The explosion of ChatGPT can help a semiconductor giant earn 11 billion USD per year

Over the past 25 years, Nvidia has been leading the computer graphics revolution, becoming a brand loved by gamers throughout the company’s development. Nvidia has dominated the graphics processing unit (GPU) market since 1999 with the GeForce 256. The gaming business brought in more than $9 billion in revenue for Nvidia in 2022 despite the difficult economic situation.

However, CNBC said that Nvidia’s recent revenue has become a new phenomenon in the GPU business. This technology is now at the heart of the explosive growth of artificial intelligence.

Nvidia CEO Jensen Huang told CNBC in an interview in February: “ We were very wise to bet on this sector. We realized early on about a decade ago that this way of doing software could change everything. And we changed, every chip that is made has to focus on artificial intelligence .”

While Microsoft and Google are competing in bringing advanced artificial intelligence models to search engines. billion-dollar startups like OpenAI or Stability AI constantly announce AI software with many special features. Powering these pieces of software is a $10,000 chip, one of the most important tools in the artificial intelligence industry: the Nvidia A100.

Currently, rival companies of ChatGPT have a lot of announcements about how many of these $10,000 chips they use. Microsoft says the supercomputer developed for OpenAI used 10,000 A100 chips to train natural language models, each of which costs between $10,000 and $15,000.

Hundreds of GPUs are required to train artificial intelligence models, such as large language models. The chips need to be powerful enough to process terabytes of data quickly in order to recognize patterns. Then, GPUs like the A100 also need “inference” to generate text, make predictions, or identify objects correctly.

“ It’s easy to use their products,” said Vivek Arya, semiconductor analyst at Bank of America Securities. This is the ‘gold mine’ of Silicon Valley, and Nvidia is already ahead of the competition .”

According to the Nvidia CEO, Nvidia’s GPUs allow startups to train models at a much lower cost than if they were using a traditional computer processor. “ Now you can build something like a big language model, like ChatGPT, for about $10-20 million. This price is really very reasonable ,” shared CEO Huang.

Market research firm TrendForce said that AI training models like GPT will flourish and need a large amount of graphics hardware to meet the demand. Initial estimates, the GPT model needs up to 20,000 graphics cards to train and this number could go up to 30,000.

According to Nvidia’s Q4/2022 revenue report, the AI ​​chip segment grew 11% to $3.6 billion. Thanks to that, the company’s shares also increased by 65%, surpassing many businesses in the semiconductor sector. Citigroup’s report forecasts that the rapid growth from ChatGPT usage could bring in revenue of $3-11 billion for Nvidia in a year.

Currently, Nvidia is among the 10 most valuable technology companies in the world, with a market capitalization of nearly $600 billion. Nvidia is also one of the few Silicon Valley giants whose founder has remained at the helm for 30 years.

Nvidia initially focused on making computer chips to create graphics for video games. They have become the dominant player in powering artificial intelligence applications, from self-driving cars to robots to cryptocurrency mining.

Thanks to that experience, Nvidia stock has become one of Wall Street’s top bets. Investors are excited about how to profit from excitement about the future of AI. This trend was further accelerated when Microsoft Corp committed to invest $ 10 billion in OpenAI, the company that developed ChatGPT.

” ChatGPT has started a race in the tech industry, and Nvidia has left the competition too far behind ,” said Christopher Rolland, senior analyst at Susquehanna Investment Group.

Reference: CBNC