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SUMMARY:AI for Materials Discovery in Practice: Effect of low data on RL a
 pproaches - Joonatan Laulainen (Altrove)
DTSTART:20260320T153000Z
DTEND:20260320T163000Z
UID:TALK244495@talks.cam.ac.uk
DESCRIPTION:Novel materials have enabled industries and technologies: LEDs
 \, electric motors and batteries. Their development is glacially slow\, of
 ten taking decades. How do we speed up materials discovery using ML and AI
  tools. This talk will break down the extreme data challenges of materials
  discovery. How do we best gain information from 10 or less data points? H
 ow do we do that efficiently while accepting that science operates in an e
 xceptionally complex and high-dimensional space? How do we take the correc
 t sequence of decisions that maximise the synthesis outcome for a novel ma
 terial? How do we bring as much of this complexity 'in-distribution'? The 
 talk will discuss both traditional ML\, LLM-based\, and mixed approaches w
 ith a holistic view on materials discovery.
LOCATION:Seminar Room 1\, Newton Institute
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