Small reactors, big problems: the nuclear mirage behind AI's energy hype (medium.com)

The article pushes back on a rising narrative that small modular nuclear reactors (SMRs) are the ideal, zero‑carbon power source for fast‑growing AI infrastructure. While SMRs are marketed as “safe,” modular, and quick to deploy for data centers and networks, the piece argues those claims don’t withstand scrutiny: a reactor—no matter the size—relies on fissile materials, high temperatures and complex cooling and containment systems, so multiplying installations multiplies safety, security and operational risk vectors. Historically, modular nuclear projects have faced runaway costs, difficult engineering, supply‑chain and scaling problems, and long lead times that undercut the “rapid deployment” case. For the AI/ML community the implications are practical and policy‑level. SMRs currently can’t economically or logistically outcompete mature renewables plus storage, and they introduce regulatory, siting and safety constraints that complicate rapid data‑center expansion. The debate is also shaped by political and financial incentives that sometimes favor nuclear over renewables, not purely technical merit. The takeaway: planners should subject SMR proposals to rigorous cost, risk and timeline analysis, prioritize proven low‑carbon mixes (wind/solar + storage and efficiency), and treat nuclear as one contested option rather than a turnkey solution for AI’s power needs.