Artificial Intelligence and its subsets like machine learning are driving the latest technologies like the best LLMs and creating power demands that current infrastructure might not be able to keep up with. 

According to the International Energy Agency, electricity consumption from data centers could double by 2026. In 2022, data centers consumed approximately 460 TWh and is expected to reach 1,000 TWh in the next couple of years. The equivalent to the entire electrical energy consumption of Japan.

It is predicated that the limiting factor of AI advancement in the near future will not be processing power, but rather energy infrastructure. We spoke to Jay Jiang Yu on how to tackle this obstacle and why he believes the  future of AI will depend on nuclear energy.

INTERVIEW WITH:Jay Jiang Yu

Founder and Executive Chairman of Nano Nuclear Energy Inc

1. With the growth of data centers, when do you expect the tipping point to be when our current infrastructure cannot keep up with demand?

The tipping point may have been reached already. The systems which would need to be in place to meet the expected energy demand would need to commence their installation now, to ensure that the AI and data centers in 2-3 years had the power supply necessary to continue their upscaling and expansion. Currently the deficit in energy is expected to hit the tech centers sometime around 2026-2027, and currently no new system looks able to come online before those dates.