Chapter 1: What is the main topic discussed in this episode?
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Chapter 2: What is Nvidia's latest sales forecast and market reaction?
Are we needing to hear more about growth in China, for example, which, again, isn't being factored into the forecast? How much can we support that the capital expenditure is going to last through 2027 fiscal?
Yeah, so look, the adaption is broadening. There's no question about it. We are seeing that on the enterprise side, on the sovereign side. China is kind of a little tricky because there's a lot of geopolitical issues here. The good thing is that the management did not include any China revenue in the guidance. So if it comes through, it's upside to the model.
I think it's going to be incremental longer term. We're not counting on China. You look at the valuation. You know, it's in the low to mid 20s today on forward numbers. You know, that's pretty attractive for a stock, for a company that's growing, you know, 70 percent plus. Obviously, that's not sustainable. But our expectation is that even in 27, this company can grow at least 30 percent.
And at this level of gross margins and profitability, I think that's a particularly attractive valuation.
In your risks to rating column in your research note, very clearly hyperscale spending is a leading indicator for AI demand. Jensen Wong was asked that on the call. This is what he said.
I am confident in their cash flow growing. You need compute capacity. And that translates directly to growth and that translates directly to revenues.
He was asked about capital expenditures growth going forward. His answer was confidence in cash flows, because of course, cash flows have been impacted by the CapEx commitment. He didn't really answer the question, but what did you interpret from what he did say?
Look, at the end of the day, you know, the spending has to have a return, right? The ROI is very important, but we're still very early in terms of the AI cycle. And Part of the reason we are seeing this elevated spending is that the competition among this big four or five hyperscalers is pretty intense. It's still the battle for leadership is still not settled.
I mean, just recently, Google took the lead in terms of the large language model performance. And you have OpenAI, Anthropic right behind them, and XAI. So the competition is quite intense. And we don't expect that battle to settle anytime soon. So it's not so much about ROI right now. Longer term, it does matter.
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Chapter 3: How do Nvidia's earnings compare to market expectations?
Let's bring in Snowflake CEO, Sridhar Ramaswamy. Sridhar. I'm reading notes, Mizuho saying bookings were a standout. They're talking about the seven nine-figure deals that have come. Where are those deals coming from? What are those customers demanding of you? Great to see you, Caroline. Yes, we had seven nine-figure deals, including a mammoth $400 million deal.
It reflects the confidence that our customers have, both in where Snowflake is right now, but importantly, where we are going. We all understand that software is being disrupted by AI in a very, very big way. But what our customers understand is that what enterprise AI to truly succeed. They need a single source of enterprise truth. They need built-in security, auditability, trust, and access.
Of course, you also need the best models. That's what Snowflake provides for them. And we're creating great products, products like Snowflake Intelligence that put the power of data into the hands of every business user.
Whoop, the healthcare company, I mean the health company loves using us and there are lots of partners that are using products like Cortex Code to speed up what can be done with Snowflake. They're really looking to the future and making sure that we can deliver value with Snowflake and we are creating the products that help them deliver that kind of value day in and day out.
That's why you're seeing companies, as I said, make commitments of 400 plus million dollars with Snowflake. I'm really interested in Codex Code was something that was talked a lot about on the call and people are adopting swiftly.
But that partnership model that you have, the fact that you have integrations with Anthropic, OpenAI, also Google Cloud, but some of these have very good coding tools of their own. How do you see this ecosystem evolving? Because customers get it, but the investor base has been questioning whether they'll take away your market share.
Well, so there are a lot of things that are specific to Snowflake and to data. Absolutely, there are coding agents that are often provided by the model companies themselves. But we know a lot about how data systems are supposed to work, about how Snowflake is supposed to work. And Cortex code is super tightly integrated with the customer's Snowflake account. Data does not go anywhere.
And remember, we have earned the trust of all of these customers with certifications, with the guarantee around things like AIUs. We never use customer data for things like training models. They get the superior models that we get through partnerships with these folks, but we also add the secret sauce of data of how Snowflake works into products like Cortex Code.
And we are seeing amazing wins both internally and also externally. One of our partners told us that having Cortex Code was like Snowflake supplying them with bulldozers where previously they had shovels. Trudeau, one of the core pillars for you to grow is to go out and find new customers.
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Chapter 4: What challenges does Nvidia face in the AI market?
It's hard for them to get these insights. But increasingly, what we are able to do is have our sales team build an honest-to-goodness customized demo of something like a Snowflake Intelligence on the kind of data that a customer is going to have. It is that easy access that really is the big winner for our customers.
And smart customers are also quickly realizing that having data in Snowflake means that they can think about how this data is going to be used in ways that they had not done before. Sanofi, which is an existing customer, is now using Snowflake Intelligence, our AI products, to redefine a lot of workflows, replacing a lot of existing software.
These are the use cases that drive these customers to come to Snowflake and adopt it. Sridhar, last night, Jensen Wang, who you know very well, talked about profitable tokens. The idea that the output of an AI model is worth paying for, customers do pay, and they pay at a price that is greater than the compute used to generate it.
Are you able to give me any evidence through Snowflake's lens that you actually see that in the real world? Well, what I can assure you is getting projects done has been changed dramatically. Something like setting up a pipeline used to be a multi-week task. We can get that done in a small number of hours.
teams come to me just last weekend with speed ups going from four weeks for a software engineering project that they did down to 40 minutes. That is 100x speed up. And we are happy to spend any number of tokens in those 40 minutes to save that kind of time. I think coding agents are really quite magical in the value that they deliver. And I think it's only going to accelerate from here.
And so these investments are going to be pretty foundational in every company succeeding and thriving. And that's why we are so bullish about Cortex Code. And how much are you having to invest in your own business? I mean, the bullying case for many is you need to keep up with a furious pace of innovation. Can you at this moment briefly? We can because we are organized to drive rapid innovation.
The team that is driving a product like Snowflake Intelligence is not that large, but we have structured it in such a way that they can make rapid progress. And it is more the meta structure of how you set up environments where people can get work done quickly and effectively. That matters a lot more than things like how much hardware you're investing in and things like that.
The current moment is magical because all of us have access to great tools. It really comes down to how effectively we set up teams and projects to get things done. And that's why we are very bullish on how we have set things up at Snowflake because we now have a demonstrated capability to be right at the cutting edge of where AI is having impact.
Snowflake CEO Sridhar Ramaswamy, great to have you back on Bloomberg Tech. Thank you very much. Now coming up...
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Chapter 5: How is Nvidia managing supply chain constraints?
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Chapter 6: What insights does Snowflake's CEO provide on AI adoption?
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