WEBVTT - The Crypto Market and AI's Impact on Jobs

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<v Speaker 1>We're from Marhart where Innovation, Money and power Collie in

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<v Speaker 1>Silicon Vallet NBN. This is Bloomberg Technology with Caroline Hyde

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<v Speaker 1>and Ed Ludlow.

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<v Speaker 2>I'm Caroline Hyde at Bloomberg's World headquarters in New York

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<v Speaker 2>and Imed Ludlow in San Francisco.

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<v Speaker 3>This is Bloomberg Technology.

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<v Speaker 2>Coming up, we'll discuss the state of the crypto market

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<v Speaker 2>tech managers with us the CEO and founder of bitcoin

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<v Speaker 2>payment app Strike.

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<v Speaker 4>And we'll look at how artificial intelligence is changing the

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<v Speaker 4>labor force, especially for the heavy hit tech industry, which

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<v Speaker 4>has already lost two hundred thousand employees this year due

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<v Speaker 4>to layoffs.

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<v Speaker 5>And let's talk more about AI.

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<v Speaker 2>We'll break down the Bloomberg big take on how Silicon

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<v Speaker 2>Valley is playing catch up with Microsoft when it comes

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<v Speaker 2>to the dominance in artificial intelligence. That says the tech

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<v Speaker 2>giant nears a new record high a stock. I know

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<v Speaker 2>you're going to be diving into ED, but first let's

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<v Speaker 2>go a little bit broader to two crypto lenders links

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<v Speaker 2>in South Korea. They've holded withdrawals in quick successions, sparking

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<v Speaker 2>of course for the deja vu here the termal the

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<v Speaker 2>market faced Celsius, for example, back in twenty twenty two.

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<v Speaker 5>However, investors seem to be shrugging off.

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<v Speaker 2>The risk of contagion, joining us for insight someone who

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<v Speaker 2>knows bitcoin really well. Digital asset market make of course,

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<v Speaker 2>Jackmanners Strike, founder and CEO Strike, a mobile payments app

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<v Speaker 2>that uses Bitcoin network to facilitate fast, cheap global transactions

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<v Speaker 2>and actually allows users to send receive money currency including bitcoin,

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<v Speaker 2>without intermediaries, without fees. I'm interested, in particular your own

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<v Speaker 2>move to self custody, Jack of late, Is this, yes,

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<v Speaker 2>about reducing counterparty risk? I understand there's a lot of

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<v Speaker 2>benefits to being your own custody, some of the products

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<v Speaker 2>that you can therefore offer your customers. But how much

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<v Speaker 2>does that reflect some of the worry in the ecosystem

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<v Speaker 2>at large?

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<v Speaker 1>First of all, Hello, nice to see you both. I

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<v Speaker 1>hope you missed me.

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<v Speaker 3>Yeah.

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<v Speaker 1>So the vision for the company we believe strictly in bitcoin.

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<v Speaker 1>We think, and I think personally that bitcoin is the

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<v Speaker 1>innovation of digital currency, of cryptocurrency, of blockchain. There's bitcoin

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<v Speaker 1>and there's everything else, and so US as a company,

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<v Speaker 1>we're laser focused on being a global Bitcoin provider and

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<v Speaker 1>providing financially impressive tools on top of the tech, and

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<v Speaker 1>so we made a move to take all of our custody,

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<v Speaker 1>a lot of our KYC process in house. We do

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<v Speaker 1>not want to work with other parties because we want

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<v Speaker 1>to do it the best in the world. So we've

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<v Speaker 1>been it's a really long process to get all of

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<v Speaker 1>the licenses and comply with regulation to be a money

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<v Speaker 1>service business in the United States, and we're really proud

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<v Speaker 1>to take all that in house so that we could

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<v Speaker 1>be the best in the world at bitcoin not crypto.

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<v Speaker 1>And that's why because we think we could do it

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<v Speaker 1>better than everybody else, but we're going to do it ourselves.

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<v Speaker 4>Jack, Good morning to you from San Francisco. Bitcoin and

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<v Speaker 4>not create. So it's really interesting our crypto team here

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<v Speaker 4>at Bloomberg. We're writing overnight that crypto share a bitcoin

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<v Speaker 4>sorry share of the total crypto market is at a

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<v Speaker 4>twenty month high, and there's a lot of caution about

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<v Speaker 4>the broader market away from bitcoin.

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<v Speaker 3>What does that tell you?

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<v Speaker 1>It tells me that markets are efficient, that the world

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<v Speaker 1>is figuring out where true innovation orhere true value is.

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<v Speaker 1>I mean, if I'm being honest with you, guys, crypto

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<v Speaker 1>is worth zero. It's just not realized as that yet,

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<v Speaker 1>which takes time. This is a new industry, it's a

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<v Speaker 1>new technology. But I think everyone's waking up to the

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<v Speaker 1>fact that the only thing that delivered a technical innovation

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<v Speaker 1>and made conscious ground forward for humanity as far as

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<v Speaker 1>money is a technology is Bitcoin, and regulators are realizing that,

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<v Speaker 1>speculators are realizing that, hedge funds are realizing that, businesses

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<v Speaker 1>are realizing that, and so I don't know if.

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<v Speaker 3>That's what that means.

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<v Speaker 1>The number still seems a bit off because it's not

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<v Speaker 1>one hundred percent bitcoin, but I think the world could

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<v Speaker 1>take its time.

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<v Speaker 3>It's okay.

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<v Speaker 5>I don't know, Jack.

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<v Speaker 2>Many would say smart contracts as a signal development. Many

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<v Speaker 2>people would like eath, even if perhaps some of the

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<v Speaker 2>smaller old coins at the moment are under some concerns

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<v Speaker 2>around overall regulatory impact. I'm interested, though, Jack, like many

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<v Speaker 2>would say, Look, where is the real use case at

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<v Speaker 2>the moment for many of these old coins and other

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<v Speaker 2>areas of crypto. Your use case of bitcoin largely is

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<v Speaker 2>it remittance? And how much are we seeing that being

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<v Speaker 2>adopted by the emerging markets where many do see rampant inflation.

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<v Speaker 2>That's really what the calling of bitcoin has been for

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<v Speaker 2>many Yeah, I mean.

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<v Speaker 1>We let customers buying sell bitcoin, and we use the

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<v Speaker 1>technology to improve payments. I mean you're talking about there's

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<v Speaker 1>a digital public infrastructure for payments. It's going to a moment

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<v Speaker 1>of silence for that. That's insane. Wift is not public

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<v Speaker 1>infrastructure for the world. Visas not public infrastructure for the world.

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<v Speaker 1>It's like a park that we all share, a public

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<v Speaker 1>utility that we get to all utilize for the benefits

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<v Speaker 1>of our own lives. It's owned by no one, accessible

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<v Speaker 1>by everyone. We're taking new digital public infrastructure, which, by

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<v Speaker 1>the way, guys think of it like the Internet. The

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<v Speaker 1>Internet is global, open, public infrastructure for the world to

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<v Speaker 1>communicate really really powerful thing, really really enhanced humanity, really

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<v Speaker 1>changed lives, and really empowered fundamental human rights and human freedoms,

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<v Speaker 1>creamous speech. Bitcoin is very similar for money and for

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<v Speaker 1>property rights, and so we use digital public infrastructure to

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<v Speaker 1>make financial transactions faster, cheaper, more global, more inclusive. It's

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<v Speaker 1>really cool stuff. And I don't think it's that complicated

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<v Speaker 1>your smart contract comment, I want to get to because

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<v Speaker 1>I think it's super simple, it's super known, it's super understood,

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<v Speaker 1>it's very sound and yeah, that's exactly what we do.

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<v Speaker 3>Jack, We appreciate it.

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<v Speaker 4>We don't have time for moments of silence on this program.

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<v Speaker 4>It's a limited show with commercial breaks. Let's talk about

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<v Speaker 4>real world use cases and also the kind of competitive

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<v Speaker 4>landscape with strike. I noticed that coinbase announced a partnership

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<v Speaker 4>with blocks. Bit Key itself is about the use of

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<v Speaker 4>self custody. Wallet's recognize that as competition. What do you

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<v Speaker 4>make of that partnership in the context of the work

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<v Speaker 4>you're doing.

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<v Speaker 6>No.

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<v Speaker 1>I think the way we think about the next ten, twenty, thirty,

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<v Speaker 1>forty fifty years of this industry is it's not a

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<v Speaker 1>winner take all or winner take most. In fact, it's

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<v Speaker 1>implied the opposite is that if a new network of

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<v Speaker 1>constituents that are delivering value to the world through monetary

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<v Speaker 1>services are to be developed, it implies that a network

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<v Speaker 1>has more than one right or else it wouldn't be

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<v Speaker 1>a network. And so I love to see we love

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<v Speaker 1>to see other businesses and companies join us on the

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<v Speaker 1>Bitcoin and the Lightning network. It makes our services more valuable.

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<v Speaker 1>It enhances the network effects and the economies of scale

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<v Speaker 1>that come with this new open digital infrastructure. So I'm

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<v Speaker 1>a huge fan of Jack Dorsey and block and all

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<v Speaker 1>they're doing, and that's great. More people are gonna be

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<v Speaker 1>able to buy bitcoin on coin based self custody, and

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<v Speaker 1>hopefully coinbas can then move out of the Lightning network.

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<v Speaker 1>That'd be awesome.

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<v Speaker 5>He's a fellow Bitcoin maximum List.

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<v Speaker 2>I'm interested Jack in ultimately the overall regulatory overhang at

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<v Speaker 2>the moment, particularly in the US, the issues that yes,

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<v Speaker 2>you've moved to self custody, but many would say it

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<v Speaker 2>happened in tandem when there was warriors, rumors about the

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<v Speaker 2>bancucy of your former custodian, these sorts of issues weaknesses

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<v Speaker 2>that seem to be in the rest of crypto. Does

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<v Speaker 2>that ultimately damage its adoption longer term?

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<v Speaker 5>Do you think? Is it frustrating or is it an opportunity?

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<v Speaker 1>Well, let me ask you a question back damage witch adoption,

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<v Speaker 1>crypto adoption or bitcoin adoption two different.

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<v Speaker 2>Things Bitcoin too, because I think they will get caught

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<v Speaker 2>up in the same narrative. Bitcoin is still ultimately deemed cryptocurrency.

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<v Speaker 1>Yeah, totally, No, I think it's this is a great cleansing.

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<v Speaker 1>It's really phenomenal. I mean, listen, guys, the SEC.

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<v Speaker 3>Their job is to theoretically.

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<v Speaker 1>And I'm just explaining what's going on. The SEC's job

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<v Speaker 1>is to protect the ethics and morality in the United

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<v Speaker 1>States financial markets, and the notion that they would have

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<v Speaker 1>an issue with everything. But bitcoin does a lot. It

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<v Speaker 1>doesn't seem like a very ethical moral like it's a problem,

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<v Speaker 1>and so how do we fix that. We go through

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<v Speaker 1>what we're going through now, People that shouldn't be in

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<v Speaker 1>business go bankrupt, Things that are illegal and im moral

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<v Speaker 1>and unethical should be required to disclose and give proper

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<v Speaker 1>transparency to the American public.

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<v Speaker 3>And so I think all of this is good for bitcoin.

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<v Speaker 1>I think where this leaves us is values going to

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<v Speaker 1>accrue where it's real and where I think it's real,

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<v Speaker 1>and where I think it's moral, where I think it's ethical,

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<v Speaker 1>where I think it's innovative, where I think it's better, faster, cheaper, stronger.

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<v Speaker 3>It's bitcoin.

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<v Speaker 1>And so the path on how we get there is

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<v Speaker 1>always going to be complicated, and that's the part of

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<v Speaker 1>free markets, which America loves deeply, right, And so I

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<v Speaker 1>think we're just going through free market discovery of what's

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<v Speaker 1>truly innovative in a new technology sector. We've been through

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<v Speaker 1>before in the Internet, and we're seeing similar patterns now

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<v Speaker 1>and I think that that's becoming abundantly clear that it's bitcoin.

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<v Speaker 1>So on a day to day basis, if you're tracking

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<v Speaker 1>a chart, maybe it looks choppy, but over a long

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<v Speaker 1>term trajectory, I mean bitcoin is being widely considered the

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<v Speaker 1>best version of money.

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<v Speaker 2>Communities or de widely might be taking issue with, but

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<v Speaker 2>certainly by some jack Man As, we thank you so

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<v Speaker 2>much for bringing us your perspective. Really great to have

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<v Speaker 2>you the Strike founder there. Coming up, well, we're going

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<v Speaker 2>to be discussing how fresh Works is bringing the power

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<v Speaker 2>of AI to its customers, how India in fact is

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<v Speaker 2>joining the AI race. We'll talk about all of that

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<v Speaker 2>with the CEO of fresh Works next. Plus, let's just

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<v Speaker 2>quick look in on Adobe, the photoshop maker hour' earnings tonight,

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<v Speaker 2>the company's artificial intelligence plan and it's deal with Figma

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<v Speaker 2>that's going to be front and center in its second

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<v Speaker 2>quarter revenue expected.

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<v Speaker 5>Look, we're looking at the direction.

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<v Speaker 2>Of travel for how revenue continues to be perhaps generated

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<v Speaker 2>by generator of AI.

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<v Speaker 5>Rough at one point eight percent of a Bloomberg.

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<v Speaker 7>The most likely outcome for Europe trying to regulate it

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<v Speaker 7>is they basically prevent the industrial revolution from happening in

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<v Speaker 7>Europe and it remains a place where it's very nice

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<v Speaker 7>to take my daughters on vacation, but maybe it's not

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<v Speaker 7>part of the future of the world innovation wise if

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<v Speaker 7>they're not very careful.

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<v Speaker 3>Is the one possible upside or brex that.

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<v Speaker 7>You could talk about is that maybe Europe commits suicide

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<v Speaker 7>with its regulation and stops in a development there, and

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<v Speaker 7>maybe the you know, UK gets it right and doesn't do.

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<v Speaker 2>So sunshine over there in Europe. Eight Partners founding partner

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<v Speaker 2>and Palentae co founder Joe Lonsdale, speaking on the sidelines

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<v Speaker 2>of the Founder's Forum in London, essentially saying Europe's making

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<v Speaker 2>a mistake in wanting to regulate AI. Now stick with

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<v Speaker 2>all of this because beyond regulation, another key concerns going

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<v Speaker 2>to be, well, how it affects you and I our.

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<v Speaker 5>Jobs, the displacement are worry that.

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<v Speaker 2>All the greater tech industry has already seen what two

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<v Speaker 2>hundred thousand employees laid off this year and could that

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<v Speaker 2>even be affected further and the fact that the machines

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<v Speaker 2>can be doing it.

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<v Speaker 5>Let's bring in Bloomberg's Ellen Hewitt for.

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<v Speaker 2>More on all of this, and we've already heard it

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<v Speaker 2>discussed IBM, for example, putting numbers to it, eight hundred

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<v Speaker 2>back office rolls could be impacted by AI. Are you

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<v Speaker 2>seeing the pipeline change when it comes to people looking

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<v Speaker 2>at tech and wanting a job there.

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<v Speaker 8>So we are seeing the pipeline change because you know,

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<v Speaker 8>young people who want to join tech aren't seeing these

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<v Speaker 8>layoff numbers. You know, two hundred thousand people lost their

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<v Speaker 8>job already in twenty twenty three. More happened in twenty

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<v Speaker 8>twenty two, and they're thinking, maybe this job isn't as

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<v Speaker 8>secure as I once thought it was. I don't know

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<v Speaker 8>that that's happening yet because of AI. And so that's

0:11:19.920 --> 0:11:21.920
<v Speaker 8>kind of an interesting question that people are talking about

0:11:21.960 --> 0:11:24.160
<v Speaker 8>right now. It's just because of the economy. But when

0:11:24.240 --> 0:11:27.640
<v Speaker 8>these CEOs are sending out these big memos explaining why

0:11:27.679 --> 0:11:30.640
<v Speaker 8>they're laying off so many workers, they're often citing AI

0:11:31.040 --> 0:11:32.880
<v Speaker 8>not as a job replacement. That's saying we need to

0:11:32.920 --> 0:11:35.880
<v Speaker 8>shift our business to focus more on how AI can

0:11:36.040 --> 0:11:38.480
<v Speaker 8>enhance our business, and that might mean cutting some jobs

0:11:38.520 --> 0:11:42.040
<v Speaker 8>and hiring more AI or machine learning engineers.

0:11:42.480 --> 0:11:45.000
<v Speaker 2>We certainly had that from Meta. We've heard it from

0:11:45.600 --> 0:11:49.560
<v Speaker 2>plenty of other founders. At the moment when we have

0:11:49.640 --> 0:11:53.160
<v Speaker 2>seen a ce change culturally of people thinking it was

0:11:53.800 --> 0:11:57.120
<v Speaker 2>you know, I get a computer ability when I go

0:11:57.160 --> 0:12:00.200
<v Speaker 2>to university, I get some great instruction, and I've got

0:12:00.240 --> 0:12:03.720
<v Speaker 2>a job made. Ultimately, are people now trying to work

0:12:03.760 --> 0:12:06.160
<v Speaker 2>out the ways in which they can work with big tech?

0:12:06.160 --> 0:12:07.800
<v Speaker 2>Are they more interesting going to startups?

0:12:07.800 --> 0:12:09.559
<v Speaker 5>For example? There's all this talk of silver.

0:12:09.360 --> 0:12:11.480
<v Speaker 2>Linings that people won't be employed by big tech, but

0:12:11.480 --> 0:12:13.839
<v Speaker 2>my goodness, they'll go and start their own thing, are they?

0:12:14.280 --> 0:12:17.480
<v Speaker 8>I think overall people are nervous right now, even the

0:12:17.520 --> 0:12:21.640
<v Speaker 8>companies that seemed safe Google, Facebook, even these big startups

0:12:21.640 --> 0:12:24.360
<v Speaker 8>like Stripe. You know, these private companies that are essentially public.

0:12:24.360 --> 0:12:26.319
<v Speaker 8>They've been around so long and are so big. These

0:12:26.320 --> 0:12:29.839
<v Speaker 8>companies are slashing jobs, and not just you know, often

0:12:29.880 --> 0:12:32.640
<v Speaker 8>recruiters are the first to go when a company isn't

0:12:32.720 --> 0:12:35.080
<v Speaker 8>hiring anymore, but they're cutting you know, people who have

0:12:35.080 --> 0:12:37.920
<v Speaker 8>been software engineers at this company for ten years. There's

0:12:37.920 --> 0:12:40.920
<v Speaker 8>a fear that's happening in the job market in Silicon Valley.

0:12:41.040 --> 0:12:43.560
<v Speaker 8>I know people who aren't leaving jobs that they don't like,

0:12:43.960 --> 0:12:45.840
<v Speaker 8>which they normally would leave because they're concerned that they

0:12:45.880 --> 0:12:47.760
<v Speaker 8>won't be able to find a good one if they do.

0:12:49.160 --> 0:12:51.400
<v Speaker 3>Hey, and beyond just the layoffs.

0:12:51.440 --> 0:12:54.240
<v Speaker 4>I get the headline of the layoffs, but how is

0:12:54.280 --> 0:12:56.959
<v Speaker 4>AI altering the jobs market in terms of the type

0:12:57.000 --> 0:13:00.280
<v Speaker 4>of talent that startups are going out for. Your out

0:13:00.280 --> 0:13:02.840
<v Speaker 4>in New York, you usually hear with me in broader

0:13:02.880 --> 0:13:06.000
<v Speaker 4>Silicon Valley. You know, there is a lot of excitement

0:13:06.080 --> 0:13:08.480
<v Speaker 4>right now and a lot of hiring as people pivot

0:13:08.520 --> 0:13:10.800
<v Speaker 4>towards what is in vogue.

0:13:10.960 --> 0:13:13.960
<v Speaker 8>I mean, if you're a software engineer with experience in

0:13:14.080 --> 0:13:17.200
<v Speaker 8>artificial intelligence machine learning, you are in high demand. And

0:13:17.559 --> 0:13:19.680
<v Speaker 8>we even saw that show up in some stats. I

0:13:19.720 --> 0:13:24.120
<v Speaker 8>talk to someone who runs a database that collects compensation information.

0:13:24.200 --> 0:13:27.080
<v Speaker 8>They said that senior software engineers with AI machine learning

0:13:27.080 --> 0:13:30.760
<v Speaker 8>backgrounds are getting paid salaries on average twelve percent higher

0:13:30.760 --> 0:13:34.360
<v Speaker 8>than senior software engineers without that relevant experience. I think

0:13:34.440 --> 0:13:37.200
<v Speaker 8>the money is definitely going toward people who say that

0:13:37.240 --> 0:13:39.840
<v Speaker 8>they can help these companies, you know, pivot toward AI

0:13:39.960 --> 0:13:41.560
<v Speaker 8>or use AI to enhance their business.

0:13:42.360 --> 0:13:43.520
<v Speaker 3>I think that's.

0:13:43.280 --> 0:13:45.360
<v Speaker 8>One thing that's happening. And then another thing is, look,

0:13:45.360 --> 0:13:48.120
<v Speaker 8>if you play around with JATGBT and you try to

0:13:48.480 --> 0:13:50.800
<v Speaker 8>use it to code, I think you pretty quickly see

0:13:50.800 --> 0:13:51.360
<v Speaker 8>that while.

0:13:51.200 --> 0:13:52.800
<v Speaker 5>It can't do the job on its own, it.

0:13:52.760 --> 0:13:56.160
<v Speaker 8>Can pretty quickly replace a couple extra programmers that you

0:13:56.240 --> 0:13:57.840
<v Speaker 8>might need to build out a certain product. I know

0:13:57.920 --> 0:13:59.839
<v Speaker 8>I have a friend who's building an app on his own.

0:14:00.200 --> 0:14:02.600
<v Speaker 8>He would have hired a developer instead, he's just using

0:14:02.679 --> 0:14:05.199
<v Speaker 8>chat GPT because it can code, and it can correct

0:14:05.240 --> 0:14:06.640
<v Speaker 8>its own code. All he has to do is kind

0:14:06.679 --> 0:14:08.800
<v Speaker 8>of tell it what he wants, and he knows enough

0:14:09.520 --> 0:14:11.040
<v Speaker 8>to be able to make it work that way. It's

0:14:11.120 --> 0:14:13.079
<v Speaker 8>not hard to imagine how this could replace jobs.

0:14:13.280 --> 0:14:14.520
<v Speaker 5>A little bit down the line.

0:14:15.080 --> 0:14:17.760
<v Speaker 4>All right, Blimberg Zellen here, all things start up, all

0:14:17.800 --> 0:14:20.560
<v Speaker 4>Things Technology Worker, Thank you. All right, let's stick with

0:14:20.600 --> 0:14:24.360
<v Speaker 4>AI and bring in Garish Matribute and CEO of Customer

0:14:24.400 --> 0:14:28.520
<v Speaker 4>Service Productivity startup fresh Works. They call fresh Works the

0:14:28.600 --> 0:14:31.840
<v Speaker 4>sales force of India. And I don't know whether Garish

0:14:31.880 --> 0:14:33.400
<v Speaker 4>you're going to say that's fair or not, but what

0:14:33.440 --> 0:14:36.840
<v Speaker 4>you're doing is taking generative AI tools and integrating it

0:14:36.880 --> 0:14:38.200
<v Speaker 4>into existing suite.

0:14:38.400 --> 0:14:40.080
<v Speaker 3>Freddy, how does that work?

0:14:42.000 --> 0:14:44.160
<v Speaker 9>Good morning, Ed and Carolyn, thanks for having me on

0:14:44.200 --> 0:14:48.040
<v Speaker 9>the show. At fresh Works, we've always believed in building

0:14:48.080 --> 0:14:50.440
<v Speaker 9>software for the fortune five million, not just for the

0:14:50.440 --> 0:14:54.720
<v Speaker 9>fortune five hundred and me have been on the Freddie

0:14:54.800 --> 0:14:58.000
<v Speaker 9>journey for over five years now because we all know

0:14:58.080 --> 0:15:04.200
<v Speaker 9>how AI was changing business, and we are solely taking

0:15:04.240 --> 0:15:07.840
<v Speaker 9>the same idea of generative AI to democratize the access

0:15:07.840 --> 0:15:12.080
<v Speaker 9>for generative AI to fortune five million companies and specifically

0:15:12.120 --> 0:15:14.600
<v Speaker 9>in the areas of customer experience and employee experience. That's

0:15:15.160 --> 0:15:15.960
<v Speaker 9>our mission now.

0:15:17.840 --> 0:15:20.000
<v Speaker 4>The question is how does it help the customers in

0:15:20.040 --> 0:15:23.160
<v Speaker 4>real terms? You know, we dangle the words generative AI

0:15:23.200 --> 0:15:26.120
<v Speaker 4>in front of everything at the moment, Gearish tell us

0:15:26.160 --> 0:15:28.880
<v Speaker 4>how in practice this helps your customer base.

0:15:30.160 --> 0:15:33.440
<v Speaker 9>Okay, I'll give you two clear examples. If you take

0:15:33.480 --> 0:15:36.880
<v Speaker 9>customer service, which is our largest business. We've all seen

0:15:37.280 --> 0:15:40.600
<v Speaker 9>from the days of call center and IVR how businesses

0:15:40.600 --> 0:15:43.840
<v Speaker 9>have always wanted our miation. So generative AI will bring

0:15:43.880 --> 0:15:47.400
<v Speaker 9>that conversational style of customer self service for all of us.

0:15:48.080 --> 0:15:52.840
<v Speaker 9>And more importantly, we believe in a human augmented AI,

0:15:53.000 --> 0:15:56.440
<v Speaker 9>which is I think of copilot. So we are building

0:15:57.520 --> 0:16:01.640
<v Speaker 9>an AI assistant for salespeople, support people, marketing people, so

0:16:02.360 --> 0:16:05.880
<v Speaker 9>and so think of this new world where your employees

0:16:05.920 --> 0:16:08.080
<v Speaker 9>can become even more productive, where they don't have to

0:16:08.080 --> 0:16:10.880
<v Speaker 9>do the mundane boarding protein tasks and they can move

0:16:10.920 --> 0:16:15.480
<v Speaker 9>on to doing higher productivity tasks, and that is going

0:16:15.520 --> 0:16:17.600
<v Speaker 9>to make life a lot easier for all of us.

0:16:18.120 --> 0:16:20.920
<v Speaker 2>So you're thinking more of an augmented human rather than

0:16:20.920 --> 0:16:24.760
<v Speaker 2>one that's replaced garrish. What about coding yourself? Are you

0:16:25.000 --> 0:16:27.480
<v Speaker 2>not having to hire as many people as you ultimately

0:16:27.480 --> 0:16:29.720
<v Speaker 2>thought you would have to, because we're just hearing from

0:16:29.720 --> 0:16:33.640
<v Speaker 2>Ellen about how you can do basic coding using tails

0:16:33.680 --> 0:16:34.640
<v Speaker 2>such as CHATCHYBT.

0:16:37.360 --> 0:16:40.920
<v Speaker 9>So I think developer productivity will definitely increase and that

0:16:41.160 --> 0:16:43.040
<v Speaker 9>will allow us to do a lot more and do

0:16:43.120 --> 0:16:47.560
<v Speaker 9>it faster. And you will still continue to hire developers,

0:16:47.560 --> 0:16:49.520
<v Speaker 9>but maybe the skill set of the developers that you

0:16:49.600 --> 0:16:53.200
<v Speaker 9>hire may change a little bit. As you are discussing

0:16:53.280 --> 0:16:57.920
<v Speaker 9>there is more AI in demand, but we believe that

0:16:58.680 --> 0:17:01.720
<v Speaker 9>overall developer pro activity will go up and that should

0:17:01.720 --> 0:17:03.520
<v Speaker 9>help us do a lot more and there's going to

0:17:03.520 --> 0:17:06.800
<v Speaker 9>be plenty of new opportunities for us to kind of solve.

0:17:08.280 --> 0:17:12.439
<v Speaker 2>What's interesting is, of course, the AI hype that has today,

0:17:12.720 --> 0:17:16.280
<v Speaker 2>for example, pushed Microsoft have a higher potentially at the

0:17:16.400 --> 0:17:19.640
<v Speaker 2>highest record high for the stock. Ever, I'm looking at

0:17:19.760 --> 0:17:23.200
<v Speaker 2>your share price and when it's languished to be Frank

0:17:23.320 --> 0:17:25.760
<v Speaker 2>has picked up of late, but nowhere near the highs

0:17:25.960 --> 0:17:29.440
<v Speaker 2>of previous years. And I'm interested, Grrishan, whether you feel

0:17:29.680 --> 0:17:34.240
<v Speaker 2>that ultimately our companies are eating the AI lunch, whether

0:17:34.280 --> 0:17:38.040
<v Speaker 2>that's rightly so or not. So it is perhaps the

0:17:38.080 --> 0:17:40.840
<v Speaker 2>hype too much around certain names. Why hasn't yours been

0:17:41.000 --> 0:17:41.600
<v Speaker 2>caught up in it?

0:17:43.359 --> 0:17:46.399
<v Speaker 9>So we are more in the business productivity software. We

0:17:46.440 --> 0:17:50.520
<v Speaker 9>are not in the business of hyping up AI. So

0:17:51.400 --> 0:17:54.639
<v Speaker 9>we all know what's happened to tech stocks. And we

0:17:54.680 --> 0:17:56.840
<v Speaker 9>are a young public company in the process of building

0:17:56.840 --> 0:18:00.879
<v Speaker 9>credibility with the public investors. And we have shown like

0:18:00.960 --> 0:18:04.000
<v Speaker 9>the last six eight quarters of consistent credible growth and

0:18:04.000 --> 0:18:06.600
<v Speaker 9>we will continue to execute and I think the markets

0:18:06.640 --> 0:18:10.200
<v Speaker 9>will eventually catch up to where the efficiencies are.

0:18:12.080 --> 0:18:13.560
<v Speaker 3>Curious, I want to ask you about India.

0:18:13.720 --> 0:18:15.840
<v Speaker 4>Sam Altman was in India who was talking about the

0:18:15.880 --> 0:18:20.359
<v Speaker 4>opportunity for AI. You've expanded your operations and talent pool there.

0:18:20.720 --> 0:18:24.600
<v Speaker 4>Some of what sam Altman said also invoked to respond,

0:18:24.640 --> 0:18:25.520
<v Speaker 4>what did you make of it?

0:18:28.800 --> 0:18:31.919
<v Speaker 9>Well, first of all, I think that in jen AI

0:18:32.119 --> 0:18:35.879
<v Speaker 9>is a great opportunity for India with we just have

0:18:36.600 --> 0:18:39.520
<v Speaker 9>crossed over five million developers in India. I think the

0:18:39.600 --> 0:18:43.120
<v Speaker 9>number was three million a few years ago. So this

0:18:43.200 --> 0:18:45.480
<v Speaker 9>is going to be a pivotal moment. And you have

0:18:45.560 --> 0:18:48.879
<v Speaker 9>to understand that from a demographic standpoint, India has a

0:18:49.040 --> 0:18:52.680
<v Speaker 9>very young workforce and who's hungry to learn and there's

0:18:52.800 --> 0:18:57.280
<v Speaker 9>a lot of aspiration. And I was also amazed to

0:18:57.320 --> 0:19:01.240
<v Speaker 9>see that universities in India have already started launching ai

0:19:01.520 --> 0:19:05.080
<v Speaker 9>am a LINJENEVII courses. So you I think this is

0:19:05.119 --> 0:19:09.600
<v Speaker 9>going to be a phenomenal opportunity for India and we

0:19:09.640 --> 0:19:12.080
<v Speaker 9>are going to see a lot of startups focusing on

0:19:12.119 --> 0:19:13.080
<v Speaker 9>that coming from India.

0:19:14.200 --> 0:19:16.959
<v Speaker 2>Well, you're a prominent VC as well as being the

0:19:17.000 --> 0:19:19.200
<v Speaker 2>founder of this particular company. Gerish, we thank you so

0:19:19.280 --> 0:19:21.840
<v Speaker 2>much for spending some time in askurishrom Ratham Boutham, your

0:19:21.880 --> 0:19:23.560
<v Speaker 2>CEO of Fresh Works.

0:19:31.400 --> 0:19:32.840
<v Speaker 3>Time for talking tech TikTok.

0:19:32.880 --> 0:19:34.960
<v Speaker 4>Parent byte Dance is drawing up plans to build an

0:19:35.000 --> 0:19:38.639
<v Speaker 4>app capable of providing multiple services. The everything app model

0:19:38.760 --> 0:19:41.560
<v Speaker 4>is popular in China thanks to ten cents we Chat.

0:19:41.640 --> 0:19:44.280
<v Speaker 4>Byte Dance aims to offer a range of services from

0:19:44.320 --> 0:19:48.320
<v Speaker 4>food delivery to travel bookings plus. TikTok CEO says it

0:19:48.359 --> 0:19:51.760
<v Speaker 4>plans to invest billions of dollars in Southeast Asia over

0:19:51.800 --> 0:19:54.119
<v Speaker 4>the next year three to five years. In fact, it's

0:19:54.160 --> 0:19:56.800
<v Speaker 4>part of an effort to strengthen the presence of its

0:19:56.880 --> 0:20:00.160
<v Speaker 4>hit video app in the region. And speaking of tikto

0:20:00.400 --> 0:20:04.960
<v Speaker 4>a bipartisan group of US lawmakers reintroduce legislation that restricts

0:20:04.960 --> 0:20:08.640
<v Speaker 4>social media companies like TikTok from sending sensitive user data

0:20:08.760 --> 0:20:21.800
<v Speaker 4>to foreign adversaries. The bill doesn't explicitly mention TikTok. Welcome

0:20:21.800 --> 0:20:24.560
<v Speaker 4>back to Number Technology. I'm Ed Ludlow here in San Francisco.

0:20:24.640 --> 0:20:26.320
<v Speaker 5>I'm Caroline hid in New York. Let's go back to

0:20:26.320 --> 0:20:26.960
<v Speaker 5>the world of AI.

0:20:27.760 --> 0:20:30.399
<v Speaker 4>Yeah, the topic of the day, week, month, and year AI.

0:20:30.760 --> 0:20:33.720
<v Speaker 4>So let's talk AI and data with AWS Vice president

0:20:33.800 --> 0:20:37.240
<v Speaker 4>Milan Thompson Bukovic, who leads some of the company's largest

0:20:37.280 --> 0:20:39.840
<v Speaker 4>scale data services. The way that I explain it is,

0:20:39.840 --> 0:20:43.520
<v Speaker 4>if you're an AWS Cloud customer who is either storing

0:20:43.640 --> 0:20:46.320
<v Speaker 4>or processing data, that's your responsibility.

0:20:46.800 --> 0:20:49.720
<v Speaker 6>That is my rema. Thank you for having me here.

0:20:49.720 --> 0:20:50.439
<v Speaker 3>You're very welcome.

0:20:50.480 --> 0:20:53.840
<v Speaker 4>Why then, are you so focused on generative AI?

0:20:54.520 --> 0:20:57.240
<v Speaker 6>Well, I have to tell you, ed ouraws.

0:20:57.280 --> 0:21:00.439
<v Speaker 10>Customers are asking us, how do I chieve change my

0:21:00.560 --> 0:21:02.200
<v Speaker 10>data strategy with GENAI?

0:21:02.359 --> 0:21:04.800
<v Speaker 6>How do I make sure my GENI.

0:21:04.440 --> 0:21:08.840
<v Speaker 10>Strategy is using my data to differentiate because that is

0:21:08.880 --> 0:21:10.320
<v Speaker 10>what customers want.

0:21:10.560 --> 0:21:13.040
<v Speaker 4>I think we've learned in recent weeks and months that

0:21:13.160 --> 0:21:15.840
<v Speaker 4>training models on the thing that you want to.

0:21:16.200 --> 0:21:17.840
<v Speaker 3>Reflect your own data is key.

0:21:18.040 --> 0:21:21.919
<v Speaker 4>There is an argument that Amazon or AWS strong on

0:21:22.040 --> 0:21:25.960
<v Speaker 4>AI machine learning behind on generative AI.

0:21:26.560 --> 0:21:27.760
<v Speaker 3>What do you make of that argument?

0:21:27.880 --> 0:21:30.600
<v Speaker 10>Well, I don't think that's the case actually, ed I

0:21:30.600 --> 0:21:33.440
<v Speaker 10>think right now we have over one hundred thousand customers

0:21:33.440 --> 0:21:37.120
<v Speaker 10>that are doing all different types of mL, including generative

0:21:37.160 --> 0:21:39.840
<v Speaker 10>AI on AWS today.

0:21:40.160 --> 0:21:41.080
<v Speaker 3>And if you look.

0:21:40.920 --> 0:21:44.440
<v Speaker 10>At the customers that are pivoting quickly and they're launching

0:21:44.440 --> 0:21:48.680
<v Speaker 10>with GENI capabilities today, they're launching them on a shared

0:21:48.760 --> 0:21:51.560
<v Speaker 10>data set with the data strategy and the mL tools

0:21:51.560 --> 0:21:55.119
<v Speaker 10>that Amazon provides. So I'll give you one example. Snap

0:21:55.200 --> 0:21:58.440
<v Speaker 10>recently launched a new feature called my AI and so

0:21:58.480 --> 0:22:01.040
<v Speaker 10>snapchatter is all over the world can use my AI

0:22:01.160 --> 0:22:03.760
<v Speaker 10>to ask questions about what to word, would job interview

0:22:03.840 --> 0:22:08.159
<v Speaker 10>or what movie to see? And my AI is running

0:22:08.160 --> 0:22:11.399
<v Speaker 10>a generative AI. Many of the models for what Snap

0:22:11.440 --> 0:22:14.520
<v Speaker 10>is using is using Amazon S three and their own

0:22:14.640 --> 0:22:17.560
<v Speaker 10>data that they're training off of Amazon S three as

0:22:17.560 --> 0:22:21.000
<v Speaker 10>well as Amazon EC two for the training.

0:22:20.680 --> 0:22:24.560
<v Speaker 2>Itself, and they were able to move so nimbly because

0:22:24.720 --> 0:22:27.440
<v Speaker 2>they had a cloud based model. How are you having

0:22:27.440 --> 0:22:31.000
<v Speaker 2>those conversations with companies that aren't yet using cloud based model?

0:22:31.040 --> 0:22:33.680
<v Speaker 2>Are you seeing the promise of generative AI the need

0:22:33.680 --> 0:22:36.000
<v Speaker 2>to get into it as false tracking?

0:22:36.040 --> 0:22:39.359
<v Speaker 5>Some of that sales process went on absolutely.

0:22:40.160 --> 0:22:43.080
<v Speaker 10>That question of what is my data strategy and how

0:22:43.119 --> 0:22:45.359
<v Speaker 10>does it help me move to gen AI is just

0:22:45.560 --> 0:22:46.600
<v Speaker 10>top of mind.

0:22:46.400 --> 0:22:48.440
<v Speaker 6>For CTOs and CIOs everywhere.

0:22:48.960 --> 0:22:51.720
<v Speaker 10>If you look at some of the customers of AWS,

0:22:51.760 --> 0:22:55.160
<v Speaker 10>if you look at Cox Automotive. Cox Automotive has been

0:22:55.200 --> 0:22:59.320
<v Speaker 10>transforming the auto purchase experience with Kelly Bluebook and Autotrader,

0:22:59.800 --> 0:23:02.840
<v Speaker 10>and they have been doing a data like a centralized

0:23:02.920 --> 0:23:05.960
<v Speaker 10>data strategy model for many years now, and they started

0:23:06.480 --> 0:23:10.120
<v Speaker 10>because of business analytics, but they found that when they

0:23:10.440 --> 0:23:14.040
<v Speaker 10>centralize their data with their data strategy on Amazon S three,

0:23:14.240 --> 0:23:16.880
<v Speaker 10>they were able to move that much more quickly into

0:23:16.960 --> 0:23:21.520
<v Speaker 10>machine learning and computer vision. And now when you're looking

0:23:21.520 --> 0:23:25.639
<v Speaker 10>at an image of a car on a Cox property,

0:23:26.280 --> 0:23:30.560
<v Speaker 10>that computer vision models. Well, model will tell you if

0:23:30.600 --> 0:23:33.640
<v Speaker 10>that's a shadow in the picture or it's actually a scratch,

0:23:34.160 --> 0:23:37.040
<v Speaker 10>and that is an incredible, incredibly important.

0:23:36.600 --> 0:23:38.399
<v Speaker 6>Part of the auto purchase experience.

0:23:38.560 --> 0:23:41.440
<v Speaker 10>And so those customers need to start with the right

0:23:41.520 --> 0:23:44.760
<v Speaker 10>data strategy, just like Cox Automotive did and in order

0:23:44.840 --> 0:23:47.040
<v Speaker 10>to move as quickly as they can to all these

0:23:47.080 --> 0:23:48.000
<v Speaker 10>new technologies.

0:23:48.040 --> 0:23:49.720
<v Speaker 6>Informs the machine learning.

0:23:49.800 --> 0:23:54.600
<v Speaker 2>How is it thosets of examples that get a potential

0:23:54.600 --> 0:23:58.640
<v Speaker 2>customer coming to you rather than Microsoft, because it feels

0:23:58.760 --> 0:24:01.240
<v Speaker 2>like Microsoft managed to just sort of take some of

0:24:01.240 --> 0:24:02.600
<v Speaker 2>the ultrogen out of the room when it came to

0:24:02.640 --> 0:24:03.320
<v Speaker 2>generative AI.

0:24:03.520 --> 0:24:04.720
<v Speaker 5>How you fool back against that?

0:24:06.400 --> 0:24:09.119
<v Speaker 10>Well, the things that we do, Caroline is really to

0:24:09.200 --> 0:24:12.720
<v Speaker 10>just listen to our customers. And we have over twenty

0:24:12.720 --> 0:24:16.080
<v Speaker 10>five machine learning services today and the latest thing that

0:24:16.119 --> 0:24:18.560
<v Speaker 10>we have introduced is Amazon Bedrock.

0:24:18.640 --> 0:24:22.760
<v Speaker 6>So again listening to customers. For us, we know data

0:24:22.840 --> 0:24:23.560
<v Speaker 6>has gravity.

0:24:24.200 --> 0:24:27.080
<v Speaker 10>We know that our customers want to bring their machine

0:24:27.119 --> 0:24:30.160
<v Speaker 10>learning models to the data. And I'll tell you why

0:24:30.200 --> 0:24:34.119
<v Speaker 10>that's the case. If you think about what data a

0:24:34.160 --> 0:24:38.399
<v Speaker 10>customer has, it's their business data, but it's a lot

0:24:38.480 --> 0:24:42.119
<v Speaker 10>of their customer's data and for data governance reasons, that

0:24:42.280 --> 0:24:44.879
<v Speaker 10>they do not want to take their customer data and

0:24:44.960 --> 0:24:47.520
<v Speaker 10>bring it over to another provider and have that train

0:24:48.040 --> 0:24:50.440
<v Speaker 10>off site and off host and out of their control.

0:24:50.960 --> 0:24:54.560
<v Speaker 6>And so with Bedrock, when we're training or we're.

0:24:54.240 --> 0:24:57.640
<v Speaker 10>Giving the capabilities for customers to pick any open source

0:24:57.720 --> 0:25:01.080
<v Speaker 10>model or to use Titan, the Amazon model, they're training

0:25:01.080 --> 0:25:03.600
<v Speaker 10>their data on a local custom copy.

0:25:04.080 --> 0:25:05.760
<v Speaker 6>They're able to integrate with.

0:25:05.800 --> 0:25:09.600
<v Speaker 10>Stage Maker today to train off data that's in their

0:25:09.720 --> 0:25:10.280
<v Speaker 10>data lake.

0:25:11.000 --> 0:25:12.200
<v Speaker 5>And I think that is.

0:25:12.160 --> 0:25:17.480
<v Speaker 10>A huge, huge differentiator for AWS because we have hundreds

0:25:17.520 --> 0:25:20.320
<v Speaker 10>of thousands of data lakes running on Amazon S three

0:25:20.359 --> 0:25:24.000
<v Speaker 10>today and customers want to start from there and not

0:25:24.359 --> 0:25:27.560
<v Speaker 10>spin off all these data silos.

0:25:26.960 --> 0:25:27.800
<v Speaker 6>Just for Jenai.

0:25:28.280 --> 0:25:32.040
<v Speaker 10>They need to use their data to differentiate and to

0:25:32.040 --> 0:25:36.000
<v Speaker 10>do it safely with the data governance that their CIOs need.

0:25:36.440 --> 0:25:41.680
<v Speaker 4>Milan first half of this year, AWS customers were cost optimizing.

0:25:42.280 --> 0:25:44.760
<v Speaker 3>Has that continued well.

0:25:44.800 --> 0:25:48.560
<v Speaker 10>I think the keyword there ed is optimizing. When I

0:25:48.600 --> 0:25:50.960
<v Speaker 10>talk to customers, and we hear this from customers all

0:25:50.960 --> 0:25:54.240
<v Speaker 10>the time, it's all about prioritization. I think that's true

0:25:54.280 --> 0:25:57.040
<v Speaker 10>for every company in the world right now.

0:25:57.440 --> 0:25:59.159
<v Speaker 6>And so what our customers are doing is.

0:25:59.160 --> 0:26:02.840
<v Speaker 10>They're prior to what are the most important investments to make,

0:26:03.200 --> 0:26:05.359
<v Speaker 10>and for many of them, it's GENAI and how they

0:26:05.440 --> 0:26:08.240
<v Speaker 10>take advantage of it. And so they're pivoting what they're

0:26:08.320 --> 0:26:11.440
<v Speaker 10>spending on the cloud with AWS to focus on that

0:26:11.840 --> 0:26:15.480
<v Speaker 10>and maybe deprioritizing, which just means do later some of

0:26:15.480 --> 0:26:16.520
<v Speaker 10>the other initiatives.

0:26:16.840 --> 0:26:19.440
<v Speaker 4>It kind of crystallize that for us in the context

0:26:19.520 --> 0:26:22.679
<v Speaker 4>of generative AI, because if you're an aw's cloud customer,

0:26:22.760 --> 0:26:25.880
<v Speaker 4>that can mean many things. They're pulling back in some areas,

0:26:26.160 --> 0:26:29.040
<v Speaker 4>but are they tuning up in generative AI.

0:26:29.560 --> 0:26:32.560
<v Speaker 10>Well, when I talked about that shared data set, and

0:26:33.840 --> 0:26:38.000
<v Speaker 10>that is such an accelerator because when our customers tune up,

0:26:38.160 --> 0:26:40.200
<v Speaker 10>as you say, on generative AI.

0:26:40.320 --> 0:26:42.119
<v Speaker 6>They can do it that much faster.

0:26:42.400 --> 0:26:46.320
<v Speaker 10>Let's take patre duty, so patro duty automates instant response.

0:26:46.400 --> 0:26:50.879
<v Speaker 10>And just recently they launched three new generative AI capabilities,

0:26:51.240 --> 0:26:54.399
<v Speaker 10>and their ability to launch that was based on the

0:26:54.400 --> 0:26:58.600
<v Speaker 10>fact that they're training their data now on a huge

0:26:58.720 --> 0:27:03.159
<v Speaker 10>data set in Amazons three that's also being used for

0:27:03.280 --> 0:27:07.120
<v Speaker 10>analytics and other prediction based machine learning. So those customers

0:27:07.160 --> 0:27:09.280
<v Speaker 10>that are able to pivot, they don't have to come

0:27:09.359 --> 0:27:12.359
<v Speaker 10>up with a new data strategy. They just pivot and

0:27:12.400 --> 0:27:15.320
<v Speaker 10>they go fast on JENNI because they're starting from that

0:27:15.720 --> 0:27:16.560
<v Speaker 10>data strategy.

0:27:16.680 --> 0:27:19.520
<v Speaker 4>Caroline, if you just peel back behind generatord AI, just

0:27:19.560 --> 0:27:20.959
<v Speaker 4>get rid of that word for a second.

0:27:21.280 --> 0:27:22.760
<v Speaker 3>There are some pretty cool things happening.

0:27:22.760 --> 0:27:26.080
<v Speaker 4>People are building things software with new use cases.

0:27:26.160 --> 0:27:28.760
<v Speaker 5>And we were just hearing about my AI from Snapchat.

0:27:28.800 --> 0:27:30.800
<v Speaker 5>You were talking about cops my land.

0:27:31.480 --> 0:27:34.320
<v Speaker 2>Ultimately, though, what is like the coolest thing that you've

0:27:34.320 --> 0:27:37.160
<v Speaker 2>seen built that just wouldn't have been possible a year ago?

0:27:37.240 --> 0:27:39.360
<v Speaker 2>Because I feel we get so caught up in the hype,

0:27:39.480 --> 0:27:41.240
<v Speaker 2>But actually a lot of this stuff, as you say,

0:27:41.320 --> 0:27:44.959
<v Speaker 2>is machine learning AI that perhaps was already predictive in nature.

0:27:45.160 --> 0:27:49.439
<v Speaker 2>What is ultimately actually new that you've seen that couldn't

0:27:49.440 --> 0:27:50.360
<v Speaker 2>have been done previously?

0:27:51.320 --> 0:27:53.760
<v Speaker 10>Well, Caroline, I have to say, I have three children,

0:27:53.840 --> 0:27:56.080
<v Speaker 10>and if you asked me to pick my favorite child,

0:27:56.119 --> 0:27:58.440
<v Speaker 10>I don't think I could do that. That is much

0:27:58.480 --> 0:28:01.199
<v Speaker 10>the same with so many any of the new innovations

0:28:01.200 --> 0:28:04.439
<v Speaker 10>that are coming out everywhere. I think, you know, if

0:28:04.480 --> 0:28:07.679
<v Speaker 10>I look at the my AI capability for snap I

0:28:07.680 --> 0:28:10.879
<v Speaker 10>think that's that's really transformative.

0:28:10.160 --> 0:28:13.920
<v Speaker 6>In the social media space. We have so many different examples.

0:28:13.960 --> 0:28:19.760
<v Speaker 10>I think Canva is another one Canvas, a graphics tool,

0:28:19.960 --> 0:28:22.119
<v Speaker 10>and it has over one hundred and thirty five million

0:28:22.240 --> 0:28:26.240
<v Speaker 10>monthly active users and they are generating imagery off of

0:28:26.320 --> 0:28:29.040
<v Speaker 10>text props. That's I think that's pretty amazing and I

0:28:29.040 --> 0:28:31.919
<v Speaker 10>think it's really cool what AWS has with code Whisper.

0:28:32.320 --> 0:28:34.919
<v Speaker 10>You know, as somebody who builds software services myself, the

0:28:35.000 --> 0:28:39.160
<v Speaker 10>idea that you can generate code from existing code and

0:28:39.280 --> 0:28:43.480
<v Speaker 10>comments automatically, I think is just going to be transformative

0:28:43.920 --> 0:28:45.719
<v Speaker 10>for how we build software in the future.

0:28:45.960 --> 0:28:48.040
<v Speaker 3>That's what we want to talk about building things.

0:28:48.120 --> 0:28:51.920
<v Speaker 4>AWS Vice president Mylan Thompson Bookovec thank you very much.

0:28:51.960 --> 0:28:55.280
<v Speaker 4>Now coming out Tesla offering three months of free fast

0:28:55.360 --> 0:28:58.240
<v Speaker 4>charging in the US, with a goal of clearing inventory

0:28:58.520 --> 0:29:01.360
<v Speaker 4>of Model threesidands before the end of the quarter. Much

0:29:01.400 --> 0:29:04.880
<v Speaker 4>more on that next Real Quick watching shares of software one.

0:29:04.920 --> 0:29:08.080
<v Speaker 4>The company's board said. Bain Capital's three point two billion

0:29:08.120 --> 0:29:11.320
<v Speaker 4>dollar offer to take the IT Services provide a private

0:29:11.800 --> 0:29:14.640
<v Speaker 4>undervalues the company. The latest heard when the private equity

0:29:14.680 --> 0:29:17.960
<v Speaker 4>firms attempt to buy that big European technau.

0:29:18.320 --> 0:29:19.040
<v Speaker 3>This is Bloomberg.

0:29:28.080 --> 0:29:31.840
<v Speaker 4>This is a North American charging standard or NACS connector,

0:29:31.960 --> 0:29:34.680
<v Speaker 4>and it was invented by Tesla, and this is a

0:29:34.680 --> 0:29:39.160
<v Speaker 4>CCS connector and CCS stands for Combined Charging system and

0:29:39.240 --> 0:29:43.520
<v Speaker 4>it was used by almost everybody else. Dad's until big news. O,

0:29:43.680 --> 0:29:45.520
<v Speaker 4>hey Tesla, this is Ford and GM.

0:29:45.600 --> 0:29:47.200
<v Speaker 3>Yeah, we're joining team NACS.

0:29:47.560 --> 0:29:51.520
<v Speaker 4>Ford and GM announced they'd adopt NACS in future models

0:29:51.560 --> 0:29:55.080
<v Speaker 4>and they get access to the Tesla charger network, and

0:29:55.240 --> 0:29:59.520
<v Speaker 4>that essentially created a US wide standard. Charging Providers like

0:29:59.640 --> 0:30:03.520
<v Speaker 4>charge Point, EVgo, Rulebox, and Blink followed suit, saying they'd

0:30:03.520 --> 0:30:07.760
<v Speaker 4>offer technology that works with Tesla's connectors and offer CCS.

0:30:07.840 --> 0:30:08.640
<v Speaker 3>Here's the history.

0:30:08.760 --> 0:30:13.440
<v Speaker 4>Twenty eleven, automakers like four, GM, Volkswagen, and BMW say

0:30:13.480 --> 0:30:14.840
<v Speaker 4>they'll collaborate.

0:30:14.360 --> 0:30:16.160
<v Speaker 3>On the combined Charging system.

0:30:16.400 --> 0:30:20.400
<v Speaker 4>Their goal use CCS to standardize how evs are charged

0:30:20.520 --> 0:30:24.320
<v Speaker 4>in the US and Europe. Meanwhile, Tesla develops its own

0:30:24.360 --> 0:30:27.760
<v Speaker 4>proprietary technology that's been used since twenty twelve when.

0:30:27.640 --> 0:30:29.240
<v Speaker 3>The Model Less went into production.

0:30:29.520 --> 0:30:34.880
<v Speaker 4>Those NACS connectors are lighter, approximately half the size, and

0:30:34.920 --> 0:30:38.960
<v Speaker 4>can transfer more power than CCS. The reality is Tesla's

0:30:39.080 --> 0:30:43.080
<v Speaker 4>NACS network is already bigger than the CCS network in America,

0:30:43.160 --> 0:30:46.160
<v Speaker 4>but there's still some concerns. Advocates for CCS say that

0:30:46.320 --> 0:30:49.280
<v Speaker 4>NACS is not open source and it has not been

0:30:49.360 --> 0:30:50.120
<v Speaker 4>peer reviewed.

0:30:50.480 --> 0:30:51.120
<v Speaker 3>For now, it.

0:30:51.120 --> 0:30:58.120
<v Speaker 4>Seems to be a case of Tesla's way or all

0:30:58.240 --> 0:31:00.560
<v Speaker 4>right for more, let's bring in Bloomberg's to a whole.

0:31:00.680 --> 0:31:03.360
<v Speaker 4>That's the context of the last week, Dana the news

0:31:03.800 --> 0:31:05.360
<v Speaker 4>Tesla offering free charging.

0:31:05.360 --> 0:31:08.360
<v Speaker 3>What do we know? Well, it's not free.

0:31:08.560 --> 0:31:12.200
<v Speaker 11>I mean, you know, Ford and GM customers are going

0:31:12.240 --> 0:31:14.360
<v Speaker 11>to have to pay for it. But supercharging has become

0:31:14.400 --> 0:31:16.520
<v Speaker 11>a big value add for Tesla, and I think we've

0:31:16.560 --> 0:31:19.719
<v Speaker 11>seen consumers now you know, they're no longer worried about

0:31:20.280 --> 0:31:22.480
<v Speaker 11>range anxiety so much as they are if I go

0:31:22.560 --> 0:31:25.000
<v Speaker 11>to a charging station, isn't going to work because we've

0:31:25.000 --> 0:31:28.720
<v Speaker 11>seen a lot of reliability studies out about broken chargers

0:31:28.760 --> 0:31:30.840
<v Speaker 11>and that's just not okay. Like we're in this big

0:31:30.880 --> 0:31:33.680
<v Speaker 11>transition to electric vehicles, being able to know that you're

0:31:33.680 --> 0:31:35.000
<v Speaker 11>going to be able to charge when you go to

0:31:35.080 --> 0:31:37.600
<v Speaker 11>your destination is a big point for consumers.

0:31:38.200 --> 0:31:41.760
<v Speaker 2>Meanwhile, they're still trying to sell that caused Tesla as

0:31:41.760 --> 0:31:44.760
<v Speaker 2>well as being able to beef up their revenue streams

0:31:44.760 --> 0:31:48.200
<v Speaker 2>and the forward looking nature of being able to you know,

0:31:48.320 --> 0:31:51.600
<v Speaker 2>share its own capacity to charge. What are they doing

0:31:51.600 --> 0:31:53.360
<v Speaker 2>with all the Model threes that they are not able

0:31:53.360 --> 0:31:54.000
<v Speaker 2>to shift right.

0:31:53.920 --> 0:31:57.920
<v Speaker 11>Now, right, so they are offering free supercharging for three months.

0:31:58.000 --> 0:32:00.440
<v Speaker 11>Anyone who takes a Model three takes livery of a

0:32:00.440 --> 0:32:03.600
<v Speaker 11>Model three before June thirtieth, which conveniently is the end

0:32:03.640 --> 0:32:06.200
<v Speaker 11>of the second quarter. So you're now start of seeing

0:32:06.240 --> 0:32:09.680
<v Speaker 11>supercharger be a lever that Tesla is pulling to kind

0:32:09.720 --> 0:32:12.040
<v Speaker 11>of help spur demand as they're trying to clear that inventory.

0:32:12.080 --> 0:32:14.080
<v Speaker 5>It's a sort of what price with that? Ultimately, what

0:32:14.120 --> 0:32:14.719
<v Speaker 5>are you saving?

0:32:15.360 --> 0:32:17.040
<v Speaker 11>I think it really depends on how much you drive.

0:32:17.080 --> 0:32:18.959
<v Speaker 11>I mean, the important thing is that most people who

0:32:19.040 --> 0:32:22.640
<v Speaker 11>own an electric car charge overnight at home. Supercharging is

0:32:22.680 --> 0:32:24.440
<v Speaker 11>really just for those longer road traditions.

0:32:24.520 --> 0:32:25.640
<v Speaker 5>Yeah, but it's not.

0:32:25.720 --> 0:32:27.320
<v Speaker 11>I mean, it used to be free when Tesla was

0:32:27.320 --> 0:32:29.800
<v Speaker 11>first a company, and now now you know it's it's

0:32:29.800 --> 0:32:32.320
<v Speaker 11>a it's a cost, but it's it's free if you

0:32:32.320 --> 0:32:33.320
<v Speaker 11>buy a car before.

0:32:33.120 --> 0:32:33.760
<v Speaker 5>The end of the month.

0:32:34.240 --> 0:32:37.040
<v Speaker 4>I thought, so, Donna, the story with Tesla's kind of changed.

0:32:37.080 --> 0:32:40.600
<v Speaker 4>You always nail it and you wrote that the charger

0:32:40.880 --> 0:32:43.880
<v Speaker 4>or the network is Tesla's shrewdest product.

0:32:44.280 --> 0:32:45.120
<v Speaker 3>What do you mean by that?

0:32:46.080 --> 0:32:48.440
<v Speaker 11>I just think they had the foresight very early on,

0:32:48.640 --> 0:32:51.480
<v Speaker 11>going over a decade now that charging was going to

0:32:51.480 --> 0:32:54.120
<v Speaker 11>be really key to consumer adoption, and you know, the

0:32:54.160 --> 0:32:57.040
<v Speaker 11>CCS standard is kind of like a standard by committee,

0:32:57.080 --> 0:32:59.600
<v Speaker 11>it was very slow moving. Tesla was like, we can't

0:32:59.640 --> 0:33:01.320
<v Speaker 11>wait coming out with the model S. We're going to

0:33:01.320 --> 0:33:04.320
<v Speaker 11>make our own. And they have really chosen very good

0:33:04.360 --> 0:33:07.520
<v Speaker 11>locations and they have the telematics and the data from

0:33:07.560 --> 0:33:10.320
<v Speaker 11>how people to charge to know where they need to

0:33:10.320 --> 0:33:12.920
<v Speaker 11>add more chargers, where people charge the longest, what the

0:33:12.920 --> 0:33:16.320
<v Speaker 11>biggest stops are. I mean, the Harris Rants supercharger station

0:33:16.920 --> 0:33:20.360
<v Speaker 11>has ninety eight stalls. That's the big station on the

0:33:20.440 --> 0:33:24.200
<v Speaker 11>route between the Bay Area and Los Angeles. And you know,

0:33:24.320 --> 0:33:27.560
<v Speaker 11>other car companies, I mean they just serve I think

0:33:27.600 --> 0:33:32.720
<v Speaker 11>recognizing that the superchargers are better, they're faster, they work,

0:33:32.880 --> 0:33:36.080
<v Speaker 11>and like Tesla maintains them, whereas like with these other

0:33:36.360 --> 0:33:38.320
<v Speaker 11>charging companies that are out there, like it's not really

0:33:38.400 --> 0:33:41.200
<v Speaker 11>clear who maintains them once they're installed, and the user

0:33:41.240 --> 0:33:44.280
<v Speaker 11>interface isn't as good. So you know what's interesting is

0:33:44.320 --> 0:33:46.560
<v Speaker 11>this is this dominance is not the case in Europe

0:33:46.560 --> 0:33:49.080
<v Speaker 11>and China, but in the US for sure, like the

0:33:49.120 --> 0:33:51.800
<v Speaker 11>supercharger network is seen as the best out there, which

0:33:51.880 --> 0:33:54.200
<v Speaker 11>is why Ford and GM have just joined it.

0:33:54.280 --> 0:33:56.840
<v Speaker 5>Donahow, great to have you here in EYL. Thank people

0:33:56.840 --> 0:33:58.120
<v Speaker 5>coming and spending some time with us.

0:33:58.480 --> 0:34:10.760
<v Speaker 2>Really appreciate it. Now tonight's episode of The Circuit, Emily

0:34:10.840 --> 0:34:14.120
<v Speaker 2>Chang sits down with Open aiyes Mira Mariti, the company's

0:34:14.200 --> 0:34:17.239
<v Speaker 2>chief technology officer, and really just gets to grips with

0:34:17.360 --> 0:34:19.760
<v Speaker 2>some of the potential risks the rewards of a world

0:34:19.800 --> 0:34:22.600
<v Speaker 2>with widespread artificial intelligence.

0:34:23.600 --> 0:34:25.759
<v Speaker 6>Through certainly a risk that.

0:34:28.239 --> 0:34:30.799
<v Speaker 12>When we have this AI systems that are able to

0:34:30.880 --> 0:34:33.920
<v Speaker 12>set to their own goals, they decide that their goals

0:34:33.960 --> 0:34:39.080
<v Speaker 12>are not aligned with ours and they do not benefit

0:34:39.160 --> 0:34:42.480
<v Speaker 12>from having us around and could lead to human execution.

0:34:43.560 --> 0:34:44.719
<v Speaker 10>That is a risk.

0:34:46.320 --> 0:34:46.960
<v Speaker 3>The Circuit.

0:34:47.239 --> 0:34:50.280
<v Speaker 4>To watch more of Emily Chang's interview with Miramurati, opens

0:34:50.400 --> 0:34:53.439
<v Speaker 4>Ai CTO and Read Hoffman actually, who was an early

0:34:53.440 --> 0:34:57.080
<v Speaker 4>Open Ai investor, watched The Circuit Emily Chang tonight ten

0:34:57.120 --> 0:35:00.040
<v Speaker 4>pm in New York on Bloomberg Television, or stream it

0:35:00.360 --> 0:35:04.400
<v Speaker 4>at eight pm Eastern on Bloomberg Originals. Now much of

0:35:04.480 --> 0:35:07.640
<v Speaker 4>Silicon Valley is playing catch up in the AI race,

0:35:07.760 --> 0:35:11.400
<v Speaker 4>chasing after Microsoft, which has been investing in the hottest

0:35:11.400 --> 0:35:15.319
<v Speaker 4>startup on the market open Ai since twenty nineteen. Now

0:35:15.320 --> 0:35:18.720
<v Speaker 4>it's preparing to cash in on that investment. It's today's

0:35:18.760 --> 0:35:20.880
<v Speaker 4>big take, and joining us for more is one of

0:35:20.880 --> 0:35:22.560
<v Speaker 4>the co buy lines on that big take.

0:35:22.840 --> 0:35:25.640
<v Speaker 3>Dina bass this in Business Week.

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<v Speaker 4>Talk to me about the leapfrogging Google years and years

0:35:30.360 --> 0:35:34.959
<v Speaker 4>of research, but didn't want to go towards commercialization. Microsoft

0:35:35.080 --> 0:35:38.120
<v Speaker 4>this scattergun approach, multiple chains looking at ai.

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<v Speaker 3>Clippy is in there along the way. Now everything's changed.

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<v Speaker 13>A lot of the difference is Microsoft's ceostat Inadella's decision

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<v Speaker 13>to really bet on open Ai and to premise a

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<v Speaker 13>lot of Microsoft's strategy to underpin a lot of its products,

0:35:55.480 --> 0:35:58.640
<v Speaker 13>the entire load of products that's been unveiling in the

0:35:58.719 --> 0:36:02.440
<v Speaker 13>last six months on the open Ai technology. That's a

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<v Speaker 13>really unusual move for Microsoft. Microsoft has you know, we

0:36:05.880 --> 0:36:08.080
<v Speaker 13>spoke to a lot of people inside and outside the company.

0:36:08.320 --> 0:36:11.480
<v Speaker 13>The company is really never before relied on an outside

0:36:11.560 --> 0:36:15.800
<v Speaker 13>company to underpin so significantly, it's bet on a major

0:36:15.880 --> 0:36:18.799
<v Speaker 13>platform shift such as as ai is expected to be.

0:36:19.320 --> 0:36:21.840
<v Speaker 13>So that's that's a real difference, and it's made a

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<v Speaker 13>huge difference for Microsoft because if you go back a

0:36:24.000 --> 0:36:26.840
<v Speaker 13>couple of years when they're Microsoft had a lot of

0:36:26.880 --> 0:36:30.280
<v Speaker 13>AI efforts going on, but they weren't amounting too much

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<v Speaker 13>in terms of products or in terms of a coherence strategy.

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<v Speaker 4>The Big Take also poses questions about open Ai, whether

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<v Speaker 4>it's actually the hottest startup out there or actually, in practice,

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<v Speaker 4>if it's a subsidiary of Microsoft.

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<v Speaker 13>Now you know, I mean financially it's clearly not a subsidiary.

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<v Speaker 13>Microsoft's put a total of thirteen billion into open Ai,

0:36:53.160 --> 0:36:56.000
<v Speaker 13>according to people familiar with the deals with Not all

0:36:56.040 --> 0:36:59.960
<v Speaker 13>of those deals amounts republic obviously, but you know, there

0:37:00.120 --> 0:37:01.480
<v Speaker 13>is and this is a little bit of, like, you know,

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<v Speaker 13>one of the hotter parlor games in tech right now,

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<v Speaker 13>a discussion of you know, who is the controlling party here?

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<v Speaker 13>You know, does Microsoft? You know, is Microsoft the more

0:37:10.520 --> 0:37:12.920
<v Speaker 13>important party? Is open Ai the more important party? And

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<v Speaker 13>the truth is that to a large extent, they're very

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<v Speaker 13>codependent on each other. They're, you know, both the futures

0:37:18.400 --> 0:37:21.000
<v Speaker 13>of both companies and some pretty significant ways are tied

0:37:21.080 --> 0:37:22.480
<v Speaker 13>up in the work of the other one.

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<v Speaker 4>At this point, there's a key character in this story,

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<v Speaker 4>Kevin Scott, Microsoft's chief technology officer. He finds his way

0:37:30.560 --> 0:37:34.400
<v Speaker 4>to Microsoft through the LinkedIn acquisition, and then in twenty

0:37:34.520 --> 0:37:38.880
<v Speaker 4>nineteen he basically gets Microsoft's act together in how it

0:37:39.160 --> 0:37:42.120
<v Speaker 4>goes about tackling AI. Right.

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<v Speaker 13>So Kevin Scott, very shortly after LinkedIn closes taught him

0:37:45.719 --> 0:37:48.879
<v Speaker 13>makes Kevin Scott the CTO for the whole company, and

0:37:49.080 --> 0:37:52.360
<v Speaker 13>one of his missions, one of his charges, was to

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<v Speaker 13>come up with a way for Microsoft's AI strategy to

0:37:55.640 --> 0:38:00.200
<v Speaker 13>be more focused, more coherent, and most importantly, more impactful.

0:38:00.440 --> 0:38:03.799
<v Speaker 13>And Kevin, you know who has a long standing relationship,

0:38:04.360 --> 0:38:06.960
<v Speaker 13>you know, with Sam Altman, actually you know, winds up

0:38:07.000 --> 0:38:10.600
<v Speaker 13>being the go between and the negotiations between the two companies.

0:38:10.760 --> 0:38:12.600
<v Speaker 13>He's also someone that spent a fair amount of time

0:38:12.640 --> 0:38:14.719
<v Speaker 13>at Google. And one of the things he notices when

0:38:14.719 --> 0:38:17.279
<v Speaker 13>he comes in and he looks at the Microsoft AI efforts, Spaci.

0:38:17.320 --> 0:38:19.040
<v Speaker 13>You know, a lot of your listeners might think, you know,

0:38:19.080 --> 0:38:21.920
<v Speaker 13>Microsoft just got into AI. Actually Microsoft been working on

0:38:21.960 --> 0:38:25.080
<v Speaker 13>AI for more than two decades. But what Scott saw

0:38:25.320 --> 0:38:27.520
<v Speaker 13>started looking at all the projects and he looked at

0:38:27.560 --> 0:38:31.960
<v Speaker 13>it via the request for GPUs, these key AI chips

0:38:32.000 --> 0:38:34.759
<v Speaker 13>for every AI project in the company, and there were

0:38:34.840 --> 0:38:37.120
<v Speaker 13>so many requests. He told us it was basically the

0:38:37.160 --> 0:38:40.160
<v Speaker 13>magnitude of Microsoft's entire capital budget, and there were all

0:38:40.239 --> 0:38:44.160
<v Speaker 13>these disparate projects that didn't have a business model, weren't

0:38:44.200 --> 0:38:47.840
<v Speaker 13>talking to each other, and he, you know, around twenty nineteen,

0:38:48.000 --> 0:38:49.719
<v Speaker 13>he and the Della come up with his plans, are

0:38:49.719 --> 0:38:53.279
<v Speaker 13>really instilled some discipline and make sure everything is you know,

0:38:53.600 --> 0:38:56.320
<v Speaker 13>marching towards some big goals. But also they do the

0:38:56.360 --> 0:38:59.200
<v Speaker 13>open Ai investment that same year, which is a huge bet.

0:38:59.239 --> 0:39:01.720
<v Speaker 13>Again not on my work, else's.

0:39:02.360 --> 0:39:06.279
<v Speaker 4>Bloomberg's Dina Burs just terrific deep reporting for the big

0:39:06.320 --> 0:39:08.279
<v Speaker 4>take in Business Week. Check it out online on the

0:39:08.320 --> 0:39:11.960
<v Speaker 4>Bloomberg terminal. Also talks a lot about how Microsoft commercialized

0:39:12.200 --> 0:39:14.799
<v Speaker 4>the technology, which we didn't have time to get to.

0:39:14.960 --> 0:39:15.960
<v Speaker 3>That does it, I'm afraid.

0:39:16.160 --> 0:39:19.440
<v Speaker 4>For this edition of Bloomberg Technology, we are four days

0:39:19.440 --> 0:39:22.759
<v Speaker 4>into a mega mega week from Silicon Valley.

0:39:22.520 --> 0:39:23.200
<v Speaker 3>And in New York.

0:39:23.239 --> 0:39:26.080
<v Speaker 4>You can recap what we've been talking about with the

0:39:26.120 --> 0:39:32.040
<v Speaker 4>Bloomberg Technology Podcast wherever you get your podcasts, Apple, Spotify, iHeart,

0:39:32.080 --> 0:39:35.799
<v Speaker 4>and the Bloomberg platforms of course from San Francisco. This

0:39:36.360 --> 0:39:37.640
<v Speaker 4>is Bloomberg Technology