Is GenAI running out of chips?

The demand for the specialist chips that power generative AI models has sent prices through the roof and created a worldwide shortage. Competitors and governments are moving to close the gap, but lead times in the advanced chip segment are notoriously long.

The explosion of generative AI (GenAI) has caused a parallel demand for GPU chips, making Nvidia, the manufacturer, one of the most valuable companies in the world. However, it has also led to a global shortage of powerful chips.

We look at the efforts by other chipmakers and AI companies themselves to close the gap as well as government responses. How will this affect AI developments in the near future?

Why GenAI needs GPUs

Increasingly, chips make the world go around, but when it comes to natural language processing (NLP) or generating images, not just any chip will do. The graphic processing units (GPUs) developed to handle the rapid video streams of computer gaming turned out to be ideal for the massive parallel processing needed to train AI models. From specialist supplier to the gaming sector, Nvidia found itself thrust almost overnight into the role of sole supplier of silicon to the exploding GenAI revolution.

AI Multiple Research explains “the number of parameters (consequently the width and depth) of the neural networks and therefore the model size is increasing. To build better deep learning models and power generative AI applications, organizations require increased computing power and memory bandwidth.” And it’s no easy feat to develop one of these powerful and specialized chips. Even Intel had to shelve its efforts after three years of trying to develop a chip to compete with Nvidia’s V100 TensorCore technology. Eventually, they went back to the drawing board - more on that later.

For its part, Nvidia had a headstart on some of the other chip makers, putting it in a prime position for the GenAI revolution.

How Nvidia dominates

Back in the 1990s, Nvidia got its start in the gaming sector by making chips for Playstation and Xbox. These days, it also makes chips like Volta, Xavier, and Tesla, enabling everything from data centers to autonomous driving. Now, as GenAI takes off, NVIDIA has a head start on other chip developers, resulting in impressive results. In Q2 of 2023, the company reached $1 trillion valuation, claiming its spot at the top of the GPU market. Last month Forbes predicted that the stock price would exceed $1,000 per share, which it duly did.

At the heart of these skyrocketing prices is the equally meteoric rise in demand for Nvidia’s AI-focused chips, which Forbes put at 410% to $18.4 billion at the end of January. Big-name customers like Microsoft, Google, and Meta are all turning to Nvidia for their upcoming AI initiatives.

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