Radical AI puts autonomous labs on materials science
Radical AI is using robots and AI to run iterative materials-science experiments with minimal human intervention between cycles.
AI is moving from analysing scientific data to deciding which physical experiments should happen next.
What happened
Radical AI is operating a self-driving laboratory where robots synthesise and test materials while AI analyses results and selects subsequent experiments. The company has raised more than $65 million cumulatively and is applying the system to areas including batteries, semiconductors and heat-resistant materials.
Why it matters
Materials discovery is traditionally slow because experiments are sequential and labour intensive. Automating the feedback loop between hypothesis, synthesis, testing and analysis could allow many more iterations in the same period.
The bigger picture
Autonomous laboratories are one of the most tangible forms of AI-driven science. If they work reliably, the impact could extend beyond software productivity into the pace at which new physical technologies are discovered.