Researchers Propose Thermodynamic Computing Architecture That Could Dramatically Reduce AI Energy Use
Insider Brief Researchers proposed a transistor-based thermodynamic computing architecture that could rmatch GPU-based performance while consuming about 10,000 times less energy. The system uses probabilistic hardware, Boltzmann machines and denoising models to generate outputs by gradually turning random noise into structured data. The results are based on simulations and a tested random-number circuit, with scaling … Read more