At the GTC conference, Nvidia(Nasdaq: NVDA) Gave investors 1 trillion potential reasons to buy his shares. That came in the form of CEO Jensen Huang, who projected that Datacenter infrastructure capital expenditure (Capex) would hit $ 1 trillion or more by 2028.
Investors nevertheless largely achieved the robust prediction and other cheerful news from the event. That said, when the projections of Nvidia flourish, the shares here have much more upside down.
$ 1 trillion at Datacenter infrastructure Capex By 2028 would be a continuous acceleration of spending in space, which would be great news for Nvidia. The graphic processing units (GPUs) of the company have become the backbone of the Buildout of Artificial Intelligence (AI), because of their powerful data processing options and ease of use.
In a graph of the presentation, NVIDIA 2024 Datacenter infrastructure expenditure estimated around $ 400 billion in 2024. For the past tax year (tax year 2025 ended in January), the company produced a total turnover of $ 130.5 billion, of which $ 115.2 billion was. In the meantime, research agency Dell’oro Group has just estimated that the expenditure for data center infrastructure 2024 reached $ 455 billion. This translates into Nvidia, which currently records around 25% to 30% of these expenses.
If Nvidia was able to retain its current share in these spending, it would translate into between $ 250 billion to $ 300 billion in data center infrastructure in 2028. The company is planning to continue to lead the way with both its chips and its software. It introduced the new Blackwell Ultra GPU during the event, which will be sent in the second half of this year. The new Blackwell chips are more powerful, making them great for more time-sensitive services. Nvidia predicted that Blackwell income would be much larger than the income it generated from his earlier Hopper architecture.
Continuing with its chip innovation, the company is also ready to introduce its new Vera Rubin chip, which will combine a GPU with its next generation of Rubin architecture and a tailor-made central processing unit (CPU), with the help of ArmTechnology. It said that the CPU will be twice as fast as the ready-made planned in his earlier Grace Blackwell chips. In the meantime, it will try to increase the number of GPU stuff in its current Blackwell -Chips from two to four with the “Rubin Next” chip that is planning to launch in the second half of 2027.
Nvidia does not only innovate on the hardware side. It also revealed a new open-source software system called Nvidia Dynamo that helps to increase the transit of the inference and lower costs. The company said that the new software will help with orchestrate and accelerate communication between thousands of GPUs. It said that Dynamo is not only an operating system for a data center, but for a whole AI factory.
However, Nvidia has not only arranged his sights on data centers. It also wants to tackle the robotics and autonomous riding markets. Huang stated that “the era of generalistic robotics is here” with the introduction of Isaac Groot N1, which he called the first “Open Humanoid Robot Foundation model in the world.” The model can be trained on real or synthetic data to help humanoid robots control tasks. The company thinks these robots will be able to fulfill jobs in the workforce and to help with a worldwide shortage of 50 million job.
The company will also work together General Motors To help the car maker to develop its own autonomous driving system. The move is somewhat surprising because GM deleted its earlier attempt at a robotaxi company last year. The unit was entangled in controversy when one of his cruise pants robotaxis dragged a pedestrian on the road after the person was originally hit by another vehicle.
Nvidia said that in addition to delivering GPU’s GM, it will help to build adapted AI systems. GM will also use NVIDIA GPUs and software to train AI production models to build factory robots of the next generation. This follows on Nvidia that closes a deal Toyota Last month to offer chips and software to perform its advanced driver-assistance functions.
Image source: Getty images.
Although Nvidia has been the biggest winner of the AI infrastructure building, it still has a very good chance. AI infrastructure expenditure is still increasing and Nvidia does not rest on its laurels. It continues to stimulate innovation and wants to ensure that it is the winner in AI insertion, not just AI training. In the meantime, it is looking for growth outside the data center in other large potential markets.
At the same time, the shares of Nvidia remain attractively appreciated after the recent sale of the market. The shares act at a forward price gain (p/e) ratio of less than 26 times the estimates of this year’s analysts and a price/profit growth (PEG) under 0.5. A pen of 1 is usually the threshold for a stock that is considered undervalued, and the multiple of Nvidia is far below this figure.
As such, Nvidia looks like a solid long -term purchase at these levels.
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Geoffrey Seiler has no position in one of the aforementioned shares. The Motley Fool has positions and recommends Nvidia. The Motley Fool recommends General Motors. The Motley Fool has a disclosure policy.
1 trillion reasons to now buy the shares of Nvidia, was originally published by the Motley Fool
