Simulating large-scale quantum computers has become more difficult as the quality of quantum processing units (QPUs) improves. Validating the results is key to ensure that after the devices scale…

The Hao AI Lab research team at the University of California San Diego recently received an NVIDIA DGX B200 system to elevate their work in LLM inference.

Quantum computing devices of increasing complexity are becoming more and more reliant on automatised tools for design, optimization and operation. In this Review, the authors discuss recent developments in “AI for quantum", from hardware design and control, to circuit compiling, quantum error correction and postprocessing, and discuss future potential of quantum accelerated supercomputing, where AI, HPC, and quantum technologies converge.