WEBVTT - Snowflake Jumps Most Since 2020 After Amazon Deal

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

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

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<v Speaker 1>and ever Low in sentences.

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<v Speaker 2>Go this is Bloomberg Tech coming up.

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<v Speaker 3>Bloomberg News pulls back the curtains on Apple's revamped Siri

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<v Speaker 3>design ahead of its WWDC debut.

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<v Speaker 4>Plus Snowflake jumps the most It's twenty twenty after the

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<v Speaker 4>software maker gave a stronger outlook and sign a six

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<v Speaker 4>billion dollar deal with Amazon.

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<v Speaker 5>We'll hear from the CEO.

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<v Speaker 3>And Meta introduces paid chatbot subscriptions to help offset its

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<v Speaker 3>AI infrastructure costs.

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<v Speaker 4>First we look at infrastructure and how actually an infrastructure

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<v Speaker 4>deal with Amazon is helping summon the narrative around Snowflake.

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<v Speaker 4>Extraordinary move, the biggest jump in the stock since twenty twenty.

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<v Speaker 4>We're looking at thirty four percent gain after a thirty

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<v Speaker 4>four percent in product revenue for this company. It was

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<v Speaker 4>a beat, it was a raise, and there's real acceleration

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<v Speaker 4>in people using their AI coding tool. In particular, twenty

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<v Speaker 4>two billion dollars added in a market cap so much

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<v Speaker 4>to digest today.

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<v Speaker 2>Ed a lot of news headlines this morning.

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<v Speaker 3>One coming from the information that Microsoft next week is

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<v Speaker 3>going to introduce a coding model, a model focused on coding,

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<v Speaker 3>a marketplace we've covered so much of late the stock

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<v Speaker 3>off session highs that we saw gains three and a

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<v Speaker 3>half almost four percent, So the market taking it seriously.

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<v Speaker 2>If we hear more, will give you more.

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<v Speaker 4>Well, and now we can give you more on what

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<v Speaker 4>to expect with Apple's Siri overhaul, because it's going to

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<v Speaker 4>take center stage in the company's next major software update,

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<v Speaker 4>and Bloomberg News has details on what to expect ahead

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<v Speaker 4>of the WWDC debut.

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<v Speaker 5>Now, these Bloomberg.

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<v Speaker 4>Created illustrations, they offer a look at the revamped Sery interface,

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<v Speaker 4>including a new chatbot style app that the images that

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<v Speaker 4>you're currently looking at they're based on information viewed by

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<v Speaker 4>Bloomberg and people with knowledge of the company's plans.

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<v Speaker 5>Well those plans.

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<v Speaker 4>It's Bloomberg Consumer Tech and Apple Managing editor Mark German.

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<v Speaker 5>So the look the feel is really building.

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<v Speaker 4>On some of the updates we've had in the past

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<v Speaker 4>and improving them.

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<v Speaker 6>Well, I'll just say this, this is an incredibly exciting

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<v Speaker 6>moment for Apple.

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<v Speaker 7>I think consumers should be pumped.

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<v Speaker 6>What Apple is doing here is they've seen everything that

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<v Speaker 6>Open Ai and Google and Anthropic have done. They believe

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<v Speaker 6>that AI has a place at the center of its products,

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<v Speaker 6>and they're finally going to implement that.

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<v Speaker 7>So this is a really big deal for consumers.

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<v Speaker 6>People have been clamoring for a version of Siri that

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<v Speaker 6>works properly for the better part of fifteen years, and

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<v Speaker 6>my strong belief as we are finally going to get

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<v Speaker 6>this fall So I see this as a major development

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<v Speaker 6>and accomplishment for Apple in its quest to try to

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<v Speaker 6>bring AI to the masses, taking a slightly different tack

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<v Speaker 6>than their rivals in the space.

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<v Speaker 3>There's two parts to this, as you report it. There's

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<v Speaker 3>the standalone Siri app, let's say it's a kin to

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<v Speaker 3>a chat GPT app. And then there's how you interact

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<v Speaker 3>with Siri on the screen of your phone. You know, however,

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<v Speaker 3>you open up the phone, we're going to go through

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<v Speaker 3>some of the images that you included in the story,

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<v Speaker 3>But could you just explain those two parts that we're detailing,

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<v Speaker 3>and as we cycle through the images, we're showing them on.

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<v Speaker 2>The screen right now.

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<v Speaker 3>Again, these are Bloomberg generated images based on our reporting,

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<v Speaker 3>both discussions with sources and documentation that we viewed but

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<v Speaker 3>those two new features.

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<v Speaker 6>Please, So to launch Sirie today, you say, obviously the

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<v Speaker 6>SII wake word or Hey Siri if you have an older.

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<v Speaker 7>Device, or you can hold down the power button.

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<v Speaker 6>That continues, and there's a new animation that pops out.

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<v Speaker 7>Of the dynamic island.

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<v Speaker 6>Obviously they added that with the fourteen proback in twenty

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<v Speaker 6>twenty two, so this is with modern iPhone hardware in mind.

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<v Speaker 6>The second thing you can do was swipe down from

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<v Speaker 6>the top center of the iPhone. So how you open

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<v Speaker 6>notifications today will be how you open a new serie

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<v Speaker 6>interface called search or Ask, and that essentially takes you

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<v Speaker 6>into a type to serie interface basically a system wide

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<v Speaker 6>AI agent. You can tell it to get things done

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<v Speaker 6>on your behalf. You can do searches on your device

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<v Speaker 6>as well as the open Web. So there's a perplexity

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<v Speaker 6>competitor from Apple, built by Apple, developed by Apple, designed

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<v Speaker 6>by Apple in there as well. And then there's the

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<v Speaker 6>serie app. You know, chatbots have taken the world by storm.

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<v Speaker 6>Chat GPT has nearly a billion users. People are using Gemini,

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<v Speaker 6>people are using claud. This is clearly something that people want.

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<v Speaker 6>So this is a product an app in line with

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<v Speaker 6>what you're getting from Google Gemini.

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<v Speaker 7>Obviously, as we reported last year, the.

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<v Speaker 6>Underlying models for a lot of these new technologies in

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<v Speaker 6>Siri are powered by Gemini and running on Google's cloud infrastructure.

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<v Speaker 4>How worried should like a chat che should open aib

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<v Speaker 4>right now? You reported that maybe they even considering legal action.

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<v Speaker 4>Is this going to be a real standalone competitor.

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<v Speaker 6>Well, we've seen this time and time again where Apple

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<v Speaker 6>releases a standalone app of its own that's built into

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<v Speaker 6>the operating system. I think chat GPT has the strongest brand.

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<v Speaker 6>Serie doesn't have a very strong brand. I still think

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<v Speaker 6>they should, you know, rebrand the whole effort. That's neither

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<v Speaker 6>here nor there, at least for now, but definitely having

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<v Speaker 6>a chatbop built into iOS, mac os, iPad os north

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<v Speaker 6>of two billion devices that is threatening. I would say

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<v Speaker 6>to Gemini to chat GPT and to Claude, especially if

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<v Speaker 6>over time Apple is able to make it really competitive

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<v Speaker 6>to what you're seeing to chat GPT.

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<v Speaker 7>So we'll have to see how this plays out.

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<v Speaker 6>Over time, but at least, you know, in the short term,

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<v Speaker 6>a lot of people are going to be introduced to

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<v Speaker 6>the concept of a chat or a conversational AI interface

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<v Speaker 6>who haven't used it before, despite the popularity of church.

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<v Speaker 3>Gipt, Bluebo's Mark Gumman, Thank you very much. Let's get

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<v Speaker 3>to another story. Shares a Salesforce up about a percentage point,

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<v Speaker 3>kind of a muted move, and you're gonna understand why.

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<v Speaker 3>In a few minutes time, the company gave a revenue

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<v Speaker 3>outlook for the current period that just fell short of

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<v Speaker 3>an this estimates Bloemberg's Brady Ford covering Salesforce with us.

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<v Speaker 3>Now we're kind of waiting for a different story in

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<v Speaker 3>a minute's time, which might give us some context on

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<v Speaker 3>that move. But what was the story of Salesforce? Forget

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<v Speaker 3>the outlook the numbers. What were they saying?

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<v Speaker 8>Application companies are trying to reinvent themselves as AI companies,

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<v Speaker 8>and so Salesforce came out and said, we have an

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<v Speaker 8>AI product that's kind of ramping and revenue.

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<v Speaker 7>We have all these.

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<v Speaker 8>Positive traction points, but our core products, for you know,

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<v Speaker 8>sales and service are slowing down, and so it's how

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<v Speaker 8>quickly can they reinvent themselves At this point, not very

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<v Speaker 8>I mean their app a percentage point today, but if

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<v Speaker 8>that chart zooms out, it has not been a rosy

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<v Speaker 8>picture for Salesforce, and the last year or two it's down.

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<v Speaker 5>Thirty percent year to date.

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<v Speaker 4>Brody, I loved your content on LinkedIn, just showing that,

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<v Speaker 4>like basically all earnings caols are now turning into podcasts,

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<v Speaker 4>so they're.

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<v Speaker 5>Trying to reframe and rebrand the way in which they

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<v Speaker 5>present these results.

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<v Speaker 4>But like many off is saying, this is still a

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<v Speaker 4>record quarter, So how do we get more confident that.

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<v Speaker 5>There is going to be that.

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<v Speaker 4>Second half inflection on organic growth?

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<v Speaker 8>Yeah, it's just that reacceleration story, right, I mean, their

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<v Speaker 8>biggest products keep slowing down, They've done acquisitions, they've added

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<v Speaker 8>new products, and so there's kind of a lot of

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<v Speaker 8>rosy things to look at. But until that kind of

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<v Speaker 8>core sales, cloud service, cloud that really built their house,

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<v Speaker 8>until that speeds back up due to AI, they're going

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<v Speaker 8>to stay in that penalty box.

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<v Speaker 3>Should we just very quickly talk about the actual story today?

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<v Speaker 3>Teams throw it up on the screen. Snowflake is going

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<v Speaker 3>absolutely parabolic.

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<v Speaker 9>Yep.

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<v Speaker 8>Why, it's a tale of two cities, right, I Mean

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<v Speaker 8>snow makes data infrastructure software, So a lot of companies

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<v Speaker 8>have their most important data sitting in Snowflake and they

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<v Speaker 8>have to use it if they want to do all

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<v Speaker 8>these cool AI features on top of it. And we're

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<v Speaker 8>seeing in the numbers that demand for Snowflake's products is

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<v Speaker 8>kind of going gangbusters. So they had a great day.

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<v Speaker 4>They did, and Brodiefd, you're gonna stick with us to

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<v Speaker 4>talk about a little bit more Snowflake so you can

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<v Speaker 4>see that move means it's added twenty two billion dollars

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<v Speaker 4>to its market capitalization. I mean after beating and expectations.

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<v Speaker 4>They've also locked in that massive six billion dollar infrastructure

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<v Speaker 4>deal with Amazon. We could talk about that with Brody

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<v Speaker 4>in a minute, but first of all, just take from

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<v Speaker 4>the Snowflake CEO himself, Shieto Ramaswami.

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<v Speaker 5>We spoke to Melia.

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<v Speaker 7>First of all, they're.

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<v Speaker 9>A longtime partner. They are the biggest cloud service provider

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<v Speaker 9>that be run on top of and on on top

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<v Speaker 9>of Azura as well as GCP. The really important thing

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<v Speaker 9>with Amazon is how we go to our customers.

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<v Speaker 2>Together.

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<v Speaker 9>Bothrians are extraordinary value that we deliver for our customers,

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<v Speaker 9>and with deals like this we get massive economies of

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<v Speaker 9>scale that let us pass on some of these savings

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<v Speaker 9>back to our customers. We ounced a huge change in

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<v Speaker 9>how we price AI that makes AI a lot less

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<v Speaker 9>expensive for our customers. It's aided by deals like this

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<v Speaker 9>because of this ability to bulk purchase confidently, which, as

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<v Speaker 9>I said, in turn, we give to our customers create

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<v Speaker 9>amazing products on top.

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<v Speaker 2>This deal makes us much more effective.

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<v Speaker 9>Together, Amazon is interested in solving customer problems, and having

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<v Speaker 9>a data platform is a key part of solving customer problems,

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<v Speaker 9>us being able to go to market together. We work

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<v Speaker 9>at every level of the hierarchy. Matt and I are garment,

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<v Speaker 9>the CEO and I are in constant touch, but so

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<v Speaker 9>on our teams. It's that ability to collaborate at a

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<v Speaker 9>deep level to solve complex problems, for example, like ed

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<v Speaker 9>data migration that makes us pretty unique.

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<v Speaker 2>It is truly a better gather story.

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<v Speaker 3>What timing Caroline's conversation with the CEO of snowfake and

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<v Speaker 3>audio issues there that's tech happens.

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<v Speaker 2>Is this stock up thirty five.

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<v Speaker 3>Percent because of a compute deal with AWS or is

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<v Speaker 3>it up for a different reason, Like it's really difficult

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<v Speaker 3>in this moment to see the impact of that relationship

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<v Speaker 3>in how the market's cheering the name today.

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<v Speaker 8>It seems that most of the rally is due to

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<v Speaker 8>their own products and the fact that they have a

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<v Speaker 8>pretty strong outlook. But the Amazon deal is interesting because

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<v Speaker 8>a big part of the software story right now is

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<v Speaker 8>when you're spending all of this money on LMS on

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<v Speaker 8>AI features, that does hurt your margins, and so anything

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<v Speaker 8>that companies are able to do to get economies of

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<v Speaker 8>scale and drive costs down, which appears to be what's happening,

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<v Speaker 8>that's also good news.

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<v Speaker 5>I mean, ed will know this more than anyone.

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<v Speaker 4>The graviton offering that comes from AWS and the idea.

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<v Speaker 4>In your story, you make clear that maybe they're pushing

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<v Speaker 4>towards that because of.

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<v Speaker 5>These efficiency gains.

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<v Speaker 4>And we're going to hear from Shreidar a little bit

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<v Speaker 4>later in the show about that brody, but well, broady,

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<v Speaker 4>how are we seeing the adoption of coding tools Cortex

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<v Speaker 4>in particular seven thousand more than subscriptions?

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<v Speaker 5>Is that a lot? When you're thinking about the competitors

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<v Speaker 5>out there.

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<v Speaker 8>It's interesting because a lot of application platforms, they've had

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<v Speaker 8>their own tools like a coding assistant or other productivity

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<v Speaker 8>tools right and there in the platform. In a lot

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<v Speaker 8>of cases, we hadn't seen great uptake for it. And

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<v Speaker 8>so Snowflakes saying, Hey, actually the coding tool that we're

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<v Speaker 8>putting on here is being used. It is driving revenue.

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<v Speaker 8>That's kind of new. We haven't seen that from a

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<v Speaker 8>ton of other companies. And so I think that's a

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<v Speaker 8>pretty significant positive point that's being reacted to here.

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<v Speaker 5>And you just think about where Shreidar comes from.

0:11:44.120 --> 0:11:46.760
<v Speaker 4>Like his whole business AI business was bought by Snowflake

0:11:46.880 --> 0:11:49.600
<v Speaker 4>neither before, So no wonder he's managing to integrate at

0:11:49.600 --> 0:11:50.640
<v Speaker 4>Bloomberg's brody Ford.

0:11:50.800 --> 0:11:52.959
<v Speaker 5>Great Nawk, thanks for joining now.

0:11:52.960 --> 0:11:55.360
<v Speaker 4>Coming up, Navy is going to be joining us making

0:11:55.400 --> 0:11:58.319
<v Speaker 4>a major push towards electric marine travel, deploying one hundred

0:11:58.360 --> 0:12:02.920
<v Speaker 4>electric vessels are across the Maldives. How nice because speaking

0:12:02.960 --> 0:12:04.760
<v Speaker 4>with the CEO next, that's Bloomberg Tech.

0:12:20.679 --> 0:12:24.559
<v Speaker 3>US based maritime technology company Navier is deploying one hundred

0:12:24.600 --> 0:12:28.240
<v Speaker 3>electric vessels across the Maldives to build an inter island

0:12:28.280 --> 0:12:33.040
<v Speaker 3>transportation network linking airports, resorts, local communities. Roll up marks

0:12:33.040 --> 0:12:37.040
<v Speaker 3>a major milestone for electrified marine mobility. Joining us now

0:12:37.040 --> 0:12:41.680
<v Speaker 3>as Navy CEO some pretty badasharia back on Bloomberg Tech,

0:12:41.760 --> 0:12:45.640
<v Speaker 3>and with respect, last time you're on the program. Nava

0:12:45.679 --> 0:12:49.800
<v Speaker 3>was in a very different place just getting started. Fast forward,

0:12:50.200 --> 0:12:52.880
<v Speaker 3>you're going to put one hundred of your vessels in

0:12:52.960 --> 0:12:56.959
<v Speaker 3>a really interesting market, and you're really ramping up commercially

0:12:57.400 --> 0:12:59.120
<v Speaker 3>with one hundred million dollar deal.

0:12:59.480 --> 0:13:00.920
<v Speaker 2>Let's start with Moldives. Piece.

0:13:01.600 --> 0:13:03.400
<v Speaker 3>When we lost FOT, you weren't looking at this kind

0:13:03.400 --> 0:13:04.880
<v Speaker 3>of luxury into island market.

0:13:04.960 --> 0:13:05.440
<v Speaker 2>Now you are.

0:13:05.559 --> 0:13:12.160
<v Speaker 10>Why Actually we always saw the potential for you know,

0:13:12.240 --> 0:13:13.600
<v Speaker 10>transportation with the N.

0:13:13.679 --> 0:13:15.480
<v Speaker 11>Thirty for islands.

0:13:15.520 --> 0:13:19.680
<v Speaker 10>But what is interesting here is that Maldives is this

0:13:19.840 --> 0:13:23.520
<v Speaker 10>place where there's a natural need for the technology, and

0:13:23.640 --> 0:13:27.280
<v Speaker 10>that aligns very well with our vision. You know, it

0:13:27.280 --> 0:13:31.840
<v Speaker 10>has a vision for twenty thirty net zero and there's

0:13:32.040 --> 0:13:35.160
<v Speaker 10>over a thousand islands today, there is over you know,

0:13:35.400 --> 0:13:39.560
<v Speaker 10>two thousand, eight hundred gas guzzling boats. The fit is

0:13:39.640 --> 0:13:42.120
<v Speaker 10>so on spot, and you know, we are very grateful

0:13:42.160 --> 0:13:44.840
<v Speaker 10>for the partners we found who have like the you

0:13:44.880 --> 0:13:48.520
<v Speaker 10>know JIH who have the similar vision of like developing

0:13:48.559 --> 0:13:50.640
<v Speaker 10>the country's infrastructure.

0:13:51.200 --> 0:13:54.000
<v Speaker 4>Let's talk about the N thirty Pioneer edition. What does

0:13:54.040 --> 0:13:57.280
<v Speaker 4>it show in terms of performance? What does it do

0:13:57.320 --> 0:13:59.599
<v Speaker 4>that's unlike anything that's on the market.

0:14:00.800 --> 0:14:03.600
<v Speaker 10>Yeah, absolutely, you know, at a high level, our goal

0:14:03.760 --> 0:14:07.640
<v Speaker 10>at NAVIA is to build a standardized foundational layer I

0:14:07.679 --> 0:14:11.160
<v Speaker 10>would say the best possible platform on the water with

0:14:11.480 --> 0:14:14.199
<v Speaker 10>you know, dual use case, whether that's transportation or defense.

0:14:14.240 --> 0:14:15.719
<v Speaker 11>And we are very focused on.

0:14:15.720 --> 0:14:20.520
<v Speaker 10>Making this reliable, long range and applicable for different kind

0:14:20.600 --> 0:14:24.120
<v Speaker 10>of sea states. So this is not just the deployment

0:14:24.160 --> 0:14:26.840
<v Speaker 10>of the boat, but this is also the deployment of

0:14:26.880 --> 0:14:27.520
<v Speaker 10>a network.

0:14:27.640 --> 0:14:29.880
<v Speaker 11>So usually when you go somewhere.

0:14:29.600 --> 0:14:31.760
<v Speaker 10>You know you have one of boats that takes you

0:14:31.800 --> 0:14:34.920
<v Speaker 10>to an island, but in this case, it's more like

0:14:34.960 --> 0:14:35.880
<v Speaker 10>what you see in the land.

0:14:35.880 --> 0:14:36.880
<v Speaker 11>What do you see in the air? Right?

0:14:36.960 --> 0:14:39.680
<v Speaker 10>You have United Airlines, you have Black Lane, you have

0:14:39.760 --> 0:14:42.240
<v Speaker 10>four seasons on the land right, But when it comes

0:14:42.240 --> 0:14:44.479
<v Speaker 10>to the water, there is no standardization.

0:14:45.160 --> 0:14:47.520
<v Speaker 11>And what is different is that you know.

0:14:47.480 --> 0:14:50.320
<v Speaker 10>You are in this beautiful resource right, which are so

0:14:50.480 --> 0:14:54.680
<v Speaker 10>into sustainability, and then you get on the water and there's.

0:14:54.520 --> 0:14:55.720
<v Speaker 11>A huge disconnect.

0:14:56.200 --> 0:14:58.720
<v Speaker 10>And that's where we really come in. You know, that

0:14:58.960 --> 0:14:59.880
<v Speaker 10>experience part of.

0:14:59.840 --> 0:15:03.400
<v Speaker 3>It some pretty How much pressure are you under to

0:15:03.520 --> 0:15:08.160
<v Speaker 3>deliver for JIH and the Moldives project, like a hundred

0:15:08.280 --> 0:15:11.640
<v Speaker 3>of these are they built? How quickly do you build them?

0:15:11.680 --> 0:15:13.400
<v Speaker 3>Where do they get built? How do they get to

0:15:13.400 --> 0:15:15.440
<v Speaker 3>the Moltives give us a sense of how real this is.

0:15:16.360 --> 0:15:19.640
<v Speaker 10>Yes, absolutely, so, just to give a background, you know,

0:15:19.760 --> 0:15:22.840
<v Speaker 10>jih is led by Mama Dali Jihana. He's one of

0:15:22.880 --> 0:15:26.480
<v Speaker 10>the most influential business leaders of Maldives who have literally

0:15:26.560 --> 0:15:29.640
<v Speaker 10>known as the man who built Maldives, driving force behind

0:15:29.840 --> 0:15:34.480
<v Speaker 10>most of the prestigious hotels and resorts like the World

0:15:34.440 --> 0:15:36.840
<v Speaker 10>War four seasons, and they have also a presence in

0:15:37.440 --> 0:15:40.760
<v Speaker 10>the GCC. So I'm really working very closely with them

0:15:40.840 --> 0:15:44.120
<v Speaker 10>the first year, this very year, we're starting with five vessels.

0:15:44.600 --> 0:15:46.760
<v Speaker 10>The first one is going to get there you know,

0:15:47.120 --> 0:15:50.000
<v Speaker 10>end of summer, and then we are going to test

0:15:50.000 --> 0:15:52.560
<v Speaker 10>out this fleet and at the same time we will

0:15:52.600 --> 0:15:56.840
<v Speaker 10>be working very closely with you know jih to plan

0:15:56.880 --> 0:16:00.480
<v Speaker 10>out the infrastructure, the routes and then the you know,

0:16:00.960 --> 0:16:04.200
<v Speaker 10>deployment is phased over the next three years. So there

0:16:04.240 --> 0:16:07.280
<v Speaker 10>is a bit of like the infrastructure planning, route planning

0:16:07.320 --> 0:16:08.840
<v Speaker 10>and then the software lure of it.

0:16:09.000 --> 0:16:11.120
<v Speaker 11>Right, So we want to make this.

0:16:11.400 --> 0:16:14.960
<v Speaker 10>A very seamless experience where Malis really become almost like

0:16:15.040 --> 0:16:18.440
<v Speaker 10>the you know, it becomes a playbook of how to

0:16:18.600 --> 0:16:21.520
<v Speaker 10>replicate this in you know, many other places.

0:16:21.160 --> 0:16:24.480
<v Speaker 4>Well, how do you replicate that into a defense narrative

0:16:24.760 --> 0:16:26.680
<v Speaker 4>not just luxury briefly.

0:16:27.800 --> 0:16:30.680
<v Speaker 10>Right, because you know, if you go back to it,

0:16:31.760 --> 0:16:34.480
<v Speaker 10>the company is really focused on what we called building

0:16:34.760 --> 0:16:38.760
<v Speaker 10>the generalized marine vessel platform and the that is the

0:16:38.840 --> 0:16:40.360
<v Speaker 10>standardized core.

0:16:40.560 --> 0:16:40.800
<v Speaker 11>Right.

0:16:40.880 --> 0:16:44.440
<v Speaker 10>If you forget the if you strip it to the

0:16:44.480 --> 0:16:47.880
<v Speaker 10>physics of it. The role of a vessel is to

0:16:47.960 --> 0:16:52.400
<v Speaker 10>carry per unit payload pernit mile reliably efficiently and go

0:16:52.480 --> 0:16:54.920
<v Speaker 10>the longest distance at speed. What do you put on

0:16:55.000 --> 0:16:57.720
<v Speaker 10>top of that, Like people often get caught into this, Oh,

0:16:57.960 --> 0:16:59.480
<v Speaker 10>is it is it a luxury boat?

0:16:59.520 --> 0:17:02.520
<v Speaker 11>It looks too pretty. No, forget it, it's just your physics,

0:17:02.560 --> 0:17:03.440
<v Speaker 11>you know, it's just.

0:17:03.360 --> 0:17:06.119
<v Speaker 10>The physics of the vessel, right, And our goal is

0:17:06.200 --> 0:17:09.560
<v Speaker 10>to get as many vessels out there as possible for

0:17:09.800 --> 0:17:12.840
<v Speaker 10>us to win as a generational maritime company. What you

0:17:12.840 --> 0:17:15.720
<v Speaker 10>have seen today in asymmetric warfare, Right, we have to

0:17:15.760 --> 0:17:20.239
<v Speaker 10>move away from exotic vessel building to standardize you know,

0:17:20.520 --> 0:17:24.119
<v Speaker 10>scalabild systems, and that you can only do when you're

0:17:24.119 --> 0:17:27.480
<v Speaker 10>going to dual use and commercial use cases forces you

0:17:27.920 --> 0:17:30.040
<v Speaker 10>to like ruthlessly cut down cost.

0:17:30.520 --> 0:17:33.760
<v Speaker 11>So that's a big part of it. When you have

0:17:33.840 --> 0:17:35.000
<v Speaker 11>dual use platforms.

0:17:35.200 --> 0:17:39.160
<v Speaker 10>You streamline everything the building, maintenance, supply chain and so on.

0:17:39.520 --> 0:17:43.000
<v Speaker 4>So some realty fascinating, some reti battetaria. Thank you for

0:17:43.080 --> 0:17:46.760
<v Speaker 4>joining us and Ivia and discussing the mold. These move meanwhile,

0:17:46.760 --> 0:17:50.720
<v Speaker 4>from electric vessels to electric vehicles. Weimo set to deploy

0:17:50.920 --> 0:17:55.960
<v Speaker 4>new autonomous vehicles purpose built forever taxi use without human supervision.

0:17:56.359 --> 0:17:57.920
<v Speaker 5>Now topped the OHI.

0:17:58.440 --> 0:18:00.840
<v Speaker 4>The cars will be made available to select riders in

0:18:00.840 --> 0:18:04.240
<v Speaker 4>San Francisco, Los Angeles and Phoenix. You were one of

0:18:04.240 --> 0:18:07.560
<v Speaker 4>those select individuals. Talk us through the ride you took

0:18:07.560 --> 0:18:08.520
<v Speaker 4>and am I saying it right?

0:18:09.359 --> 0:18:12.040
<v Speaker 3>Yeah, o hi ohi as in the city in SoCal

0:18:12.160 --> 0:18:15.399
<v Speaker 3>but also like oh hi. But for Weimo, like this

0:18:15.520 --> 0:18:17.480
<v Speaker 3>is very serious, right, this is the next phase of

0:18:17.520 --> 0:18:20.480
<v Speaker 3>them scaling. So the Bloomberg Tech audience has probably seen

0:18:20.520 --> 0:18:23.959
<v Speaker 3>one of the white Weimo Jaguar Eye paces. This is

0:18:24.359 --> 0:18:27.560
<v Speaker 3>a vehicle that Weimo developed with Zeka, an arm of

0:18:27.680 --> 0:18:31.280
<v Speaker 3>China's Gli, and you know it's a completely different design,

0:18:31.400 --> 0:18:33.960
<v Speaker 3>more like a shuttle. But the point being that they

0:18:34.000 --> 0:18:37.359
<v Speaker 3>final assemble these in Mesa, Arizona, and at scale of

0:18:37.400 --> 0:18:39.520
<v Speaker 3>like you're talking tens of thousands per annum.

0:18:39.880 --> 0:18:42.600
<v Speaker 2>So in the first instance. Yeah, free rides.

0:18:42.359 --> 0:18:44.960
<v Speaker 3>Get user feedback, but if Weimo's going to break into

0:18:44.960 --> 0:18:47.280
<v Speaker 3>the mainstream, this is what they see as being their

0:18:47.320 --> 0:18:48.919
<v Speaker 3>mass volume transporter.

0:18:49.640 --> 0:18:52.720
<v Speaker 5>Fascinating and particularly the China Angler as well.

0:18:52.720 --> 0:18:55.600
<v Speaker 2>Ed particularly the China Angle.

0:18:55.680 --> 0:18:58.000
<v Speaker 3>But I think that's the story here that because it's

0:18:58.040 --> 0:19:02.240
<v Speaker 3>final assembly in Mesa and that the skateboard arrives without

0:19:02.240 --> 0:19:03.680
<v Speaker 3>any of the self driving.

0:19:03.400 --> 0:19:06.720
<v Speaker 2>Tech, they get going here, you are there.

0:19:06.760 --> 0:19:09.080
<v Speaker 3>I am a lot of fun read the Bloomberg story

0:19:09.080 --> 0:19:10.879
<v Speaker 3>will have more on the socials later now coming up,

0:19:11.040 --> 0:19:16.000
<v Speaker 3>Andthropics explosive growth has turned into a highly sought after employer.

0:19:16.320 --> 0:19:18.320
<v Speaker 2>We've got more in that next. This is boombog Tech.

0:19:26.520 --> 0:19:30.479
<v Speaker 4>Landing a job at Anthropic is so fiercely competitive that

0:19:30.600 --> 0:19:33.680
<v Speaker 4>applicants are spending get this, six hundred dollars on.

0:19:33.680 --> 0:19:35.719
<v Speaker 5>Average on private interview coaching.

0:19:36.040 --> 0:19:39.920
<v Speaker 4>Candidates say the startups intense culture screen feels that's like

0:19:39.960 --> 0:19:43.120
<v Speaker 4>an interview and more like therapy on the company faces

0:19:43.400 --> 0:19:46.719
<v Speaker 4>some incredible pressure to survive economically while keeping its values.

0:19:46.760 --> 0:19:49.840
<v Speaker 4>People like really cammoring to be part of that story. Bloomo,

0:19:49.880 --> 0:19:51.959
<v Speaker 4>Joe Constance and place to say it is with us

0:19:51.960 --> 0:19:54.600
<v Speaker 4>you do this fascinating deep dive what it's like to

0:19:54.680 --> 0:19:57.679
<v Speaker 4>go through interview rounds and anthropic What is it like?

0:19:58.440 --> 0:20:01.240
<v Speaker 12>Well, I mean, I mean, for for the first things,

0:20:01.400 --> 0:20:05.040
<v Speaker 12>it's competitive. There are so many applicants. Now, there's so

0:20:05.119 --> 0:20:07.800
<v Speaker 12>many people who are you know, just would be thrilled

0:20:07.840 --> 0:20:13.040
<v Speaker 12>to join. Even the most seasoned engineers, the most high

0:20:13.119 --> 0:20:16.280
<v Speaker 12>level executives, recruiters tell me, are willing to take the

0:20:16.320 --> 0:20:19.880
<v Speaker 12>call from the recruiter and the interview process.

0:20:19.960 --> 0:20:21.000
<v Speaker 5>While a lot of it is.

0:20:20.960 --> 0:20:24.520
<v Speaker 12>Pretty standard, the culture interview, from what I hear from

0:20:24.560 --> 0:20:29.640
<v Speaker 12>candidates and recruiters is a little unusual and more of

0:20:30.040 --> 0:20:32.800
<v Speaker 12>you know, a lot of companies, the culture fit interview

0:20:32.920 --> 0:20:34.680
<v Speaker 12>is kind of a vibe check, just to make sure

0:20:34.880 --> 0:20:35.760
<v Speaker 12>you know you're not.

0:20:38.119 --> 0:20:38.479
<v Speaker 5>Odd.

0:20:39.040 --> 0:20:41.359
<v Speaker 12>But then this interview is a little bit more.

0:20:41.880 --> 0:20:44.040
<v Speaker 4>They want you to be old in many ways, I

0:20:44.080 --> 0:20:46.480
<v Speaker 4>mean differently, you'll push back against thoughts at all.

0:20:46.400 --> 0:20:49.480
<v Speaker 12>Different They have a very defined sense of their own

0:20:49.480 --> 0:20:52.639
<v Speaker 12>culture and so they are looking for particular people to

0:20:52.680 --> 0:20:54.080
<v Speaker 12>fit that environment.

0:20:55.119 --> 0:20:57.000
<v Speaker 2>Hey, Joe, a lot of people I know work at them.

0:20:57.040 --> 0:20:59.240
<v Speaker 3>FROPIK are pretty odd and if you're watching the show today,

0:20:59.320 --> 0:21:01.800
<v Speaker 3>you know where to find me. So if you're a candidate,

0:21:01.800 --> 0:21:03.680
<v Speaker 3>because I imagine Actually a lot of the blom Beg

0:21:03.720 --> 0:21:06.400
<v Speaker 3>Tech audience are aspirational. They want to go and work

0:21:06.440 --> 0:21:09.840
<v Speaker 3>at anthropic What does forty six hundred dollars actually get you? Like,

0:21:10.080 --> 0:21:12.720
<v Speaker 3>what are you paying for? And is it working?

0:21:13.440 --> 0:21:13.800
<v Speaker 8>Sure?

0:21:14.240 --> 0:21:17.800
<v Speaker 12>You know, part of this story was interesting to discover

0:21:17.840 --> 0:21:21.720
<v Speaker 12>a little bit more about this, this cottage industry of

0:21:21.920 --> 0:21:26.160
<v Speaker 12>interview prep companies, these career coaches that are really selling

0:21:26.840 --> 0:21:30.160
<v Speaker 12>you know, their services to help people prepare for these

0:21:30.560 --> 0:21:35.040
<v Speaker 12>what feels like and you know, oftentimes very high stakes

0:21:35.080 --> 0:21:39.240
<v Speaker 12>sorts of you know, rounds and rounds of these interviews

0:21:39.240 --> 0:21:42.879
<v Speaker 12>and skills assessments, and so in some cases it's just

0:21:43.400 --> 0:21:47.520
<v Speaker 12>some resources to prep candidates on you know, what types

0:21:47.560 --> 0:21:52.280
<v Speaker 12>of questions they can expect. For other coaches they're offering

0:21:52.440 --> 0:21:53.800
<v Speaker 12>mock interviews.

0:21:53.400 --> 0:21:56.320
<v Speaker 4>And what time can you expect because it is different,

0:21:56.359 --> 0:21:59.040
<v Speaker 4>you are going to be sort of pushed more than

0:21:59.080 --> 0:22:01.960
<v Speaker 4>you might be elsewhere because they're really so based on

0:22:02.000 --> 0:22:03.440
<v Speaker 4>the mission right briefly.

0:22:03.440 --> 0:22:06.800
<v Speaker 12>Right, So, I mean that's that's the thing that I've

0:22:06.800 --> 0:22:09.720
<v Speaker 12>heard from candidates that sometimes they're not quite expecting as

0:22:09.800 --> 0:22:13.280
<v Speaker 12>much intro respection, you know, these types of questions that

0:22:13.320 --> 0:22:18.680
<v Speaker 12>are really pushing folks to reflect on, you know, past experiences,

0:22:18.760 --> 0:22:22.080
<v Speaker 12>decisions they've made, have they felt about those decisions, which

0:22:22.160 --> 0:22:24.359
<v Speaker 12>is a bit unusual for people who are used to

0:22:24.480 --> 0:22:26.800
<v Speaker 12>just talking about, you know, this project they did at

0:22:26.800 --> 0:22:29.000
<v Speaker 12>work and how it went and my great.

0:22:28.840 --> 0:22:32.199
<v Speaker 5>Is failing being how how I'm too orientated?

0:22:32.359 --> 0:22:37.560
<v Speaker 3>Yes, exactly, the most constants with pretty much the most

0:22:37.600 --> 0:22:40.239
<v Speaker 3>read story on Bloomberg today, Thanks very much. Coming up,

0:22:40.280 --> 0:22:44.560
<v Speaker 3>Meta is selling consumer subscriptions to its METAAI chatbot for

0:22:44.600 --> 0:22:47.880
<v Speaker 3>the first time. Got that story next halfway through the program.

0:22:47.960 --> 0:22:50.480
<v Speaker 3>Heck of a lot more to come. This is Bloomberg Tech.

0:23:00.200 --> 0:23:02.760
<v Speaker 4>Welcome back to Bloomberg Tech. Let us take a look

0:23:02.760 --> 0:23:06.440
<v Speaker 4>at today's big number, twenty two billion dollars and counting

0:23:06.760 --> 0:23:09.520
<v Speaker 4>is how much the market cap for Snowflake has grown

0:23:09.640 --> 0:23:12.320
<v Speaker 4>from just one day's market gain. The stock we know

0:23:12.520 --> 0:23:15.119
<v Speaker 4>is surging today. So after the software maker gain a

0:23:15.160 --> 0:23:18.040
<v Speaker 4>stronger than expected annual outlook, we in fact managed to

0:23:18.040 --> 0:23:20.800
<v Speaker 4>speak with a Snowflake CEO, should A Ramaswami on how

0:23:20.840 --> 0:23:23.560
<v Speaker 4>AI is really helping to boost their bottom line.

0:23:23.760 --> 0:23:27.440
<v Speaker 9>Well, we had a landmark quarter caroline strongest sequential dollar

0:23:27.440 --> 0:23:31.040
<v Speaker 9>growth in company's history. Product revenue op to one point

0:23:31.119 --> 0:23:34.120
<v Speaker 9>three three four billion dollars of thirty four percent net

0:23:34.160 --> 0:23:36.720
<v Speaker 9>revenue retention rate, a key metric we watch up to one

0:23:36.760 --> 0:23:39.520
<v Speaker 9>hundred and twenty six percent. But I think the bigger

0:23:39.560 --> 0:23:42.760
<v Speaker 9>news really was this is the quarter where we clearly

0:23:42.800 --> 0:23:47.520
<v Speaker 9>showed that AI is compounding snowflakes advantage in data. We

0:23:47.600 --> 0:23:50.399
<v Speaker 9>did this ole fashion way by creating amazing products like

0:23:50.440 --> 0:23:53.800
<v Speaker 9>Snowflake Intelligence, which is our work agent, which doubled it

0:23:53.880 --> 0:23:57.560
<v Speaker 9>that option with respect to our accounts, and our coding agent,

0:23:57.720 --> 0:24:01.239
<v Speaker 9>which excoed our coco which is used by more than

0:24:01.320 --> 0:24:03.520
<v Speaker 9>seven thousand our counts. And this is what gives us

0:24:03.600 --> 0:24:06.280
<v Speaker 9>confidence in the business. That's why we raise that your

0:24:06.520 --> 0:24:10.119
<v Speaker 9>items from twenty seven to thirty one percent started performance.

0:24:10.200 --> 0:24:12.240
<v Speaker 9>But I think is much more of what does this

0:24:12.359 --> 0:24:14.679
<v Speaker 9>mean for our future that you're very happy with.

0:24:16.359 --> 0:24:18.720
<v Speaker 3>Another big story in the world of tech is Meta.

0:24:18.760 --> 0:24:20.760
<v Speaker 3>This is a two day chart. Yesterday the stock up

0:24:20.800 --> 0:24:24.479
<v Speaker 3>almost four percent. We're basically flat today. Meta is selling

0:24:24.560 --> 0:24:27.880
<v Speaker 3>consumer subscriptions to its Meta AI chatbot for the first time.

0:24:27.960 --> 0:24:31.480
<v Speaker 3>Two tiers basic tier seven dollars n nine cents a

0:24:31.560 --> 0:24:33.680
<v Speaker 3>month that's cool, and then one that's like kind of

0:24:33.720 --> 0:24:37.040
<v Speaker 3>higher tier Meta one plus like I guess those of

0:24:37.080 --> 0:24:39.920
<v Speaker 3>you that are more in it, we write a Bloomberg

0:24:39.960 --> 0:24:43.640
<v Speaker 3>News that this is about offsetting the AI infrastructure costs,

0:24:43.920 --> 0:24:45.920
<v Speaker 3>but other people have slightly different take. I want to

0:24:45.920 --> 0:24:49.760
<v Speaker 3>get to sweader Conjuria Wolf Research managing director joins us. Now,

0:24:50.200 --> 0:24:53.240
<v Speaker 3>because you put research out right when the when the

0:24:53.280 --> 0:24:57.640
<v Speaker 3>news comes, and you're basically saying our thesis, which we'd

0:24:57.640 --> 0:25:01.840
<v Speaker 3>already outlined, is playing out you multiple new revenue streams.

0:25:02.720 --> 0:25:06.320
<v Speaker 3>This is a potential bigger total addressable market for you,

0:25:06.760 --> 0:25:10.080
<v Speaker 3>rather than an action to offset that high capex or

0:25:10.160 --> 0:25:11.320
<v Speaker 3>high infrastructure spending.

0:25:13.119 --> 0:25:16.560
<v Speaker 13>Yeah, that's right, and thanks for having me ed so

0:25:16.800 --> 0:25:19.000
<v Speaker 13>at a high level. One of the deeper dives that

0:25:19.040 --> 0:25:22.240
<v Speaker 13>we did prior to the news coming out was part

0:25:22.240 --> 0:25:25.280
<v Speaker 13>of the reason why Meta is even underperforming Google and

0:25:25.440 --> 0:25:29.639
<v Speaker 13>Amazon is that Meta is spending like a hyperscaler without

0:25:29.680 --> 0:25:33.399
<v Speaker 13>any clear line of sight into demand that Google and

0:25:33.480 --> 0:25:36.560
<v Speaker 13>Amazon have in their hyperscale business. And so where is

0:25:36.640 --> 0:25:40.960
<v Speaker 13>Meta spending all this money to really justify this type

0:25:40.960 --> 0:25:44.080
<v Speaker 13>of spend and cap x and when will we see

0:25:44.080 --> 0:25:46.520
<v Speaker 13>that revenue? So that's the fundamental question, and so in

0:25:46.560 --> 0:25:48.879
<v Speaker 13>that when we dug deeper, it could be subscription or

0:25:48.920 --> 0:25:51.239
<v Speaker 13>it could be a gentic commerce or it could be

0:25:52.520 --> 0:25:55.040
<v Speaker 13>business AI. And now we're starting to see with this

0:25:55.119 --> 0:25:58.720
<v Speaker 13>product release of subscription across consumer businesses and Meta AI

0:25:59.160 --> 0:26:00.600
<v Speaker 13>that this could be the beginning of.

0:26:00.600 --> 0:26:02.879
<v Speaker 5>It about how this is going to scale.

0:26:02.920 --> 0:26:05.240
<v Speaker 4>First quarter, it was about one point three billion dollars

0:26:05.240 --> 0:26:07.000
<v Speaker 4>that was in the non advertising revenue.

0:26:07.040 --> 0:26:09.639
<v Speaker 5>So tiny, how much could that rise?

0:26:10.880 --> 0:26:14.439
<v Speaker 13>Yeah, so in the non advertising revenue right now, a

0:26:14.480 --> 0:26:16.920
<v Speaker 13>lot of it could be business AI that they are

0:26:16.960 --> 0:26:22.159
<v Speaker 13>actually monetizing in WhatsApp through their businesses in WhatsApp. Now

0:26:22.280 --> 0:26:26.200
<v Speaker 13>an add on is going to be subscription. So a

0:26:26.359 --> 0:26:29.960
<v Speaker 13>clearest comp that we have today is Snapchat, and Snapchat

0:26:30.040 --> 0:26:34.760
<v Speaker 13>arguably has surprisingly done a great job in converting its

0:26:35.160 --> 0:26:38.240
<v Speaker 13>da user, daily active users, and monthly active users to

0:26:38.320 --> 0:26:41.760
<v Speaker 13>subscriber base. If Meta can do something similar to that,

0:26:41.800 --> 0:26:43.960
<v Speaker 13>and I'm not saying it's going to be exactly the same,

0:26:44.280 --> 0:26:47.600
<v Speaker 13>but say low to mid single legit percentage of their

0:26:47.680 --> 0:26:52.560
<v Speaker 13>daus actually convert to subscription, well, that in itself implies

0:26:52.680 --> 0:26:56.000
<v Speaker 13>about a one to three percent percentage point uplift to

0:26:56.040 --> 0:26:59.719
<v Speaker 13>their revenue. In other words, approximately anywhere from five to

0:26:59.720 --> 0:27:04.480
<v Speaker 13>fIF teen billion dollars of incremental subscription revenue from consumers

0:27:04.480 --> 0:27:06.080
<v Speaker 13>in the next three to five years.

0:27:06.600 --> 0:27:07.520
<v Speaker 2>Look at it differently.

0:27:07.680 --> 0:27:12.520
<v Speaker 3>In a world where you're paying monthly for Chat, GPT, Clawed, Gemini, etc.

0:27:13.520 --> 0:27:16.520
<v Speaker 3>Is Meta AI worth paying eight dollars or twenty dollars

0:27:16.560 --> 0:27:17.360
<v Speaker 3>a month four.

0:27:18.920 --> 0:27:21.640
<v Speaker 13>That is going to be a key question for them.

0:27:21.680 --> 0:27:24.560
<v Speaker 13>So there is a consumer subscription piece, there is this

0:27:25.000 --> 0:27:29.560
<v Speaker 13>Meta AI type subscription piece which competes directly with Gemini

0:27:29.560 --> 0:27:31.879
<v Speaker 13>to your point, and then there is a business like

0:27:31.960 --> 0:27:35.160
<v Speaker 13>if you are a creator, then you can subscribe as well.

0:27:35.280 --> 0:27:39.119
<v Speaker 13>I see great value in the consumer subscription and the

0:27:39.160 --> 0:27:41.840
<v Speaker 13>creator subscription because it allows them to create more content.

0:27:42.160 --> 0:27:44.360
<v Speaker 13>But in the question that you are asking, where if

0:27:44.400 --> 0:27:47.119
<v Speaker 13>I have a Gemini subscription or a GPT, do I

0:27:47.160 --> 0:27:49.840
<v Speaker 13>need Meta AI, jury is still out on that you

0:27:49.840 --> 0:27:52.040
<v Speaker 13>would need it. If you're running out of capacity and

0:27:52.080 --> 0:27:54.320
<v Speaker 13>you're paying twenty bucks, you don't want to pay additional

0:27:54.400 --> 0:27:57.280
<v Speaker 13>higher tier to a one hundred or two hundred dollars tier,

0:27:57.320 --> 0:27:59.879
<v Speaker 13>and you want just a little bit more of access capacity,

0:28:00.040 --> 0:28:03.000
<v Speaker 13>maybe you bade bucks do Meta Maybe in that scenario

0:28:03.119 --> 0:28:06.960
<v Speaker 13>does make sense. Or if it is highly personalized social

0:28:07.080 --> 0:28:10.800
<v Speaker 13>sort of a use case that they give us which

0:28:10.840 --> 0:28:14.760
<v Speaker 13>cannot be created by Claude because they don't have that information,

0:28:15.400 --> 0:28:18.200
<v Speaker 13>or perhaps the GPD perhaps there is a use case

0:28:18.480 --> 0:28:22.160
<v Speaker 13>in those instances. Yes, but I'm not fully sure. Jury

0:28:22.160 --> 0:28:25.880
<v Speaker 13>is still out on that. On the meta AA subscription scaling.

0:28:25.760 --> 0:28:29.080
<v Speaker 4>Schredo Cajuria, great research, great analysis from Wolf Research.

0:28:29.160 --> 0:28:30.560
<v Speaker 5>We thank you, Mick.

0:28:30.680 --> 0:28:33.920
<v Speaker 4>NASA it selected Blue Origin, far Fly Aerospace and other

0:28:33.960 --> 0:28:36.200
<v Speaker 4>private space firms to help build out its long term

0:28:36.280 --> 0:28:40.120
<v Speaker 4>lunar ambitions. The agency says monthly missions could begin in

0:28:40.120 --> 0:28:43.160
<v Speaker 4>twenty twenty seven, laying the groundwork for astronauts striveging live

0:28:43.400 --> 0:28:46.200
<v Speaker 4>work on the lunar surface. We spoke with the NASA Administrator,

0:28:46.280 --> 0:28:48.840
<v Speaker 4>Jaredisingman about the timeline for a moon.

0:28:48.720 --> 0:28:52.480
<v Speaker 14>Base starting in twenty twenty seven. You should see see

0:28:52.480 --> 0:28:56.760
<v Speaker 14>a near monthly cadence of robotic landers on the Moon,

0:28:57.200 --> 0:28:59.920
<v Speaker 14>several rovers. In fact, we initially we provided in a

0:29:00.080 --> 0:29:04.640
<v Speaker 14>ward for the first two, you know, crude and autonomous

0:29:05.040 --> 0:29:07.920
<v Speaker 14>capable rovers for the lunar surface. So when our astronauts

0:29:08.000 --> 0:29:10.880
<v Speaker 14>arrive on Artemis four and twenty twenty eight, they're going

0:29:10.920 --> 0:29:13.200
<v Speaker 14>to already have some infrastructure of the moon base waiting

0:29:13.200 --> 0:29:13.479
<v Speaker 14>for them.

0:29:13.520 --> 0:29:15.840
<v Speaker 7>They're already going to have a rover waiting for them.

0:29:16.240 --> 0:29:20.560
<v Speaker 4>And then in that timeframe, it's not just intermittent anymore.

0:29:20.600 --> 0:29:23.080
<v Speaker 4>It's not just those monthly visits. But when do you

0:29:23.120 --> 0:29:26.600
<v Speaker 4>think people be working? Humans might even be living in

0:29:26.640 --> 0:29:28.040
<v Speaker 4>some capacity on the moon.

0:29:27.880 --> 0:29:32.520
<v Speaker 14>There, So we are approaching the moon base in phases.

0:29:32.720 --> 0:29:35.160
<v Speaker 14>So Phase one is a lot of littles. We are

0:29:35.200 --> 0:29:37.720
<v Speaker 14>dusting off the playbook that worked very well for NASA

0:29:37.720 --> 0:29:40.640
<v Speaker 14>in the nineteen sixties. We're getting back to an iterative approach.

0:29:40.680 --> 0:29:43.640
<v Speaker 14>So you know, there was the Mercury program before there

0:29:43.680 --> 0:29:46.560
<v Speaker 14>was Geminy, There was Geminy before Apollo, and an awful

0:29:46.600 --> 0:29:49.240
<v Speaker 14>lot of Apollo missions before we went right to the

0:29:49.280 --> 0:29:51.360
<v Speaker 14>moon landing on Apollo eleven. We are doing the same

0:29:51.400 --> 0:29:54.200
<v Speaker 14>thing now. So Phase one we're calling it a science

0:29:54.240 --> 0:29:57.280
<v Speaker 14>of survival. We're not going to lock in what the

0:29:57.600 --> 0:30:02.560
<v Speaker 14>mobility strategy should be, for logistics for astronauts, the power strategy,

0:30:02.640 --> 0:30:05.800
<v Speaker 14>the surface comms, the orbital coms. Why would we try

0:30:05.840 --> 0:30:08.280
<v Speaker 14>and nail and get all of that perfect today when

0:30:08.280 --> 0:30:09.640
<v Speaker 14>we haven't been to the Moon in more than a

0:30:09.640 --> 0:30:12.120
<v Speaker 14>half century. So Phase one will be a lot of

0:30:12.200 --> 0:30:15.960
<v Speaker 14>landings again, that near monthly cadence to learn and inform

0:30:16.080 --> 0:30:18.840
<v Speaker 14>Phase two, where perhaps now you're putting a lot more

0:30:18.880 --> 0:30:21.480
<v Speaker 14>tonnage on the lunar surface. You have a lot more

0:30:21.960 --> 0:30:25.160
<v Speaker 14>direction as to the type of hardware and capabilities you

0:30:25.240 --> 0:30:27.080
<v Speaker 14>want to lock in on, so you don't need to

0:30:27.120 --> 0:30:29.640
<v Speaker 14>have maybe monthly landings when we get into phase two,

0:30:29.920 --> 0:30:32.280
<v Speaker 14>but you have a lot more direction as to what

0:30:32.320 --> 0:30:34.760
<v Speaker 14>should work for our intended objectives, which is to build

0:30:34.800 --> 0:30:37.800
<v Speaker 14>out that habital environment. And then phase two we're going

0:30:37.880 --> 0:30:40.880
<v Speaker 14>to learn now having astronauts go from let's call it

0:30:41.440 --> 0:30:44.400
<v Speaker 14>a period of maybe even days on the lunar surface

0:30:44.440 --> 0:30:47.720
<v Speaker 14>in phase one, to potentially weeks in phase two, to

0:30:47.760 --> 0:30:49.680
<v Speaker 14>where you might get by the time we move into

0:30:49.680 --> 0:30:53.240
<v Speaker 14>Phase three, a similar astronaut rotation like you see on

0:30:53.280 --> 0:30:56.280
<v Speaker 14>the International Space Station, where we could have crews potentially

0:30:56.320 --> 0:30:58.840
<v Speaker 14>being on the lunar surface for months on end.

0:31:00.000 --> 0:31:03.640
<v Speaker 3>You don't have that marked on your calendar, administrator, when

0:31:03.680 --> 0:31:06.680
<v Speaker 3>phase three might have a base that has humans actually

0:31:06.760 --> 0:31:07.920
<v Speaker 3>living and working inside it.

0:31:09.040 --> 0:31:10.800
<v Speaker 7>Oh, we absolutely have time frames.

0:31:10.840 --> 0:31:13.240
<v Speaker 14>I mean we are looking at basically twenty twenty seven

0:31:13.320 --> 0:31:16.320
<v Speaker 14>through twenty twenty nine for phase one. You have twenty

0:31:16.360 --> 0:31:19.520
<v Speaker 14>twenty nine out into the early twenty thirties for Phase two.

0:31:19.760 --> 0:31:22.400
<v Speaker 14>But again, this is all going to be informed on

0:31:22.480 --> 0:31:25.480
<v Speaker 14>what we learn during those first landings in phase one.

0:31:27.200 --> 0:31:29.280
<v Speaker 2>That was NATA administrator Jared Isicman.

0:31:29.360 --> 0:31:30.880
<v Speaker 3>All right, coming up on the show, we're going to

0:31:30.880 --> 0:31:35.000
<v Speaker 3>be joined by Eric Vistria Benchmark for his outlook the

0:31:35.040 --> 0:31:38.600
<v Speaker 3>physical AI space. Yes, we're going to talk about hardware.

0:31:38.800 --> 0:31:48.680
<v Speaker 3>This has Belen bog Tech, French AI startup Mistro AI

0:31:48.800 --> 0:31:52.880
<v Speaker 3>is expanding into advanced manufacturing, striking deals with new customers

0:31:52.920 --> 0:31:56.320
<v Speaker 3>Airbus and BMW as it looks to so called physical

0:31:56.360 --> 0:31:59.360
<v Speaker 3>AI to fuel growth. CEO and co founder of the men,

0:31:59.400 --> 0:32:02.400
<v Speaker 3>she spoke with blue Ink Tech Europe's Tom McKenzie.

0:32:03.960 --> 0:32:05.280
<v Speaker 2>For US, it's a massive market.

0:32:05.880 --> 0:32:09.040
<v Speaker 15>We see in particular the europe is our in core

0:32:09.120 --> 0:32:14.000
<v Speaker 15>market and one of the Europeans the strength of Europe

0:32:14.080 --> 0:32:18.280
<v Speaker 15>is to is in its high end manufacturing. So it's

0:32:19.480 --> 0:32:23.000
<v Speaker 15>the manufacturing world. Is the thirty trillion market. If you

0:32:23.040 --> 0:32:26.400
<v Speaker 15>think of a police that I can bring to it,

0:32:26.560 --> 0:32:28.400
<v Speaker 15>if you only look at ten percent of that, you're

0:32:28.440 --> 0:32:30.920
<v Speaker 15>looking at the three trillion market. And that's happening in

0:32:30.920 --> 0:32:31.960
<v Speaker 15>the next five years.

0:32:32.720 --> 0:32:35.680
<v Speaker 4>Man Over in Asia, Mini Max is annualized revenue more

0:32:35.680 --> 0:32:38.240
<v Speaker 4>than double these past two months to at least three

0:32:38.280 --> 0:32:41.040
<v Speaker 4>hundred million dollars. As the Chinese AI startup prepares to

0:32:41.120 --> 0:32:43.920
<v Speaker 4>roll out its next flagship model, Mean Max co founder

0:32:43.920 --> 0:32:47.160
<v Speaker 4>and President's Yaean joined Blomberg Steven Engel on the sidelines

0:32:47.160 --> 0:32:49.280
<v Speaker 4>of thebs Asian Investment Conference over in Hong Kong.

0:32:50.920 --> 0:32:54.680
<v Speaker 16>Agent and the models are really important for manimalization, but

0:32:54.880 --> 0:32:58.000
<v Speaker 16>definitely the foundation model is a key. You will see

0:32:58.080 --> 0:33:03.480
<v Speaker 16>a better performance. Models with specialization and differentiation will drive

0:33:03.680 --> 0:33:07.920
<v Speaker 16>the token consumption, also drives the enterprise and the consumers

0:33:08.080 --> 0:33:12.680
<v Speaker 16>retention and the consumption. The model performers product commantization will

0:33:12.720 --> 0:33:16.400
<v Speaker 16>become the frive wear. So you will see we did

0:33:16.480 --> 0:33:19.200
<v Speaker 16>the end to end optimization with the whole group. There

0:33:19.240 --> 0:33:22.720
<v Speaker 16>are lots of innovation, technical innovation inside, so you will

0:33:22.760 --> 0:33:26.480
<v Speaker 16>see we can provide probably similar performers models with probably

0:33:26.560 --> 0:33:29.280
<v Speaker 16>lower price even sometimes higher margins.

0:33:29.600 --> 0:33:32.320
<v Speaker 17>Yeah, so how do you change your revenue mix where

0:33:32.720 --> 0:33:35.959
<v Speaker 17>most of your revenue is coming from your consumer facing

0:33:36.080 --> 0:33:40.680
<v Speaker 17>products like the chatboxing and also high level which just

0:33:40.800 --> 0:33:44.240
<v Speaker 17>last year's that's like the text to video generation. But

0:33:44.920 --> 0:33:47.800
<v Speaker 17>next year, as you go into your model three, right

0:33:47.880 --> 0:33:51.400
<v Speaker 17>from two point seven to three, how is your revenue

0:33:51.640 --> 0:33:52.560
<v Speaker 17>mixed going to change?

0:33:52.760 --> 0:33:52.920
<v Speaker 2>Yeah?

0:33:53.160 --> 0:33:55.640
<v Speaker 16>So the number you mentioned is last year's number, but

0:33:55.840 --> 0:33:59.200
<v Speaker 16>right now it's almost like fifty enterprise and fifty consumers,

0:33:59.240 --> 0:34:03.600
<v Speaker 16>so the enterprise increase a lot. And also, yes, the

0:34:03.720 --> 0:34:06.160
<v Speaker 16>model is a key, so we think the model is

0:34:06.240 --> 0:34:08.600
<v Speaker 16>our product, no matter it's a B to B R

0:34:08.920 --> 0:34:12.600
<v Speaker 16>digital C. It's all the Chinnel's for the commercialization. So

0:34:12.760 --> 0:34:16.040
<v Speaker 16>we've spent most of our resources and the spendings of

0:34:16.200 --> 0:34:18.960
<v Speaker 16>the model layer. Yes, we are going to release I'm

0:34:19.040 --> 0:34:22.040
<v Speaker 16>three very very soon in a few days, which probably

0:34:22.280 --> 0:34:26.240
<v Speaker 16>I think, which is the first open source native multi model.

0:34:27.440 --> 0:34:29.319
<v Speaker 3>That was Min and Max co founder and president Yea

0:34:29.480 --> 0:34:32.359
<v Speaker 3>Ian along with our own Stephen Engel. We're gonna stick

0:34:32.400 --> 0:34:34.880
<v Speaker 3>with AI and we're going to discuss the outlook for

0:34:35.000 --> 0:34:39.000
<v Speaker 3>physical AI with Eric Visher, a partner at Benchmark Today's

0:34:39.080 --> 0:34:39.840
<v Speaker 3>VC Spotlight.

0:34:40.320 --> 0:34:41.560
<v Speaker 2>Been really looking forward to this one.

0:34:41.760 --> 0:34:41.920
<v Speaker 14>Eric.

0:34:42.719 --> 0:34:45.960
<v Speaker 3>Ten years ago, you're very welcome to be here. Ten

0:34:46.080 --> 0:34:48.759
<v Speaker 3>years ago you led a series A in a little

0:34:48.840 --> 0:34:54.560
<v Speaker 3>company called Cerebras. Fast forward ten years what an IPO,

0:34:55.480 --> 0:34:58.360
<v Speaker 3>but it's indicative of where we're at right now in

0:34:58.440 --> 0:34:59.920
<v Speaker 3>this demand for fast inference.

0:35:01.480 --> 0:35:03.280
<v Speaker 2>I just want to start with that case study.

0:35:03.680 --> 0:35:06.239
<v Speaker 3>You know, the timing of this IPO and where it

0:35:06.320 --> 0:35:09.480
<v Speaker 3>fits in what's actually happening in physical AI right now.

0:35:10.920 --> 0:35:13.800
<v Speaker 18>Well, I think that it's very very clear that the

0:35:15.000 --> 0:35:20.040
<v Speaker 18>demand for inference and AI is operal charts, and I

0:35:20.080 --> 0:35:22.680
<v Speaker 18>don't think that's going to stop anytime soon. I think

0:35:22.719 --> 0:35:26.120
<v Speaker 18>it was Alex Scattered at at Whale Rock who kind

0:35:26.120 --> 0:35:29.239
<v Speaker 18>of recently said, if you think of the population of

0:35:29.280 --> 0:35:32.120
<v Speaker 18>the world, there's like one percent of the world.

0:35:32.280 --> 0:35:34.680
<v Speaker 2>Is maybe AI power users today.

0:35:35.160 --> 0:35:37.359
<v Speaker 18>So if one percent of the world is AI power

0:35:37.480 --> 0:35:42.160
<v Speaker 18>users today and we're completely compute constrained, for as far

0:35:42.239 --> 0:35:45.120
<v Speaker 18>as I can see, what happens when three percent of

0:35:45.160 --> 0:35:46.719
<v Speaker 18>the world, or four percent of the world, or five

0:35:46.719 --> 0:35:51.440
<v Speaker 18>percent of the world becomes AI super users or power users.

0:35:51.800 --> 0:35:54.160
<v Speaker 18>And so I think that we are going to be

0:35:54.520 --> 0:35:58.560
<v Speaker 18>in this compute constrained world for quite some time. And

0:35:59.800 --> 0:36:02.359
<v Speaker 18>I think that that's going to lead to a lot

0:36:02.400 --> 0:36:05.319
<v Speaker 18>of success in all of the hardware layers. And it's

0:36:05.360 --> 0:36:08.239
<v Speaker 18>also going to lead to the bottleneck moving around. You know,

0:36:08.640 --> 0:36:11.040
<v Speaker 18>some days, some months it's going to be memory, some

0:36:11.719 --> 0:36:13.480
<v Speaker 18>months it's going to be data center and power. Some

0:36:13.560 --> 0:36:16.360
<v Speaker 18>once it's going to be chips. And I think that

0:36:16.480 --> 0:36:17.680
<v Speaker 18>bottleneck is going to keep.

0:36:17.520 --> 0:36:20.399
<v Speaker 4>Moving around some days it's all of them combined, Derek,

0:36:20.520 --> 0:36:24.040
<v Speaker 4>So totally at this exact moment, where are the startups

0:36:24.120 --> 0:36:26.239
<v Speaker 4>you're most interested in, or the ones you already sit

0:36:26.280 --> 0:36:28.400
<v Speaker 4>on boards of starting.

0:36:28.080 --> 0:36:29.080
<v Speaker 5>To innovate at the edges?

0:36:29.120 --> 0:36:31.080
<v Speaker 4>When are we going to really see like movement of

0:36:31.120 --> 0:36:33.919
<v Speaker 4>photonics or a different type of compute being used.

0:36:34.840 --> 0:36:36.279
<v Speaker 11>Well, I think, I think you know.

0:36:36.400 --> 0:36:38.840
<v Speaker 18>One of the benefits of being an early stage ventry

0:36:38.880 --> 0:36:41.520
<v Speaker 18>capitalists is we have a very long time horizon, so

0:36:41.680 --> 0:36:44.439
<v Speaker 18>we're not trying to figure out what's going to happen

0:36:44.640 --> 0:36:47.200
<v Speaker 18>in eighteen months or twelve months or twenty four months.

0:36:47.520 --> 0:36:51.239
<v Speaker 18>We're really looking and trying to have some idea of

0:36:51.360 --> 0:36:54.520
<v Speaker 18>what might happen in five years or seven years or

0:36:54.600 --> 0:36:58.040
<v Speaker 18>ten years. And as we look out, we are really excited.

0:36:58.280 --> 0:37:01.840
<v Speaker 18>For example, we invested in star Cloud, which is a

0:37:01.920 --> 0:37:05.680
<v Speaker 18>space data center. We invested in Sunday Robotics, which is

0:37:05.760 --> 0:37:08.880
<v Speaker 18>a domestic robot And when you kind of work at

0:37:08.920 --> 0:37:12.200
<v Speaker 18>companies like that, they're very much on the frontier. It's

0:37:12.280 --> 0:37:14.880
<v Speaker 18>going to take a bunch of time. There are very

0:37:14.960 --> 0:37:19.759
<v Speaker 18>capital intensive projects, but they're amazing teams that are doing

0:37:20.320 --> 0:37:24.800
<v Speaker 18>really cool development, pushing the edge, and it's going to

0:37:24.840 --> 0:37:27.960
<v Speaker 18>require a lot of flexibility on their parts as the

0:37:28.040 --> 0:37:31.439
<v Speaker 18>market evolves. There's obviously a lot of unknowns, but there's

0:37:31.520 --> 0:37:33.879
<v Speaker 18>also tremendous possibilities.

0:37:35.560 --> 0:37:37.359
<v Speaker 3>I just want to go back to Cerebris for a minute,

0:37:37.480 --> 0:37:40.280
<v Speaker 3>and to some this is now ancient history is academic.

0:37:40.440 --> 0:37:44.120
<v Speaker 3>But two days before the IPO I broke a story

0:37:44.400 --> 0:37:47.600
<v Speaker 3>that arm and soft Bank had basically gone to Andrew

0:37:47.640 --> 0:37:52.040
<v Speaker 3>Feldman and said we'd buy you for a large number.

0:37:52.400 --> 0:37:55.000
<v Speaker 3>And Andrew very quickly shut it down, and the rest

0:37:55.120 --> 0:37:57.279
<v Speaker 3>is history, of course, because they went public. But it's

0:37:57.320 --> 0:37:59.680
<v Speaker 3>somebody that joined the board in twenty sixteen and has

0:37:59.680 --> 0:38:02.280
<v Speaker 3>had three if the five major investments go to IPO.

0:38:03.600 --> 0:38:06.279
<v Speaker 3>What would you have made of that outcome instead of

0:38:06.320 --> 0:38:06.920
<v Speaker 3>going public.

0:38:07.800 --> 0:38:11.880
<v Speaker 18>Well, obviously you can't comment on that specific reporting, but

0:38:12.600 --> 0:38:14.040
<v Speaker 18>we're a public company now.

0:38:14.320 --> 0:38:15.640
<v Speaker 11>I think that has opened up.

0:38:15.560 --> 0:38:17.800
<v Speaker 18>A lot of possibilities in terms of what we can do.

0:38:18.360 --> 0:38:20.800
<v Speaker 18>We've raised a ton of capital to finance the business

0:38:21.440 --> 0:38:25.080
<v Speaker 18>and allow us to take advantage of the tremendous demand.

0:38:25.360 --> 0:38:27.840
<v Speaker 18>And I think we're really at the beginning. You know,

0:38:27.920 --> 0:38:32.080
<v Speaker 18>if you feel like there is an end in sight,

0:38:32.239 --> 0:38:36.359
<v Speaker 18>you might take a different, different tact. But as far

0:38:36.400 --> 0:38:39.880
<v Speaker 18>as we can see the demand is tremendous.

0:38:40.360 --> 0:38:41.960
<v Speaker 4>You say, you're just backed a company and it's about

0:38:42.000 --> 0:38:44.200
<v Speaker 4>orbital space centers, and that immediately makes us all think

0:38:44.239 --> 0:38:46.640
<v Speaker 4>of SpaceX and how they're going to be sucking a

0:38:46.719 --> 0:38:48.320
<v Speaker 4>lot of the oxygen out of the room when it

0:38:48.360 --> 0:38:51.640
<v Speaker 4>comes to a public offering. How are your companies currently

0:38:51.719 --> 0:38:53.839
<v Speaker 4>feeling the need for cash? How are you thinking about

0:38:53.920 --> 0:38:56.960
<v Speaker 4>permanently fundraising or looking for exits right now?

0:38:57.960 --> 0:38:59.280
<v Speaker 11>Well, you know, it's really interesting.

0:38:59.440 --> 0:39:02.640
<v Speaker 18>Right now, the venture landscape is very much have and

0:39:02.760 --> 0:39:06.080
<v Speaker 18>have not, which is, if you are oriented around AI

0:39:06.400 --> 0:39:09.279
<v Speaker 18>and you're growing really quickly or have something that's very

0:39:09.360 --> 0:39:13.920
<v Speaker 18>much on the frontier, there's almost there's almost like limitless

0:39:14.880 --> 0:39:18.000
<v Speaker 18>cash available and funding available. And if you're not, even

0:39:18.040 --> 0:39:20.319
<v Speaker 18>if it's a good business that would have people would

0:39:20.320 --> 0:39:23.359
<v Speaker 18>have fallen on all over themselves. For you know, five

0:39:23.480 --> 0:39:26.480
<v Speaker 18>or six years ago, there's almost no funding available. So

0:39:26.719 --> 0:39:30.319
<v Speaker 18>it's a very it's a very bimodal setup right now,

0:39:30.440 --> 0:39:33.719
<v Speaker 18>which is which is challenging certainly, But each of these

0:39:34.239 --> 0:39:37.800
<v Speaker 18>financing eras kind of they come and go, and you know,

0:39:37.920 --> 0:39:39.400
<v Speaker 18>one of the really important things for any of these

0:39:39.440 --> 0:39:42.759
<v Speaker 18>companies or entrepreneurs is just to keep on, keep on

0:39:42.880 --> 0:39:46.800
<v Speaker 18>grinding and finding the way that there's building a company

0:39:47.440 --> 0:39:51.200
<v Speaker 18>that is impactful as a roller coaster. And it takes

0:39:51.239 --> 0:39:54.120
<v Speaker 18>a long time, and even if you take the Cerever's journey,

0:39:54.400 --> 0:39:56.359
<v Speaker 18>there's been lots and lots of ups and downs over

0:39:56.440 --> 0:40:01.120
<v Speaker 18>the time. Obviously, taking an AI sending conductor company public

0:40:01.239 --> 0:40:04.000
<v Speaker 18>in maybe twenty twenty six is about as good timing

0:40:04.040 --> 0:40:07.640
<v Speaker 18>as you can get. But you know, part of that

0:40:08.000 --> 0:40:12.719
<v Speaker 18>is the timing. Part of that's just luck. And then

0:40:13.000 --> 0:40:16.560
<v Speaker 18>obviously it's all built on top of a decade of

0:40:16.920 --> 0:40:18.160
<v Speaker 18>the team grinding.

0:40:17.800 --> 0:40:20.960
<v Speaker 4>At okasor another interesting one that we're looking at in

0:40:21.000 --> 0:40:23.319
<v Speaker 4>your portfolio. We have to talk about that another time. Eric,

0:40:23.360 --> 0:40:27.120
<v Speaker 4>it's great to have you on. Eric Vishrha of Benchmark.

0:40:27.560 --> 0:40:30.680
<v Speaker 4>Now coming up TikTok, but it's moving away from music,

0:40:30.960 --> 0:40:33.000
<v Speaker 4>scaling back tis with major music labels.

0:40:33.000 --> 0:40:34.799
<v Speaker 5>We'll dig into that next. This is Bloomberg Tech.

0:40:41.440 --> 0:40:45.320
<v Speaker 3>AI could provoke a fifteen percent displacement of knowledge workers.

0:40:45.360 --> 0:40:48.799
<v Speaker 3>That's according to Muddy Waters Capital CEO Carson Block, who

0:40:48.880 --> 0:40:52.279
<v Speaker 3>joined Bloomberg's has Linda Amen in an exclusive interview to

0:40:52.360 --> 0:40:53.800
<v Speaker 3>discuss AI demand listen to this.

0:40:55.880 --> 0:40:59.440
<v Speaker 19>Our house view is that we're going to see fifteen

0:40:59.719 --> 0:41:03.880
<v Speaker 19>percent displacement of knowledge workers. You know, we think it

0:41:03.960 --> 0:41:07.279
<v Speaker 19>could be as soon as three years, is it four?

0:41:07.520 --> 0:41:08.040
<v Speaker 2>Is it five?

0:41:08.760 --> 0:41:12.160
<v Speaker 19>At some point and it's in the single digit number

0:41:12.200 --> 0:41:15.719
<v Speaker 19>of years. This will this will be a factor or

0:41:15.800 --> 0:41:18.640
<v Speaker 19>this this will occur in our view, and yes, there

0:41:18.680 --> 0:41:21.680
<v Speaker 19>will be jobs that are created by AI, but we're

0:41:21.760 --> 0:41:26.680
<v Speaker 19>talking about net losses because the technology is increasing in

0:41:26.800 --> 0:41:30.960
<v Speaker 19>capability faster than we humans are able to adapt to it.

0:41:31.520 --> 0:41:33.760
<v Speaker 5>Let's talk about the displacement of music labels.

0:41:34.200 --> 0:41:36.600
<v Speaker 4>Maybe over at TikTok, because music has been called to

0:41:36.680 --> 0:41:40.640
<v Speaker 4>TikTok's identity since its days. Is musically helping artists like

0:41:40.719 --> 0:41:44.480
<v Speaker 4>Little nas X or Olivia Rodrigu just global stardom and

0:41:44.560 --> 0:41:47.160
<v Speaker 4>waits Now TikTok there is skinning back ties with major

0:41:47.200 --> 0:41:49.720
<v Speaker 4>music labels and focusing more directly on those artists.

0:41:49.920 --> 0:41:51.640
<v Speaker 5>It's according to sources, that's.

0:41:51.480 --> 0:41:55.080
<v Speaker 4>All discovered by Blue Megs Alex Levine along with Ashley Carmen.

0:41:55.960 --> 0:41:59.479
<v Speaker 5>What is happening with a company that identify with music?

0:41:59.520 --> 0:42:02.040
<v Speaker 4>I mean it's it's in the icon, it's in the branding.

0:42:02.239 --> 0:42:03.760
<v Speaker 4>How are they moving away from labels?

0:42:04.200 --> 0:42:04.880
<v Speaker 11>So exactly?

0:42:05.239 --> 0:42:07.600
<v Speaker 20>Music has really been part of its DNA since the

0:42:07.719 --> 0:42:10.160
<v Speaker 20>very beginning. It is the thing that made helped make

0:42:10.200 --> 0:42:13.040
<v Speaker 20>TikTok this global cultural phenomenon and got more than half

0:42:13.040 --> 0:42:17.680
<v Speaker 20>of America using it. Though TikTok continues importantly to work

0:42:17.719 --> 0:42:20.400
<v Speaker 20>with major music labels, including some of the world's biggest,

0:42:21.520 --> 0:42:26.160
<v Speaker 20>it is deprioritizing those relationships in part by building out projects,

0:42:26.200 --> 0:42:30.360
<v Speaker 20>prioritizing internal efforts to actually have products and services that

0:42:30.440 --> 0:42:34.360
<v Speaker 20>compete directly with the labels and that allow the company

0:42:34.480 --> 0:42:37.640
<v Speaker 20>to have sort of more direct relations with the artists

0:42:37.760 --> 0:42:39.200
<v Speaker 20>rather than through the representatives.

0:42:40.160 --> 0:42:43.880
<v Speaker 3>Alex, TikTok changed music. Now labels worry it's leaving them behind.

0:42:44.040 --> 0:42:47.000
<v Speaker 3>But present day, how does music work on TikTok. So

0:42:47.040 --> 0:42:49.960
<v Speaker 3>it's Friday night, I'm kicking back on the couch. I

0:42:50.080 --> 0:42:53.680
<v Speaker 3>go to YouTube on the TV and play concerts, music videos.

0:42:54.000 --> 0:42:57.239
<v Speaker 3>I don't think present day like, you know what yep,

0:42:57.400 --> 0:43:00.800
<v Speaker 3>music music video like, just explain what we're talking about mechanically.

0:43:01.280 --> 0:43:03.440
<v Speaker 20>So mechanically, when you open your app, you've got your

0:43:03.480 --> 0:43:06.839
<v Speaker 20>four you feed. Every video that you see is going

0:43:06.880 --> 0:43:09.279
<v Speaker 20>to have some sort of audio behind it, whether that's

0:43:09.320 --> 0:43:13.440
<v Speaker 20>people speaking or whether that's music, and oftentimes those sounds

0:43:13.600 --> 0:43:18.200
<v Speaker 20>are our songs that have gone viral, and sometimes it's

0:43:18.239 --> 0:43:21.719
<v Speaker 20>new songs from emerging artists. Sometimes it's made you know,

0:43:22.040 --> 0:43:24.719
<v Speaker 20>it's it's global hits from artists like Paul McCartney, like

0:43:24.760 --> 0:43:28.160
<v Speaker 20>Bruno Mars, and sometimes it's simply just you know, sort

0:43:28.200 --> 0:43:31.759
<v Speaker 20>of repetitive meme type noises that you can find through

0:43:32.040 --> 0:43:34.839
<v Speaker 20>through various other means on the app. But I think

0:43:34.880 --> 0:43:37.480
<v Speaker 20>that there's always sort of been this question, especially more recently,

0:43:37.600 --> 0:43:40.799
<v Speaker 20>about whether blowing up on TikTok or going viral can

0:43:40.840 --> 0:43:44.520
<v Speaker 20>actually mint a legitimate star and and have have them

0:43:44.600 --> 0:43:46.279
<v Speaker 20>develop really an enduring career from that.

0:43:47.320 --> 0:43:50.240
<v Speaker 3>Bloomberg's Alex Savine with what's going on in music on TikTok,

0:43:50.320 --> 0:43:51.200
<v Speaker 3>Thank you very much.

0:43:51.400 --> 0:43:54.120
<v Speaker 5>Character that does it for this edition of Bloomberg Tech.

0:43:54.200 --> 0:43:55.200
<v Speaker 5>What an edition has been?

0:43:56.480 --> 0:43:58.560
<v Speaker 3>Yeah, a lot of market moves, a lot of great interviews,

0:43:58.600 --> 0:44:00.720
<v Speaker 3>a lot of top stories, recap up on the podcast.

0:44:00.800 --> 0:44:02.880
<v Speaker 3>You know exactly where to find it all the Bloomberg

0:44:02.920 --> 0:44:05.239
<v Speaker 3>platforms and online, Apple, Spotify.

0:44:05.840 --> 0:44:07.759
<v Speaker 2>In iHeart, this is Bloomberg Tech