Topusko AI Data Center – One Gigawatt of Silicon and the Future of Computing
Inside the proposed 1 GW campus, the five questions a gigawatt AI factory has to answer, and the photonic, analog, fluidic, chemical, neuromorphic and quantum machines that might one day make a building this large unnecessary.
The provided text examines the severe energy and thermal bottlenecks facing modern artificial intelligence infrastructure, particularly driven by massive gigawatt-scale silicon data centers like the planned Pantheon facility in Croatia. It explores various post-silicon computing paradigms—including photonic, analog in-memory, neuromorphic, fluidic, chemical, and quantum architectures—that offer drastically lower energy consumption by processing information natively outside traditional electronic frameworks. Despite their theoretical efficiencies, these alternative substrates face significant obstacles such as precision scaling limits and software ecosystem inertia, notably the dominance of NVIDIA's CUDA platform. Consequently, while the industry continues to deploy brute-force complementary metal-oxide-semiconductor (CMOS) hardware to meet immediate demands, it is increasingly forced to consider hybrid architectures that combine digital processing with optical transport and analog calculation.
