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Speaker 1: From Mahart 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 Heine Bluemug's World headquarters in New York, and

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Speaker 3: I'm Ed Ludlow in San Francisco.

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Speaker 2: This is Bloombay Technology.

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Speaker 3: Coming up full earnings coverage ahead salesforce and jumps after

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Speaker 3: forecasting profit the top estimates and showing signs of momentum

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Speaker 3: in cost cutting.

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Speaker 4: And Elon Musk says the advertiser boycotton X may kill

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Speaker 4: the platform. Will break down his comments and look at

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Speaker 4: the rollout of Tesla's cyber truck plus.

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Speaker 3: Today marks one year since the public rollout of chat GPT,

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Speaker 3: bringing AI into the spotlight and sparking a wave of

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Speaker 3: investment and hiring. Will dig in to what that one

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Speaker 3: year anniversary red means. But first that's checking on these

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Speaker 3: markets because while we're coming to the end of the

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Speaker 3: month here and what a month it has been, but

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Speaker 3: in the short term we just perhaps give off some

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Speaker 3: of those profits. We see off about nine ten percent

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Speaker 3: on the Nasdaq. Look the PCE, the number, the inflationary

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Speaker 3: indicator coming in basically where.

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Speaker 5: The market had anticipated.

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Speaker 3: So they're already priced in the good news and maybe

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Speaker 3: we sell the fact we'll look at the ten yure

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Speaker 3: YELD actually just bouncing up a little bit after what

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Speaker 3: has been a roaring November for the bomb market as well.

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Speaker 3: I mean, just phenomenal by everything rally for the November month,

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Speaker 3: and we're seeing Crypto just giving off a little bit,

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Speaker 3: but look hardly any movement there down a by a

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Speaker 3: tenth of a percent, moving on, and I just want

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Speaker 3: to give you the context of where we've been this

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Speaker 3: month because an extraordinary move high that we have seen

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Speaker 3: in the Nasdaq overall, and we've given well, well you

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Speaker 3: see over the last actually there is Bitcoin over the

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Speaker 3: last month that's up some nine percent, Nasdaq itself up

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Speaker 3: well ten percent on the months, which has clearly been

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Speaker 3: the best month for the Nasdaq since January, and Bitcoin

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Speaker 3: as well, up more than nine percent. Really, it's been

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Speaker 3: in everything rally, risk on and what about the individual movers.

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Speaker 4: To It's been a really busy twenty four hours in

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Speaker 4: the earnings context with Technology Snowflakes strong outlook boosting that

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Speaker 4: stock up almost five percent. HPEU graded at Morgan Stanley

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Speaker 4: which is adding to a two day rally. It posted

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Speaker 4: results Wednesday night, you'll remember, but it is showing real strength.

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Speaker 4: Then a thriller for you in the story's face, pure

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Speaker 4: story is giving a weak sales outlook that really hammering

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Speaker 4: the stock. And then elsewhere, big rival Newtoni's actually upgrading

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Speaker 4: its billings forecast that's supporting that stock. The main earning

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Speaker 4: story is Salesforce, and you're right, the story with Salesforce

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Speaker 4: is that it's cost discipline, its cost cutting is showing

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Speaker 4: a real path to boosting profitability. The stock up six

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Speaker 4: and a half percent, putting it on track for its

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Speaker 4: biggest jump since March.

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Speaker 2: Is this the Mark Benioff effect?

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Speaker 4: Is this him listening to the investors and acting while

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Speaker 4: the stock seems to be reacting such that it is.

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Speaker 3: Yeah, I mean, look at that up more than six percent.

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Speaker 3: Let's get to it with our own Salesforce reporter bringing

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Speaker 3: Brody Ford, and.

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Speaker 5: It does seem to be this new era of cost

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Speaker 5: discipline that really benefits Salesforce. Is there underlying revenue generation

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Speaker 5: going on?

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Speaker 2: Hit to you, that's everybody's fear, right.

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Speaker 6: I mean, it was a year ago, about a year

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Speaker 6: ago today that Salesforce said that their co CEO is

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Speaker 6: stepping down. It kicked off as kind of unprecedented wave

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Speaker 6: of chaos.

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Speaker 5: Right over the period of a quarter or two.

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Speaker 6: We saw executive resignations, activists, investors.

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Speaker 7: Taylor is right, right, but yeah, and ultimately though they

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Speaker 7: raised their profits incredibly, it made people very happy, but

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Speaker 7: then it made them very scared because then revenue growth

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Speaker 7: started slowing down.

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Speaker 6: What we saw last night is that as long as

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Speaker 6: revenue growth stays stable and profit keeps going up, well

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Speaker 6: that's good enough for now.

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Speaker 4: Hey Brady, how does AI play into that story? I

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Speaker 4: know it's something that any off flights to talk about.

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Speaker 2: Yep.

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Speaker 6: Yeah, so they're really big hope here with AI is

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Speaker 6: that it can help bring revenue growth back up. That's

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Speaker 6: immaterial for the current year, but they're hoping that when

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Speaker 6: it comes to next year, it'll help, you know, upsell

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Speaker 6: people on most new so descriptions. Right, You got to

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Speaker 6: pay a little extra to get the chat bar in

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Speaker 6: your apps where you can use that to automate your processes,

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Speaker 6: ask good questions, bring in your favorite large language models,

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Speaker 6: and so there you have been pretty much putting AI

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Speaker 6: into every single press release you can find and it.

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Speaker 6: You know, the cat is out on whether it will

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Speaker 6: truly boost revenue growth the way they hope.

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Speaker 4: Doomber's brady for busy earning season. For you covering Snowflake

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Speaker 4: as well, Thank you very much, all right. The other

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Speaker 4: top story. Ever since Musk agreed with an anti semitic

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Speaker 4: post on his social platform X earlier this month, that

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Speaker 4: was November fifteenth, the billionaire has been under fire Caro

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Speaker 4: from the White House, several test investors. But for the

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Speaker 4: first time since that post prompted the global backlash, let's

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Speaker 4: be honest, Musk has apologized to his choice of words,

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Speaker 4: saying that the post was quote the worst and dumbest

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Speaker 4: he's ever done. That was during the New York Times

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Speaker 4: Deal Book conference in New York. He also said his

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Speaker 4: trip to Israel was planned before the advertiser backlash and

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Speaker 4: wasn't an apology tour. So, I mean, look, you and

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Speaker 4: I were talking about this this morning at our desks.

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Speaker 4: This is an apology first and foremost, and then an

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Speaker 4: exploit expletive laid in message to the advertisers, which was basically,

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Speaker 4: don't advertise.

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Speaker 5: Yeah, he's not apologizing to them.

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Speaker 3: He might be apologizing to the media, to the user base,

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Speaker 3: to those that he feels have perhaps misunderstood his messaging

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Speaker 3: along and certainly once again time and time again saying

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Speaker 3: he's not antisemitic, but many will point to the way

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Speaker 3: in which he interacts on his own social media platform

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Speaker 3: as not being clear and consistent with that thought.

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Speaker 5: But putting to that to one side, the fact that.

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Speaker 3: He can basically bring Bob Iger's name into the conversation

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Speaker 3: on stage explutive least as you say, and basically saying, look,

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Speaker 3: you're the ones that are killing X. Meanwhile, I mean

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Speaker 3: many would say is he the one killing X in

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Speaker 3: the respect that it's his own actions that perhaps push

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Speaker 3: away some of these advertisers, but also he's the guy

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Speaker 3: who could perhaps sustain it.

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Speaker 5: He's got the money.

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Speaker 2: Yeah, I think you know.

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Speaker 4: There are the debt equation of Twitter and X and

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Speaker 4: how he bought it. There are the equity holders in X,

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Speaker 4: the platform formerly known as Twitter. That basically what he said,

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Speaker 4: and it's fair to point out. On November fifteenth, he

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Speaker 4: regretted that post, but he said he immediately followed up

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Speaker 4: with the clarification that the media ignored in his words,

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Speaker 4: and as for Bob Byger, he basically said, hey, Bob,

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Speaker 4: I'm sure you're in the audience. We think that's a

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Speaker 4: reference to Disney CEO Bobbieger, though he wasn't explicit.

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Speaker 3: Yeah, and probably they'd been together in the green room

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Speaker 3: perhaps before of that, because Bobbigo had been speaking at

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Speaker 3: the same conference as well.

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Speaker 5: But all of this basically is noise around what.

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Speaker 3: Is going to be a big main event for one

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Speaker 3: of his key companies, Tesla. We just referenced how some

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Speaker 3: investors have been concerned about the way he's been behaving

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Speaker 3: on his social media platform, and we want to be

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Speaker 3: bringing in Craig Trudell now on the fact that actually

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Speaker 3: what he wants to dominate the headlines today is a

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Speaker 3: cyber truck unveiling RNE.

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Speaker 8: I don't think I'll have any trouble doing that. Of course,

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Speaker 8: it's a pickup that made an awful lot of headlines

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Speaker 8: going back four years now. Right, So, this was a

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Speaker 8: truck that they showed very famously or infamously, I guess,

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Speaker 8: depending on your view through the metal ball at the

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Speaker 8: windows they cracked.

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Speaker 9: You know.

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Speaker 2: I think a lot of people.

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Speaker 8: Who were in the room sort of gasp when this

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Speaker 8: truck was first shown and you know, some weren't really

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Speaker 8: sure how serious it was.

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Speaker 2: It's dead serious.

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Speaker 8: It's finally ready for deliveries a couple of years late.

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Speaker 8: But it's no question that this one's sort of a

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Speaker 8: head turner and you know, sort of as polemic a

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Speaker 8: vehicle as they come, you.

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Speaker 4: Know, Craig, the pickup category, be it electric, hall combustion engine,

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Speaker 4: is just sacred in North America. And you know, donah

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Speaker 4: Hole has written really smartly about how Musk has been

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Speaker 4: signposting for like years that this is really ambitious, is

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Speaker 4: not going to be easy to build.

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Speaker 8: Yeah, and I think she did a great story this week,

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Speaker 8: you know, really drawing parallels between you know, this is

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Speaker 8: their first pick up. They had a first suv years ago,

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Speaker 8: the Model X. That there's a lot of similarities in

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Speaker 8: the way Musk has talked about these two, you know,

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Speaker 8: with the Model X, you know, he talked about, you know,

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Speaker 8: regretting the fact that they sort of overloaded it with technology,

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Speaker 8: and then he's gone on to say that he's overloaded

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Speaker 8: the cyber truck with an awful lot of technology. So

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Speaker 8: there's a lot of ways that this, you know, manufacturing

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Speaker 8: this pickup could go sideways. I think he's really sort

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Speaker 8: of you know, gone out of his way to bring

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Speaker 8: expectations down in terms of how quickly they'll be able

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Speaker 8: to scale this up, when they'll be able to do

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Speaker 8: so in a way that's not you know, burning through

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Speaker 8: lots of cash, and so, you know, I think, you know,

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Speaker 8: we may be surprised. There are some people who, you know,

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Speaker 8: think that this thing is kind of hideous and and

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Speaker 8: a bit of a monstrosity. There are some who think

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Speaker 8: it's really really cool. I think, you know, there's probably

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Speaker 8: going to be no trouble here with demand. For me,

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Speaker 8: the question is how the heck are they going to

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Speaker 8: scale this thing up and overcome the various manufacturing challenges

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Speaker 8: that he's flagged going into this.

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Speaker 5: Craig, we thank you. Bliombo's craigtured all On.

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Speaker 4: Sam Altman is officially reinstated as CEO of open Ai,

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Speaker 4: and it has a new initial board of directors, with

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Speaker 4: Microsoft now joining as a non voting observer. All of

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Speaker 4: this happening one year to the day after chat GPT

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Speaker 4: was released and made it accessible to the public. Let's

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Speaker 4: bring in Bloombo's Rachel Metz. Lots of news out overnight,

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Speaker 4: and you had an interview with Sam Altman.

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Speaker 10: He did, Yeah, there's a lot going on at OPENINGI

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Speaker 10: A lot of it is rubber stamping in a sense

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Speaker 10: of things that we had already learned that Sam Altman

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Speaker 10: is now officially back at the company as a CEO,

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Speaker 10: and and Greg Brackman, who had been president, is also

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Speaker 10: back at the company. Miramrati, who was very very briefly

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Speaker 10: interim CEO, is now back as a chief Technology officer,

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Speaker 10: and a bunch of other things that you just recount.

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Speaker 5: I'm a whole bunch of other things.

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Speaker 3: I mean, notably, Microsoft comes on as a non voting observer.

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Speaker 3: Still a lack of diversity at the interim board level

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Speaker 3: as we can currently see, but I'm interested that they

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Speaker 3: are saying is certainly Brett Taylor was writing alongside some

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Speaker 3: Mountman in a post that look, prepare yourself. We are

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Speaker 3: going to be diverse, and we're also going to look

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Speaker 3: into why any of this upheaval happen to begin with.

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Speaker 10: Yes, absolutely so on the first point, diversity and just

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Speaker 10: enlarging the board. When I spoke to Sam yesterday, and

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Speaker 10: also I got to speak briefly to Larry Summers, who's

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Speaker 10: one of the new board members. They both said that

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Speaker 10: they're planning to enlarge the board significantly. Wouldn't give a

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Speaker 10: number on how many people will be in it eventually,

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Speaker 10: but they're definitely planning to add people. Or as to

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Speaker 10: the other point that you were making, now I'm blinking

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Speaker 10: on what that was.

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Speaker 5: Go back now.

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Speaker 3: I mean, it's so what you have covered and the

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Speaker 3: amount that you have covered over the last few days,

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Speaker 3: no wonder you're going to be blanking. But really, Larry

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Speaker 3: Summer's coming on board, many feeling is sort of like

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Speaker 3: the experienced board director and himself thinking about the way

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Speaker 3: in which this board can be expanded and thought upon.

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Speaker 3: And he says, like, give us a minute. We've only

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Speaker 3: been in the board of interim board for about half

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Speaker 3: an hour. I think, what's the coak that he gave you.

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Speaker 3: Rachel Metz, we thank you so much for your time

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Speaker 3: and of course continued conversation that she manages to have

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Speaker 3: with these key executives. Let's get another key angle from Sarahkrat's,

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Speaker 3: Professor of Government and director of Tech Policy Institute over

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Speaker 3: at Cornell University. And Sarah, you yourself were you were

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Speaker 3: back in the day before open AI became a for

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Speaker 3: profit business. You were helping alongside early open ai employees

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Speaker 3: co author research documents, thinking about ultimately how generative AI

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Speaker 3: can work in hand and be good for humanity. How

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Speaker 3: has the era of chatchpt fast forward in what you

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Speaker 3: thought was achievable in artificial intelligence?

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Speaker 11: Right? No, So, I started working with OpenAI back in

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Speaker 11: twenty eighteen when it was still the nonprofit, and then

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Speaker 11: in twenty nineteen it became the for profit. I've but

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Speaker 11: I think as the company it's really almost only a

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Speaker 11: year old because it was so formative in that time.

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Speaker 11: Between twenty fifteen and twenty twenty two, most people hadn't

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Speaker 11: heard of it. We were writing and researching, and then

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Speaker 11: in twenty twenty two, chat gpt became this consumer facing

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Speaker 11: platform that was so easy to use, so user friendly,

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Speaker 11: and it just took off the fast setting records for

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Speaker 11: its uptake one hundred million users within the first two

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Speaker 11: months and now one hundred million users per week, which

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Speaker 11: is really astonishing.

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Speaker 4: It's incredible to track how far we've come in the

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Speaker 4: space of the year. But much of the last two

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Speaker 4: events put the spotlight on what's to come next, the

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Speaker 4: next generation of large language model on the board issue

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Speaker 4: this is what Brett Taylor, whose interim chair of Open

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Speaker 4: Aiyes Board, said, we will build a qualified, diverse board

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Speaker 4: of exceptional individuals reflecting open ais message from technology to policy.

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Speaker 4: That last bit, technology to policy. Why is the makeup

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Speaker 4: of Open Aiyes Board important to their success in developing

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Speaker 4: the technology?

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Speaker 11: Yeah. I think what we saw in those two weeks,

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Speaker 11: in these last two weeks was just that kind of

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Speaker 11: tug of war on was between the two visions of

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Speaker 11: what AI should look like. And there have been a

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Speaker 11: lot of discussions about how much of that was just

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Speaker 11: kind of a myth and outsiders reading things that weren't there.

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Speaker 11: But it does seem like there are these two real

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Speaker 11: philosophies about how quickly to move, and that the philosophy

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Speaker 11: about moving quickly seems to have one out. And I

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Speaker 11: think what the board should do, or its intended role,

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Speaker 11: is to be kind of a rudder in shoppy water

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Speaker 11: or what could be choppy waters. But I think where

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Speaker 11: the nonprofit board, the former board got in the way

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Speaker 11: was that its vision was so at odds or seemed

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Speaker 11: to be at odds with not just the direction Open

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Speaker 11: AI is going, but AI in general. And so I

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Speaker 11: think right now We're in a real arms race, and

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Speaker 11: the I think legitimate perspective of the Open AI people

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Speaker 11: who have stayed is that this technology is developing quickly,

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Speaker 11: whether we're on board or not, and so we might

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Speaker 11: as well be. We Open AI be leading and trying

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Speaker 11: to do it responsibly. So you know, the nonprofit or

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Speaker 11: what was the not what is the nonprofit board, but

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Speaker 11: the former board I think it wasn't that they didn't

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Speaker 11: want to develop AI, but I think they just had

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Speaker 11: different ways of doing it. So the new board will

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Speaker 11: come in and try to i think, be more compatively

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Speaker 11: aligned with that, with the direction that the company and

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Speaker 11: with the direction the AI is going.

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Speaker 3: And of course much of the hand wringing around AI

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Speaker 3: and safety has been a worry about bias. That is

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Speaker 3: why many people are saying, you need to have minor

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Speaker 3: at the table. You need to ensure that all voices

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Speaker 3: are heard. Here we re established at the interim board

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Speaker 3: as it stands, looks pretty undiverse, one of them being

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Speaker 3: Larry Summers the course, a paid contributor of Bloomberg. I'm

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Speaker 3: interested as to what you think, Sarah will be the

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Speaker 3: next situation. Will open AI be able to be as

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Speaker 3: agile going forward. Do you think after this, No, I

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Speaker 3: think there.

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Speaker 11: Has to be a real goal and I think for

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Speaker 11: them and in general, the diversity is not an end

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Speaker 11: in itself, but it does give you different perspectives. Some

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Speaker 11: of the early versions of AI really did, I think,

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Speaker 11: warrant some criticism about bias and discrimination. So I think

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Speaker 11: there is a lot of attentiveness to that. So it's

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Speaker 11: important for that board to be able to read team

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Speaker 11: different ideas and present different perspectives without being misaligned. I

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Speaker 11: know alignment is a big term in the AI world,

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Speaker 11: but just kind of contributing to a different set of

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Speaker 11: perspectives that can kind of be a force for good

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Speaker 11: while not holding back the technology.

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Speaker 4: Sarah As, Professor of Government and Director of the Technolicy

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Speaker 4: Institute at Cornell University.

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Speaker 2: Thank you so much.

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Speaker 4: This is Bloomberg Technology.

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Speaker 3: It's time to turn to the intersection of artificial intelligence

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Speaker 3: and healthcare. Phillips is exploring the technologies potential in when

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Speaker 3: of course, when it comes to wearables, imaging, hospital task automation.

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Speaker 5: We're pleased to welcome to the show.

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Speaker 3: Roy Yakovs is Phillips CEO, marking one year at the

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Speaker 3: helm of the company, a company that is now fully

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Speaker 3: focused on the medical use and healthcare applications, and AI

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Speaker 3: is a key driver in that. Just tell us how

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Speaker 3: already you're working with well the departments in some ways

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Speaker 3: of those that are looking at tracking using an or

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Speaker 3: ring or whether it be a garment watch, how are

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Speaker 3: you already working with governments and indeed consumers.

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Speaker 2: So we are in un monitoring business.

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Speaker 9: We have a wrong collaboration where we can actually include

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Speaker 9: all the data from any Apple devices or rings devices

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Speaker 9: that you're using in the house or in the home

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Speaker 9: to insert that into a patient context to understand how

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Speaker 9: that actually makes a better diagnosis or full patient picture.

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Speaker 9: Were also remotely monitoring in the home, for example, for

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Speaker 9: cardiac rhythm problems to early pick up signals that can

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Speaker 9: actually then prevent deterioration later. So bringing here to the

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Speaker 9: home is a big part of what we're doing, making

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Speaker 9: sure that actually we start the journey as early as

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Speaker 9: possible so that actually you can prevent deerioration. But then

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Speaker 9: also in the hospital we see that actually AI is

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Speaker 9: picking up very quickly. Just coming out of Chicago where

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Speaker 9: we had a very big show around how we can

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Speaker 9: improve imaging because there's a huge demand for more images.

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Speaker 9: But actually the hospital sector is really challenged to have

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Speaker 9: enough radiologist or technicians to do all the cats.

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Speaker 2: So that's where AI can come.

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Speaker 9: To the rescue to really make a productivity difference.

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Speaker 3: I think of how I use my connected wearables, and

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Speaker 3: some of that's to track my sleep. Now I want

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Speaker 3: to shift gears a little bit because there has been

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Speaker 3: a safety issue involving your dream Station two. This is

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Speaker 3: about sleep apnea and the machine there. The FDA having

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Speaker 3: a certain reports of overheating, worrying about fire smoke burns.

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Speaker 3: There's also been other concerns around just sleep at near products.

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Speaker 3: How are you tackling that as the CEO right now?

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Speaker 9: Yeah, when I came into the office, I said, first

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Speaker 9: priority is patient safety quality, so I put a world

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Speaker 9: class team on it to work through the challenges. We

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Speaker 9: also said we need to get very proactive and identifying

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Speaker 9: what is out here so that actually we can.

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Speaker 2: Address it and put the quality on up.

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Speaker 9: So it's about how we identify and then make sure

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Speaker 9: that we across the company provide the best quality care

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Speaker 9: and make sure that in the daily practices when we

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Speaker 9: work with customers and in the context that they have,

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Speaker 9: we can make sure that actually they can rely on

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Speaker 9: our products, so that's something we have doing in our strategy.

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Speaker 9: You also have seen that from the recent quarters we

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Speaker 9: have been seeing quite an uptake in the performance of

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Speaker 9: the company because we have.

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Speaker 2: Been able to start growing again. Now we have four

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Speaker 2: quarters of growth. We have up the guidance twice.

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Speaker 9: But also that what's under the premise that basic safety

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Speaker 9: and quality, supply chain improvements and simplification of the organization

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Speaker 9: are really important to drive better impact for care.

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Speaker 4: Mister Jacob's good morning from San Francisco. That issue, the

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Speaker 4: most recent was on the thermal issue of your current generation,

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Speaker 4: but it's kind of brought back the discussion about the

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Speaker 4: recall of two years ago over the polyphone deterioration.

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Speaker 2: There's a large body.

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Speaker 4: Of academic work that shows a latency in the cancers

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Speaker 4: that arise from exposure to deteriorating polyphone periods of twenty

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Speaker 4: to forty years down the road. Is Phillip's conscious of

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Speaker 4: that latency.

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Speaker 9: So we have done extensive testing towards the health risk

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Speaker 9: of degradation of the p perform. We've also come forward

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Speaker 9: with our testing which actually shown that there's no peaceable

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Speaker 9: harm from the usage of our devices. So that's something

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Speaker 9: that we have done over three period with very strong

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Speaker 9: evidence created together with the best scientific bodies, external bodies

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Speaker 9: and toxicologists to make sure that actually we have no

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Speaker 9: patients patient safety home for our users. Also from there,

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Speaker 9: we have been working with the whole group of healthcare

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Speaker 9: providers that we currently are addressing to make sure that

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Speaker 9: patient safety and quality is the first priority. That actually

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Speaker 9: also transmits into how you can use AI to improve

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Speaker 9: the daily practice of AI, because if you look at

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Speaker 9: what AI can do, actually can help you read and

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Speaker 9: interpret images in a more accurate fashion. Can also make

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Speaker 9: sure that the radiologists that are reading from home nowadays

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Speaker 9: seventy percent is reading from home, can get access to

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Speaker 9: the images and then make sure that they have the

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Speaker 9: propriate interpretation support with AI before and after their week miss.

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Speaker 4: The actives set aside one point one billion for remediation

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Speaker 4: and half a billion for law suits. Is that sufficient

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Speaker 4: or we have to add to that.

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Speaker 9: So we have been dealing with it. We call we

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Speaker 9: made great progress. We actually have now we mediated the

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Speaker 9: sleep patients and actually we are getting back into providing

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Speaker 9: sleep products outside of the US to our patients. So

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Speaker 9: we have provided for that that actually is also been

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Speaker 9: sufficient to date. We took economic loss provision early this

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Speaker 9: year that actually also will be evactuated next year. And

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Speaker 9: then if you look to how we are getting the

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Speaker 9: rest of Phillips to where it needs to be. We

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Speaker 9: have been making significant progress with the profitability that went up.

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Speaker 9: We have guided or increased our guidance now twice for

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Speaker 9: this year. We're heading towards six or seven percent growth

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Speaker 9: rate this year, both from health as well as from

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Speaker 9: the consumer health side. So we actually getting the company

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Speaker 9: back in to a growth and contributing level. And we

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Speaker 9: do that on the back of our innovations that have

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Speaker 9: real meaningful impact in the healthcare challenges of today where

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Speaker 9: they have a massive productivity gap that they need to address,

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Speaker 9: where our technology ANAI comes to the rescue.

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Speaker 3: Roy Jakobs, Solips CEO. Should we have more time? This

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Speaker 3: is Bloomberg Technology.

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Speaker 4: Welcome back to Bloomberg Technology. Ed Ludlow here in San Francisco,

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Speaker 4: cal and hired in New York.

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Speaker 3: Let's get a check on these markets, because halfway through

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Speaker 3: this training day, look.

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Speaker 5: A little bit of profit taking.

441
00:22:38,119 --> 00:22:40,040
Speaker 3: Maybe after we come off a stellar month and as

442
00:22:40,080 --> 00:22:42,440
Speaker 3: back had its best month since January, we're up about

443
00:22:42,480 --> 00:22:44,080
Speaker 3: ten percent. We pull back a little bit, but not

444
00:22:44,160 --> 00:22:45,800
Speaker 3: quite a percentage point, and then as that one hundred

445
00:22:45,840 --> 00:22:48,000
Speaker 3: off by nine ten seven percent, we're seeing the bond

446
00:22:48,000 --> 00:22:50,440
Speaker 3: market seeing significant action on the day at seven basis points.

447
00:22:50,440 --> 00:22:52,200
Speaker 5: But remember how far how fast.

448
00:22:51,920 --> 00:22:54,560
Speaker 3: We've come, basically the best month for the bond market

449
00:22:54,600 --> 00:22:56,679
Speaker 3: since the nineteen eighties. And therefore you're seeing this sort

450
00:22:56,720 --> 00:22:59,480
Speaker 3: of everything rally, risk assets pushing higher as everyone anticipates

451
00:22:59,520 --> 00:23:02,400
Speaker 3: a federal's that just cools down on its rate hiking path,

452
00:23:02,440 --> 00:23:04,639
Speaker 3: indeed starts cutting as soon as May. We're looking at

453
00:23:04,680 --> 00:23:06,480
Speaker 3: what's happening in the risk asset of choice in the

454
00:23:06,480 --> 00:23:08,800
Speaker 3: technology market, which is bitcoin. It's currently off by just

455
00:23:08,840 --> 00:23:10,520
Speaker 3: about a tenth of a percent as the dollar just

456
00:23:10,760 --> 00:23:12,480
Speaker 3: kicks up a little bit. Remember it's been a story

457
00:23:12,520 --> 00:23:14,959
Speaker 3: of dollar weakness on the month of November two. Move on,

458
00:23:15,040 --> 00:23:16,880
Speaker 3: look at some of the individual names that we're looking

459
00:23:16,920 --> 00:23:18,560
Speaker 3: at on the day, and look at shine a light

460
00:23:18,600 --> 00:23:20,840
Speaker 3: on some of the key movers like PDD what now

461
00:23:21,280 --> 00:23:24,520
Speaker 3: eight year old startup from China now worth more from

462
00:23:24,520 --> 00:23:28,119
Speaker 3: a market cap position versus Ali Baba more than one

463
00:23:28,160 --> 00:23:30,280
Speaker 3: hundred and eighty eight billion dollars. IT eclipses IT were

464
00:23:30,320 --> 00:23:32,359
Speaker 3: up three percent on the trading day. I'm looking at

465
00:23:32,359 --> 00:23:34,520
Speaker 3: what's happening also in terms of some numbers. Synopsis have

466
00:23:34,600 --> 00:23:37,320
Speaker 3: actually been doing well before the market opened. They then

467
00:23:37,400 --> 00:23:40,399
Speaker 3: pull back, even though they're managing to postgit gains. Remember,

468
00:23:40,440 --> 00:23:44,840
Speaker 3: this is all about electronic automatic this is about design, automation, design,

469
00:23:44,880 --> 00:23:47,119
Speaker 3: and particularly around the world of chips, they might be

470
00:23:47,160 --> 00:23:49,560
Speaker 3: selling off some parts of the business. So we're looking

471
00:23:49,560 --> 00:23:51,960
Speaker 3: at a currently a pullback of about three percent for

472
00:23:52,000 --> 00:23:54,280
Speaker 3: that particular business. And lastly, I'm looking what's happening with

473
00:23:54,359 --> 00:23:57,000
Speaker 3: in video, because we're all thinking about artificial intelligence and

474
00:23:57,040 --> 00:24:00,000
Speaker 3: chips and more generally, and it seems as though actually

475
00:24:00,000 --> 00:24:01,560
Speaker 3: a lot of these chip related names in the world

476
00:24:01,560 --> 00:24:03,800
Speaker 3: of artificial intelligence said I'm just offer a little bit

477
00:24:03,800 --> 00:24:06,360
Speaker 3: in video pulling back by some three percent as well.

478
00:24:06,560 --> 00:24:09,119
Speaker 4: Over g those are the public market moves. There are

479
00:24:09,119 --> 00:24:12,199
Speaker 4: big moves in private markets. Big Series A together AI

480
00:24:12,400 --> 00:24:16,080
Speaker 4: research driven AI company working for more open source models

481
00:24:16,080 --> 00:24:18,680
Speaker 4: and data sets, just raised one hundred and two point

482
00:24:18,680 --> 00:24:21,600
Speaker 4: five million dollars in a Series A round led by

483
00:24:21,640 --> 00:24:25,359
Speaker 4: Klina Perkins. Other investors who've participated in the round, including Nvidia,

484
00:24:25,600 --> 00:24:28,160
Speaker 4: Luxe Capital, Greycroft, and a few others you can see

485
00:24:28,160 --> 00:24:31,080
Speaker 4: there on your screen. Clina Perkins partner Bucky Moore and

486
00:24:31,160 --> 00:24:34,560
Speaker 4: Vple Bedpra Cash, CEO and co founder together Ai, both

487
00:24:34,560 --> 00:24:37,960
Speaker 4: here with us in San Francisco. You want to offer

488
00:24:38,000 --> 00:24:40,920
Speaker 4: a place where you can take a custom model, an

489
00:24:40,960 --> 00:24:44,480
Speaker 4: open source model and build it affordably. I think Bedrock

490
00:24:44,560 --> 00:24:47,560
Speaker 4: aws because of this week and what's been in the newsflow.

491
00:24:48,240 --> 00:24:49,400
Speaker 2: What are you trying to build?

492
00:24:50,240 --> 00:24:53,359
Speaker 1: First? Thank you so much for having us here together.

493
00:24:53,520 --> 00:24:55,760
Speaker 1: We believe open source is a big part of the

494
00:24:56,040 --> 00:24:59,560
Speaker 1: ICs future. So what we've built is a very optimized

495
00:25:00,040 --> 00:25:04,240
Speaker 1: out platform for buildings some data AI applications on open

496
00:25:04,320 --> 00:25:07,959
Speaker 1: and custom models. You know, we provide APIs where if

497
00:25:08,000 --> 00:25:10,200
Speaker 1: we have hundreds of models to feed packaged the user's

498
00:25:10,200 --> 00:25:12,600
Speaker 1: going to use, and we provide for best in class

499
00:25:12,680 --> 00:25:16,679
Speaker 1: tools to allow companies to build their models from scratch

500
00:25:16,840 --> 00:25:18,840
Speaker 1: or take an open model and bap them with find

501
00:25:18,880 --> 00:25:20,000
Speaker 1: doing for their purposes.

502
00:25:20,480 --> 00:25:23,560
Speaker 4: Bucky, it's a big check, a few checks for a

503
00:25:23,600 --> 00:25:26,480
Speaker 4: series A. You know this space better than many you're

504
00:25:26,480 --> 00:25:29,359
Speaker 4: taking on the hyper scalas and you're trying to offer

505
00:25:29,400 --> 00:25:33,040
Speaker 4: something at a better price than they are. But you're

506
00:25:33,080 --> 00:25:35,520
Speaker 4: confident that this gather AI can do that.

507
00:25:36,680 --> 00:25:38,639
Speaker 12: So you've been covering this space for a reason. This

508
00:25:38,760 --> 00:25:41,119
Speaker 12: is a fundamentally new form of computing that is going

509
00:25:41,160 --> 00:25:43,600
Speaker 12: to be as disruptive as internet and mobile and with

510
00:25:43,680 --> 00:25:47,639
Speaker 12: respect it together like an OS basically absolutely and with

511
00:25:47,720 --> 00:25:50,080
Speaker 12: respect it together. What we're seeing as enterprises are now

512
00:25:50,119 --> 00:25:52,080
Speaker 12: leaning in and wanting to build on these open source

513
00:25:52,119 --> 00:25:54,359
Speaker 12: and custom models, and to do that, they're going to

514
00:25:54,359 --> 00:25:56,600
Speaker 12: need a platform upon which these models can run, and

515
00:25:56,640 --> 00:25:58,000
Speaker 12: we think Together's that platform.

516
00:25:58,760 --> 00:26:04,480
Speaker 3: I'm interested from your perspective, what we like to categorize

517
00:26:04,480 --> 00:26:07,760
Speaker 3: perhaps in the media is this tension between open source

518
00:26:08,240 --> 00:26:11,440
Speaker 3: and closed models. And I mean, the open source movement

519
00:26:11,480 --> 00:26:14,000
Speaker 3: is as old as software itself Forbell, but I am

520
00:26:14,080 --> 00:26:16,840
Speaker 3: interested in the perhaps car crash of a story that

521
00:26:16,880 --> 00:26:19,040
Speaker 3: we had a couple of weeks ago around open AI.

522
00:26:19,160 --> 00:26:23,159
Speaker 3: Suddenly corporates are thinking about business continuity, about ensuring that

523
00:26:23,200 --> 00:26:25,760
Speaker 3: perhaps they're not dependent on one particular LL and provider.

524
00:26:26,119 --> 00:26:28,919
Speaker 3: Has that changed in the conversations you're having.

525
00:26:28,640 --> 00:26:34,080
Speaker 1: With corporates, I would say it certainly illustrates the need

526
00:26:34,160 --> 00:26:38,440
Speaker 1: for a choice. You know, companies that are building the

527
00:26:38,600 --> 00:26:42,000
Speaker 1: strategies around and radio AI want control of their models.

528
00:26:42,000 --> 00:26:45,399
Speaker 1: They want to own the output of their efforts, and

529
00:26:45,760 --> 00:26:46,840
Speaker 1: open source is.

530
00:26:48,400 --> 00:26:49,560
Speaker 2: It's a great way of doing that.

531
00:26:51,160 --> 00:26:56,480
Speaker 3: Okay, from your perspective, can be more resource intentive though,

532
00:26:56,880 --> 00:26:59,600
Speaker 3: to sort of manage your open source code in some way.

533
00:26:59,640 --> 00:27:03,320
Speaker 3: And I'm interested in how companies are really going to

534
00:27:03,400 --> 00:27:05,840
Speaker 3: end up aligning when it comes to their own proprietary

535
00:27:05,960 --> 00:27:08,520
Speaker 3: data and building on these open source models.

536
00:27:09,920 --> 00:27:12,600
Speaker 12: So, first of all, open source AI is really history

537
00:27:12,640 --> 00:27:15,840
Speaker 12: repeating itself. Business has been leveraging open source in the

538
00:27:15,840 --> 00:27:18,479
Speaker 12: form of databases and other core underpaintings of how they

539
00:27:18,480 --> 00:27:21,440
Speaker 12: develop their software for decades. So again, this is history

540
00:27:21,440 --> 00:27:23,960
Speaker 12: repeating itself. And in that sense, yes, there is some

541
00:27:24,080 --> 00:27:26,199
Speaker 12: operational burden that a company has to take on to

542
00:27:26,320 --> 00:27:29,119
Speaker 12: leverage open source relative to a managed service, but this

543
00:27:29,160 --> 00:27:31,600
Speaker 12: is precisely where Together's technology comes in. They want to

544
00:27:31,640 --> 00:27:33,520
Speaker 12: make that piece easy and take it off the hands

545
00:27:33,520 --> 00:27:35,880
Speaker 12: of enterprises so they can realize all those benefits without

546
00:27:35,880 --> 00:27:36,840
Speaker 12: the operational burden.

547
00:27:37,200 --> 00:27:41,439
Speaker 4: Vivo, You've got Nvideo as an investor, fantastic, but have

548
00:27:41,480 --> 00:27:43,280
Speaker 4: you got them as a technology partners? You have a

549
00:27:43,320 --> 00:27:45,560
Speaker 4: big old bag of h one hundreds that you can

550
00:27:45,600 --> 00:27:47,000
Speaker 4: sling over the shoulder.

551
00:27:46,680 --> 00:27:48,080
Speaker 2: And call it a day.

552
00:27:48,280 --> 00:27:51,439
Speaker 1: Everyone wants that, right, you know, the other technology partner

553
00:27:51,520 --> 00:27:54,919
Speaker 1: and Ridia is really a leading company the space. I

554
00:27:54,920 --> 00:27:59,359
Speaker 1: would say they have the platform today for AI everywhere.

555
00:27:59,400 --> 00:28:00,720
Speaker 2: Well, what are there er options to you?

556
00:28:00,800 --> 00:28:03,439
Speaker 4: I mean, I guess considering what you're trying to build

557
00:28:03,600 --> 00:28:08,520
Speaker 4: right the whole business offering from you, were there any

558
00:28:08,560 --> 00:28:11,560
Speaker 4: alternatives other than Nvidia to get the compute needed to

559
00:28:11,560 --> 00:28:12,560
Speaker 4: build a platform like that?

560
00:28:13,080 --> 00:28:13,320
Speaker 2: To day?

561
00:28:15,119 --> 00:28:17,960
Speaker 1: We get a lot about price performance. So the services

562
00:28:17,960 --> 00:28:21,480
Speaker 1: we provide for our infant service are six times cheaper

563
00:28:21,520 --> 00:28:24,560
Speaker 1: than Opening Eyes, our training services are four times cheaper

564
00:28:24,560 --> 00:28:26,600
Speaker 1: than AWS, and we're able to do.

565
00:28:26,640 --> 00:28:30,560
Speaker 4: More times cheaper than AWS. Can you absolutely guarantee.

566
00:28:30,000 --> 00:28:33,879
Speaker 1: That, absolutely guarantee that yes. And this is both a

567
00:28:33,960 --> 00:28:38,480
Speaker 1: combination of our hardware stack as well as the software

568
00:28:38,520 --> 00:28:42,280
Speaker 1: that we have both on it make training and infence more.

569
00:28:42,120 --> 00:28:43,920
Speaker 5: Efficient, Buckie.

570
00:28:44,640 --> 00:28:48,800
Speaker 3: There has been much said about the hype dare we

571
00:28:48,880 --> 00:28:49,239
Speaker 3: call it?

572
00:28:49,360 --> 00:28:53,640
Speaker 5: Around artificial intelligence? What draws you to a team like People's.

573
00:28:53,800 --> 00:28:54,560
Speaker 5: Is it talent?

574
00:28:54,720 --> 00:28:56,720
Speaker 3: Is it what they've already been putting out there in

575
00:28:56,800 --> 00:29:00,040
Speaker 3: terms of innovation? Isn't how they look there to be

576
00:29:00,200 --> 00:29:02,440
Speaker 3: using a very large check that you've all managed to

577
00:29:02,440 --> 00:29:02,920
Speaker 3: put together.

578
00:29:04,480 --> 00:29:06,440
Speaker 12: So Caroline, when we've thought through what it takes to

579
00:29:06,560 --> 00:29:10,120
Speaker 12: emerge as the leading provider of platform infrastructure for all

580
00:29:10,120 --> 00:29:12,320
Speaker 12: of these businesses who we believe will be leaning in

581
00:29:12,400 --> 00:29:15,160
Speaker 12: on open source and custom models, we really think it

582
00:29:15,200 --> 00:29:18,800
Speaker 12: requires this unique combination of systems engineering and research talent,

583
00:29:18,840 --> 00:29:20,360
Speaker 12: and both of those have to come together in a

584
00:29:20,400 --> 00:29:23,160
Speaker 12: world class way to really build that market leading product.

585
00:29:23,400 --> 00:29:25,280
Speaker 12: And together is the first company we've seen that really

586
00:29:25,280 --> 00:29:27,520
Speaker 12: brings that to the marketplace in that manner, and that's

587
00:29:27,520 --> 00:29:28,880
Speaker 12: why we're so proud to be their partner.

588
00:29:29,720 --> 00:29:34,440
Speaker 3: Fiple the money, what will be allocated towards talent? How

589
00:29:34,480 --> 00:29:36,640
Speaker 3: expensive is talent at the moment and is it all

590
00:29:36,680 --> 00:29:40,360
Speaker 3: being brought together to bear where you sit now over

591
00:29:40,400 --> 00:29:42,640
Speaker 3: on the West coast or are you're looking more geographically?

592
00:29:44,840 --> 00:29:45,040
Speaker 11: You know?

593
00:29:45,160 --> 00:29:49,000
Speaker 1: The capital one we are going to do deep investments

594
00:29:49,040 --> 00:29:49,720
Speaker 1: and product.

595
00:29:51,680 --> 00:29:52,880
Speaker 2: You know what as.

596
00:29:52,920 --> 00:29:56,480
Speaker 1: Keeper is saying, we have a very deep research effort.

597
00:29:56,560 --> 00:30:01,160
Speaker 1: We have a research company. We invest a lot, you know,

598
00:30:01,360 --> 00:30:06,040
Speaker 1: corea research to build better models, build better model architectures,

599
00:30:06,120 --> 00:30:10,280
Speaker 1: build better data sets, and a little better platform. So

600
00:30:10,360 --> 00:30:13,000
Speaker 1: that will be a known investment. And yes, I think

601
00:30:13,120 --> 00:30:15,000
Speaker 1: the talent.

602
00:30:14,760 --> 00:30:21,000
Speaker 2: Market is you know, very tight today. But we have

603
00:30:22,320 --> 00:30:22,760
Speaker 2: some of.

604
00:30:22,640 --> 00:30:25,959
Speaker 1: The sort of leading researchers in the space are our

605
00:30:26,040 --> 00:30:28,720
Speaker 1: co founders and part of the company and that really

606
00:30:29,040 --> 00:30:32,560
Speaker 1: helps bring together the research community and have them attached

607
00:30:32,560 --> 00:30:33,120
Speaker 1: to the company.

608
00:30:33,360 --> 00:30:36,640
Speaker 4: But you always find interesting is the rationale of making

609
00:30:36,680 --> 00:30:38,600
Speaker 4: investment based on what's put in front of you right

610
00:30:38,680 --> 00:30:41,880
Speaker 4: with the greatest respects together. AI is not a massive company.

611
00:30:42,520 --> 00:30:44,800
Speaker 4: How much weight do you put on the individuals they have?

612
00:30:44,840 --> 00:30:48,800
Speaker 4: From a talent perspective, everyone's got GPUs. There are very

613
00:30:48,840 --> 00:30:51,720
Speaker 4: few data scientists or engineers that can actually make them

614
00:30:51,760 --> 00:30:53,280
Speaker 4: work from what I understand.

615
00:30:54,400 --> 00:30:56,520
Speaker 12: So look at this stage, startups are all about the

616
00:30:56,560 --> 00:30:58,680
Speaker 12: people behind them, and this is a world class team.

617
00:30:58,680 --> 00:31:01,040
Speaker 12: As I said, that brings together this unique combination of

618
00:31:01,080 --> 00:31:03,800
Speaker 12: systems engineering and research talent that we think is the

619
00:31:03,800 --> 00:31:05,920
Speaker 12: most potent combination to go and build a market leading

620
00:31:05,920 --> 00:31:07,920
Speaker 12: company in this space. And that's what we're excited about here.

621
00:31:08,000 --> 00:31:09,440
Speaker 2: I just asked you both very quickly.

622
00:31:09,800 --> 00:31:12,680
Speaker 4: It is one year to the date day since chatjept

623
00:31:13,160 --> 00:31:16,240
Speaker 4: was released. For Paul, how has the last twelve months

624
00:31:16,360 --> 00:31:19,240
Speaker 4: changed or accelerated what you've tried to do in AI?

625
00:31:19,560 --> 00:31:22,240
Speaker 1: I think it has act beautiful a moment that made

626
00:31:22,240 --> 00:31:25,360
Speaker 1: it very clear with a power of foundation models and

627
00:31:25,400 --> 00:31:29,440
Speaker 1: their applicability, and that's really sort of you know, created

628
00:31:29,560 --> 00:31:34,600
Speaker 1: a huge market around and interest in large and rated models.

629
00:31:36,000 --> 00:31:37,520
Speaker 5: Fascinating from both of you.

630
00:31:37,920 --> 00:31:40,160
Speaker 3: Always bucking more with your seeing around corners when it

631
00:31:40,160 --> 00:31:42,440
Speaker 3: comes to infrastructure in the future thereof particularly when it

632
00:31:42,440 --> 00:31:44,360
Speaker 3: comes to the world of AI. We thank you Kleine

633
00:31:44,440 --> 00:31:48,040
Speaker 3: Perkins partner there and vivill Read Pracash of course CEO

634
00:31:48,080 --> 00:31:51,320
Speaker 3: and co found together AI with that one hundred point

635
00:31:51,360 --> 00:31:54,560
Speaker 3: to five million Series A. Meanwhile, coming up, let's talk

636
00:31:54,600 --> 00:31:57,200
Speaker 3: about the social media and well got to think about

637
00:31:57,240 --> 00:32:00,560
Speaker 3: how it implicates child safety online. We're going to be

638
00:32:00,640 --> 00:32:03,160
Speaker 3: talking about how tech CEOs have been called to Capitol

639
00:32:03,240 --> 00:32:05,880
Speaker 3: Hill to testify on exploitation.

640
00:32:05,440 --> 00:32:08,760
Speaker 4: At I'm taking a quick check on shares of Meta

641
00:32:08,960 --> 00:32:11,600
Speaker 4: down more than two percent. The whole market kind of

642
00:32:11,600 --> 00:32:14,280
Speaker 4: took a weird turn at some point in the session.

643
00:32:14,360 --> 00:32:17,400
Speaker 4: But the company plans to appeal a district court decision

644
00:32:17,440 --> 00:32:21,560
Speaker 4: rejecting its attempt to block the FTC from modifying a

645
00:32:21,600 --> 00:32:24,960
Speaker 4: twenty twenty settlement with the agency that required the company

646
00:32:25,200 --> 00:32:28,320
Speaker 4: to update its privacy practices. Something that's playing out in

647
00:32:28,360 --> 00:32:30,720
Speaker 4: court and drawing no cause or link, but it is

648
00:32:30,760 --> 00:32:36,360
Speaker 4: interesting to see meta under pressure. This has been Bow Technology.

649
00:32:50,120 --> 00:32:50,520
Speaker 2: All right.

650
00:32:50,600 --> 00:32:53,920
Speaker 4: Time for talking at tech. First up, move over Ali Barber.

651
00:32:54,160 --> 00:32:57,240
Speaker 4: It's lost its spot as China's most valuable e commerce

652
00:32:57,280 --> 00:33:00,240
Speaker 4: company to Pinned wod Woe, best known for its opping

653
00:33:00,240 --> 00:33:02,560
Speaker 4: apps Timu and pinned Woad wide. The eight year old

654
00:33:02,600 --> 00:33:05,800
Speaker 4: PDD has gained more traction with investors, while growth for

655
00:33:05,880 --> 00:33:08,760
Speaker 4: Jack Mars Ali Baba has softened. A big story of

656
00:33:08,800 --> 00:33:11,240
Speaker 4: the week and if you're a fan of NASCAR, you'll

657
00:33:11,240 --> 00:33:13,800
Speaker 4: now be able to stream the racing sport online. NASCAR

658
00:33:14,080 --> 00:33:17,080
Speaker 4: sign deals with Amazon and Warner Brothers Discovery to show

659
00:33:17,080 --> 00:33:21,000
Speaker 4: its races on their respective Prime Video and Max streaming platforms.

660
00:33:21,000 --> 00:33:25,440
Speaker 4: The deal reportedly valued at seven point eight billion dollars plus.

661
00:33:25,720 --> 00:33:28,360
Speaker 4: Morgan Stanley CEO James Gorman will now have a seat

662
00:33:28,400 --> 00:33:31,560
Speaker 4: on Walt Disney's board of directors. Gorman's appointment will take

663
00:33:31,600 --> 00:33:34,440
Speaker 4: effect on February fifth, twenty twenty four. The move comes

664
00:33:34,480 --> 00:33:38,440
Speaker 4: ahead of an expected proxy fight and amid reports of

665
00:33:38,440 --> 00:33:42,240
Speaker 4: interests in a board seat from billionaire Nelson Pelts. Veteran

666
00:33:42,280 --> 00:33:45,600
Speaker 4: media executive Jeremy Dearrek will also be appointed to Disney's

667
00:33:45,600 --> 00:33:47,560
Speaker 4: board effective January nine.

668
00:33:47,560 --> 00:33:50,080
Speaker 2: A former Sky CEO, carro.

669
00:33:50,840 --> 00:33:53,600
Speaker 3: Let's take a turn and talk about some of the

670
00:33:53,640 --> 00:33:57,120
Speaker 3: other executives across the technology at large right now, but

671
00:33:57,120 --> 00:33:59,200
Speaker 3: in particularly the CEO is a matter of ex a TikTok,

672
00:33:59,240 --> 00:34:01,800
Speaker 3: a snap of disc They've all just been summoned dead

673
00:34:01,840 --> 00:34:04,240
Speaker 3: by the Senate Judiciary Committee to testify at a hearing

674
00:34:04,280 --> 00:34:06,880
Speaker 3: on child sexual exploitation that's now been given the date

675
00:34:07,280 --> 00:34:10,880
Speaker 3: of January. This comes just a few weeks after Meta,

676
00:34:10,960 --> 00:34:13,440
Speaker 3: of course, was sued by California group of more than

677
00:34:13,520 --> 00:34:15,760
Speaker 3: thirty states have a claims that its social media platforms

678
00:34:15,800 --> 00:34:19,680
Speaker 3: exploit youths for profit and feed them harmful content. It's

679
00:34:19,680 --> 00:34:21,440
Speaker 3: a sensitive discussion and we're going to have it with

680
00:34:21,480 --> 00:34:25,560
Speaker 3: Camille Carton, Center of Humane Technology Senior policy manager, And

681
00:34:25,600 --> 00:34:27,520
Speaker 3: all of this comes at a time no matter where

682
00:34:27,520 --> 00:34:30,200
Speaker 3: you're seeing the lawsuits coming from, whether they're families, whether

683
00:34:30,200 --> 00:34:33,959
Speaker 3: they're coming from of course ultimately ages, whether they're coming

684
00:34:34,040 --> 00:34:38,400
Speaker 3: from a federal level, all of them are they likely

685
00:34:38,560 --> 00:34:42,799
Speaker 3: to disrupt the business models of these companies enough that

686
00:34:42,880 --> 00:34:46,080
Speaker 3: we do see greater protection in whatever guys you might

687
00:34:46,120 --> 00:34:48,160
Speaker 3: want to see it happen whether it's internally if you're

688
00:34:48,160 --> 00:34:51,240
Speaker 3: working at the company, or externally using their products.

689
00:34:51,280 --> 00:34:53,040
Speaker 13: I think what we're seeing right now is that we

690
00:34:53,080 --> 00:34:55,960
Speaker 13: are absolutely at an inflection point, which is what you

691
00:34:56,160 --> 00:35:01,240
Speaker 13: just described. Whether it's research that has been done by whistleblowers,

692
00:35:02,040 --> 00:35:06,760
Speaker 13: researchers themselves, whether it's the lawsuits from ags, from parents,

693
00:35:06,880 --> 00:35:11,800
Speaker 13: school districts, we are just seeing overwhelming kind of support

694
00:35:12,080 --> 00:35:15,440
Speaker 13: for these platforms to take on much more responsibility, for

695
00:35:15,520 --> 00:35:18,560
Speaker 13: them to be accountable to their actions, and for them

696
00:35:18,600 --> 00:35:21,600
Speaker 13: to change the way that they design their products. Right now,

697
00:35:21,719 --> 00:35:26,000
Speaker 13: these products are designed to capitalize on children's vulnerabilities, the

698
00:35:26,040 --> 00:35:29,680
Speaker 13: things that make their development different than older users, and

699
00:35:29,719 --> 00:35:33,160
Speaker 13: we know this from these disclosures, and so that's exactly

700
00:35:33,200 --> 00:35:35,880
Speaker 13: what people are looking for when they're going through with

701
00:35:35,960 --> 00:35:37,959
Speaker 13: these lawsuits and with these testimonies.

702
00:35:38,400 --> 00:35:40,520
Speaker 3: When we think of the testimonies, we think, if Judge

703
00:35:40,680 --> 00:35:43,080
Speaker 3: von Rogers has allowed them to proceed in some way,

704
00:35:43,360 --> 00:35:46,600
Speaker 3: many would say, actually, the decisions that they've made means that.

705
00:35:46,560 --> 00:35:48,760
Speaker 5: Much business model disruption won't happen.

706
00:35:48,800 --> 00:35:51,200
Speaker 3: The fact that the endless scrolling isn't going to be

707
00:35:51,280 --> 00:35:53,320
Speaker 3: something that's focused on but it will be more about

708
00:35:53,360 --> 00:35:56,920
Speaker 3: protection and ultimately oversight from parents.

709
00:35:57,480 --> 00:35:58,880
Speaker 5: Is that going to be enough? And how do you

710
00:35:58,920 --> 00:36:00,480
Speaker 5: think if you think about.

711
00:36:00,239 --> 00:36:02,480
Speaker 3: The other side, what Meta and other companies would say

712
00:36:02,520 --> 00:36:04,759
Speaker 3: is what we're building isn't wrong.

713
00:36:04,800 --> 00:36:06,360
Speaker 5: It's the way in which you mounted to use is

714
00:36:06,400 --> 00:36:07,640
Speaker 5: it that is wrong?

715
00:36:07,920 --> 00:36:10,920
Speaker 3: How can we get a better balance between the two.

716
00:36:11,239 --> 00:36:13,040
Speaker 13: So I think the most important thing is to look

717
00:36:13,080 --> 00:36:16,840
Speaker 13: at the incentives. Right These companies right now are incentivized

718
00:36:16,840 --> 00:36:20,200
Speaker 13: to design their products with profits first. But we have

719
00:36:20,440 --> 00:36:23,440
Speaker 13: tons of legislative solutions out there. We have COSA at

720
00:36:23,440 --> 00:36:27,080
Speaker 13: the federal level that has over fifty bipartisan co sponsors.

721
00:36:27,400 --> 00:36:29,840
Speaker 13: We have the Age Appropriate Design Code that's been in

722
00:36:29,880 --> 00:36:33,320
Speaker 13: place in the UK was introducing California you mentioned Judge

723
00:36:33,960 --> 00:36:37,520
Speaker 13: von Rogers. These solutions look at actually changing the way

724
00:36:37,640 --> 00:36:41,000
Speaker 13: these platforms are designed. They look at how can we

725
00:36:41,080 --> 00:36:44,600
Speaker 13: change these platforms so that kids' best interests are put

726
00:36:44,719 --> 00:36:49,200
Speaker 13: forth first. They focus on privacy, they focus on changing

727
00:36:49,239 --> 00:36:52,560
Speaker 13: features that are addictive, and they also provide a duty

728
00:36:52,600 --> 00:36:56,800
Speaker 13: of care, basically requiring platforms to prioritize the best interests

729
00:36:56,800 --> 00:36:59,439
Speaker 13: of kids over profits. And I think that's the best

730
00:36:59,440 --> 00:37:00,279
Speaker 13: way forward here.

731
00:37:01,800 --> 00:37:02,280
Speaker 2: Camille.

732
00:37:02,520 --> 00:37:05,880
Speaker 4: Your position, and it's shared by others, is that social

733
00:37:05,920 --> 00:37:10,400
Speaker 4: media platforms are deliberately designed as pieces of technology to

734
00:37:10,440 --> 00:37:13,200
Speaker 4: be addictive to children and teenagers.

735
00:37:13,480 --> 00:37:14,359
Speaker 2: Have I got that right?

736
00:37:14,760 --> 00:37:15,040
Speaker 5: Yes.

737
00:37:16,440 --> 00:37:19,640
Speaker 4: TikTok is an example, set out a policy in March.

738
00:37:19,719 --> 00:37:22,920
Speaker 4: That policy was that you have to be age thirteen

739
00:37:23,719 --> 00:37:26,560
Speaker 4: or a different age at least depending on local law

740
00:37:26,640 --> 00:37:31,399
Speaker 4: restrictions to use the platform. Aside from legislation and the

741
00:37:31,440 --> 00:37:36,920
Speaker 4: policies of companies like TikTok, what fixes would you recommend

742
00:37:37,480 --> 00:37:41,960
Speaker 4: to safeguard teens and children? What technological solutions are there?

743
00:37:42,480 --> 00:37:46,239
Speaker 13: Yeah, this is a great question, and TikTok has this

744
00:37:46,400 --> 00:37:50,279
Speaker 13: policy as well as Facebook and many other platforms. But

745
00:37:50,840 --> 00:37:53,719
Speaker 13: what we're learning from many of these disclosures related to

746
00:37:54,120 --> 00:37:58,520
Speaker 13: the Attorney's general investigation is, for instance, Meta actually knows

747
00:37:58,640 --> 00:38:02,600
Speaker 13: that they have millions of underage users. They have millions

748
00:38:02,640 --> 00:38:04,799
Speaker 13: of users under the age of thirteen, which is in

749
00:38:04,880 --> 00:38:06,680
Speaker 13: violation of that are a law that they are collecting

750
00:38:06,760 --> 00:38:10,280
Speaker 13: data on. Not only do they know this, they are

751
00:38:10,320 --> 00:38:13,200
Speaker 13: taking great lengths to make sure that the public doesn't

752
00:38:13,239 --> 00:38:15,840
Speaker 13: know that they know this, and they're studying these users,

753
00:38:16,160 --> 00:38:20,400
Speaker 13: they're capitalizing on these users. So these platforms already have

754
00:38:20,480 --> 00:38:23,759
Speaker 13: a way of knowing who is and isn't on their platform,

755
00:38:24,080 --> 00:38:26,160
Speaker 13: but they're choosing not to do anything about it, and

756
00:38:26,200 --> 00:38:29,480
Speaker 13: they're choosing not to make sure that underage users are

757
00:38:29,480 --> 00:38:32,000
Speaker 13: not accessing products that are not built for them.

758
00:38:33,520 --> 00:38:35,560
Speaker 2: In January, on January.

759
00:38:35,200 --> 00:38:38,799
Speaker 4: The thirty first, I believe a number of CEOs will

760
00:38:38,800 --> 00:38:43,000
Speaker 4: go to Capitol Hill for a Senate hearing. When executives

761
00:38:43,000 --> 00:38:46,000
Speaker 4: go before lawmakers. What is it that you hope comes

762
00:38:46,040 --> 00:38:48,520
Speaker 4: out of public hearings like that? How does it move

763
00:38:48,760 --> 00:38:51,200
Speaker 4: the agenda forward?

764
00:38:51,480 --> 00:38:53,759
Speaker 13: I think that this is a really big opportunity for

765
00:38:53,840 --> 00:38:58,200
Speaker 13: policymakers to push these executives on the fact that they

766
00:38:58,320 --> 00:39:00,920
Speaker 13: know they have users that are on their platform that

767
00:39:00,960 --> 00:39:02,960
Speaker 13: are not supposed to be the fact that we now

768
00:39:03,000 --> 00:39:06,680
Speaker 13: have evidence that they are intentionally designing products in ways

769
00:39:06,719 --> 00:39:10,959
Speaker 13: that are harmful to users. For instance, Artur Bihar, who

770
00:39:11,200 --> 00:39:15,759
Speaker 13: was the most recent metawhistleblower, shared that one in eight

771
00:39:16,160 --> 00:39:20,960
Speaker 13: young users under the age of sixteen experienced unwanted sexual advances,

772
00:39:21,440 --> 00:39:24,560
Speaker 13: and despite Meta knowing this, instead of designing a reporting

773
00:39:24,600 --> 00:39:28,440
Speaker 13: mechanism for users to be able to report this to Facebook,

774
00:39:30,040 --> 00:39:33,000
Speaker 13: sorry to Instagram, for Instagram to be able to fix

775
00:39:33,080 --> 00:39:36,240
Speaker 13: what was going on, they intentionally designed a reporting flow

776
00:39:36,400 --> 00:39:39,080
Speaker 13: that was really hard for users. It took a lot

777
00:39:39,080 --> 00:39:41,520
Speaker 13: of effort, it was really long, and they took out

778
00:39:41,520 --> 00:39:45,200
Speaker 13: all human oversight. So young users are essentially not incentivized

779
00:39:45,200 --> 00:39:47,680
Speaker 13: to report this anymore because the company doesn't do anything

780
00:39:47,880 --> 00:39:50,160
Speaker 13: and the company is no longer being flagged about these

781
00:39:50,160 --> 00:39:52,960
Speaker 13: issues that are happening. So I hope that these sessions

782
00:39:53,000 --> 00:39:55,319
Speaker 13: we can actually get to the bottom of the fact

783
00:39:55,320 --> 00:39:58,320
Speaker 13: that these companies know that some of the product designs

784
00:39:58,360 --> 00:40:02,200
Speaker 13: are harmful and that we need to end this practice.

785
00:40:02,920 --> 00:40:06,640
Speaker 3: Camilla, I'm sure we will go forth to these companies'

786
00:40:06,680 --> 00:40:09,480
Speaker 3: leadership and say as to how they have been responding,

787
00:40:09,520 --> 00:40:12,640
Speaker 3: because I'm sure they'd like to say a response to

788
00:40:12,719 --> 00:40:15,000
Speaker 3: us to all whether or not indeed they have been

789
00:40:15,040 --> 00:40:17,279
Speaker 3: trying to make it more or less difficult for these

790
00:40:17,320 --> 00:40:19,880
Speaker 3: sorts of things to be reported. But Camille Carston, we

791
00:40:19,920 --> 00:40:22,040
Speaker 3: thank you so much for your insights the Center of

792
00:40:22,080 --> 00:40:24,760
Speaker 3: Humane Technology, of course, and we'd.

793
00:40:24,560 --> 00:40:26,520
Speaker 5: Potentially like to be getting back ahead of that. January

794
00:40:26,520 --> 00:40:29,200
Speaker 5: the thirty first up on Capitol.

795
00:40:28,880 --> 00:40:41,439
Speaker 4: Hill, Robin Hood's making its international debut, launching commission free

796
00:40:41,560 --> 00:40:44,480
Speaker 4: stock trading in the UK. The firm has started rolling

797
00:40:44,520 --> 00:40:47,520
Speaker 4: out trading of more than six thousand US listed stocks

798
00:40:47,640 --> 00:40:51,000
Speaker 4: and other securities to British retail investors. CEO of vlad

799
00:40:51,000 --> 00:40:53,560
Speaker 4: Tenev spoke to Bloomberg's Tom McKenzie.

800
00:40:54,760 --> 00:41:00,640
Speaker 14: So we have products for customers that who have low

801
00:41:00,960 --> 00:41:03,799
Speaker 14: risk appetite for financial risk as well, and I think

802
00:41:03,800 --> 00:41:07,640
Speaker 14: we can serve their needs. But I think there's two

803
00:41:07,680 --> 00:41:10,880
Speaker 14: things we do exceptionally well in the US that carry

804
00:41:10,880 --> 00:41:15,520
Speaker 14: over in the UK despite any cultural differences. People in

805
00:41:15,560 --> 00:41:20,279
Speaker 14: the UK love easy to use, compelling mobile interfaces and

806
00:41:20,320 --> 00:41:24,680
Speaker 14: they love getting the best possible economics on investing in

807
00:41:24,760 --> 00:41:29,040
Speaker 14: other financial services. And I think these two things have

808
00:41:29,120 --> 00:41:33,120
Speaker 14: been the cornerstones of Robinhood product design and development. We

809
00:41:33,200 --> 00:41:38,680
Speaker 14: have really a beautiful our customers love the beautiful, almost

810
00:41:38,760 --> 00:41:42,719
Speaker 14: magical quality of the Robinhood experience, and they appreciate the

811
00:41:43,600 --> 00:41:46,680
Speaker 14: fact that they're getting industry leading economics. And when we

812
00:41:46,719 --> 00:41:49,400
Speaker 14: talk to customers in the UK, there's a lot of

813
00:41:49,560 --> 00:41:52,920
Speaker 14: enthusiasm over bringing these things to this market.

814
00:41:53,200 --> 00:41:55,680
Speaker 15: As crypto bottom do you think and is it what's

815
00:41:55,680 --> 00:41:58,880
Speaker 15: still being in the crypto space given what's happened with

816
00:41:58,880 --> 00:42:01,359
Speaker 15: the likes of Finance and an FTX, or is that

817
00:42:01,400 --> 00:42:04,120
Speaker 15: an opportunity for robin Hood to take market share.

818
00:42:04,640 --> 00:42:09,319
Speaker 14: I think in the long run, it's certainly an opportunity

819
00:42:09,640 --> 00:42:13,600
Speaker 14: and it's good for the industry to have unscrupulous actors

820
00:42:13,640 --> 00:42:18,000
Speaker 14: weeded out and kind of falling off, because I think

821
00:42:18,040 --> 00:42:21,320
Speaker 14: in order for the industry and the technology to become

822
00:42:22,200 --> 00:42:26,880
Speaker 14: truly globally accepted, there has to be a foundation of

823
00:42:26,920 --> 00:42:30,040
Speaker 14: regulatory compliance and it has to be integrated more and

824
00:42:30,080 --> 00:42:34,560
Speaker 14: more into the traditional financial system and help solve real

825
00:42:34,600 --> 00:42:40,080
Speaker 14: problems for people. So Robinhood continues to build crypto technology

826
00:42:40,120 --> 00:42:42,680
Speaker 14: and be a leader there. We've been pleased with the

827
00:42:42,719 --> 00:42:46,239
Speaker 14: growing market share we've been seeing in the US even

828
00:42:46,239 --> 00:42:51,279
Speaker 14: through the winter, and as you probably know, in the UK,

829
00:42:51,800 --> 00:42:56,200
Speaker 14: we're not launching with crypto. We're very focused on US

830
00:42:56,360 --> 00:42:59,920
Speaker 14: shares and the high interest product with no FX fees,

831
00:43:01,320 --> 00:43:04,560
Speaker 14: but we are also expanding in the EU and we

832
00:43:04,640 --> 00:43:07,360
Speaker 14: will have a crypto available in the EU in the

833
00:43:07,360 --> 00:43:08,160
Speaker 14: coming weeks.

834
00:43:08,520 --> 00:43:11,480
Speaker 5: How does it for this edition of Bloomberg Technology.

835
00:43:11,040 --> 00:43:15,239
Speaker 4: Yet Bloomberg Technology Podcast. Check it out wherever you get

836
00:43:15,280 --> 00:43:18,239
Speaker 4: your podcasts. From New York City and SF. This is

837
00:43:18,280 --> 00:43:19,360
Speaker 4: Bloomberg Technology