WEBVTT - Tech Sell Off Continues as Investors Question AI ROI

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<v Speaker 1>Bloomberg Audio Studios, Podcasts, radio news. Bloomberg Tech is alive

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<v Speaker 1>from coast to coast with Caroline Hide in New York

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<v Speaker 1>and Edlow in Sentrancesco.

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<v Speaker 2>This is Bloomberg Tech coming up. The tech sell of

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<v Speaker 2>accelerates as investors question valuations in the AI trade. This

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<v Speaker 2>is mit flag's concerns about enterprise AI adoption. We speak

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<v Speaker 2>but the return on tech investments, the Bank of America's

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<v Speaker 2>top technology officer, and what AI infused gadgets to expect

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<v Speaker 2>from Made by Google. Event that kicks off this afternoon.

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<v Speaker 2>But first we return to these markets that are having

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<v Speaker 2>another ugly day, two straight days of losses. We are

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<v Speaker 2>sinking significantly on the nastat one hundred, and they accelerate

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<v Speaker 2>off by more than three percentage points. Let's get into

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<v Speaker 2>some of the big points drags. We've got Netflix that's tumbling.

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<v Speaker 2>But I'm also looking at Palenteed. It is having its

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<v Speaker 2>worst two days in at least now four years. It's

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<v Speaker 2>twenty twenty two. We're seeing it sell off. We're off

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<v Speaker 2>by eight percent. Add that to the nine percent we

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<v Speaker 2>saw sell off yesterday. Those valuations that we were questioning

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<v Speaker 2>are actually coming down a fair bit in Video is

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<v Speaker 2>off by three point three percent after yesterday's about two

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<v Speaker 2>or three percent sell off as well. And Intel. It's

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<v Speaker 2>been outperforming the rest of the market previously, of course,

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<v Speaker 2>on the hopes of US investment coming from the government

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<v Speaker 2>and indeed two billion dollars coming from SoftBank, but today

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<v Speaker 2>even it succumbs to some of the anxiety. Let's stick

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<v Speaker 2>with a sell off. Let's get Ryan Rastellika's take. Go

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<v Speaker 2>really talk us through some of the worries in the market. Ryan,

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<v Speaker 2>what are we saying. We're having a questioning of AI valuations,

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<v Speaker 2>Is it macro concerns, is it August? And the fact

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<v Speaker 2>that we've got thin liquidity, what is it?

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<v Speaker 3>You know, I've heard all of those sort of things.

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<v Speaker 3>I've heard that this is sort of a seasonal issue

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<v Speaker 3>that we've seen in past years. So there are some

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<v Speaker 3>people saying this looks like an attractive time to be buying.

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<v Speaker 3>The tech trade remains intact, but you do have a

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<v Speaker 3>number of these names sort of really come up this year.

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<v Speaker 3>You mentioned Palenteer, also companies like Core, We've Nvidia, a

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<v Speaker 3>lot of the MAGS seven names have been very strong

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<v Speaker 3>performance this year that has brought multiples and valuations, so

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<v Speaker 3>levels that are really kind of getting tougher to justify.

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<v Speaker 3>We are out of the earning season, We're in sort

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<v Speaker 3>of a slow news environment right now, and it just

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<v Speaker 3>seems like when you've seen moves like this, some kind

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<v Speaker 3>of consolidation or pullback.

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<v Speaker 4>Is going to be expected.

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<v Speaker 3>And when you have such high momentum names like Palenteer,

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<v Speaker 3>like core Weave, you start to see some of the

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<v Speaker 3>most aggressive selling in names like that.

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<v Speaker 2>First Palenteers, who said worst two days set off in

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<v Speaker 2>three years, currently trading at one hundred and eighty times

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<v Speaker 2>future profit, but that's down from two hundred and forty

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<v Speaker 2>times street ship profits that it was current and previously

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<v Speaker 2>trading app but two days ago. Ryan is interesting. You'd

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<v Speaker 2>been digging into some of the valuations of the high

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<v Speaker 2>fliers that actually had only recently caught a bid. I

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<v Speaker 2>think of Intel and the fact that they'd added what

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<v Speaker 2>twenty four billion dollars in market capitalization in this month alone,

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<v Speaker 2>that's coming down today, and it did show this desire

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<v Speaker 2>to be getting into some AI related names.

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<v Speaker 3>Yeah, so Intel's a bit of a special case. You

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<v Speaker 3>mentioned how there was reports of government wanting to take

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<v Speaker 3>a stake. You had soft Bait coming out and looking

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<v Speaker 3>to invest about two billion dollars into the company. You

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<v Speaker 3>did see a pull up there. I think the stock

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<v Speaker 3>rows twenty to thirty percent something like that. However, this

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<v Speaker 3>is the third twenty percent rally that Intel has seen

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<v Speaker 3>this year. We did see those previous rallies fade pretty quickly.

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<v Speaker 3>There still continues to be a lot of questions and

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<v Speaker 3>concerns about whether Intel will be able to re establish

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<v Speaker 3>itself as a major player within chip manufacturing but also

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<v Speaker 3>chip design. It is very much behind Nvidia and AMD

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<v Speaker 3>and AI chips. It's behind TSMC on the manufacturing side,

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<v Speaker 3>so there's still a lot of questions there. It's not

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<v Speaker 3>necessarily surprising to see the stock pull back after that

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<v Speaker 3>initial excitement, especially since you know, as we reported yesterday,

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<v Speaker 3>the multiple gotta levels last scene in the dot com era.

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<v Speaker 2>And it's interesting that SoftBank's pulling back as well. It's

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<v Speaker 2>sun about seven percent, and in Asia trade we have

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<v Speaker 2>seen a bit of a global anxiety around tech by

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<v Speaker 2>doos lower as well after its results. Telling us a

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<v Speaker 2>little bit though about the next set of catalysts, because

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<v Speaker 2>at the moment we have been treading water more around

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<v Speaker 2>the macro concerns. We do get in Video's results next week,

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<v Speaker 2>that could be a key catalyst.

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<v Speaker 5>Yeah.

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<v Speaker 3>Absolutely, I think a lot of people are waiting to

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<v Speaker 3>see what is said there. I think there's a lot

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<v Speaker 3>of optimism about this report because we did just come

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<v Speaker 3>out of an earning season where all of its major

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<v Speaker 3>customers Microsoft, Meta, Alphabet, Amazon, they really affirmed their plans

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<v Speaker 3>to continue investing aggressively in AI, which is obviously going

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<v Speaker 3>to help Nvidia kind of first and foremost among the

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<v Speaker 3>infrastructure plays. Now, if they say anything about the outlook weakening,

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<v Speaker 3>or there's further skepticism about China or so on and

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<v Speaker 3>so forth, there is room for us to continue moving

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<v Speaker 3>down just because, like I said, we have seen really

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<v Speaker 3>strong gains in some of these stocks so far this year.

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<v Speaker 3>There is room for them to move down now. If

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<v Speaker 3>in Vidia is very strong, It's very possible that that

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<v Speaker 3>is a kind of sig people use to you know,

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<v Speaker 3>buy the step and maybe move back into tech.

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<v Speaker 5>Ran plus SELCA as always, we thank you.

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<v Speaker 2>Let's get you some breaking news now actually revolving around

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<v Speaker 2>a big tech player and China.

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<v Speaker 5>Microsoft is on the move.

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<v Speaker 2>The company says it has curtailed Chinese companies access to

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<v Speaker 2>advance notifications about cybersecurity vulnerabilities in its own technology. That,

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<v Speaker 2>of course, is after investigating whether a leak led to

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<v Speaker 2>a series of hacks exploiting flaws in its share points software. Now,

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<v Speaker 2>the announcement from Microsoft follows a campaign of cyber attacks

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<v Speaker 2>that Microsoft blamed on state sponsored hackers in China who

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<v Speaker 2>targeted security weaknesses in its SharePoint servers. We're off by

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<v Speaker 2>just seven tens percent. It's not as bad as the

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<v Speaker 2>rest of the market, but still trading lower. Let's get

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<v Speaker 2>you full context on this market. Anna Rathbunners with US

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<v Speaker 2>CEO founder of wealth management firm Grenandilla Advisory, And I mean,

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<v Speaker 2>what a difference a couple of days makes. What do

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<v Speaker 2>you make about this sudden AI valuation anxiety?

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<v Speaker 6>Yeah, good morning. In some ways it's expected, right, you

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<v Speaker 6>can't expect everything to go up all the time. I

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<v Speaker 6>do think that there is something to be said about

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<v Speaker 6>the month of August being you know, special in a

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<v Speaker 6>seasonal way. But the other thing is there are people

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<v Speaker 6>who are taking gains. There's also when there's fear that

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<v Speaker 6>comes into the markets. Usually the ones that are casualties

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<v Speaker 6>first are the ones with the highest valuations and those

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<v Speaker 6>are in the big techniques. So you know, this, this

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<v Speaker 6>I think is temporary. I don't think this is a

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<v Speaker 6>start of anything that will become a trend, but certainly

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<v Speaker 6>it's part of being an investor.

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<v Speaker 2>Part of being an investor, and how do you protect

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<v Speaker 2>what have been profits made? Is this actually just a

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<v Speaker 2>profit taking moment and people are locking in really big

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<v Speaker 2>wins that they've seen run up this summer.

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<v Speaker 6>You know, it would be prudent to certainly lock in

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<v Speaker 6>some of those gains, But I don't think you can

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<v Speaker 6>be out of it because AI is where all the growth.

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<v Speaker 4>And investment is going into it.

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<v Speaker 6>I mean, you saw, you know, about a month ago

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<v Speaker 6>Trump administration coming out and basically pledging its support behind

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<v Speaker 6>AI and data centers and all the infrastructure and hardware.

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<v Speaker 4>That's a part of it.

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<v Speaker 6>And certainly I think this move into taking an equity

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<v Speaker 6>stake in Intel is a part of that story and

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<v Speaker 6>also part of the story of bringing manufacturing back into

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<v Speaker 6>the United States.

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<v Speaker 4>So there's a lot of momentum here.

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<v Speaker 6>Now, government being a part of a private company is

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<v Speaker 6>a double edged sword, but if we're to take a

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<v Speaker 6>look at the upside, there's a lot of support around

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<v Speaker 6>AI and text, So I don't think investors can really

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<v Speaker 6>ignore it.

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<v Speaker 2>And to that point, I mean, when you get Intel

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<v Speaker 2>suddenly prior to today running up valuation sword to well

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<v Speaker 2>the most expensive it's been since the dot com era,

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<v Speaker 2>should you be putting that much credence in government backing

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<v Speaker 2>and in the ability for them to secure long term

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<v Speaker 2>demand for future chip innovations.

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<v Speaker 4>Yeah.

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<v Speaker 6>I don't think this is just about the government, because

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<v Speaker 6>we also had softwarek coming in and committing to or

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<v Speaker 6>talking about committing two billion dollars in terms of investment.

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<v Speaker 6>So I don't think this is the end of it.

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<v Speaker 6>And also I know the Trump administraturs said that they're

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<v Speaker 6>not going to be taking a governance role in this,

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<v Speaker 6>but you know, if you're the US government and you're

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<v Speaker 6>one of the largest shareholders, you can definitely influence through tweet.

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<v Speaker 6>And if the government has skin in the game, is

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<v Speaker 6>it really going to sit to the sidelines and look

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<v Speaker 6>at you know, Intel maybe not following through with the

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<v Speaker 6>Ohio foundry. I could see a scenario, there's a speculation,

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<v Speaker 6>but I could see a scenario in which the government

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<v Speaker 6>can help to garner those customers for those chips. I

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<v Speaker 6>don't think this is we'll take an equity steck and

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<v Speaker 6>be done with it.

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<v Speaker 4>I don't think that's that.

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<v Speaker 2>It's interesting SoftBank came on board many fitting that with

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<v Speaker 2>the help of ARM we could start to see real competition,

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<v Speaker 2>maybe even to in video in the longer term. Had

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<v Speaker 2>been some of the analysis written Anna, let's think about

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<v Speaker 2>in video for a moment. It's two down over the

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<v Speaker 2>last couple of days. We anticipate its earnings. Look more broadly,

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<v Speaker 2>of the tech tail wins. The AI trade still on.

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<v Speaker 4>I think it's still on.

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<v Speaker 6>I mean, you know, Meta just came out, and I

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<v Speaker 6>mean there I think there are issues there with the

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<v Speaker 6>management and the team structure and everything, and I don't

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<v Speaker 6>think it's necessarily good news for Meta.

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<v Speaker 2>But you know this hiring s Sorry. Why why is

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<v Speaker 2>the restructuring of the AI department Alexander Wang leading when

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<v Speaker 2>it comes to LMS and the breakdown of these four

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<v Speaker 2>different areas of focus. Why is that perhaps not good

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<v Speaker 2>news for Meta?

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<v Speaker 4>Well, it's not good news.

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<v Speaker 6>Good news in a sense that in the last two

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<v Speaker 6>months we've seen a lot of restructuring.

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<v Speaker 4>This is the type of stuff.

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<v Speaker 6>That makes investors nervous in terms of effective management. You know,

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<v Speaker 6>you can hire the smartest people at high price tag and.

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<v Speaker 4>Put them in a room.

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<v Speaker 6>If they can't work together, and if they can't like

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<v Speaker 6>produce a product, then you don't really have anything.

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<v Speaker 4>You don't have an ROI on that right.

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<v Speaker 6>So this is a type of stuff that makes investors nervous.

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<v Speaker 6>So I think that's a very meta specific problem.

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<v Speaker 2>I love that you have that idea of ROAI because

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<v Speaker 2>that is what many are looking at this MIT report about.

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<v Speaker 2>At the moment, we're blaming and it's in an unnuanced manner.

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<v Speaker 2>This particular report out at MIT is saying, look, ninety

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<v Speaker 2>five percent of the work done by company is to

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<v Speaker 2>integrate AI hasn't returned money or productivity. What did you

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<v Speaker 2>make of the report?

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<v Speaker 6>Ana, Well, I mean what would you expect? I mean,

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<v Speaker 6>this is such new technology, you know. I think you

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<v Speaker 6>have to expect a lot of these efforts to fail

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<v Speaker 6>in the beginning. You have to have a lot of

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<v Speaker 6>failures before you can have the wins. That's why I

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<v Speaker 6>look at the AI efforts by these mag seven names

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<v Speaker 6>as incubation. I mean to look at ROI and expect

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<v Speaker 6>ROI within a year or two of them actually really

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<v Speaker 6>embarking and investing in it. I think it's too soon.

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<v Speaker 6>I think this is more of a long term play,

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<v Speaker 6>and so that report was sort of expected in my mind.

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<v Speaker 5>Anna Rathbund, it's great to have you back on. Thank you.

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<v Speaker 2>Brenna del Advisory now coming up and pleased to say

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<v Speaker 2>we're going to be digging into the return on AI

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<v Speaker 2>investment with Harry go Pel Krishnan is the chief Technology

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<v Speaker 2>and Information Officer for Bank of America. All about where

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<v Speaker 2>they've been focusing in on artificial intelligence and tech more broadly.

0:11:15.920 --> 0:11:18.120
<v Speaker 2>Let's get tech more broadly for a moment. So we

0:11:18.160 --> 0:11:19.440
<v Speaker 2>are in the eye the storm of a bit of

0:11:19.440 --> 0:11:21.079
<v Speaker 2>a sell off today. We're off by one and a

0:11:21.080 --> 0:11:23.120
<v Speaker 2>half percent on the Nasdaq one hundred, coming off of

0:11:23.160 --> 0:11:26.319
<v Speaker 2>our lows, the socks though Semiconductor Index, or by two

0:11:26.320 --> 0:11:28.120
<v Speaker 2>and a half percent. In Video off by two point

0:11:28.160 --> 0:11:31.760
<v Speaker 2>eight percent, Pallenteer having its worst couple of days in

0:11:31.840 --> 0:11:41.959
<v Speaker 2>three years. This is the Bloomberg Tech Oracle's cloud infrastructure unit. Well,

0:11:41.960 --> 0:11:44.600
<v Speaker 2>it's helped to propel CEO Larry Ellison to become the

0:11:44.640 --> 0:11:47.040
<v Speaker 2>second richest person in the world at one point. With

0:11:47.120 --> 0:11:49.839
<v Speaker 2>the AI boom, the company saw huge demand for its

0:11:49.840 --> 0:11:53.600
<v Speaker 2>computing and storage over the Internet, gaining foothold among key customers.

0:11:53.720 --> 0:11:57.680
<v Speaker 2>TikTok Open Ai for more. Bloomberg's Brodie Ford, who covers Oracle,

0:11:58.040 --> 0:12:02.440
<v Speaker 2>joins us now and many point in history, Oracle almost

0:12:02.480 --> 0:12:04.560
<v Speaker 2>pushed against this trend, and now they are well and

0:12:04.600 --> 0:12:05.240
<v Speaker 2>truly into it.

0:12:05.880 --> 0:12:08.760
<v Speaker 7>Two thousand and eight, Larry Ellison gave the speech people

0:12:08.840 --> 0:12:11.959
<v Speaker 7>love citing. He said, this cloud is gibberish. And I mean,

0:12:12.360 --> 0:12:16.640
<v Speaker 7>they were making so much money and continue on old

0:12:16.679 --> 0:12:20.360
<v Speaker 7>school database software. But in the last couple of years

0:12:20.400 --> 0:12:23.840
<v Speaker 7>they've managed to really reinvent themselves from a legacy company

0:12:23.880 --> 0:12:26.400
<v Speaker 7>to one that's at the center of the AI boom.

0:12:26.720 --> 0:12:29.480
<v Speaker 7>And yeah, I mean there's no better example in their

0:12:29.520 --> 0:12:32.760
<v Speaker 7>work with open ai and stargate. Right we have the

0:12:32.840 --> 0:12:35.880
<v Speaker 7>details that on one new data center in West Texas

0:12:35.880 --> 0:12:38.520
<v Speaker 7>they're going to be spending over one billion per year

0:12:38.840 --> 0:12:41.440
<v Speaker 7>just to power the thing with gas. I mean that's

0:12:41.480 --> 0:12:45.320
<v Speaker 7>before construction, that's before all the chips. The scale of

0:12:45.360 --> 0:12:48.240
<v Speaker 7>the cloud build out happening for AI right now is

0:12:48.360 --> 0:12:51.600
<v Speaker 7>just it's a comical scale that we haven't seen before,

0:12:51.640 --> 0:12:53.880
<v Speaker 7>and Oracle has found itself at the center of it.

0:12:54.320 --> 0:12:57.400
<v Speaker 2>Let's just talk about who's driven this because the CEO

0:12:57.480 --> 0:13:01.240
<v Speaker 2>is it called suffracats. How much has she been the

0:13:01.280 --> 0:13:03.720
<v Speaker 2>pinpointing of this growth area. How much has Larry Alison

0:13:03.800 --> 0:13:05.600
<v Speaker 2>really been playing a key role? What do you make

0:13:05.640 --> 0:13:07.440
<v Speaker 2>of the internal work and so good this business.

0:13:07.840 --> 0:13:09.800
<v Speaker 7>We spoke with a lot of folks that are close

0:13:09.840 --> 0:13:13.520
<v Speaker 7>to this business, and you know, the CEO. Everybody wants

0:13:13.559 --> 0:13:16.319
<v Speaker 7>money from you, And for a long time, Saphra said, no,

0:13:16.440 --> 0:13:18.400
<v Speaker 7>we are not giving you all the money that it

0:13:18.440 --> 0:13:20.600
<v Speaker 7>takes to build these data centers. Right, I mean she

0:13:20.720 --> 0:13:24.000
<v Speaker 7>was skeptical the business for a long time, and then

0:13:24.040 --> 0:13:27.040
<v Speaker 7>these big deals started hitting. I mean, TikTok around twenty

0:13:27.080 --> 0:13:29.760
<v Speaker 7>twenty two was making so much money that it was

0:13:29.840 --> 0:13:33.280
<v Speaker 7>bigger than the entire rest of Oracle's Cloud all put together.

0:13:33.960 --> 0:13:36.160
<v Speaker 7>And so she saw deals like that, she saw deals

0:13:36.160 --> 0:13:38.360
<v Speaker 7>like open Ai, and that's when it became clear that

0:13:38.920 --> 0:13:41.720
<v Speaker 7>this isn't just part of Oracle's business. This is going

0:13:41.760 --> 0:13:45.280
<v Speaker 7>to be the business. Wall Street expects that by twenty

0:13:45.400 --> 0:13:48.280
<v Speaker 7>twenty nine that cloud Infra will actually be the largest

0:13:48.280 --> 0:13:51.280
<v Speaker 7>share of Oracle's revenue. And so this is a true

0:13:51.440 --> 0:13:55.120
<v Speaker 7>reinvention of the company for good and potentially for bad. Right,

0:13:55.120 --> 0:13:58.280
<v Speaker 7>I mean it's a much lower margin business. There's more

0:13:58.360 --> 0:14:01.280
<v Speaker 7>risk to it. But clearly for now the sentiment is

0:14:01.280 --> 0:14:04.200
<v Speaker 7>good and something is working well for them and the.

0:14:04.160 --> 0:14:08.079
<v Speaker 2>Breadth of customer here, Brodie, because we think of TikTok

0:14:08.120 --> 0:14:10.240
<v Speaker 2>and we know they're a key strutch player for them,

0:14:10.400 --> 0:14:12.960
<v Speaker 2>we know the relationship with Stargate and therefore open Ai.

0:14:13.040 --> 0:14:15.400
<v Speaker 7>But how broad is this getting It is a bit

0:14:15.440 --> 0:14:18.120
<v Speaker 7>of a whale business right now. It's a bit concentrated,

0:14:18.200 --> 0:14:22.920
<v Speaker 7>right The majority of their backlog is AI deals, largely training.

0:14:24.240 --> 0:14:28.040
<v Speaker 7>There are questions out there around how long does the

0:14:28.120 --> 0:14:30.880
<v Speaker 7>training boom last? What are the margins of it. It's

0:14:30.920 --> 0:14:33.480
<v Speaker 7>a very impressive customer list for sure, right. I mean,

0:14:33.560 --> 0:14:35.520
<v Speaker 7>as you said, we got open Ai, we got TikTok,

0:14:35.560 --> 0:14:39.040
<v Speaker 7>we got Elon Musk's Xai, we have Meta, we have

0:14:39.120 --> 0:14:41.520
<v Speaker 7>a kind of cadre of you know, all the AI

0:14:41.640 --> 0:14:44.880
<v Speaker 7>names that we all know, and so they've signed all

0:14:44.920 --> 0:14:48.000
<v Speaker 7>the right people. But the real test I'm going forward

0:14:48.080 --> 0:14:50.560
<v Speaker 7>is can you sell these folks more than just GPUs

0:14:51.720 --> 0:14:52.880
<v Speaker 7>and what can.

0:14:52.760 --> 0:14:55.640
<v Speaker 2>They do with them? Punning Meg's Brodie Ford, fantastic to

0:14:55.680 --> 0:14:57.760
<v Speaker 2>have you, thank you. Let's talk about what you can

0:14:57.840 --> 0:15:00.800
<v Speaker 2>do with all of this GPU, this compute and how

0:15:00.800 --> 0:15:04.640
<v Speaker 2>it ultimately brings productivity to study from MIT saying that actually,

0:15:04.680 --> 0:15:07.720
<v Speaker 2>despite the billions enterprises have spent on general to AI,

0:15:08.120 --> 0:15:11.880
<v Speaker 2>perhaps only ninety five percent of organizations, well they say

0:15:12.000 --> 0:15:14.240
<v Speaker 2>they're actually getting a zero return. Thus far, only five

0:15:14.240 --> 0:15:17.360
<v Speaker 2>percent have got any return. This is really true. Harry

0:15:17.400 --> 0:15:19.560
<v Speaker 2>gopel Chrishnan is with us. He is the new Chief

0:15:19.600 --> 0:15:22.000
<v Speaker 2>Technology and Information officer over at Bank of America, but

0:15:22.160 --> 0:15:24.800
<v Speaker 2>he leads the bank's global technology approach. You've been at

0:15:24.800 --> 0:15:27.120
<v Speaker 2>Bank of America for fourteen years, but you've very recently

0:15:27.160 --> 0:15:30.600
<v Speaker 2>taken on this real global helm job. And there is

0:15:30.680 --> 0:15:33.680
<v Speaker 2>more nuance to that MIT report than the market has

0:15:33.720 --> 0:15:36.520
<v Speaker 2>given credence to. Basically, it's saying, look, if you just

0:15:36.560 --> 0:15:39.800
<v Speaker 2>tried to make it up and perhaps build some CHATCHBT

0:15:40.240 --> 0:15:42.680
<v Speaker 2>like products yourself, it didn't always work. But what have

0:15:42.760 --> 0:15:45.520
<v Speaker 2>you been doing internally to make things work for Bank

0:15:45.560 --> 0:15:46.600
<v Speaker 2>of America? Yeah?

0:15:46.600 --> 0:15:48.880
<v Speaker 8>Great, thanks for having me. And look, we get to

0:15:48.880 --> 0:15:51.960
<v Speaker 8>serve seventy million clients every single day and AI is

0:15:52.000 --> 0:15:52.640
<v Speaker 8>not new to us.

0:15:52.720 --> 0:15:53.680
<v Speaker 4>It's been part of our journey.

0:15:53.760 --> 0:15:55.440
<v Speaker 8>So if I could offer you some soundbites of what

0:15:55.440 --> 0:15:57.960
<v Speaker 8>we've seen in the last five years, ninety nine percent

0:15:57.960 --> 0:16:00.760
<v Speaker 8>of our customers and clients today interact with us digitally

0:16:00.840 --> 0:16:04.080
<v Speaker 8>fully self serviced. Ninety nine percent of interactions in the

0:16:04.080 --> 0:16:07.440
<v Speaker 8>consumer business our self service digital. We have sixty five

0:16:07.480 --> 0:16:09.840
<v Speaker 8>percent of our account opening is digitally done. Ten years

0:16:09.840 --> 0:16:13.040
<v Speaker 8>ago zero percent. Our client satisfaction number, which we care

0:16:13.080 --> 0:16:15.640
<v Speaker 8>a lot about, has gone from the high seventies to

0:16:15.680 --> 0:16:17.960
<v Speaker 8>eighty nine point one. And yes we're counting, and so

0:16:18.000 --> 0:16:21.000
<v Speaker 8>you think about it, better client satisfaction. Shift to more

0:16:21.160 --> 0:16:24.960
<v Speaker 8>self service channels and more automation always yields great results.

0:16:25.000 --> 0:16:26.560
<v Speaker 8>And AI has been part of that.

0:16:26.560 --> 0:16:27.200
<v Speaker 4>Journey for us.

0:16:27.320 --> 0:16:30.280
<v Speaker 2>And I think of as the client. The customer perspective

0:16:30.320 --> 0:16:33.600
<v Speaker 2>is Erica. But your client and your other stakeholders, you

0:16:33.720 --> 0:16:36.560
<v Speaker 2>can your own employee base. How have they been adopting

0:16:36.640 --> 0:16:38.560
<v Speaker 2>general TODAI? Have them am using assistance?

0:16:38.840 --> 0:16:39.040
<v Speaker 4>Yeah?

0:16:39.080 --> 0:16:40.880
<v Speaker 8>And maybe if you just ruround the clock a bit right.

0:16:40.920 --> 0:16:43.040
<v Speaker 8>Our first journey into AI started with things like fraud

0:16:43.120 --> 0:16:46.480
<v Speaker 8>models and fraud algorithms. We have fourteen hundred plus patents

0:16:46.480 --> 0:16:49.000
<v Speaker 8>and two hundred and fifteen models in production with things

0:16:49.040 --> 0:16:51.240
<v Speaker 8>like AI models, and what we realized seventy eight years

0:16:51.240 --> 0:16:53.720
<v Speaker 8>ago is humans wanted to interact with machines in a

0:16:53.760 --> 0:16:57.280
<v Speaker 8>more humanistic fashion. And long before the large language models

0:16:57.320 --> 0:17:00.160
<v Speaker 8>came along, we thought about things like Erica, which allows

0:17:00.000 --> 0:17:02.560
<v Speaker 8>a customer to simply say a few words and for

0:17:02.680 --> 0:17:04.720
<v Speaker 8>us to figure out what they want rather than them

0:17:04.720 --> 0:17:07.119
<v Speaker 8>trying to figure out what our systems actually did. And

0:17:07.160 --> 0:17:10.040
<v Speaker 8>that's where we've now seen significant adoption. So this morning

0:17:10.080 --> 0:17:11.680
<v Speaker 8>we had a press release that we now had three

0:17:11.720 --> 0:17:14.919
<v Speaker 8>billion transactions that have been conducted on an aircut and

0:17:14.960 --> 0:17:16.000
<v Speaker 8>that continues to grow at.

0:17:15.960 --> 0:17:16.840
<v Speaker 4>An exponential pace.

0:17:17.400 --> 0:17:19.920
<v Speaker 8>So that's our clients and customers saying we actually like.

0:17:19.880 --> 0:17:21.200
<v Speaker 4>To engage with you in this way.

0:17:21.640 --> 0:17:23.879
<v Speaker 8>When you then pivot to our employee base, they're like, well,

0:17:23.880 --> 0:17:25.960
<v Speaker 8>why can't we use the same capability. So we've taken

0:17:26.000 --> 0:17:29.320
<v Speaker 8>this platform and broadened it use. So today a high

0:17:29.320 --> 0:17:32.160
<v Speaker 8>network advisor can actually look to Erica to say, look,

0:17:32.200 --> 0:17:35.000
<v Speaker 8>I need to hear about some complex trust policy in Delaware.

0:17:35.160 --> 0:17:36.920
<v Speaker 8>Can you summarize it for me and tell me how

0:17:36.920 --> 0:17:39.200
<v Speaker 8>I should talk to the client about it. And one

0:17:39.200 --> 0:17:41.520
<v Speaker 8>of the more recent implementation has been is I'm about

0:17:41.520 --> 0:17:43.840
<v Speaker 8>to meet a client, how do I prepare for that meeting?

0:17:44.160 --> 0:17:46.639
<v Speaker 8>Before a junior banker would take days to prepare a

0:17:46.800 --> 0:17:49.399
<v Speaker 8>docier for that. Now we can actually use Generati VI

0:17:49.640 --> 0:17:52.199
<v Speaker 8>models to create the first version of a draft that

0:17:52.320 --> 0:17:55.120
<v Speaker 8>saves hours and minutes, if not time, which then drops

0:17:55.160 --> 0:17:55.879
<v Speaker 8>to the bottom line.

0:17:55.960 --> 0:17:58.080
<v Speaker 2>Harry, I know in many ways this is your secret source.

0:17:58.119 --> 0:18:01.080
<v Speaker 2>But I'm reading that you've got what seven eight hundred

0:18:01.080 --> 0:18:03.919
<v Speaker 2>patents of your own. How much are you having to

0:18:04.000 --> 0:18:07.240
<v Speaker 2>depend on purpose built general to AI. How much are

0:18:07.280 --> 0:18:09.960
<v Speaker 2>you looking to an open AI for the enterprise offering

0:18:10.080 --> 0:18:11.720
<v Speaker 2>or are you going to build it yourself?

0:18:12.000 --> 0:18:14.520
<v Speaker 8>Well, I think we have a multi level approach to this, right,

0:18:14.560 --> 0:18:17.560
<v Speaker 8>We're not you know, we have enough reality to know

0:18:17.600 --> 0:18:19.719
<v Speaker 8>that we're not going to go build foundation models. We

0:18:19.760 --> 0:18:21.720
<v Speaker 8>want to build upon all the investments that are happening

0:18:21.760 --> 0:18:24.359
<v Speaker 8>in the industry. But the reason they're called foundation models

0:18:24.400 --> 0:18:25.840
<v Speaker 8>is they let you do a lot of things on

0:18:25.880 --> 0:18:27.280
<v Speaker 8>top of them. So we have a level of the

0:18:27.320 --> 0:18:29.600
<v Speaker 8>stack where we absolutely will embrace.

0:18:29.240 --> 0:18:31.120
<v Speaker 2>Commodity, which ones I don't interest.

0:18:31.240 --> 0:18:32.679
<v Speaker 8>Well, I think a little bit of everything. Right, We

0:18:32.720 --> 0:18:35.080
<v Speaker 8>are looking at it, and we intentionally want to be madalagnostic. Right,

0:18:35.119 --> 0:18:36.800
<v Speaker 8>We intentionally do not want to be wedded to any

0:18:36.800 --> 0:18:39.119
<v Speaker 8>one single solution, but then built upon it. When it

0:18:39.200 --> 0:18:41.919
<v Speaker 8>comes to our complex workflows. When you think about our

0:18:41.960 --> 0:18:44.360
<v Speaker 8>business processes, if it was just as simple as buy

0:18:44.400 --> 0:18:46.680
<v Speaker 8>something off the shelf, every one of us would be done.

0:18:47.080 --> 0:18:49.119
<v Speaker 8>The reality is you have to take these models in

0:18:49.160 --> 0:18:51.800
<v Speaker 8>and back to your productivity question, the way you unleash

0:18:51.840 --> 0:18:56.080
<v Speaker 8>productivities applying these to your business process. Understanding how your

0:18:56.080 --> 0:18:59.040
<v Speaker 8>current process work. Don't just try to replicate it, figure

0:18:59.040 --> 0:19:01.399
<v Speaker 8>out where you can eliminate parts of it, simplify it,

0:19:01.680 --> 0:19:03.320
<v Speaker 8>and then use AI to go after it.

0:19:03.320 --> 0:19:05.159
<v Speaker 4>And what we've seen is it's yield a tremendous results

0:19:05.160 --> 0:19:05.399
<v Speaker 4>for us.

0:19:05.440 --> 0:19:08.240
<v Speaker 2>I mean you said, and we're counting. How are you

0:19:08.320 --> 0:19:11.439
<v Speaker 2>measuring that productivity gain apart from the sheer scale of

0:19:11.480 --> 0:19:13.280
<v Speaker 2>interactions and numbers that you're seeing?

0:19:13.480 --> 0:19:14.639
<v Speaker 8>Yea, I'll give you an example of it.

0:19:14.720 --> 0:19:14.880
<v Speaker 1>Right.

0:19:14.920 --> 0:19:18.000
<v Speaker 8>We now have seventeen thousand developers in my own team

0:19:18.080 --> 0:19:21.119
<v Speaker 8>that use coding agents to help their day to day activities.

0:19:21.560 --> 0:19:24.720
<v Speaker 8>Within that, we actually measure things like cost per story point,

0:19:25.160 --> 0:19:27.760
<v Speaker 8>defect density. There's a set of metrics productivity metrics that

0:19:27.800 --> 0:19:29.320
<v Speaker 8>we look at and we look at it before and

0:19:29.359 --> 0:19:32.359
<v Speaker 8>after we expect to do similar things on a business

0:19:32.359 --> 0:19:35.840
<v Speaker 8>process by business process basis. To actually understand the metrics

0:19:35.880 --> 0:19:38.320
<v Speaker 8>when we went into the problem how we deploy these

0:19:38.320 --> 0:19:40.439
<v Speaker 8>capabilities because they're not cheap, so we need to make

0:19:40.440 --> 0:19:42.880
<v Speaker 8>sure there's an ROI component to it. But coming out

0:19:42.880 --> 0:19:44.679
<v Speaker 8>of it, be able to see what comes out and

0:19:44.720 --> 0:19:47.040
<v Speaker 8>fail fast if it seems like a given process doesn't

0:19:47.119 --> 0:19:48.080
<v Speaker 8>lend itself appropriately.

0:19:48.160 --> 0:19:50.879
<v Speaker 2>So I go to the sensitive question of those employees

0:19:50.920 --> 0:19:52.679
<v Speaker 2>that are embracing these coding agents.

0:19:52.760 --> 0:19:54.600
<v Speaker 5>Yeah, to have a few of them.

0:19:54.440 --> 0:19:57.639
<v Speaker 2>How are they feeling about being augmented or replaced?

0:19:57.840 --> 0:19:59.879
<v Speaker 8>Well, I would say it actually allows us to get

0:20:00.080 --> 0:20:02.560
<v Speaker 8>to a backlog we could never get to. There's always

0:20:02.600 --> 0:20:05.119
<v Speaker 8>more work than you can get to. There's always things

0:20:05.119 --> 0:20:07.320
<v Speaker 8>that you could modernize, There's always more things to do.

0:20:07.359 --> 0:20:09.400
<v Speaker 8>And I actually tell you that our first reaction from

0:20:09.400 --> 0:20:11.800
<v Speaker 8>our teammates is been this frees them to do more

0:20:11.840 --> 0:20:15.120
<v Speaker 8>innovative work rather than the mundane work that was consuming

0:20:15.160 --> 0:20:16.639
<v Speaker 8>their time and resources. And I think we're going to

0:20:16.680 --> 0:20:18.440
<v Speaker 8>see that pattern play itself out over time.

0:20:18.840 --> 0:20:22.040
<v Speaker 2>Sunny One, what a few weeks into the leading job.

0:20:22.240 --> 0:20:24.320
<v Speaker 2>It's wonderful to speak with you, Harry. Harry go for

0:20:24.480 --> 0:20:28.200
<v Speaker 2>Christian who's the chief technology and information officer over Bank

0:20:28.240 --> 0:20:36.800
<v Speaker 2>of America. Time now for talking tech and first up,

0:20:36.880 --> 0:20:39.520
<v Speaker 2>Shaomi says it's looking to sell its first EVS in

0:20:39.640 --> 0:20:42.159
<v Speaker 2>Europe by twenty twenty seven, taking on the likes of

0:20:42.200 --> 0:20:45.280
<v Speaker 2>Tesla and byd Now. The company announced its strategy after

0:20:45.280 --> 0:20:48.080
<v Speaker 2>posting a thirty one percent rise in quarterly revenue, boosted

0:20:48.119 --> 0:20:50.840
<v Speaker 2>by the launch of its second EV Now. According to

0:20:50.880 --> 0:20:54.000
<v Speaker 2>the Shaomi president, the company is doing research and preparation,

0:20:54.520 --> 0:20:57.560
<v Speaker 2>has no specific product plan yet, plus shares a by

0:20:57.600 --> 0:21:00.720
<v Speaker 2>do where they're lower today. The company posting second revenue

0:21:00.800 --> 0:21:03.760
<v Speaker 2>that slips slightly as it faces an economic downturn in

0:21:03.840 --> 0:21:07.080
<v Speaker 2>China and our AI rivals and difficulties in net growth areas.

0:21:07.119 --> 0:21:11.080
<v Speaker 2>In particular, China's Internet search is looking to Genai to

0:21:11.160 --> 0:21:14.040
<v Speaker 2>drive future growth, but it is struggling as open source

0:21:14.040 --> 0:21:17.920
<v Speaker 2>models like Deep Sea gain traction and startup. Game Science

0:21:18.080 --> 0:21:20.399
<v Speaker 2>has unveiled its working on a successor to one of

0:21:20.480 --> 0:21:24.480
<v Speaker 2>last year's best selling RPG titles now at games Con

0:21:24.600 --> 0:21:26.880
<v Speaker 2>conference it was over in Germany, the company showed off

0:21:26.920 --> 0:21:30.680
<v Speaker 2>a teaser trailer to Black Myth chron Qui, a sequel

0:21:30.720 --> 0:21:32.560
<v Speaker 2>to twenty twenty fours Black Myth Wukong.

0:21:32.840 --> 0:21:32.919
<v Speaker 4>Now.

0:21:32.920 --> 0:21:35.800
<v Speaker 2>According to game Science back at tencent, the project is

0:21:35.920 --> 0:21:40.080
<v Speaker 2>quote little more than an empty folder at its current stage,

0:21:40.640 --> 0:21:45.520
<v Speaker 2>coming up Meta making those restructuring moves of its AI group.

0:21:46.080 --> 0:21:48.920
<v Speaker 2>They have the details. Next, at first, that's check in

0:21:48.960 --> 0:21:51.680
<v Speaker 2>on these markets. We are down, and we're down significantly.

0:21:51.800 --> 0:21:55.480
<v Speaker 2>Then a's that one hundred really accelerating yesterday's losses. We

0:21:55.520 --> 0:21:57.840
<v Speaker 2>bounce off our lowers, but still we're seeing some of

0:21:57.880 --> 0:21:59.919
<v Speaker 2>the worst sell off that we've seen in a few months.

0:22:00.000 --> 0:22:03.159
<v Speaker 2>Are also saying names like Palenteer really eroding some of

0:22:03.200 --> 0:22:05.600
<v Speaker 2>that valuation that we've seen, having its worst couple of

0:22:05.640 --> 0:22:08.680
<v Speaker 2>days in three years, Other names such as Apple and

0:22:08.880 --> 0:22:11.720
<v Speaker 2>contributing to the points perspective. This is the Blombg Tech.

0:22:17.720 --> 0:22:20.000
<v Speaker 2>Welcome back to Bloomberg Tech. Let's take a look at

0:22:20.040 --> 0:22:22.439
<v Speaker 2>these markets. We're in sell off mode. We are bouncing

0:22:22.440 --> 0:22:24.520
<v Speaker 2>off our lows. Nevertheless, we're off by two point four

0:22:24.560 --> 0:22:27.360
<v Speaker 2>percent in the last two days, worst sell off since

0:22:27.359 --> 0:22:31.480
<v Speaker 2>about April. In fact, we have some deep anxiety surrounding valuations,

0:22:31.520 --> 0:22:34.520
<v Speaker 2>particularly in the AI trade, whether it's macro concerns as

0:22:34.520 --> 0:22:36.800
<v Speaker 2>we anticipate. J. Powell and an awful lot of FED

0:22:36.800 --> 0:22:40.000
<v Speaker 2>talk what rates mean, but also more broadly, what these

0:22:40.040 --> 0:22:43.280
<v Speaker 2>valuations have got to extreme levels really mean. When you've

0:22:43.320 --> 0:22:47.160
<v Speaker 2>got perhaps Enterprise not fully adopting in the productivity means

0:22:47.160 --> 0:22:51.160
<v Speaker 2>that some anticipated that MIT research report causing some girations.

0:22:51.240 --> 0:22:52.960
<v Speaker 2>Let's move on to the individual movers that we keep

0:22:52.960 --> 0:22:55.520
<v Speaker 2>an eye on. Look, I'm off by overall in the

0:22:55.560 --> 0:22:58.960
<v Speaker 2>last few days, well five and a half percent for Palenteer,

0:22:59.000 --> 0:23:01.080
<v Speaker 2>but worst couple of days set off in a few years.

0:23:01.119 --> 0:23:03.560
<v Speaker 2>Intel is off by more than six percent, wiping out

0:23:03.560 --> 0:23:06.879
<v Speaker 2>a lot of yesterday's gains. After we were enthusiasmor and

0:23:07.000 --> 0:23:09.679
<v Speaker 2>soft Bank investing in this company, and indeed talk of

0:23:09.680 --> 0:23:12.080
<v Speaker 2>the US government taking at least a ten percent stake.

0:23:12.240 --> 0:23:14.560
<v Speaker 2>But we pull back on Intel as people really lock

0:23:14.640 --> 0:23:16.600
<v Speaker 2>in profits. On Meta as well, we're off by one

0:23:16.600 --> 0:23:19.840
<v Speaker 2>point four percent. It's down the three straight trading days,

0:23:19.840 --> 0:23:22.480
<v Speaker 2>having lost five point six percent in the course of

0:23:22.520 --> 0:23:25.440
<v Speaker 2>those three days. Let's just stick with Meta more broadly.

0:23:25.480 --> 0:23:29.040
<v Speaker 2>In the company announcing yesterday yet another restructuring of its

0:23:29.080 --> 0:23:32.679
<v Speaker 2>AI group, pursuing superintelligence. Now it will be splitting its

0:23:32.720 --> 0:23:36.400
<v Speaker 2>AI team into four distinct teams and move. The company says,

0:23:36.440 --> 0:23:39.280
<v Speaker 2>we'll allow it to better capitalize on its recently acquired talent.

0:23:39.520 --> 0:23:42.320
<v Speaker 2>Bloomberg's tech reporter Riley Griffin is here to break it

0:23:42.359 --> 0:23:45.280
<v Speaker 2>all down. You're in San Francisco really digesting what seems

0:23:45.280 --> 0:23:50.480
<v Speaker 2>to be a focus on llms, still on the frontier research,

0:23:50.880 --> 0:23:54.000
<v Speaker 2>but then there's the application of this research and the infrastructure.

0:23:54.040 --> 0:23:56.200
<v Speaker 2>Of course, no doubt.

0:23:56.320 --> 0:23:59.159
<v Speaker 9>Yesterday we were able to obtain a memo that was

0:23:59.200 --> 0:24:03.280
<v Speaker 9>shared by Alan are Weighing, the new chief of Metasuperintelligence Labs,

0:24:03.600 --> 0:24:05.879
<v Speaker 9>and he's really laying out the new structure for this

0:24:06.000 --> 0:24:10.439
<v Speaker 9>organization after weeks and weeks of an incredible effort to

0:24:10.600 --> 0:24:14.800
<v Speaker 9>hire talent. As you might remember, Caroline, this is hundreds

0:24:14.840 --> 0:24:19.240
<v Speaker 9>of millions of dollars sometimes nearing billion dollars in total

0:24:19.240 --> 0:24:23.040
<v Speaker 9>compensation for individual AI researchers, and now they are finding

0:24:23.080 --> 0:24:25.240
<v Speaker 9>their home within META, within these four teams.

0:24:25.480 --> 0:24:29.680
<v Speaker 2>Yeah, and the home how are you seeing the perhaps

0:24:29.720 --> 0:24:32.800
<v Speaker 2>what some have reported by the scenes of some jostling

0:24:32.920 --> 0:24:36.520
<v Speaker 2>or discomfort with what had been suddenly incredibly expensive talent

0:24:36.600 --> 0:24:39.239
<v Speaker 2>coming in and a reorientation of where the focus is.

0:24:40.000 --> 0:24:43.600
<v Speaker 2>Does this help better align that talent and actually push forward?

0:24:43.640 --> 0:24:46.639
<v Speaker 2>And ultimately is it open large language models for example?

0:24:46.680 --> 0:24:48.920
<v Speaker 2>Are they going to delve into closed ones? Potentially?

0:24:50.080 --> 0:24:52.960
<v Speaker 9>That is a really a burning question for all of us.

0:24:53.240 --> 0:24:55.920
<v Speaker 9>What we do know is that one team will continue

0:24:55.920 --> 0:24:59.280
<v Speaker 9>to be dedicated to large language models, the Lama product

0:24:59.400 --> 0:25:04.000
<v Speaker 9>that under pins metas AI efforts broadly.

0:25:04.520 --> 0:25:06.280
<v Speaker 2>And the one team that I.

0:25:06.200 --> 0:25:08.760
<v Speaker 9>Really am keeping an eye on is the infrastructure team.

0:25:08.960 --> 0:25:11.639
<v Speaker 9>Mark Zuckerberg has pledged to spend hundreds of billions of

0:25:11.680 --> 0:25:15.640
<v Speaker 9>dollars specifically on AI infrastructure, and now we are seeing

0:25:16.400 --> 0:25:20.000
<v Speaker 9>talent from within the company go and lead that specific effort.

0:25:20.160 --> 0:25:23.080
<v Speaker 9>We expect more capital to be deployed there this year

0:25:23.119 --> 0:25:24.960
<v Speaker 9>and then certainly next some.

0:25:25.000 --> 0:25:28.600
<v Speaker 2>Great reporting Ridley Griffin, we so appreciate it. Let's get

0:25:28.760 --> 0:25:31.439
<v Speaker 2>some of the investor and analysis take now. Rohit kol

0:25:31.480 --> 0:25:33.880
<v Speaker 2>Con is with this managing director and scene analyst covering

0:25:33.880 --> 0:25:37.159
<v Speaker 2>Internet and capital markets research at Growth Capital Partners. And

0:25:37.200 --> 0:25:41.000
<v Speaker 2>that commitment to infrastructure that Riley articulates there, that money

0:25:41.640 --> 0:25:42.440
<v Speaker 2>is it proving out?

0:25:44.040 --> 0:25:45.119
<v Speaker 4>I hey, thanks for having me.

0:25:45.200 --> 0:25:48.200
<v Speaker 10>I think so far, what we have seen looking backwards

0:25:48.880 --> 0:25:52.920
<v Speaker 10>last twelve perhaps fifteen months, Meta is probably the best

0:25:53.359 --> 0:25:59.760
<v Speaker 10>poster child in providing qualifiable returns on investment in AI

0:25:59.800 --> 0:26:02.560
<v Speaker 10>in ffrastructure. By that, what I mean is the company

0:26:02.600 --> 0:26:07.359
<v Speaker 10>has demonstrated accelerating revenues. The company has demonstrated upside to

0:26:07.480 --> 0:26:11.760
<v Speaker 10>industry growth and a lot of other belts and vestles

0:26:11.880 --> 0:26:16.439
<v Speaker 10>around AI investment. So looking backwards, yes, definitely is the

0:26:16.440 --> 0:26:21.320
<v Speaker 10>poster child of showing written on investment looking forward.

0:26:21.400 --> 0:26:23.240
<v Speaker 4>That's the question mark in the stock today.

0:26:23.520 --> 0:26:25.760
<v Speaker 2>Okay, so they've been able to make it work for

0:26:25.800 --> 0:26:29.359
<v Speaker 2>advertising in the business model, but now for superintelligence and

0:26:29.400 --> 0:26:32.199
<v Speaker 2>the race to be one what business model does that

0:26:32.280 --> 0:26:33.199
<v Speaker 2>align itself with?

0:26:33.280 --> 0:26:33.800
<v Speaker 5>For Meta?

0:26:33.960 --> 0:26:36.840
<v Speaker 2>How much are we going to see generative AI affect

0:26:36.920 --> 0:26:38.720
<v Speaker 2>the way in which we interact and communicate.

0:26:40.240 --> 0:26:44.000
<v Speaker 10>I believe the problems that Meta is trying to solve

0:26:44.680 --> 0:26:49.639
<v Speaker 10>using AI and using superintelligence are just compounding with the

0:26:49.760 --> 0:26:52.720
<v Speaker 10>data that they're collecting and the possible business models that

0:26:52.720 --> 0:26:55.959
<v Speaker 10>they are exploring. Remember, they have invested a lot of

0:26:56.000 --> 0:26:59.920
<v Speaker 10>money in the augmented reality virtual reality glasses they are

0:27:00.280 --> 0:27:02.240
<v Speaker 10>They have been working on that over the last four years.

0:27:02.280 --> 0:27:05.040
<v Speaker 10>There has been a reset in that and now probably

0:27:05.040 --> 0:27:07.399
<v Speaker 10>we are not now looking at twenty twenty seven for

0:27:07.520 --> 0:27:10.919
<v Speaker 10>the actual launch, So there is a timetable to build

0:27:11.000 --> 0:27:14.200
<v Speaker 10>AI within those glasses. I believe that's going to take

0:27:14.240 --> 0:27:17.400
<v Speaker 10>up a lot of money. And second, integrating the three

0:27:17.440 --> 0:27:20.120
<v Speaker 10>apps that they have, and those are the three largest

0:27:20.160 --> 0:27:23.240
<v Speaker 10>mobile apps in the world with billions of people using

0:27:23.280 --> 0:27:26.679
<v Speaker 10>on a daily basis. To make those apps super intelligent

0:27:26.760 --> 0:27:30.160
<v Speaker 10>and to make them extremely sticky is probably a monumental

0:27:30.200 --> 0:27:35.400
<v Speaker 10>investment opportunity for them. So these two are orthogonal investment opportunities,

0:27:35.400 --> 0:27:39.760
<v Speaker 10>but I think both are probably going to be something

0:27:39.760 --> 0:27:42.480
<v Speaker 10>that Zuckerberg is going to be fully invested in.

0:27:43.240 --> 0:27:47.479
<v Speaker 2>At one point eight seven trillion dollars, is that a

0:27:47.600 --> 0:27:50.680
<v Speaker 2>full valuation for this full investment theme.

0:27:50.480 --> 0:27:55.360
<v Speaker 10>That you have ro head, I believe, like the layers

0:27:55.600 --> 0:27:59.399
<v Speaker 10>unpacking in the future, it's just going to be something

0:27:59.440 --> 0:28:00.840
<v Speaker 10>that we are going to be excited about.

0:28:00.880 --> 0:28:01.560
<v Speaker 4>I feel we are.

0:28:02.440 --> 0:28:04.280
<v Speaker 10>We have still not yet scratched the surface of the

0:28:04.320 --> 0:28:07.960
<v Speaker 10>potential of jen Ai on a very large, multi dimensional

0:28:07.960 --> 0:28:13.399
<v Speaker 10>platform like Meta, and I feel Zuckerberg has the founder

0:28:13.440 --> 0:28:17.240
<v Speaker 10>whip if you feel he's investing behind this as if

0:28:17.280 --> 0:28:21.400
<v Speaker 10>it's an existential, once in a lifetime opportunity, even bigger

0:28:21.440 --> 0:28:26.120
<v Speaker 10>than when iPhone was launched. So I feel the excitement

0:28:26.480 --> 0:28:30.520
<v Speaker 10>and the kind of attitude that they can disrupt the

0:28:31.000 --> 0:28:34.919
<v Speaker 10>Apple card while redoing something new is something that the

0:28:35.000 --> 0:28:38.640
<v Speaker 10>investors are willing to be patient around on Metasta, and

0:28:38.720 --> 0:28:39.200
<v Speaker 10>so are we.

0:28:39.680 --> 0:28:42.560
<v Speaker 2>Your patient is still got a buy rating. Compare and

0:28:42.600 --> 0:28:44.720
<v Speaker 2>contrast to some of the other key companies that you

0:28:44.800 --> 0:28:47.280
<v Speaker 2>do analyze. When I'm thinking that, you're looking at Alphabet

0:28:47.280 --> 0:28:50.480
<v Speaker 2>and Amazon and they as bigger winners. Have they been

0:28:50.520 --> 0:28:52.880
<v Speaker 2>as bigger winners in the capex? They've already spent and

0:28:52.920 --> 0:28:55.640
<v Speaker 2>do they have as good a road map as you

0:28:55.720 --> 0:28:56.960
<v Speaker 2>currently articulate for Meta?

0:28:58.440 --> 0:29:00.959
<v Speaker 4>So far, I think Meta is the clear winner.

0:29:01.360 --> 0:29:05.360
<v Speaker 10>Amazon is so far probably a number three, and Google

0:29:05.400 --> 0:29:08.400
<v Speaker 10>is a number two player, number two winner as far

0:29:08.440 --> 0:29:14.640
<v Speaker 10>as demonstrating returns on GENEI investments. Having said that, I

0:29:14.680 --> 0:29:18.640
<v Speaker 10>think the complex problems that each of these very large,

0:29:18.640 --> 0:29:22.440
<v Speaker 10>massive companies are solving or trying to solve using AI

0:29:23.480 --> 0:29:27.400
<v Speaker 10>are essentially compounding with every day, and that is leading

0:29:27.400 --> 0:29:31.480
<v Speaker 10>to more investment and more investment needed to solve those problems.

0:29:31.640 --> 0:29:37.200
<v Speaker 10>Think of the multi dimensional e commerce, cloud, advertising, prime video,

0:29:37.360 --> 0:29:38.360
<v Speaker 10>same day delivery.

0:29:38.800 --> 0:29:40.560
<v Speaker 4>All of these elements.

0:29:40.120 --> 0:29:43.440
<v Speaker 10>Can be optimized using AI, and at any given time,

0:29:43.480 --> 0:29:44.600
<v Speaker 10>probably Amazon.

0:29:44.280 --> 0:29:46.040
<v Speaker 4>Is focused on maybe one or two of those.

0:29:46.120 --> 0:29:50.760
<v Speaker 10>So I feel over the longer arc, the bigger winner

0:29:50.800 --> 0:29:53.080
<v Speaker 10>is probably going to be a company like Amazon.

0:29:53.200 --> 0:29:54.960
<v Speaker 4>Given the surface area of improvement.

0:29:55.040 --> 0:29:59.560
<v Speaker 10>They have the potential, but in the near term probably

0:29:59.560 --> 0:30:03.680
<v Speaker 10>a one pony like a Facebook, has executed better in

0:30:03.720 --> 0:30:07.120
<v Speaker 10>the last eighteen months, and they are demonstrating better returns today.

0:30:07.840 --> 0:30:09.960
<v Speaker 2>I hate to talk about the near term because I

0:30:09.960 --> 0:30:11.720
<v Speaker 2>know you're a man who likes to give longer term

0:30:11.760 --> 0:30:14.080
<v Speaker 2>projections and price targets. But when you're seeing a sell

0:30:14.120 --> 0:30:15.880
<v Speaker 2>off like we've had after the last couple of days,

0:30:16.120 --> 0:30:18.680
<v Speaker 2>a lot of it tied up with worries about ROAI

0:30:18.880 --> 0:30:21.720
<v Speaker 2>and the report coming out of MIT, the GENAI divide,

0:30:21.760 --> 0:30:25.040
<v Speaker 2>and the state of AI and business. Do you give

0:30:25.040 --> 0:30:27.240
<v Speaker 2>credence to that? Do you think there's a lack of

0:30:27.280 --> 0:30:29.040
<v Speaker 2>nuance or do you think actually we should be worried

0:30:29.080 --> 0:30:31.400
<v Speaker 2>about how much we're investing in the returns on it.

0:30:33.160 --> 0:30:34.520
<v Speaker 4>I think there are two ways to.

0:30:36.000 --> 0:30:39.720
<v Speaker 10>Interpret miit and just the overall questions that are being

0:30:39.800 --> 0:30:44.080
<v Speaker 10>raised that hey, by the way we applied Genni algorithms llms,

0:30:44.120 --> 0:30:46.280
<v Speaker 10>we invested so much, but we are not getting the

0:30:46.320 --> 0:30:50.320
<v Speaker 10>returns as much as we wanted. I think these large

0:30:50.360 --> 0:30:54.960
<v Speaker 10>companies are trying to solve really large problems. The efficiency

0:30:54.960 --> 0:30:57.360
<v Speaker 10>gains that they will provide over the next twelve months

0:30:57.400 --> 0:31:00.560
<v Speaker 10>are something that we are very confident on whether that

0:31:00.600 --> 0:31:04.479
<v Speaker 10>translates into revenue uplift that remains to be seen only

0:31:05.120 --> 0:31:08.600
<v Speaker 10>a company like Meta has demonstrated that other guys are

0:31:08.920 --> 0:31:13.440
<v Speaker 10>kind of TVD. That's why from AI winner standpoint, Meta

0:31:13.520 --> 0:31:15.960
<v Speaker 10>is the one to buy on this weakness today.

0:31:16.520 --> 0:31:18.960
<v Speaker 2>Right here, Kolk Carney, Managing director and Senior analyst at

0:31:19.000 --> 0:31:21.200
<v Speaker 2>Growth Capital Partners, it's great to catch up with you.

0:31:22.160 --> 0:31:24.000
<v Speaker 2>This is Bloomberg Tech and you're looking at a live

0:31:24.000 --> 0:31:27.000
<v Speaker 2>shot of the principal room. Bloomberg is live at Jackson

0:31:27.000 --> 0:31:29.920
<v Speaker 2>Hole this week. Tune in a continuing coverage leading up

0:31:29.920 --> 0:31:33.120
<v Speaker 2>to a special episode of Bloomberg Surveilience on Friday. This

0:31:33.320 --> 0:31:45.720
<v Speaker 2>is Bloomberg. Elisei, which ultimates complex healthcare housing systems, has

0:31:45.800 --> 0:31:48.000
<v Speaker 2>just announced a two hundred and fifty million dollars Series

0:31:48.080 --> 0:31:51.320
<v Speaker 2>E round led by Andrews and Horowitz. The startup, which

0:31:51.400 --> 0:31:53.920
<v Speaker 2>was founded back in twenty seventeen, off is Conversational AI,

0:31:54.200 --> 0:31:56.480
<v Speaker 2>a platform for users. And I'm pleased to say that

0:31:56.560 --> 0:31:59.600
<v Speaker 2>the CEO and founder and Lisa Mina Song is here

0:31:59.640 --> 0:32:02.400
<v Speaker 2>with me. You're based in New York and just how

0:32:02.560 --> 0:32:05.640
<v Speaker 2>was it raising these funds? How quickly are you able

0:32:05.720 --> 0:32:07.200
<v Speaker 2>to raise such an enormous amount of money?

0:32:07.960 --> 0:32:08.960
<v Speaker 11>Thank you for having me.

0:32:09.240 --> 0:32:11.840
<v Speaker 12>It was pretty quick actually to raise the round of funding.

0:32:11.880 --> 0:32:15.720
<v Speaker 12>I think investors are incredibly excited about investing in vertical AI,

0:32:15.920 --> 0:32:20.760
<v Speaker 12>which is AI that solves specific problems for specific industries,

0:32:20.800 --> 0:32:24.360
<v Speaker 12>which is exactly what we do, particularly focused in the

0:32:24.440 --> 0:32:25.840
<v Speaker 12>housing and healthcare industries.

0:32:26.040 --> 0:32:28.600
<v Speaker 2>And why those particular industries. Was it just the pain

0:32:29.200 --> 0:32:31.240
<v Speaker 2>points were just so obvious and glaring to you.

0:32:31.800 --> 0:32:34.240
<v Speaker 12>I think so it's pretty obvious to all of us

0:32:34.320 --> 0:32:38.320
<v Speaker 12>how inefficient and how limited the technology is when we

0:32:38.400 --> 0:32:41.120
<v Speaker 12>interact with these industries. But the core mission of the

0:32:41.200 --> 0:32:45.520
<v Speaker 12>company has always been to develop advanced technology for industries

0:32:45.560 --> 0:32:47.000
<v Speaker 12>that serve fundamental human needs.

0:32:47.040 --> 0:32:48.360
<v Speaker 11>So housing and healthcare are some of the.

0:32:48.400 --> 0:32:52.120
<v Speaker 12>Most important decisions we make and the important, most basic

0:32:52.200 --> 0:32:53.360
<v Speaker 12>needs that we have as humans.

0:32:53.520 --> 0:32:55.040
<v Speaker 2>So the way in which the business works is you're

0:32:55.240 --> 0:32:58.080
<v Speaker 2>selling your conversational AI in a B to B manner,

0:32:58.120 --> 0:33:00.360
<v Speaker 2>but then it's me that ends up experience it as

0:33:00.400 --> 0:33:05.880
<v Speaker 2>a consumer. How have you seen healthcare institutions, housing institutions

0:33:06.000 --> 0:33:09.360
<v Speaker 2>willingness to just these sorts of products thus far?

0:33:10.040 --> 0:33:12.920
<v Speaker 12>Yeah, they're extremely excited to use it. So we serve

0:33:13.240 --> 0:33:15.840
<v Speaker 12>on the housing side, One in every eight apartments in

0:33:15.920 --> 0:33:19.400
<v Speaker 12>the US today are using our AI software and they

0:33:19.600 --> 0:33:24.280
<v Speaker 12>we're using AI to automate manual processes to make operations

0:33:24.320 --> 0:33:26.960
<v Speaker 12>more efficient and to make them more cost effective. And

0:33:27.080 --> 0:33:30.120
<v Speaker 12>these inefficiencies really affect all of us. When an industry

0:33:30.560 --> 0:33:35.560
<v Speaker 12>is inefficient, then those that drives up costs for owners,

0:33:35.680 --> 0:33:38.960
<v Speaker 12>which ultimately trickles down to renters, which is really important

0:33:39.440 --> 0:33:41.680
<v Speaker 12>and really affects all of our lives. So there's a

0:33:41.720 --> 0:33:42.840
<v Speaker 12>lot of excitement about AI.

0:33:43.080 --> 0:33:45.680
<v Speaker 2>Okay, And so with the money you do want.

0:33:46.360 --> 0:33:48.160
<v Speaker 12>A significant amount of the funds are going to be

0:33:48.440 --> 0:33:51.640
<v Speaker 12>going to expanding our teams, so a lot of engineering

0:33:51.720 --> 0:33:56.440
<v Speaker 12>team members, product team members, research operations and more. We're

0:33:56.440 --> 0:33:59.840
<v Speaker 12>expanding our offices in New York City, San Francisco, Chicago,

0:34:00.080 --> 0:34:03.080
<v Speaker 12>in Boston. So we're looking for people who want to

0:34:03.120 --> 0:34:06.000
<v Speaker 12>have real world impact and solve really important problems that

0:34:06.160 --> 0:34:07.640
<v Speaker 12>impact millions of people's lives.

0:34:07.880 --> 0:34:10.560
<v Speaker 2>We've talked a lot about talent wars and how expensive

0:34:11.120 --> 0:34:14.400
<v Speaker 2>certain researches have become. Is it the mission that therefore

0:34:14.440 --> 0:34:17.879
<v Speaker 2>attracts them or have you got to up the paycheck significantly?

0:34:17.920 --> 0:34:18.400
<v Speaker 2>And indeed, the.

0:34:18.400 --> 0:34:21.600
<v Speaker 12>Reward of equity absolutely the mission. I think people who

0:34:21.680 --> 0:34:26.160
<v Speaker 12>want to apply these great advancements in artificial intelligence, but

0:34:26.280 --> 0:34:28.680
<v Speaker 12>want to see that that has real world impact and

0:34:28.760 --> 0:34:31.920
<v Speaker 12>that it can affect all of us is what attracts

0:34:31.960 --> 0:34:33.359
<v Speaker 12>people to working at alys Ai.

0:34:34.040 --> 0:34:38.360
<v Speaker 2>How do you tend to offer when you think about packages.

0:34:38.560 --> 0:34:40.720
<v Speaker 2>Are people coming on board wanting to see a roadmap

0:34:40.760 --> 0:34:42.120
<v Speaker 2>for you to go public? I mean you're already a

0:34:42.200 --> 0:34:43.080
<v Speaker 2>series stage.

0:34:43.800 --> 0:34:47.920
<v Speaker 12>We're focused on building a generational company. That's what's really

0:34:47.960 --> 0:34:50.440
<v Speaker 12>important to us. We want to change the face of

0:34:50.560 --> 0:34:52.719
<v Speaker 12>housing and healthcare and want people to look back on

0:34:52.840 --> 0:34:55.520
<v Speaker 12>it and say, I can't imagine what it was like

0:34:55.680 --> 0:34:59.360
<v Speaker 12>back when all of these services were so expensive expensive?

0:35:00.120 --> 0:35:00.719
<v Speaker 11>Were they like that?

0:35:00.960 --> 0:35:03.320
<v Speaker 12>And people who are joining want to be part of

0:35:03.360 --> 0:35:04.400
<v Speaker 12>making that change happen.

0:35:04.640 --> 0:35:07.080
<v Speaker 2>How do you calm any anxiety that you're not going

0:35:07.160 --> 0:35:08.960
<v Speaker 2>to do a wind surf, You're not going to do

0:35:09.480 --> 0:35:12.200
<v Speaker 2>suddenly a big purchase where you, as the founder get

0:35:12.280 --> 0:35:16.279
<v Speaker 2>lifted Alexander Wang style but leave others behind. How do

0:35:16.320 --> 0:35:18.759
<v Speaker 2>you ensure that this idea that you take the team

0:35:18.840 --> 0:35:20.200
<v Speaker 2>with you remains resilient.

0:35:20.600 --> 0:35:22.480
<v Speaker 12>I think we've been through and through dedicated to the

0:35:22.520 --> 0:35:25.320
<v Speaker 12>mission of the company, and there's so much more that

0:35:25.560 --> 0:35:27.080
<v Speaker 12>we all want to be a part of. To make

0:35:27.120 --> 0:35:30.840
<v Speaker 12>this happen and it's a really exciting journey to be on.

0:35:31.120 --> 0:35:33.880
<v Speaker 2>We have no plans to do that well. Thus far,

0:35:34.000 --> 0:35:35.640
<v Speaker 2>it seems as though the clients have loved you and

0:35:35.760 --> 0:35:38.480
<v Speaker 2>speak very highly about the impact that your technology is

0:35:38.520 --> 0:35:42.000
<v Speaker 2>having serving people in healthcare, people in housing. Mina Song,

0:35:42.080 --> 0:35:43.640
<v Speaker 2>founder and CEO of Elise AI.

0:35:43.840 --> 0:35:45.480
<v Speaker 5>On that fundraise, we can gractually done.

0:35:45.560 --> 0:35:49.200
<v Speaker 2>Meanwhile, soaring valuations are coming from the likes also of

0:35:49.600 --> 0:35:53.279
<v Speaker 2>the major foundational models think open Ai, think Anthropic, but

0:35:53.360 --> 0:35:56.600
<v Speaker 2>also data bricks. They've also been boosting, but they're creating

0:35:56.600 --> 0:35:58.239
<v Speaker 2>perhaps a bit of a full sense of strength among

0:35:58.280 --> 0:36:00.920
<v Speaker 2>the VC markets. In reality, only the top one percent

0:36:00.960 --> 0:36:03.360
<v Speaker 2>of companies are pulling in the majority of capital, and

0:36:03.440 --> 0:36:05.799
<v Speaker 2>now more investors are beginning to worry about the health

0:36:05.840 --> 0:36:08.279
<v Speaker 2>of the young Silicon Valley startups who most k Clark

0:36:08.400 --> 0:36:11.400
<v Speaker 2>joins us for more And really you've been uncovering, as

0:36:11.480 --> 0:36:14.160
<v Speaker 2>you always do within tech and venture capital. That's some

0:36:14.239 --> 0:36:17.719
<v Speaker 2>of the trends. So these big whopping valuations cover up

0:36:17.719 --> 0:36:18.359
<v Speaker 2>a dark side.

0:36:19.160 --> 0:36:21.440
<v Speaker 11>Yeah, there's a tale of two markets and venture capital.

0:36:21.520 --> 0:36:21.759
<v Speaker 13>Right now.

0:36:21.920 --> 0:36:25.759
<v Speaker 11>You have the AI mega companies Open ai Andthropic, Deta

0:36:25.840 --> 0:36:30.000
<v Speaker 11>Bricks raising rounds in what feels like in a monthly cadence.

0:36:30.160 --> 0:36:32.040
<v Speaker 11>And then you have all of the other startups and

0:36:32.200 --> 0:36:35.440
<v Speaker 11>many of them are actually struggling or even raising down rounds.

0:36:36.160 --> 0:36:38.279
<v Speaker 2>So who are those types of startups because we just

0:36:38.320 --> 0:36:40.040
<v Speaker 2>had a lease AI on these very two hundred and

0:36:40.040 --> 0:36:43.720
<v Speaker 2>fifty million, relatively young startup and actually managing to well raise.

0:36:44.120 --> 0:36:46.400
<v Speaker 2>But who are those who have been left behind, particularly

0:36:46.400 --> 0:36:48.160
<v Speaker 2>those peraps who did well in twenty twenty one and

0:36:48.200 --> 0:36:49.560
<v Speaker 2>don't really want to admit that they're going to have

0:36:49.600 --> 0:36:50.360
<v Speaker 2>to face a downroute.

0:36:50.400 --> 0:36:52.080
<v Speaker 11>I mean, it's exactly companies like that. A lot of

0:36:52.120 --> 0:36:54.400
<v Speaker 11>the unicorns that were minted in twenty twenty one, a

0:36:54.480 --> 0:36:57.160
<v Speaker 11>lot of the companies that were founded before twenty twenty one.

0:36:57.520 --> 0:36:59.640
<v Speaker 11>The vcs like to call these sort of the non

0:36:59.760 --> 0:37:02.680
<v Speaker 11>A native companies that are maybe trying to catch up,

0:37:02.800 --> 0:37:05.480
<v Speaker 11>trying to incorporate AI, but really they were They were

0:37:05.520 --> 0:37:09.000
<v Speaker 11>born before chat GPT, born before CHATCHAPT.

0:37:09.160 --> 0:37:10.520
<v Speaker 2>Some of them have made the pivot, like I think

0:37:10.520 --> 0:37:13.480
<v Speaker 2>of a Figma, for example, managed then IPO at evaluation

0:37:13.560 --> 0:37:15.480
<v Speaker 2>that they were previously going to be bought at, and

0:37:15.880 --> 0:37:18.520
<v Speaker 2>people have really managed to think of them as generative

0:37:18.560 --> 0:37:21.000
<v Speaker 2>AI business even though they've integrated it as they grew.

0:37:21.880 --> 0:37:24.600
<v Speaker 2>Where are some of the pitfalls? Where are the industry

0:37:24.680 --> 0:37:26.440
<v Speaker 2>exposures that we're not liking right now?

0:37:27.280 --> 0:37:30.560
<v Speaker 11>I mean, I think you have to look at e commerce, fintech, cryptocurrency.

0:37:30.560 --> 0:37:32.400
<v Speaker 11>There are many areas in which investors are not as

0:37:32.440 --> 0:37:35.040
<v Speaker 11>excited because they don't see how generative AI can really

0:37:35.080 --> 0:37:38.200
<v Speaker 11>help that business. I think, though, the main point of

0:37:38.280 --> 0:37:42.000
<v Speaker 11>weakness are the companies that raise at extremely high valuations

0:37:42.080 --> 0:37:44.680
<v Speaker 11>during the last hype cycle, and investors now just don't

0:37:44.719 --> 0:37:47.120
<v Speaker 11>see a path to allowing them to raise money at

0:37:47.160 --> 0:37:49.600
<v Speaker 11>an even higher price. So those companies are kind of

0:37:49.719 --> 0:37:53.440
<v Speaker 11>becoming what again VCS call like zombie unicorns and are

0:37:53.520 --> 0:37:55.919
<v Speaker 11>just sort of slowly, slowly dying.

0:37:56.640 --> 0:37:58.800
<v Speaker 2>Will they be allowed to die? Will they be forced

0:37:58.840 --> 0:37:59.520
<v Speaker 2>to consolidate?

0:37:59.640 --> 0:37:59.959
<v Speaker 5>What happen?

0:38:00.800 --> 0:38:02.719
<v Speaker 11>I think there'll be some consolidation, But I do think

0:38:02.760 --> 0:38:05.920
<v Speaker 11>you'll you'll sadly see a lot of just companies quietly

0:38:06.600 --> 0:38:09.839
<v Speaker 11>disappearing and slowly dying over time. But of course there'll

0:38:09.840 --> 0:38:11.600
<v Speaker 11>be M and A, and of course there will be winners.

0:38:11.640 --> 0:38:14.320
<v Speaker 11>There will be companies like Figma and many others that

0:38:15.000 --> 0:38:17.840
<v Speaker 11>were born pre CHATDPT and still find success.

0:38:18.120 --> 0:38:20.080
<v Speaker 5>And you'll be there to document it. Okay, comeup, we

0:38:20.200 --> 0:38:20.759
<v Speaker 5>appreciate it.

0:38:26.800 --> 0:38:29.560
<v Speaker 2>Google. Well, it's set to show off new Pixel hardware

0:38:29.640 --> 0:38:32.840
<v Speaker 2>later today and it's made by Google. Event just bringing

0:38:32.880 --> 0:38:35.840
<v Speaker 2>man leap Sing who has technearch of Bloomberg Intelligence and

0:38:35.960 --> 0:38:39.800
<v Speaker 2>talk about well, how important is the hardware for Alphabet

0:38:39.920 --> 0:38:40.880
<v Speaker 2>parent company of Google.

0:38:41.160 --> 0:38:44.440
<v Speaker 13>I mean everyone realizes Google has an advantage on the

0:38:44.520 --> 0:38:49.520
<v Speaker 13>custom chip side because of their TPUs. I think that's

0:38:49.560 --> 0:38:52.600
<v Speaker 13>going to show up in repeatedly, like they release Pixel

0:38:52.640 --> 0:38:55.280
<v Speaker 13>every year, so you will see a much better Pixel

0:38:55.400 --> 0:38:59.080
<v Speaker 13>version that can run LLLMS natively. That's the one thing

0:38:59.200 --> 0:39:02.200
<v Speaker 13>everyone wants Apple to do. I think Google is already

0:39:02.280 --> 0:39:05.400
<v Speaker 13>doing that obviously on device l LAMS is not that

0:39:05.560 --> 0:39:09.720
<v Speaker 13>big off an opportunity right now. But look, whatever people

0:39:10.440 --> 0:39:14.440
<v Speaker 13>think in terms of AI agents, to me, AI agent

0:39:14.560 --> 0:39:18.480
<v Speaker 13>opportunity will come through on device l LAMS and yes

0:39:18.600 --> 0:39:23.440
<v Speaker 13>there will be apps that run AI. LLMS browser is

0:39:23.560 --> 0:39:25.680
<v Speaker 13>very important. I mean, in the case of Google, they

0:39:25.760 --> 0:39:30.040
<v Speaker 13>have the Chrome browser for now now and then layering

0:39:30.280 --> 0:39:33.320
<v Speaker 13>it on operating system I think gives them a unique

0:39:33.320 --> 0:39:36.239
<v Speaker 13>advantage along with the chips. So that's what I feel

0:39:36.280 --> 0:39:37.640
<v Speaker 13>they will emphasize at the event.

0:39:38.080 --> 0:39:41.000
<v Speaker 2>This asset is incredibly useful to them and really only

0:39:41.120 --> 0:39:43.080
<v Speaker 2>useful to them and will wither and die on the

0:39:43.160 --> 0:39:46.160
<v Speaker 2>vine if sold to another. But compare and contrast how

0:39:46.520 --> 0:39:48.920
<v Speaker 2>important it is to show off it within their hardware.

0:39:49.360 --> 0:39:52.200
<v Speaker 2>That's to say, a Samsung which was also infused with

0:39:52.320 --> 0:39:53.000
<v Speaker 2>Gemini too.

0:39:53.440 --> 0:39:56.520
<v Speaker 13>Yeah, and look, Android operating system is used by a

0:39:56.600 --> 0:39:59.919
<v Speaker 13>lot of other OEMs. So from that perspective, what Google

0:40:00.080 --> 0:40:04.480
<v Speaker 13>has done well is to showcase AI capabilities on all

0:40:04.680 --> 0:40:08.239
<v Speaker 13>kinds of hardware. I mean, even the earbuds that they

0:40:08.280 --> 0:40:11.320
<v Speaker 13>will showcase I expect at the event will have some

0:40:11.719 --> 0:40:15.319
<v Speaker 13>integration of AI into variables because that's what they want

0:40:15.400 --> 0:40:18.160
<v Speaker 13>to show. At the end of the day. Your llms

0:40:18.280 --> 0:40:21.920
<v Speaker 13>right now will be distilled into smaller versions that can

0:40:22.040 --> 0:40:26.040
<v Speaker 13>do intelligent tasks, whether it's scheduling or voice assistance. And

0:40:26.160 --> 0:40:29.200
<v Speaker 13>that's where Google has a unique advantage because it has

0:40:29.280 --> 0:40:32.279
<v Speaker 13>the chips, it has the LLM, it has all the data,

0:40:32.600 --> 0:40:34.800
<v Speaker 13>and it has the family of apps with you know,

0:40:34.880 --> 0:40:37.960
<v Speaker 13>over two billion plus users, and that is why it

0:40:38.080 --> 0:40:41.880
<v Speaker 13>knows so much that it can do personalized AI that

0:40:42.120 --> 0:40:44.279
<v Speaker 13>others can. So to my mind, they are in a

0:40:44.400 --> 0:40:47.200
<v Speaker 13>unique position. Obviously, they have a small market share when

0:40:47.239 --> 0:40:51.160
<v Speaker 13>it comes to smartphones, but they're doing enough to showcase

0:40:51.360 --> 0:40:55.200
<v Speaker 13>that embedded AI element which could potentially drive up their

0:40:55.280 --> 0:40:57.279
<v Speaker 13>share when it comes to the hardware side.

0:40:57.440 --> 0:41:00.360
<v Speaker 2>Yeah, briefly, how much could they steal from a cluster

0:41:00.480 --> 0:41:01.440
<v Speaker 2>theory offering.

0:41:01.880 --> 0:41:04.840
<v Speaker 13>Well, I mean, look, Apple has their problems. They have

0:41:05.000 --> 0:41:07.680
<v Speaker 13>to figure out a way to integrate llms, whether through

0:41:07.760 --> 0:41:10.520
<v Speaker 13>partnerships or through their own I think it will be

0:41:10.600 --> 0:41:13.440
<v Speaker 13>through partnerships. In the case of Google, they will use

0:41:13.560 --> 0:41:16.480
<v Speaker 13>all the OEMs, so really the advancements will be at

0:41:16.520 --> 0:41:19.040
<v Speaker 13>the operating system later, but they have to showcase that

0:41:19.200 --> 0:41:22.120
<v Speaker 13>in their own hardware first. So that's why this event

0:41:22.239 --> 0:41:23.000
<v Speaker 13>is quite important.

0:41:23.320 --> 0:41:25.640
<v Speaker 2>So too is as we wait in anticipation of Judge

0:41:25.719 --> 0:41:28.319
<v Speaker 2>Metas ruling on whether or not they're able to keep

0:41:28.400 --> 0:41:31.239
<v Speaker 2>Chrome as well. Bloombig Intelligence man Deep saying we love

0:41:31.320 --> 0:41:33.840
<v Speaker 2>having him as always as we anticipate some of that

0:41:33.920 --> 0:41:36.279
<v Speaker 2>hardware coming out. But that does it for this edition

0:41:36.400 --> 0:41:39.439
<v Speaker 2>a Bloomberg Tech. One last check on these markets before

0:41:39.440 --> 0:41:41.960
<v Speaker 2>we leave, because it's been a volatile hour of trading

0:41:42.120 --> 0:41:43.719
<v Speaker 2>during the show. We're off by one and a quarter

0:41:43.760 --> 0:41:46.360
<v Speaker 2>percent on then astat one hundred socks is feeling the

0:41:46.400 --> 0:41:48.680
<v Speaker 2>pain and video is down significantly. We're off by two

0:41:48.760 --> 0:41:52.200
<v Speaker 2>percent on the Semiconductor Index scrypto though turning back into

0:41:52.280 --> 0:41:54.719
<v Speaker 2>the red. There is risk and anxiety building about some

0:41:54.800 --> 0:41:57.479
<v Speaker 2>of the valuations in the market. We see some profit taking.

0:41:58.000 --> 0:42:00.160
<v Speaker 2>Don't forget, though, to check out our podcast. You can

0:42:00.200 --> 0:42:01.759
<v Speaker 2>find it on the terminal as well as you do

0:42:02.000 --> 0:42:05.840
<v Speaker 2>online on Apple, Spotify, and iHeart from New York. This

0:42:05.960 --> 0:42:06.799
<v Speaker 2>is Boomberg Tech.

0:42:08.120 --> 0:42:21.240
<v Speaker 6>Mm hmmm mm hmmmmmmmmmmmmmmmm