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Speaker 1: From the heart of where innovation, money and power collide

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Speaker 1: in Silicon Valley and beyond. This is Bloomberg Technology with

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Speaker 1: Caroline Hyde and Ed Ludlow.

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Speaker 2: Live from San Francisco. This is Bloomberg Technology coming up

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Speaker 2: in Nvidia drives a global route in chip stocks after

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Speaker 2: new US government restrictions on tech exports to China. Plus

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Speaker 2: Lift buys its way into the European market with an

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Speaker 2: eye on rolling out autonomous driving. And we speak to

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Speaker 2: the President's Chief Technology Advisor and Director of the White

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Speaker 2: House Office of Science and Technology Policy, Michael Kratzios. Again,

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Speaker 2: it is the chip sector, semiconductors, where our focus is

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Speaker 2: new export controls and license requirements on two big names

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Speaker 2: for the export of specific technologies designed for the Chinese market.

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Speaker 2: This is the picture at the index level. We're down

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Speaker 2: three and a half percent. Clearly some pain across the

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Speaker 2: industry that's spreading the key names of this in Video

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Speaker 2: and AMD, both of them taking write downs in the

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Speaker 2: first quarter. We'll get to the numbers very soon. Elsewhere

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Speaker 2: ASML is an earning story out of Europe. It missed

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Speaker 2: its bookings by almost a billion dollars and it's saying

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Speaker 2: we don't know how to quantify the impact of tariff's

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Speaker 2: on our business. Their business. They are the biggest and

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Speaker 2: most important maker of the machines that make the chips

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Speaker 2: chip making equipment. Again, we will go deep on that

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Speaker 2: story in the show. Let's get to our top story

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Speaker 2: and Video and AMD have been hit hard by new

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Speaker 2: US restrictions on semiconductor exports to China. Bluebow Technology editor

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Speaker 2: Michael Shepherd joins us from DC give us the details

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Speaker 2: the license requirements and I guess, Michael, what happens next

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Speaker 2: for these two names.

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Speaker 3: Well, what happened just now is the write downs that

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Speaker 3: the company had to report.

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Speaker 2: First of all, they are not small.

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Speaker 3: In video report out of five point five billion dollar

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Speaker 3: dollar charge for the first quarter, AMD eight hundred million,

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Speaker 3: and all from these new restrictions that they are now

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Speaker 3: facing on the chips that they have designed specifically for

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Speaker 3: the Chinese market. And these were designed to comply with

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Speaker 3: previous rounds of US restrictions on sales of advanced semiconductors

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Speaker 3: to China. The goal for the administration and for the

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Speaker 3: prior administration too, has been to try to keep those

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Speaker 3: sophisticated semiconductors out of Chinese hands where they can help

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Speaker 3: Beijing gain an edge militarily and give Chinese companies perhaps

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Speaker 3: a way to gain ground on American hyperscalers, an American

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Speaker 3: advantage in artificial intelligence. Now, the catch with these chips

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Speaker 3: is that while they have been scaled down our lower

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Speaker 3: power for the Chinese market AD, they are also useful

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Speaker 3: in inference and this is an emerging area in AI

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Speaker 3: where it is helping companies develop models faster and more effectively,

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Speaker 3: something that we saw with Deep Seek, and that was

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Speaker 3: one of the wake up calls for the Trump administration

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Speaker 3: as it took offices.

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Speaker 4: I'm sure you'll recall, and we heard Commerce.

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Speaker 3: Secretary Howard Lutner articulate.

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Speaker 4: This and make clear that restrictions like these would be coming,

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Speaker 4: and now we're seeing them today and the companies, of

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Speaker 4: course are feeling the pain. And this is compounded, of

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Speaker 4: course by all the concerns about tariffs and elsewhere.

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Speaker 2: In Bloomberg's Mike Shepherd in Washington, d C. Thank you

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Speaker 2: very much. The other big downward pressure on the semiconductor

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Speaker 2: space is ASML, the world's biggest chip equipment maker, posting

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Speaker 2: orders that missed estimates in a very big way. It

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Speaker 2: has dimmed the outlook for the semiconductor sector overall, particularly

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Speaker 2: with regards to anxiety about tariffs. Bloomberg's executive editor, Peter

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Speaker 2: Elstrom is in London and it's a one billion dollar

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Speaker 2: miss basically on bookings. But what accounted for the miss

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Speaker 2: and what did ASML say about the impact of tariffs

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Speaker 2: principally and efforts by the United States for ASML to

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Speaker 2: bring some manufacturing to this country.

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Speaker 5: Peter, Yeah, it's a big miss by ASML. And ASML

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Speaker 5: of course makes the machines that produce chips for the

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Speaker 5: likes of TSMC and Intel and Samsung, so they're kind

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Speaker 5: of a bell weather for chip demand in particular. Now,

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Speaker 5: the CEO, Christoph Fouquet, was pressed pretty hard on the

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Speaker 5: earnings call that we were just listening to now, asking

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Speaker 5: questions about what's driving this, what are the implications. One

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Speaker 5: key factor is certainly this tariff uncertainty that we're seeing.

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Speaker 5: It's not exactly clear what kind of demand is going

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Speaker 5: to be generated in some of these areas, including artificial

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Speaker 5: intelligence and other areas. Another key question is whether tariffs

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Speaker 5: are going to be levied on the machines that ASML

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Speaker 5: makes as they're getting shipped into the United States. The

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Speaker 5: Biden administration now the Trump administration both want to build

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Speaker 5: up the chip capacity within the United States, but that's

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Speaker 5: going to be more difficult if TSMC and Intel and

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Speaker 5: other companies have to pay more for these machines. At

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Speaker 5: the same time, you're seeing some weakness in some of

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Speaker 5: the key players here. Intel, of course, is struggling quite

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Speaker 5: a bit. Even Samsung Electronics now is having a bit

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Speaker 5: of a difficult time building up its capacity. Has slowed

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Speaker 5: things down, so you don't want to add additional costs

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Speaker 5: on top of that. Just to give a sense of

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Speaker 5: the scale, ASML's machines can go for three hundred and

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Speaker 5: eighty million dollars, if you put a terrif on top

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Speaker 5: of that, in the range that the Trump administration is

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Speaker 5: talking about, it could be ninety five million dollars in

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Speaker 5: tariff costs.

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Speaker 6: Now.

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Speaker 5: Fo K was very clear to say that the customers

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Speaker 5: are going to bear the brunt of those costs. It's

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Speaker 5: not going to be ALML themselves. But even if the

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Speaker 5: customers bear those costs, it may slow them down a

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Speaker 5: bit in terms of buying these machines and then deploying them.

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Speaker 5: They may have to think twice about how quickly they're

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Speaker 5: going to move ahead in building the kind of capacity

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Speaker 5: that the administration actually does want in the United States.

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Speaker 2: Bloomberg's Pizza Elstrom in London, Thank you very much. Denny

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Speaker 2: Fish is a tech investor with skin in the game.

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Speaker 2: His funds at Janis Henderson count Nvidia and ASML among

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Speaker 2: its top holdings. There's also TSMC, Broadcom, some of the hyperscalers.

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Speaker 2: Let's get the investors take on technology, export controls and tariffs.

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Speaker 2: Good morning, Denny Fish. Were you ready for those headlines

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Speaker 2: on in video and AMD.

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Speaker 7: No. I wasn't, particularly because there was reporting just a

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Speaker 7: couple of days ago that they had come to an

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Speaker 7: agreement the administration within video that they weren't going to

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Speaker 7: have these restrictions. Obviously, that was just a report, but

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Speaker 7: it definitely took the market by surprise.

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Speaker 2: I want to show a chart which is the proportion

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Speaker 2: of Nvidia's revenue that comes from China, and clearly the

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Speaker 2: chart tells a clear story. In twenty twenty two, China

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Speaker 2: revenues around twenty six percent, currently twenty twenty five with

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Speaker 2: down the thirteen percent. I think many except that this

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Speaker 2: is headed towards single digit because of the impact of

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Speaker 2: technology export controls. Does that matter to you as an

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Speaker 2: Nvidia investor, Denny, do you sort of worry about that

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Speaker 2: and lay awake at night thinking about in Vidia's business

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Speaker 2: in China?

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Speaker 7: Well, two parts of that question. One is whether it

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Speaker 7: matters to me as an investor. In two, I lay

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Speaker 7: awake thinking about China. I think the important thing is

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Speaker 7: it's actually good to just get it out of the model. Okay,

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Speaker 7: So I mean we're kind of wiping it clean. We're

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Speaker 7: taking a clean cut to estimates. And to your point,

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Speaker 7: the revenue contribution from China has come down materially over

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Speaker 7: the last few years. I think something else that's important

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Speaker 7: is that you know, there's something that's it's called the

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Speaker 7: diffusion Rule that is supposed to come into effect in

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Speaker 7: the month of May, and effectively with that is that

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Speaker 7: just puts a quota on the number of GPUs that

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Speaker 7: certain countries can actually buy. Now, one might think that

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Speaker 7: potentially the diffusion rule could be relaxed somewhat.

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Speaker 6: That could benefit in video.

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Speaker 7: The other thing that's just kind of puzzling about all

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Speaker 7: of this is that in some ways this makes no

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Speaker 7: sense at all for.

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Speaker 6: The administration to do. And why is that.

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Speaker 7: Huawei already produces a chip it's somewhat comparable to the

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Speaker 7: H twenty that is actually the customized chip that Nvidia

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Speaker 7: has been selling in to China, and as a result,

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Speaker 7: they're just giving the market to Huawei. And so they're

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Speaker 7: penalizing a US company by you know, restricting a chip

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Speaker 7: that's not even that competitive relative to a locally supplied chip. So,

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Speaker 7: you know, we've already thought about this, you know, pretty extensively.

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Speaker 7: We didn't know if we would get a full cut,

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Speaker 7: but I think, you know, the direction of travel was clear.

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Speaker 7: Contribution from China was going to go way down, and

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Speaker 7: you know, because we're still supply constrained, and Nvidia has

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Speaker 7: the benefit of being able to read direct wafers to

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Speaker 7: other areas where they can actually sell more powerful chips

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Speaker 7: and chips with higher gross margins.

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Speaker 2: The goal of this administration appays to be to shift

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Speaker 2: mores of the United States, be it localized fabrication of

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Speaker 2: the core chip assembly, whatever it may be. And so

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Speaker 2: the companies will face the higher cost of doing business

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Speaker 2: in this country, or they will face twenty thirty five

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Speaker 2: percent net tariff somewhere else. What are the pros and

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Speaker 2: cons of just going with what this administration was and saying, Okay,

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Speaker 2: we're going to do this in America.

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Speaker 7: Well, the pros are that to the extent that we

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Speaker 7: actually have the capacity to manufacture leading edge.

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Speaker 6: Chips, that's a good thing.

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Speaker 7: And it's a good thing because those are the types

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Speaker 7: of chips that are used in our most important industries

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Speaker 7: for national security and for maintaining our competitive advantage globally

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Speaker 7: as we you know, race towards artificial general intelligence. The

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Speaker 7: cons are it is more expensive, but nonetheless, you would

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Speaker 7: think that the productivity gains that we get in agg

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Speaker 7: it from deploying AI probably more than offsets what the

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Speaker 7: aggregate costs would be for manufacturing the chips in the

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Speaker 7: United States. And I just say, you know, thank goodness,

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Speaker 7: TSMC put a shovel in the ground, you know several

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Speaker 7: years ago in Arizona that they're actually in a position

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Speaker 7: now for companies like Nvidian a MD to actually announce

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Speaker 7: that they're going to be producing leading edge two nanometer

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Speaker 7: chips with TSMC in Arizona as well as configuring full

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Speaker 7: systems in the United States.

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Speaker 6: From a manufacturing standpoint, a story.

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Speaker 2: We put heavy emphasis on this week. So in video

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Speaker 2: is your top holding across a couple of funds, right,

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Speaker 2: TSMC is always in there? You said, Thank goodness, that's

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Speaker 2: the case basically, But how does your your thinking now change?

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Speaker 6: Right?

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Speaker 2: Do you stick with this this idea that capital expenditures

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Speaker 2: will continue to grow in twenty five, twenty six, twenty seven,

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Speaker 2: the hyperscalers will continue to take from Nvidia or are

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Speaker 2: you now going to adjust where you put your end assist.

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Speaker 6: Any Well, we take the data as it comes.

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Speaker 7: But most importantly, I think if you just look at

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Speaker 7: the most recent comments out of Nvidia where they just

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Speaker 7: had their GtC conference, if you actually parsed through the

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Speaker 7: comments from ASML today and you pars through the comments

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Speaker 7: that we've heard from hyperscalar CEOs, we don't see signs

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Speaker 7: of a slow down in AI capex and so now

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Speaker 7: the growth may slow, but nonetheless the signs still support

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Speaker 7: healthy growth in AI capex. Well, like I said, we'll

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Speaker 7: take the data as it comes. But ASML was still

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Speaker 7: optimistic about AI. And you know, it's really the lagging

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Speaker 7: edge stuff, you know, analog chips and so forth that

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Speaker 7: go into industrial and auto and things like that that

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Speaker 7: still you know, continue to be soft. And I will

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Speaker 7: remind you, you know, I know this is different with

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Speaker 7: the tariffs and the geopolitical situation, but just rewind the

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Speaker 7: clock one year and asml same thing happened, they missed bookings,

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Speaker 7: the stock was down, and then all they because the

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Speaker 7: bookings are really lumpy, and then bookings just reaccelerated throughout

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Speaker 7: the year and they're doing some really cool stuff. And

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Speaker 7: you know, one of the things they talked about is,

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Speaker 7: you know, one of the reasons that you know they

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Speaker 7: can continue to drive higher pricing for their EUV and

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Speaker 7: high NA EUV is because they're starting to do what's

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Speaker 7: called single layer and what that effectively does it increases

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Speaker 7: the throughput, it's more valuable, and therefore they can charge

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Speaker 7: a higher price that.

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Speaker 2: A technology charge a higher price. Danny Fisher, Jannis Henderson

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Speaker 2: is great to have you back on the program. Thank

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Speaker 2: you very much. Now coming up here on Bloomberg Technology,

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Speaker 2: list is expanding outside of the US and Canada. We

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Speaker 2: have CEO David Risha on the company's European acquisition. That's next.

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Speaker 2: This is Bloomberg Technology. Some deal news. Lift has agreed

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Speaker 2: to buy the European Multi Mobility and taxi ailing app

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Speaker 2: Free Now for about one hundred and ninety seven million dollars.

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Speaker 2: It marks its first global expansion beyond the US and Canada.

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Speaker 2: Lift CEO David Risha joins US. Now, I've been using Uber,

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Speaker 2: your main competitor in Europe for a really long time.

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Speaker 2: I've been going in taxis in Europe for a really

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Speaker 2: long time. Why acquire free now and not just launch

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Speaker 2: the Lift app in that jurisdiction.

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Speaker 8: Because Frenal is a great company that's got great relationships

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Speaker 8: all across Europe in the really important taxi industry. I mean, look,

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Speaker 8: so Lift, as you know ed you've been following us

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Speaker 8: for a while. We're in a stronger position than we've

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Speaker 8: ever been. We're picking riders up faster than we've ever

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Speaker 8: picked them up before. Drivers are making billions on the

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Speaker 8: platform in the US and Canada, and so now's the

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Speaker 8: right time for us to go global. And what's great

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Speaker 8: about it is it expands our market, doubles our market,

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Speaker 8: and it allows us to plug into, as you say,

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Speaker 8: the taxi world, which is a huge, huge part of

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Speaker 8: the European mobility scene.

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Speaker 2: Tomorrow. I think I'm right in saying it's your two

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Speaker 2: year anniversary at Lyft, good memories and you have fixed

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Speaker 2: the finances of that company to an extent. But the

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Speaker 2: data is so key, right, Uber has what one million

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Speaker 2: drivers in Europe and I think free now has about

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Speaker 2: one hundred and fifty thousand registered taxi drivers nine cities.

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Speaker 2: How do you bridge the gap? Are you confident you

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Speaker 2: can bridge the gap? Yeah?

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Speaker 8: I am the goodness So free Now is a great

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Speaker 8: company and one of the things that makes them so

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Speaker 8: strong is they really understand the local dynamics, market by

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Speaker 8: market by market. Here's that thing. The mobility market in

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Speaker 8: Europe for this this kind of you ride heiling is

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Speaker 8: about forty billion euros.

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Speaker 6: Half of that are offline taxes.

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Speaker 8: This are literally still people calling up a taxi company

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Speaker 8: and saying, come take me to the airport, come take me,

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Speaker 8: I'm going on a business trip.

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Speaker 6: Whatever it is.

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Speaker 8: So well, it's true, there are other companies there. Free

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Speaker 8: Now is the leader in the taxi space. And remember

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Speaker 8: is you know, taxi is kind of an elevat experience

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Speaker 8: to a lot of Europe think of the London Blackpam.

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Speaker 8: So we think that the company is really well positioned

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Speaker 8: to really sort of you know, continue to grow and

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Speaker 8: take over the much bigger space.

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Speaker 2: But it is a company that's only recently broken even

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Speaker 2: it's had historic losses. What are you modeling for in

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Speaker 2: terms of what it adds to your top line and

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Speaker 2: bottom line and how immediately.

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Speaker 8: Yeah, so it's a profitable company. It hasn't been a

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Speaker 8: billion dollars in bookings, which is significant. Now I've left,

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Speaker 8: of course, has sixteen billion in booking. So you know,

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Speaker 8: there's a lot of growth, you know, ahead of both

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Speaker 8: of us. But it'll be financially creative for us, which

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Speaker 8: is wonderful. And I think as we you know, they've

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Speaker 8: been owned by Mercedes and BMW, two great sort of

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Speaker 8: storied bottom manufacturers, but I think combining with US is

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Speaker 8: going to give them some new energy, some new expertise

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Speaker 8: to really allow.

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Speaker 2: Both of us to grow. There is zero mention in

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Speaker 2: the release about autonomous driving, and every cell side note

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Speaker 2: about this deal says it's your plan to roll out

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Speaker 2: autonomous driving in Europe with those two OEMs that you

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Speaker 2: just mentioned. Yeah, so here's how we.

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Speaker 8: Think about autonomous as we've said, I mean, first of all,

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Speaker 8: of course it's happening in the US.

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Speaker 6: We're actually a.

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Speaker 8: Little bit further ahead Europe a little bit not so much.

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Speaker 8: One of the great things free Now has is well too,

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Speaker 8: they've got great relationships with European regulators, and they've got

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Speaker 8: great fleet management and as you and I have discussed before,

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Speaker 8: fleet management is so important to autonomous So yeah, we

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Speaker 8: think it sets this up really well. Let's be clear,

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Speaker 8: this is going to be years down the road, but

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Speaker 8: it's a really important part of the overall strategy for

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Speaker 8: being a global player.

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Speaker 2: Two years in you've done some M and A, will

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Speaker 2: you do more M and A?

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Speaker 6: And where.

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Speaker 8: I mean, never say never, but this really is our

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Speaker 8: focus right now, right, I mean, the good news is,

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Speaker 8: you know again free Now is a great, strong company

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Speaker 8: and we've got.

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Speaker 6: So much to build on.

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Speaker 8: So we're going to be really focused on our European expansion,

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Speaker 8: obviously making sure it's a big success. And then who knows,

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Speaker 8: we'll talk later about someone else.

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Speaker 2: Engine capital activists, investor they want to change your board.

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Speaker 2: Your reaction please, I mean, we.

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Speaker 8: Interact with shareholders all the time and you know, listen

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Speaker 8: to their feedback. Take it seriously. You know, there's a

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Speaker 8: whole process for dealing with activist investors that were involved

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Speaker 8: in but probably speaking if you look at what shareholders want,

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Speaker 8: you know, capital return. We're giving out five hundred million

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Speaker 8: dollars in a share buyback. Growth, we're growing, We're now expanding,

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Speaker 8: We're strengthening our business by going international.

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Speaker 6: I think we're really.

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Speaker 8: Well positioned to address all of the issue.

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Speaker 2: Have you that shareholders bring Sorry to interrupt, David. Have

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Speaker 2: you spoken to them about the free now deal since

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Speaker 2: it happened? No, Okay, that's kind of interesting. Final questions

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Speaker 2: on technology Atlanta technology partnerships, MAME Mobility operationally give me

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Speaker 2: an update please.

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Speaker 8: Yeah, so you're referring to the partnership we have with

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Speaker 8: MAME Mobility and Autonomous Vehicle group or company that's on

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Speaker 8: track for this summer. So super excited to launch right

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Speaker 8: in the middle of downtown Atlanta.

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Speaker 2: On track for this summer, being commercially on track or

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Speaker 2: this is a kind of toe in the water.

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Speaker 6: Well, it's on track.

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Speaker 8: For us to start operationally this summer in Atlanta and

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Speaker 8: then you know it'll grow from there. But first we've

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Speaker 8: got to get you know, riders in the cars, and

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Speaker 8: that'll be sometime.

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Speaker 2: This summer because I have the term to do so

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Speaker 2: two years in What would you score yourself or grade

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Speaker 2: yourself on the job you've done as the Lift CEO.

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Speaker 8: Look, I am a self critical person.

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Speaker 2: I am.

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Speaker 8: I guess maybe one of the things that I do

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Speaker 8: is always look for the next thing. But I do

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Speaker 8: have to say I'm proud of what we've accomplished as

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Speaker 8: a team over two years, you know, getting to profitability,

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Speaker 8: seven hundred million dollars plus in free cash and maybe

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Speaker 8: most importantly, picking up riders faster than ever and drivers

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Speaker 8: making more on the platform than ever. So if I

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Speaker 8: look at it from the customer's point of view, we're

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Speaker 8: doing super well. It's up to other people to tell

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Speaker 8: me how I'm doing as a.

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Speaker 2: CEO, and the street gives you a lot of credit

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Speaker 2: for that. M and A maybe they didn't see coming

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Speaker 2: so much. Maybe we'll see some more Lift CEO David Risha,

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Speaker 2: thank you for joining us here on Bloomberg Technology. Now

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Speaker 2: coming up, Americans are still using Chinese e commerce apps

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Speaker 2: to shop cheap alternatives to some high end brands. We're

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Speaker 2: going to drive into the surge in sales for Timu

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Speaker 2: and Sian.

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Speaker 9: This is Bloomberg Technology.

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Speaker 2: A trade war won't stop Americans from shopping on Chinese apps.

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Speaker 2: Revenue surge for both she and and Timu this month

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Speaker 2: as US shoppers anticipate price increases due to tariffs. Bloomberg's

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Speaker 2: Lily Maya joins US and covers the retail Beat. It's

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Speaker 2: really interesting data. A lot of people in my world

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Speaker 2: use both of those apps. I don't what are we learning.

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Speaker 10: Yeah, it seems like these apps are seeing a lot

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Speaker 10: of success and people are going to them as tariffs

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Speaker 10: are starting to loom.

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Speaker 2: The eco data kind of comes in here right when

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Speaker 2: you think about tariffs, we think about passing on the

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Speaker 2: costs of the consumer through your beat, through the tech

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Speaker 2: companies that are in the ecomma space. What are we

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Speaker 2: learning about the consumer and that march data? Yeah, absolutely so.

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Speaker 2: It seems like the consumer is looking to spend right now.

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Speaker 10: The EGO data showed a lot of spending, and it

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Speaker 10: seems like people might be stocking up or buying now

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Speaker 10: before prices might get more expensive.

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Speaker 2: Lily, you cover retail, specialty retail in particular. What are

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Speaker 2: you learning about tariffs? Like, how do companies really think

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Speaker 2: about what happens next? They even know?

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Speaker 10: Yeah, so a lot of companies are doing different things.

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Speaker 10: A lot of the companies I cover report in the

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Speaker 10: next month, so that will be really interesting to hear,

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Speaker 10: you know, what they're looking to say to investors and shareholders.

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Speaker 10: But it seems like a lot of people are in

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Speaker 10: kind of a wait and see mode. They're not exactly

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Speaker 10: sure how tariffs are going to impact their business, and

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Speaker 10: they're trying to figure that out.

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Speaker 2: Bloomers really might great to have you on here on

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Speaker 2: Bloomberg Technology. Thank you very much. Now, coming up, Mark

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Speaker 2: Zuckerberg's email reveals his Instagram and what's strategies from the past.

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Speaker 2: We're going to go back to that antitrust case next.

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Speaker 2: Let's get to markets as well. It is the semiconductor

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Speaker 2: space that's dragging down technologies to shares broadly, but the

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Speaker 2: NASDAQ one hundred is under pressure generally speaking, and by

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Speaker 2: association some of the other key names in our world.

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Speaker 2: The Hyperscala's consumer tech under pressure. Bitcoin is going in

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Speaker 2: the opposite direction eighty five thousand US dollars per token

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Speaker 2: upper percent or so in the session, but it's not

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Speaker 2: behaved uniformly like as risk on risk off. It doesn't

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Speaker 2: sort of take into account the same fact as tech does.

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Speaker 2: We'll dig into that later in the week. Be right back.

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Speaker 2: This is Bloomberg Technology. Welcome back to Bloomberg Technology. I'm

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Speaker 2: Ed Ludlow in San Francisco. The market's picture is very clear.

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Speaker 2: We are under pressure and that largely comes from the

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Speaker 2: chip sector. New US restrictions on technology imports to China,

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Speaker 2: specifically for Nvidia and AMD, that is causing pain. But

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Speaker 2: by association you see a lot of the mag seven

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Speaker 2: megacap names down. Earning season is right around the corner.

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Speaker 2: The underperformance of the Philadelphia Semiconductor Index distills that chip pain.

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Speaker 2: The single names we know about Nvidia, AMD. Very interesting

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Speaker 2: discussion throughout the show on how long that pain will last.

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Speaker 2: But ASML is an earning story at missed bookings by

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Speaker 2: one billion dollars. Later in the program, per Ferregue, New

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Speaker 2: Street Research is going to come on and give us

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Speaker 2: deeper and more granular context about this name. There is

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Speaker 2: other news elsewhere. In his second day on the FDC's

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Speaker 2: antitrust trial, Mark Zuckerberg revealed that he once considered spinning

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Speaker 2: off Instagram back in twenty eighteen. In a letter to

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Speaker 2: senior leaders, he writes, quote, I'm beginning to wonder whether

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Speaker 2: spinning out Instagram is the only structure that will accomplish

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Speaker 2: a number of important goals. We should keep in mind

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Speaker 2: that there's a real chance that all our work to

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Speaker 2: build a family of apps may be something we don't

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Speaker 2: get to keep for more. Bloombers Kirk Wagner, who has

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Speaker 2: been in the courtroom at that trial, joins us, let's

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Speaker 2: go back over it and explain it. At one time

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Speaker 2: in twenty eighteen, of his own volition, Mark Zuckerberg considered

439
00:23:54,440 --> 00:23:57,400
Speaker 2: spinning off Instagram. What does that mean in the context

440
00:23:57,440 --> 00:24:00,880
Speaker 2: of this trial, Well.

441
00:24:00,680 --> 00:24:03,720
Speaker 11: It's very prophetic, right, Obviously he was sort of foreseeing

442
00:24:04,000 --> 00:24:06,760
Speaker 11: the issue that he's facing right now coming down the

443
00:24:06,840 --> 00:24:10,479
Speaker 11: road for him, you know, six seven years ago. I

444
00:24:10,560 --> 00:24:13,399
Speaker 11: don't think the fact that he thought about doing this really,

445
00:24:14,200 --> 00:24:16,119
Speaker 11: you know, hurts him so much today. I think it

446
00:24:16,200 --> 00:24:19,399
Speaker 11: was shared in the context of the FTC trying to

447
00:24:19,440 --> 00:24:22,680
Speaker 11: show that Instagram has perhaps harmed users.

448
00:24:22,840 --> 00:24:24,800
Speaker 2: Right, That's part of their play here, is.

449
00:24:24,800 --> 00:24:27,480
Speaker 11: That they want to show that buying Instagram buying WhatsApp

450
00:24:27,560 --> 00:24:30,840
Speaker 11: was actually bad for consumers. And if they can show that,

451
00:24:30,880 --> 00:24:33,680
Speaker 11: you know, Mark Zuckerberg even thought, Hey, maybe we shouldn't

452
00:24:33,680 --> 00:24:36,160
Speaker 11: be doing this seven years ago, maybe that's a sign

453
00:24:36,200 --> 00:24:39,399
Speaker 11: that they weren't you know, employing the best strategy for consumers.

454
00:24:39,520 --> 00:24:41,440
Speaker 11: But it is a very interesting thing, in part because

455
00:24:41,480 --> 00:24:43,959
Speaker 11: it was so foreshadowing of where he is today.

456
00:24:45,280 --> 00:24:48,840
Speaker 2: This is a multi week but potentially multi month process.

457
00:24:49,119 --> 00:24:51,119
Speaker 2: What else does the audience need to know about the

458
00:24:51,200 --> 00:24:54,320
Speaker 2: trial and proceedings? Where his META focused and where have

459
00:24:54,359 --> 00:24:55,520
Speaker 2: the FTC focused.

460
00:24:56,800 --> 00:25:01,040
Speaker 11: It really hinges on this definition of what you know.

461
00:25:01,320 --> 00:25:04,480
Speaker 11: The FTC is considering the friends and family sharing social

462
00:25:04,520 --> 00:25:07,280
Speaker 11: networking market, right, So so they're saying, hey, look, there's

463
00:25:07,280 --> 00:25:09,480
Speaker 11: a lot of places you can spend time online. There's

464
00:25:09,560 --> 00:25:12,240
Speaker 11: very few places where you actually go specifically to share

465
00:25:12,240 --> 00:25:14,679
Speaker 11: with your friends and family, and that is where META

466
00:25:14,800 --> 00:25:15,800
Speaker 11: has their monopoly.

467
00:25:15,840 --> 00:25:17,080
Speaker 2: This is the FTC's case.

468
00:25:17,320 --> 00:25:19,440
Speaker 11: Meta, on the other hand, is arguing, hey, wait a minute,

469
00:25:19,440 --> 00:25:22,919
Speaker 11: we have tons of competitors, right. TikTok is a competitor.

470
00:25:23,280 --> 00:25:28,200
Speaker 11: Well's I message is a competitor, obviously, x Elon Musk's

471
00:25:28,400 --> 00:25:31,360
Speaker 11: X and none of those, by the very narrow definition

472
00:25:31,400 --> 00:25:34,520
Speaker 11: that the FTC is going with, are considered competitors. And

473
00:25:34,560 --> 00:25:37,560
Speaker 11: so this is basically a fight to determine what the

474
00:25:37,720 --> 00:25:41,040
Speaker 11: market should be and if you know, the FTC succeeds

475
00:25:41,040 --> 00:25:43,080
Speaker 11: and keeping it very very narrow. They may have a

476
00:25:43,080 --> 00:25:46,480
Speaker 11: good case, but as Facebook has pointed out repeatedly, they

477
00:25:46,520 --> 00:25:48,680
Speaker 11: consider their competition very wide.

478
00:25:50,040 --> 00:25:52,080
Speaker 2: Being bes Kutwagner, who I am sure we will come

479
00:25:52,119 --> 00:25:55,000
Speaker 2: back to multiple times over the course of proceedings. Thank

480
00:25:55,000 --> 00:25:57,159
Speaker 2: you very much. Let's break down more on what the

481
00:25:57,240 --> 00:26:01,879
Speaker 2: FTC's trial against Meta could mean in regulation the future

482
00:26:01,880 --> 00:26:05,680
Speaker 2: of digital markets. Joining us now is Jennifer Huddleston, Technology

483
00:26:05,920 --> 00:26:09,520
Speaker 2: Policy Senior Fellow at the Cato Institute, and as a

484
00:26:09,560 --> 00:26:13,640
Speaker 2: piece of documentary evidence in a trial like this, the

485
00:26:13,680 --> 00:26:17,639
Speaker 2: CEO at the center of it in a letter six

486
00:26:17,760 --> 00:26:21,080
Speaker 2: years ago, seven years ago saying maybe we should spin

487
00:26:21,160 --> 00:26:25,800
Speaker 2: off Instagram. How does that play in this environment? What

488
00:26:26,040 --> 00:26:29,600
Speaker 2: is this environment of antitrust that this trial represents.

489
00:26:31,680 --> 00:26:34,920
Speaker 12: We've seen a lot of animosity towards some of America's

490
00:26:34,960 --> 00:26:38,320
Speaker 12: leading tech companies and this presumption that big is automatically bad.

491
00:26:38,760 --> 00:26:41,639
Speaker 12: One of the key elements of the FTC's case is

492
00:26:41,680 --> 00:26:45,920
Speaker 12: it's basically imagining a world that never existed. It's trying

493
00:26:45,960 --> 00:26:48,480
Speaker 12: to ask for a do overall on an acquisition it

494
00:26:48,560 --> 00:26:51,760
Speaker 12: approved more than a decade ago. And at the same time,

495
00:26:51,800 --> 00:26:54,520
Speaker 12: the social media dynamics have been changing. They were changing

496
00:26:54,520 --> 00:26:57,600
Speaker 12: in twenty eighteen when that letter came about. They were

497
00:26:57,640 --> 00:27:01,440
Speaker 12: also changing more recently with the emergence of the like TikTok.

498
00:27:01,760 --> 00:27:04,480
Speaker 12: We have to remember that at the time Meta acquired

499
00:27:04,600 --> 00:27:08,320
Speaker 12: Instagram and WhatsApp, these were not surefire successes. In fact,

500
00:27:08,359 --> 00:27:11,439
Speaker 12: there were jokes, particularly about the acquisition of Instagram at

501
00:27:11,480 --> 00:27:13,840
Speaker 12: the time, kind of why are they doing this? Why

502
00:27:13,880 --> 00:27:16,000
Speaker 12: are they paying all this money. We don't want to

503
00:27:16,000 --> 00:27:19,919
Speaker 12: see a world where government enforcers penalize businesses for taking

504
00:27:20,359 --> 00:27:23,240
Speaker 12: risky chances that turn out to be good bets and

505
00:27:23,359 --> 00:27:26,040
Speaker 12: turn out to allow more innovation and more benefits for

506
00:27:26,080 --> 00:27:27,200
Speaker 12: consumers in the market.

507
00:27:29,080 --> 00:27:32,280
Speaker 2: This is a trial, and it is contested between the

508
00:27:32,320 --> 00:27:37,240
Speaker 2: FTC and Meta. But we are a few months into

509
00:27:37,320 --> 00:27:41,560
Speaker 2: this new administration. In the White House. Prior to the

510
00:27:41,560 --> 00:27:45,200
Speaker 2: election and after the inauguration of President Trump, many put

511
00:27:45,240 --> 00:27:50,040
Speaker 2: emphasis on Vice President JD. Vance's views on big tech

512
00:27:50,320 --> 00:27:54,200
Speaker 2: and antitrust. How does that context play here in the trial.

513
00:27:54,280 --> 00:27:58,119
Speaker 2: It seems as if this administration will follow through with

514
00:27:58,200 --> 00:28:01,760
Speaker 2: the general attitude towards big tech that the prior administration did.

515
00:28:03,680 --> 00:28:05,600
Speaker 12: If you look at the history of many of these cases,

516
00:28:05,640 --> 00:28:08,880
Speaker 12: many of them began in the first Trump administration. Then

517
00:28:08,920 --> 00:28:12,959
Speaker 12: we saw further gasoline on the fire during the Biden administration,

518
00:28:13,040 --> 00:28:16,639
Speaker 12: particularly under Chair Lena Kahn at the FTC, and this

519
00:28:16,760 --> 00:28:20,479
Speaker 12: real push towards this big as bad mentality. It seems

520
00:28:20,520 --> 00:28:23,159
Speaker 12: like so far, both with the remedies proposed in the

521
00:28:23,200 --> 00:28:25,359
Speaker 12: Google cases as well as with what we're seeing in

522
00:28:25,359 --> 00:28:29,280
Speaker 12: the medic caase, that this administration seems determined to continue

523
00:28:29,480 --> 00:28:32,600
Speaker 12: that shift away from the kind of law and economics,

524
00:28:32,640 --> 00:28:36,640
Speaker 12: consumer welfare based approach to anti trust, to something that

525
00:28:37,040 --> 00:28:40,880
Speaker 12: makes more presumptions about competitors than consumers, and something that

526
00:28:40,960 --> 00:28:44,719
Speaker 12: perhaps is using anti trust enforcement for other policy goals.

527
00:28:44,840 --> 00:28:45,600
Speaker 2: And that should be.

528
00:28:45,560 --> 00:28:48,840
Speaker 12: Concerning because if we lose focus on the consumers whom

529
00:28:48,920 --> 00:28:53,000
Speaker 12: anti trust was designed to protect, we risk losing the

530
00:28:53,120 --> 00:28:57,000
Speaker 12: purpose behind anti trust and making this powerful tool more subjective.

531
00:28:57,720 --> 00:29:00,520
Speaker 2: Jennifer, why would a breakup of Meta in its family

532
00:29:00,560 --> 00:29:02,320
Speaker 2: of apps be bad for the consumer?

533
00:29:03,960 --> 00:29:05,680
Speaker 12: I think that's what's really at the heart that we

534
00:29:05,760 --> 00:29:08,000
Speaker 12: need to remember when it comes to this case. You'd

535
00:29:08,040 --> 00:29:11,800
Speaker 12: lose certain cross functionality that consumers like, but you also

536
00:29:11,880 --> 00:29:15,560
Speaker 12: would have companies with fewer resources to engage in research

537
00:29:15,880 --> 00:29:19,560
Speaker 12: and development technology to engage in rolling out new features

538
00:29:19,800 --> 00:29:23,320
Speaker 12: that consumers want in the time that AI is disrupting things,

539
00:29:23,600 --> 00:29:25,920
Speaker 12: but also fewer resources to do some of the things

540
00:29:25,920 --> 00:29:30,120
Speaker 12: that consumers have expected around things like young people's online safety.

541
00:29:30,480 --> 00:29:32,960
Speaker 12: And finally, you might have companies that have to rely

542
00:29:33,120 --> 00:29:36,200
Speaker 12: more on data and advertisers because they no longer can

543
00:29:36,240 --> 00:29:39,120
Speaker 12: share those resources, and so they would have to actually

544
00:29:39,200 --> 00:29:42,800
Speaker 12: shift more towards using their consumer data and more on

545
00:29:43,040 --> 00:29:46,719
Speaker 12: doing what the advertisers want rather than what their consumers want.

546
00:29:47,240 --> 00:29:51,280
Speaker 2: Jennifer, the core of Meta's argument or defense is that

547
00:29:51,440 --> 00:29:56,080
Speaker 2: the FTC has this narrow definition, but they're misunderstanding the marketplace,

548
00:29:56,440 --> 00:30:01,440
Speaker 2: that Meta's competition is TikTok and that it is you too.

549
00:30:01,640 --> 00:30:03,720
Speaker 2: How successful do you think that defense will be.

550
00:30:06,320 --> 00:30:09,880
Speaker 12: The FDC is seeking a really narrow definition of personal

551
00:30:09,880 --> 00:30:13,240
Speaker 12: friends and family social media networks, which is a definition

552
00:30:13,320 --> 00:30:16,880
Speaker 12: I don't think the average consumer thinks about, and it's

553
00:30:16,880 --> 00:30:20,400
Speaker 12: something that, if it's successful, could potentially lead to larger

554
00:30:20,400 --> 00:30:24,960
Speaker 12: disruptive disruption in the social media marketplace. Not only does

555
00:30:24,960 --> 00:30:29,080
Speaker 12: this definition exclude companies like TikTok that are incredibly popular

556
00:30:29,080 --> 00:30:33,280
Speaker 12: with gen Z, it also excludes other messaging apps like Signal.

557
00:30:33,560 --> 00:30:37,240
Speaker 12: It excludes platforms like Snap that have grown in popularity,

558
00:30:37,480 --> 00:30:39,760
Speaker 12: so it doesn't seem to reflect the experience of the

559
00:30:39,800 --> 00:30:43,040
Speaker 12: average consumer when it comes to social media and messaging,

560
00:30:43,280 --> 00:30:46,280
Speaker 12: let alone when it comes to broader conversations around things

561
00:30:46,360 --> 00:30:48,680
Speaker 12: like advertising or entertainment more generally.

562
00:30:49,720 --> 00:30:53,200
Speaker 2: In your research and your review of policy pending the

563
00:30:53,240 --> 00:30:57,160
Speaker 2: outcome of this trial, do you expect actions against other

564
00:30:57,200 --> 00:30:58,520
Speaker 2: big tech names, and if so.

565
00:30:58,480 --> 00:31:03,840
Speaker 12: Who We have already seen cases against four of America's

566
00:31:03,920 --> 00:31:06,480
Speaker 12: leading tech companies, Google, which is now in a remedy

567
00:31:06,520 --> 00:31:08,920
Speaker 12: phase in one of its case. There are also penning

568
00:31:08,960 --> 00:31:12,040
Speaker 12: cases against Amazon and Apple, and of course this case

569
00:31:12,320 --> 00:31:15,960
Speaker 12: against Facebook and Meta. All of these cases really raise

570
00:31:16,040 --> 00:31:19,600
Speaker 12: concerns about the potential government intervention into what has been

571
00:31:19,600 --> 00:31:23,200
Speaker 12: a very dynamic ecosystem. Not only could these cases have

572
00:31:23,280 --> 00:31:26,120
Speaker 12: consequences for consumers, but there's going to be a question

573
00:31:26,160 --> 00:31:28,120
Speaker 12: as well of what are we missing out on while

574
00:31:28,160 --> 00:31:32,200
Speaker 12: companies spend their time dealing with enforcement actions instead of

575
00:31:32,200 --> 00:31:35,680
Speaker 12: innovating and trying to provide better things for consumers. What

576
00:31:35,720 --> 00:31:38,800
Speaker 12: sort of messages this side to the startup ecosystem.

577
00:31:39,480 --> 00:31:41,880
Speaker 2: Jennifer Alison of the Cato Institute, thank you very much.

578
00:31:41,920 --> 00:32:00,920
Speaker 2: We'll be right back this is Bloomberg Technology. This is

579
00:32:00,920 --> 00:32:03,120
Speaker 2: Bloomberg Technology, and you're looking at a live shot of

580
00:32:03,160 --> 00:32:06,160
Speaker 2: the principal room. Check out the Bloomberg Technology podcast. You

581
00:32:06,160 --> 00:32:08,320
Speaker 2: can find it on the terminal as well as online

582
00:32:08,320 --> 00:32:22,840
Speaker 2: on Apple, Spotify, and iHeart this is Bloomberg. The United

583
00:32:22,880 --> 00:32:25,800
Speaker 2: States will have to make a creative R and D

584
00:32:25,920 --> 00:32:30,040
Speaker 2: push while making quote smart choices with budgets to stay

585
00:32:30,080 --> 00:32:33,000
Speaker 2: ahead in the AI race. Those were the first public

586
00:32:33,040 --> 00:32:36,520
Speaker 2: remarks by Michael Kratzios, Advisor to the President and White

587
00:32:36,560 --> 00:32:40,000
Speaker 2: House Office of Science and Tech Policy Director, since his

588
00:32:40,080 --> 00:32:43,440
Speaker 2: confirmation in March. The main message on strategy for tech

589
00:32:43,920 --> 00:32:48,200
Speaker 2: promote and protect. Mister Gratzios joins us. Now specifically, what

590
00:32:48,240 --> 00:32:51,040
Speaker 2: do you mean by smart choices? This is a time

591
00:32:51,080 --> 00:32:55,600
Speaker 2: where budgets across federal government are being cut. Some tools

592
00:32:55,600 --> 00:32:59,000
Speaker 2: and examples please, mister Grazios, thank you so much for

593
00:32:59,040 --> 00:33:01,040
Speaker 2: having me ed. I think if you zoom out a

594
00:33:01,080 --> 00:33:01,480
Speaker 2: little bit.

595
00:33:01,560 --> 00:33:03,479
Speaker 13: The message that we were trying to share in Austin

596
00:33:03,480 --> 00:33:05,880
Speaker 13: a few days ago was this question of how does

597
00:33:05,920 --> 00:33:10,120
Speaker 13: the US ensure its position as the global leader in

598
00:33:10,200 --> 00:33:13,160
Speaker 13: critical and emerging technologies? And in order to do that,

599
00:33:13,320 --> 00:33:15,640
Speaker 13: you have to do two major things. You have to

600
00:33:15,680 --> 00:33:19,720
Speaker 13: do promotion and protection, and the key pillar of the

601
00:33:19,760 --> 00:33:23,200
Speaker 13: promote agenda is around being more creative in the way

602
00:33:23,480 --> 00:33:27,240
Speaker 13: that we spend fairly funded research and development dollars. For

603
00:33:27,320 --> 00:33:29,560
Speaker 13: far too long, these R and D dollars have been

604
00:33:29,600 --> 00:33:32,200
Speaker 13: spent in the same ways by the same agencies of the.

605
00:33:32,120 --> 00:33:33,160
Speaker 2: Same types of research.

606
00:33:33,520 --> 00:33:35,520
Speaker 13: And there's a lot more that we can do in

607
00:33:35,800 --> 00:33:40,360
Speaker 13: all sorts of things like prizes and challenges, advanced market commitments,

608
00:33:40,640 --> 00:33:43,520
Speaker 13: or even fast track action grants where we can actually

609
00:33:43,840 --> 00:33:45,920
Speaker 13: worry a little bit less about how much and more

610
00:33:45,960 --> 00:33:49,080
Speaker 13: about how we actually deploy these dollars in ways that

611
00:33:49,120 --> 00:33:52,440
Speaker 13: we can ensure we're making in the best discoveries here

612
00:33:52,480 --> 00:33:54,000
Speaker 13: in the United States for years to come.

613
00:33:54,680 --> 00:33:58,080
Speaker 2: We've reported a lot on DOGE that's the context right,

614
00:33:58,080 --> 00:34:02,320
Speaker 2: the work to cut wasting government. But very specifically, mister Kretsios,

615
00:34:02,720 --> 00:34:06,000
Speaker 2: do you call for support an increase in R and

616
00:34:06,080 --> 00:34:08,719
Speaker 2: D budgets? Growth in R and D budgets?

617
00:34:09,680 --> 00:34:11,400
Speaker 13: Again, the most important thing we have to do is

618
00:34:11,440 --> 00:34:14,280
Speaker 13: make sure that we are prioritizing our R and D budgets.

619
00:34:14,640 --> 00:34:17,440
Speaker 13: Spending a lot of money on the wrong things is

620
00:34:17,520 --> 00:34:20,320
Speaker 13: far worse than spending less money on the right things.

621
00:34:20,840 --> 00:34:22,560
Speaker 2: So what we do at the White House.

622
00:34:22,320 --> 00:34:25,040
Speaker 13: In coordination with the Office of Management and Budget, is

623
00:34:25,080 --> 00:34:28,600
Speaker 13: helped set research and development priorities for the country. The

624
00:34:28,640 --> 00:34:30,959
Speaker 13: President spelled these out and a letter that he sent

625
00:34:30,960 --> 00:34:32,759
Speaker 13: to me two weeks ago, and the ones that he

626
00:34:32,800 --> 00:34:36,960
Speaker 13: did call out were artificial intelligence, quantum computing, and nuclear

627
00:34:37,080 --> 00:34:40,200
Speaker 13: to name three. And you can imagine that in future

628
00:34:40,239 --> 00:34:42,960
Speaker 13: budget cycles these areas that we're going to be prioritizing

629
00:34:43,600 --> 00:34:46,840
Speaker 13: because those are key to our national economic security.

630
00:34:47,840 --> 00:34:53,200
Speaker 2: Are those priorities achievable AI leadership from America with the

631
00:34:53,239 --> 00:34:57,200
Speaker 2: tariffs that we have in place and the technology export controls,

632
00:34:57,719 --> 00:34:59,840
Speaker 2: some of which were amplified overnight on the likes of

633
00:35:00,080 --> 00:35:03,239
Speaker 2: and Video and AMD. Absolutely.

634
00:35:03,280 --> 00:35:05,320
Speaker 13: If you think back to the strategy that we discussed

635
00:35:05,320 --> 00:35:07,719
Speaker 13: a couple of days ago, in order to achieve this

636
00:35:07,800 --> 00:35:11,800
Speaker 13: leadership position, we have to do both promotion and protection.

637
00:35:12,360 --> 00:35:14,120
Speaker 13: On the promote side, we talked a little about the

638
00:35:14,200 --> 00:35:16,320
Speaker 13: R and D pillar. The second piece of that is

639
00:35:16,360 --> 00:35:20,399
Speaker 13: around deregulation. For far too long, especially in the last administration,

640
00:35:20,840 --> 00:35:22,920
Speaker 13: you know, a lot of our regulatory policy has been

641
00:35:23,000 --> 00:35:25,680
Speaker 13: driven by the spirit of fear, this idea that we

642
00:35:25,719 --> 00:35:28,799
Speaker 13: should be worried about these emerging technologies, and what the

643
00:35:28,840 --> 00:35:30,960
Speaker 13: President in the White House has said many times is

644
00:35:31,280 --> 00:35:33,279
Speaker 13: we have to make sure that we lead in this

645
00:35:33,320 --> 00:35:36,680
Speaker 13: technology and actually deploy it, and then on the promote

646
00:35:36,760 --> 00:35:38,840
Speaker 13: on the protect side of the equation, we have to

647
00:35:38,920 --> 00:35:42,280
Speaker 13: make sure that we're not giving our adversaries the critical

648
00:35:42,320 --> 00:35:44,240
Speaker 13: tools that could help.

649
00:35:44,120 --> 00:35:45,839
Speaker 2: Them try to catch up to us in this race.

650
00:35:46,239 --> 00:35:48,960
Speaker 13: We know that the PRC is attempting to catch up

651
00:35:49,000 --> 00:35:51,680
Speaker 13: with us and things like artificial intelligence, and there's no

652
00:35:51,719 --> 00:35:55,000
Speaker 13: reason why we should be helping them do so. So

653
00:35:55,040 --> 00:35:57,360
Speaker 13: that's why in order to kind of achieve this US

654
00:35:57,400 --> 00:36:01,799
Speaker 13: position of leadership in artificial intelligence and other emerging technologies,

655
00:36:02,040 --> 00:36:04,920
Speaker 13: you have to have a balanced promotion and protection agenda.

656
00:36:06,040 --> 00:36:08,560
Speaker 2: In Nvidia and AMD now face the situation where they

657
00:36:08,600 --> 00:36:11,160
Speaker 2: have to apply for licenses to be able to explore

658
00:36:11,360 --> 00:36:14,600
Speaker 2: H twenty and I THREEH eight to China, and the

659
00:36:14,640 --> 00:36:18,040
Speaker 2: administration's argument was they could end up in supercomputers. The

660
00:36:18,080 --> 00:36:21,719
Speaker 2: company's argument is these are much lower performance, and one

661
00:36:21,880 --> 00:36:25,000
Speaker 2: idea is that if they haven't got access to American technology,

662
00:36:25,440 --> 00:36:28,960
Speaker 2: China will simply champion a domestic name. Huawei has a

663
00:36:29,000 --> 00:36:33,319
Speaker 2: similar ACCE accelerator. How will you advise the President on

664
00:36:33,360 --> 00:36:36,359
Speaker 2: whether or not AMD and Nvidia should be granted those

665
00:36:36,440 --> 00:36:40,360
Speaker 2: license to export lower performance accelerators to China.

666
00:36:41,719 --> 00:36:44,600
Speaker 13: Yeah, I'm not going to opine on the specifics there,

667
00:36:44,640 --> 00:36:47,120
Speaker 13: but I will say that there has been a track

668
00:36:47,200 --> 00:36:49,640
Speaker 13: record of a wide variety of chips being used to

669
00:36:49,760 --> 00:36:54,200
Speaker 13: drive the development and training of what are almost frontier

670
00:36:54,320 --> 00:36:58,560
Speaker 13: level open source models by companies within the PRC, And

671
00:36:58,640 --> 00:37:02,440
Speaker 13: as we think about our protect agenda, it's critical that

672
00:37:02,480 --> 00:37:07,000
Speaker 13: we develop an export control regime that is simple and

673
00:37:07,080 --> 00:37:11,120
Speaker 13: clear and is one that we enforce very very strongly.

674
00:37:13,000 --> 00:37:16,440
Speaker 2: One of the elements of PROMOTE is to bring manufacturing

675
00:37:16,480 --> 00:37:20,399
Speaker 2: of lead edge chips and assembling of compute systems to America, Right,

676
00:37:20,400 --> 00:37:23,560
Speaker 2: mister Crassios and ASML is in the splotlight as an

677
00:37:23,600 --> 00:37:27,959
Speaker 2: example because of its earnings report overnight, with this administration,

678
00:37:28,760 --> 00:37:33,480
Speaker 2: consider an exemption of tariffs on the leading chip equipment

679
00:37:33,560 --> 00:37:36,120
Speaker 2: maker in order that they might be able to do

680
00:37:36,160 --> 00:37:38,640
Speaker 2: that bring more of their activity to the United States.

681
00:37:39,960 --> 00:37:42,560
Speaker 13: Again, I can't oppine on specifics, but I think what

682
00:37:42,600 --> 00:37:45,680
Speaker 13: we saw from the news last week on in Nvidia,

683
00:37:46,320 --> 00:37:49,719
Speaker 13: there is a continual effort and we see that from

684
00:37:49,760 --> 00:37:52,800
Speaker 13: all around the world of people wanting to bring manufacturing

685
00:37:52,880 --> 00:37:56,799
Speaker 13: and these core sort of bleeding edge technologies back here

686
00:37:56,800 --> 00:37:59,160
Speaker 13: to the United States. And that's something that the White

687
00:37:59,160 --> 00:38:00,640
Speaker 13: House is very proud of and something that we have

688
00:38:00,719 --> 00:38:04,160
Speaker 13: seen across industry. The policies that the President in our

689
00:38:04,200 --> 00:38:08,240
Speaker 13: trade team have implemented is one that is actually proving true.

690
00:38:08,280 --> 00:38:10,040
Speaker 13: And just a few short days we've had so many

691
00:38:10,040 --> 00:38:13,960
Speaker 13: great announcements about companies coming here to build and manufacture

692
00:38:14,000 --> 00:38:16,759
Speaker 13: these critical technologies in the US, and I suspect that

693
00:38:16,800 --> 00:38:18,440
Speaker 13: we'll be seeing a lot more of those in the

694
00:38:18,480 --> 00:38:19,359
Speaker 13: months in.

695
00:38:19,320 --> 00:38:24,600
Speaker 2: Weeks ahead, there is some confrontation between the administration and

696
00:38:25,200 --> 00:38:30,040
Speaker 2: leading academic and research institutions. Harvard is an example. How

697
00:38:30,120 --> 00:38:35,160
Speaker 2: does the potential of cutting budgets at institutions like that

698
00:38:35,640 --> 00:38:39,480
Speaker 2: impact America's competitiveness in the field of research. I reflect

699
00:38:39,560 --> 00:38:44,040
Speaker 2: on Jensen Wong's comments. I believe in March at GtC

700
00:38:44,200 --> 00:38:46,920
Speaker 2: that well more than fifty percent of the AI research

701
00:38:46,960 --> 00:38:49,920
Speaker 2: is either being done in China or by Chinese nationals,

702
00:38:50,520 --> 00:38:53,720
Speaker 2: and yet here in America we have some debate about

703
00:38:53,840 --> 00:38:55,400
Speaker 2: funding for these institutions.

704
00:38:56,880 --> 00:38:59,520
Speaker 13: Yeah, I want to make sure we don't necessarily conflate

705
00:38:59,600 --> 00:39:02,360
Speaker 13: to such issues. To me, I don't think this is

706
00:39:02,440 --> 00:39:07,480
Speaker 13: particularly hard. There is no reason why we should be

707
00:39:07,719 --> 00:39:12,400
Speaker 13: supporting anti semitism on college campuses or tolerate that. I

708
00:39:12,440 --> 00:39:16,160
Speaker 13: think we can be intolerant of anti semitism on university

709
00:39:16,280 --> 00:39:21,120
Speaker 13: campuses and also support the academic research enterprise. Those two

710
00:39:21,120 --> 00:39:25,120
Speaker 13: things can happen simultaneously. And I think first and foremost

711
00:39:25,200 --> 00:39:28,400
Speaker 13: these universities think very carefully about about Title six, and

712
00:39:28,440 --> 00:39:31,720
Speaker 13: I leave that to the DOJ and to DOE Department

713
00:39:31,719 --> 00:39:32,560
Speaker 13: of Education.

714
00:39:32,320 --> 00:39:32,920
Speaker 2: To think about.

715
00:39:33,200 --> 00:39:36,600
Speaker 13: On my end, and what I've advocated very strongly is

716
00:39:36,920 --> 00:39:40,720
Speaker 13: we continue to need great universities to work on basic

717
00:39:41,120 --> 00:39:45,360
Speaker 13: research that has funded and fueled or innovation ecosystem for decades,

718
00:39:45,600 --> 00:39:47,480
Speaker 13: and that's something the White House will continue to advocate

719
00:39:47,560 --> 00:39:49,640
Speaker 13: for well. At the same time, we can never stand

720
00:39:49,680 --> 00:39:52,200
Speaker 13: for anti semitism on our university campuses.

721
00:39:53,480 --> 00:39:56,320
Speaker 2: Mister Kretzios. Is part of your offices request for information,

722
00:39:56,440 --> 00:40:01,520
Speaker 2: several AI companies submitted responses to you, you asking basically

723
00:40:01,600 --> 00:40:06,440
Speaker 2: to preserve their ability to learn from copyrighted material. We're

724
00:40:06,480 --> 00:40:10,920
Speaker 2: talking about those training frontier models, foundation models, very simple

725
00:40:11,000 --> 00:40:15,239
Speaker 2: yes or no if you will. Is copyright reform on

726
00:40:15,280 --> 00:40:18,320
Speaker 2: the table as part of this President's AI action plan

727
00:40:18,360 --> 00:40:20,560
Speaker 2: and how would you advise him on that? Please?

728
00:40:21,560 --> 00:40:23,759
Speaker 13: Yeah, we were so delighted with how many responses we

729
00:40:23,840 --> 00:40:27,120
Speaker 13: got to the I Action Plan RFI. I think in

730
00:40:27,160 --> 00:40:29,279
Speaker 13: the coming days we'll hopefully be able to release all

731
00:40:29,320 --> 00:40:32,040
Speaker 13: of those responses. It was many, many thousands, and it

732
00:40:32,160 --> 00:40:35,799
Speaker 13: just showed how far and wide the community is that

733
00:40:36,640 --> 00:40:39,640
Speaker 13: wants to think about and help shape the national agenda

734
00:40:39,680 --> 00:40:42,520
Speaker 13: for artificial intelligence. And obviously copyright is going to be

735
00:40:42,560 --> 00:40:45,799
Speaker 13: one of the issues that many people commented on over

736
00:40:45,800 --> 00:40:46,880
Speaker 13: the last few months.

737
00:40:47,640 --> 00:40:51,960
Speaker 2: Mister Christio's copyright reform yes or no again. I think

738
00:40:52,000 --> 00:40:53,320
Speaker 2: we could not be more.

739
00:40:53,160 --> 00:40:56,600
Speaker 13: Thrilled with how many people commented on all sorts and

740
00:40:56,640 --> 00:40:59,359
Speaker 13: all facets of the AI agenda, And this is one

741
00:40:59,400 --> 00:41:02,120
Speaker 13: that we had a lot of commenters send us some

742
00:41:02,520 --> 00:41:04,160
Speaker 13: very interesting and detailed thoughts on.

743
00:41:05,200 --> 00:41:08,080
Speaker 2: The President has spoken with admiration about Jensen Wong and

744
00:41:08,120 --> 00:41:12,239
Speaker 2: in Nvidia's leadership. Just as our audience Boombog Technology gets

745
00:41:12,280 --> 00:41:14,239
Speaker 2: to know you, mister Kratzios and your work in the

746
00:41:14,239 --> 00:41:16,800
Speaker 2: White House, Have you had the opportunity to meet with

747
00:41:16,880 --> 00:41:20,279
Speaker 2: Jensen Wong and his peers about what they plan to

748
00:41:20,320 --> 00:41:23,239
Speaker 2: do in America and also critical markets for them. Which

749
00:41:23,239 --> 00:41:26,319
Speaker 2: once included China. I have yeah.

750
00:41:26,360 --> 00:41:29,160
Speaker 13: In the first two weeks after my confirmation, I had

751
00:41:29,160 --> 00:41:32,279
Speaker 13: the opportunity to meet with most of the leading technology

752
00:41:33,080 --> 00:41:35,719
Speaker 13: industry CEOs and chat with them about how we can

753
00:41:35,880 --> 00:41:38,960
Speaker 13: together usher in this golden age of American innovation that

754
00:41:39,080 --> 00:41:43,200
Speaker 13: the President has called for. With Jensen specifically, he's a

755
00:41:43,200 --> 00:41:45,480
Speaker 13: tremendous thinker, and one of the great things that we

756
00:41:45,600 --> 00:41:48,719
Speaker 13: connected on is the question of AI for science. There's

757
00:41:48,760 --> 00:41:51,480
Speaker 13: been this almost this extreme fixation on thinking about the

758
00:41:51,920 --> 00:41:55,480
Speaker 13: protect side of the agenda when it comes to specific semiconductors.

759
00:41:55,960 --> 00:41:58,560
Speaker 13: But I think another equally more and maybe even more

760
00:41:58,560 --> 00:42:01,239
Speaker 13: important part of the are the problems we face ahead

761
00:42:01,280 --> 00:42:04,000
Speaker 13: of us and our challenges is how can we actually

762
00:42:04,040 --> 00:42:08,240
Speaker 13: implement this technology to drive transformational change for the American people.

763
00:42:08,560 --> 00:42:10,359
Speaker 2: And Jensen and Nvidia he.

764
00:42:10,400 --> 00:42:14,200
Speaker 13: Was extraordinarily excited to help us think through and see

765
00:42:14,200 --> 00:42:17,720
Speaker 13: what we can do more on driving scientific discoveries through AI.

766
00:42:17,880 --> 00:42:20,839
Speaker 13: And it's something that I will be encouraging Secretary right

767
00:42:20,880 --> 00:42:23,880
Speaker 13: with our labs and punch at National Science Foundations so

768
00:42:23,920 --> 00:42:26,160
Speaker 13: many of our other leaders to stick more seriously because

769
00:42:26,160 --> 00:42:26,879
Speaker 13: we have to do better.

770
00:42:28,239 --> 00:42:31,600
Speaker 2: Michael Kratzio's White House Office of Science and Tech Policy Director,

771
00:42:31,920 --> 00:42:35,280
Speaker 2: Thank you, look forward to speaking more over the coming years. Okay,

772
00:42:35,360 --> 00:42:38,840
Speaker 2: I mentioned ASML shares trading significantly lower, the company posting

773
00:42:39,120 --> 00:42:42,080
Speaker 2: a sales miss that was almost a billion euros less

774
00:42:42,120 --> 00:42:44,840
Speaker 2: than expected. Per Fareger of New Street Research, head of

775
00:42:44,840 --> 00:42:48,319
Speaker 2: Global Tech Infrastructure is with us. There are people out there, Pierre,

776
00:42:48,520 --> 00:42:50,399
Speaker 2: and it's good to see you again that a bit

777
00:42:50,440 --> 00:42:53,960
Speaker 2: more sanguine. Right, Orders can be lumpy, But the thing

778
00:42:54,040 --> 00:42:59,360
Speaker 2: that's spooky to many is the inability to quantify tariff impact.

779
00:42:59,560 --> 00:43:03,680
Speaker 2: How are you modeling for that in ASML's case. Yeah,

780
00:43:03,680 --> 00:43:04,680
Speaker 2: I think you're making a good point.

781
00:43:04,760 --> 00:43:08,040
Speaker 14: The way I modeled it is by actually modeling orders

782
00:43:08,080 --> 00:43:10,520
Speaker 14: coming down in the nearter, Because while you're not too

783
00:43:10,520 --> 00:43:14,600
Speaker 14: certain bout tariffs in some industries, you could see people

784
00:43:14,680 --> 00:43:17,520
Speaker 14: like front loading orders before time it gets into place.

785
00:43:18,360 --> 00:43:22,040
Speaker 14: Doesn't work very well with these very large pieces of equipment.

786
00:43:22,080 --> 00:43:24,200
Speaker 14: And then the second approach is to actually wait and

787
00:43:24,280 --> 00:43:29,960
Speaker 14: see and be more careful in the long run. Modeling

788
00:43:30,080 --> 00:43:33,600
Speaker 14: like tariffs requires you to take a view on what

789
00:43:33,640 --> 00:43:35,640
Speaker 14: the tariffs are here for. You know what the US

790
00:43:35,719 --> 00:43:38,839
Speaker 14: administration want to do with these tariffs, and so if

791
00:43:38,840 --> 00:43:42,520
Speaker 14: you listen to them. You know, they want to encourage

792
00:43:42,800 --> 00:43:46,719
Speaker 14: changes in behavior with straight partners. They want to bring

793
00:43:46,840 --> 00:43:52,799
Speaker 14: back to the US or to reliable partners manufacturing, and

794
00:43:52,800 --> 00:43:56,600
Speaker 14: they want to create additional revenues. And if you put

795
00:43:56,760 --> 00:44:00,640
Speaker 14: that into into motion around SEMITAP equipments, what you see

796
00:44:00,680 --> 00:44:03,719
Speaker 14: is that none of these objectives are going to go

797
00:44:03,840 --> 00:44:07,799
Speaker 14: against the ability for the US to build actually the

798
00:44:07,840 --> 00:44:11,279
Speaker 14: AI infrastructure and to continue to, let you know, the

799
00:44:11,320 --> 00:44:16,200
Speaker 14: manufacturing of leading h semiconductors like memory chips and logic chips.

800
00:44:16,960 --> 00:44:19,480
Speaker 2: Yes, as they built up in the US.

801
00:44:19,280 --> 00:44:21,880
Speaker 14: You still need to continue to have like technology advancing

802
00:44:21,920 --> 00:44:24,520
Speaker 14: everywhere in the world. So I'm not too worried about

803
00:44:24,560 --> 00:44:27,280
Speaker 14: the impact of tariff's on SEMITAP equipments.

804
00:44:28,000 --> 00:44:30,680
Speaker 2: You heard mister Kratziosk decline to answer my question on

805
00:44:30,719 --> 00:44:34,120
Speaker 2: whether there would be an exemption for chip equipment makers,

806
00:44:35,000 --> 00:44:38,520
Speaker 2: but mister Fouquet was very clear, we will assemble in

807
00:44:38,560 --> 00:44:41,960
Speaker 2: the Netherlands. Does the administration have a say on what

808
00:44:42,040 --> 00:44:43,840
Speaker 2: a SML does in this case, Pierre.

809
00:44:46,280 --> 00:44:48,520
Speaker 14: They definitely have a say. I think if they if

810
00:44:48,520 --> 00:44:51,080
Speaker 14: they give a phone call, the phone call will be

811
00:44:51,480 --> 00:44:56,600
Speaker 14: will be taken. The specifics of ASML tools is that

812
00:44:56,680 --> 00:45:00,160
Speaker 14: it's very unlikely to see like the final assembly of

813
00:45:00,160 --> 00:45:03,960
Speaker 14: these tools moving away from the Netherlands. The same way

814
00:45:04,400 --> 00:45:06,759
Speaker 14: it's very unlikely to see like the most leading edge

815
00:45:06,760 --> 00:45:12,239
Speaker 14: manufacturing node of TSMC moving away from from Taiwan. Is

816
00:45:12,280 --> 00:45:16,359
Speaker 14: probably like a hard limit that cannot be surpassed. Now,

817
00:45:16,760 --> 00:45:20,320
Speaker 14: what must said as well is that you know, increasing

818
00:45:20,400 --> 00:45:23,120
Speaker 14: the amount of manufacturing done in the US, which is

819
00:45:23,160 --> 00:45:26,680
Speaker 14: already very significant. Yes, where I live, you you already

820
00:45:26,719 --> 00:45:30,799
Speaker 14: have like very critical stages that have been manufactured, Like

821
00:45:30,840 --> 00:45:33,760
Speaker 14: the light source, which is the most critical piece of

822
00:45:33,560 --> 00:45:36,800
Speaker 14: the IVY tool, is manufactured in the US, and seeing

823
00:45:36,840 --> 00:45:40,960
Speaker 14: that going up is a possibility. Like changing like the

824
00:45:41,040 --> 00:45:45,319
Speaker 14: final assembly of these tools is yes, probably probably a

825
00:45:45,360 --> 00:45:48,320
Speaker 14: stype and particularly in practical terms, not doable.

826
00:45:48,640 --> 00:45:51,799
Speaker 2: Right PF Faeryg of New Street Research. Good to catch

827
00:45:51,880 --> 00:45:54,239
Speaker 2: up have you back here on Bloomberg Technology. But that

828
00:45:54,360 --> 00:45:57,400
Speaker 2: does it for this edition of Bloomberg Technology. A huge

829
00:45:57,400 --> 00:45:59,799
Speaker 2: thanks to those of you that submitted questions for some

830
00:45:59,880 --> 00:46:02,400
Speaker 2: of our key interviews throughout the hour. There is a

831
00:46:02,400 --> 00:46:04,400
Speaker 2: lot to recap. Don't forget to check out the podcast.

832
00:46:04,440 --> 00:46:06,560
Speaker 2: You know where to find it on the Bloomberg terminal

833
00:46:06,560 --> 00:46:11,160
Speaker 2: as well as online on Apple, Spotify, and iHeart. What

834
00:46:11,320 --> 00:46:17,640
Speaker 2: a week from San Francisco. This is Bloomberg technology