SAN FRANCISCO —
The hottest thing in technology is an unprepossessing sliver of silicon closely related to the chips that power video game graphics. This is an artificial-intelligence chip that was designed to speed up and reduce the cost of building AI systems like ChatGPT.
Such chip have taken the center stage of what experts believe is an AI revolution which could change the entire technology industry and even the whole world. Shares of Nvidia, the leading designer of AI chips, rocketed up almost 25% last Thursday after the company forecast a huge jump in revenue that analysts said indicated soaring sales of its products. The company was briefly worth more than $1 trillion on Tuesday.
SO WHAT ARE AI CHIPS, ANYWAY?
That isn’t an easy question to answer. Hannah Dohmen is a researcher at the Center for Security and Emerging Technology. She said that there’s no consensus on what AI chips are.
In a broader sense, however, this term refers to computing hardware that is specialized for AI workloads, such as by ‘training’ AI systems on difficult problems which can overwhelm conventional computers.
VIDEO GAME ORIGINS
Three entrepreneurs founded Nvidia in 1993 to push the boundaries of computational graphics. In a matter of years, Nvidia had created a chip known as a graphics processor unit (GPU), which accelerated both the development and playing of video games. This was done by simultaneously performing complex graphics calculations.
This technique known as parallel processing would be key in the development of AI and games. Two graduate students at the University of Toronto used a GPU-based neural network to win a prestigious 2012 AI competition called ImageNet by identifying photo images at much lower error rates than competitors.
The win kick-started interest in AI-related parallel processing, opening a new business opportunity for Nvidia and its rivals while providing researchers powerful tools for exploring the frontiers of AI development.
MODERN AI CHIPS
Eleven years later, Nvidia is the dominant supplier of chips for building and updating AI systems. One of its recent products, the H100 GPU, packs in 80 billion transistors — about 13 million more than Apple’s latest high-end processor for its MacBook Pro laptop. Unsurprisingly, this technology isn’t cheap; at one online retailer, the H100 lists for $30,000.
Nvidia does not manufacture these GPU chips, as it would take a huge investment in new factories. Instead it relies on Asian chip foundries such as Taiwan Semiconductor Manufacturing Co. and Korea’s Samsung Electronics.
Cloud computing services like those offered by Amazon or Microsoft are some of the largest customers for AI chip technology. By renting out their AI computing power, those services make it possible for smaller companies and groups that couldn’t afford to build their own AI systems from scratch to use cloud-based tools to help with tasks that can range from drug discovery to customer management.
OTHER USES AND COMPETITION
Parallel processing has many uses outside of AI. In the past, Nvidia graphic cards were scarce because bitcoin miners had taken them all. They set up large banks of computers in order to solve complex mathematical problems. That problem faded as the cryptocurrency market collapsed in early 2022.
Analysts say Nvidia will inevitably face tougher competition. One potential rival is Advanced Micro Devices, which already faces off with Nvidia in the market for computer graphics chips. AMD has recently taken steps to bolster its own lineup of AI chips.
Nvidia is based in Santa Clara, California. Jensen Huang, the co-founder of Nvidia remains its president and CEO. The post AI chips are in vogue. Here’s what they are, what they’re for and why investors see gold appeared first on Associated Press.