How Nvidia Chips are Dominating the AI Market?

There’s no other firm that has benefitted from the AI boom as much as Nvidia. This is clearly visible from its blistering stock rally, which has made it one of the world’s three most valuable companies. Since January 2023, the company’s share price has increased by almost 450%. The reason behind the increasing prominence of Nvidia remains the semiconductors and subcontractors made by the company.?

With increasing interest in AI, Nvidia remains a leading supplier in the AI industry. The company's revenue continues to grow, and there is strong demand for its Hopper chip series and its upcoming successor, Blackwell.

However, Nvidia's future success depends on whether industry giants Microsoft and Google can find enough ways to use AI from their enormous investments in Nvidia chips. At the same time, antitrust authorities are investigating Nvidia's strong market position to see if it is making it difficult for customers to switch to other suppliers.

Nvidia's stock has recovered from its low point in August. Experts predict that the company's revenue will more than double this year, similar to the growth seen in 2023. Unless there is an unexpected drop in share prices, Nvidia is set to become the world's most valuable chipmaker by a large margin.

Let’s discover what’s fueling Nvidia's impressive growth and dominance in the AI market.?

Nvidia AI Chips Taking the Lead

Nvidia's AI chips, also known as Graphics Processing Units (GPUs) or AI Accelerators, have been a crucial piece of technology fueling the AI revolution. The current top performer is the Hopper H100, named after computer science pioneer Grace Hopper. This powerful GPU, originally designed for enhancing video game graphics, is now being replaced by the Blackwell series, named after mathematician David Blackwell.

The Hopper and Blackwell chips can combine multiple Nvidia chips into single units, allowing them to handle large amounts of data and perform fast computations. This makes them ideal for training the neural networks that power modern AI technologies.

Nvidia, founded in 1993, has been a leader in this field, investing in parallel processing technology for nearly 20 years. Based in California, the company will offer the Blackwell chips in various configurations, including the GB200 super chip, which pairs two Blackwell GPUs with one Grace CPU, a general-processing central processing unit.        

What’s So Special About Nvidia Chips?

If you are tech-savvy and interested in the field of AI, you probably know how AI works. If not? Here’s how - Generative AI platforms, like those used for translating text, summarizing reports, and creating images, learn by processing large amounts of existing data. The more data they analyze, the better they become at tasks such as understanding human speech or writing job cover letters. These platforms improve through trial and error, making billions of attempts to get things right, which requires a lot of computing power.

According to Nvidia, their new Blackwell chip is 2.5 times more efficient than the Hopper chip in training AI. The Blackwell chip has so many tiny switches, called transistors, that it can't be made using traditional methods. Instead, it's made up of two chips connected in a way that makes them work together as one.

The advanced performance of the Hopper and Blackwell chips is very important for companies looking to train their AI systems to perform new tasks. These chips are so crucial for AI development that the US government has restricted their sale to China.

Nvidia’s Journey from Gaming, Graphics to Artificial Intelligence?

Nvidia has been a leading name in graphics chip development, which creates the images you see on your computer screen. The most advanced chips have thousands of processing cores that can handle many tasks at once, such as creating detailed 3D images with shadows and reflections.

In the early 2000s, Nvidia's engineers found new uses for these graphics chips. At the same time, AI researchers realized that these chips could make their work more practical.?

According to IDC, a market research firm, Nvidia controls about 90% of the market for data center GPUs today. Major cloud computing companies like Amazon's AWS, Google's Cloud, and Microsoft's Azure are trying to create their own chips. Nvidia's competitors, AMD and Intel, are also working on their own versions.

Despite these efforts, Nvidia remains dominant. AMD expects to make up to $4.5 billion in AI accelerator sales this year, which is a big increase from almost nothing in 2023. However, this is still small compared to the over $100 billion Nvidia is expected to make in data center sales this year, according to analysts.

Nvidia’s Upper Hand Over Its Competitors

Not just with products, Nvidia has been a pioneer in updating its software at a rapid pace. They have also created cluster systems that allow customers to buy H100s in large quantities and set them up quickly. While Intel’s Xeon processors can handle more complex data tasks, they have fewer cores and are slower at processing the large amounts of data needed for training AI software. Intel, once a leading provider of data center components, has struggled to offer accelerators that customers prefer over Nvidia's products.

Nvidia's CEO, Jensen Huang, mentioned that customers are frustrated because they can't get enough chips. He said, "The demand is so high, and everyone wants to be first and the best," during a technology conference in San Francisco on September 11. "We probably have more emotional customers today. It's understandable. It's tense. We're trying our best."

Huang also noted that the demand for current products is strong, and orders for the new Blackwell range are coming in as supply improves. When asked if the large AI spending is giving customers a return on investment, he said that companies have no choice but to adopt "accelerated computing."

AMD vs Intel vs Nvidia AI Chips

AMD, the second-largest maker of computer graphics chips, introduced a new version of its Instinct line last year to compete with Nvidia's products.?

At the Computex show in Taiwan in early June, AMD CEO Lisa Su announced that an updated version of their MI300 AI processor would be available in the fourth quarter. She also mentioned that more products would be released in 2025 and 2026, showing AMD's dedication to this market.

Both AMD and Intel, which are also creating chips for AI tasks, claim that their latest products perform well compared to Nvidia's H100 and its upcoming H200 in some cases. However, Nvidia's competitors haven't yet matched the significant advancements that Nvidia's new Blackwell chip is expected to bring.?

Nvidia's strength isn't just in its hardware performance. The company created CUDA, a programming language for its graphics chips, which is widely used for AI applications. This software tool has helped keep the industry reliant on Nvidia's hardware.

What’s About the Antitrust Probe Against Nvidia?

Nvidia's increasing influence in the industry has caught the attention of regulators. The US Justice Department has sent requests for information to Nvidia and other companies, looking for evidence of potential antitrust violations.?

Although Nvidia denied receiving a subpoena, the DOJ often uses civil investigative demands, which are similar to subpoenas, to gather information. The Justice Department is particularly interested in Nvidia's acquisition of RunAI and certain aspects of its chip business.?

Nvidia maintains that its leading position in the AI accelerator market is due to the quality of its products and the fact that customers have the freedom to choose.

The Future of Nvidia AI Chips

The most awaited release is Nvidia's Blackwell series. Nvidia expects to earn a lot from this new product line this year. However, they have faced some engineering problems that will delay the release of some products.

At the same time, the demand for their H series hardware keeps growing. Nvidia's CEO, Jensen Huang, has been promoting the technology, encouraging both governments and private companies to buy early. He warns that those who don't adopt AI soon might fall behind. Nvidia also knows that once customers start using their technology for AI projects, it will be easier to sell upgrades to them compared to their competitors.