• Samuel Aby

Nvidia's potential Is Immense Through The Arrival of 2 New Data Center Types

Updated: Jun 3

A new style of Datacenter is developing, one that requires high-performance CPUs to function 24 hours a day, seven days a week. Long-term investors will find appealing chances in technology during down markets.

During the first quarter, Nvidia (NVDA -1.88 percent) announced record data center sales (the three months ended May 1, 2022). Indeed, as AI becomes more practical and inexpensive, it is no longer considered cutting-edge technology. AI is being used in industries across the economy, and Nvidia is emerging as the leading platform for the trend. As a consequence, data centers are anticipated to continue to be the company's primary source of revenue in the future.

Because of Nvidia's business change, the company might see many more years of tremendous growth.

At the results conference, CEO Jensen Huang highlighted that two new data center kinds are developing, and that development of these AI computing units is just getting started.

The fast growth of a $10 billion-plus-per-year corporation

Every few years or so, a new hardware upgrade cycle begins as semiconductor technology improves computational power and energy efficiency. All physical infrastructure, including chips, has a limited lifespan. The wonderful thing about technological infrastructure (such as data centers that provide cloud computing services) is that when a corporation replaces outdated equipment, it also receives a performance boost.

A similar upgrading cycle is presently ongoing, triggered by the pandemic and a renewed focus on digital technologies following the world's brief lockdown in 2020. Nvidia has been developing new chips targeting the data center and AI spaces in order to maximize its profits from this upgrade cycle. Over the last few years, the firm has transformed from a high-end video game chip creator to an AI platform.

With Huang and company expecting data center revenue to climb sequentially every quarter for the remainder of the year, it looks that data centers will continue to be Nvidia's largest end market (data centers briefly overtook the gaming segment for a single quarter a couple of years ago before consumers went on a PC upgrade cycle of their own at the start of the pandemic). Video game sales have been outstanding in their own right over the last few years, but Nvidia has emerged as a formidable data center competitor.

It made as much money from data centers in just a few weeks last quarter as it did in the whole fiscal year of 2017. For the sake of comparison, the present hardware update cycle may continue to boost income. During the first quarter, Intel's "Data Center and AI Group" generated $6 billion in revenue. In other words, Nvidia has plenty of potential to eat into Intel's market share in this area.

It's More Than A Hardware Update Cycle

However, this isn't just a tale about data center renovations. Nvidia's AI research has aided the development of two new types of data centers (beyond the traditional use case as a cloud services computing unit). At the earnings conference, Huang explained:

"Over time, you're going to see even more types of [chip] configurations. And the reason for that has to do with a couple of very important new types of data centers that are emerging. And you're starting to see that now with fairly large installations, infrastructures with Nvidia [high-performance computing] and Nvidia AI. These are really AI factories where you're processing the data, refining the data, and turning that data into intelligence. These AI factories are essentially running one major workload and they're running at 24/7. Deep recommender systems is a good example of that...

And then on the other end, you're seeing data centers at the edge that are going to be robotics or autonomous data centers that are running 24/7. They are going to be running in factories and retail stores and warehouses, logistics warehouses, all over the world. "

The first of Huang's two new data center categories is "AI factories," which are designed to absorb huge volumes of data in order to train AI models (software systems that will later be used to make decisions, recommendations, or automate a process). We already engage with the products of these "factories," for example, when a website suggests goods we would want to buy. With the aid of Nvidia hardware, Facebook parent Meta Platforms revealed one of the world's most powerful AI factories earlier this year.

The second sort of modern data center is basically a robotic equipment operator. This might be a vehicle manufacturer's factory or a retailer's distribution center, which processes and ships client orders. The USPS began collaborating with Nvidia a few years ago to develop an AI platform to aid in the effective operation of the huge postal system. This is another instance of a robotics data center operating at the "network edge".

To summarize, Nvidia's AI hardware is assisting the company in gaining market share in the existing data center area. Nvidia, on the other hand, is helping to broaden the scope of the sector, placing its company in a unique position to shape its own future. It's difficult to estimate how much of a market opportunity Nvidia still has ahead of it, but based on the company's recent pace, AI data centers will be a huge thing by the end of this decade.

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