How Nvidia Is Leading Other Chipmakers Amid The Emergence Of ChatGPT

With the emergence of ChatGPT, the technology industry has shifted its focus towards Artificial Intelligence (AI). Today, ChatGPT is being used widely in writing scripts, coding, and even making portfolios. This would not have been possible without some powerful computers and semiconductors.

But one semiconductor company has been at the centre of the AI bonanza, California-based Nvidia. Since its quarterly results were announced, the shares have been on a bull run. On Thursday alone, they surged around 25 per cent.

Founded in 1993 in California, USA, Nvidia is a multinational tech company that makes computer chips with the primary aim of making graphics better for gaming and other applications. Jansen Huang, one of the company's co-founders, has been its chief executive officer (CEO) since April 1993.

In 1999, the company started developing graphics processing units (GPUs) for computers to improve image display.

A research by Stanford University surfaced in 2006 stating that GPUs can accelerate maths operations in a way that regular processing chips could not.

Soon, Nvidia started investing in tools to make GPUs programmable and opening up the capability of these chips to perform beyond graphics. This new tool was installed in Nvidia's chips. The gamers had no particular use of this capability, but soon other programmers started developing new programmes.

In 2012, an AI tool that could classify images, Alexnet, was launched. It was trained using just two Nvidia chips. This started a new revolution in image processing.

For a decade, several high-quality tools for image processing were unveiled.

In 2021, an AI start-up, Metaphysic, was launched and quickly became popular for creating photorealistic videos of celebrities. The company said that it used Nvidia chips to both train and run the tool.

In November last year, the launch of ChatGPT shook up the tech world. What earlier seemed to be at least a decade later was now easily accessible and evolving fast. Major tech companies, including Microsoft and Google, make quick moves to make full use of the situation.

Nvidia, however, was at the heart of the revolution.

According to a report by BBC, ChatGPT was trained using 10,000 GPUs of Nvidia, clustered together in a Microsoft computer. As per a report by CB Insights, Nvidia has around 95 per cent of the GPU market for machine learning.

In its financial results, Nvidia announced that it is raising its production to meet the "surging demand".

One expert quoted in the BBC report said, "What Nvidia is to AI is almost like what Intel was to PCs."

Investors have responded positively to the company's announcement, and it seems to be having a good time on the bourses.

Other tech giants not far behind

There are a few semiconductor companies that can provide some competition to Nvidia. AMD and Intel can also make dedicated GPUs for AI applications, the BBC report said.

Google uses its tensor processing units (TPUs) for search results and also for certain machine-learning tasks. Amazon, on the other hand, has a custom-built chip for training AI models.