AI for science
proposedAI systems that propose, test and refine scientific hypotheses, designs and experiments well enough that their results are confirmed in the laboratory at a rate that speeds up discovery.
0 open gaps · not assessed
Overview / Domain
Artificial intelligence
Learning systems: their capability, reliability and the energy and data they consume.
Readiness on Technology readiness levelSDG: Industry, innovation and infrastructure
Moderators: none yet: volunteer
Running trained AI models to answer queries at a small fraction of today's energy per generated token, across the whole stack from the chip to the cooling plant, so that wider use of AI does not need proportionally more electricity.
Energy per token: 0.72 J now, target 0.07 J (1.0 orders of magnitude) · 5 open gaps · TRL 6 (6 of 9)