It is 2026 and artificial intelligence (AI) models are better than ever. Google recently released Gemini 3.1 Pro, its most-advanced model yet, which even outperforms Anthropic’s Claude Opus 4.6 in certain benchmarks. However, Google DeepMind CEO Demis Hassabis believes that this rapid growth could come to a standstill due to one factor – memory.
In recent weeks, we have heard chatter surrounding a memory shortage. AI data centres need thousands of GPUs and computing power to run AI models. This has created a shortage in supply which is skyrocketing prices of various electronics, including smartphones.
Demis Hassabis says AI could reach a choke point
Hassabis raised concerns that this shortage in supply of memory chips could become a major bottleneck for AI progress. He told CNBC, “You need a lot of chips to be able to experiment on new ideas at a big enough scale that you can actually see if they’re going to work.” The Google DeepMind chief described this to be a potential “choke point.”
Previously Meta CEO Mark Zuckerberg has stated that AI researchers want “the most chips possible.”
At a time when AI companies are pursuing ever-larger models and greater computational power, the constraints on memory chip supply are creating significant headwinds for the industry as a whole.
Google is also prone to this shortage
Google manufactures its own Tensor Processing Units (TPUs) and has the advantage of proprietary chip design, which helps reduce its reliance on third-party suppliers such as Nvidia. However, Hassabis emphasized that the company also faced an issue. He said, “It still, in the end, actually comes down to a few suppliers of a few key components.”
Demis Hassabis even claimed that Google was constrained to a point where it could not actually meet the demand for its Gemini models.
This memory crunch has forced companies like Google and Microsoft to send executives to South Korea in an effort to secure more supply. The world has three major players in memory chip production – Samsung, Micron, and SK Hynix. Micron has announced plans to shut down its production of chips for personal electronics to focus on AI chip production.
Industry forecasts suggest that the chip shortage is unlikely to ease soon. Google recently disclosed plans for significant capital expenditure on AI infrastructure, projecting $175 billion to $185 billion in spending for 2026, as it prepares for more growth in this sector.
