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Speaker 1: From Marhart were Innovation, Money and Power Collie in Silicon

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Speaker 1: Valley NBN. This is Bloomberg Technology with Caroline Hyde and

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Speaker 1: Ed Loved Love.

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Speaker 2: Lie from New York and San Francisco. This is Bloomberg

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Speaker 2: Technology coming up. Pamela Harris and Donald Trump squaring off

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Speaker 2: in their first presidential debate.

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Speaker 3: We talked the tech angles and.

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Speaker 4: The crypto sector, nursing declines as betting markets reveal new

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Speaker 4: momentum for the vice president. Markets react to the debate.

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Speaker 2: And Amazon that's big on Britain looking to expand its

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Speaker 2: cloud business with a ten point four billion dollar UK

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Speaker 2: investment plan. The first is market sink. Let's get straight

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Speaker 2: to the first US president debate that saw former President

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Speaker 2: Trump and Vice President Kamala Harris trading on the handling

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Speaker 2: of America's semiconductor industry and the feature of AI.

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Speaker 5: Well, let's be clear that the Trump administration resulted in

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Speaker 5: a trade deficit, one of the highest we've ever seen

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Speaker 5: in the history of America. He invited trade wars. You

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Speaker 5: want to talk about his deal with China. What he

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Speaker 5: ended up doing is under Donald Trump's presidency, he ended

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Speaker 5: up selling American chips to China to help them improve

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Speaker 5: and modernize their military.

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Speaker 6: First of all, they bought their chips from Taiwan. We

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Speaker 6: hardly make chips anymore because of philosophies like they have

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Speaker 6: and policies like they have. I don't say her because

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Speaker 6: she has no policy. Everything that she believed three years

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Speaker 6: ago and four years ago is out the window. She's

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Speaker 6: going to my philosophy now.

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Speaker 7: In fact, I was going to send her a mega hat.

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Speaker 2: Blomberg's David Gura is in Philadelphia. You were there for

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Speaker 2: the live action, David, We focus on the tech angle.

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Speaker 3: But what did you draw from the debate?

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Speaker 7: Well, welcome back to what you just played there.

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Speaker 1: I mean, I think that was a more robust exchange

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Speaker 1: on policy than we saw many of the topics that

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Speaker 1: were covered during the course of that debate. So there

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Speaker 1: were questions about former President Trump's tariff's policy, and of

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Speaker 1: course He's doubled down saying that he's going to impose

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Speaker 1: more blanket tariffs, not just on China, but on Mexico

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Speaker 1: as well other countries. So I thought that that was

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Speaker 1: kind of an illuminating moment and something that Vice President

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Speaker 1: Harris then spoke about afterward were the investments that the

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Speaker 1: Biden administration has made in trying to boost semiconductor production

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Speaker 1: here in the United States during this administration, and also

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Speaker 1: noting the fact that when you look at tariffs and

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Speaker 1: tariffs have been levied on China when it comes to semiconductors,

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Speaker 1: in fact, it has been the Biden Harris administration that

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Speaker 1: has elevated them even more so. Look, this was more

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Speaker 1: than ninety minutes long. It went longer than we thought

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Speaker 1: it would go. Was there's little policy at the beginning,

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Speaker 1: but we saw diversions from that pretty quickly, and I think,

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Speaker 1: you know, to the gree to which economics was discussed.

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Speaker 1: Trade was one moment again where I thought there was

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Speaker 1: at least some spirited back and forth between these two

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Speaker 1: candidates getting to subsubstance on that issue.

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Speaker 4: Guys Harris kept in line with the administration's policy that

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Speaker 4: everything to do with chips from a restriction standpoint is

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Speaker 4: in the interest in national security. And then Trump went

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Speaker 4: after the track record right what they did or didn't

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Speaker 4: do over the last four years. It's hard to see

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Speaker 4: where an aggregate we've landed. David, you know, look at

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Speaker 4: social media and the reporting on the Bloomberg terminal. What

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Speaker 4: is the net result of that debate last night.

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Speaker 1: Well, I go back to what I heard from Governor

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Speaker 1: Gavin Newsom of California before this debate. I said, how

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Speaker 1: pivotal is and how important is it? What difference could

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Speaker 1: this make? And he said, think of it like World

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Speaker 1: War One, where it's going to be something determined by inches,

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Speaker 1: not anything more than that. This is such an incredibly

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Speaker 1: close race between these two candidates, it would be folly

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Speaker 1: to think that a good performance in that debate would

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Speaker 1: have a sizable impact in raising a candidates stature in

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Speaker 1: the polls. Conversely, if there were a bad performance, that

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Speaker 1: would have a negati effect, dramatically negative effect on those

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Speaker 1: polls as well. I think you're right. I mean, you

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Speaker 1: look ahead here. We've got fewer than sixty days until

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Speaker 1: this election. Both of these candidates, I think rightly recognize

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Speaker 1: this is going to be a very hard fought campaign

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Speaker 1: and one that's going to be decided fundamentally by just

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Speaker 1: a few thousand voters. And it's rather extraordinary to say

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Speaker 1: when you look at the whole population of this country

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Speaker 1: and the voting electorate. We talk about swing states, it's

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Speaker 1: more granular than that. Of course, you all know that

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Speaker 1: as well. We're talking about districts in particular. So I

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Speaker 1: think what we're going to see is in effort to

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Speaker 1: capitalize and whatever ment in these candidates got last night,

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Speaker 1: carry that onto the campaign trail. Vice President Harris going

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Speaker 1: down to North Carolina tomorrow, then back up to Pennsylvania,

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Speaker 1: those two swing states over the course of this week.

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Speaker 1: Donald Trump making the pilgrimage out to California for a

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Speaker 1: press conference at the end of the week, when in

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Speaker 1: Nevada and Arizona as well. So they're going to be

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Speaker 1: back on the trail here, trying to talk their book,

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Speaker 1: trying to do all they can to woo those undecided

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Speaker 1: voters again a very small sliver of the US electorate.

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Speaker 4: And of those voters, Taylor Swift now coming out endorsing

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Speaker 4: Kamala Harris, which we'll get to in more detail later

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Speaker 4: in the program. David Gourr on the ground, Thank you

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Speaker 4: very much. Let's continue with the CKS reaction to last

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Speaker 4: night's debate. Bluebogs abail do a little with us, and

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Speaker 4: I think this is cross asset. What are you seeing?

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Speaker 8: It is certainly cross asset, and it's interesting right now,

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Speaker 8: stocks down broadly, the S and P five hundred and

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Speaker 8: the nasack down more than one percent. I think that

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Speaker 8: has less to do with the debate and has more

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Speaker 8: to do with other factors of uncertainty. Relative to the

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Speaker 8: reaction to the debate, I would say right now, DJT

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Speaker 8: is one of the better signals in terms of what

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Speaker 8: investors saw, with the stockdown about fifteen percent, the worst

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Speaker 8: day since April.

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Speaker 4: So I would say this is.

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Speaker 8: Clearly a vote away from the Trump trade, if you will,

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Speaker 8: and one way that the markets are backing VP Kamala Harris.

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Speaker 8: In fact, if we take a look at the betting odds,

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Speaker 8: just yesterday, both candidates had been at fifty two percent

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Speaker 8: a piece. This after former President Donald Trump, right when

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Speaker 8: Kamala Harris got into the race, led her by let's

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Speaker 8: call it twenty percent. She then led Donald Trump by

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Speaker 8: about twelve to fifteen percent. But again yesterday, going into

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Speaker 8: that debate, fifty two percent a piece, the spread five

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Speaker 8: to seven percent apart in favor of VP Harris. So

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Speaker 8: this is another way markets are telling you that they

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Speaker 8: thought that Kamala Harris's performance was at least stronger, and

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Speaker 8: or do they think that she will in fact be

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Speaker 8: elected in November. In fact, if we dig in just

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Speaker 8: a little bit deeper and we take a look at

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Speaker 8: what could be a Harris trade, which would be green energy,

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Speaker 8: it would be healthcare that goes toward Medicare Medicaid along

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Speaker 8: with the home builders. It's interesting that's one area that

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Speaker 8: is actually not favoring her right now. One of her

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Speaker 8: policies for the best that we know is a twenty

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Speaker 8: five thousand dollars tax credit excuse me, down payment for

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Speaker 8: first time homebuilders. Some of the homebuilders that are geared

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Speaker 8: toward those early homebuilders or home buyers, they are down today,

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Speaker 8: but those.

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Speaker 3: Other areas are higher.

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Speaker 8: And then finally, if we round it out with a

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Speaker 8: look at crypto, some clearly Donald Trump is in favor

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Speaker 8: of crypto.

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Speaker 3: Actually this is the VIC.

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Speaker 8: So we do have the VIC signaling overall Caroline the

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Speaker 8: idea of risk off rising, and that's what crypto would

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Speaker 8: signal too. It's down about three percent on the day.

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Speaker 8: If you look at crypto is another way of looking

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Speaker 8: at as a tell on risk on risk off. It's

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Speaker 8: being down confirms the VIX and stocks down confirms a

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Speaker 8: six the VIC higher and stocks down that investors are

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Speaker 8: a little bit uncertain, but overall, the debate right now

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Speaker 8: signals that investors are a little bit more favorable. I

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Speaker 8: would argue toward VP Herris and that uncertainty into November

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Speaker 8: while it's rising.

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Speaker 3: Abigail Dodittle with a wrap up, We thank you.

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Speaker 2: There's also, of course, the macro picture at play with

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Speaker 2: inflation print today and a risk off tone. Let's dig

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Speaker 2: in with Cerah Malic, head of Equities and fixing. Come at,

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Speaker 2: Chief investment officer ever atte Neuven. So great to have

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Speaker 2: you in the studio.

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Speaker 3: Yeah, thanks for having me.

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Speaker 2: I mean, when one factors in political concerns or lead

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Speaker 2: at least uncertainty, and then you have the uncertainty of

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Speaker 2: what inflation is doing, what the Fed's going to do,

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Speaker 2: how do you measure up those risks?

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Speaker 9: I think, yeah, there's three factors driving the markets right

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Speaker 9: now versus seasonality. Second, of course is the election and

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Speaker 9: then the economy. So second half of September for the

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Speaker 9: past four years in a row on on average, tends

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Speaker 9: to be the worst period for the markets for the year.

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Speaker 9: So we're just approaching that and look where we already are.

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Speaker 9: The election I think creating some uncertainty, mostly around expiration

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Speaker 9: of tax cuts and What will that mean in terms

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Speaker 9: of inflation? Could cost up to four points six trillion

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Speaker 9: to renew those for whichever candidate wins the election. But

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Speaker 9: I think the real main event is the economy. Inflation

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Speaker 9: coming out today higher than expected. With CPI driven by shelter.

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Speaker 9: People are worried that the economy is slowing, and inflation

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Speaker 9: isn't slowing fast enough. It holds the FED back. I

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Speaker 9: think we get twenty five basis points this month for

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Speaker 9: a cut, and then we may have a slow start

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Speaker 9: to FED cuts if inflation remains sticky, and that is

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Speaker 9: concerning because economic data is slowly moving to the downside.

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Speaker 2: What does that mean there for around one's portfolio diversification

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Speaker 2: key but people have been putting so much money into

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Speaker 2: seven key names when it comes to technology, does tech

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Speaker 2: continue to outperform?

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Speaker 9: I think tech will outperform as rate cuts six. We

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Speaker 9: can break down tech into three buckets semiconductors, software and megacaps.

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Speaker 9: So software has been the laggard year today. That's where

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Speaker 9: we're most interested. We think there's some attractive names there.

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Speaker 9: It's under owned by portfolio managers, market leading companies like

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Speaker 9: Microsoft and Salesforce. Salesforce in particular looks kind of cheap

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Speaker 9: on evaluation basis, people could as rate cuts happen, could

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Speaker 9: start spending more on their products. Semiconductors probably a little

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Speaker 9: more downside to go and a typical downturn that segment

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Speaker 9: goes down thirty to forty percent. We are not there yet,

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Speaker 9: so I think semis as we approach twenty twenty five,

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Speaker 9: we could see an inflection point as twenty twenty five

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Speaker 9: could be when people start a replacement cycle post COVID

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Speaker 9: and then megacap you need to be selective. We have

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Speaker 9: Meta and Nvidia dominating returns this year. I think people

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Speaker 9: are waiting to see monetization of artificial intelligence for some

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Speaker 9: of those companies return on investment, So megacap you need

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Speaker 9: to be selective. A company we like is Apple, where

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Speaker 9: it's a low cap X play for them to get

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Speaker 9: AI into their phones. That iPhone replacement cycle is slowly

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Speaker 9: starting this year we'll pick up next year. Is more

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Speaker 9: AIS into those phones. I think Apple is the attractive

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Speaker 9: play in megacap.

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Speaker 4: Sarah, do those themes you've outlined continue through the second

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Speaker 4: half of the year into next year irrespective of the

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Speaker 4: outcome of the election. I'm particularly thinking about the megacaps

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Speaker 4: and your commentary on the chip sector, I.

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Speaker 9: Think, well, first of all, on a macro basis, inflation

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Speaker 9: and the economy will continue to be themes throughout this year.

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Speaker 9: I think for semiconductors, you know, the biggest stuff reason

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Speaker 9: for them to inflect will be a replacement cycle. For

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Speaker 9: the socks, you know, whether we're manufacturing and global supply

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Speaker 9: chains onshoreing versus offshoreing could be someone of a bigger

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Speaker 9: issue depending on which candidate wins. Software, I think is

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Speaker 9: more of a rate play, and as companies start to

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Speaker 9: spend more on software and the stocks evaluation. So I

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Speaker 9: think mostly it's the fundamentals is stay intact and which

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Speaker 9: candidate wins the election doesn't have a huge impact on them,

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Speaker 9: but it could have somewhat because we also have to

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Speaker 9: worry about regulations and the degree of regulations on some

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Speaker 9: of these megacap companies.

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Speaker 4: Sarah, I sat on my sofa for like everyone around

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Speaker 4: the country, hoping that AI would come up in the debate.

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Speaker 4: The question for markets is how much longer does this

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Speaker 4: trend have to run? Listen to what Mike Wilson said

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Speaker 4: on Bloomberg Television earlier today, we just.

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Speaker 10: Got overcooked on the whole AI theme. Doesn't mean it's

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Speaker 10: over We've written about this extensively, like we're not believers

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Speaker 10: that this is going to change productivity materially in the

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Speaker 10: short term.

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Speaker 7: That's a long term story.

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Speaker 4: And that's why I asked you about the election. Does

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Speaker 4: it happen irrespective of the outcome, Do you agree that

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Speaker 4: this AI trade's overcooked right now?

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Speaker 9: Well, definitely became overcrowded from an investment point of view,

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Speaker 9: and with any new structural change in the technology landscape

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Speaker 9: like artificial intelligence, which I think is here to say,

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Speaker 9: there's going to be fits and starts, and what people

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Speaker 9: have been worrying about since the July tenth peak is

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Speaker 9: where is the where are the signs of monetization and

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Speaker 9: what is the return on investment on this tens of

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Speaker 9: billions of AI investments that technology companies have made and

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Speaker 9: that companies are making in order to improve their revenue

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Speaker 9: growth and improve their efficiencies and productivity. That's what we're

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Speaker 9: not seeing yet. So I think we are in a

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Speaker 9: bit of a plateau or a pause for this stocks,

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Speaker 9: for these stocks until we start to see more clear

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Speaker 9: signs of what it really means. In the impact on businesses.

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Speaker 9: Not surprisingly, consumer technology companies are seeing positive impacts from

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Speaker 9: AI meta with its targeting ads on Facebook, on Instagram,

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Speaker 9: and also Amazon, which is targeting what people more efficiently

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Speaker 9: should be buying. But in other areas like manufacturing companies,

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Speaker 9: we're not seeing the yield increases yet. And I think

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Speaker 9: that's the other nontech areas of the economies where we

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Speaker 9: want to see that impact of artificial intelligence c matic.

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Speaker 2: So good to have you here from van We appreciate

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Speaker 2: it coming up, so it mentions Amazon we get to

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Speaker 2: dig in as it continues to expand its cloud business

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Speaker 2: in the United Kingdom.

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Speaker 3: Well details next.

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Speaker 2: This is pretty big technology.

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Speaker 4: Amazon says it would spend ten point five billion dollars

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Speaker 4: in the UK to grow its cloud business, adding to

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Speaker 4: a string of recent expansion moves in Europe and giving

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Speaker 4: Britain's new labor government a welcome investment boost. Bloomberg's Matt Day,

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Speaker 4: who covers Amazon, joins US now from Seattle, and Matt,

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Speaker 4: you and I have covered many of these deals, right.

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Speaker 4: I think about Virginia where AWS in particular pledges. I

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Speaker 4: think it's thirty five billion through twenty forty, but it's

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Speaker 4: still a significant bet on Amazon's footprint in the United Kingdom.

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Speaker 10: Yeah, it is, and it's about in line with what

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Speaker 10: they should be spending there. You look at the UK

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Speaker 10: chunk of sales for Amazon. This probably makes sense within

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Speaker 10: the context of Amazon's capex because they are spending just

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Speaker 10: a ton on data centers, as you mentioned.

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Speaker 4: You know, this year alone, we've had.

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Speaker 10: Announcements in Saudi Arabia, Mexico, in Europe and Germany and

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Speaker 10: in Spain and now United Kingdom, just a kind of

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Speaker 10: a full force of a wusay whe they're going to

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Speaker 10: stay relevant the cloud market by expanding more than anybody else.

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Speaker 2: Yeah, give us context to the race here, the need

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Speaker 2: for compute to satisfy demand.

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Speaker 10: So it's at least two separate things. One is sort

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Speaker 10: of the ongoing move to the cloud. Company has on

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Speaker 10: plugging their data centers favor of rented computing power. You know,

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Speaker 10: that's Amazon, that's Microsoft, that's Google. You've also had this

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Speaker 10: AI cocktail thrown in there, where folks have just had

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Speaker 10: to ramp up their budgets to afford these pricey chips,

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Speaker 10: to afford the.

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Speaker 4: Cooling that makes them happen.

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Speaker 10: And then just on top of that, you know, power

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Speaker 10: is scarce just about everywhere you look. So it's a

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Speaker 10: real kind of land grab on of big cloud companies

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Speaker 10: to build new campuses, to expand kind of as quick

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Speaker 10: as they can to meet this new emerging command.

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Speaker 4: Matt, Caroline and I will spare you from the UK

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Speaker 4: political component of this story, although the Chancellor of the

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Speaker 4: Checker Racial reas rating no time to kind of point

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Speaker 4: out this is a big win for UK PLC. The

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Speaker 4: business is interesting. Every time we talk about Amazon awsis

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Speaker 4: footprint in Europe on this program, I know that quite

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Speaker 4: a lot of Amazon staff will engage on LinkedIn. There's

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Speaker 4: a lot of them there. But how does it compare

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Speaker 4: to their presence in North America and elsewhere.

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Speaker 10: Well, their biggest hubs are in North America, right, that's

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Speaker 10: where the majority of their data center investment over time

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Speaker 10: has then, you know, but they are going more international

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Speaker 10: and they are going into sort of smaller and smaller markets.

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Speaker 10: If you roll back the clock many years, you know,

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Speaker 10: it used to be they invested in kind of big

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Speaker 10: centralized data center locations. I believe that was outside of

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Speaker 10: Paris in the EU, and then slowly over time they've

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Speaker 10: kind of gone down and said, you know, listen, not

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Speaker 10: only do we need points of presence in in local markets,

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Speaker 10: but we need to spend you know, billions of dollars

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Speaker 10: in local markets to take advantage of the opportunities there

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Speaker 10: to be close to just the big corporates who are

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Speaker 10: demanding cloud computing.

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Speaker 2: What about taking advantage of benefits at certain government's offer.

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Speaker 3: Is that part of the game, you know?

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Speaker 11: It is?

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Speaker 10: You know, I think Amazon, you know, certainly wants any

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Speaker 10: incentives that are on offer or wherever they go. But

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Speaker 10: I'm not sure it's it's necessarily the driving force. If

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Speaker 10: you listen to Amazon's critics, you know, they will say, listen,

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Speaker 10: if you map their data centers, it just maps out.

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Speaker 4: To where their customers are.

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Speaker 10: Right So certainly policy would play a role. I'm just

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Speaker 10: not sure the market thinks it's a very big one.

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Speaker 2: Matt Day, great to have the expertise, thank you. In

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Speaker 2: today's AI and Action, we are taking a look at Corti.

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Speaker 2: It's a global AI engine designed for healthcare with AI

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Speaker 2: that not only takes practitioner notes, but it helps with

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Speaker 2: quality assurance of journals with prompts and helps document every

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Speaker 2: patient interaction. And the company just announced the higher form

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Speaker 2: of Microsoft and Phillips executives to help me the company's

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Speaker 2: expansion here in the United States. Courty CEO Andreas Cleve

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Speaker 2: joins US. Now, why is the US such a focus.

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Speaker 12: It's the most important healthcare market in the world. It's

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Speaker 12: where I myself live and I'm a patient, and it's

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Speaker 12: a place we feel very excited to work in as

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Speaker 12: some of the best providers and pairs are there and

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Speaker 12: I think they'll be the cornerstone of building the most

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Speaker 12: important solutions for healthcare.

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Speaker 2: What do you offer those practitioners, those experts, Because we're

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Speaker 2: all trying to find out what the return on AI

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Speaker 2: investment is, what do you offer healthcare practicingers.

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Speaker 12: Actual time back? And that's a promise that's been promised

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Speaker 12: a lot of times having been here for a while,

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Speaker 12: so we were founded as a research company back in

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Speaker 12: twenty sixteen to prove we could research and find ways

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Speaker 12: of delivering safe and trustworthy AI.

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Speaker 7: And that's exactly what we give today to providers.

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Speaker 12: We have a solution you can build into whatever tool

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Speaker 12: or application you use, and here are are Real time

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Speaker 12: AI actually helps deliver on some of these promises by

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Speaker 12: doing medical coding. We do summaris we do documentation and

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Speaker 12: in the end help them carve back some of that

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Speaker 12: time loss to administration.

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Speaker 4: Andreas a startup founded in twenty sixteen, is a little

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Speaker 4: bit refreshing. Actually, there have been many new companies formed

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Speaker 4: in the last two years in this area. So in

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Speaker 4: that time you built up data one hundred million customer interactions.

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Speaker 4: What's the benefit that the health system gets from those interactions? Now?

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Speaker 12: Yeah, Yeah, I am excited as an entrepreneur to see

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Speaker 12: so much AI being adopted, but I am still astounded

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Speaker 12: by the amount of AI that's being deployed in healthcare

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Speaker 12: today that isn't built for healthcare. We see a lot

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Speaker 12: of model today who are as good as doing haiku

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Speaker 12: or finding a great kitchen recipe as they are at

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Speaker 12: doing healthcare AI. And what we're offering is obviously an

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Speaker 12: AI that solely built for healthcare. We have been here

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Speaker 12: for a while researching on this, publishing on this, and

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Speaker 12: partnering with some of the best providers to build an

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Speaker 12: AI that is only tuned to one thing, and that

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Speaker 12: is listen to healthcare providers and pairs and actually deliver

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Speaker 12: automations and augmentations that really work.

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Speaker 4: The difficulty in this country is insurance and established healthcare systems.

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Speaker 4: Have you been able to navigate that?

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Speaker 12: I think the way we think about it a lot

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Speaker 12: is to ensure that we don't just come with yet

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Speaker 12: another application. So what we want to come with is

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Speaker 12: a technology that you build into whatever you use already

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Speaker 12: today and that can be used both by payers and providers.

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Speaker 12: So today we're lucky that more than one hundred thousand

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Speaker 12: patient interactions are flowing through Cordy across all fifty state

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Speaker 12: in the US. And ultimately I just heard this from

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Speaker 12: a doctor the other day. It actually helps them ensure

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Speaker 12: that they are more on point also and handing over

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Speaker 12: patients data or documentation between let's say a peer and provider.

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Speaker 2: Let's exactly talk about patient data. There's a lot of

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Speaker 2: anxiety about it running through various people's hands.

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Speaker 3: Andreas, how are you ensuring the security?

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Speaker 12: So we are originally a company from Denmark and the

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Speaker 12: Cold North in Scandinavia in Europe, so in our DNA

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Speaker 12: is compliance, we are from the most regulated part of

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Speaker 12: the global healthcare system and also known to be one

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Speaker 12: of the best healthing systems, and we have been lucky

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Speaker 12: enough to be partnering with the European Union and their

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Speaker 12: legislative arm when they wrote the AI Act, and we've

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Speaker 12: been lucky enough to work with them on GDPR, so

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Speaker 12: into the engine of cority and all the technology we've built,

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Speaker 12: compliance and data safety is among them. And that means

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Speaker 12: that we are not taking data, we are not appropriating data,

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Speaker 12: we're not misusing data. As we come from a market

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Speaker 12: that's driven by patients, and those patients they give each

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Speaker 12: other health care for free, and we really have an

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Speaker 12: ethos of ensuring that patients come first, and that's I

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Speaker 12: think very core to what we believe in andress.

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Speaker 4: The most recent piece of news for you is all

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Speaker 4: of the sort of top talent you've been hiring from

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Speaker 4: both tech and healthcare. How difficult and how expensive was that.

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Speaker 12: It's definitely been a big challenge. I think there's a

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Speaker 12: lot of hype around AI startups, but I think we've

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Speaker 12: been lucky to see some of the best talents in

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Speaker 12: healthcare meeting customers providers, payers all the time who really

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Speaker 12: want to get on this AAR journey, but they've maybe

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Speaker 12: not yet found the provider that actually was trustworthy. So

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Speaker 12: we've been lucky enough to show them that and Luckily,

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Speaker 12: we keep hearing that from patients and providers who start

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Speaker 12: using it that they actually see the outcomes they want.

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Speaker 12: And I think that entices a lot of the sort

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Speaker 12: of the titans of our industry to come and see.

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Speaker 7: If it's real, and luckily.

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Speaker 12: When they see it, they actually want to join.

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Speaker 4: Cool to CEO, Andreas Cleve. Great to have you on

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Speaker 4: the program. Thank you.

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Speaker 2: Welcome back to Blue Meg Technology. I'm Karen Hider, New

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Speaker 2: York and.

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Speaker 4: I med lod Low in San Francisco.

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Speaker 2: Check on these markets that have been under pressure post

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Speaker 2: the CPI print, of course, ed Look, we've got a

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Speaker 2: bit of risk aversion creeping into the markets. Were off

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Speaker 2: of our lows, but still the nast that one hundred

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Speaker 2: is dragged on by about nine.

440
00:21:23,040 --> 00:21:23,960
Speaker 3: Tenths of a percent.

441
00:21:24,240 --> 00:21:26,360
Speaker 2: We seem to see a slight move to the havens,

442
00:21:26,359 --> 00:21:28,840
Speaker 2: that is, the bond market Felds currently flat. We had

443
00:21:28,840 --> 00:21:31,360
Speaker 2: seen more of a bid a little bit earlier in trading. Look,

444
00:21:31,359 --> 00:21:34,080
Speaker 2: but the overall question is can the FED be cutting

445
00:21:34,119 --> 00:21:36,960
Speaker 2: to the whacking proportion of a fifty basis point as

446
00:21:36,960 --> 00:21:39,359
Speaker 2: soon as September most now daling that back to a

447
00:21:39,400 --> 00:21:43,520
Speaker 2: twenty five basis point expectation. Therefore, maybe just when coming

448
00:21:43,600 --> 00:21:46,360
Speaker 2: out of some of these more risk on trades, i'd

449
00:21:46,400 --> 00:21:48,639
Speaker 2: talk of that within the spectrum of Bitcoin off by

450
00:21:48,640 --> 00:21:50,359
Speaker 2: more than two percent. But of course, maybe that's the

451
00:21:50,400 --> 00:21:53,879
Speaker 2: political reflection of the debate of yesterday, when you know,

452
00:21:54,280 --> 00:21:57,640
Speaker 2: former President Trump is deemed a more crypto pro candidate

453
00:21:57,920 --> 00:22:00,399
Speaker 2: and perhaps maybe the market feeling his before moments was

454
00:22:00,440 --> 00:22:03,639
Speaker 2: lackluster versus that of VP Harris. Let's move on and

455
00:22:03,640 --> 00:22:05,440
Speaker 2: have a look at what the individual movers are looking

456
00:22:05,520 --> 00:22:08,040
Speaker 2: like in terms of technology. Look the bid up in

457
00:22:08,080 --> 00:22:10,719
Speaker 2: certain solar names more than nine percent high for First Solar,

458
00:22:10,960 --> 00:22:14,040
Speaker 2: that again being deemed perhaps a fallout of what was

459
00:22:14,200 --> 00:22:17,600
Speaker 2: a strong performance by VP Harris yesterday. And also looking

460
00:22:17,680 --> 00:22:20,399
Speaker 2: what's happening with Armholding once again rising some three percent.

461
00:22:20,440 --> 00:22:22,320
Speaker 2: This is more back to its V nine chip design.

462
00:22:22,480 --> 00:22:25,400
Speaker 2: Maybe that's been integated into the new Apple chip. And look,

463
00:22:25,520 --> 00:22:28,920
Speaker 2: really Morgan Stanley once again singling this name out as

464
00:22:28,960 --> 00:22:32,520
Speaker 2: one of its best forward focuses for sort of edge

465
00:22:32,640 --> 00:22:35,879
Speaker 2: AI as they're calling in and Tesla look biggest points

466
00:22:35,920 --> 00:22:37,800
Speaker 2: drag on the NASDAC wanted to call it out more

467
00:22:37,800 --> 00:22:39,040
Speaker 2: than two and a half percent lower ed.

468
00:22:39,200 --> 00:22:40,000
Speaker 3: What are you looking.

469
00:22:39,840 --> 00:22:44,879
Speaker 4: At Waimo, the autonomous driving arm of Google parent Alphabet,

470
00:22:44,920 --> 00:22:48,119
Speaker 4: has been making some progress of late. Autonomous ride hailing

471
00:22:48,359 --> 00:22:51,520
Speaker 4: has hit more than one hundred thousand weekly paid rides

472
00:22:51,720 --> 00:22:55,119
Speaker 4: across Waymo's first markets, and the companies also published new

473
00:22:55,240 --> 00:22:58,720
Speaker 4: data showing it's done twenty two million rider only miles

474
00:22:58,760 --> 00:23:01,560
Speaker 4: to date with no one in the driver's seat. Joining

475
00:23:01,600 --> 00:23:05,400
Speaker 4: us to discuss Waymo co CEO Tequidra Maurakana, who last

476
00:23:05,400 --> 00:23:08,880
Speaker 4: week was also named in Times one hundred Most Influential

477
00:23:08,920 --> 00:23:12,880
Speaker 4: in AI list for twenty twenty four. Good morning to you, Tequidra.

478
00:23:13,119 --> 00:23:15,480
Speaker 4: When we said you were coming on the show, lots

479
00:23:15,480 --> 00:23:17,879
Speaker 4: of people have very sort of granular questions about the

480
00:23:17,920 --> 00:23:20,919
Speaker 4: paid rides, so let's start there. You know, what is

481
00:23:20,960 --> 00:23:25,000
Speaker 4: the average distance taken, the average fare per ride, and

482
00:23:25,040 --> 00:23:27,400
Speaker 4: a bit more about the economics of what you've achieved.

483
00:23:28,440 --> 00:23:31,480
Speaker 13: Yeah, thank you so much Ed for having me, and

484
00:23:31,520 --> 00:23:34,040
Speaker 13: I would love to hear more about your experience because

485
00:23:34,080 --> 00:23:36,600
Speaker 13: I've been watching your social engagement.

486
00:23:36,480 --> 00:23:40,040
Speaker 14: Like so many of our riders. So you said it.

487
00:23:40,280 --> 00:23:43,440
Speaker 13: You know, we've reached over one hundred thousand rides per

488
00:23:43,480 --> 00:23:45,120
Speaker 13: week across.

489
00:23:44,840 --> 00:23:48,080
Speaker 14: San Francisco, Phoenix and Los Angeles.

490
00:23:48,760 --> 00:23:52,600
Speaker 13: Those the distances that people travel and how they're using

491
00:23:52,640 --> 00:23:57,439
Speaker 13: a service very wildly between those locations. In San Francisco,

492
00:23:57,520 --> 00:24:00,640
Speaker 13: we're finding that like thirty six percent of people are

493
00:24:00,680 --> 00:24:04,600
Speaker 13: actually using the service to connect with transit, you know,

494
00:24:04,600 --> 00:24:06,959
Speaker 13: which is really surprising for us. So that's like depending

495
00:24:06,960 --> 00:24:08,359
Speaker 13: on where they are in the city, it could be

496
00:24:08,440 --> 00:24:11,040
Speaker 13: like about a three mile ride to get to a

497
00:24:11,080 --> 00:24:14,600
Speaker 13: transit or to get to work. Other people are using

498
00:24:14,600 --> 00:24:16,879
Speaker 13: it to run errands and to doctor's appointments, So it

499
00:24:16,920 --> 00:24:19,840
Speaker 13: really depends. And when you talk about the economics, you know,

500
00:24:19,920 --> 00:24:24,680
Speaker 13: we're a premium service, and so people are paying for

501
00:24:24,920 --> 00:24:28,399
Speaker 13: the consistency and the safety of the Waimo driver in

502
00:24:28,440 --> 00:24:29,680
Speaker 13: the Waimo one service.

503
00:24:30,760 --> 00:24:33,439
Speaker 4: Under the sort of co ceo model, you're really focused

504
00:24:33,440 --> 00:24:35,960
Speaker 4: on the commercialization of what Weimo has been doing for

505
00:24:36,000 --> 00:24:37,600
Speaker 4: quite a long time. And just going back to what

506
00:24:37,640 --> 00:24:39,879
Speaker 4: you just said, Yeah, I use way Moo often. I

507
00:24:39,920 --> 00:24:43,919
Speaker 4: also use Tessa's FSD supervised and was using crews and

508
00:24:44,200 --> 00:24:47,240
Speaker 4: you know, the experience is interesting, but I'm trying to

509
00:24:47,240 --> 00:24:48,880
Speaker 4: think about how I would use it in the course

510
00:24:48,920 --> 00:24:51,600
Speaker 4: of my normal life, and for me, SFO is a

511
00:24:51,600 --> 00:24:53,200
Speaker 4: big thing. So when am I going to be able

512
00:24:53,240 --> 00:24:55,560
Speaker 4: to go down to SFO in a way moo from

513
00:24:55,560 --> 00:24:58,760
Speaker 4: here on Peer three Embarcadero, and what's the progress you're

514
00:24:58,800 --> 00:24:59,240
Speaker 4: making there.

515
00:25:00,440 --> 00:25:03,760
Speaker 13: Yeah, So, you know, when we launched in Phoenix, one

516
00:25:03,800 --> 00:25:06,840
Speaker 13: of the early early engagements was with the Phoenix Sky

517
00:25:06,880 --> 00:25:10,159
Speaker 13: Harbor Airport and so now we offer twenty four to

518
00:25:10,200 --> 00:25:12,320
Speaker 13: seven pickup at the curb side there.

519
00:25:12,640 --> 00:25:13,879
Speaker 14: You know, it's a process.

520
00:25:14,000 --> 00:25:17,680
Speaker 13: We were the first autonomous vehicle company to receive FA

521
00:25:17,720 --> 00:25:19,840
Speaker 13: approval to be able to do that kind of pickup,

522
00:25:20,200 --> 00:25:23,520
Speaker 13: and so we're deeply engaged with SFO officials so that

523
00:25:23,600 --> 00:25:25,479
Speaker 13: we can do exactly that kind of pickup.

524
00:25:25,520 --> 00:25:28,040
Speaker 14: The other thing that we're also deeply engaged in with.

525
00:25:28,160 --> 00:25:32,240
Speaker 13: Our employees right now is fully autonomous rides on freeways

526
00:25:32,640 --> 00:25:34,719
Speaker 13: because you know, people want to take trips to and

527
00:25:34,720 --> 00:25:37,240
Speaker 13: from the airport and they want to do it on freeways,

528
00:25:37,280 --> 00:25:39,679
Speaker 13: and so we have that going in Phoenix. We have

529
00:25:39,760 --> 00:25:42,240
Speaker 13: it also in San Francisco with our employees right now.

530
00:25:42,240 --> 00:25:45,080
Speaker 13: And both of those are really critical unlocks for us,

531
00:25:45,400 --> 00:25:47,879
Speaker 13: and we're really focused on it right now. And you know,

532
00:25:48,040 --> 00:25:51,200
Speaker 13: doing everything with safety at the center of how we move.

533
00:25:51,400 --> 00:25:55,119
Speaker 13: It's iterative, it's deliberate and it's it takes what it

534
00:25:55,160 --> 00:25:56,120
Speaker 13: takes to get it right.

535
00:25:56,680 --> 00:25:59,280
Speaker 2: Let's dwell on that safety to Quiedra and thank you

536
00:25:59,320 --> 00:26:03,040
Speaker 2: for joining us day because SMP actually cut us to

537
00:26:03,119 --> 00:26:05,399
Speaker 2: you calling out WEIMO as the front runner in the

538
00:26:05,400 --> 00:26:08,280
Speaker 2: field of avs in the United States. But they do

539
00:26:08,400 --> 00:26:12,080
Speaker 2: say challenges remain, including an ongoing investigation from the National

540
00:26:12,160 --> 00:26:13,679
Speaker 2: Highway Traffic Safety Administration.

541
00:26:14,000 --> 00:26:15,359
Speaker 3: How are you discussing that?

542
00:26:15,520 --> 00:26:18,480
Speaker 2: How are you looking at your safety data?

543
00:26:18,600 --> 00:26:20,240
Speaker 14: So we're really really proud.

544
00:26:20,359 --> 00:26:22,199
Speaker 13: I mean we you know, found in two thousand and

545
00:26:22,280 --> 00:26:25,800
Speaker 13: nine as a Google self driving car project. Our company

546
00:26:25,880 --> 00:26:29,000
Speaker 13: culture is built around safety, and it's built around the

547
00:26:29,040 --> 00:26:32,080
Speaker 13: transparency of our safety. You know, there's not one measure

548
00:26:32,440 --> 00:26:35,199
Speaker 13: of safety, so we've built a lot of measures and

549
00:26:35,280 --> 00:26:38,000
Speaker 13: a lot of transparency. In last week, we launched the

550
00:26:38,000 --> 00:26:41,080
Speaker 13: Safety Hub, and we're the only company that's sort of

551
00:26:41,080 --> 00:26:44,920
Speaker 13: putting all of our data out there for academics, the media,

552
00:26:45,119 --> 00:26:48,960
Speaker 13: everyone to engage with it and understand why it is

553
00:26:49,000 --> 00:26:52,000
Speaker 13: that we know that we are through the data improving

554
00:26:52,080 --> 00:26:54,560
Speaker 13: road safety. You just had some of the stats up right,

555
00:26:54,680 --> 00:26:59,120
Speaker 13: like reducing the number of air bag deployments injury causing crashes.

556
00:26:59,160 --> 00:27:01,960
Speaker 13: I mean, this is why we exist right. Level four

557
00:27:02,000 --> 00:27:07,840
Speaker 13: technology should make the road safer for humans, for pedestrians,

558
00:27:07,840 --> 00:27:12,440
Speaker 13: for cyclists, vulnerable road users, and we're showing that that's

559
00:27:12,480 --> 00:27:16,320
Speaker 13: the case. But we're still with the NITSA investigation, engaging

560
00:27:16,640 --> 00:27:20,160
Speaker 13: demonstrating that you know, engaging at every level of government

561
00:27:20,359 --> 00:27:22,159
Speaker 13: is what you have to do when you're the first

562
00:27:22,240 --> 00:27:25,000
Speaker 13: to do this. No one's reached this level of scale,

563
00:27:25,320 --> 00:27:27,880
Speaker 13: and so we understand NITSA has a role to play,

564
00:27:27,920 --> 00:27:29,480
Speaker 13: and we also have a role to play in being

565
00:27:29,600 --> 00:27:30,520
Speaker 13: very transparent.

566
00:27:31,080 --> 00:27:34,120
Speaker 2: And for that you need money and luckily you've got

567
00:27:34,440 --> 00:27:37,000
Speaker 2: a large amount of it five billion coming from Alphabet.

568
00:27:37,440 --> 00:27:40,760
Speaker 2: Just tell us about the investment needs, the focus of

569
00:27:40,760 --> 00:27:42,520
Speaker 2: that S and P again calling out in the need

570
00:27:42,600 --> 00:27:46,080
Speaker 2: for this sort of capital investment to drive the US forward.

571
00:27:47,320 --> 00:27:51,840
Speaker 13: Yeah, so super fortunate to be backed by Alphabet as

572
00:27:51,880 --> 00:27:55,200
Speaker 13: well as our other external investors. You know, we're laser

573
00:27:55,280 --> 00:27:59,280
Speaker 13: focused on scaling this technology and so that investment, while

574
00:27:59,280 --> 00:28:02,479
Speaker 13: it's a big number, doesn't represent a significant growth in

575
00:28:02,520 --> 00:28:07,320
Speaker 13: our overall trajectory because we've been very diligent.

576
00:28:07,000 --> 00:28:09,160
Speaker 14: About bringing down our cost structure over time.

577
00:28:09,320 --> 00:28:11,399
Speaker 13: And so you saw us in the last couple of

578
00:28:11,400 --> 00:28:14,800
Speaker 13: weeks introduce our sixth generation driver. When you see us

579
00:28:14,800 --> 00:28:18,120
Speaker 13: introducing a new technology or a new approach to our

580
00:28:18,680 --> 00:28:21,159
Speaker 13: go to market strategy, one of the things that you

581
00:28:21,160 --> 00:28:24,640
Speaker 13: can think about is that's going to make scaling our

582
00:28:24,840 --> 00:28:28,560
Speaker 13: business more efficient over time. And so that's what we're

583
00:28:28,600 --> 00:28:31,320
Speaker 13: really focused on doing, and having the backing of Alphabet

584
00:28:31,400 --> 00:28:34,120
Speaker 13: is a great, great place to be Ti.

585
00:28:34,080 --> 00:28:36,680
Speaker 4: Keijra, what's your relationship like with Ruth Korat. I had

586
00:28:36,680 --> 00:28:39,440
Speaker 4: my sort of final quarterly earning school with her at

587
00:28:39,480 --> 00:28:42,080
Speaker 4: the last call, and she's focused on other things. Now,

588
00:28:42,120 --> 00:28:45,240
Speaker 4: how will you work together as she kind of transitions

589
00:28:45,280 --> 00:28:47,920
Speaker 4: to a different function at Alphabet.

590
00:28:49,040 --> 00:28:52,400
Speaker 13: Yeah, so Ruth is going to remain involved, right She's

591
00:28:52,440 --> 00:28:55,240
Speaker 13: taking on this role as president, and she's investment officer

592
00:28:55,400 --> 00:28:58,560
Speaker 13: and we are obviously a really important investment for Alphabet,

593
00:28:58,680 --> 00:29:01,280
Speaker 13: and so she's been involved since I joined the company.

594
00:29:01,680 --> 00:29:04,120
Speaker 14: She's a very very ardent supporter of.

595
00:29:04,080 --> 00:29:06,320
Speaker 13: Weimo and I look forward to continuing to work with

596
00:29:06,360 --> 00:29:07,719
Speaker 13: her in this new capacity.

597
00:29:09,000 --> 00:29:11,479
Speaker 4: Takeidra, as you know, I kind of have a hands

598
00:29:11,520 --> 00:29:15,560
Speaker 4: on experience of your competitive landscape. What do you make

599
00:29:15,600 --> 00:29:20,120
Speaker 4: of sort of testless strategy with robotaxi in a proprietary

600
00:29:20,200 --> 00:29:23,760
Speaker 4: ride hailing app and also why sort of is your

601
00:29:24,000 --> 00:29:26,640
Speaker 4: approach different and going to succeed to them or to

602
00:29:26,760 --> 00:29:28,000
Speaker 4: a cruise for example.

603
00:29:29,720 --> 00:29:32,880
Speaker 13: You know, this sort of question of competitive landscape I

604
00:29:32,920 --> 00:29:35,680
Speaker 13: think is so interesting because we are in the business

605
00:29:35,720 --> 00:29:38,080
Speaker 13: of trying to make the road safer, and we are

606
00:29:38,080 --> 00:29:40,000
Speaker 13: in the business of doing it in a way that

607
00:29:40,040 --> 00:29:41,280
Speaker 13: takes the human out of the.

608
00:29:41,280 --> 00:29:42,520
Speaker 14: Lip for two reasons.

609
00:29:42,880 --> 00:29:45,400
Speaker 13: One is it expands the number of people who have

610
00:29:45,680 --> 00:29:48,400
Speaker 13: access to mobility options. Right, if you don't need a

611
00:29:48,480 --> 00:29:51,440
Speaker 13: driver's license, if you don't have to sit behind the wheel,

612
00:29:51,920 --> 00:29:55,640
Speaker 13: then Waymo's a perfect opportunity for you. And hopefully any

613
00:29:55,760 --> 00:29:58,880
Speaker 13: level four that actually any level four system that actually

614
00:29:58,880 --> 00:30:02,040
Speaker 13: makes you know a road safer, will be there.

615
00:30:02,440 --> 00:30:04,400
Speaker 14: And so that's the way we think about it.

616
00:30:04,800 --> 00:30:06,640
Speaker 13: And so when I think about some of the other

617
00:30:06,680 --> 00:30:08,760
Speaker 13: approaches that people are taking, I think, if you need

618
00:30:08,760 --> 00:30:11,160
Speaker 13: a driver's license or if the human has to take over,

619
00:30:11,240 --> 00:30:13,280
Speaker 13: it's just very different and it's not you know, we're

620
00:30:13,320 --> 00:30:16,640
Speaker 13: heads down focused on our strategy, which is a level

621
00:30:16,680 --> 00:30:17,600
Speaker 13: for technology.

622
00:30:18,600 --> 00:30:20,720
Speaker 2: Thank you for talking us through the strategy today, my

623
00:30:20,880 --> 00:30:22,920
Speaker 2: mon Coco Takeidra Mama Kana.

624
00:30:23,160 --> 00:30:24,160
Speaker 3: We appreciate your time.

625
00:30:24,880 --> 00:30:26,800
Speaker 2: Now coming up, we'll be joined by a Liz Yang,

626
00:30:27,000 --> 00:30:29,320
Speaker 2: head of Growth and Azuki for her take on the

627
00:30:29,360 --> 00:30:31,520
Speaker 2: presidential debates impact on crypto markets.

628
00:30:31,600 --> 00:30:33,760
Speaker 3: Well, they're same line. This is Bluemeg technology.

629
00:30:42,000 --> 00:30:45,760
Speaker 2: It's gone viral. Taylor Swift has endorsed Kamala Harris. She

630
00:30:45,840 --> 00:30:48,640
Speaker 2: made the announcement just minutes after the debate of yesterday,

631
00:30:48,680 --> 00:30:50,960
Speaker 2: wrapped through a social media post, as you can see,

632
00:30:51,000 --> 00:30:53,600
Speaker 2: featuring her cat as she calls herself a childless cat lady.

633
00:30:54,000 --> 00:30:55,160
Speaker 3: We understand the reference there.

634
00:30:55,400 --> 00:30:57,520
Speaker 2: She says she is voting for Harris because quote, she

635
00:30:57,640 --> 00:31:00,600
Speaker 2: fights for the rights and causes I believe need a

636
00:31:00,680 --> 00:31:02,360
Speaker 2: warrior to champion them.

637
00:31:02,880 --> 00:31:06,120
Speaker 3: Bloomberg Opinion. David Lee is with us now, Dave.

638
00:31:07,120 --> 00:31:10,400
Speaker 2: It feels though that underlying all of this is artificial intelligence,

639
00:31:10,440 --> 00:31:11,040
Speaker 2: and you point.

640
00:31:10,880 --> 00:31:11,600
Speaker 3: That out on your piece.

641
00:31:12,240 --> 00:31:15,520
Speaker 15: Yes, I mean this was the thing that Taylor Swift says,

642
00:31:15,920 --> 00:31:18,480
Speaker 15: I kind of motivate her to speak out and publicly

643
00:31:18,640 --> 00:31:21,080
Speaker 15: endorse the Harris campaign. I mean, she may have done

644
00:31:21,080 --> 00:31:23,040
Speaker 15: it anyway, but she made a specific point of bringing

645
00:31:23,040 --> 00:31:25,280
Speaker 15: this up in her post. She said there had been

646
00:31:25,880 --> 00:31:29,680
Speaker 15: misinformation posted about her by Trump on truth social suggesting

647
00:31:29,760 --> 00:31:33,160
Speaker 15: that she had been that she was endorsing him, and

648
00:31:33,480 --> 00:31:37,000
Speaker 15: some of her fans were supporting him as well. And

649
00:31:37,120 --> 00:31:39,160
Speaker 15: so what I think this kind of represents is, you know,

650
00:31:39,720 --> 00:31:42,600
Speaker 15: the first kind of major impact we've seen from the

651
00:31:42,720 --> 00:31:43,000
Speaker 15: use of.

652
00:31:43,040 --> 00:31:44,640
Speaker 4: AI in an election.

653
00:31:45,120 --> 00:31:48,520
Speaker 15: We've heard researchers warn that deep fakes and other kind

654
00:31:48,520 --> 00:31:52,520
Speaker 15: of misinformation using AI would perhaps influence voters, and this

655
00:31:52,640 --> 00:31:54,680
Speaker 15: is kind of what's happened, although it's come from a

656
00:31:54,800 --> 00:31:59,920
Speaker 15: rebuttal rather than the original content itself, and Taylor swift

657
00:32:00,240 --> 00:32:02,200
Speaker 15: response is going to be seen by many more people

658
00:32:02,280 --> 00:32:04,400
Speaker 15: than the original post part by Trump.

659
00:32:05,520 --> 00:32:07,840
Speaker 4: As you point out in your opinion column, we can

660
00:32:07,920 --> 00:32:12,840
Speaker 4: only speculate if Swift would have endorsed Harris had that

661
00:32:13,760 --> 00:32:17,320
Speaker 4: fake endorsement not happened. But then there's like the Taylor

662
00:32:17,360 --> 00:32:20,360
Speaker 4: Swift effect, right, and you know, you try and make

663
00:32:20,400 --> 00:32:23,480
Speaker 4: sense of a presidential debate. What's your conclusion in the

664
00:32:23,560 --> 00:32:27,080
Speaker 4: column about the impact Taylor Swift coming out and endorsing

665
00:32:27,160 --> 00:32:30,360
Speaker 4: Kamala Harris will have on this election race? Opinion Tech

666
00:32:30,400 --> 00:32:33,680
Speaker 4: columnist davely Go, Well, I.

667
00:32:33,720 --> 00:32:35,720
Speaker 15: Think one of the things we've seen in the past

668
00:32:35,880 --> 00:32:40,000
Speaker 15: when Taylor Swift has brought herself into politics, which we

669
00:32:40,080 --> 00:32:42,160
Speaker 15: know she does very very carefully, and with a great

670
00:32:42,240 --> 00:32:44,280
Speaker 15: deal of thought. Is that what we typically see is

671
00:32:44,400 --> 00:32:48,640
Speaker 15: voter registrations among young people, among young women in particular,

672
00:32:48,960 --> 00:32:52,040
Speaker 15: tends to jump to go up quite considerably, So I

673
00:32:52,120 --> 00:32:54,800
Speaker 15: imagine we'd see that happen again here. There's questions of

674
00:32:54,920 --> 00:32:57,040
Speaker 15: how much of that translates to people actually going.

675
00:32:57,000 --> 00:32:57,640
Speaker 4: To the polls.

676
00:32:58,200 --> 00:33:00,240
Speaker 15: But put it this way, Taylor Swift's endorsement, and it's

677
00:33:00,240 --> 00:33:03,440
Speaker 15: certainly one you prefer to have then not have, right, so,

678
00:33:03,720 --> 00:33:06,160
Speaker 15: particularly when it's done in a way that is drawing

679
00:33:06,200 --> 00:33:08,640
Speaker 15: attention to one of the major criticisms of Trump, which

680
00:33:08,680 --> 00:33:11,600
Speaker 15: is that he makes things up and puts them on

681
00:33:11,680 --> 00:33:12,240
Speaker 15: his website.

682
00:33:12,840 --> 00:33:17,440
Speaker 2: Wienberg Opinions davely appreciate it. Go check out his column. Meanwhile,

683
00:33:17,840 --> 00:33:20,720
Speaker 2: let's get to where other youthful voters have been looking crypto,

684
00:33:20,840 --> 00:33:23,120
Speaker 2: and more importantly, let's look at bitcoin because it is

685
00:33:23,200 --> 00:33:25,560
Speaker 2: actually under some pressure today after the last two training

686
00:33:25,640 --> 00:33:28,200
Speaker 2: days off by a quarter of percent. Call that CPI,

687
00:33:28,360 --> 00:33:30,720
Speaker 2: but maybe also call it a reaction to the US

688
00:33:30,760 --> 00:33:34,680
Speaker 2: presidential debate. Let's discuss with Lizziang's head of growth at

689
00:33:34,840 --> 00:33:38,720
Speaker 2: True Labs, and Liz I'm really interested more broadly in

690
00:33:39,400 --> 00:33:43,640
Speaker 2: how crypto is being used as a gauge for the

691
00:33:43,880 --> 00:33:47,840
Speaker 2: former president Trump's performance or chances of being re elected.

692
00:33:48,680 --> 00:33:51,960
Speaker 16: There are several different ways. So firstly, if you look

693
00:33:52,000 --> 00:33:54,239
Speaker 16: up the price of bitcoin, you can consider that as

694
00:33:54,320 --> 00:33:57,880
Speaker 16: a proxy for how the crypto sectory views Trump's chances

695
00:33:58,240 --> 00:34:01,400
Speaker 16: of being elected and the upcoming president election. This is

696
00:34:01,440 --> 00:34:04,520
Speaker 16: because Trump has come out as a staunchly pro crypto candidate,

697
00:34:04,840 --> 00:34:08,719
Speaker 16: forcing the Democrat's hand on the issue of crypto policy. Now,

698
00:34:08,840 --> 00:34:12,279
Speaker 16: if you look at prediction markets like polymarket, what's really

699
00:34:12,360 --> 00:34:15,960
Speaker 16: really fascinating is that almost in real time, viewers were

700
00:34:16,000 --> 00:34:21,759
Speaker 16: able to track crypto sector's sentiment around the timestamps of

701
00:34:21,840 --> 00:34:24,280
Speaker 16: when each candidate came up with their respective arguments.

702
00:34:26,040 --> 00:34:29,040
Speaker 4: Liz I was doing something similar last night because we'd

703
00:34:29,080 --> 00:34:30,960
Speaker 4: reported on it. We said, okay, if you want to

704
00:34:31,000 --> 00:34:33,840
Speaker 4: follow some sort of real time sentiment, look at specific

705
00:34:33,880 --> 00:34:36,680
Speaker 4: crypto assets at trade twenty four to seven. What I

706
00:34:36,719 --> 00:34:39,960
Speaker 4: couldn't work out was is this just a clear situation

707
00:34:40,080 --> 00:34:43,719
Speaker 4: where Trump is the crypto candidate and Harris is not,

708
00:34:44,200 --> 00:34:47,080
Speaker 4: or there's just not a thorough understanding of policy for

709
00:34:47,200 --> 00:34:48,000
Speaker 4: either candidate.

710
00:34:49,560 --> 00:34:50,640
Speaker 3: It's a really good question.

711
00:34:51,200 --> 00:34:54,120
Speaker 16: So overall, when you take a look at markets like

712
00:34:54,200 --> 00:34:57,640
Speaker 16: prediction markets. Information is of course imperfect, but I think

713
00:34:57,680 --> 00:35:00,200
Speaker 16: that's a reflection of the American populace at lar in

714
00:35:00,320 --> 00:35:02,359
Speaker 16: terms of how they vote. What I think is very

715
00:35:02,480 --> 00:35:06,600
Speaker 16: powerful about tools like polymarket, other prediction markets, as well

716
00:35:06,600 --> 00:35:10,279
Speaker 16: as political meme coins or politifyed coins is that they're

717
00:35:10,360 --> 00:35:13,000
Speaker 16: a way to be able to gauge the barometer in

718
00:35:13,120 --> 00:35:16,000
Speaker 16: terms of sentiment. And I think that if you take

719
00:35:16,040 --> 00:35:19,239
Speaker 16: a look at previous selections, there's been enormous appetite in

720
00:35:19,320 --> 00:35:22,239
Speaker 16: terms of using statistics to track where sentiments at, so

721
00:35:22,400 --> 00:35:25,279
Speaker 16: for example five thirty eight, and I see polymarket and

722
00:35:25,360 --> 00:35:28,280
Speaker 16: politify meme coins as a natural extension of this behavior.

723
00:35:28,960 --> 00:35:31,920
Speaker 2: Let's just talk about how the campaign Trump campaign more

724
00:35:31,920 --> 00:35:36,759
Speaker 2: broadly has embraced crypto non fungible tokens me, but also

725
00:35:37,600 --> 00:35:41,279
Speaker 2: this liberty financial world. Liberty financial it seems to be

726
00:35:41,440 --> 00:35:45,319
Speaker 2: a DeFi potential protocol doesn't seem to be live yet,

727
00:35:45,440 --> 00:35:47,680
Speaker 2: but being talked around, particularly by his sons.

728
00:35:48,160 --> 00:35:49,920
Speaker 3: What do you make of that particular project.

729
00:35:50,560 --> 00:35:52,879
Speaker 16: I think Trump is trying to put his money where

730
00:35:52,920 --> 00:35:55,040
Speaker 16: his mouth is, and he's trying to enter into these

731
00:35:55,120 --> 00:35:59,080
Speaker 16: various different forays to show his you know, dedication and

732
00:35:59,320 --> 00:36:00,640
Speaker 16: interest in the cryptospace.

733
00:36:03,080 --> 00:36:05,560
Speaker 4: Where do we go from here? I mean, there comes

734
00:36:05,600 --> 00:36:09,359
Speaker 4: a point where the markets can continue doing what they're doing,

735
00:36:10,120 --> 00:36:13,080
Speaker 4: be their prediction or specific asset you track, or people

736
00:36:13,200 --> 00:36:17,319
Speaker 4: look elsewhere. What's your kind of hunch in that respect, So.

737
00:36:17,640 --> 00:36:21,160
Speaker 16: When it comes to tools like prediction markets and meme coins,

738
00:36:21,520 --> 00:36:25,080
Speaker 16: I see this as a natural extension of behavior that

739
00:36:25,200 --> 00:36:29,239
Speaker 16: actually started during the pandemic with Wall Street bets. And

740
00:36:29,480 --> 00:36:31,840
Speaker 16: what happened during then is that because of the pandemic,

741
00:36:32,280 --> 00:36:36,320
Speaker 16: people were starved for social contact with their friends and family,

742
00:36:36,400 --> 00:36:38,480
Speaker 16: and they were able to form these bonds with other

743
00:36:38,719 --> 00:36:42,200
Speaker 16: traders on such forums. So what it means is that

744
00:36:42,320 --> 00:36:44,960
Speaker 16: for a lot of younger people, investing is not necessarily

745
00:36:45,120 --> 00:36:49,040
Speaker 16: just about ROI. It's also about Internet culture and memes

746
00:36:49,480 --> 00:36:53,279
Speaker 16: and also entertainment as well as community. And where I

747
00:36:53,360 --> 00:36:56,520
Speaker 16: see political meme coins coming out of this, or polified

748
00:36:56,560 --> 00:37:01,480
Speaker 16: tokens is that it really is a natural successor of

749
00:37:01,600 --> 00:37:04,840
Speaker 16: this kind of trend. So with politify meme coins that

750
00:37:05,320 --> 00:37:10,839
Speaker 16: it combines financial nihilism with political satire, with Internet grown

751
00:37:10,880 --> 00:37:14,600
Speaker 16: culture as well as entertainment, So really transforming how the

752
00:37:14,719 --> 00:37:18,640
Speaker 16: younger generations not only looking at investing, but participating in

753
00:37:18,719 --> 00:37:19,680
Speaker 16: the political process.

754
00:37:21,200 --> 00:37:23,960
Speaker 4: Liz Yang, head of growth at a Zuki and Kira Labs.

755
00:37:31,320 --> 00:37:34,920
Speaker 2: Let's talk about Sony's PlayStation five. It's got a refresh

756
00:37:34,960 --> 00:37:37,120
Speaker 2: and the company is debuting a UPS five.

757
00:37:37,040 --> 00:37:40,479
Speaker 3: Pro, but it comes with a premium price tag. Megs.

758
00:37:40,560 --> 00:37:43,879
Speaker 2: Jason Shadd joins us some more hoof it's called people by.

759
00:37:43,800 --> 00:37:49,600
Speaker 11: Surprise, seven hundred dollars for the PlayStation five Pro. There

760
00:37:49,719 --> 00:37:51,759
Speaker 11: was a meme way back in the day when the

761
00:37:51,760 --> 00:37:55,520
Speaker 11: PlayStation three was announced because they came up on stage

762
00:37:55,560 --> 00:37:59,040
Speaker 11: and said that'll be five hundred and ninety nine US dollars.

763
00:37:59,160 --> 00:38:00,760
Speaker 11: That was a whole meme in Now it's one hundred

764
00:38:00,800 --> 00:38:03,200
Speaker 11: dollars more. So I guess the memes have to keep

765
00:38:03,280 --> 00:38:04,200
Speaker 11: up with inflation too.

766
00:38:05,600 --> 00:38:07,440
Speaker 4: I was taken aback Jason because as you know, like

767
00:38:07,680 --> 00:38:12,040
Speaker 4: I'm a loyal, avid PlayStation user. It's my console of choice.

768
00:38:12,600 --> 00:38:14,840
Speaker 4: But when you think about the console market as a whole,

769
00:38:15,200 --> 00:38:19,000
Speaker 4: this is like PlayStation raising prices when the market is

770
00:38:19,040 --> 00:38:21,080
Speaker 4: kind of going to other direction, right like kids today.

771
00:38:21,680 --> 00:38:25,360
Speaker 4: Apologies for the expression, but they're doing something different with gaming.

772
00:38:26,760 --> 00:38:27,520
Speaker 7: Yeah, it's funny.

773
00:38:27,880 --> 00:38:30,920
Speaker 11: I think that if I can offer a few words

774
00:38:31,160 --> 00:38:33,960
Speaker 11: in PlayStation's defense, here are at least trying to understand

775
00:38:34,000 --> 00:38:35,080
Speaker 11: where they're coming from.

776
00:38:35,440 --> 00:38:37,960
Speaker 7: So the PS five Pro, this is not a new console.

777
00:38:38,160 --> 00:38:41,080
Speaker 11: This is a model of the PlayStation Vibe that will

778
00:38:41,320 --> 00:38:46,280
Speaker 11: essentially play the same games at more vivid graphics, higher

779
00:38:46,400 --> 00:38:50,520
Speaker 11: refresh rates, and better resolutions. Essentially, this thing is meant

780
00:38:50,719 --> 00:38:54,239
Speaker 11: for tech officionadas, the same types of people who maybe

781
00:38:54,280 --> 00:38:58,960
Speaker 11: bought an Apple Vision Pro or are getting a new

782
00:38:59,120 --> 00:39:02,720
Speaker 11: phone every year. So this is not meant for kids

783
00:39:02,920 --> 00:39:04,880
Speaker 11: or the mass market. This is a model that is

784
00:39:05,000 --> 00:39:08,919
Speaker 11: meant for people who have money to spend, who don't

785
00:39:08,960 --> 00:39:12,000
Speaker 11: really care about price quite as much and just want

786
00:39:12,360 --> 00:39:14,160
Speaker 11: the highest end gear.

787
00:39:14,239 --> 00:39:15,799
Speaker 7: In fact, I saw a good stat here.

788
00:39:16,160 --> 00:39:19,759
Speaker 11: This is from Matt Piscatella, and analyst for Circana, and

789
00:39:19,880 --> 00:39:22,759
Speaker 11: he said that the PS four Pro or sorry, the

790
00:39:22,840 --> 00:39:26,680
Speaker 11: PS four Pro, which was a refresh of the PlayStation four,

791
00:39:26,760 --> 00:39:30,680
Speaker 11: the last generation console, accounted for thirteen percent of total

792
00:39:30,760 --> 00:39:34,440
Speaker 11: lifetime PS four units, so not a significant amount, and

793
00:39:34,520 --> 00:39:37,399
Speaker 11: I expect this will be a similar This will play

794
00:39:37,440 --> 00:39:38,680
Speaker 11: a similar role in the market.

795
00:39:39,160 --> 00:39:42,080
Speaker 3: Told to me about a lack of disk drive Jason.

796
00:39:43,040 --> 00:39:45,959
Speaker 11: Yeah, man, I had a conversation not too long ago

797
00:39:46,760 --> 00:39:50,239
Speaker 11: at a party in La where I was talking to

798
00:39:50,320 --> 00:39:52,520
Speaker 11: an executive for one of these big console companies and

799
00:39:52,600 --> 00:39:56,040
Speaker 11: I was like, huh, it's funny the the market is

800
00:39:56,160 --> 00:39:58,080
Speaker 11: moving to digital pretty quickly.

801
00:39:58,200 --> 00:40:00,399
Speaker 7: And he was like, now, Jason, it's a red There.

802
00:40:01,360 --> 00:40:03,120
Speaker 7: A large and very large.

803
00:40:03,080 --> 00:40:06,799
Speaker 11: Percent of customers are buying their games digitally these days.

804
00:40:06,840 --> 00:40:09,799
Speaker 11: Are not even buying bothering with discs. You guys are

805
00:40:09,840 --> 00:40:13,200
Speaker 11: about stalking about game stop. That is why they've been

806
00:40:13,239 --> 00:40:15,759
Speaker 11: on the dancing for a long time. And so I

807
00:40:15,840 --> 00:40:19,880
Speaker 11: think Sony sees the disk drive as an accessory, and

808
00:40:20,040 --> 00:40:22,200
Speaker 11: it is you can buy one as an add on.

809
00:40:22,840 --> 00:40:26,000
Speaker 7: They see it as not necessary for the large majority

810
00:40:26,040 --> 00:40:26,319
Speaker 7: of people.

811
00:40:26,360 --> 00:40:26,880
Speaker 4: And in fact, I.

812
00:40:26,880 --> 00:40:29,759
Speaker 11: Would say that the next generation of consoles, it's very

813
00:40:29,920 --> 00:40:31,840
Speaker 11: likely that they will not come with dis drives, and

814
00:40:31,920 --> 00:40:34,000
Speaker 11: that disk drives will be will be add ons for

815
00:40:34,120 --> 00:40:34,680
Speaker 11: those as well.

816
00:40:35,440 --> 00:40:38,000
Speaker 4: I have so much nostalgia for a disk Jason super

817
00:40:38,080 --> 00:40:41,680
Speaker 4: quick the details of pre ordering and when PS five

818
00:40:41,719 --> 00:40:42,640
Speaker 4: Pro actually comes.

819
00:40:42,480 --> 00:40:45,600
Speaker 11: Out, Yes, it comes out, I believe November sixth, and

820
00:40:45,760 --> 00:40:48,360
Speaker 11: it is seven hundred dollars and pre orders they're going

821
00:40:48,440 --> 00:40:49,239
Speaker 11: to make available.

822
00:40:49,520 --> 00:40:51,520
Speaker 7: I believe in the next couple of weeks. I believe

823
00:40:51,600 --> 00:40:53,000
Speaker 7: in two weeks or so.

824
00:40:53,680 --> 00:40:56,480
Speaker 2: Some of those FX price point differences from the UK

825
00:40:56,640 --> 00:40:59,480
Speaker 2: and EU as well. Want to watch plame most Jason Schreyer,

826
00:41:00,120 --> 00:41:00,600
Speaker 2: joy to have you.

827
00:41:00,840 --> 00:41:04,960
Speaker 3: Thank you. That's it for this edition of Bloomberg Technology ED.

828
00:41:05,040 --> 00:41:06,840
Speaker 3: Don't dwell on your nostalgia for discs.

829
00:41:07,480 --> 00:41:10,120
Speaker 4: I know, but I will play some PlayStations today. Now,

830
00:41:10,160 --> 00:41:12,040
Speaker 4: don't forget recap the show on the podcast. You know

831
00:41:12,080 --> 00:41:14,400
Speaker 4: where to find it on the Bloomberg terminal as well

832
00:41:14,440 --> 00:41:18,160
Speaker 4: as online on Apple, Spotify and iHeart huge. Thanks to

833
00:41:18,160 --> 00:41:20,400
Speaker 4: everyone out in New York City, the team here in

834
00:41:20,480 --> 00:41:23,120
Speaker 4: San Francisco. This is Bloomberg Technology