Everything on Operational Integration

Machine learning for material processing and manufacturing is currently undeveloped, despite processing playing a critical role in device-scale performance.

Impact: Expanding ML scope to include processing parameters bridges the gap between material design and commercial viability, addressing the 'bits-to-atoms' bottleneck.

— from AI in Materials Science: Discovery, Data Gaps, and Active Learning · Latent Space: The AI Engineer Podcast· Mar 24, 2026