Machine-learning system based on light could yield more powerful, efficient large language models

MIT system demonstrates greater than 100-fold improvement in energy efficiency and a 25-fold improvement in compute density compared with current systems. The current work is the latest achievement in a drumbeat of progress over the last few years by Englund and many of the same colleagues. For example, in 2019 an Englund team reported the theoretical work that led to the current demonstration. The first author of that paper, Ryan Hamerly, now of RLE and NTT Research Inc., is also an author of the current paper. Machine-learning system based on light could yield more powerful, efficient large language models | MIT News | Massachusetts Institute of Technology