저자: JimCramer · 외국인
요약 보기
IBM은 IT 예산 압박과 실적 부진으로 하락했으나 AI 전략 강점이 과도하게 무시됐다고 보며, 역풍이 길어질 수 있어 하락 매수는 권하지 않음. 엔비디아는 밸류에이션이 낮아졌고 하이퍼스케일러 AI 투자 확대와 소버린 AI·피지컬 AI 등 장기 성장 여력이 크다고 봄. 메모리(마이크론)는 AI 수요로 공급 부족과 가격 상승이 이어지고 있다고 평가. 엔비디아 목표가 280달러를 언급하며 가을에 기술주 성장 재부각을 기대.
다듬은 글
What happens when the three main areas of IT spending become a priority, as has happened now? Other types of expenses should take a back seat. Unfortunately for IBM, they have too many products and services that fall into these other types of costs. Even though they have a pretty decent overall strategy for AI, which I've been talking about for a long time.
So, while IBM shares fell 25% today, which seems excessive given the scale of the disappointment, I can't advise buying these stocks on the decline, as I believe this weakness could be prolonged. Of course, the shares are pretty cheap right now . Yes, they are trading at about 17 times this year's earnings projections , but those projections are due for significant revision.
Yes, IBM's dividend yield has risen above 3% again. This is nice, but not a compelling enough reason to buy shares. I like that Christian took responsibility for the bad quarter. He's a good guy, a good leader, and I think IBM still has some advantages in AI that were completely ignored in today's meltdown.
But frankly , I'm too concerned about these trends to say it's safe to buy IBM after this drop. We are now at that point in the year when IT managers are forming their budgets for 2027. And you have to understand that these three priorities that I just outlined will continue to dominate, which means that everything else will have real problems.
I hope IBM is really only facing deal delays, not cancellations. But I can't advise buying stocks just because I hope for the best. Hope should not be part of the equation in this situation. So let me summarize. Corporate IT budgets are suffering due to skyrocketing prices for all equipment—this is research by the author of the book “Everybody Wants to Rule the World.” When considering Nvidia, we take into account the fact that the P/E ratio has declined.
Many guests who come to us say: look, it's gotten better . It is cheaper now than it was in January. What do you think about Nvidia's recent results? What impresses you the most , Nicole? Nvidia is running at full capacity but is n't getting any benefits from it. And this is largely due to the fact that the market is not confident in the availability of additional capacity.
What will actually happen after Vera Rubin, Rubin Ultra, and what will happen to all the other chips after that. But the reality is that the demand is there, and I think many are just being cautious . They're waiting to see what the hyperscalers will do, what Microsoft will do next week. Are they going to invest more?
Are they going to retreat? Do they have the revenues to support such growth? But this was the largest reallocation of capital in history from hyperscalers and software to hardware and chips. And you have a target price . You buy for 280. Is that right? What will be the catalyst to take us from 209 to 280?
I think in the fall we will face a harsh reality: only the technology sector is growing. I know there's a rotation of capital out of the tech sector right now, but when we start thinking about those who are showing double-digit growth, who are creating opportunities for the next innovations, it will be the tech sector again .
And this is what actually determines the target price. Another point is that we have not yet reached sovereign AI. You talked about agent-based AI. You talked about physical AI. All these areas have not yet been properly assessed. These are huge markets coming up, especially in the area of sovereign AI, as each country tries to figure out whether it can provide AI to its citizens and do so on its own terms.
This will be one of the biggest trends, and this development will continue. We're only in the third inning of a nine-inning AI game , and we don't even know who the winner is going to be. We know who the players are, but we're not sure who will ultimately win, and there's a long road ahead. Investors are punishing companies for spending heavily on AI.
For example, this week we saw Alphabet Google announce an increase in capital spending to $205 billion, and overall for hyperscalers we expect $1.2–1.7 trillion. Do you think companies should be more frugal in capital expenditures and change their business model? This is a different situation, right?
When we thought about the internet or cloud technologies, we imagined something different. It was about decentralization, openness, and a large number of players. Prices were falling. And, as you know, brick-and-mortar stores suffered from this. Here everything is the opposite. It is centralized. This costs more.
You will need resources , because these are effectively closed systems entering the market. So the game requires capital. The game needs scale. And only a few companies will be able to compete in this market in the long term to claim the creation of general AI. They will provide inference. They will be able to provide work at the periphery thanks to decentralized physical AI.
There are few players, which is why hyperscalers are betting big on it . I expected Google to leave their capital expenditure forecast at 190, but something else happened: they said, “No, inflation and many other factors. We will continue to move along this path. We had a great quarter and we're going to spend ." And this confused investors .
And I'm thinking about this as I await the Meta, Microsoft, and Amazon reports next week. But you said you expected something more stagnant from Google, but called Alphabet's increasing capital spending a good signal of durability. What does this mean? This is important because Alphabet continues to believe they will invest in the years ahead.
So when we saw predictions of $700 billion for AI infrastructure from hyperscalers and others at the beginning of the year, and then we see predictions of $800, $ 900, and eventually $1 trillion. This is the momentum that drives this trade. We are seeing further acceleration in growth, not leveling off.
And once those numbers drop, yes, you will see a shift from AI trading to hardware, memory, and storage. It will all come back to software and services. So companies that can deliver results and solutions will take care of the rest. And this is where the likes of Palantir come into play again. This is where some stocks that have fallen sharply, such as ServiceNow, Salesforce, Workday, will have a chance, because by then they will have agent systems that will use this infrastructure.
How do you compare these names to hyperscalers, as we await more news and perhaps you are not giving investment advice? The history of AI investment is entering a new phase, and one of the biggest winners may no longer be companies building AI models . Instead, the companies that use the hardware for these models are becoming increasingly important.
Recent earnings reports from some of the world's largest technology companies point to the same conclusion. Artificial intelligence is becoming much more infrastructure- intensive than many investors initially expected. This shift creates huge opportunities for companies across th is the memory market.
For decades, memory chips have grew, prices rose, and producers increased production. Eventually, supply caught up with demand, margins fell, and the cycle weakened again. Artificial intelligence is changing this dynamic. Today, memory is not just another semiconductor component. It has become one of the most valuable resources in the AI ecosystem.
Without modern, high- bandwidth memory, the latest AI accelerators simply cannot perform at their highest level. This reality is forcing the world's largest companies to rethink their approach to memory procurement. Instead of relying on short-term orders, companies are increasingly entering into multi-year agreements with suppliers.
And the goal here is simple. Guarantee access in the future until production volumes are fully distributed. Tesla's recent earnings report clearly highlighted how valuable this relationship has become. Elon Musk has openly thanked Micron for securing future memory supplies, acknowledging that suppliers are forced to make difficult decisions about which customers will receive limited production.
He also acknowledged that current memory prices have become exponentially high. These comments reveal something important. Competitive advantage now lies not only in creating better AI systems. And in providing the components necessary for their construction. This marks a major change in the semiconductor industry.
Companies with long-term relationships gain access to scarce resources. Companies without such relationships risk facing delays, higher costs, or reduced production. This environment naturally strengthens the position of companies like Micron. High demand combined with limited supply creates pricing power, which directly translates into higher revenue and profitability.
And this same trend benefits Nvidia. While investors often focus on Nvidia's GPUs , the company's true advantage extends across the entire AI platform: hardware, networking, software development tools , systems integration, and, increasingly, supply chain coordination. Recent announcements about advanced semiconductor packaging demonstrate that Nvidia doesn't just make chips.
The company is investing in the entire production process so that future production volumes keep up with demand. Packaging has quietly become another critical bottleneck . Creating the world's fastest AI processor means little. If advanced packaging capacity cannot support production, the company clearly understands this challenge and, rather than waiting for a shortage to become a problem, helps expand that capacity in advance.
Such a proactive strategy could strengthen its competitive position in the coming years. Meanwhile, another debate is underway on Wall Street . Aren't hyperscalers spending too much money? Investors continue to question
댓글 0