Some of the best companies in the world have been taken in the recent market sale, in particular Nvidia (Nasdaq: NVDA). The action is negotiated more than 25% on its heights established earlier this year at the time of writing this article.
However, this weakness has created a great opportunity to buy in the stock. Let’s look at three reasons why investors should buy the action as if there was no tomorrow.
The recent withdrawal of the stock market left Nvidia to a very attractive assessment. It is now negotiated at a price ratio / in the long term (P / E) benefit of only 24.5 on the basis of this year’s analysts estimates. That’s not all, however; Its price / benefit / growth ratio (PEG) is less than 0.5. PEG ratios take into account the growth of a business and a multiple of less than 1 is generally considered undervalued. As such, Nvidia’s actions are extremely cheap when you take into account its growth prospects.
Nvidia has been one of the main growth actions in the past two years. His income has skyrocketed 383% in the past two years, going from $ 27 billion in the year 2023 to 130.5 billion dollars in the year 2025 (finished January). It is not often that you see a company the size of Nvidia doubled its income in one year, then double it the following year.
Meanwhile, its strong growth in income is expected to continue in 2025. Analysts expect the company to increase its revenues this year from 54% to 204.4 billion dollars, then almost 24% in 2026 to 252.4 billion dollars. Although Nvidia has given no annual orientation, it has planned its tax turnover to jump by 65%.
NVIDIA is the clear leader in graphic processing units (GPU), with a market share of more than 80%. The GPUs were initially designed to accelerate the rendering of graphics in video games. However, today, they have become the backbone of artificial intelligence infrastructure (AI) because of their ability to quickly process large amounts of data. In addition to their high memory bandwidth, it makes the fleas perfect to manage the rigors of the workloads of the AI.
Nvidia, meanwhile, stood out in the field with his Cuda software platform, which he created to allow his chips to be programmed for tasks outside their original objective. Its nearest competitor, Advanced micro-apparentsdid not take out its own software solution to program its chips until about a decade later, giving Nvidia a great lead in this area. Meanwhile, the company has since built a collection of libraries and tools above Cuda, called Cuda X, which now allows developers to use its software for AI applications.
The gap that Nvidia created was exposed during recent tests carried out by the semiconductor research company SemianalysisWho found the GPUs of AMD unusable to employment for the formation of the AI due to bugs in its software and that this has removed the paper advantages that its GPUs may have had. Meanwhile, he noted that the out -of -box performance of Nvidia was “incredible” with little need for technical support for Nvidia engineers.
Given its broad gap, what matters most for Nvidia at this stage, is the infrastructure expenses of the AI. The company has a dominant market share, so as long as IA data center spends continue to increase, the company is well placed to continue to grow.
Currently, the only way to considerably improve AI models is to train them on larger and more diverse data sets. This requires more computing power, which comes from the AI chips, in particular GPUs. As the AI models have progressed, there has been a steep ascending curve of the number of GPUs used to form them. Meta-platforms“ Llama and the XAI GROK models are two of the best examples accessible to the public, with the latest versions of the two models using 10 times more GPU to form than their predecessors.
Meanwhile, Cloud Computing companies are among the largest GPU buyers while they are looking to extend the capacity to follow the workload request for AI. In addition to building their own AI models, these companies essentially provide AI as a service where they give access to pre-formulated foundation models, automatic learning frames and APIs, which developers use to integrate AI into their existing applications. The three major cloud computing companies will spend around $ 250 billion by expanding their data center infrastructure this year overall to meet the growing demand for these services.
In addition, other technological companies, such as the aforementioned meta and xai, also spend large on AI infrastructure in AI models, while Openai, the manufacturer of Chatgpt, announced plans with Flexible bank And others to spend $ 500 billion on capital expenses of the data center in the coming years thanks to the Stargate project. Large companies of various industries, on the other hand, also invest in AI infrastructure, often adopting a hybrid cloud strategy where they use both infrastructure and on -site cloud services.
For its part, Nvidia sees the infrastructure expenses of the AI data center exceeding $ 1 billion in 2028. If this occurs, the Nvidia stock has a lot of advantages from here.
Before buying actions in Nvidia, consider this:
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Randi Zuckerberg, former Director of Development of the Facebook and Sister of the CEO of Meta Platforms, Mark Zuckerberg, is a member of the board of directors of Motley Fool’s. Geoffrey Seiler has no position in any of the actions mentioned. The Motley Fool has positions and recommends advanced micro-apparently, meta-platforms and Nvidia. The Motley Fool has a policy of disclosure.
3 reasons to buy NVIDIA actions as if there was no tomorrow published by the Motley Fool
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