Kindred Ventures' Steve Jang estimates that demand for AI compute will reach 80–100GW by 2030, outpacing supply and leaving a gap of roughly 60GW. The comment reflects a growing view that securing power has become the biggest bottleneck for AI infrastructure as training and inference demand from generative AI and large language models surges.
Continue reading
The rest of this article is for AI News Blitz readers. Choose an option below to keep reading.
Already purchased? Sign in✓ Signed in — this article isn’t included in your current plan.