Why does Nvidia dominate the AI ​​chip market?

Artificial intelligence is a word that many companies are associated with today, and each of them has found a way to continue and survive in providing new technologies and tools in this sector. Nvidia is one of these companies that, according to the general opinion of experts, owes its prosperity and the increase in the value of its shares to the development of artificial intelligence. Since January 2023, the stock value of this company has increased by about 450% and with its market value exceeding 2 trillion dollars, it holds the third place after Microsoft and Apple. Also, Nvidia's revenue in the last quarter was 22 billion dollars, which has experienced an increase of 6 billion dollars compared to the same period last year.

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Nvidia now owns more than 95% of the AI ​​chip market, and analysts have reported the possibility of this multinational company completely dominating such a market. But how did all these developments happen? What makes Nvidia chips different from other competitors? Stay with us to answer the questions.

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Chip design and processing

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Nvidia graphics processors, also known as “accelerators”, were originally designed for video game processing. Using parallel processing, these parts divide various calculations into smaller parts and then distribute them between the chip cores, bringing faster calculations and easier multitasking to users. Such an approach was ideal for running games, and now Nvidia chips are able to process 80% of game graphics.

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But the world of this company's chips became wider day by day and now they are used in various fields such as digital currency mining, self-driving cars, training artificial intelligence models and machine learning algorithms as the basis of AI. As we said, what sets Nvidia chips apart is their design, which, with the benefit of multiple cores, can give you fast multitasking processing and running heavy programs. Realizing that its chips were very efficient at training AI models, Nvidia focused on optimizing them and bringing them to market. In the decade leading up to 2023, this trend led to a 1,000-fold increase in chip processing speed, and Nvidia processors were able to keep up with more complex artificial intelligence models.

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Strengthening networks and data centers

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Nvidia's superiority is not only due to the production of powerful chips, but also the company's strategic focus on the development of data networks and their ability to use the power of graphics processors, which makes Nvidia famous in the artificial intelligence industry.

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With the development of AI-based models, data centers also need multiple processors to manage them and increase their performance. Unlike most systems that use few GPUs, Nvidia markets its multiple chips with networking based on products from Mellanox, a networking technology supplier that was acquired by Nvidia in 2019. By doing this, the network performance of Nvidia chips was optimized in a way that other manufacturers could not compete with.

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Powerful software platform

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Another reason that has led to Nvidia's victory in the world of artificial intelligence is Cuda, the company's software platform that allows customers to adjust the performance of processors. Nvidia has invested in the platform since the mid-2000s and has long encouraged developers to use it to test and design AI-based applications.

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Nvidia's rich profits from the artificial intelligence accelerator market, as well as the rapid growth of this market, have encouraged other companies to enter the field. Amazon and Alphabet (Google's parent company) are now building AI chips for their data centers, and in December 2023, AMD unveiled a chip with a double advantage in some metrics compared to Nvidia's most powerful chip. Also, other startups also dream of having a business similar to Nvidia.

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In general, providing the best hardware cannot be a guarantee of excellence. Nvidia was able to succeed in the market of AI-based chips because of this, because the best Network kit And Software platform on the side Powerful chips Offers. So if a company like AMD is looking to beat Nvidia in this almost one-sided competition, it needs to be able to perform as well as possible in all three areas above.

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