Artificial ielligence is a word that many companies are associated with today, and each of them has found a way to coinue 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 developme of artificial ielligence. 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.
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 developmes happen? What makes Nvidia chips differe from other competitors? Stay with us to answer the questions.
Chip design and processing
Nvidia graphics processors, also known as “accelerators”, were originally designed for video game processing. Using parallel processing, these parts divide various calculations io 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.
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 ielligence 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 efficie 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 ielligence models.
Strengthening networks and data ceers
Nvidia's superiority is not only due to the production of powerful chips, but also the company's strategic focus on the developme of data networks and their ability to use the power of graphics processors, which makes Nvidia famous in the artificial ielligence industry.
With the developme of AI-based models, data ceers 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.
Powerful software platform
Another reason that has led to Nvidia's victory in the world of artificial ielligence 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.
Nvidia's rich profits from the artificial ielligence accelerator market, as well as the rapid growth of this market, have encouraged other companies to eer the field. Amazon and Alphabet (Google's pare company) are now building AI chips for their data ceers, and in December 2023, AMD unveiled a chip with a double advaage in some metrics compared to Nvidia's most powerful chip. Also, other startups also dream of having a business similar to Nvidia.
In general, providing the best hardware cannot be a guaraee 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.
