Snowflake Jumps Most Since 2020 After Amazon Deal

26:02And so in some cases, it's just some resources to prep candidates on, you know, what types of questions they can expect for other coaches they're offering mock interviews. And what type can you expect? Because it is different. You are going to be sort of pushed more than you might be elsewhere because they're really so based on the mission, right, briefly. Right. So, I mean, that's the thing that I've heard from candidates that sometimes they're not quite expecting as much introspection, you know, these types of questions that are really pushing folks to reflect on, you know, past experiences, decisions they've made, have they felt about those decisions, which is a bit unusual for people who are used to just talking about, you know, this project I did at work and how it went and that kind of thing.

26:50My greatest failing being how successful orientated Yes, exactly. Bloomberg's Joe Constance with pretty much the most read story on Bloomberg today. Thank you very much. Coming up, Meta is selling consumer subscriptions to its Meta AI chatbot for the first time. Got that story next. Halfway through the program, heck of a lot more to come. This is Bloomberg Tech.

27:22Welcome back to Bloomberg Tech. Let us take a look at today's big number,$22 billion. And counting is how much the market cap for Snowflake has grown from just one day's market gain. Look, the stock we know is surging today. So after the software maker gave a stronger than expected annual outlook, we in fact managed to speak with Snowflake CEO, Sridhar Ramaswamy, on how AI is really helping to boost their bottom line. We had a landmark quarter-cattle line. Strongest sequential dollar growth in company's history. product revenue up to$1.334 billion, up 34%. Net revenue retention rate, a key metric we watch, up to 126%.

27:59But I think the bigger news really was that this is the quarter where we clearly showed that AI is compounding Snowflake's advantage in data. We did this the old-fashioned way, by creating amazing products like Snowflake Intelligence, which is our work agent, which doubled its adoption with respect to accounts, and And a coding agent, which is Code or Coco, which is used by more than 7 ,000 accounts. And this is what gives us confidence in the business. That's why we raised the yearly guidance from 27 to 31%. Solid performance. But I think it's much more of what does this mean for our future that we are very happy with.

28:38Another big story in the world of tech is Meta. This is a two-day chart. Yesterday, the stock up almost 4%. We're basically flat today. Meta is selling consumer subscriptions to its Meta AI chatbot for the first time. Two tiers. Basic tier,$7.99 a month. That's cool. And then one that's like kind of higher tier, Meta 1 +, like I guess those of you that are more in it. We write at Bloomberg News that this is about offsetting the AI infrastructure costs. But other people have a slightly different take. I want to get to Shweta Kajuria, Wolf Research Managing Director, joins us now. because you put research out, right, when the news comes and you're basically saying our thesis, which we'd already outlined, is playing out.

29:21You saw multiple new revenue streams. This is a potential bigger total addressable market for you rather than an action to offset that high capex or high infrastructure spending. Yeah, that's right. And thanks for having me, Ed. So at a high level, one of the deeper dives that we did prior to the news coming out was part of the reason why Meta is even underperforming Google and Amazon is that Meta is spending like a hyperscaler without any clear line of sight into demand that Google and Amazon have in their hyperscale business. And so where is Meta spending all this money to really justify this type of spend on CapEx?

30:04And when will we see that revenue? So that's the fundamental question. And so in that, when we dug deeper, it could be subscription or it could be agentic commerce or it could be business AI. And now we're starting to see with this product release of subscription across consumer businesses and meta AI that this could be the beginning of it. Talk about how this is going to scale. First quarter, it was about$1.3 billion that was in the non-advertising revenue. So tiny. But how much could that rise? Yeah. So in the non-advertising revenue right now, a lot of it could be business AI that they are actually monetizing in WhatsApp through their businesses in WhatsApp.

30:43Now an add-on is going to be subscription. So a clearest comp that we have today is Snapchat. And Snapchat arguably has surprisingly done a great job in converting its DA users, daily active users and monthly active users to subscriber base. If Meta can do something similar to that, and I'm not saying it's going to be exactly the same, but say low to mid single legit percentage of their DAUs actually convert to subscription, well, that in itself implies about a 1 to 3 % percentage point uplift to their revenue. In other words, approximately anywhere from$5 to$15 billion of incremental subscription revenue from consumers in the next three to five years.

31:28Look at it differently. In a world where you're paying monthly for ChatGPT, Claude, Gemini, etc., is Meta AI worth paying$8 or$20 a month for? That is going to be a key question for them. So there is a consumer subscription piece. There is this Meta AI type subscription piece, which competes directly with Gemini, to your point. And then there is a business, like if you are a creator, then you can subscribe as well. I see great value in the consumer subscription and the creator subscription because it allows them to create more content. But in the question that you are asking where if I have a Gemini subscription or a GPT, do I need Meta AI?

32:10Jury is still out on that. You would need it if you're running out of capacity and you're paying 20 bucks. You don't want to pay additional higher tier to a hundred to two hundred dollar tier and you want just a little bit more of access capacity. Maybe you paid bucks to Meta. Maybe in that scenario, it does make sense. or if it is highly personalized social sort of a use case that they give us, which cannot be created by Claude because they don't have that information, or perhaps a GPT, perhaps there is a use case. In those instances, yes, but I'm not fully sure. Jury is still out on that, on the Meta AI subscription scaling.

32:48Shreda Kajuria, great research, great analysis from Wolf Research. We thank you. NASA, it selected Blue Origin, Firefly, Aerospace, and other private space firms to help build out its long-term lunar ambitions. The agency says near-monthly missions could begin in 2027, laying the groundwork for astronauts to eventually live, work on the lunar surface. We spoke with the NASA administrator, Jared Isaacman, about the timeline for a moon base. Starting in 2027, you should see a near-monthly cadence of robotic landers on the moon. several rovers. In fact, we provided an award for the first two, you know, crewed and autonomous capable rovers for the lunar surface.

33:29So when our astronauts arrive on Artemis 4 in 2028, they're going to already have some infrastructure of the moon base waiting for them. They're already going to have a rover waiting for them. And then in that time frame, it's not just intermittent anymore. It's not just those monthly visits. But when do you think people will be working? Humans might even be living in some capacity on the moon there. So we are approaching the moon base in phases. So phase one is a lot of littles. We are dusting off the playbook that worked very well for NASA in the 1960s. We're getting back to an iterative approach.

34:02So, you know, there was the Mercury program before there was Gemini. There was Gemini before Apollo and an awful lot of Apollo missions before we went right to the moon landing on Apollo 11. We Phase one, we're calling it a science of survival. We're not going to lock in what the mobility strategy should be for logistics, for astronauts, the power strategy, the surface comms, the orbital comms. Why would we try and nail and get all of that perfect today when we haven't been to the moon in more than a half century? So phase one will be a lot of landings. Again, that near monthly cadence to learn and inform phase two, where perhaps now you're putting a lot more tonnage on the lunar surface.

34:42You have a lot more direction as to the type of hardware and capabilities you want to lock in on. So you don't need to have maybe monthly landings when we get into phase two, but you have a lot more direction as to what should work for our intended objectives, which is to build out that habitable environment. And then phase two, we're going to learn now having astronauts go from, let's call it a period of maybe even days on the lunar surface in phase one to potentially weeks in phase two to where you might get by the time we move into phase three a similar astronaut rotation like you see on the International Space Station where we could have crews potentially being on the lunar surface for months on end.

35:21You don't have that marked on your calendar, administrator, when phase three might have a base that has humans actually living and working inside it? Oh, we absolutely have timeframes. I mean, we are looking at basically 2027 through 2029 for phase one. You have 2029 out into the early 2030s for phase two. But again, this is all going to be informed on what we learn during those first landings in phase one. That was NASA Administrator Jared Isaacman. All right, coming up on the show, we're going to be joined by Eric Vistrier, benchmark for his outlook, the physical AI space. Yes, we're going to talk about hardware.

36:00This is Bloomberg Tech.

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38:47CEO and co-founder Arthur Mensch spoke with Bloomberg Tech Europe's Tom McKenzie. For us, it's a massive market. We see in particular, Europe is our anchor market, and the strength of Europe is in its high-end manufacturing. So the manufacturing world is the 30 trillion market. If you think of the uplift that AI can bring to it, if you only look at 10 % of that, you're looking at the 3 trillion market and that's happening in the next five years. Then over in Asia, Minimax's annualized revenue more than doubled these past two months to at least$300 million. as the Chinese AI startup prepares to roll out its next flagship model.

39:33Minwax co-founder and president, Ye Yeun, joined Bloomberg's Stephen Engel on the sidelines of the UBS Asian Investment Conference over in Hong Kong. Agent and models are really important for monetization, but definitely the foundation model is a key. You will see a better performance model with specialization and differentiation will drive the token consumption, also drives the enterprise and the consumers' retention and consumption. The model performance, product, monetization will become the flywheel. So you will see we did the end-to-end optimization with the whole group. There are lots of innovation, technical innovation inside.

40:12So you will see we can provide probably similar performance models with probably lower price, even sometimes higher margin. So how do you change your revenue mix where most of your revenue is coming from your consumer-facing products, like the chat box, Xingye, and also Hylio, which... That's last year's number. That's like the text-to-video generation. But next year, as you go into your Model 3, right, from 2.7 to 3, how is your revenue mix going to change? Yeah, so the number you mentioned is last year's number, but right now it's almost like 50 enterprise and 50 consumers, so the enterprise increase a lot.

40:51and also, yes, the model is a key. So we think the model is our product. No matter it's a B2B or G2C, it's all the channels for the commercialization. So we've spent most of our resources and the spending on the model layer. Yes, we are going to release M3 very, very soon, in a few days, which probably, I think, which is the first open source native multi-model. That was Minimax co-founder and president Ye Ye Yun along with our own Stephen Engel. We're going to stick with AI and we're going to discuss the outlook for physical AI with Eric Vichry, a partner at Benchmark. Today's VC spotlight. I've been really looking forward to this one, Eric.

41:32Ten years ago, you were very welcome to be here. Ten years ago, you led a series A in a little company called Cerebras. Fast forward 10 years. What an IPO. But it's indicative of where we're at right now in this demand for fast inference. I just want to start with that case study you know the timing of this IPO and where it fits in what's actually happening in physical AI right now well I think that it's very very clear that the demand for inference in AI is awful charts and I don't think that's going to stop anytime soon I think it was Alex Scatterditt at Whale Rock who kind of recently said if you think of the population in the world there's like 1 % of the world is maybe AI power users today.

42:24So if 1 % of the world is AI power users today and we're completely compute constrained for as far as I can see, what happens when 3 % of the world or 4 % of the world or 5 % of the world becomes AI super users or power users? And so I think that we are going to be in this compute constrained world for quite some time. And I think that that's going to lead to a lot of success in all of the hardware layers. And it's also going to lead to the bottleneck moving around. You know, some days, some months it's going to be memory, some months it's going to be data center and power, some months it's going to be chips.

43:05And I think that bottleneck is going to keep moving around. Some days it's all of them combined, Derek. Yeah, totally. So at this exact moment, where are the startups that you're most interested in or the ones that you already sit on boards of starting to innovate at the edges? When are we going to really see the movement of photonics or a different type of compute being used? Well, I think one of the benefits of being an early stage venture capitalist is we have a very long time horizon. So we're not trying to figure out what's going to happen in 18 months or 12 months or 24 months. We're really looking and trying to have some idea of what might happen in five years or seven years or 10 years.

43:45And as we look out, we're really excited. For example, we invested in StarCloud, which is a space data center. We invested in Sunday Robotics, which is a domestic robot. And when you kind of look at companies like that, they're very much on the frontier. It's going to take a bunch of time. There are very capital intensive projects, but they're amazing teams that are doing really cool development, pushing the edge. And it's going to require a lot of flexibility on their parts as the market evolves. There's obviously a lot of unknowns, but there's also tremendous possibilities. I just want to go back to Cerebris for a minute.

44:27And to some, this is now ancient history. it's academic but two days before the IPO I broke a story that Arm and SoftBank had basically gone to Andrew Feldman and said we'd buy you for a large number and Andrew very quickly shut it down and the rest is history of course because they went public but as somebody that joined the board in 2016 and has had three of the five major investments go to IPO what would you have made of that outcome instead of going public? Well, obviously, you can't comment on that specific reporting, but we're a public company now. I think that has opened up a lot of possibilities in terms of what we can do.

45:08We've raised a ton of capital to finance the business and allow us to take advantage of the tremendous demand. And I think we're really at the beginning. And, you know, if you feel like there is an end in sight, you might take a different tact. But as far as we can see, the demand is tremendous. You say you just backed a company that's about orbital space centers, and that immediately makes us all think of SpaceX and how they're going to be sucking a lot of the oxygen out of the room when it comes to a public offering. How are your companies currently feeling the need for cash? How are you thinking about permanently fundraising or looking for exits right now?

45:47Well, it's really interesting right now. The venture landscape is very much have and have nots, which is if you are oriented around AI and you're growing really quickly or have something that's very much on the frontier, there's almost like limitless cash available and funding available. And if you're not, even if it's a good business that people would have fallen all over themselves for five or six years ago, there's almost no funding available. So it's a very bimodal setup right now, which is challenging, certainly. But each of these financing eras, they come and go. And one of the really important things for any of these companies or entrepreneurs is just to keep on grinding and finding a way.

46:34There's building a company that is impactful, is a roller coaster, and takes a long time. And even if you take the Cerebra's journey, there have been lots and lots of ups and downs over the time. Obviously, taking an AI semiconductor company public in May 2026 is about as good timing as you can get. But, you know, part of that is the timing part is part of that's just luck. And then obviously it's all built on top of a decade of the team grinding at it. Cursor, another interesting one that we're looking at in your portfolio. We'll have to talk about that another time. Eric, it's great to have you on.

47:14Eric Bishria of Benchmark. Now coming up, TikTok. Well, it's moving away from music, scaling back ties with major music labels. We'll dig into that next. This is Bloomberg Tech.

47:31AI could provoke a 15 % displacement of knowledge workers. That's according to Muddy Waters Capital CEO, Carson Block, who joined Bloomberg's Hasilina Amin in an exclusive interview to discuss AI demand. Listen to this. Our house view is that we're going to see 15 percent displacement of knowledge workers. You know, we think it could be as soon as three years. Is it four? Is it five? at some point, and it's in the single digit number of years, this will be a factor or this will occur in our view. And yes, there will be jobs that are created by AI, but we're talking about net losses because the technology is increasing in capability faster than we humans are able to adapt to it.

48:21Let's talk about the displacement of music labels, maybe over at TikTok, because music's been called to TikTok's identity since its days is Musically, helping artists like Lil Nas X or Olivia Rodrigo, just global stardom and weights. Now TikTok, though, is scaling back ties with major music labels and focusing more directly on those artists, according to sources. That was all discovered by Blueberg's Alex Levine along with Ashley Carman. What is happening with a company that identify with music? I mean, it's in their icon, it's in their branding. How are they moving away from labels? So, exactly.

48:54Music has really been part of its DNA since the very beginning. It is the thing that helped make TikTok this global cultural phenomenon and got more than half of America using it. Though TikTok continues, importantly, to work with major music labels, including some of the world's biggest, it is deprioritizing those relationships in part by building out projects, prioritizing internal efforts to actually have products and services that compete directly with the labels and that allow the company to have sort of more direct relations with the artists rather than through the representatives. Alex, TikTok changed music.

49:32Now labels worry it's leaving them behind. But present day, how does music work on TikTok? So it's Friday night. I'm kicking back on the couch. I go to YouTube on the TV and play concerts, music videos. I don't think present day, like, you know what? Yep, music, music video. Like, just explain what we're talking about mechanically. So mechanically, when you open your app, you've got your For You feed. Every video that you see is going to have some sort of audio behind it, whether that's people speaking or whether that's music. And oftentimes those sounds are songs that have gone viral. And sometimes it's new songs from emerging artists.

50:09Sometimes it's global hits from artists like Paul McCartney, like Bruno Mars. And sometimes it's simply just, you know, sort of repetitive meme type noises that you can find through various other means on the app. But I think that there's always sort of been this question, especially more recently, about whether blowing up on TikTok or going viral can actually mint a legitimate star and have them develop really an enduring career from that. Bloomberg's Alex Levine with what's going on in music on TikTok. Thank you very much, Cara. And that does it for this edition of Bloomberg Tech. What an edition it's been.

50:46Yeah, a lot of market moves, a lot of great interviews, a lot of top stories, recap on the podcast. You know exactly where to find it. All the Bloomberg platforms and online, Apple, Spotify and iHeart. This is Bloomberg Tech.

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