25,240 --> 00:27:26,680
Speaker 4: the hole in high bandwidth memory.

513
00:27:26,720 --> 00:27:28,399
Speaker 5: Of course Dram sort of goes to the backseat a

514
00:27:28,440 --> 00:27:29,000
Speaker 5: little bit here.

515
00:27:29,040 --> 00:27:31,720
Speaker 4: But are we seeing any competitive threats because at the moment,

516
00:27:31,760 --> 00:27:35,280
Speaker 4: analysts all the community think keep buying these stocks. The

517
00:27:35,320 --> 00:27:37,400
Speaker 4: bottlenecks are going to last through twenty twenty seven.

518
00:27:38,200 --> 00:27:40,479
Speaker 11: Yeah, I mean. The other that's a good point, Caroline,

519
00:27:40,520 --> 00:27:41,920
Speaker 11: And the other way to look at that is why

520
00:27:42,000 --> 00:27:44,520
Speaker 11: there are only three companies left. The answer is because

521
00:27:44,560 --> 00:27:47,000
Speaker 11: this has been a horrible market for years. Right. We've

522
00:27:47,000 --> 00:27:48,280
Speaker 11: had some good years, but we've had a lot of

523
00:27:48,320 --> 00:27:51,560
Speaker 11: bad years as well. There's only three real providers because

524
00:27:51,560 --> 00:27:53,720
Speaker 11: it's so expensive, the bets are so big, and it's

525
00:27:53,760 --> 00:27:56,680
Speaker 11: so difficult to make us sustain living in this business.

526
00:27:56,680 --> 00:28:00,920
Speaker 11: There survivors, not necessarily thrivers, even though that's what's going

527
00:28:01,000 --> 00:28:01,640
Speaker 11: on right now.

528
00:28:02,000 --> 00:28:04,919
Speaker 3: Could you just educate the Bloombert audience a bit on

529
00:28:04,920 --> 00:28:08,199
Speaker 3: the history of memory. The idea was foom and bust

530
00:28:08,520 --> 00:28:12,159
Speaker 3: where memory principally went before there was this great demand

531
00:28:12,160 --> 00:28:13,399
Speaker 3: from the data center space.

532
00:28:13,560 --> 00:28:15,760
Speaker 11: Yeah, I mean, the key point is that this is

533
00:28:15,800 --> 00:28:19,200
Speaker 11: a commodity. One chip from one company can be swapped

534
00:28:19,200 --> 00:28:22,040
Speaker 11: out for another, so you effectively have a market, right,

535
00:28:22,119 --> 00:28:22,680
Speaker 11: Prices go.

536
00:28:22,680 --> 00:28:25,080
Speaker 2: Up and down, supply and demand prices exactly.

537
00:28:25,160 --> 00:28:27,800
Speaker 11: It's a commodity, right. And in the past, you know,

538
00:28:27,800 --> 00:28:31,320
Speaker 11: the big market was PCs and then it was smartphones,

539
00:28:31,359 --> 00:28:34,000
Speaker 11: and of course these are consumer devices by in lige,

540
00:28:34,000 --> 00:28:39,160
Speaker 11: so long term supply versus short term fluctuations in demand

541
00:28:39,640 --> 00:28:40,760
Speaker 11: was a recipe for disaster.

542
00:28:41,560 --> 00:28:44,000
Speaker 2: In Boxie and King, Thank you very much. Carry some

543
00:28:44,040 --> 00:28:44,440
Speaker 2: more news.

544
00:28:44,640 --> 00:28:46,880
Speaker 4: Yeah, it's time now for talking tech ed and first

545
00:28:46,920 --> 00:28:49,880
Speaker 4: up and FTE. Dance is planning just sharply increased capital

546
00:28:49,880 --> 00:28:51,920
Speaker 4: spending to lead the Chinese AI market.

547
00:28:52,000 --> 00:28:52,080
Speaker 7: Now.

548
00:28:52,120 --> 00:28:54,760
Speaker 5: The company is considering a seventy billion dollars.

549
00:28:54,520 --> 00:28:57,480
Speaker 4: This year to build out data centers, another AI infrastructure,

550
00:28:57,640 --> 00:29:00,160
Speaker 4: and it may boost capex roughly one hundred billion dollars

551
00:29:00,200 --> 00:29:03,120
Speaker 4: next year. As an update on the Samsung strike talks,

552
00:29:03,160 --> 00:29:06,440
Speaker 4: the company's union members rooted in favor of a compensation

553
00:29:06,520 --> 00:29:09,200
Speaker 4: deal that will hand Chip workers an average bonus about

554
00:29:09,200 --> 00:29:11,080
Speaker 4: three hundred and forty thousand dollars now.

555
00:29:11,120 --> 00:29:13,480
Speaker 5: The agreement avoids a strike that had threatened.

556
00:29:13,160 --> 00:29:17,480
Speaker 4: To disrupt global chip supply, and similarly, TSMC chief cc

557
00:29:17,640 --> 00:29:20,120
Speaker 4: Way told staff that they'll see more than a thirty

558
00:29:20,120 --> 00:29:23,360
Speaker 4: percent jump and profit sharing payouts this year on average,

559
00:29:23,560 --> 00:29:26,880
Speaker 4: according to a source. Whays comments come after some employees

560
00:29:27,000 --> 00:29:30,440
Speaker 4: voiced concerns over their incentive plans online and followed the

561
00:29:30,440 --> 00:29:31,520
Speaker 4: Samsung union deal.

562
00:29:31,400 --> 00:29:36,800
Speaker 3: There Okay, back to private markets, Cognition has raised over

563
00:29:36,840 --> 00:29:40,280
Speaker 3: a billion dollars at a twenty six billion dollar valuation.

564
00:29:40,440 --> 00:29:43,920
Speaker 3: Lux Capital, General, Catalyst and AVC led the new round.

565
00:29:44,360 --> 00:29:46,560
Speaker 3: Cognition CEO Scott, who was here to discuss the news.

566
00:29:46,560 --> 00:29:50,760
Speaker 3: We're also give an update on the company's AI codey agent, Devin,

567
00:29:51,320 --> 00:29:53,240
Speaker 3: not just one agent, like I think Caroline made a

568
00:29:53,280 --> 00:29:55,360
Speaker 3: good point, like it's an army of agents, and we'll

569
00:29:55,360 --> 00:29:58,440
Speaker 3: get to that. Start with some basic Scott, A billion dollars,

570
00:29:58,640 --> 00:29:59,360
Speaker 3: big valuation.

571
00:30:00,080 --> 00:30:00,800
Speaker 2: Why'd you do that?

572
00:30:01,200 --> 00:30:03,200
Speaker 12: Yeah, yeah, absolutely well, thank thank you so much for

573
00:30:03,280 --> 00:30:05,840
Speaker 12: having me back. A few different reasons. First of all,

574
00:30:06,480 --> 00:30:08,240
Speaker 12: you know, the growth that we've seen in the business

575
00:30:08,240 --> 00:30:10,440
Speaker 12: has been incredible, and I think really across the board,

576
00:30:10,440 --> 00:30:12,440
Speaker 12: what we're seeing is that AI.

577
00:30:12,240 --> 00:30:14,240
Speaker 2: Is doing real work at real companies everywhere.

578
00:30:14,760 --> 00:30:16,600
Speaker 12: And you know, every company in twenty twenty six is

579
00:30:16,640 --> 00:30:19,160
Speaker 12: a software company, and so we work with, for example,

580
00:30:19,320 --> 00:30:21,400
Speaker 12: the top five health insurance in the United States. We're

581
00:30:21,400 --> 00:30:24,120
Speaker 12: seeing folks building way more tooling for all of their

582
00:30:24,160 --> 00:30:26,840
Speaker 12: care providers. They're able to cut down on price and

583
00:30:26,840 --> 00:30:30,000
Speaker 12: cover more people. We're working with banks on delivering software

584
00:30:30,000 --> 00:30:32,920
Speaker 12: and making sure to give their customers access to what

585
00:30:32,960 --> 00:30:35,800
Speaker 12: they need right. We're seeing this with the Treasury and

586
00:30:35,880 --> 00:30:38,600
Speaker 12: NASA as well, and so a couple of reasons for

587
00:30:38,600 --> 00:30:38,960
Speaker 12: the raise.

588
00:30:39,000 --> 00:30:41,160
Speaker 2: I think, first of all, we.

589
00:30:41,080 --> 00:30:43,160
Speaker 12: Want to continue to grow aggressively and this really allows

590
00:30:43,200 --> 00:30:45,080
Speaker 12: us to do that. It allows us to scale our compute,

591
00:30:45,120 --> 00:30:47,000
Speaker 12: it allows us to grow the team and so on.

592
00:30:47,160 --> 00:30:50,040
Speaker 12: Second of all, it allows us to stay independent and

593
00:30:50,080 --> 00:30:52,959
Speaker 12: to really continue as an independent business, which is really

594
00:30:53,000 --> 00:30:53,960
Speaker 12: really important for us.

595
00:30:54,440 --> 00:30:56,240
Speaker 2: It's going well as an independent business.

596
00:30:56,280 --> 00:30:58,680
Speaker 3: Like, what's interesting talking to you over let's say an

597
00:30:58,680 --> 00:31:02,200
Speaker 3: aggregate over a period of year is to trap growth.

598
00:31:02,360 --> 00:31:02,640
Speaker 12: Yeah.

599
00:31:02,720 --> 00:31:04,840
Speaker 3: Right, So when you first start coming on the show,

600
00:31:04,920 --> 00:31:07,720
Speaker 3: like beginning of twenty five to twenty four, the revenue.

601
00:31:07,480 --> 00:31:09,680
Speaker 2: Run rate was a few million with respect.

602
00:31:09,920 --> 00:31:12,080
Speaker 3: Then exactly a year ago, you're kind of in a

603
00:31:12,160 --> 00:31:15,840
Speaker 3: run rate of about thirty seven million dollars. Where's your

604
00:31:15,840 --> 00:31:16,640
Speaker 3: revenue run rate now?

605
00:31:16,720 --> 00:31:18,760
Speaker 12: Yeah, so we're getting close to five hundred million today.

606
00:31:19,480 --> 00:31:21,480
Speaker 12: As you said, we've only been in business for about

607
00:31:21,480 --> 00:31:22,840
Speaker 12: two years. And I think a lot of what it

608
00:31:22,880 --> 00:31:25,360
Speaker 12: speaks to is just how much demand there is out

609
00:31:25,400 --> 00:31:27,120
Speaker 12: there for all of this. And you know, there's about

610
00:31:27,160 --> 00:31:29,440
Speaker 12: thirty thirty five million software engineers in the world today.

611
00:31:29,680 --> 00:31:31,480
Speaker 12: We want to make all of them ten times more efficient,

612
00:31:31,520 --> 00:31:33,239
Speaker 12: and then we think there is a lot more than

613
00:31:33,240 --> 00:31:34,480
Speaker 12: ten times more software to build.

614
00:31:35,360 --> 00:31:38,120
Speaker 4: There is so much demand, Scott, but there's also a

615
00:31:38,160 --> 00:31:40,960
Speaker 4: pretty crowded market when it thinks of startups. And admittedly

616
00:31:40,960 --> 00:31:42,840
Speaker 4: you've been talking about how labs are sort of buying

617
00:31:42,840 --> 00:31:44,800
Speaker 4: these startups, and we think about what deal Curse has

618
00:31:44,840 --> 00:31:46,920
Speaker 4: just been doing over with SpaceX.

619
00:31:46,960 --> 00:31:49,520
Speaker 5: But I'm interested as to how you see.

620
00:31:49,320 --> 00:31:52,160
Speaker 4: The threat from the big labs in and of themselves.

621
00:31:52,760 --> 00:31:54,920
Speaker 2: Yeah, yeah, absolutely. For us, it's actually the other way around.

622
00:31:55,320 --> 00:31:58,320
Speaker 12: I think for us it's you know, being fully independent

623
00:31:58,320 --> 00:32:00,160
Speaker 12: and fully neutral is actually the best way for us

624
00:32:00,200 --> 00:32:02,240
Speaker 12: to be aligned with our customers. And so we work

625
00:32:02,360 --> 00:32:05,080
Speaker 12: very closely with all these labs, Opening Eye Andthropic, but

626
00:32:05,120 --> 00:32:06,680
Speaker 12: also Google, Xai and so on.

627
00:32:07,240 --> 00:32:08,880
Speaker 2: We have deep relationships with them.

628
00:32:08,920 --> 00:32:11,320
Speaker 12: We work with them on research, and it allows us

629
00:32:11,360 --> 00:32:13,240
Speaker 12: to work with our customers and provide them the best

630
00:32:13,240 --> 00:32:15,520
Speaker 12: model for every different use case. And so Devin is

631
00:32:15,560 --> 00:32:18,200
Speaker 12: a compound system that works with all of these different models,

632
00:32:18,320 --> 00:32:22,480
Speaker 12: and because of that, we're able to be the Switzerland

633
00:32:22,680 --> 00:32:23,720
Speaker 12: in the equation here.

634
00:32:24,200 --> 00:32:26,960
Speaker 4: Switzerland that sometimes makes the most of the disruption when

635
00:32:26,960 --> 00:32:28,840
Speaker 4: it comes to talent and the like. I think about

636
00:32:29,000 --> 00:32:32,080
Speaker 4: what happened last year the Windsurf assets, the IP, the brand,

637
00:32:32,160 --> 00:32:36,360
Speaker 4: the employees after Google took well, the key CEO and

638
00:32:36,440 --> 00:32:39,400
Speaker 4: leadership of that company will more in a M and

639
00:32:39,480 --> 00:32:41,480
Speaker 4: A happen. Is that where some of the new funding

640
00:32:41,520 --> 00:32:43,400
Speaker 4: will come into perspective.

641
00:32:44,400 --> 00:32:46,320
Speaker 12: I'm sure there will be more, and you know there

642
00:32:46,320 --> 00:32:48,960
Speaker 12: will be different things that come up. It's for us,

643
00:32:49,000 --> 00:32:51,800
Speaker 12: you know, what we're personally most focused on is just

644
00:32:51,840 --> 00:32:53,080
Speaker 12: continue to grow the business and.

645
00:32:54,720 --> 00:32:55,520
Speaker 2: As best as we can.

646
00:32:55,640 --> 00:32:59,280
Speaker 3: You said, well, a heavy emphasis on independence and you

647
00:32:59,280 --> 00:33:02,719
Speaker 3: cooled yourselves the Switzerland of this space. Yes, you know,

648
00:33:03,280 --> 00:33:05,400
Speaker 3: what do you think will happen if SpaceX does it

649
00:33:05,520 --> 00:33:08,200
Speaker 3: acquire Cursor? Is the base question. But when I speak

650
00:33:08,240 --> 00:33:12,080
Speaker 3: to say the engineering teams at Nvidia, the reason Laydight

651
00:33:12,200 --> 00:33:15,440
Speaker 3: Cursor was the freedom to swap in and out the

652
00:33:15,520 --> 00:33:19,040
Speaker 3: underlying model depending on what your your coding objective was.

653
00:33:19,440 --> 00:33:22,440
Speaker 3: I suppose that's one reason why they like Devin Right,

654
00:33:22,880 --> 00:33:26,360
Speaker 3: But if Cursor becomes a part of space XAI, you know,

655
00:33:26,360 --> 00:33:29,440
Speaker 3: how do you see that changing the field data is

656
00:33:29,440 --> 00:33:30,680
Speaker 3: so critically important?

657
00:33:31,160 --> 00:33:34,200
Speaker 2: Right? And who you are beholden to? Yeah?

658
00:33:34,240 --> 00:33:36,240
Speaker 12: Absolutely, No, I mean it's a great question. I think

659
00:33:36,240 --> 00:33:38,040
Speaker 12: in practice, I think there are a lot of great

660
00:33:38,040 --> 00:33:40,760
Speaker 12: teams working on could, including of course the labs themselves.

661
00:33:41,200 --> 00:33:44,040
Speaker 12: I think what we see is that the ecosystem is

662
00:33:45,080 --> 00:33:47,080
Speaker 12: broad enough and vibrant enough that it makes sense for

663
00:33:47,120 --> 00:33:49,239
Speaker 12: there to be different players in different positions, and so

664
00:33:49,280 --> 00:33:51,720
Speaker 12: there are going to continue to be first party products

665
00:33:51,760 --> 00:33:54,360
Speaker 12: from the labs themselves. But as we're kind of saying,

666
00:33:54,520 --> 00:33:56,719
Speaker 12: you know, to your point, I think having the ability

667
00:33:56,760 --> 00:33:58,720
Speaker 12: to serve each of the different models, and not just

668
00:33:58,760 --> 00:34:01,120
Speaker 12: the ability, but also the new vitality in terms of

669
00:34:01,200 --> 00:34:03,680
Speaker 12: being incentivized to just serve whatever is the best model

670
00:34:03,680 --> 00:34:05,959
Speaker 12: for each case rather than a single you know, a

671
00:34:05,960 --> 00:34:08,880
Speaker 12: single series of models, I think is an important position

672
00:34:08,880 --> 00:34:09,120
Speaker 12: in the.

673
00:34:09,040 --> 00:34:09,800
Speaker 2: Space as well.

674
00:34:10,160 --> 00:34:14,160
Speaker 3: You would say that Devin is the first AI software engineer,

675
00:34:14,560 --> 00:34:17,359
Speaker 3: and we talked about the revenue run rate. Clearly that's

676
00:34:17,440 --> 00:34:20,920
Speaker 3: evidence of momentum and success. But are you able to

677
00:34:20,960 --> 00:34:24,680
Speaker 3: sort of give any data on how pervasive DEVN is,

678
00:34:24,920 --> 00:34:28,240
Speaker 3: how it has changed the structure of different engineering orgs

679
00:34:28,800 --> 00:34:31,759
Speaker 3: at software companies, at other technology companies for sure.

680
00:34:31,840 --> 00:34:34,120
Speaker 12: Yeah, I mean we're seeing this across the board. Where

681
00:34:34,239 --> 00:34:38,480
Speaker 12: as teams are adopting devon and coding agents on mass

682
00:34:38,920 --> 00:34:41,520
Speaker 12: that in practice they're able to.

683
00:34:41,440 --> 00:34:43,600
Speaker 2: Do much more and execute much more aggressively on road mass.

684
00:34:43,640 --> 00:34:45,359
Speaker 3: This is a new code or is it going back

685
00:34:45,400 --> 00:34:46,640
Speaker 3: over old code bases.

686
00:34:47,080 --> 00:34:49,600
Speaker 12: It's both and so as you can imagine, the large

687
00:34:49,600 --> 00:34:52,640
Speaker 12: majority of work is working on these existing codebases and

688
00:34:52,680 --> 00:34:55,560
Speaker 12: continue to build and add new features and so on.

689
00:34:55,719 --> 00:34:58,120
Speaker 12: But even internally at Cognition, for example, more than ninety

690
00:34:58,160 --> 00:34:59,759
Speaker 12: percent of the code that we write is written by

691
00:35:00,280 --> 00:35:02,040
Speaker 12: and so of course we're using devon all day when

692
00:35:02,080 --> 00:35:03,480
Speaker 12: we're going and building devon itself.

693
00:35:03,640 --> 00:35:08,520
Speaker 4: And even with that productivity, you've been scaling the amount

694
00:35:08,560 --> 00:35:09,360
Speaker 4: of people you hire.

695
00:35:09,400 --> 00:35:11,479
Speaker 5: Scott, just reflect on what.

696
00:35:11,400 --> 00:35:14,200
Speaker 4: This means in terms of how many software engineers we're

697
00:35:14,200 --> 00:35:17,800
Speaker 4: going to need. Like this ongoing anxiety is the disruption

698
00:35:17,840 --> 00:35:20,239
Speaker 4: that AI causes in all its ways and across all

699
00:35:20,239 --> 00:35:20,960
Speaker 4: these industries.

700
00:35:21,760 --> 00:35:24,479
Speaker 12: Yeah, No, I think what we'll see is, of course

701
00:35:24,480 --> 00:35:26,319
Speaker 12: the job will evolve over time, and we'll see some

702
00:35:26,320 --> 00:35:27,919
Speaker 12: of the skill sets change, but I think we will

703
00:35:27,960 --> 00:35:30,400
Speaker 12: have far more people doing this in building software and

704
00:35:30,400 --> 00:35:33,000
Speaker 12: building products, not less. And you know my favorite sat

705
00:35:33,040 --> 00:35:35,200
Speaker 12: on this personally is today there's about thirty or thirty

706
00:35:35,200 --> 00:35:37,799
Speaker 12: five million software engineers in the world. Just twenty twenty

707
00:35:37,800 --> 00:35:39,480
Speaker 12: five years ago, at the start of the century, it

708
00:35:39,560 --> 00:35:43,000
Speaker 12: was under one million, and that's clearly come with a

709
00:35:43,080 --> 00:35:45,640
Speaker 12: massive rise in the amount of software that we've produced,

710
00:35:45,680 --> 00:35:47,440
Speaker 12: and I think as we continue to make it more

711
00:35:47,440 --> 00:35:49,520
Speaker 12: and more efficient, we're actually just going to produce even

712
00:35:49,560 --> 00:35:50,800
Speaker 12: more software, not less.

713
00:35:51,000 --> 00:35:52,160
Speaker 2: Scope very very quick.

714
00:35:52,280 --> 00:35:54,520
Speaker 3: What's the goal you've set the team for the balance

715
00:35:54,560 --> 00:35:55,640
Speaker 3: of the year one metric?

716
00:35:56,200 --> 00:36:00,279
Speaker 12: Yeah, yeah, Look, I think for this year we firmly

717
00:36:00,280 --> 00:36:02,279
Speaker 12: intended crass a billion in revenue run rate. We want

718
00:36:02,320 --> 00:36:04,919
Speaker 12: to keep going for anther even beyond that, and from

719
00:36:04,920 --> 00:36:06,719
Speaker 12: there we just want to grow and share many of

720
00:36:06,880 --> 00:36:08,040
Speaker 12: the companies in the world that we can.

721
00:36:08,480 --> 00:36:11,760
Speaker 4: Cognition CEO Scott Wu, thank you very much for joining

722
00:36:11,800 --> 00:36:16,360
Speaker 4: us today. Now coming up, Salesforce Snowflake, both reporting earnings

723
00:36:16,360 --> 00:36:19,000
Speaker 4: after the closing bell, would discuss what to expect how's

724
00:36:19,000 --> 00:36:20,440
Speaker 4: AI disrupting their business models.

725
00:36:20,440 --> 00:36:21,239
Speaker 5: This is Bloomberg Tech.

726
00:36:34,520 --> 00:36:38,360
Speaker 3: We're watching shares of Salesforce up one point two percent,

727
00:36:38,480 --> 00:36:42,000
Speaker 3: set to report quarterly results this afternoon. Wall Street's watching

728
00:36:42,040 --> 00:36:45,040
Speaker 3: closely for science that the company's AI offerings can help

729
00:36:45,320 --> 00:36:49,040
Speaker 3: reignite revenue growth. Bloomberg's Brady Ford, who covers Salesforce, is

730
00:36:49,080 --> 00:36:51,520
Speaker 3: with us, and twenty four hours ago we were talking

731
00:36:51,560 --> 00:36:54,560
Speaker 3: about the idea that right now the AI agent story

732
00:36:54,640 --> 00:36:59,880
Speaker 3: is more marketing than real in terms of revenues. That

733
00:37:00,040 --> 00:37:02,640
Speaker 3: will be the test this evening, right is that kind

734
00:37:02,640 --> 00:37:03,399
Speaker 3: of what you're looking for.

735
00:37:03,800 --> 00:37:06,800
Speaker 13: It's all these as apocalypse spheres, right, That's what everyone's

736
00:37:06,840 --> 00:37:09,080
Speaker 13: been worried about for the last couple of quarters, and

737
00:37:09,120 --> 00:37:13,120
Speaker 13: tonight the only real way Salesforce can beat pack all

738
00:37:13,200 --> 00:37:16,600
Speaker 13: that skepticism, all the pessimism is showing that revenue is

739
00:37:16,640 --> 00:37:20,520
Speaker 13: accelerating and it's coming from these new AI offerings. We

740
00:37:20,680 --> 00:37:23,560
Speaker 13: haven't seen that yet. That's what folks are hoping for

741
00:37:23,560 --> 00:37:24,839
Speaker 13: in the back half of this year.

742
00:37:25,400 --> 00:37:27,799
Speaker 5: We've had that Agent Force was sort of offering.

743
00:37:27,480 --> 00:37:30,520
Speaker 4: One an eight one hundred million dollar revenue stream thus far.

744
00:37:30,600 --> 00:37:34,320
Speaker 4: But we're also seeing not bad revenue growth from Salesforce,

745
00:37:34,360 --> 00:37:36,080
Speaker 4: or at least predicted, but a lot of that's coming

746
00:37:36,080 --> 00:37:38,760
Speaker 4: from Informatica, right, from inorganic growth.

747
00:37:39,920 --> 00:37:42,840
Speaker 13: Yeah, that's been the classic debate with Salesforce for so long,

748
00:37:42,880 --> 00:37:45,040
Speaker 13: which is you know how much revenue growth is from

749
00:37:45,040 --> 00:37:48,879
Speaker 13: those organic products versus some of the acquisitions that's come

750
00:37:48,960 --> 00:37:50,240
Speaker 13: back with Informatica.

751
00:37:50,719 --> 00:37:51,440
Speaker 2: And yeah, eight.

752
00:37:51,360 --> 00:37:54,160
Speaker 13: Hundred million a year on Agent Force nothing to scoff at.

753
00:37:54,200 --> 00:37:55,759
Speaker 13: But at the end of the day, right now, if

754
00:37:55,800 --> 00:37:59,400
Speaker 13: you're an application company, and your revenue is decelerating.

755
00:38:00,120 --> 00:38:01,799
Speaker 5: Market is really going to punish you.

756
00:38:02,480 --> 00:38:05,520
Speaker 3: Ryan Blastellica Inequities team who you know, we're all very

757
00:38:05,560 --> 00:38:07,319
Speaker 3: close buddies, where they help us out a lot with

758
00:38:07,400 --> 00:38:10,680
Speaker 3: their their sort of stock coverage. They frame this is actually,

759
00:38:10,880 --> 00:38:12,240
Speaker 3: if this goes well, it could.

760
00:38:12,160 --> 00:38:15,359
Speaker 2: Change the story for the stock. What has the story been.

761
00:38:15,440 --> 00:38:17,879
Speaker 3: I mean, his salesforce been one of the I want

762
00:38:17,880 --> 00:38:20,799
Speaker 3: to say victims, but those under pressure from the SaaS

763
00:38:20,800 --> 00:38:22,040
Speaker 3: apocalypse kind of narrative.

764
00:38:22,120 --> 00:38:24,480
Speaker 13: I mean, it could change the narrative for the whole sector, right,

765
00:38:24,520 --> 00:38:27,920
Speaker 13: because salesforce is these SaaS companies. So when folks think

766
00:38:27,960 --> 00:38:32,120
Speaker 13: about the SaaS industry getting hurt by AI getting displaced,

767
00:38:32,200 --> 00:38:35,759
Speaker 13: you know, the idea that innovation and technology is no

768
00:38:35,840 --> 00:38:39,440
Speaker 13: longer happening at these SaaS companies like you know, an

769
00:38:39,440 --> 00:38:43,320
Speaker 13: Adobe or a salesforce. If they can show that that's changing,

770
00:38:43,520 --> 00:38:44,560
Speaker 13: that could be very meaningful.

771
00:38:45,520 --> 00:38:47,560
Speaker 4: But still, they hit a three year low on their

772
00:38:47,600 --> 00:38:50,040
Speaker 4: stock last month. They haven't recovered much and they're down

773
00:38:50,120 --> 00:38:53,120
Speaker 4: thirty percent year to date. So is there a narrative

774
00:38:53,560 --> 00:38:56,200
Speaker 4: what anecdotal evidence to fight back as some of what

775
00:38:56,320 --> 00:38:59,080
Speaker 4: you wrote Brody that it isn't actually working at agent

776
00:38:59,120 --> 00:39:02,399
Speaker 4: thoughts with in compliance offices, yet they can't sign off

777
00:39:02,400 --> 00:39:02,600
Speaker 4: on it.

778
00:39:02,640 --> 00:39:07,040
Speaker 13: For example, the big story I think is that the

779
00:39:07,160 --> 00:39:11,000
Speaker 13: technology is real, but it takes a long time to

780
00:39:11,080 --> 00:39:14,160
Speaker 13: implement at big corporations, right, I mean you or I

781
00:39:14,200 --> 00:39:17,120
Speaker 13: can go and chat GPT and do some you know,

782
00:39:17,200 --> 00:39:20,719
Speaker 13: whatever workflow you might do, but as a corporation, that's

783
00:39:20,880 --> 00:39:22,680
Speaker 13: very difficult to implement it widely.

784
00:39:23,320 --> 00:39:27,040
Speaker 4: In many ways, that compliance stickiness, though, makes makes salesforce

785
00:39:27,040 --> 00:39:27,560
Speaker 4: pretty sticky.

786
00:39:27,600 --> 00:39:29,680
Speaker 5: BLO makes pretty good. We appreciate you.

787
00:39:29,800 --> 00:39:31,480
Speaker 4: It's gonna be a busy evening after the bell. There's

788
00:39:31,520 --> 00:39:35,879
Speaker 4: also other stocks reporting, for example Marvel and fascinating chip stock.

789
00:39:35,920 --> 00:39:38,200
Speaker 4: Like this is in many ways about the focus on photonics,

790
00:39:38,239 --> 00:39:41,600
Speaker 4: on optics, on networking, but it's also think about that

791
00:39:41,600 --> 00:39:44,200
Speaker 4: two billion dollar investment in video made in but March

792
00:39:44,239 --> 00:39:45,920
Speaker 4: and Marvel Technology, how.

793
00:39:45,800 --> 00:39:48,000
Speaker 5: Have they been performing within videos backing?

794
00:39:48,880 --> 00:39:51,200
Speaker 3: Yeah, it's interesting. The stock's down so much, you know,

795
00:39:51,239 --> 00:39:53,319
Speaker 3: ahead of the earnings print. I don't see anything on

796
00:39:53,320 --> 00:39:54,440
Speaker 3: the Bloomberg.

797
00:39:56,760 --> 00:39:57,160
Speaker 5: This year.

798
00:39:57,239 --> 00:39:58,799
Speaker 2: Yeah, exactly. It's a high flight.

799
00:39:58,880 --> 00:40:01,560
Speaker 3: So in our conversations about custom silicon, we super focus

800
00:40:01,640 --> 00:40:05,400
Speaker 3: on broad com principally Marvel has XPU exactly the same idea.

801
00:40:05,480 --> 00:40:08,600
Speaker 3: Rather than selling a chip, which is it, it partners

802
00:40:08,600 --> 00:40:11,440
Speaker 3: with a hyperscala or a technology company and says we

803
00:40:11,520 --> 00:40:13,960
Speaker 3: will do this with you custom silicon. There's also some

804
00:40:14,280 --> 00:40:16,719
Speaker 3: examples that that might extend outside of the world the

805
00:40:16,800 --> 00:40:17,280
Speaker 3: data centers.

806
00:40:17,280 --> 00:40:18,600
Speaker 2: We can talk about that at later date.

807
00:40:18,800 --> 00:40:20,840
Speaker 3: But yeah, if this is happening and we're in a

808
00:40:20,840 --> 00:40:23,520
Speaker 3: compute deficit, Marvel's a likely winner, and.

809
00:40:23,440 --> 00:40:24,880
Speaker 4: We'll see whether they can live up to some of

810
00:40:24,920 --> 00:40:27,440
Speaker 4: the expectations around their numbers, and there are some lofty

811
00:40:27,440 --> 00:40:29,560
Speaker 4: ones out there. But all of this at the moment

812
00:40:29,600 --> 00:40:33,160
Speaker 4: is around AI's obvious rapid growth, but it is actually

813
00:40:33,160 --> 00:40:37,480
Speaker 4: pushing global energy demand eb A skyward two, forcing electrical grids,

814
00:40:37,480 --> 00:40:40,480
Speaker 4: for example, to expand and modernized. Now companies from China

815
00:40:40,560 --> 00:40:44,200
Speaker 4: to Nigeria investing in new tech to power the future.

816
00:40:44,480 --> 00:40:46,040
Speaker 4: That's a focus of doing their primer this week.

817
00:40:46,080 --> 00:40:46,560
Speaker 5: Take a listen.

818
00:40:48,040 --> 00:40:50,239
Speaker 4: For a long time, rich countries haven't had to think

819
00:40:50,280 --> 00:40:54,000
Speaker 4: about their grids all that much. Their electricity demand has

820
00:40:54,000 --> 00:40:56,720
Speaker 4: been pretty much flat since the two thousands.

821
00:40:57,040 --> 00:40:58,560
Speaker 5: The times are changing.

822
00:41:00,080 --> 00:41:03,560
Speaker 3: Explosive growth of AI, the rapid build out of data centers.

823
00:41:03,680 --> 00:41:06,400
Speaker 2: They're consuming enormous amounts of energy.

824
00:41:06,520 --> 00:41:09,319
Speaker 13: A few have four companies now that are intending to

825
00:41:09,360 --> 00:41:12,120
Speaker 13: spend over three hundred billion dollars this year.

826
00:41:12,600 --> 00:41:15,839
Speaker 4: With industries like AI and EV's growing fast, the world

827
00:41:15,960 --> 00:41:19,160
Speaker 4: is predicted to use twice as much electricity by twenty fifty.

828
00:41:19,800 --> 00:41:23,640
Speaker 4: That's roughly a whole new USA's worth of electricity every

829
00:41:23,760 --> 00:41:27,040
Speaker 4: five years. To make all that power and get it

830
00:41:27,080 --> 00:41:29,399
Speaker 4: to where it needs to go, the world's grids need

831
00:41:29,480 --> 00:41:33,520
Speaker 4: to evolve. All that new infrastructure will cost billions of dollars,

832
00:41:33,880 --> 00:41:37,400
Speaker 4: but so did broadband internet and that's ended up creating

833
00:41:37,520 --> 00:41:42,200
Speaker 4: trillions of dollars of value. And some countries' grids are

834
00:41:42,239 --> 00:41:44,520
Speaker 4: evolving faster than others.

835
00:41:44,520 --> 00:41:47,680
Speaker 12: In China, power generation has gone up seven times since

836
00:41:47,719 --> 00:41:48,320
Speaker 12: two thousand.

837
00:41:48,680 --> 00:41:50,920
Speaker 2: The battle to build the best grid is a battle

838
00:41:50,960 --> 00:41:51,640
Speaker 2: to win the future.

839
00:41:52,280 --> 00:41:54,680
Speaker 3: Here more from the team at Bloomberg Originals on today's

840
00:41:54,719 --> 00:41:57,520
Speaker 3: episode of Primer that's tonight on Bloomberg at six pm

841
00:41:57,560 --> 00:42:01,120
Speaker 3: Eastern and on Bloomberg Originals at apm Okay. Coming up,

842
00:42:01,160 --> 00:42:04,480
Speaker 3: we hear from UBS Asia Pacific President ikbau Khan on

843
00:42:04,600 --> 00:42:07,440
Speaker 3: how he sees AI impacting jobs.

844
00:42:07,920 --> 00:42:08,919
Speaker 2: This is Bloomberg Tech.

845
00:42:23,960 --> 00:42:27,600
Speaker 3: UBS Asia Pacific President ikbaw Khan says AI will free

846
00:42:27,680 --> 00:42:31,600
Speaker 3: up capacity and improve productivity, but also have an impact

847
00:42:31,600 --> 00:42:34,840
Speaker 3: on jobs. He spoke exclusively to Bloomberg Stephen Engel on

848
00:42:34,880 --> 00:42:38,040
Speaker 3: the sidelines of the firm's Asian Investment conference in Hong Kong.

849
00:42:39,080 --> 00:42:42,000
Speaker 14: I think the opportunity that we're seeing now with technology

850
00:42:42,000 --> 00:42:47,279
Speaker 14: and with AI is very much around simplifying, speeding up

851
00:42:47,320 --> 00:42:51,839
Speaker 14: the processes, not cutting corners, but actually fundamentally improving the.

852
00:42:51,760 --> 00:42:53,560
Speaker 2: Process consistency of process.

853
00:42:53,680 --> 00:42:57,319
Speaker 14: Just think about documenting source of wealth of an individual.

854
00:42:57,400 --> 00:42:58,840
Speaker 2: It's a pretty complex task.

855
00:42:59,200 --> 00:43:01,719
Speaker 14: But if AI can help you contextualize that and help

856
00:43:01,760 --> 00:43:04,640
Speaker 14: you actually do that and ensure that there's consistency, you're

857
00:43:04,640 --> 00:43:07,799
Speaker 14: going to fundamentally improve the process in addition to what

858
00:43:07,800 --> 00:43:08,520
Speaker 14: you're doing today.

859
00:43:08,719 --> 00:43:13,480
Speaker 15: Nice segue, AI. It's in everyone's discussion book right now. Obviously,

860
00:43:13,520 --> 00:43:16,319
Speaker 15: we just had Jamie Diamond of JP Morgan talking about that.

861
00:43:16,440 --> 00:43:18,520
Speaker 15: We've heard some comments that he got a little bit

862
00:43:18,560 --> 00:43:22,000
Speaker 15: of blowback. Bill Winters at Standard Chartered saying it's going

863
00:43:22,080 --> 00:43:25,640
Speaker 15: to have a significant impact obviously on maybe some of

864
00:43:25,840 --> 00:43:27,840
Speaker 15: the rank and files in the banking industry. How do

865
00:43:27,880 --> 00:43:30,920
Speaker 15: you see AI over the next couple of years changing

866
00:43:30,960 --> 00:43:32,640
Speaker 15: the way you hire and who you hire.

867
00:43:33,520 --> 00:43:34,520
Speaker 2: So let's step back right.

868
00:43:34,560 --> 00:43:36,680
Speaker 14: I mean, clearly there's a lot of focus on AI.

869
00:43:37,120 --> 00:43:40,319
Speaker 14: We see high valuations around AI. There's a lot of

870
00:43:41,280 --> 00:43:46,279
Speaker 14: talk around the value chain, everything from actual lms to

871
00:43:46,440 --> 00:43:50,360
Speaker 14: data centers to respective foundations infrastructure. For US, at UBS,

872
00:43:50,360 --> 00:43:53,759
Speaker 14: we've been very focused on AI specifically, also led and

873
00:43:53,840 --> 00:43:57,840
Speaker 14: driven by Sanjo multiur Group CEO. We've implemented, for example,

874
00:43:57,880 --> 00:44:00,759
Speaker 14: copilot across the board as just one example, and I

875
00:44:00,760 --> 00:44:02,520
Speaker 14: have to tell you, in the last six months, I've

876
00:44:02,520 --> 00:44:05,960
Speaker 14: been using it more myself and I've been using it

877
00:44:06,000 --> 00:44:08,239
Speaker 14: personally as well as professionally and has actually made me

878
00:44:08,320 --> 00:44:11,480
Speaker 14: more efficient, more effective, and I think over time everybody

879
00:44:11,560 --> 00:44:12,800
Speaker 14: will become an AI native.

880
00:44:13,280 --> 00:44:16,000
Speaker 2: It comes down to adoption and application.

881
00:44:16,120 --> 00:44:20,000
Speaker 14: Fundamentally, we look at this as something that will really

882
00:44:20,120 --> 00:44:23,640
Speaker 14: enhance and increase capacity. What does that mean as we

883
00:44:23,719 --> 00:44:26,600
Speaker 14: become more productive, we can use that capacity to grow,

884
00:44:26,960 --> 00:44:29,560
Speaker 14: we can use that capacity to serve our clients better.

885
00:44:30,520 --> 00:44:33,200
Speaker 14: Imagine at UBS, when you come in through the door

886
00:44:33,200 --> 00:44:35,839
Speaker 14: as a client, you get onboarded and if you're eligible

887
00:44:35,920 --> 00:44:36,520
Speaker 14: to getting.

888
00:44:36,320 --> 00:44:37,360
Speaker 2: A solution or a service.

889
00:44:37,400 --> 00:44:40,920
Speaker 14: From a compliance and regulatory perspective, it comes down to

890
00:44:41,600 --> 00:44:42,920
Speaker 14: is that valuable to you or not?

891
00:44:43,040 --> 00:44:43,880
Speaker 2: And we will serve you.

892
00:44:44,160 --> 00:44:48,440
Speaker 14: Now, all of that process is curated, semi automated, manual,

893
00:44:48,719 --> 00:44:52,120
Speaker 14: people driven. You can aifi that if that's actually a

894
00:44:52,200 --> 00:44:54,960
Speaker 14: word to day right, and it is. You do that, you

895
00:44:55,000 --> 00:44:57,200
Speaker 14: can create a lot of capacity and that capacity can

896
00:44:57,239 --> 00:44:59,239
Speaker 14: be used to serve clients even better and grow.

897
00:44:59,360 --> 00:45:02,680
Speaker 15: What does it mean about top line job growth? Do

898
00:45:02,760 --> 00:45:05,160
Speaker 15: you cut back to get more efficient? How does it

899
00:45:05,239 --> 00:45:06,759
Speaker 15: work and how do you communicate that?

900
00:45:07,200 --> 00:45:08,359
Speaker 14: Look at the end of the day, as I said,

901
00:45:08,360 --> 00:45:11,360
Speaker 14: I think it's more about productivity capacity. Now, if we

902
00:45:11,400 --> 00:45:14,600
Speaker 14: can use that capacity to serve our clients better, gain

903
00:45:14,680 --> 00:45:18,560
Speaker 14: more share of wallet, grow faster, grow more, then the

904
00:45:18,600 --> 00:45:22,319
Speaker 14: impact on costs and jobs is going to be less. Now,

905
00:45:22,360 --> 00:45:25,040
Speaker 14: if we cannot, and this is an industry wide topic,

906
00:45:25,239 --> 00:45:27,680
Speaker 14: then of course it will have ramifications and implications on

907
00:45:28,040 --> 00:45:28,840
Speaker 14: costs and jobs.

908
00:45:30,040 --> 00:45:34,200
Speaker 4: Steven Angel that with the UBS focus. But we now

909
00:45:34,239 --> 00:45:36,719
Speaker 4: turn our attention to the White House. President Trump is

910
00:45:36,760 --> 00:45:39,200
Speaker 4: now speaking as a lot of his cabinet meetings it's

911
00:45:39,239 --> 00:45:39,680
Speaker 4: just take a less

912
00:45:39,719 --> 00:45:43,080
Speaker 9: Minages and they've really been that way for a year