Radical AI Co-founder: Experimental Data is the Ground Truth for AI4Science
CatAstro_Piyush · x · 2026-08-07
Using material science as an example, Radical AI co-founder Josephfkrause explains the logic of applying AI in scientific research. He notes that what makes a material real and industrially relevant lies in the latter phases of discovery: characterization and synthesis.
To achieve this, it is crucial to build a closed-loop system like a Self Driving Lab: run experiments, capture data, and feed this experimental 'ground truth' back to the AI. This continuous loop enables the AI to accurately learn and predict materials relevant to industry.
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