저자: JimCramer · 외국인
요약 보기
크레이머는 ServiceNow의 SaaS 우려와 분석가 미팅을 언급하고, 데이터센터 수혜주로 Eaton을 꼽았다. Shopify와 UPS 실적 기대를 밝혔고, AMD에 대해 이번 주 호재 기대와 매수 의사를 표명했다. 또한 Lumentum, Arista Networks, Astera Labs를 강하게 긍정했다. 후반부는 석유 기업 임원 발언(호르무즈 공급 차질, 유가 1~6개월 전망 질의)과 Nvidia-Applied Digital 파트너십, AI 인프라 수요 확대 논리가 이어진다.
다듬은 글
Let me I would think. Now, we have an analyst meeting Monday for ServiceNow, okay? A stock that's been hammered relentlessly because of the AI displacement worries that have dragged down the entire software-as-a-service space. These companies typically charge per user, and that perception is that AI is wiping out too many jobs for that business model remain viable.
I want to hear if customers are cutting the length of the contracts they've taken in preparation for AI agents reaching the point where they can take over from people and possibly do a better job in ServiceNow. The software-as-a-service group caught fire today, though. Maybe that bodes well for ServiceNow.
I am sure that Bill McDermott will put on a good show. He's the CEO, and he's a very good promoter of his company. Tuesday jammed. We've got the dilemma of the data centers identified by Eaton, which provides electric hookups and air conditioners to keep things cool. We know that for the travel trust has had a big run.
The ones that have had big runs, they tend to sell off. I got to be careful, all right? I want to monitor Shopify. I want to watch Tuesday because the universal fulfillment company has a great read on small and medium-sized businesses. I always worry about them. The this company is the chief e-commerce enabler for these smaller companies.
Stock's been meandering of late. I think it's going to have good numbers. We'll have to find out, though. Can you advise it break out of its multi-year rut? Now, a lot depends on the presentation because I haven't seen any needle movers in the portfolio. Primarily cheap, good yield, but if I want good yield, I'll buy a bond.
You want to upset surprise? Okay, I'm going to say that I'm going to I'm going to say it's going to come from AMD this week. And I'll buy some AMD ahead of the quarter. Lisa Su is the best. Oh, you know what? Let me give you TWO MORE. I WOULD BUY LUMENTUM. I would buy Arista Networks. Yeah, I'm that bullish on this day.
Two companies that help the machines in the data center talk to each other. I press my bet with Astera Labs, fabulous semi-conductor company that also does connectivity. And when people ask me, "What does Astera Energy Labs do, I always say it goes up. There will be plenty of profit like this, uh particularly operational disruptions, uh when it came to the steps that we had to take to protect our people, that was critical.
The work that we're doing to meet that growing uh divide between demand and falling supply with the organizational construct we put in place. We've been in a position to to respond and re and divert barrels, take advantage of our big footprint to optimize make sure we're meeting the most critical demand irrespective of where it occurs around the world.
We redeployed about 13 million barrels uh to make sure it's getting to the markets that need it most. And you mentioned that's one of the the things that we called out in our press release with the timing. Because we moved so many barrels, our trading organization, which we stood up uh several years ago, we're in a position to to manage all that and uh put hedges in place to lock in that profit.
Uh as you close the quarter in the volatile market, you know, you book the hedges, the paper, but the physical barrels are in inventory until they get delivered. So, you get this deferred uh profit that we wanted to basically highlight and make sure that the the our investors understood that the work that we're actually doing to to meet the demands today are resulting in uh benefit uh not necessarily booked in the quarter.
Yeah, I I I I I understand that. I I realize that the loss that was booked this quarter will be made up for probably in the next quarter. Uh so, you got to smooth that out over a quarter to quarter. Um Darren, just in terms of where oil prices are headed, I know this is a difficult game anytime to try and predict, now even trickier than normal, but what's your best case?
What's your base base case best gas base case scenario for this? Where we're headed over the next 1 to 6 months? Yeah, I think it's it's well obviously very difficult to to call based on what's happening there in the region and this the externalities associated with those things that are happening. What I would say is it is an unprecedented disruption of supply in the markets and so our expectation is over time we'll see prices respond to that unprecedented disruption.
Once the strait opens up, it'll take 1 to 2 months for for the flow to reestablish itself and then you within that time it's going to take you know transit time to get the barrels out of the the Persian Gulf into the the demand destinations. The customers are going to it usually takes about a month of transit time.
So there will be a time where it takes for the market to recover. Um Fortunately, we haven't seen the full impact of the strait being closed because of the the oil that was on the water in transit when the strait closed and as that cleared we had the the strategic petroleum reserve releases, we had commercial inventory draws.
So so far the world has seen a mitigated impact to that loss of supply and the prices bu latest partnership between Nvidia and Applied Digital shows how the AI industry is entering a completely different phase. In the early days of artificial intelligence, most of the focus was on model development and the software breakthrough.
Now the conversation has shifted toward the infrastructure, power, compute availability, networking capacity and large-scale deployment. AI is no longer just a software story. It has become global infrastructure race. Under the agreement, Applied Digital will provide Nvidia with a massive AI infrastructure capacity measured in gigawatts.
While Nvidia will lease billions of dollars worth of cloud computer services from Applied Digital over the multiple years. Nvidia also secured a warrant that would allow it to purchase a significant amount of Applied Digital shares in the future. This structure reflect a broader trend where AI companies are increasingly for meeting forming a strategic infrastructure partnership instead of purchasing the traditional acquisitions.
The reason behind this partnership is simple. Demand for AI is exploding faster than the industry can build the capacity. Hyperscalers, enterprises, startups, government, and research labs all are computing for the same finite pool of GPUs, networking equipment, energy supply, and data center space.
As a result, access to infrastructure itself has become one of the most valuable strategic advantage in the technology. Nvidia remain at the center of this transformation because nearly every major AI workload still depend on Nvidia hardware in some form. Jensen Huang spent years of building the company around the accelerated computing long before the most of the industry realized how important GPUs would become for the machine learning and AI.
Today, that early investment is paying off at extraordinary scale. One of the most important development in recent months is rapid rise of AI genetic AI. Traditional AI system mainly respond to prompt or generated content. AI genetic AI goes much further. These systems can perform task automatically using digital tools, software platform, databases, browsers, and spreadsheet.
And enterprises application also. That should drastically increase the infrastructure requirements because every AI agent consume both the GPUs and CPUs resources simultaneously. The GPUs handle the inferences and reasoning process, while CPUs execute many of many of the surrounding operational task, workflow, and software actions.
This is why demand is now spreading across the entire semiconductor ecosystem instead of remaining the concentrated solely in the GPUs. Companies tied to CPUs, memory systems, optical networking, power delivery, cooling infrastructure, and the storage systems all are benefiting from AI expansion. This broader infrastructure buildout is the one of the reason many analysts believe the AI cycle is still relatively early.
Several market competitor commentators describe the current environment as being only the third inning of a much larger long-term transformation. This logic behind that argument is that enterprises are only beginning to integrate AI into their operational workflow at scale. Most businesses are still experimenting with how to deploy AI effectively, and infrastructure demand continue accelerating as adoption expands.
Another key factor supporting Nvidia's long-term outlook is increasing monetization of AI services. Earlier concrete at round the weather companies could actually generate meaningful revenue from AI product to justify the massive capital expenditure. But recent growth numbers from major AI labs and cloud providers suggest that enterprises demand is growing rapidly.
AI coding tools, enterprises automations system, and AI-powered productivity platforms are already generating a significant recurring revenue streams.
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