Although Nvidia’s powerful processors are selling in huge quantities to the cryptocurrency sector, the US chipmaker has stated that cryptocurrencies do not offer any useful contribution to society.
Michael Kagan, the company’s chief technology officer, has claimed that processing power could be better utilized for more meaningful purposes, such as artificial intelligence chatbot ChatGPT.
Nvidia has never fully embraced the crypto community and even went as far as releasing software in 2021 that limited the ability to use its graphics cards for mining the popular Ethereum cryptocurrency.
The move was made to prioritize the supply of graphics cards for its preferred customers, such as AI researchers and gamers. Kagan defended the decision, stating that the limited value of mining cryptocurrencies justified the move.
The initial version of ChatGPT was trained on a supercomputer that consisted of approximately 10,000 Nvidia graphics cards.
According to Kagan, the popularity of using Nvidia’s graphics cards for parallel processing in the cryptocurrency sector was due to the company’s superior technology. However, the cryptocurrency industry eventually collapsed, as it was not seen as a useful contribution to society compared to artificial intelligence.
Kagan explained that ChatGPT allows anyone to create their own machine and program it according to their needs. If it doesn’t work as intended, the user can simply tell it to do something different.
In contrast, the cryptocurrency industry was more akin to high-frequency trading, which was a profitable business for Mellanox, the company that Kagan founded before it was acquired by Nvidia.
I never believed that [crypto] is something that will do something good for humanity. You know, people do crazy things, but they buy your stuff, you sell them stuff. But you don’t redirect the company to support whatever it is.
Initially recognized for its high-performance graphics cards designed for PC gaming, Nvidia’s products inadvertently became an integral component of the AI revolution.
It was discovered that the computationally intensive process of training new AI systems, which could cost millions or even billions of dollars in computing power, could be completed much more efficiently on the simple yet powerful graphical processors utilized by gamers. As a result, Nvidia’s products were perfectly positioned to meet the demands of the AI industry.