The market value of semiconductor maker Nvidia is rising. What are AI chips and why do investors see gold in them?
The hottest thing in technology is an unreactive sliver of silicon closely related to the chips powering video game graphics.
It is an artificial intelligence (AI) chip specially designed to make AI systems like ChatGPT faster and cheaper.
Such chips have suddenly taken center stage in what some experts believe to be an AI revolution that could reshape the technology sector — and possibly the world along with it.
Shares of Nvidia, the leading designer of AI chips, soared nearly 25 percent last Thursday after the company forecast a huge jump in revenue that analysts said signaled a jump in sales of its products.
The company’s value briefly exceeded $1 trillion (€937 billion) on Tuesday.
What are AI Chips?
It is not an easy question to answer. “There really isn’t a fully agreed upon definition of AI chips,” said Hannah Dohmen, a research analyst at the Center for Security and Emerging Technology.
In general, however, the term encompasses computing hardware that is specialized to handle AI workloads—for example, “training” AI systems to tackle difficult problems that might choke traditional computers.
Three entrepreneurs founded Nvidia in 1993 to push the boundaries of computational graphics. Within a few years, the company had developed a new chip called the graphics processing unit, or GPU, which dramatically accelerated both the development and playing of video games by performing many complex graphics calculations at once.
That technology, formally known as parallel processing, would prove crucial to the development of both games and AI. Two graduate students from the University of Toronto used a GPU-based neural network to win a prestigious 2012 AI competition called ImageNet by identifying photo images at a much lower error rate than competitors.
The win jump-started interest in AI-related parallel processing, opening up a new business opportunity for Nvidia and its rivals, while providing researchers with powerful tools for exploring the limits of AI development.
Eleven years later, Nvidia is the leading supplier of chips for building and updating AI systems.
One of its recent products, the H100 GPU, is packed 80 billion transistors– About 13 crore more than Apple latest high end processors Its for macbook pro laptop. Unsurprisingly, this technology isn’t cheap; On one online retailer, the H100 is listed for $30,000 (€28,000).
Nvidia doesn’t make these complex GPU chips itself, a task that would require huge investments in new factories. Instead, it relies on Asian chip foundries such as Taiwan Semiconductor Manufacturing Co. and Korea’s Samsung Electronics.
Some of the biggest customers of AI chips are cloud-computing services such as those run by Amazon and Microsoft.
By renting out their AI computing power, these services make it possible for small companies and groups that want to use their own AI to use cloud-based tools to help with tasks ranging from drug discovery to customer management. Could not build the system. ,
What are Nvidia’s competitors?
Parallel processing has many uses outside of AI.
A few years ago, for example, Nvidia graphics cards were in short supply as cryptocurrency miners, who set up banks of computers to solve thorny mathematical problems for bitcoin rewards, snapped up most of them. The problem seems to have faded away with the collapse of the cryptocurrency market in early 2022.
Analysts say that Nvidia will inevitably face tough competition.
A potential rival is Advanced Micro Devices (AMD), which already has a market share with Nvidia for computer graphics chips. AMD has recently taken steps to bolster its lineup of AI chips.
Nvidia is based in Santa Clara, California. Co-founder Jensen Huang remains the company’s president and chief executive officer.
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