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Speaker 1: From Mahard where Innovation, money and power collie in Silicon Valley, NBN.

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Speaker 2: This is Bloomberg Technology with Caroline Hyde and Ed Ludlove.

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Speaker 3: I'm Caroline Hyde at Bloomberg's world headquarters in New York.

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Speaker 4: I'm Ed Lovelow in San Francisco. This is Bloomberg Technology

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Speaker 4: coming up.

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Speaker 3: Microsoft to invest one and a half billion dollars in

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Speaker 3: a UAE top AI firm.

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Speaker 5: It's G forty two.

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Speaker 3: That's the US government pushes the Abu Dhabi business to

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Speaker 3: end all cooperation with China. We analyze the business and

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Speaker 3: the political drivers.

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Speaker 4: Europe has its eye on fintech and crypto. We sit

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Speaker 4: down with the EU's Commissioner for Financial Services on her

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Speaker 4: visit to Silicon Valley. Is ais all the rage in

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Speaker 4: bank earnings, and.

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Speaker 3: We digest a two hundred and fifty million dollar fundraise

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Speaker 3: for a Silicon Valley chip developer, Revos, which is yet

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Speaker 3: to bring about its first product. We discussed the race

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Speaker 3: for AI infrastructure and so much more. Throughout this hour,

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Speaker 3: we focus, though, just on the public markets, which in

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Speaker 3: the United States relatively sanguine right now, and the NASDAC

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Speaker 3: is off just by about.

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Speaker 5: A quarter of a percent.

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Speaker 3: The action is actually what's happening in Asia and Europe,

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Speaker 3: trading both those benchmarks under a lot of pressure following

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Speaker 3: some sell off that we've seen in the US. But

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Speaker 3: really what's been happening also in the bond market, yields

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Speaker 3: up three basis points on a two year yield that

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Speaker 3: at one point was very close to the five percent level.

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Speaker 5: We're all eyes on j Powell what.

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Speaker 3: He sees for the future of FED policy when we've

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Speaker 3: still got such a resilient US economy and inflatory pressures.

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Speaker 3: Moving on, have a look at what's happening in the

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Speaker 3: world of as a dollar that rises for five straight

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Speaker 3: days and having the best run in at least a year.

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Speaker 3: The bitcoin on the flip side versus the US dollar

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Speaker 3: is down one point seven percent. We're at sixty two

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Speaker 3: thousand dollars, so there's still some risk aversion in this

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Speaker 3: market ed when it comes to certain risk assets.

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Speaker 5: Well, looking in on the micro I'm.

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Speaker 4: Continuing to look at Tesla. This is a two day chart,

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Speaker 4: the stockdown and another four percent. We broke the news

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Speaker 4: yesterday that the job cuts at Tesla will be nearer

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Speaker 4: to twenty percent. Elon Musk's memo said more than ten percent.

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Speaker 4: We also broke the story that Drew Baglino, an eighteen

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Speaker 4: year veteran and one of four named executives, had resigned.

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Speaker 4: He then confirmed it on social media. The milestone is

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Speaker 4: that Tesla's now below five hundred billion dollars of market cap.

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Speaker 4: There's a lot of questions we're going to ask some

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Speaker 4: of them throughout this week, throughout this quarter about what

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Speaker 4: comes next for the ev name. Also looking at Microsoft

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Speaker 4: up half a percentage point, had a slow start to

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Speaker 4: the session. The headline on news is the one point

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Speaker 4: five billion dollar investment in G forty two.

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Speaker 6: There's a backstory which.

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Speaker 4: Is, you know, I've been looking into for a few months.

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Speaker 4: G forty two really likes what Sam Outman and OpenAI

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Speaker 4: are doing. I think they want a piece of that.

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Speaker 4: They now have a relationship with Microsoft. I wonder if

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Speaker 4: that helps. And the backstory is a political one as well,

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Speaker 4: that G forty two is now safe for a US

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Speaker 4: company to invest in. It's very complicated, but it's an

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Speaker 4: we're going to hear.

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Speaker 5: More and more about, certainly, and let's get straight to it.

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Speaker 3: Microsoft and the deal Blue Magatinea Bass you come of

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Speaker 3: this of course with the Microsoft expertise covering all things

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Speaker 3: of that business. But just take a step back, I mean,

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Speaker 3: what had to happen first? What led to the divestment

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Speaker 3: of China to move away from China?

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Speaker 7: Sure, so, what a bunch of Bloomberg reporters in Doting

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Speaker 7: and some of my other colleagues has been tracking for

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Speaker 7: a while is that there have been is behind the

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Speaker 7: scenes secret talks between the US government and G forty two,

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Speaker 7: And what we reported last night is that that resulted

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Speaker 7: in kind of a secret pack that was reached in

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Speaker 7: which G forty two agreed to divest from China.

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Speaker 8: Remember.

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Speaker 7: G forty two was under a lot of criticism from

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Speaker 7: US government from some members of Congress where its close

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Speaker 7: ties to some Chinese companies, including Parkway, and they were

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Speaker 7: under threat that they might not be able to continue

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Speaker 7: to have access to the key in video chips that

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Speaker 7: they need for their AI work. This kind of you know,

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Speaker 7: secret pack result of it and used the way to

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Speaker 7: this Microsoft deal.

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Speaker 4: Did I think it's worth explaining to our audience what

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Speaker 4: G forty two is. It's essentially an investment firm. But

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Speaker 4: in all the conversations I have G forty two comes

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Speaker 4: up a lot in the context of the Sam Outman

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Speaker 4: chip initiative. We've reported that, you know, Sam Outman has

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Speaker 4: met with G forty two, that G forty two wants

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Speaker 4: to give him lots of money, But I don't think

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Speaker 4: we've ever stopped and said, what's G forty two.

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Speaker 7: Sure, it's essentially, you know, the biggest AI company in

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Speaker 7: that region, in the UAE and large parts of that.

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Speaker 9: Part of the world.

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Speaker 7: It's a wholding company that's focused on AI, but it

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Speaker 7: has its hands in a lot of different parts of AI.

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Speaker 7: There's significant healthcare initiatives than talking on in artificial intelligence.

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Speaker 7: For Microsoft, this is a multi stage deal and they

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Speaker 7: want to take advantage of several parts of what G

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Speaker 7: forty two offers them, including Microsoft President Brent Smith told

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Speaker 7: us yesterday. In the later stage of the deal, they're

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Speaker 7: hoping to put Microsoft services in G forty Tuesday data

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Speaker 7: centers and use that as a way to access markets

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Speaker 7: in Central Asia and Africa where Microsoft doesn't really have

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Speaker 7: a presence and doesn't have its own data center. So

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Speaker 7: that's another role the G forty two plays, sort of,

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Speaker 7: you know, easing the speed of cloud and AI into

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Speaker 7: some of those regions where US companies don't really have access.

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Speaker 7: That's part of the reason why the Biden administration wanted

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Speaker 7: to make sure that it removed gboty two from the

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Speaker 7: Chinese sphere influence and you know, got closer to the

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Speaker 7: US techology companies in the US technology industry.

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Speaker 4: Bloomberg's Dina Bass one of the bylines on what is

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Speaker 4: one of the most read stories and important pieces of

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Speaker 4: reporting on Bloomberg this Tuesday.

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Speaker 6: We've had the reporting and the details. Let's get some.

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Speaker 4: More analysis and reaction with Dan Ives of Webbersion. Dan,

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Speaker 4: you know, you kind of cover this from Microsoft's perspective,

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Speaker 4: but you've written a few notes about the bigger picture

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Speaker 4: as well with what happening with open AI and AI

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Speaker 4: infrastructure build out. Just give us your kind of scorecard

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Speaker 4: on this Redmond UAE tie up.

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Speaker 9: Oh, I mean, this is a massive strategic bet.

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Speaker 10: It's another flex the muscle. It's for redmen and the

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Speaker 10: Dalla because really for G forty two, they had a

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Speaker 10: choice China or US and Redmen and you're gonna take

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Speaker 10: Microsoft every day of the week.

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Speaker 9: Right now along with Nvideo.

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Speaker 10: And for Microsoft, it's just another doubling it down.

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Speaker 9: They're playing chess. Others are playing checkers.

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Speaker 4: Then Microsoft is forming a lot of relationships with a

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Speaker 4: lot of different people. Are they just making sure they're

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Speaker 4: covered basically well look ed.

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Speaker 9: They know their way ahead. So what they're doing is

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Speaker 9: they're putting the.

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Speaker 10: Guardrails up really around the world Joinny blind Spot Middle

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Speaker 10: East being.

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Speaker 9: One of them.

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Speaker 10: They're gonna bet on the big Horus right here, and

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Speaker 10: they ultimately even had to invest the Chinese piece. Also

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Speaker 10: making sure that within the Beltway to or two area

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Speaker 10: could there's no issues there. So from Microsoft, this is

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Speaker 10: an example they're miles ahead. They're just further and further

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Speaker 10: gaining share from an AI perspective, given this AI revolution

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Speaker 10: where them all mean the golden child of AI resides Dan.

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Speaker 3: What's interesting is in this case US government played a

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Speaker 3: role in other areas. I think of just what happened

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Speaker 3: last week with the UK CMA worrying from a regulatory

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Speaker 3: perspective about certain key players having a web of relationships

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Speaker 3: and then crossing over too much in the world of AI.

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Speaker 3: Will this be regulated from a competition perspective?

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Speaker 10: Well, I think what Brad Smith knows it as well

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Speaker 10: as anyone. He's going to proactively in Microsoft make sure

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Speaker 10: US and Beltware are good with this because they don't

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Speaker 10: want all of a sudden a year eighteen months from

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Speaker 10: now this becomes a bigger issue. And they checked all

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Speaker 10: those boxes. The Chinese divestiture I think was important from

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Speaker 10: a G forty two perspective, and now it's a green

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Speaker 10: light going ahead at the same time where Amazon and

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Speaker 10: Google still trying to play catch up, and this is

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Speaker 10: Nedella just continuing to make aggressive bets and we'll see

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Speaker 10: it again earnings.

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Speaker 9: Where they continue to be the lead from an AI perspective.

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Speaker 3: Phenomenal game of chess, as we sort of referenced, And

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Speaker 3: what is on many players' minds right now is where

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Speaker 3: are the bottlenecks? Time and time again from Sam Altman

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Speaker 3: and many that it's to do with energy and it's

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Speaker 3: to do with access to AI infrastructure. Is that what

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Speaker 3: you hear from the leaders of these companies and how

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Speaker 3: much more investment and we likely to see to try

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Speaker 3: to see a solution globally for that.

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Speaker 10: Yeah, And I think ed now that when you was

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Speaker 10: talking about on the chip side, there's a two parter

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Speaker 10: here because I think this is ultimately going to lead

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Speaker 10: from a chip perspective to more and more investment from

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Speaker 10: Middle East towards some of the all men and chip

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Speaker 10: ventures that's now going on within Open AI and Microsoft.

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Speaker 10: Of course, energy continues to be the constraint, but use

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Speaker 10: cases are.

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Speaker 9: Exploding across the board.

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Speaker 10: And now this fourth industrial revolutions here being led by

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Speaker 10: the Dell and of course the godfather of AI, Jensen

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Speaker 10: Na Vidio.

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Speaker 3: I love having the perspective Dan Ives, who can make

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Speaker 3: it a global conversation.

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Speaker 5: We thank you for web Bush.

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Speaker 3: Meanwhile, let's just go to another key player that many

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Speaker 3: in human eye on Apple, It's pledged to buy more

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Speaker 3: components and accessories for its devices from Vietnam suppliers. Now

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Speaker 3: the move is a big boost for the Southeast Asian country,

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Speaker 3: says it emerges as a global electronics hub. Apple is

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Speaker 3: exploring ways to shift production, of course of its GAVET

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Speaker 3: gadgets away from China. That's to minimize those geopolitical risks.

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Speaker 3: And the iphonemaker is exploring India and in Vietnam.

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Speaker 5: Which has seen about a fourfold.

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Speaker 3: Increase in companies assembling Apple products over the past decade. Meanwhile,

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Speaker 3: coming up, well, let's talk about global regulation for a moment.

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Speaker 3: We're joining the European Commission of Financial Services to discuss

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Speaker 3: all things digital finance and regulation.

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Speaker 5: There at.

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Speaker 4: I'm taking a quick look at shares of the Swedish

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Speaker 4: company Ericsson. This is the Swedish SES two percent higher

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Speaker 4: as it stands. The USA dr is actually a little

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Speaker 4: bit higher even still than that beat on earnings, and

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Speaker 4: it's really interesting there's a company going through restructuring at

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Speaker 4: a time where the mobile phone or cell carriers are

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Speaker 4: just not spending on five G network infrastructure, but the

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Speaker 4: market likes what it sees. Stock up two percent. This

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Speaker 4: is Bloomberg Technology.

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Speaker 8: Okay.

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Speaker 4: The European Unions back in Silicon Valley, and this time

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Speaker 4: the focus is payments, crypto and the impact of artificial

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Speaker 4: intelligence on banks. European Commissioner for Financial Services Marade McGinnis

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Speaker 4: has met with coinbase and Plaid, and has meetings lined up.

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Speaker 6: With Apple and Stripe.

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Speaker 4: I'm delighted to say the Commissioner joins me now on set.

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Speaker 6: Welcome.

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Speaker 8: Yeah, to be here in person.

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Speaker 1: It's been a while since I was this side of

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Speaker 1: the countries.

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Speaker 8: So it's good.

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Speaker 4: It's interesting that the ongoing relationship between the Commission and

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Speaker 4: Silicon Valley based companies. You forget there are more than

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Speaker 4: four hundred million people in Europe who have access to

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Speaker 4: those companies and their products. Just summarize the purpose of

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Speaker 4: your visit and your objectives.

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Speaker 1: Well, it's always good to meet colleagues and you can

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Speaker 1: talk to them by phone, but being here in person matters.

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Speaker 1: We're at a critical stage, so this commission is coming

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Speaker 1: towards the end of its mandate. There's been an awful

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Speaker 1: lot of change around finance, digitalization, we have artificial intelligence,

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Speaker 1: and really we're here to exchange views and to listen

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Speaker 1: to what's happening on the ground here because it's a

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Speaker 1: fast moving area. Even since my taking up this role,

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Speaker 1: we've seen a huge evolution in banking. COVID accelerated the

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Speaker 1: use of digital payments. We want payments to be instant.

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Speaker 1: We've got legislation around that. So basically, what we're trying

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Speaker 1: to do is harness the benefits of all of these technologies.

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Speaker 8: But all the way I look at the risks that

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Speaker 8: might be.

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Speaker 1: Involved in them, and our idea is not to stifle innovation,

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Speaker 1: and this is a place where innovation flourishes, so it's

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Speaker 1: good just to exchange.

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Speaker 4: We have a lot to discuss I'd like to very

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Speaker 4: quickly just tick off crypto coinbased from the show with

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Speaker 4: me last week, and they had a number of grievances,

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Speaker 4: particularly about legislating for regulation.

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Speaker 6: Instead of going through courts.

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Speaker 4: What were the grievances they brought up to you in

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Speaker 4: the context of Europe.

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Speaker 1: The grievance where it didn't arise because actually they feel

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Speaker 1: comfortable that Europe has provided certainty with our markets and

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Speaker 1: crypto assets legislation, and while there might be minor issues

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Speaker 1: within that, at least they know how they will be

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Speaker 1: regulated and licensed at the European level.

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Speaker 8: I think here it's different.

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Speaker 1: So we were able to talk about the benefits of certainty.

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Speaker 1: Very often Europe can be accused of being a rules

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Speaker 1: based which I think is actually a good accusation because

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Speaker 1: rules matter, but sometimes overregulating. I was very interested to

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Speaker 1: hear how certainty is important for a company like coin base,

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Speaker 1: and I was also interested that maybe a few years

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Speaker 1: ago this was an area of concern, but actually when

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Speaker 1: you listen to that company and its vision for what

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Speaker 1: could come next in terms of innovation and how they

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Speaker 1: believe regulation is important. I was very encouraged by that.

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Speaker 1: So we didn't have so much of the grievances. I mean,

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Speaker 1: there are issues that they will talk to us about,

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Speaker 1: and we're very open to talking with and to those

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Speaker 1: who are using our legislation and who need clarification.

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Speaker 3: Commissioner again, it's can I push back a little bit

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Speaker 3: because I'm reading a report from Tether, for example, now

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Speaker 3: nowhere near as much oversight as the previous business we're

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Speaker 3: just talking about, but key player within stable coins, the

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Speaker 3: player and stable coins, many would say, and they've gone

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Speaker 3: on the record saying the message being sent is that

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Speaker 3: Europe does not want crypto regulation has had that is

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Speaker 3: largely limiting access, especially for retail investors. Brussels effect for

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Speaker 3: many feels like a cooling effect.

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Speaker 1: Well, look, everyone has a different opinion on this, and

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Speaker 1: I think we had three options when it came to crypto,

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Speaker 1: ignore it and let things evolve, ban it because.

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Speaker 8: We couldn't control it.

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Speaker 1: Or and this is the approach we have taken regulated

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Speaker 1: so that those that are in the industry have certainty

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Speaker 1: about when they're dealing with clients within the European Union,

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Speaker 1: and I think we took the right course. Now, it's

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Speaker 1: a fast moving area and equally many who are in

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Speaker 1: that space originally came to it because they didn't want

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Speaker 1: to be in the regulated zone, if you like. But

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Speaker 1: I do think there's more maturity now that those who

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Speaker 1: want to have a lifetime in this business, which will

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Speaker 1: evolve over that time, want certainty in terms of their

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Speaker 1: dealing in the European Union, and we have provided that certainty.

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Speaker 1: And I think that's all to the good of the

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Speaker 1: industry itself. It's in one sense AI has overtaken some

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Speaker 1: of the conversations around crypto because crypto has been around

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Speaker 1: for some time.

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Speaker 8: It looks like it will prevail. There are different views.

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Speaker 1: In Europe about whether crypto is an asset or not,

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Speaker 1: and we have all of these conversations. What we do

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Speaker 1: in the permission is bear in mind, you know that

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Speaker 1: the greater good, so is the balance of regulation better

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Speaker 1: than allowing things evolved without any guardrails.

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Speaker 3: Commissioner apologies to drump in, but the AI guardrails, for example,

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Speaker 3: the AI Act. How much you think AI is a

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Speaker 3: concern in terms of well financial stability right now?

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Speaker 1: Well, I mean that's a very big question. I think

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Speaker 1: the issue of AI. Yeah, but it's such a big

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Speaker 1: question that when you listen to some of the scary

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Speaker 1: stories around AI, you would really want to stop it immediately,

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Speaker 1: but it is not something that you can actually contain.

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Speaker 1: What we can do is try and look in a

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Speaker 1: measured way of what.

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Speaker 8: Are the risks, because not only AI.

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Speaker 1: Is higher risk, In fact, some of it is extremely useful.

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Speaker 8: And again our approach, and it sounds dull, but it's

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Speaker 8: important to say it. It's about balance.

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Speaker 1: Allow the industry evolve, but allow those who are you know,

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Speaker 1: if you're like in charge of watching these things, like

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Speaker 1: the Commission and our Parliament, to have us say in

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Speaker 1: how it evolves. And we wanted to do good, so

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Speaker 1: we again look at the risks involved rather than allow

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Speaker 1: an unfettered evolution of artificial intelligence, which is already being

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Speaker 1: used in the financial system in any event, I gather

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Speaker 1: I have one who who talks to me on my

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Speaker 1: banking app. We get on sometimes not all the time,

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Speaker 1: and I think behind all of this is a desire

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Speaker 1: to harness technology but not remove the human dimension around technology,

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Speaker 1: and there's a risk that that could happen. So we've

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Speaker 1: been mindful of all of these things and we have

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Speaker 1: been careful to categorize where the risks are. Conscious also

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Speaker 1: that this will evolve. It is evolving before our very eyes.

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Speaker 3: It is commissioner, and that's why you've got plenty of conversations.

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Speaker 3: Still we had, we wish we had longer with you, right,

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Speaker 3: We get as wonderful to have you on the show.

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Speaker 3: Europeing Commissioner for Financial Services.

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Speaker 4: Revos is a Silicon Valley AI chip developer without a

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Speaker 4: product on offer yet, but it's raised more than two

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Speaker 4: hundred and fifty million dollars in an oversubscribed funding round,

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Speaker 4: with Matrix Capital Management, the largest investor in the round,

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Speaker 4: joining the board. Delighted to bring in Rivos CEO Punic

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Speaker 4: Kumar for more. This is an AI chip based on

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Speaker 4: Risk five architecture. I hear a lot about that at

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Speaker 4: the moment as an alternative to a video.

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Speaker 6: But let's go back to the idea that it is

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Speaker 6: in design.

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Speaker 4: You're in the R and D phase, that's correct. The

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Speaker 4: two hundred and fifty million, where does it get you?

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Speaker 11: Okay? So first of all, thank you for having me

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Speaker 11: on the show. An honor to be here. What we

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Speaker 11: plan to deal with this fundraise that we are announcing

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Speaker 11: today is to really primarily support our increasing customers. We

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Speaker 11: have huge demand coming at.

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Speaker 4: Us increased customers if you haven't got anything to give

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Speaker 4: him yet.

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Speaker 11: So we've been speaking with a lot of potential customers

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Speaker 11: already and they're very intrigued by our design. What we

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Speaker 11: have to offer and what we're going to do today

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Speaker 11: is use this money that we eraised to expand our

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Speaker 11: operations globally, increase our hiring, increase our engineering efforts, get

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Speaker 11: to production of our parts, and really get to trial.

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Speaker 4: I hear increasingly there is a market for Risk five

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Speaker 4: based AI accelerator or AI chip. It's a point of

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Speaker 4: differentiation from Nvidia and prior for cupcoming generations. But it

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Speaker 4: doesn't seem like that market's here in America. No one's

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Speaker 4: taking it seriously, that's right, is it in China?

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Speaker 11: Actually that's not true. It is here too. If you

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Speaker 11: in the last few days, you saw an announcement, for example,

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Speaker 11: from one of the big AI drivers that they are

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Speaker 11: using risk five in their in their chips already. So

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Speaker 11: we definitely see a place for Risk five in the

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Speaker 11: air market, and there's several companies in this market space already.

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Speaker 3: BENI for those who aren't as well versus and Risk

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Speaker 3: five versus our architecture break.

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Speaker 5: Down, what alternative offers.

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Speaker 3: Is this about cost? Is this about ability efficiency?

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Speaker 11: It's actually a combination of many factors. Cost is just

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Speaker 11: saving a license fee, for example, rather than paying somebody else.

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Speaker 11: But really the biggest thing I think is drives a

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Speaker 11: lot of innovation because it's a brand new architecture. It's open,

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Speaker 11: so that allows anybody to do research with that architecture.

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Speaker 11: And this is where we kind of see innovation happening

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Speaker 11: in the next five to ten years, and it'll eventually,

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Speaker 11: we think, will displace many of the other players in

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Speaker 11: the market, the existing incumbents. This really is the Linux moment.

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Speaker 11: We think risk Fribe brings a Linux moment to instruction

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Speaker 11: set architectures for CPU designs Perny.

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Speaker 3: Therefore, there is this handringing going on about the access

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Speaker 3: to AI infrastructure, a need for energy. We've talked a

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Speaker 3: lot about just the teaming up a Microsoft and G

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Speaker 3: forty two, the obvious global conversation going on around access

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Speaker 3: to chips.

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Speaker 5: Who would be your customer?

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Speaker 3: Are you going after in video's customers or are you

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Speaker 3: going after ones that can't access in video?

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Speaker 11: Okay, so I think first of all, we are going

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Speaker 11: after any customer that is really using a lot of data.

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Speaker 11: That's our biggest thing is that any data driven business

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Speaker 11: that needs more hardware support is a potential customer. Now

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Speaker 11: we know that the big three or four players in

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Speaker 11: the market of the cnvideo is the biggest. There's AMD,

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Speaker 11: there's Intel, and there's many other startups in the area

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Speaker 11: that are building hardware for AI. We think the field

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Speaker 11: is growing fast enough that we have ample opportunity to

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Speaker 11: address any other players who can't get access to in

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Speaker 11: video hardware or who want to look for an alternative.

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Speaker 11: Whether it's cheaper, whether it's more power efficient, there's many

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Speaker 11: factors that would go into the decision making process.

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Speaker 4: You were associated with a company called Paseemi that that

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Speaker 4: company was sold to Apple. Yes, there has been a

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Speaker 4: piece of legal proceeding or litigation that's now been settled

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Speaker 4: which came before this funding round.

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Speaker 6: Could you just explain that and where we sit with it.

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Speaker 11: You know, what we're celebrating today is our fundraise. What

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Speaker 11: we are really trying to do here is keep at

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Speaker 11: our product. Yes, it was a litigation and it's behind us,

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Speaker 11: but what we really are trying to do today is

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Speaker 11: focus on our product going forward. We've been beavering away

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Speaker 11: at this for about three years, Laser focused on getting

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Speaker 11: what we where we want to get to and we

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Speaker 11: really look forward to our product being announced in the

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Speaker 11: next six months two.

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Speaker 6: Year come back when the product's ready to show.

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Speaker 4: Absolutely all right, We're delighted to real CEO Kuma, thank

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Speaker 4: you so much.

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Speaker 3: Welcome back to MENWBG technology and how I had in

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Speaker 3: New York and I met Lovelow in San Francisco.

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Speaker 6: Markets carac Yeah, quick check.

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Speaker 3: On them because we've I've seen perhaps a little bit

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Speaker 3: more stability in the US that you've seen abroad, certainly,

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Speaker 3: and then as that one hundred actually managing to turn

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Speaker 3: green at the moment, the benchmark seeing a little bit

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Speaker 3: of inbound as we await J.

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Speaker 5: Powell speaking a little bit later.

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Speaker 3: All important for the one market which has seen a

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Speaker 3: sell off earlier and two year yels near a five

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Speaker 3: percent handle. But nevertheless we see some money going back

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Speaker 3: into big tech, m sci or country world innex so

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Speaker 3: under pressure. Europe sold off hard, so did the Asia

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Speaker 3: in fact, playing a little bit of catch up to

444
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Speaker 3: some of the risker version we've seen in the US,

445
00:22:26,680 --> 00:22:29,000
Speaker 3: Bitcoin off by one point three percent as the US

446
00:22:29,080 --> 00:22:31,359
Speaker 3: dollar just March is higher. What will we hear on

447
00:22:31,400 --> 00:22:34,280
Speaker 3: the inflationary pressure from chair power at sixty two thousand

448
00:22:34,359 --> 00:22:36,680
Speaker 3: bitcoin versus the US dollar move over. Have a look

449
00:22:36,680 --> 00:22:39,320
Speaker 3: at some of the individual names now, I said that

450
00:22:39,359 --> 00:22:41,240
Speaker 3: Europe was under pressure. I start with a name over

451
00:22:41,280 --> 00:22:43,600
Speaker 3: in the UK Wise transfer Wise and many would know

452
00:22:43,640 --> 00:22:47,280
Speaker 3: it basically sending money abroad down almost nine percent. Look,

453
00:22:47,320 --> 00:22:50,000
Speaker 3: revenue was up twenty four percent for this particular fintech Darling.

454
00:22:50,119 --> 00:22:53,360
Speaker 3: We're just speaking to the European Commissioner all around digital finance,

455
00:22:53,440 --> 00:22:56,320
Speaker 3: but it was not as much as the market wanted

456
00:22:56,359 --> 00:22:58,840
Speaker 3: to see and were under pressure significantly. TESL off by

457
00:22:58,880 --> 00:23:01,359
Speaker 3: more than two percent. Europort ed front and center as

458
00:23:01,359 --> 00:23:04,480
Speaker 3: they see executives lead and of course leave and indeed

459
00:23:04,480 --> 00:23:08,159
Speaker 3: potentially as much as twenty percent headcut and cuts in

460
00:23:08,200 --> 00:23:11,359
Speaker 3: certain areas of the business. Netflix, though you're outperformer today,

461
00:23:11,560 --> 00:23:13,520
Speaker 3: we brace ourselves for earnings at the end of the week.

462
00:23:13,600 --> 00:23:15,959
Speaker 3: We're getting some upgrades to the price targets coming from

463
00:23:16,040 --> 00:23:18,280
Speaker 3: various as. Today we're six hundred and twenty for Netflix,

464
00:23:18,280 --> 00:23:21,240
Speaker 3: But what are you looking at on other earnings areas well?

465
00:23:21,400 --> 00:23:24,800
Speaker 4: Banks and banks are big this Tuesday. AI has been

466
00:23:24,880 --> 00:23:26,440
Speaker 4: changing the game. I just want to use to listen

467
00:23:26,480 --> 00:23:29,160
Speaker 4: to a SoundBite from PGM CEO David Hunt, who joined

468
00:23:29,240 --> 00:23:29,600
Speaker 4: us earlier.

469
00:23:29,600 --> 00:23:30,240
Speaker 6: Here's what he said.

470
00:23:31,040 --> 00:23:34,119
Speaker 12: Technology now is allowing us to move data to the

471
00:23:34,119 --> 00:23:37,280
Speaker 12: cloud and then to do things with artificial intelligence that

472
00:23:37,359 --> 00:23:40,199
Speaker 12: we never could do before. And so it now is

473
00:23:40,240 --> 00:23:43,440
Speaker 12: actually being used by our investors, it's actually being used

474
00:23:43,440 --> 00:23:47,159
Speaker 12: by the frontline to make decisions. That's a very different

475
00:23:47,200 --> 00:23:49,000
Speaker 12: use of technology that it was before. And I think

476
00:23:49,000 --> 00:23:49,840
Speaker 12: that's very exciting.

477
00:23:52,760 --> 00:23:55,600
Speaker 4: Let's bring in Bloomberg Snari Bass like the Keywell Street name.

478
00:23:56,119 --> 00:24:00,480
Speaker 4: Bank of America is what's moving in the markets and

479
00:24:00,960 --> 00:24:04,320
Speaker 4: pgim's thoughts on the AI story and banks could have

480
00:24:04,320 --> 00:24:06,520
Speaker 4: put it better than I have a kid just summarize

481
00:24:06,560 --> 00:24:07,960
Speaker 4: what's happening this Tuesday morning.

482
00:24:08,240 --> 00:24:10,240
Speaker 13: There are a few things happening at the same time.

483
00:24:10,240 --> 00:24:12,159
Speaker 13: When you think about Bank of America, it is their

484
00:24:12,200 --> 00:24:15,080
Speaker 13: propensity to bring new clients in, lend them money, and

485
00:24:15,280 --> 00:24:19,240
Speaker 13: also keep a handle on costs. One thing being asked

486
00:24:19,280 --> 00:24:23,480
Speaker 13: of CEO Brian moynihan was if this further investment in

487
00:24:23,800 --> 00:24:27,920
Speaker 13: digitization of the bank would help bring their efficiency ratio

488
00:24:28,040 --> 00:24:31,800
Speaker 13: down below sixty percent, And you had CEO Brian Monahan

489
00:24:32,000 --> 00:24:33,720
Speaker 13: say they were really pushing to.

490
00:24:33,720 --> 00:24:34,400
Speaker 5: Get that done.

491
00:24:34,520 --> 00:24:37,280
Speaker 13: Now, some interesting statistics for you here, ed when you

492
00:24:37,320 --> 00:24:40,920
Speaker 13: think about how quickly things are going digital, it's that

493
00:24:41,119 --> 00:24:45,080
Speaker 13: this quarter alone, Zell transactions at Bank of America past

494
00:24:45,200 --> 00:24:48,840
Speaker 13: the combined number of checks written plus the amount of

495
00:24:48,880 --> 00:24:52,280
Speaker 13: cash withdrawalers from tellers and from ATMs. So that is

496
00:24:52,280 --> 00:24:55,600
Speaker 13: how quickly money is moving online at Bank of America. Now,

497
00:24:55,600 --> 00:24:57,560
Speaker 13: the faster they can get this done, they believe that

498
00:24:57,560 --> 00:24:59,600
Speaker 13: they would be able to create cross savings not just

499
00:24:59,640 --> 00:25:02,480
Speaker 13: for them, but for their customers as well. That's one

500
00:25:02,520 --> 00:25:06,040
Speaker 13: side of things, how the banks themselves are using digitization

501
00:25:06,119 --> 00:25:09,159
Speaker 13: and AI to really drive efficiency. The other end of

502
00:25:09,200 --> 00:25:11,120
Speaker 13: things here, I want to pull up a quote from

503
00:25:11,359 --> 00:25:14,000
Speaker 13: David Solomon Goldman Sachs, a CEO ES a day ago

504
00:25:14,400 --> 00:25:18,480
Speaker 13: about how the significant demand for AI related infrastructure and

505
00:25:18,520 --> 00:25:21,920
Speaker 13: as a result financing would be a tailwind to their business.

506
00:25:22,200 --> 00:25:23,760
Speaker 5: A day later, just today.

507
00:25:23,440 --> 00:25:26,200
Speaker 13: Now we have Morgan Stanley saying that it had the

508
00:25:26,240 --> 00:25:30,400
Speaker 13: top amount in equity underwriting fees so far this year.

509
00:25:30,680 --> 00:25:33,480
Speaker 13: The more that people are raising money in these markets,

510
00:25:33,600 --> 00:25:35,760
Speaker 13: the more you can fuel some progress in terms of

511
00:25:35,920 --> 00:25:37,640
Speaker 13: fee generation for these banks.

512
00:25:38,200 --> 00:25:40,280
Speaker 3: It isn't that fascinating thing because AI is almost a

513
00:25:40,359 --> 00:25:42,760
Speaker 3: driver on both fronts. We got the cost efficiency, We've

514
00:25:42,800 --> 00:25:44,560
Speaker 3: also got the fact that anything with AI in its

515
00:25:44,600 --> 00:25:46,920
Speaker 3: name is looking to go public at the moment, or indeed.

516
00:25:46,640 --> 00:25:48,560
Speaker 5: Try to spin that story.

517
00:25:49,040 --> 00:25:52,120
Speaker 3: How much resilience is there coming from some of these

518
00:25:52,119 --> 00:25:55,280
Speaker 3: CEOs playing catch up ultimately to Jamie Dimond, who seems

519
00:25:55,280 --> 00:25:56,680
Speaker 3: to have led the pack when it comes to AI.

520
00:25:56,800 --> 00:25:59,040
Speaker 13: Well, one thing that's interesting is you look at the

521
00:25:59,240 --> 00:26:01,280
Speaker 13: bottom line and you look at how much they're spending

522
00:26:01,280 --> 00:26:04,520
Speaker 13: on technology. You have cost rising at every bank, particularly

523
00:26:04,560 --> 00:26:07,840
Speaker 13: in terms of compensation, even with headcount following. But for

524
00:26:08,040 --> 00:26:11,360
Speaker 13: many of these banks, including Bank of America, Morgan Stanley,

525
00:26:11,359 --> 00:26:14,160
Speaker 13: you're seeing technology really be on the rise as well

526
00:26:14,200 --> 00:26:16,040
Speaker 13: when you look at the cost rising at these firms.

527
00:26:16,080 --> 00:26:18,760
Speaker 13: So they are competing not just to invest in talent,

528
00:26:18,840 --> 00:26:22,760
Speaker 13: but also to invest in the way of automating these

529
00:26:22,760 --> 00:26:25,560
Speaker 13: banks as quickly as humanly possible, because at the end

530
00:26:25,600 --> 00:26:27,600
Speaker 13: of the day, they believe it will help their bottom line.

531
00:26:27,760 --> 00:26:28,480
Speaker 5: Isn't it interesting though?

532
00:26:28,480 --> 00:26:31,600
Speaker 3: Bank of America having its worst day since well, the

533
00:26:31,680 --> 00:26:35,240
Speaker 3: Silicon Valley bank collapse back in March twenty twenty three,

534
00:26:35,240 --> 00:26:37,400
Speaker 3: which is all about money moving a bit too fast,

535
00:26:37,400 --> 00:26:41,600
Speaker 3: for everyone's pleasant relationships with it. Shanali Bassett, we please

536
00:26:41,720 --> 00:26:43,440
Speaker 3: to have you on the show today to break down

537
00:26:43,480 --> 00:26:46,119
Speaker 3: look AI and tech and banking, and let's stick with

538
00:26:46,200 --> 00:26:49,200
Speaker 3: that because over at jeffries An your private Internet conferences

539
00:26:49,240 --> 00:26:52,359
Speaker 3: on our shoulders. We've got Santa Monica is where it's

540
00:26:52,400 --> 00:26:54,840
Speaker 3: being held. Five hundred tech leaders are going to be

541
00:26:54,840 --> 00:26:57,560
Speaker 3: meeting to discuss guess what AI emerging opportunities in the

542
00:26:57,600 --> 00:27:00,359
Speaker 3: next cycle of the growth in tech Go with us.

543
00:27:00,400 --> 00:27:04,320
Speaker 3: He's Jeffrey's global co head of Internal Internet Investment Banking

544
00:27:04,720 --> 00:27:07,160
Speaker 3: joining us and Gore of congratulations on the event that's

545
00:27:07,240 --> 00:27:10,360
Speaker 3: coming today. What is front of mind from the private

546
00:27:10,400 --> 00:27:12,600
Speaker 3: allocation of money right now? Is it trying to pick

547
00:27:12,640 --> 00:27:13,840
Speaker 3: the winners in this environment?

548
00:27:14,760 --> 00:27:15,000
Speaker 8: Sure?

549
00:27:15,320 --> 00:27:18,159
Speaker 14: Firstly, thank you for having me and thank you for

550
00:27:18,280 --> 00:27:21,359
Speaker 14: covering our event over the next couple of days. What

551
00:27:21,480 --> 00:27:24,560
Speaker 14: we have here this week is a collection, as you mentioned,

552
00:27:24,560 --> 00:27:29,280
Speaker 14: of about four to five hundred company execs as well

553
00:27:29,320 --> 00:27:32,880
Speaker 14: as investors in tech and in consumer tech in particular.

554
00:27:33,520 --> 00:27:37,760
Speaker 14: This year, we have a team around AI as you've

555
00:27:37,800 --> 00:27:40,600
Speaker 14: been talking about, and it's hard to not get excited

556
00:27:40,640 --> 00:27:44,560
Speaker 14: about what the prospects are from an AI perspective. Especially

557
00:27:44,640 --> 00:27:47,439
Speaker 14: in private company land. I think there's two elements to

558
00:27:47,480 --> 00:27:51,000
Speaker 14: this that we are looking for this week. One is

559
00:27:51,040 --> 00:27:53,480
Speaker 14: the AI first company. So think about you know, companies

560
00:27:53,520 --> 00:27:59,879
Speaker 14: that are trying to disrupt existing monopolies, existing large industries,

561
00:28:00,000 --> 00:28:03,879
Speaker 14: whether that be everything from financial services to nursing to

562
00:28:04,240 --> 00:28:07,359
Speaker 14: the search and so on and so forth. There's a

563
00:28:07,359 --> 00:28:10,240
Speaker 14: whole universe of those companies. And then you've got the

564
00:28:10,320 --> 00:28:13,919
Speaker 14: large consumer internet companies that are using AI today in

565
00:28:13,960 --> 00:28:17,320
Speaker 14: their business, both from the perspective of news services as

566
00:28:17,359 --> 00:28:19,720
Speaker 14: well as from taking out costs, and so that will

567
00:28:19,720 --> 00:28:22,120
Speaker 14: be a big team across both of those sectors.

568
00:28:22,480 --> 00:28:25,040
Speaker 3: Do you expect M and A to be driven by

569
00:28:25,040 --> 00:28:26,040
Speaker 3: this AI wave.

570
00:28:27,280 --> 00:28:30,600
Speaker 14: You know, not in a meaningful way yet. And what

571
00:28:30,640 --> 00:28:32,000
Speaker 14: I mean by that is at least a lot of

572
00:28:32,000 --> 00:28:35,000
Speaker 14: the companies that we have here right now are still

573
00:28:35,200 --> 00:28:38,440
Speaker 14: relatively early in their evolution. Yes, there is a lot

574
00:28:38,440 --> 00:28:41,520
Speaker 14: of hype. Yes they are getting a lot of investment

575
00:28:41,640 --> 00:28:46,040
Speaker 14: from early stage and lead stage investors, but they're still

576
00:28:46,080 --> 00:28:49,440
Speaker 14: early in where they sit in the revenue profile of

577
00:28:49,480 --> 00:28:53,440
Speaker 14: their companies, in the maturation of business models, and so

578
00:28:53,720 --> 00:28:56,800
Speaker 14: I think everyone is monitoring it. I've talked to several

579
00:28:57,400 --> 00:29:01,520
Speaker 14: company large company executives that are here that are doing

580
00:29:01,600 --> 00:29:03,880
Speaker 14: meetings with some of these companies that are monitoring how

581
00:29:03,880 --> 00:29:06,000
Speaker 14: this is going to impact their own business. But I

582
00:29:06,040 --> 00:29:10,560
Speaker 14: think acquiring something is hard these these trade high valuations

583
00:29:10,600 --> 00:29:15,280
Speaker 14: as you noted, and acquiring for a big company to

584
00:29:15,360 --> 00:29:18,080
Speaker 14: acquire something for billions of dollars when it's not really

585
00:29:18,120 --> 00:29:20,640
Speaker 14: generating meaningful revenue, I think it's going to be really hard.

586
00:29:20,680 --> 00:29:22,240
Speaker 14: So I don't think it's going to be a big

587
00:29:22,280 --> 00:29:24,240
Speaker 14: em andity team from that perspective. I think it's going

588
00:29:24,320 --> 00:29:27,080
Speaker 14: to be a big investment team today. And by the way,

589
00:29:27,120 --> 00:29:29,720
Speaker 14: these companies can get very big, very quickly.

590
00:29:29,960 --> 00:29:30,640
Speaker 15: I think that's the.

591
00:29:30,600 --> 00:29:33,240
Speaker 14: One thing to look out for this is there's not

592
00:29:33,400 --> 00:29:36,520
Speaker 14: been as interesting of a time in consumer tech in

593
00:29:36,560 --> 00:29:39,240
Speaker 14: particular as there is today because a lot of the

594
00:29:39,280 --> 00:29:41,960
Speaker 14: companies that are in the room today could be breakout

595
00:29:42,000 --> 00:29:44,520
Speaker 14: companies in the next one to two.

596
00:29:44,320 --> 00:29:45,000
Speaker 15: To three years.

597
00:29:45,080 --> 00:29:47,480
Speaker 14: Right, These could be household names very very quickly.

598
00:29:48,760 --> 00:29:52,200
Speaker 4: Gorev It's the same in the IPO market September or

599
00:29:52,280 --> 00:29:54,920
Speaker 4: the little Reddit pop of late. You needed to have

600
00:29:54,960 --> 00:29:58,240
Speaker 4: an AI story, you called them frontline AI names or

601
00:29:58,360 --> 00:30:00,520
Speaker 4: names that needed in AI store, or even if they

602
00:30:00,520 --> 00:30:03,080
Speaker 4: had nothing to do with AI. What I'm interested from

603
00:30:03,120 --> 00:30:07,120
Speaker 4: you is in attendance this week. What's the proportion of

604
00:30:07,200 --> 00:30:11,800
Speaker 4: what you'd call genuine AI companies builders of large language

605
00:30:11,840 --> 00:30:15,640
Speaker 4: models versus those that just know in the shop window

606
00:30:15,840 --> 00:30:18,680
Speaker 4: they need the letters A and I to get some funding.

607
00:30:19,440 --> 00:30:19,760
Speaker 15: Yeah.

608
00:30:19,960 --> 00:30:22,960
Speaker 14: Yeah, it's a good question. You know, I would say

609
00:30:23,320 --> 00:30:26,520
Speaker 14: probably about you know, twenty five thirty percent of the

610
00:30:26,560 --> 00:30:29,800
Speaker 14: companies that are here are what I would say AI

611
00:30:29,920 --> 00:30:32,800
Speaker 14: first businesses. So you know, we have you know, companies

612
00:30:33,000 --> 00:30:38,480
Speaker 14: like Perplexity and glean and and Tropic and duck Bill

613
00:30:39,560 --> 00:30:43,560
Speaker 14: and eleven Labs and so on and so forth, Quora

614
00:30:44,720 --> 00:30:48,000
Speaker 14: with Poe, AI, et cetera. So you know, AI first companies,

615
00:30:48,920 --> 00:30:52,160
Speaker 14: that's probably about twenty five thirty percent of it. For

616
00:30:52,200 --> 00:30:55,960
Speaker 14: the rest, though, there will this team is so front

617
00:30:56,000 --> 00:30:56,360
Speaker 14: and central.

618
00:30:56,360 --> 00:30:57,320
Speaker 6: I'll give you examples.

619
00:30:57,560 --> 00:30:59,280
Speaker 14: You know, we've got a number of companies and travel

620
00:30:59,320 --> 00:31:03,800
Speaker 14: tech businesses like you know, Harper and a company out

621
00:31:03,840 --> 00:31:06,520
Speaker 14: of Korea, Younolgia and so on and so forth. They're

622
00:31:06,560 --> 00:31:09,640
Speaker 14: going to talk about how AI is transforming their business.

623
00:31:09,720 --> 00:31:12,160
Speaker 14: So it is not a you're right that it's a

624
00:31:12,200 --> 00:31:14,360
Speaker 14: little bit you know, they have to talk about it.

625
00:31:14,440 --> 00:31:17,080
Speaker 14: But in many cases, it is truly what is driving

626
00:31:17,120 --> 00:31:17,640
Speaker 14: their business.

627
00:31:18,600 --> 00:31:18,760
Speaker 8: You know.

628
00:31:18,800 --> 00:31:21,560
Speaker 14: Similarly, we'll have you know, companies on the music side,

629
00:31:21,680 --> 00:31:24,920
Speaker 14: and companies in fintech and in health tech, and this

630
00:31:24,960 --> 00:31:26,280
Speaker 14: will be a big team across all.

631
00:31:26,160 --> 00:31:26,840
Speaker 6: Of those as well.

632
00:31:28,160 --> 00:31:31,320
Speaker 4: Could Sir Jeffrey's Global co head of Internet Investment, Banking

633
00:31:31,360 --> 00:31:33,520
Speaker 4: and carry He mentioned one of those names that's coming up.

634
00:31:33,640 --> 00:31:35,800
Speaker 3: Yeah, I cannot wait to bring you all the highlights

635
00:31:35,840 --> 00:31:37,600
Speaker 3: from the Jeffreys conference. We're going to be joined by

636
00:31:37,600 --> 00:31:40,760
Speaker 3: the CEO of Perplexity that's coming up next. Meanwhile, let's

637
00:31:40,760 --> 00:31:42,400
Speaker 3: just go back to the public markets for a moment,

638
00:31:42,760 --> 00:31:45,640
Speaker 3: because we're also keeping a close eye on Live Nation.

639
00:31:45,920 --> 00:31:47,560
Speaker 5: The Justice Department may file.

640
00:31:47,400 --> 00:31:50,440
Speaker 3: An antitrust complaint as soon as next month aimed at

641
00:31:50,440 --> 00:31:53,360
Speaker 3: forcing Live Nation to spin off its ticket markets ticket

642
00:31:53,520 --> 00:31:57,280
Speaker 3: Master ticketing business the power of Taylor Swift without a

643
00:31:57,320 --> 00:31:59,120
Speaker 3: six point percent This is relybot technology.

644
00:32:10,200 --> 00:32:11,080
Speaker 6: Time for talking tech.

645
00:32:11,120 --> 00:32:14,760
Speaker 4: First up, Google DeepMind CEO Demis Hasbis says the company

646
00:32:14,800 --> 00:32:18,200
Speaker 4: will spend more than one hundred billion dollars over time

647
00:32:18,720 --> 00:32:22,120
Speaker 4: developing AI technology. The comment comes as a service was

648
00:32:22,160 --> 00:32:24,760
Speaker 4: asked at an event in Vancouver about a potential one

649
00:32:24,880 --> 00:32:29,320
Speaker 4: hundred billion dollars supercomputer dubbed Stargate, which is being planned

650
00:32:29,320 --> 00:32:33,120
Speaker 4: by Microsoft and OpenAI, which was reported in The Information

651
00:32:33,280 --> 00:32:35,880
Speaker 4: last month. Plus, Crypto dot Com is in the middle

652
00:32:35,920 --> 00:32:38,320
Speaker 4: of a hiring drive that could see its head count

653
00:32:38,320 --> 00:32:40,960
Speaker 4: grow by a total of fourteen hundred people. It's the

654
00:32:41,040 --> 00:32:44,760
Speaker 4: latest sign of an improved employment outlook in the sector.

655
00:32:44,800 --> 00:32:47,360
Speaker 4: Now remember, Crypto dot Com cut a fifth of its

656
00:32:47,360 --> 00:32:50,240
Speaker 4: staff in early twenty twenty three to control costs. Following

657
00:32:50,280 --> 00:32:54,520
Speaker 4: a market route, the firm began hiring again. Tokens including

658
00:32:54,520 --> 00:32:58,200
Speaker 4: bitcoin rallied rivals such as coinbased Cracking and Binance have

659
00:32:58,280 --> 00:33:02,080
Speaker 4: also been adding to their staff, and Meta's oversight board

660
00:33:02,120 --> 00:33:05,960
Speaker 4: is investigating the company's handling of AI generated deep fakes.

661
00:33:06,000 --> 00:33:09,640
Speaker 4: Earlier this year, sexually explicit deep fake images of Taylor

662
00:33:09,720 --> 00:33:14,240
Speaker 4: Swift flooded Facebook and other social platforms, prompting an outcry

663
00:33:14,280 --> 00:33:17,360
Speaker 4: from the White House, AI experts and other advocacy groups.

664
00:33:17,400 --> 00:33:19,520
Speaker 4: According to a statement made by the board, it will

665
00:33:19,560 --> 00:33:23,720
Speaker 4: evaluate whether two separate AI created images depicting nude women

666
00:33:23,880 --> 00:33:29,440
Speaker 4: posted on Facebook should have been removed under Meta's content policies.

667
00:33:29,480 --> 00:33:32,000
Speaker 3: Caroline, Now, I want to focus a bit more on

668
00:33:32,440 --> 00:33:35,880
Speaker 3: some of Meta's business models, and indeed, what's been happening

669
00:33:35,880 --> 00:33:38,800
Speaker 3: with our big take today. In the age of social media,

670
00:33:38,960 --> 00:33:41,440
Speaker 3: it's very easy ed to be deceived, but the late

671
00:33:41,600 --> 00:33:44,680
Speaker 3: scam is proving to be deadly. It's exploiting the shame

672
00:33:44,880 --> 00:33:49,120
Speaker 3: and embarrassment of teenage boys joining us now Bloomberg's Olivia Carville,

673
00:33:49,160 --> 00:33:51,960
Speaker 3: and I'm not ashamed to say that I cried several

674
00:33:52,000 --> 00:33:54,720
Speaker 3: times reading the story on the train this morning. What

675
00:33:54,880 --> 00:33:57,600
Speaker 3: BusinessWeek and what your reporting does so well? So often

676
00:33:57,720 --> 00:33:59,840
Speaker 3: as you shine a light on a few key inter

677
00:34:00,040 --> 00:34:02,880
Speaker 3: vial stories, you meet the story real. Jordan DeMay is

678
00:34:02,920 --> 00:34:05,440
Speaker 3: one of them. Can you just articulate what happened to him?

679
00:34:05,600 --> 00:34:08,200
Speaker 3: And ultimately how many more numbers of people this was

680
00:34:08,239 --> 00:34:08,680
Speaker 3: happening to.

681
00:34:09,600 --> 00:34:12,799
Speaker 16: Jordan de Maay fell victim to what is known as

682
00:34:12,840 --> 00:34:16,239
Speaker 16: a sextortion scam. This is sexual extortion.

683
00:34:16,840 --> 00:34:17,360
Speaker 5: Essentially.

684
00:34:17,400 --> 00:34:20,400
Speaker 16: He was contacted by what he thought was a teenage

685
00:34:20,440 --> 00:34:25,640
Speaker 16: girl on Instagram and she turned the conversation flirtatious. She

686
00:34:25,719 --> 00:34:28,440
Speaker 16: sent him a naked photo of herself and asked for

687
00:34:28,480 --> 00:34:32,160
Speaker 16: one in return. When Jordan complied and sent a nude

688
00:34:32,160 --> 00:34:36,120
Speaker 16: photo back to this individual through Instagram, immediately, he was

689
00:34:36,160 --> 00:34:40,680
Speaker 16: blackmailed for money. So what actually unfolded and what he

690
00:34:40,760 --> 00:34:44,600
Speaker 16: had no idea of is that who was behind that

691
00:34:44,680 --> 00:34:48,920
Speaker 16: account was actually con men or scammers based in Lagos,

692
00:34:49,000 --> 00:34:52,960
Speaker 16: Nigeria who had been contacting hundreds of teen boys across

693
00:34:53,000 --> 00:34:56,440
Speaker 16: the US, reaching out to them to try and elicit

694
00:34:56,520 --> 00:35:00,400
Speaker 16: a nude photo from them to then blackmail them. Crime

695
00:35:00,520 --> 00:35:04,280
Speaker 16: sextortion is now the fastest growing crime in the US.

696
00:35:04,520 --> 00:35:08,040
Speaker 16: The FBI has been sending out PSAs because sadly, it's

697
00:35:08,160 --> 00:35:11,840
Speaker 16: resulted in the suicide of more than two dozen teen boys,

698
00:35:11,880 --> 00:35:15,800
Speaker 16: including Jordan de May and a guilty plea coming from

699
00:35:16,000 --> 00:35:19,440
Speaker 16: two very young boys themselves ultimately and just adults in

700
00:35:19,760 --> 00:35:23,440
Speaker 16: Lagos who are now here in the US. SNAP did

701
00:35:23,480 --> 00:35:26,760
Speaker 16: respond to your reporting saying they're ramping up our tools

702
00:35:26,760 --> 00:35:29,839
Speaker 16: to combat sextortion and we have extra safeguards for teams

703
00:35:29,880 --> 00:35:33,200
Speaker 16: to protect against unwanted contact, and indeed matters global head

704
00:35:33,200 --> 00:35:35,880
Speaker 16: of Safety you've been speaking to saying that sextortion is

705
00:35:35,920 --> 00:35:38,279
Speaker 16: a horrific crime and we spent years building technology to

706
00:35:38,320 --> 00:35:41,279
Speaker 16: combat it and support law enforcement in investigating and prosecuting

707
00:35:41,280 --> 00:35:42,239
Speaker 16: their criminals behind it.

708
00:35:42,280 --> 00:35:44,560
Speaker 5: But ultimately you're saying this is still growing.

709
00:35:45,160 --> 00:35:49,000
Speaker 3: What more are stories You're hearing or indeed ways in

710
00:35:49,040 --> 00:35:51,680
Speaker 3: which is it technology that ends up being able to

711
00:35:51,719 --> 00:35:53,040
Speaker 3: be a force against this.

712
00:35:53,800 --> 00:35:55,920
Speaker 16: Yeah, I think it's a great question. I mean, for

713
00:35:56,000 --> 00:36:01,640
Speaker 16: the social media platforms, they don't want this occurring. These individuals,

714
00:36:01,680 --> 00:36:05,000
Speaker 16: these bad actors are hacking into Instagram accounts to pretend

715
00:36:05,040 --> 00:36:07,560
Speaker 16: to be these teen girls in order to coerce these

716
00:36:07,640 --> 00:36:11,040
Speaker 16: nude photos. So for the platforms, it becomes how do

717
00:36:11,120 --> 00:36:14,480
Speaker 16: we prevent this from the outset? So they're using artificial

718
00:36:14,480 --> 00:36:19,280
Speaker 16: intelligence to do things like suspect or detect suspicious activity

719
00:36:19,280 --> 00:36:23,719
Speaker 16: on the platform. Meta is now sending sextortion focused safety

720
00:36:23,760 --> 00:36:27,239
Speaker 16: notices to teens saying, you know, this is what sextortion is.

721
00:36:27,360 --> 00:36:29,960
Speaker 16: Be wary, be careful of who you're talking to. And

722
00:36:30,160 --> 00:36:32,400
Speaker 16: just last week they announced that they're going to be

723
00:36:33,160 --> 00:36:37,160
Speaker 16: automatically blurring nude images that are sent through the platform.

724
00:36:37,480 --> 00:36:39,920
Speaker 16: So all of these steps are being taken in an

725
00:36:39,960 --> 00:36:42,719
Speaker 16: effort to try and curb this crime. But from the

726
00:36:42,840 --> 00:36:47,560
Speaker 16: FBI's perspective and law enforcement perspective, it's just growing too big,

727
00:36:47,800 --> 00:36:51,360
Speaker 16: it's moving too fast, and the scammers are too ruthless

728
00:36:51,760 --> 00:36:54,719
Speaker 16: in how they blackmail the teens. They push them to

729
00:36:54,800 --> 00:36:57,279
Speaker 16: the edge and beyond to try and get as much

730
00:36:57,360 --> 00:36:59,800
Speaker 16: money as they possibly can from these young boys.

731
00:37:01,080 --> 00:37:01,520
Speaker 6: Olivia.

732
00:37:01,640 --> 00:37:05,640
Speaker 4: This is the latest in a series of investigations you've

733
00:37:05,719 --> 00:37:10,000
Speaker 4: done across quite a broad domain of AI generated content

734
00:37:10,080 --> 00:37:14,160
Speaker 4: on social media, deep fake pornography, and now this piece.

735
00:37:14,640 --> 00:37:17,040
Speaker 4: You talked about the efforts there, but also the challenges.

736
00:37:17,120 --> 00:37:21,719
Speaker 4: Is there one outcome from your investigation since publishing the

737
00:37:21,800 --> 00:37:25,520
Speaker 4: story that you can talk about anything that happened in

738
00:37:25,560 --> 00:37:26,800
Speaker 4: response to your reporting.

739
00:37:27,640 --> 00:37:30,520
Speaker 16: Well, I was surprised to see Meta announced just last

740
00:37:30,560 --> 00:37:33,839
Speaker 16: week that they're going to be blurring neod images sent

741
00:37:33,920 --> 00:37:36,160
Speaker 16: through the platform. I think that is a great step

742
00:37:36,320 --> 00:37:39,040
Speaker 16: in the right direction, and you're right. I tend to

743
00:37:39,040 --> 00:37:42,880
Speaker 16: focus these stories on the dark sides of social media,

744
00:37:42,920 --> 00:37:45,680
Speaker 16: and there's obviously so much good that social media gives

745
00:37:45,719 --> 00:37:48,360
Speaker 16: to children and young people as well. These are the

746
00:37:48,560 --> 00:37:51,279
Speaker 16: edge cases, and I think it's really important for our

747
00:37:51,400 --> 00:37:54,279
Speaker 16: viewers and our readers to know about the risks of

748
00:37:54,360 --> 00:37:58,239
Speaker 16: social media, and specifically in this story, for young teen

749
00:37:58,320 --> 00:38:02,319
Speaker 16: boys to understand maybe the person that you're messaging isn't

750
00:38:02,320 --> 00:38:05,000
Speaker 16: actually who they say they are. Maybe you need to

751
00:38:05,040 --> 00:38:08,120
Speaker 16: be more cautious about how you behave on social media,

752
00:38:08,480 --> 00:38:11,160
Speaker 16: what you put out there to the public and how

753
00:38:11,200 --> 00:38:14,799
Speaker 16: you talk to individuals who are ultimately strangers, people you

754
00:38:14,880 --> 00:38:15,319
Speaker 16: don't know.

755
00:38:16,480 --> 00:38:19,520
Speaker 3: I've urged everyone out there to go read your reporting

756
00:38:19,680 --> 00:38:22,400
Speaker 3: and indeed the implications of it. Olivia Carville, thank you

757
00:38:22,440 --> 00:38:24,560
Speaker 3: so much for spending time with us today to talk

758
00:38:24,600 --> 00:38:30,040
Speaker 3: through it.

759
00:38:33,000 --> 00:38:35,839
Speaker 4: Let's get back to the Jeffries Private Internet Conference. One

760
00:38:35,880 --> 00:38:40,480
Speaker 4: major theme the theme is AI Perplexity. CEO arab Inshrinibas

761
00:38:40,760 --> 00:38:43,160
Speaker 4: is joining us now from that conference and Perpexity, of

762
00:38:43,160 --> 00:38:47,160
Speaker 4: course the developer of an AI based search engine platform.

763
00:38:47,280 --> 00:38:50,520
Speaker 4: And I hear the name perplexity a lot. I know

764
00:38:50,560 --> 00:38:53,160
Speaker 4: a lot of people use perplexity and a lot of

765
00:38:53,160 --> 00:38:56,680
Speaker 4: people talk about perplexity. Why are you at Jeffries. What

766
00:38:56,719 --> 00:38:58,480
Speaker 4: do you want to get out of it this week?

767
00:39:00,000 --> 00:39:03,719
Speaker 2: I'm excited to meet people here, and you know, Perplexity

768
00:39:03,760 --> 00:39:06,880
Speaker 2: is still not a household name yet. I want to

769
00:39:06,880 --> 00:39:10,320
Speaker 2: be used by every person, every organization, and it always

770
00:39:10,400 --> 00:39:14,840
Speaker 2: helps to spread awareness and get more people excited about Perplexity.

771
00:39:16,239 --> 00:39:18,879
Speaker 4: There have been reports that you are now a one

772
00:39:19,000 --> 00:39:23,200
Speaker 4: billion dollar valued startup. There is a lot of interest

773
00:39:23,239 --> 00:39:27,160
Speaker 4: in your capability. Talk to us about the financial health

774
00:39:27,160 --> 00:39:28,320
Speaker 4: of Perplexity right now.

775
00:39:31,160 --> 00:39:33,920
Speaker 2: I think like what we announced was, you know, when

776
00:39:33,960 --> 00:39:36,680
Speaker 2: I was there last time here with you with the

777
00:39:36,960 --> 00:39:39,680
Speaker 2: Jeff Bezos, around five hundred and twenty million dollar evaluation.

778
00:39:40,200 --> 00:39:44,160
Speaker 2: We haven't made an official announcement on a new around yet.

779
00:39:45,080 --> 00:39:47,320
Speaker 2: We'll have more to share soon very shortly.

780
00:39:47,960 --> 00:39:50,280
Speaker 5: Oh, come back talk to us about that for now.

781
00:39:50,760 --> 00:39:52,920
Speaker 5: What strives are you making?

782
00:39:53,200 --> 00:39:56,560
Speaker 3: Are people switching from say Google as a search engine

783
00:39:56,600 --> 00:39:56,880
Speaker 3: to you?

784
00:39:57,040 --> 00:39:58,200
Speaker 5: What do your customers say.

785
00:39:58,000 --> 00:40:00,560
Speaker 15: Eravan, What is is like?

786
00:40:00,600 --> 00:40:05,239
Speaker 2: They're not viewing us as like, oh, I either use

787
00:40:05,360 --> 00:40:08,360
Speaker 2: you or Google. They're still happy to use Google for

788
00:40:08,480 --> 00:40:10,759
Speaker 2: like quickly getting onto like a website, like say they

789
00:40:10,840 --> 00:40:11,440
Speaker 2: just want to go to.

790
00:40:11,360 --> 00:40:14,239
Speaker 15: Bloomberg dot com. They're just happy to use Google for that.

791
00:40:14,880 --> 00:40:17,920
Speaker 2: But let's say they want to know like what what

792
00:40:18,080 --> 00:40:20,600
Speaker 2: is the latest thing going on at Jeff Freeze, or

793
00:40:20,600 --> 00:40:23,200
Speaker 2: like like who are the speakers at this conference that

794
00:40:23,640 --> 00:40:26,000
Speaker 2: I should be aware of for my business. I think

795
00:40:26,000 --> 00:40:28,440
Speaker 2: these are things are what Perplexity is more useful for.

796
00:40:28,960 --> 00:40:32,120
Speaker 2: So they are beginning to see us as a different too,

797
00:40:32,239 --> 00:40:35,319
Speaker 2: an answer engine that's very useful for directly coming and

798
00:40:35,360 --> 00:40:38,680
Speaker 2: asking questions and doing your research and our growth in

799
00:40:38,719 --> 00:40:42,040
Speaker 2: the United States. Since we announced the funding around last

800
00:40:42,040 --> 00:40:45,720
Speaker 2: time along with you guys has been like really good.

801
00:40:46,040 --> 00:40:49,400
Speaker 2: And that's also translated a lot to growing our revenue

802
00:40:49,440 --> 00:40:51,759
Speaker 2: because we always wanted to be a tool that's used

803
00:40:51,760 --> 00:40:55,000
Speaker 2: by people in the high income countries and that's beginning

804
00:40:55,040 --> 00:40:56,680
Speaker 2: to show up in our numbers too.

805
00:40:56,960 --> 00:40:58,080
Speaker 5: What am I a business model?

806
00:40:58,440 --> 00:41:01,440
Speaker 3: Is a lot of interesting talk of how wele Google

807
00:41:01,480 --> 00:41:04,840
Speaker 3: itself might start charging for its AI offerings within its enterprise.

808
00:41:05,280 --> 00:41:07,640
Speaker 3: Are you seeing enterprise adoption for you and you're thinking

809
00:41:07,640 --> 00:41:08,360
Speaker 3: about charging?

810
00:41:09,840 --> 00:41:11,240
Speaker 15: Definitely considering it.

811
00:41:12,680 --> 00:41:16,040
Speaker 2: And that would be something we should We'll be sharing

812
00:41:16,120 --> 00:41:19,239
Speaker 2: soon something more on that. And the way I see

813
00:41:19,280 --> 00:41:21,840
Speaker 2: it is like a lot of companies, a lot of

814
00:41:21,840 --> 00:41:26,120
Speaker 2: people tell me that, you know, I wish I could

815
00:41:26,160 --> 00:41:29,480
Speaker 2: use perplexity at work, but my company is banded.

816
00:41:29,920 --> 00:41:33,480
Speaker 15: Yes, you know, so that's a problem to solve and

817
00:41:33,520 --> 00:41:34,320
Speaker 15: we're going to work on that.

818
00:41:35,480 --> 00:41:37,960
Speaker 4: I remember, what's the challenge right now for a company

819
00:41:38,000 --> 00:41:41,200
Speaker 4: that is building lllms and working at this level.

820
00:41:41,360 --> 00:41:43,120
Speaker 6: What is your day to day that you're facing.

821
00:41:44,960 --> 00:41:48,759
Speaker 2: I mean, the biggest challenge is honestly the pace I

822
00:41:48,800 --> 00:41:53,279
Speaker 2: which this field keeps changing every week. Right one point,

823
00:41:53,360 --> 00:41:55,840
Speaker 2: we were all like GPT for is D model and

824
00:41:56,000 --> 00:41:59,200
Speaker 2: it's like there's nothing else that matters, and everyone was like,

825
00:41:59,600 --> 00:42:01,560
Speaker 2: oh yeah, and you cannot build on top of them

826
00:42:01,600 --> 00:42:03,440
Speaker 2: because like they're eventually going to do all the product

827
00:42:03,480 --> 00:42:04,360
Speaker 2: and like it doesn't matter.

828
00:42:05,160 --> 00:42:06,799
Speaker 15: There's no independence from open AI.

829
00:42:07,320 --> 00:42:11,560
Speaker 2: And then Anthropic puts out clock three and then clock

830
00:42:11,600 --> 00:42:13,879
Speaker 2: three is even better than GPT four, at least the

831
00:42:13,920 --> 00:42:18,120
Speaker 2: Opus model, and they're like models much better than three

832
00:42:18,120 --> 00:42:22,640
Speaker 2: point five, cheap, faster, open sources, moving fast data breaks.

833
00:42:22,640 --> 00:42:24,719
Speaker 15: Release the model that's like better than three point five.

834
00:42:24,719 --> 00:42:25,960
Speaker 15: Mistrals keeps using.

835
00:42:27,600 --> 00:42:29,560
Speaker 3: It's just the pace, and the pace of the show

836
00:42:29,600 --> 00:42:31,279
Speaker 3: went too fast as well. We wish we had time

837
00:42:31,320 --> 00:42:34,480
Speaker 3: with you, Aravens, turn of us perplexity, CEO, wonderful to

838
00:42:34,480 --> 00:42:35,040
Speaker 3: have his thoughts.

839
00:42:35,120 --> 00:42:37,799
Speaker 5: Let's bring my technology