The stock prices of Nvidia, a well-known designer of computer chips, had a stunning rise this week, almost bringing the company’s valuation over the trillion-dollar threshold.
Nvidia’s market value has increased significantly by 24% to an astonishing $939.3 billion. This valuation is higher than Facebook’s $647.6 billion valuation and Tesla’s $584.7 billion valuation.
In terms of market value, Nvidia is currently one of the top firms, only being surpassed by tech behemoths like Apple, Google, Microsoft, Amazon, and Saudi Aramco, the Saudi Arabian state oil company.The announcement of Nvidia’s most recent quarterly results, which were made public in the latter half of Wednesday, was what precipitated this huge rise. In order to satisfy the rising market demand, the corporation disclosed its plans to increase chip production.
The market for chips used in artificial intelligence (AI) systems has seen Nvidia successfully consolidate its position as the market leader.
Following the public release of ChatGPT in November, the sector saw an unheard-of increase in enthusiasm that had an impact well beyond the boundaries of the technological sector.
As an AI tool that offers help with a variety of tasks, including speechwriting, computer programming, and even cooking, ChatGPT has become quite popular.
The basis for all of these accomplishments, however, is solid computer technology, with a focus on the cutting-edge processors created by Nvidia, a company with its headquarters in California.
Nvidia is now an essential part of the majority of AI applications, having previously been known for producing computer chips largely used for graphics processing, particularly in the field of computer gaming.
Nvidia’s graphics processing units (GPUs) were heavily utilised during ChatGPT training. In a Microsoft-owned supercomputer, specifically, about 10,000 of these GPUs were installed and grouped together.
One of many supercomputers constructed using Nvidia’s hardware, it is. Currently, the American chip manufacturer controls around 95% of the market for GPUs used in machine learning.
