저자: DanIves · 외국인
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Dan Ives는 Microsoft 개발자 컨퍼런스 발표가 경쟁(Copilot, Azure) 방어 차원이며 시장이 MSFT를 저평가하고 있어 향후 6-12개월 수익화 국면이 올 것이라고 주장. 양자컴퓨팅 관련 MS 행보도 긍정 평가. 이후 Mayo Clinic과의 AI 헬스케어 파트너십 소개, MS가 Nvidia GB200/300 최대 구매자라 수요 급증 예상. 영상 후반부는 엔비디아의 대규모 채권 발행을 생태계 확장을 위한 재무적 옵셔널리티로 해석하며, 밸류에이션이 성장 대비 낮고 컴퓨팅 수요가 공급을 계속 초과한다고 주장.
다듬은 글
Microsoft biggest drag on the S&P. Obviously, the S&P's higher, but it's one of the reasons why it's not it's not higher as high as it could be, I should say. You have a very bullish price target on Microsoft, 575 or more than 25% upside. What do you make of the announcements at that conference today?
Does it change your view on the stock long-term at all? Yeah, Frank. I mean, look, they're defending their turf. They're going after developers, and that's really front and center in this arms race that we're seeing play out. And I think these are the important steps, not just on Copilot and Build, but what ultimately will be Azure.
And that's why I think right now the market is mispricing Microsoft to what I believe is still going to be the monetization phase that's going to happen next 6-12 months. We like everything we're seeing here at the developer conference. All right, like everything you're seeing. I want I want to just very briefly, very quickly touch on that quantum news.
Is that something that cuz we're going to talk about cybersecurity in a minute, and a lot of people see quantum as basically something that could really hurt the cyber sector. Is this quantum news significant? We see a lot of surges in the stocks from time to time, but the news out of the developer conference today.
It's a step out of look at IBM's playbook with Arvind, right? I mean, you want to see more exposure to quantum given where Microsoft plays. And look, it's our view, that's a derivative of the fourth industrial revolution that we're seeing. And not just what we're seeing from government inside, but this is one where you want to see Microsoft dive into the deep end of the pool.
And I think this is just more and more what we're going to see from Big Tech as we're continuing to see innovation expand. And I think it's accelerating a lot quicker than anyone would have expected, even though quantum's obviously been focused on some smaller companies that have now become pretty large.
All right, also want to hit on Alphabet. Your price target there at 370, just about a percent or two upside in your view. What do you make of this $80 billion equity sale that they're doing, and the fact that it's going to be in tranches? Look, I think that's This is Dan Ives. Dan, great to see you as always.
Good to be here. All right, so Dan, I just I just kind of mentioned Sticking with healthcare, AI is already helping researchers develop drugs faster and helping doctors analyze patient data. Now, Microsoft is partnering with a giant in the medical field, the Mayo Clinic, to try and advance diagnoses and treatments.
Joining us now in exclusive interview from Microsoft Build in San San Francisco is Microsoft AI CEO Mustafa Suleyman, Mayo Clinic president and CEO Dr. Gianrico Farrugia, along with our Kate Rooney. Kate. Melissa, thank you so much. Gentlemen, it's great to see you both. Thank you for being here on a big day for Build.
So, you guys announced this joint partnership. Mustafa, maybe we could start with you. And and for our audience, you are sort of a a household name in San Francisco in AI. You were a founder of DeepMind and sort of a founding father of this technology. What is the importance of having a exclusive AI model for healthcare?
Why does it matter? And tell us a bit about this partnership. I mean, healthcare is perhaps the most important application of AI. This is why we create AI models. We want to do the best that we can in the world, make all humans healthier and live longer. And so, partnering with the Mayo is a lifetime dream for me personally.
It means that we're going to have access to perhaps the most valuable, the most integrated longitudinal patient data set in the world. And I think together we'll be able to build something really incredible. And Dr. Farrugia, for you, I wonder how you measure success here. It's different than a lot of the Fortune 500 companies we talk to.
When they talk about financial metrics, the outcomes in healthcare are a bit different. But, the criticism has been that the technology investment hasn't paid off. What does it look like for you? And are you seeing the actual results, positive results in the outcomes you want based on the spending you've had to do?
Sure. First of all, Mayo Clinic is a not-for-profit. We're driven by primary value, the needs of the patient come first. We provide outstanding care. We're rated as number one healthcare system in the world. But, we also know that most people will not have the opportunity to visit us. So, for us, a big return would be if more people get access to Mayo Clinic.
We have over the past 7 years built our Mayo Clinic platform. We can reach about 100 million people. This, working with like-minded company like Microsoft that focus on excellence, allows us to reach much further. And we're already seeing in some of the models we have deployed that we can see both an increase in our ability for to create diagnostic efficiency, but also to reduce the burden on our staff.
And therefore, that is a measurable outcome that we keep in mind, which is our patient outcomes actually better. And Mustafa, who do you anticipate using these models? Is it for consumers? Is it, you know, a medical question that somebody might ask about their kids? Or is this really for doctors? I mean, the number one goal here is to put the patient first and do whatever is necessary to improve patient outcomes.
Sometimes that's going to mean going direct to the patient, which we will certainly do through our own Co-pilot health experience, but also through the digital front door the Mayo have created. But of course, we also want to make the job of a physician easier, faster, give them more accurate information, more real-time information, improve the diagnostics that they can do, too.
So, both sides are going to be just as important. People probably already use ChatGPT and others cloud for medical advice. I want to ask you, Mustafa, about that question of cost. And we've talked about tokens. And Uber, for example, today said that they were sort of cutting off cloud code because it's getting so expensive.
How are you balancing that at Microsoft when the cost of building on AI is so expensive? How do you manage it? Well, I think the other way of seeing that is that usage has gone through the roof. And that's why, you know, the demand is what's causing a constraint on supply. We're actually very proud to be the largest buyer of Nvidia GB200s and 300s in the world.
So, we have an incredible capacity pool, and we know that, you know, when we do get product market fit inside of the Mayo Clinic and many of the other hospitals, demand is going to go through the roof again. And so, we're really expecting a moment where this becomes the number one place that you get access to health information.
Hey, it's Lukman with the video. For a year, Nvidia's story has been simple. Build the best AI chips, sell every chips you can make, and generate a mountain of cash, and repeat. But, this week Nvidia made a move that suggests the company may be thinking much bigger than the most investors realize. Despite sitting on the one of the largest balance sheet in corporate America and generating staggering amount of cash flows, Nvidia announced a massive bond offering.
The immediate reaction from the many investors was obvious. Why would a company draw uh drawing in a cash need to borrow tens of billions of dollars? The answer may reveal where Nvidia believes the AI industry is headed next. Because this isn't about needing the money. It's about creating optionality.
The company could easily fund its operations without raising a dollar. Its cash generation alone is extraordinary. And yet, Nvidia chose to enter the debt market anyway. That tell you the management may be preparing for a future where financial flexibility become a competitive advantage. Think about what is happening across the AI ecosystem.
Every major player is racing to secure infrastructure. Cloud providers are expanding capacity. Startups are raising record amount of capital, and model developers are demanding more compute. Data center operators are building as fast as possible, and every participant is competing for the same limited resources.
In that environment, capital matters, relationships matters, and the ability to finance partners may matters even more. That's why some analysts believe that Nvidia bond sales isn't really about Nvidia. It's about the ecosystem. The company has increasingly become the center of AI economy. When an AI startup need fundings, Nvidia often participate.
When infrastructure providers need hardware, Nvidia benefit. When a model developer expand, Nvidia wins. The company isn't just selling the GPUs anymore. It's a helping to build the entire industry around them. And that's a required a different level of financial sophistication. What sophistication is that?
this has come at the time when an Nvidia Nvidia valuation remains surprisingly reasonable compared to its growth profile. For years investors assumed that Nvidia would eventually trade at premium multiple forever. Instead, earning growth has expanded so quickly that the valuation has compressed dramatically.
Today many analysts argue that Nvidia is trading closer to mature company than a business still growing at extraordinary rate. That's one reason why some investors continue viewing it as the one of the most attractive opportunities in the artificial intelligence. Meanwhile, the fundamentals backdrop remain incredibly strong.
The world is still doesn't have enough compute. That reality hasn't changed. Every week bring a new evidence that demand continue exceeding supply. New AI models require more resources and new applications require more resources. New agents require more resources and increasingly the consumer AI is beginning to join the party.
This is important because the next wave of AI adoption may be look very different from the first. The first wave was about training the model. The next wave is about deploying them everywhere into the smartphones, into the laptops, into the enterprises workflow, into robotics, into automation system, into every product category that can benefit from intelligence.
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