The chip developer released its second-quarter revenue forecast which came in 50% higher than market estimates, followed by a 28% increase in company shares.
The race to develop artificial intelligence (AI) continues as manufacturers around the world scramble to obtain the chips to power the technology.
On May 24, Nvidia, the company behind the chip hailed as one of the world’s most powerful semiconductors, released its second-quarter revenue forecast which came in at 50% above market expectations, according to a Reuters report.
Moreover, the company’s shares increased by nearly 28% with an all-time high stock price of $391.50. Nvidia’s stock market value topped $950 billion, pushing the company far ahead as the world’s most valuable chipmaker.
Other chip developers include Google, Intel Corp, Amazon and Apple.
Nvidia is poised for one of the biggest one-day pops in US history, with the promise of AI (and other factors) propelling its market capitalization to levels that rival Amazon. https://t.co/TmHBeD87an pic.twitter.com/FHWmBhO0wH
— Lisa Abramowicz (@lisaabramowicz1) May 25, 2023
Nvidia says it has been increasing its supply as a response to the escalating demand for its AI chips used for applications such as ChatGPT.
According to a follow-up report, Nvidia’s results sparked a rally for other AI-related companies which added an additional nearly $100 billion to the market.
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Along with Nvidia and other big tech companies, Microsoft recently said it is also in the process of developing its own AI chip to power AI applications for OpenAI, along with internal projects.
In April, Elon Musk, the CEO of SpaceX, Tesla and former CEO of Twitter, reportedly bought thousands of GPUs for an upcoming Twitter AI project, according to a source close to the matter.
On the other hand, in China, developers are finding ways to work around sanctions that ban the latest version of Nvidia chips from being obtained in the local market.
Chinese companies and developers are studying methods to develop AI, through weaker semiconductors and combinations of various chips as a solution.
While some experiments were said to be “promising,” developers currently only have access to chips that can only support small-scale AI models, such as the Nvidia chips A800 and H800.
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