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

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Speaker 1: live from Coast to Coast with Caroline Hyde and New

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Speaker 1: York and Ed Ludlow in Fendrances Go.

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Speaker 2: This is Bloomberg Tech.

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Speaker 3: Coming up, the Trump administration is eyeing CHIPSAC funds for

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Speaker 3: a steak in Intel.

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Speaker 4: Plus applied materials plunges due to growing trade concerns between

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Speaker 4: the US and China.

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Speaker 3: And an in depth interview with Open AI chairman and

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Speaker 3: Sierra CEO Brett Taylor that's later in the hour.

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Speaker 2: We go straight to.

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Speaker 3: The top story, Bloomberg reporting the White House is considering

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Speaker 3: tapping US CHIPSAC funds in an effort to take a

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Speaker 3: steak in American chip maker Intel. That's according to sources.

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Speaker 3: For more, Bloomberg's Joe Doe joins us Joe, what's the

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Speaker 3: new information?

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Speaker 2: Reporting today?

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Speaker 5: Right?

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Speaker 6: A follow on from yesterday's scoop from Bloomberg that it

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Speaker 6: looks like the funding that the White House is looking

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Speaker 6: at using would come from chips Act money. Of course,

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Speaker 6: everybody might remember that from the law pass during the

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Speaker 6: Biden administration. We've understood that some of that money has

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Speaker 6: laid dormant and could be potentially used for this potential

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Speaker 6: equity stake that the administration was looking at and Intel.

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Speaker 4: Fascinating because we understood there was almost eight billion dollars

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Speaker 4: coming Intel's way pre agreed, maybe even eleven billion dollars

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Speaker 4: and loans. We don't know the intricacies of how much

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Speaker 4: money and what equity state that would be equivalent to.

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Speaker 4: But Joe remind us why the US government is doing this,

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Speaker 4: We're even eyeing it.

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Speaker 6: The way to look at so much of this Intel

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Speaker 6: is one. Of course, this hasn't happened, but we do

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Speaker 6: have one that has happened, which was the MP Materials,

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Speaker 6: rare earth company that very few people have heard of,

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Speaker 6: but just got a four hundred million dollar preferred EQ

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Speaker 6: stake investment from the Defense Department. It is all built

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Speaker 6: around this idea of national security. What does the Trump administration,

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Speaker 6: the White House view as central to national security efforts,

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Speaker 6: in particular related to its race against China. You have

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Speaker 6: a rare earth company, potentially a chips company. Earlier this week,

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Speaker 6: had we had the announcement that in Nvidia and AMD

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Speaker 6: would be giving fifteen percent of their revenues generated out

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Speaker 6: of China to the federal government, this is all built

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Speaker 6: around this kind of new idea that Trump.

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Speaker 2: Is trying to make work. Joe some basics.

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Speaker 3: Intel has not commented directly on our reporting. They've issued

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Speaker 3: this statement. We're going to put it on the screen

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Speaker 3: now and generally right this is the point that what

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Speaker 3: the administration is trying to do is achieve onshoring of

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Speaker 3: manufacturing of chips in this country. Intel kind of wants

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Speaker 3: to do the same thing. There is more reporting that

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Speaker 3: you did that a lot of this literally relates to

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Speaker 3: the meeting this week between Bhutan and the President.

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Speaker 6: What have sources teld us We understand that this is

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Speaker 6: the idea. This idea did come up in that meeting.

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Speaker 6: I think the point that we draw from this, and

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Speaker 6: I was just saying this earlier, is we have an

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Speaker 6: administration a president I'm not an administration, a president directly

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Speaker 6: who's willing to just have a bilateral talk or negotiation

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Speaker 6: with any CEO he can bring into the White House

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Speaker 6: that he finds, you know, central to some of the

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Speaker 6: most important themes.

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Speaker 2: In his second term.

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Speaker 6: So obviously, as the Intel chief come in and as

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Speaker 6: you've pointed out ed, you know, we don't have a

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Speaker 6: full confirm here that this is happening. These things remain fluid.

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Speaker 6: We've seen this in so many different issues with the

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Speaker 6: White House. A lot of it is just hey, what

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Speaker 6: about this? What about that? But in particular related to this,

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Speaker 6: the Intel chief does show up to the White House

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Speaker 6: and has this conversation with the President, and this apparently

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Speaker 6: is where this idea whispurred.

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Speaker 4: Bloomberg's Jodo fascinating reporting. Scoops keep coming. We thank you. Look,

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Speaker 4: let's dive into the Intel side of the equation. Why

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Speaker 4: they do it? Jordan Klein, Zooho Securities Managing director joins

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Speaker 4: us now who put I don't knowe this morning discussing

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Speaker 4: the implications of a possible government stake and Jordan, you're

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Speaker 4: questioning it, asking how does the US government help Intel

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Speaker 4: fixes leading edge node when it's not a money issue?

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Speaker 7: They have no customers and.

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Speaker 4: There is a good reason for that. Jordan, extrapolate on that.

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Speaker 8: Yeah, I mean, Intel, in my opinion, has two main issues.

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Speaker 8: One is on the technology side, where their leading edge

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Speaker 8: foundry business has struggled to execute at these more advanced

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Speaker 8: nodes and they've lost you know, a lot of potential

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Speaker 8: business and share to TSM, who's executed flawlessly. And the

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Speaker 8: second big issue is, you know, and this is kind

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Speaker 8: of the chicken in the egg, is that they don't

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Speaker 8: have any external non Intel customers to move you know,

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Speaker 8: volume and bi business into these fabs on this new

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Speaker 8: leading edge. So you kind of need the former, meaning

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Speaker 8: you need to be a leader improved to customers you

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Speaker 8: can execute at these advanced nodes for these you know,

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Speaker 8: AI and leading edge chips.

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Speaker 9: And then secondly then you need to win the business.

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Speaker 8: And until they get both of those, I think they're

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Speaker 8: going to continue to struggle.

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Speaker 4: And the Bhutan really said that articulated it in the

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Speaker 4: earnings saying we are not going to have this, build

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Speaker 4: it and they will come. Mentality, they've got to say.

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Speaker 7: That they're coming before we build it.

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Speaker 4: In the fourteen a leading cutting edge nodes for example Jordan,

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Speaker 4: is government control or at a smaller equity stake going

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Speaker 4: to secure that demand.

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Speaker 8: Well, on the surface, it's not because the customers are

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Speaker 8: going to ultimately decide is Intel a company I can

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Speaker 8: depend and count on for my most advanced you know

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Speaker 8: products that I have to get to the market. Why

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Speaker 8: would I leave TSM who's proven to me year after

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Speaker 8: year that they can execute on the plan. I think

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Speaker 8: the goal here is that Trump puts some money in

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Speaker 8: or gets the government to invest, and then uses that

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Speaker 8: to get Intel to accelerate the process of building out

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Speaker 8: these new fabs in Ohio, and then he can go

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Speaker 8: to these customers like Broadcom, Qualcom, Apple and Nvidia and say, oh,

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Speaker 8: now they have the capability and you need to move

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Speaker 8: more of your orders and production to a domestic, leading

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Speaker 8: edge company like Intel.

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Speaker 3: Jordan, I really want the desk analysts take and experience.

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Speaker 3: We broke the story yesterday about the stake, We broke

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Speaker 3: the story this morning about using chips Act funds. What

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Speaker 3: was the byside saying to you about how they interpreted

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Speaker 3: that news.

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Speaker 8: Yeah, that's kind of the key question, and I think

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Speaker 8: it's it's I haven't heard a ton of questions as

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Speaker 8: to Okay, what next does this mean I go out

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Speaker 8: and buy Intel. Ultimately, if you look at semiconductors that

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Speaker 8: have led much of the market this year, I think

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Speaker 8: Intel has been the laggered due to their weak fundamentals

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Speaker 8: and a lot of people who need shorts to offset longs,

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Speaker 8: like in video, Broadcon TSM.

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Speaker 9: Have used Intel as that short.

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Speaker 8: Now today the news about a stake and what this

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Speaker 8: could mean I think gets people nervous. You know, maybe

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Speaker 8: Intel's going to go on a run. I should cover

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Speaker 8: my short But outside of that, I do not hear

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Speaker 8: you know, big mutual funds, the traditional guys who would

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Speaker 8: come in take a big steak and think this company

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Speaker 8: is going to turn it around, you know, acting on

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Speaker 8: this and these headlines. One because it's premature, but two,

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Speaker 8: I think they're coming to the same conclusion that I

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Speaker 8: just talked about, is that how does government money or

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Speaker 8: an equity stake, you know, really bring them the customers

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Speaker 8: or fixed their internal technology problems?

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Speaker 9: And that's unknown.

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Speaker 3: Jensen Wogen Nvidia have demonstrated the proximity to the President

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Speaker 3: has allowed them to move fast as I'm thinking King

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Speaker 3: Prince be actually about exports to the Gulf, a good

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Speaker 3: relationship between the President and lit Bhutan.

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Speaker 2: Is there an unlock for Intel in that, Well, you know.

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Speaker 8: I don't know what the I think ultimately, here's what

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Speaker 8: I would Here's the way I see it is that

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Speaker 8: I don't think Trump likes the fact that the you know, largest,

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Speaker 8: you know, oldest and most established kind of US foundry

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Speaker 8: logic company and Intel is on its heels struggling, losing

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Speaker 8: share to these foreign players in Asia like TSM.

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Speaker 9: I think it's a bad look.

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Speaker 8: Obviously, he wants the US, you know, to be great

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Speaker 8: again and that you know, we so much depends on semiconductors.

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Speaker 8: So I think the fact that they're firing people, reducing costs,

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Speaker 8: struggling is just a bad look under his watch. And

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Speaker 8: all this Chipsacked money was allocated and they got the

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Speaker 8: most of it.

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Speaker 9: So I think basically he's saying.

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Speaker 8: I want some return for this, and you know, I

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Speaker 8: want to try to help this, you know, semiconductor business

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Speaker 8: domestically improve, and that's got to start with you somehow.

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Speaker 9: So I think he's just putting pressure.

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Speaker 8: On them, and I don't know what other alternative Intel has,

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Speaker 8: they can't really push back, and ultimately they'll probably take

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Speaker 8: what money the government wants to invest and try to

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Speaker 8: strengthen the relationship going forward.

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Speaker 4: Jordan, what's so interesting is then we heard on Air

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Speaker 4: Force one, and we're going to discuss it more in

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Speaker 4: the show later.

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Speaker 7: A potential threat of.

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Speaker 4: Two hundred to three hundred percent tariffs on semiconductors coming

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Speaker 4: into the US.

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Speaker 7: But there are huge.

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Speaker 4: Carve outs that we understand being written here that if

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Speaker 4: you're investing a lot in America, you don't face that.

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Speaker 4: So that seems that TSMC and Samsung that are building

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Speaker 4: in America aren't affected. Is he going to allow these

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Speaker 4: big Asian chip giants to continue to build in America

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Speaker 4: and get these sorts of carve outs.

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Speaker 9: I don't know what other alternative they really have.

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Speaker 8: I mean, the US is in the government, and the

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Speaker 8: administration's kind of in a tough spot here. They need

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Speaker 8: to project, like, you know, a strategy of trying to

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Speaker 8: get you know, more domestic US semiconductor capacity. But if

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Speaker 8: you get too tough and put too high of a tariff,

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Speaker 8: that that really puts the US consumer and our strategic technology,

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Speaker 8: whether it's defense or AI, at a major disadvantage. And

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Speaker 8: the reason that is is because the US doesn't have

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Speaker 8: an alternative. It's not like, you know, we can just

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Speaker 8: shift to all this domestic capacity. It's going to take

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Speaker 8: a lot of time and money to basically get that.

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Speaker 8: And right now that's basically TSM and a lot of

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Speaker 8: Samsung and some of Intel. So I think that's why

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Speaker 8: they get the carve outs is to buy time and

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Speaker 8: then ultimately that time runs out, and then Trump's going

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Speaker 8: to say, well, if we have the capacity here and

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Speaker 8: Intel is, you know, on a better footing and track,

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Speaker 8: then we want you to push that those orders in

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Speaker 8: that money towards Intel and away from Ta Simon Samsung,

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Speaker 8: and that's where he could start to then use the

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Speaker 8: tariffs to basically push that business towards Intel.

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Speaker 4: Really thoughtful and a great note. Jordan Klein of Mizuho,

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Speaker 4: Thanks for bringing you expertise.

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Speaker 7: Shares of Applied Materials tumbling.

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Speaker 4: Worst day since March twenty twenty after the company presented

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Speaker 4: a disappointing sales forecast for the fiscal fourth quarter said

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Speaker 4: it's seeing less demand from China more. Let's bring in

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Speaker 4: Bloomberg's Brodie Ford. What's so interesting is Land Research came

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Speaker 4: out a week or so ago and look pretty buoyant

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Speaker 4: about future growth and revenue. Very different for this chip

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Speaker 4: equipment company.

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Speaker 10: You are pointing out the debate that is waging and

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Speaker 10: all the sales side reports in my inbox right now, right,

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Speaker 10: I mean on the call last night, the narrative from

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Speaker 10: the company was that China demand is worst and some

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Speaker 10: of our largest customer mergers that are holding off due

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Speaker 10: to kind of just general economic uncertainty, tariffs and all that.

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Speaker 11: But there's also a head here.

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Speaker 10: As you said, some of the peers have done relatively well.

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Speaker 10: So is applied losing share here? Or is this truly

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Speaker 10: just a macroeconomic it's hitting everybody the same way kind

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Speaker 10: of issue.

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Speaker 3: They try to explain away those two categories of customer.

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Speaker 3: Right in China, loads of chip makers have gone through

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Speaker 3: a refresh of their equipment, but the larger customers they're

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Speaker 3: talking about is largely TSMC and Samsung.

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Speaker 2: And this is a tariff's issue. What is it?

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Speaker 12: Right?

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Speaker 10: I think tariffs is the big word we heard, but

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Speaker 10: I think also, I mean, we have an administration right

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Speaker 10: now that's negotiating trade deals. I mean, we saw the

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Speaker 10: Intel news this morning. There's just a lot of economic

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Speaker 10: uncertainty right now, right, I mean, some of the data

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Speaker 10: coming out people are questioning. And so the narrative we

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Speaker 10: heard on the call, and I heard in a conversation

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Speaker 10: with the CEO is that companies are holding off purchases.

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Speaker 10: They're not sure exactly what the economic picture of it

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Speaker 10: is like in six months, and so why do you

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Speaker 10: want to make a multi billion dollar commitment right now?

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Speaker 10: How much to hit the brakes for a little while.

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Speaker 4: And Brodie, we put this in the deeper context as

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Speaker 4: you just hinted at with Intel. This is at a

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Speaker 4: time where we want more manufacturing the United States, according

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Speaker 4: to the administration, and Apply Materials.

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Speaker 7: Is part of that.

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Speaker 4: They've got what eighty percent of the revenue.

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Speaker 7: Coming from abroad.

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Speaker 4: But is that going to shift more to America?

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Speaker 10: That is the song they're singing, right, I mean they

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Speaker 10: say that we are involved with you know, Apple's initiatives

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Speaker 10: and Samsungs. The actual dollars committed at this point to

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Speaker 10: me don't look incredible, right. I mean, a lot of

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Speaker 10: companies are talking about multi billions invested in the US,

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Speaker 10: and Apply to talking about hundreds of millions, and so

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Speaker 10: I don't think the expectation is that revenue shift to

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Speaker 10: the US in a meaningful way right now. But it's

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Speaker 10: an interesting part of the narrative. I mean, how much

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Speaker 10: can the administration push the industry to, you know, reshore

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Speaker 10: more of this demanding capacity?

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Speaker 3: Then, thanks Brady Ford, thank you very much. Meanwhile, President

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Speaker 3: Trump is en route to Alaska for a high stakes

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Speaker 3: meeting with Russian President Vladimir Putin.

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Speaker 2: During the flight on air Force one.

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Speaker 3: He addressed the state of tariffs on chip makers, saying

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Speaker 3: it could rise to as much as three hundred percent.

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Speaker 2: Listen to this.

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Speaker 12: They're all coming in because they want to beat the

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Speaker 12: tariffs because if they open here, they don't have to

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Speaker 12: pay tariffs. If they don't open here, they have to

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Speaker 12: make in some cases two hundred percent, three hundred percent.

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Speaker 12: I haven't even said some of the tariffs yet till

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Speaker 12: sent Semiconductors will be setting sometime next week week.

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Speaker 3: Care for for more on the tariff implications on chips

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Speaker 3: and the broader technology sector. Martin Norton Empower Chief Investment Strategists. Actually,

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Speaker 3: of all the reporting out there, this is the President

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Speaker 3: speaking on the record saying up to three hundred percent

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Speaker 3: tariffs on chips coming into America. I haven't even said

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Speaker 3: the tariffs yet. This is the point policy keeps changing.

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Speaker 3: As a strategist, how do you interpret it?

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Speaker 13: Well, I mean, I think there's a few things that

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Speaker 13: we have to look at.

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Speaker 14: First.

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Speaker 13: We have to look at the breadth of the tariffs

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Speaker 13: that we've seen and the way the market has reacted

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Speaker 13: as tariffs have become part of the daily conversation. At first,

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Speaker 13: you know, April second, this was something that the market

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Speaker 13: felt was a disaster.

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Speaker 14: But as we've.

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Speaker 13: Rolled forward, we've seen little effect on corporate earnings, we've seen.

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Speaker 14: Little effect on economic data.

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Speaker 13: And I think there's this kind of benign neglect of

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Speaker 13: tariffs as a concern for the market, which I think

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Speaker 13: embolden's President Trump to continue to push forward bigger and

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Speaker 13: bigger numbers when we're looking at triple digits. Of course,

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Speaker 13: when we're talking about tariffs, that's a pretty astonishing thing.

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Speaker 13: I really like how your last guest with Jordan really

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Speaker 13: kind of talked about the very long term emphasis here.

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Speaker 13: Building manufacturing here in the US is a long term thing.

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Speaker 13: Forcing companies or encouraging companies to buy US as a

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Speaker 13: long term thing, and I think these tariffs are part

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Speaker 13: of that game.

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Speaker 3: So if the endgame is bring Chit manufacturing back to America,

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Speaker 3: you agree with Jordan that it will work or you disagree.

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Speaker 13: Well, I think there has to be a long term

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Speaker 13: commitment on the part of the administration and the folks

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Speaker 13: in Washington to keep those tariffs in place. I think

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Speaker 13: that's in question whether that's something that we're going to

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Speaker 13: see over the period of several years, because that's what

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Speaker 13: it would take several years to bring manufacturing back to

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Speaker 13: the United States or to the United States in the

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Speaker 13: first place.

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Speaker 14: So I think there's still.

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Speaker 13: An open question as to how effective it will be

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Speaker 13: and how long term that commitment will be, and how.

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Speaker 4: Long until you see it rewarding companies like an Applied Materials,

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Speaker 4: which right here right now is having its worst days.

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Speaker 4: It's March twenty twenty and rated all of its games

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Speaker 4: for the year Marta. How do you decide who are

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Speaker 4: the winners longer term in this environment?

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Speaker 13: I think the winners is one of the bigger questions

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Speaker 13: that we're looking at, especially when you start to look

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Speaker 13: at it in the context of artificial intelligence. When we're

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Speaker 13: taking a look at corporate earnings long term, of course

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Speaker 13: we're concerned about the that deglobalization will have on those

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Speaker 13: corporate earnings. And yet when we look at the estimates

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Speaker 13: that artificial intelligence can add to corporate earnings to profit margins,

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Speaker 13: it more than offsets it. The question is who those

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Speaker 13: winners are, And what we've seen in past periods of

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Speaker 13: innovation is that the early winners are not necessarily the

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Speaker 13: long term the enduring winners. And there's also questions as

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Speaker 13: to how different industries respond. You know, first folks thought

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Speaker 13: with software is the next leg of this story, but

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Speaker 13: that doesn't necessarily need to be the case. If some

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Speaker 13: of these big tech companies can capture some of the

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Speaker 13: developments there, it's not necessarily going.

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Speaker 14: To be the small cap companies that win.

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Speaker 13: So when I'm looking at this and I'm thinking about

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Speaker 13: how do you play this, I think it's more of

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Speaker 13: a broad based question than it is trying to find

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Speaker 13: and pick those narrow winners.

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Speaker 4: So you take tech thinking to other industry groups, that's right, Yes,

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Speaker 4: absolutely so.

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Speaker 13: For example, if you're taking a look at where can

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Speaker 13: you apply AI? Where can you apply some of these narratives.

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Speaker 13: The areas that we've heard talked about regularly is healthcare

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Speaker 13: and applying artificial intelligence to research and development. That's a

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Speaker 13: long term play, and of course there's tons of headwinds

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Speaker 13: against healthcare, pharma and the like, and when we think

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Speaker 13: about those headwinds, those are opening up pretty attractive valuations

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Speaker 13: while there's also this positive long term narrative that's there.

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Speaker 13: So I do think that we can look at some

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Speaker 13: of these other areas, particularly those that are a bit cheaper.

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Speaker 13: There's not many of them. There's a few as areas

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Speaker 13: of long term beneficiaries of AI.

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Speaker 2: Marta.

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Speaker 3: It's funny for me, but it's been a week where

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Speaker 3: economic data has impacted technology markets, right, PPI and I

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Speaker 3: grew up in the Bloomberg school of why do we

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Speaker 3: care about the FED? Because higher rates discount the present

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Speaker 3: value of future cash flows. And I just wondered if

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Speaker 3: you'd react to that statement, please well listen.

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Speaker 14: I mean, I do think when we think.

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Speaker 13: About economic data and we think about technology, there are

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Speaker 13: these secular growth themes that can really push back against

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Speaker 13: any headwind that economic data poses for technology, And of

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Speaker 13: course there are other areas of the market that are

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Speaker 13: more sensitive.

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Speaker 14: When I think about the economic.

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Speaker 13: Data that we're seeing come through, all that comes out

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Speaker 13: is this idea of mixed signals, and people can kind

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Speaker 13: of project whatever view they want on the market and

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Speaker 13: find or on the economy and find evidence to support

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Speaker 13: that view. I think at this point what matters more

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Speaker 13: are the secular themes rather than some of these economic

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Speaker 13: data points that are trickling in.

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Speaker 4: Briefly matter It's also been a week of record hizing

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Speaker 4: crypto IPOs.

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Speaker 7: How many questions you get on that?

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Speaker 14: Well, it does come up more and more.

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Speaker 13: I think one of the things that people are looking

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Speaker 13: at when they see the record highs in crypto, or

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Speaker 13: when they're looking at IPOs, or in fact the kind

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Speaker 13: of resurgence of the mean theme is what does this

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Speaker 13: mean in terms of the speculative froth in the market.

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Speaker 13: I don't think we're at all time peaks there, but

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Speaker 13: there is this measure of complacency that's been baked in,

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Speaker 13: this kind of sense that nothing can go wrong, and

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Speaker 13: of course that's reflected in valuations. So I do think

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Speaker 13: when we're looking at those kind of signals, it's important

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Speaker 13: to remember that things are a bit priced for perfection

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Speaker 13: and we could see some volatility in the nearest term.

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Speaker 4: Martin Norton, we so appreciate having you on today of Empower.

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Speaker 7: Have great weekend.

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Speaker 4: It's time now for talking tech and first up, Masuyoshi's

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Speaker 4: son has added eleven billion to his fortune in just

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Speaker 4: the first two weeks of August. That is, his AI

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Speaker 4: bets over at SoftBank sent shares to record highs.

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Speaker 7: Look Sum's net worth naws dance more.

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Speaker 4: Than thirty three billion dollars, making him the second richest

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Speaker 4: man in Japan, according to the Bloomberg Billionaires Index plus

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Speaker 4: Bill Ackman's Pershing Square Capital. Well, it's revealed that it

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Speaker 4: a mastered in nearly one point three billion dollar steak

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Speaker 4: in Amazon. The firm initially disclosed it had built a

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Speaker 4: stake during an analyst school in May. That's after the

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Speaker 4: stock tumbled more than thirty percent over AI and tariff concerns.

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Speaker 4: Look regulatory filing on Thursday show that Pershing had accumulated

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Speaker 4: more than five point eight.

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Speaker 7: Million Amazon shares.

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Speaker 4: And Jackie Bezos, mother of Jeff Bezos, has died at

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Speaker 4: the age of seventy eight. According to the Bezos Family

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Speaker 4: Foundation website, she passed away at a home in Miami

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Speaker 4: after a long battle with louis body dementia. Jackie Bezos

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Speaker 4: was an advocate for early childhood education.

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Speaker 7: Alongside her husband.

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Speaker 4: She was in fact the first to invest in Amazon

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Speaker 4: in nineteen ninety five.

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Speaker 9: ED.

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Speaker 2: Welcome back to Bloomberg Tech. I want to go back

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Speaker 2: to Intel.

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Speaker 3: The reporting is that the US government's thinking about using

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Speaker 3: chipsec funds to take a stake in Intel. Caroline, believe

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Speaker 3: it or not. On the course of the week, this

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Speaker 3: stocks up almost twenty five percent. If it continues to

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Speaker 3: chop around and climb just a percentage point higher. It

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Speaker 3: will have its best five day gain, its best weekly

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Speaker 3: gain on record ever, just seven days after the President

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Speaker 3: said that its CEO should resign after ties with China.

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Speaker 3: Later in the program, we're going to do so much

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Speaker 3: more on Intel. But when you go into the data

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Speaker 3: in the Bloomberg terminal, you can always surprise your because

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Speaker 3: in Agrica over the course of the week, what an

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Speaker 3: astonishing stat that is.

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Speaker 4: It is quite the stat six straight days against for Intel.

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Speaker 4: What a winning performance twenty five percent that you can

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Speaker 4: see it in.

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Speaker 7: All its glory.

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Speaker 4: Let's get into the world of generative AI now, though,

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Speaker 4: because we are joined by Brett Taylor ed whose extensive

446
00:22:20,640 --> 00:22:24,240
Speaker 4: Silicon Valley resume, who's Google metas Salesforce open Ai. His

447
00:22:24,359 --> 00:22:28,439
Speaker 4: startups Erra AI helps companies build agentic customer service tools.

448
00:22:28,720 --> 00:22:31,800
Speaker 4: You work with the likes of ram with clear among others. Brett,

449
00:22:32,240 --> 00:22:35,800
Speaker 4: and boy, is it competitive out there at the moment.

450
00:22:35,920 --> 00:22:40,960
Speaker 4: How are you seeing your customer facing GENDERAI products being taken.

451
00:22:40,720 --> 00:22:41,280
Speaker 7: Up right now?

452
00:22:42,440 --> 00:22:44,399
Speaker 5: Yeah, I've never quite been in a market like this,

453
00:22:44,480 --> 00:22:46,320
Speaker 5: and as you said, I've been in the Silicon Valley

454
00:22:46,320 --> 00:22:49,159
Speaker 5: for a long time. I've started three companies, one in

455
00:22:49,200 --> 00:22:51,919
Speaker 5: sort of the early days of the internet, you know,

456
00:22:52,080 --> 00:22:55,640
Speaker 5: one call it about you know, a decade ago, and

457
00:22:56,000 --> 00:22:58,960
Speaker 5: we have never seen this kind of customer interest. I've

458
00:22:58,960 --> 00:23:02,760
Speaker 5: never seen this kind of of revenue growth and customer momentum.

459
00:23:02,760 --> 00:23:05,199
Speaker 5: But as you said, a lot of competition too, you know.

460
00:23:05,200 --> 00:23:07,560
Speaker 5: I think if you look at what is the impact

461
00:23:07,600 --> 00:23:10,400
Speaker 5: of AI and society, there's probably two areas being impacted

462
00:23:10,440 --> 00:23:13,840
Speaker 5: most right now, software engineering and customer service. We're in

463
00:23:13,840 --> 00:23:16,200
Speaker 5: that latter category. We have the privilege to be the

464
00:23:16,280 --> 00:23:19,480
Speaker 5: leader survey it. As you said, traditional companies like ADT,

465
00:23:19,600 --> 00:23:23,280
Speaker 5: Home Security and direct TV, and the fastest growing companies

466
00:23:23,280 --> 00:23:25,159
Speaker 5: in Silicon Valley like Ramp. And it is such a

467
00:23:25,160 --> 00:23:26,840
Speaker 5: privilege and so much fun to be in the middle

468
00:23:26,880 --> 00:23:27,520
Speaker 5: of this right now.

469
00:23:28,119 --> 00:23:30,560
Speaker 4: I'm not sure the competitors, particularly the older god of

470
00:23:30,600 --> 00:23:33,440
Speaker 4: SaaS some that you helped work with, like Salesforce, love

471
00:23:33,480 --> 00:23:35,800
Speaker 4: the enthusiasm way that you're shaking things up in terms

472
00:23:35,800 --> 00:23:39,000
Speaker 4: of pricing though, I mean outcome based pricing models.

473
00:23:39,080 --> 00:23:41,280
Speaker 7: How are you seeing that really.

474
00:23:41,040 --> 00:23:43,520
Speaker 4: Change the cadence of which others.

475
00:23:43,240 --> 00:23:44,719
Speaker 7: Can sell and how they're selling.

476
00:23:45,840 --> 00:23:47,679
Speaker 5: It's such a great question if you look at the

477
00:23:47,720 --> 00:23:52,320
Speaker 5: history of software. These technical shifts have also given rise

478
00:23:52,400 --> 00:23:55,879
Speaker 5: to changes in business models, so kind of famously, you know,

479
00:23:56,200 --> 00:23:59,440
Speaker 5: when Mark and Parker started Salesforce, the world went from

480
00:23:59,520 --> 00:24:02,679
Speaker 5: buying a petrol license to software, to software as a

481
00:24:02,720 --> 00:24:05,920
Speaker 5: service and subscribing to it. Now, our view is at Sierra,

482
00:24:06,119 --> 00:24:08,919
Speaker 5: these agents aren't just helping you be more productive, but

483
00:24:09,000 --> 00:24:12,240
Speaker 5: actually solving problems for you. And the best business model

484
00:24:12,320 --> 00:24:14,320
Speaker 5: is to actually pay for a job well done. So

485
00:24:14,680 --> 00:24:17,560
Speaker 5: at Sierra, we only charge our customers when it solves

486
00:24:17,560 --> 00:24:20,160
Speaker 5: the problem autonomously for that customer.

487
00:24:20,320 --> 00:24:22,080
Speaker 11: We call it outcomes based pricing.

488
00:24:22,400 --> 00:24:24,399
Speaker 5: And we think it's going to really disrupt the software

489
00:24:24,400 --> 00:24:26,600
Speaker 5: industry because if you think about it as a business,

490
00:24:27,040 --> 00:24:29,879
Speaker 5: what a great alignment of values with your partners. You

491
00:24:29,960 --> 00:24:32,760
Speaker 5: only pay us when we actually save you money and

492
00:24:32,840 --> 00:24:35,760
Speaker 5: solve the customer's problem delightfully. And I think it really

493
00:24:35,800 --> 00:24:38,840
Speaker 5: aligns the software industry with all of our partners, and

494
00:24:38,840 --> 00:24:40,760
Speaker 5: I think it's a really positive trend for the industry

495
00:24:41,240 --> 00:24:41,760
Speaker 5: as a whole.

496
00:24:43,119 --> 00:24:46,240
Speaker 3: Right, you founded Sierra with Clay in twenty twenty three, Right,

497
00:24:46,280 --> 00:24:47,919
Speaker 3: and I think back to when you came on the

498
00:24:47,960 --> 00:24:51,280
Speaker 3: show in February twenty twenty four, it had grown so

499
00:24:51,440 --> 00:24:55,639
Speaker 3: quickly the company update us on what Sierra looks like today.

500
00:24:56,960 --> 00:24:59,960
Speaker 5: Well, we have customers across a wide range of industries,

501
00:25:00,040 --> 00:25:03,080
Speaker 5: from some of the largest health insurance companies to banks

502
00:25:03,359 --> 00:25:06,119
Speaker 5: to some of the fastest growing companies in Silicon Valley,

503
00:25:06,240 --> 00:25:09,000
Speaker 5: like Ramp, which is we're also a proud customer of

504
00:25:09,080 --> 00:25:12,240
Speaker 5: They power all of our corporate credit cards. What's remarkable

505
00:25:12,400 --> 00:25:15,399
Speaker 5: is just the size of customers that have aligned with us.

506
00:25:15,480 --> 00:25:18,040
Speaker 5: So over twenty percent of our customers have over ten

507
00:25:18,080 --> 00:25:20,919
Speaker 5: billion in revenue, over half have over a billion in revenue.

508
00:25:20,960 --> 00:25:23,520
Speaker 5: These aren't just early adopters, right, These are some of

509
00:25:23,520 --> 00:25:27,159
Speaker 5: the most traditional financial services firms, healthcare firms that are

510
00:25:27,200 --> 00:25:29,520
Speaker 5: really saying, Hey, I don't want my customers to.

511
00:25:29,560 --> 00:25:31,800
Speaker 11: Have to wait on hold or press two for service.

512
00:25:32,200 --> 00:25:35,920
Speaker 5: Can we have a multi lingual, delightful AI agent just

513
00:25:36,000 --> 00:25:39,040
Speaker 5: pick up the phone and solve problems automatically. And what's

514
00:25:39,040 --> 00:25:41,600
Speaker 5: remarkable is just how well it works. You know, you

515
00:25:42,080 --> 00:25:44,640
Speaker 5: brought up RAMP at the beginning of the call. Their

516
00:25:44,720 --> 00:25:48,960
Speaker 5: AI agent is actually solving ninety percent of customer cases

517
00:25:49,000 --> 00:25:52,440
Speaker 5: completely autonomously. And you know that's obviously great for Ramp

518
00:25:52,480 --> 00:25:54,520
Speaker 5: as a business, but for me as a customer of Ramp.

519
00:25:54,520 --> 00:25:56,480
Speaker 5: It means I don't have to wait on hold ninety

520
00:25:56,480 --> 00:25:59,840
Speaker 5: percent of the time. It's completely transforming the industry and

521
00:26:00,080 --> 00:26:02,600
Speaker 5: it is so fun to be able to help brands

522
00:26:02,600 --> 00:26:05,160
Speaker 5: really in every industry transform their customer experience.

523
00:26:06,680 --> 00:26:09,800
Speaker 3: Brett, I'd still like to learn more about Sierra. So

524
00:26:09,840 --> 00:26:12,639
Speaker 3: you talked about you haven't seen growth like this in

525
00:26:12,760 --> 00:26:16,240
Speaker 3: your career. Would you share with us an arr figure,

526
00:26:16,800 --> 00:26:20,199
Speaker 3: what Sierra's financials look like, number of team members, how

527
00:26:20,240 --> 00:26:21,320
Speaker 3: aggressively you're hiring.

528
00:26:22,840 --> 00:26:25,040
Speaker 5: I won't share a rr numbers, sorry, but maybe when

529
00:26:25,080 --> 00:26:26,720
Speaker 5: we do, I'll come back on this show and you

530
00:26:26,760 --> 00:26:29,240
Speaker 5: can hear it first. But I'll tell you we have

531
00:26:29,320 --> 00:26:33,080
Speaker 5: hundreds of employees. We've opened offices in New York, Atlanta, London.

532
00:26:33,440 --> 00:26:36,600
Speaker 5: We're planning our expansion into Asia. We're the leader in

533
00:26:36,600 --> 00:26:39,080
Speaker 5: this space. We'll do hundreds of millions of phone calls

534
00:26:39,119 --> 00:26:42,359
Speaker 5: on our platform this year, hundreds of millions of digital chats.

535
00:26:42,880 --> 00:26:46,320
Speaker 5: We're the highest volume company in this space, and really

536
00:26:46,359 --> 00:26:48,679
Speaker 5: that scale benefits all of our customers. It means we

537
00:26:48,720 --> 00:26:52,359
Speaker 5: support more languages, it means that we've dealt with some

538
00:26:52,400 --> 00:26:56,320
Speaker 5: of the most complex regulatory landscapes from hip A compliance

539
00:26:56,400 --> 00:27:00,840
Speaker 5: to the compliance regimes that apply to the financial industry.

540
00:27:01,240 --> 00:27:04,160
Speaker 5: We're really trying to be the best and safest bet

541
00:27:04,200 --> 00:27:06,280
Speaker 5: for every company in the world who wants to transform

542
00:27:06,320 --> 00:27:07,760
Speaker 5: their customer experience who they are.

543
00:27:08,400 --> 00:27:11,280
Speaker 4: And to do that, you're scaling, and I'm sure there's

544
00:27:11,320 --> 00:27:13,439
Speaker 4: a little bit of a fierce fight out there for

545
00:27:13,560 --> 00:27:16,359
Speaker 4: talent and that costs money before get into the talent

546
00:27:16,480 --> 00:27:18,720
Speaker 4: wars a little bit, Brett, what about having to raise

547
00:27:18,720 --> 00:27:20,800
Speaker 4: more money because you did back in twenty twenty four.

548
00:27:20,880 --> 00:27:22,480
Speaker 7: Do you need any more? We've got a good runway.

549
00:27:23,600 --> 00:27:25,440
Speaker 5: We have a good runway. But it's a great question,

550
00:27:25,640 --> 00:27:29,880
Speaker 5: just because I do think that we really want to

551
00:27:29,920 --> 00:27:32,880
Speaker 5: grow as quickly as possible. There's this great I attribute

552
00:27:32,920 --> 00:27:36,600
Speaker 5: to Albert Einstein. As quickly as possible, but no more quickly.

553
00:27:37,320 --> 00:27:40,320
Speaker 5: And you know right now our businesses work in I've

554
00:27:40,359 --> 00:27:43,119
Speaker 5: never seen product market that quite like this. And we're

555
00:27:43,160 --> 00:27:46,320
Speaker 5: always asking ourselves the question as a management team, how

556
00:27:46,359 --> 00:27:49,400
Speaker 5: fast can we grow? Because if you look around the world,

557
00:27:49,600 --> 00:27:52,920
Speaker 5: the application of technology is not limited to one industry,

558
00:27:53,040 --> 00:27:55,840
Speaker 5: is not limited to one country. How can we best

559
00:27:55,840 --> 00:27:59,159
Speaker 5: serve not just multinationals based here, but in Europe and

560
00:27:59,200 --> 00:28:02,080
Speaker 5: Asia as well? And so if raising more money will

561
00:28:02,160 --> 00:28:06,000
Speaker 5: enable us to achieve that end, we're absolutely open to it. Thankfully,

562
00:28:06,040 --> 00:28:07,959
Speaker 5: we have a really healthy business model and it's not

563
00:28:08,000 --> 00:28:10,160
Speaker 5: something we need to do, but absolutely something we're allays

564
00:28:10,240 --> 00:28:11,720
Speaker 5: open to considering because.

565
00:28:11,480 --> 00:28:13,400
Speaker 4: In many ways, Look, you raised one hundred and seventy

566
00:28:13,400 --> 00:28:16,159
Speaker 4: five million last year led by Green Oaks Capital.

567
00:28:16,680 --> 00:28:18,760
Speaker 7: I'm thinking like two hundred million.

568
00:28:18,520 --> 00:28:21,119
Speaker 4: Dollars is now what Meta is willing to pay to

569
00:28:21,160 --> 00:28:23,720
Speaker 4: get one person. In terms of talent, Brett, Yeah, we

570
00:28:23,760 --> 00:28:27,439
Speaker 4: all chose the wrong profector here. You didn't, but Brett,

571
00:28:27,440 --> 00:28:29,680
Speaker 4: I mean, I'm no coder, but Brett, tell us a

572
00:28:29,720 --> 00:28:32,359
Speaker 4: little bit about trying to get that sort off the

573
00:28:32,400 --> 00:28:33,479
Speaker 4: talent do you need it?

574
00:28:33,520 --> 00:28:34,640
Speaker 7: And how face is it?

575
00:28:35,920 --> 00:28:38,280
Speaker 5: Well, first, you know, I do think there's a slight

576
00:28:38,320 --> 00:28:43,400
Speaker 5: difference between the really small handful of researchers building these

577
00:28:43,440 --> 00:28:46,280
Speaker 5: foundation models at the research labs and you know, Sierra,

578
00:28:46,360 --> 00:28:48,480
Speaker 5: we're an apply to I company, So you can think

579
00:28:48,520 --> 00:28:51,800
Speaker 5: of us not necessarily as the folks doing the R

580
00:28:51,920 --> 00:28:55,160
Speaker 5: and D to build these frontier models like Open Eye

581
00:28:55,280 --> 00:28:58,480
Speaker 5: GPT five, but really taking all of those models and

582
00:28:58,520 --> 00:29:01,760
Speaker 5: fine tuning them and applying them to a solution in

583
00:29:01,760 --> 00:29:03,840
Speaker 5: the marketplace, so you can really think of the market.

584
00:29:03,880 --> 00:29:06,760
Speaker 5: I think of it really in three areas. The companies

585
00:29:06,760 --> 00:29:10,120
Speaker 5: building these frontier models, open the eyes models are obviously

586
00:29:10,160 --> 00:29:13,200
Speaker 5: the leading and frontier models in the space. You have

587
00:29:13,280 --> 00:29:16,000
Speaker 5: companies building tools, So what are the tools you need

588
00:29:16,520 --> 00:29:18,880
Speaker 5: if you're applying AI in your business. These are companies

589
00:29:18,880 --> 00:29:22,840
Speaker 5: that can do data labeling and data transformation and data storage.

590
00:29:22,960 --> 00:29:26,040
Speaker 5: And then you have companies like Ours and Cursor and

591
00:29:26,160 --> 00:29:29,800
Speaker 5: Harvey that are taking all of that great technology and

592
00:29:29,840 --> 00:29:32,040
Speaker 5: making a push button solution so you can just solve

593
00:29:32,080 --> 00:29:34,920
Speaker 5: a problem without a lot of implementation time. We just

594
00:29:34,960 --> 00:29:38,560
Speaker 5: went live with an international retailer in fifteen markets in

595
00:29:38,720 --> 00:29:41,719
Speaker 5: six weeks and are solving eighty five percent of their

596
00:29:41,720 --> 00:29:45,239
Speaker 5: customer service cases automatically. That's what really an apply DA

597
00:29:45,360 --> 00:29:48,360
Speaker 5: company does is makes it easy to consume, easy to deploy.

598
00:29:48,680 --> 00:29:50,880
Speaker 5: So thankfully we're not competing in the market for some

599
00:29:50,960 --> 00:29:55,480
Speaker 5: of those I think widely publicized researchers. But as you said,

600
00:29:55,480 --> 00:29:58,719
Speaker 5: it's a competitive market, a competitive market for talent, as

601
00:29:58,720 --> 00:29:59,720
Speaker 5: it always is in the Valley.

602
00:30:00,920 --> 00:30:03,400
Speaker 3: You know, Brett, Over the years, I got told a

603
00:30:03,400 --> 00:30:05,840
Speaker 3: lot of stories about you in meetings, like in the

604
00:30:05,840 --> 00:30:08,840
Speaker 3: Salesforce context. And you know, basically people say you're pretty

605
00:30:08,840 --> 00:30:12,320
Speaker 3: frighteningly effective when you talk to customers, but you're also

606
00:30:12,720 --> 00:30:15,120
Speaker 3: you know, you're a busy guy. You have a very

607
00:30:15,200 --> 00:30:19,080
Speaker 3: unusual jewel roll right as chairman of open Ai and

608
00:30:19,160 --> 00:30:22,440
Speaker 3: chairman of its board. That's an unusual gig. How do

609
00:30:22,480 --> 00:30:23,440
Speaker 3: you split the time?

610
00:30:25,480 --> 00:30:27,600
Speaker 5: You know, I love to work, is the short answer.

611
00:30:27,920 --> 00:30:29,920
Speaker 5: So I work from the moment I get up to

612
00:30:30,200 --> 00:30:32,080
Speaker 5: the moment I go to sleep, and I love every

613
00:30:32,080 --> 00:30:35,760
Speaker 5: minute of it. And you know, some weeks I'll spend

614
00:30:35,760 --> 00:30:37,560
Speaker 5: more time at some two weeks last. It's really what

615
00:30:37,640 --> 00:30:41,480
Speaker 5: the organization demands. And you know, it is a lot

616
00:30:41,520 --> 00:30:44,280
Speaker 5: of work, but it is such a privilege just because well,

617
00:30:44,280 --> 00:30:46,760
Speaker 5: I'm very excited about what Siro is doing. To be

618
00:30:46,800 --> 00:30:49,480
Speaker 5: able to spend time with I think the greatest research

619
00:30:49,600 --> 00:30:52,160
Speaker 5: lab in the world developing, I think the most important

620
00:30:52,160 --> 00:30:55,040
Speaker 5: consumer product in the world in chat GPT is such

621
00:30:55,040 --> 00:30:58,240
Speaker 5: a privilege and it makes me a better leader. I

622
00:30:58,280 --> 00:31:01,360
Speaker 5: understand AI with more depth than ones. And then similarly,

623
00:31:01,360 --> 00:31:04,520
Speaker 5: hopefully my experience having scaled a lot of companies in

624
00:31:04,560 --> 00:31:07,680
Speaker 5: the past is helping Open Eye, is it? I think

625
00:31:07,760 --> 00:31:10,240
Speaker 5: it's scaling and faster than really any company in history,

626
00:31:10,280 --> 00:31:12,880
Speaker 5: and so it's so fun. I wouldn't have it any

627
00:31:12,920 --> 00:31:16,760
Speaker 5: other way. Sleep is for the week, right.

628
00:31:17,080 --> 00:31:18,840
Speaker 3: The big question our audience has for you in the

629
00:31:18,840 --> 00:31:21,239
Speaker 3: open AYE context is how much you're working on this

630
00:31:21,280 --> 00:31:24,800
Speaker 3: relationship with Microsoft and how much you personally have focused

631
00:31:24,840 --> 00:31:27,720
Speaker 3: on the restructuring or the move to a new or

632
00:31:27,760 --> 00:31:29,040
Speaker 3: different corporate structure.

633
00:31:30,240 --> 00:31:33,840
Speaker 5: Well, Microsoft is open Ey's most important partner and has

634
00:31:33,880 --> 00:31:37,880
Speaker 5: been for years, so it's a very important relationship. The

635
00:31:37,920 --> 00:31:41,479
Speaker 5: board's role is really specific. Open Eyes a not for profit.

636
00:31:41,640 --> 00:31:45,240
Speaker 5: Our fiduciary duties on the board are really related exclusively

637
00:31:45,280 --> 00:31:47,760
Speaker 5: to our mission, which is to ensure that our official

638
00:31:47,800 --> 00:31:52,200
Speaker 5: general intelligent intelligence benefits humanity. And so we're always thinking

639
00:31:52,760 --> 00:31:55,000
Speaker 5: how do we set up the organization over the long

640
00:31:55,080 --> 00:31:57,960
Speaker 5: term to ensure that we can achieve that goal. And

641
00:31:58,080 --> 00:31:59,480
Speaker 5: you know, one of the things that we've talked a

642
00:31:59,480 --> 00:32:02,400
Speaker 5: lot about is, you know, since the company was founded

643
00:32:02,440 --> 00:32:06,040
Speaker 5: as a small research lab, the level of capital expenditure

644
00:32:06,080 --> 00:32:09,800
Speaker 5: required for the infrastructure for AI, I think exceeds anyone's

645
00:32:09,920 --> 00:32:13,479
Speaker 5: expectations that they had a year ago, let alone ten

646
00:32:13,560 --> 00:32:16,240
Speaker 5: years ago, and so really thinking about how do we

647
00:32:16,320 --> 00:32:18,560
Speaker 5: ensure that we remain a mission driven not for profit,

648
00:32:18,680 --> 00:32:21,320
Speaker 5: but also set up our organization so we can raise

649
00:32:21,360 --> 00:32:24,560
Speaker 5: the capital we need to achieve that mission. So that's

650
00:32:24,600 --> 00:32:27,000
Speaker 5: what I think the media is appropriately called the restructuring.

651
00:32:27,040 --> 00:32:29,280
Speaker 5: It is something that we're working on. Nothing to announce

652
00:32:29,320 --> 00:32:30,360
Speaker 5: it this time, but I think it's one of the

653
00:32:30,400 --> 00:32:32,680
Speaker 5: most important things we work on as a board, because

654
00:32:33,200 --> 00:32:35,560
Speaker 5: your job as a board is to set the company

655
00:32:35,640 --> 00:32:37,200
Speaker 5: up for the future, and that's really how we think

656
00:32:37,200 --> 00:32:37,520
Speaker 5: about it.

657
00:32:37,640 --> 00:32:39,160
Speaker 7: Do you think you'll get it done by the end

658
00:32:39,200 --> 00:32:39,840
Speaker 7: of this year, Brett?

659
00:32:41,920 --> 00:32:44,600
Speaker 5: I can't really comment on timelines, and you know, we're

660
00:32:44,600 --> 00:32:48,360
Speaker 5: really just trying to work with all the stakeholders who

661
00:32:48,360 --> 00:32:50,520
Speaker 5: have an interest in it and most importantly focused on

662
00:32:50,560 --> 00:32:52,960
Speaker 5: the mission. But no update on the time frame.

663
00:32:54,120 --> 00:32:57,360
Speaker 3: Redeye a CEO of Sierra and chairman of the board

664
00:32:57,360 --> 00:32:59,280
Speaker 3: for Open AI. Thank you very much for your time.

665
00:33:00,520 --> 00:33:02,520
Speaker 3: This is Bloomberg Tech and you're looking at a live

666
00:33:02,560 --> 00:33:05,840
Speaker 3: shot of the principal room. Check out the Bloomberg Tech podcast.

667
00:33:05,920 --> 00:33:08,080
Speaker 3: You can find it on the terminal so its online

668
00:33:08,120 --> 00:33:20,840
Speaker 3: on Apple, Spotify and on iHeart. This is Bloomberg. Okay,

669
00:33:21,040 --> 00:33:23,400
Speaker 3: all eyes are meta real quick. In the session, it's

670
00:33:23,400 --> 00:33:26,960
Speaker 3: made attempts to hit all time highs and at one

671
00:33:26,960 --> 00:33:30,400
Speaker 3: point go beyond two trillion dollars of market cap for

672
00:33:30,480 --> 00:33:32,280
Speaker 3: the first time. Where will we close We don't know,

673
00:33:32,360 --> 00:33:34,280
Speaker 3: but it's exciting and it's one to watch. And we're

674
00:33:34,320 --> 00:33:36,960
Speaker 3: also thinking a lot about Meta's AI app, which is

675
00:33:37,000 --> 00:33:41,720
Speaker 3: facing mounting pressure with users complaining of an underpersonalized and

676
00:33:41,920 --> 00:33:46,080
Speaker 3: inconsistent experience. The tech giant emitting this is quote just

677
00:33:46,120 --> 00:33:48,800
Speaker 3: the first and many steps, as the company will continue

678
00:33:48,880 --> 00:33:52,560
Speaker 3: to make updates over time. Joining us now is Bloomberg's

679
00:33:52,680 --> 00:33:55,800
Speaker 3: Natalie Lung. This is the post launch digest, tell us.

680
00:33:55,680 --> 00:33:56,280
Speaker 2: What we need to know.

681
00:33:57,040 --> 00:33:59,200
Speaker 15: Yeah, we have tested it for a few weeks and

682
00:33:59,400 --> 00:34:04,680
Speaker 15: asking it basic inquiries, asking it for personalized recommendations, and

683
00:34:04,720 --> 00:34:08,520
Speaker 15: overall we found the experience rather inconsistent and it felt

684
00:34:08,520 --> 00:34:11,759
Speaker 15: a little bit half baked. For example, I asked it

685
00:34:11,800 --> 00:34:14,200
Speaker 15: to give me recommendations and what to do over the

686
00:34:14,200 --> 00:34:17,120
Speaker 15: weekend here in New York City. For some reason, it

687
00:34:17,200 --> 00:34:19,239
Speaker 15: knew min zip code. I might have provided it to

688
00:34:19,239 --> 00:34:22,120
Speaker 15: an advertiser one time, but it wasn't able to personalize

689
00:34:22,160 --> 00:34:26,759
Speaker 15: it to that area. And the unique thing about it,

690
00:34:26,840 --> 00:34:30,359
Speaker 15: apart from Rivals, is that it has a discover feed

691
00:34:30,600 --> 00:34:33,680
Speaker 15: where you can see how others are prompting and interacting

692
00:34:33,680 --> 00:34:36,880
Speaker 15: with the chatbot, and they're like endless images.

693
00:34:36,920 --> 00:34:38,239
Speaker 5: There, you can see.

694
00:34:38,400 --> 00:34:40,960
Speaker 4: Endless images that perhaps aren't that relevant to you, and

695
00:34:41,040 --> 00:34:44,719
Speaker 4: sometimes the more edgy types of chatbots you might not

696
00:34:44,760 --> 00:34:47,759
Speaker 4: want to interface with, Natalie, what's so weird as well?

697
00:34:47,880 --> 00:34:51,239
Speaker 4: Is I interact with METAAI actually more within the WhatsApp

698
00:34:51,800 --> 00:34:55,880
Speaker 4: offering and maybe within the Instagram offering? Why is that

699
00:34:56,080 --> 00:34:58,880
Speaker 4: not taking my data that I'm feeding it and bringing

700
00:34:58,880 --> 00:35:01,080
Speaker 4: it over to Meta right now?

701
00:35:01,160 --> 00:35:03,879
Speaker 15: All of those experiences are not connected, as you rightly

702
00:35:03,880 --> 00:35:07,080
Speaker 15: pointed out. It is on WhatsApp, it is on Messenger,

703
00:35:07,120 --> 00:35:10,359
Speaker 15: it is on Instagram, but they're not connected, which makes

704
00:35:10,400 --> 00:35:15,719
Speaker 15: it a little bit foreshot of some of the personalization

705
00:35:15,920 --> 00:35:17,719
Speaker 15: ambitions that Zuckerberg has.

706
00:35:18,280 --> 00:35:21,600
Speaker 7: Almost Natalie Lang a real deep dive. Go read the analysis.

707
00:35:27,320 --> 00:35:29,440
Speaker 4: Getting back to our top story, the White House is

708
00:35:29,480 --> 00:35:32,120
Speaker 4: set to consider using chips At funding to take a

709
00:35:32,200 --> 00:35:35,480
Speaker 4: stake in Intel, scording to sources from more Bloombergs. Ryan

710
00:35:35,480 --> 00:35:37,719
Speaker 4: Gould is here who helped break this story. It's been

711
00:35:37,880 --> 00:35:40,239
Speaker 4: very busy twenty four hours. Do we have any idea

712
00:35:40,280 --> 00:35:41,759
Speaker 4: how much equity they could take for this?

713
00:35:42,040 --> 00:35:42,840
Speaker 2: Not yet, Caroline.

714
00:35:42,840 --> 00:35:45,440
Speaker 16: We're still trying to find out exactly how much the

715
00:35:45,440 --> 00:35:47,600
Speaker 16: government is talking. I mean, just on the base of it.

716
00:35:47,600 --> 00:35:49,600
Speaker 16: If you think about the problems that are facing Intel

717
00:35:49,680 --> 00:35:53,560
Speaker 16: right now, you're probably looking to solve something as big

718
00:35:53,600 --> 00:35:56,360
Speaker 16: as Ohio to onshore manufacturing in the US. You're talking

719
00:35:56,400 --> 00:35:58,920
Speaker 16: tens of billions of dollars that the company needs. Now,

720
00:35:58,920 --> 00:36:00,320
Speaker 16: I'm not going to suggest that they got it is

721
00:36:00,320 --> 00:36:01,600
Speaker 16: going to go out and put that money in. We

722
00:36:01,640 --> 00:36:04,279
Speaker 16: don't know, and the government has not obviously commented on

723
00:36:04,320 --> 00:36:07,800
Speaker 16: this reporting yet, but I would say that you know

724
00:36:07,920 --> 00:36:10,839
Speaker 16: that the challenges facing Intel are vast, and I think

725
00:36:10,920 --> 00:36:14,120
Speaker 16: most investors and alis know that. I think, just at

726
00:36:14,120 --> 00:36:16,080
Speaker 16: the top of this, though, it's worth taking a step

727
00:36:16,120 --> 00:36:18,440
Speaker 16: back and thinking about what a difference a week makes.

728
00:36:18,640 --> 00:36:21,280
Speaker 16: If you think about Donald Trump calling for the resignation

729
00:36:21,320 --> 00:36:24,839
Speaker 16: of Liputen, the CEO, last Thursday, last Friday, I mean

730
00:36:24,920 --> 00:36:27,040
Speaker 16: a week later, we're now on the cusp of maybe

731
00:36:27,080 --> 00:36:29,719
Speaker 16: a potentially game changing deal, at least in the short

732
00:36:29,800 --> 00:36:33,320
Speaker 16: term for one of America's most beleagued companies.

733
00:36:34,440 --> 00:36:37,040
Speaker 3: Bloombos Ryan Gould part of the reporting team, or an

734
00:36:37,080 --> 00:36:38,320
Speaker 3: astonishing week for Intel.

735
00:36:38,320 --> 00:36:38,600
Speaker 2: Thank you.

736
00:36:38,680 --> 00:36:41,200
Speaker 3: Let's get more on Intel and Washington's chip goals and

737
00:36:41,200 --> 00:36:45,319
Speaker 3: how this all fits in Ben hur in Creative Strategy CEO, Ben,

738
00:36:45,360 --> 00:36:47,440
Speaker 3: for loads of people, this isn't actually an issue of

739
00:36:47,480 --> 00:36:50,839
Speaker 3: money for Intel, It's an issue of technology and it's

740
00:36:50,880 --> 00:36:54,319
Speaker 3: an issue of no customers. How did you react to

741
00:36:54,320 --> 00:36:56,520
Speaker 3: Bloomberg's reporting in the last twenty four hours.

742
00:36:57,680 --> 00:36:59,680
Speaker 17: Yeah, I mean, I think we've been looking at this

743
00:36:59,800 --> 00:37:03,680
Speaker 17: from some sort of a leading in this direction for

744
00:37:03,760 --> 00:37:06,400
Speaker 17: some time. I mean, obviously, when you know, Trump came

745
00:37:06,480 --> 00:37:09,120
Speaker 17: up and said what he said about lip butan we

746
00:37:09,200 --> 00:37:11,279
Speaker 17: felt that this was in light of wanting to do

747
00:37:11,840 --> 00:37:14,239
Speaker 17: or at least have a broader conversation that had not

748
00:37:14,360 --> 00:37:16,680
Speaker 17: had happened prior. If he's noted like Intel was not

749
00:37:17,239 --> 00:37:19,279
Speaker 17: involved in a lot of the you know, sort of

750
00:37:19,400 --> 00:37:23,640
Speaker 17: public displays of America first, even though everybody knows they're

751
00:37:23,680 --> 00:37:27,840
Speaker 17: America first. And obviously his comments right on earnings about

752
00:37:27,920 --> 00:37:29,759
Speaker 17: you know, they may not go forward to fourteen A

753
00:37:29,880 --> 00:37:32,399
Speaker 17: without help, I think was very telling. And I think

754
00:37:32,400 --> 00:37:34,560
Speaker 17: all of that led to this moment, which is, you know,

755
00:37:34,560 --> 00:37:39,160
Speaker 17: from a national security standpoint, and really anybody in insecurity

756
00:37:39,360 --> 00:37:41,000
Speaker 17: and knowing what's going on in chips in the US

757
00:37:41,080 --> 00:37:44,400
Speaker 17: should believe we want a US company to make leading

758
00:37:44,520 --> 00:37:47,160
Speaker 17: edge chips here in the United States, and that's Intel.

759
00:37:47,239 --> 00:37:49,520
Speaker 17: So we want to see some resolution, right as one

760
00:37:49,600 --> 00:37:52,120
Speaker 17: hundred percent clear. Like you said, they need customers and

761
00:37:52,200 --> 00:37:54,200
Speaker 17: we need to figure out how to get some form

762
00:37:54,200 --> 00:37:55,640
Speaker 17: of capital so they can keep going.

763
00:37:57,360 --> 00:37:59,920
Speaker 3: Over the course of five days, Intel's up twenty seven percent.

764
00:38:00,040 --> 00:38:02,120
Speaker 3: If it closes at those levels, it will be the

765
00:38:02,160 --> 00:38:05,760
Speaker 3: biggest weekly gain on record on a closing basis, which, yeah,

766
00:38:06,160 --> 00:38:09,600
Speaker 3: is Boo Tan the man for this Ben Yeah.

767
00:38:09,400 --> 00:38:12,000
Speaker 17: I mean I think his approach is fairly pragmatic. Right,

768
00:38:12,040 --> 00:38:15,719
Speaker 17: It's not just about build and invests. Build the right technology,

769
00:38:15,719 --> 00:38:18,000
Speaker 17: but do so in a capital way that makes sense.

770
00:38:18,000 --> 00:38:19,680
Speaker 17: I think that's really what the board wants, that's what

771
00:38:19,800 --> 00:38:21,000
Speaker 17: investors wants.

772
00:38:21,480 --> 00:38:21,640
Speaker 5: You know.

773
00:38:21,640 --> 00:38:23,759
Speaker 17: And I think really the strategy is, again, how much

774
00:38:23,800 --> 00:38:26,760
Speaker 17: money do they actually need. I do think the tens

775
00:38:26,760 --> 00:38:28,680
Speaker 17: of billions of dollars is right in terms of to

776
00:38:28,760 --> 00:38:31,399
Speaker 17: get to fourteen A on top of what Intel will

777
00:38:31,400 --> 00:38:33,880
Speaker 17: bring in customers. But the bottom line is right, they

778
00:38:33,920 --> 00:38:36,000
Speaker 17: can't do this on their own, that's what they're saying.

779
00:38:36,000 --> 00:38:38,560
Speaker 17: Whether it's customers or whether it's the government. You know,

780
00:38:38,760 --> 00:38:40,880
Speaker 17: there needs to be an infusion of capital that's not

781
00:38:41,040 --> 00:38:43,560
Speaker 17: just Intel, to make sure that foundry is secured for

782
00:38:43,600 --> 00:38:44,160
Speaker 17: the long haul.

783
00:38:44,880 --> 00:38:48,440
Speaker 4: Ben there is this chicken nag situation because le Bhutan is saying,

784
00:38:48,480 --> 00:38:49,960
Speaker 4: I'm not going to build it and wait for them

785
00:38:50,000 --> 00:38:52,360
Speaker 4: to come. They've got to tell me that the demand

786
00:38:52,440 --> 00:38:55,320
Speaker 4: is there. Does in some way taking equity by the

787
00:38:55,400 --> 00:38:58,440
Speaker 4: US government incentivize others to get behind the government and

788
00:38:58,480 --> 00:39:01,040
Speaker 4: say will buy them. We'll them if indeed you do

789
00:39:01,080 --> 00:39:02,759
Speaker 4: innovate and get that fourteen A out there.

790
00:39:04,120 --> 00:39:05,400
Speaker 17: I mean, I think it's got to be more than

791
00:39:05,480 --> 00:39:07,680
Speaker 17: just the government stake. I mean, I think what everybody's

792
00:39:07,680 --> 00:39:10,120
Speaker 17: been speculating is would that come along with some form

793
00:39:10,160 --> 00:39:13,680
Speaker 17: of a of a tariff or something that you know,

794
00:39:13,960 --> 00:39:18,840
Speaker 17: strongly incentivized companies like you know, Nvidia, Apple, A, md Qualcom,

795
00:39:18,840 --> 00:39:22,440
Speaker 17: et cetera to not you know, use TSMC, but then

796
00:39:22,800 --> 00:39:25,400
Speaker 17: use some capacity of Intel, not one hundred percent, but

797
00:39:25,440 --> 00:39:25,839
Speaker 17: some of it.

798
00:39:26,080 --> 00:39:27,719
Speaker 11: So I think it would necessitate that.

799
00:39:27,960 --> 00:39:30,319
Speaker 17: You know, again, I think we want Intel to win

800
00:39:30,400 --> 00:39:32,839
Speaker 17: on the merit of technology, which we think is very

801
00:39:32,840 --> 00:39:35,040
Speaker 17: good on paper, but they just need to get some

802
00:39:35,120 --> 00:39:38,480
Speaker 17: customer wins. And I think once that happens, the confidence,

803
00:39:38,640 --> 00:39:40,799
Speaker 17: you know, continues but again they're at a they're at

804
00:39:40,840 --> 00:39:43,440
Speaker 17: a need for capital, and so how that arises is

805
00:39:43,960 --> 00:39:45,360
Speaker 17: sort of the root of this situation.

806
00:39:45,880 --> 00:39:48,720
Speaker 4: Ben, that's interesting that you say the tariff tactic because

807
00:39:48,719 --> 00:39:51,319
Speaker 4: we've heard on air Force one from President Trump today.

808
00:39:51,320 --> 00:39:52,760
Speaker 7: Then maybe it goes fast two hundred.

809
00:39:52,560 --> 00:39:55,680
Speaker 4: Three hundred percent tariffs on semiconductors. But then there's all

810
00:39:55,680 --> 00:39:58,280
Speaker 4: these carv oalves, particularly for companies investing in the US,

811
00:39:58,400 --> 00:40:02,359
Speaker 4: like TSMC likes, I'm sung Intel's biggest competitives.

812
00:40:03,320 --> 00:40:05,760
Speaker 17: Yeah, And I think the difference though, is that Intel

813
00:40:05,880 --> 00:40:08,520
Speaker 17: is more at the leading edge, So TSMC is not

814
00:40:08,560 --> 00:40:10,440
Speaker 17: going to bring in. The Taiwanese government has been very

815
00:40:10,440 --> 00:40:13,520
Speaker 17: clear they're not going to allow them to bring the

816
00:40:13,600 --> 00:40:16,720
Speaker 17: leading edge. So call it two naanimeter, one nanometer and beyond.

817
00:40:16,960 --> 00:40:20,680
Speaker 17: Samsung's equally struggling to hit that number even though they're trying.

818
00:40:20,840 --> 00:40:23,560
Speaker 17: Intel's really the best bet. And more importantly, Intel is

819
00:40:23,600 --> 00:40:26,120
Speaker 17: an American company, And so that's why I say, like,

820
00:40:26,280 --> 00:40:30,200
Speaker 17: if this is some investment of peep private equity plus government,

821
00:40:30,600 --> 00:40:32,800
Speaker 17: it makes sense that they want to protect that investment,

822
00:40:32,880 --> 00:40:35,120
Speaker 17: so they will do what they need in terms of

823
00:40:35,200 --> 00:40:38,640
Speaker 17: terrorists or some other form of regulations that just encourage

824
00:40:38,680 --> 00:40:41,640
Speaker 17: customers to use Intel. But again, I still think it's

825
00:40:41,640 --> 00:40:44,799
Speaker 17: better if Intel just wins on technological merit, which we

826
00:40:44,840 --> 00:40:45,440
Speaker 17: think they have.

827
00:40:46,160 --> 00:40:48,000
Speaker 11: But we need a bridge, we need a gap, and.

828
00:40:48,239 --> 00:40:50,279
Speaker 17: That's kind of where everybodys struggling to figure out where

829
00:40:50,280 --> 00:40:50,960
Speaker 17: that comes from.

830
00:40:52,400 --> 00:40:55,560
Speaker 3: Ben Intel will not comment on Bloomberg's reporting. The White

831
00:40:55,600 --> 00:40:59,680
Speaker 3: House hasn't said anything to confirm the reporting. But the

832
00:40:59,800 --> 00:41:01,920
Speaker 3: chart says, you assigned to this deal happening.

833
00:41:04,000 --> 00:41:05,480
Speaker 11: Oh, it's a tough it's a good question.

834
00:41:05,640 --> 00:41:08,960
Speaker 17: I mean, I think it really comes down to do

835
00:41:09,120 --> 00:41:11,640
Speaker 17: would they believe that they could structure this in the

836
00:41:11,680 --> 00:41:15,360
Speaker 17: way in a way that's fair, whether that's divesting of

837
00:41:15,400 --> 00:41:18,480
Speaker 17: shares right or paying that back like some of the

838
00:41:18,480 --> 00:41:20,319
Speaker 17: ways where you've seen them when they have to do,

839
00:41:20,560 --> 00:41:23,120
Speaker 17: you know, investments in companies, so.

840
00:41:23,040 --> 00:41:24,600
Speaker 11: It's not just a constant holding.

841
00:41:24,880 --> 00:41:27,080
Speaker 17: I think when anytime the government gets involved, it's very

842
00:41:27,160 --> 00:41:31,640
Speaker 17: very tricky. But again, right, they need customers. I'd like,

843
00:41:31,640 --> 00:41:33,400
Speaker 17: I know, this is an non answer, I'd say fifty

844
00:41:33,400 --> 00:41:34,040
Speaker 17: to fifty.

845
00:41:33,800 --> 00:41:36,839
Speaker 7: It's okay, but you know, a phone a friend. Fifty

846
00:41:36,880 --> 00:41:37,680
Speaker 7: to fifty phone a friend.

847
00:41:37,719 --> 00:41:41,880
Speaker 4: Benar creative strategies fantastic to get your opinion.

848
00:41:42,239 --> 00:41:43,120
Speaker 7: Thank you very much.

849
00:41:43,160 --> 00:41:45,239
Speaker 4: Indeed, that does it for this edition of Bloomboat Tech.

850
00:41:45,280 --> 00:41:48,000
Speaker 4: An extraordinary week around semiconductor Z.

851
00:41:48,920 --> 00:41:50,719
Speaker 3: Yeah, like the rest of the session, keep an eye

852
00:41:50,719 --> 00:41:53,400
Speaker 3: on Intel if it closes that level best week on record.

853
00:41:53,680 --> 00:41:56,239
Speaker 3: Recap everything we discussed in the podcast. You know where

854
00:41:56,239 --> 00:41:58,839
Speaker 3: to find it on the Bloomberg terminal as well as

855
00:41:58,840 --> 00:42:02,439
Speaker 3: online on Apple fight In. iHeart from New York City

856
00:42:02,480 --> 00:42:04,280
Speaker 3: and London. I'm taking a little.

857
00:42:04,080 --> 00:42:06,360
Speaker 2: Break for a while, but we'll be back. This is

858
00:42:06,400 --> 00:42:07,200
Speaker 2: Koomberg Tech.