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SUMMARY:AI-Accelerated Organic Synthesis
DTSTART:20230525T173000
DTEND:20230525T203000
DTSTAMP:20260406T194606Z
UID:cbe75c036fb9dbc5df187da115929d3a4ecc6df414aa5b6d4fd0d145
CATEGORIES:Conferences - Seminars
DESCRIPTION:Professor Philippe Schwaller Laboratory of Artificial Chemical
  Intelligence (LIAC)\n AI-accelerated Organic Synthesis is an emerging 
 field that uses machine learning algorithms to improve the efficiency and 
 productivity of chemical synthesis. Modern machine learning models\, such 
 as large language models\, can capture the knowledge hidden in large chemi
 cal databases to rapidly design and discover new compounds\, predict the o
 utcome of reactions\, and help optimise chemical reactions. One of the key
  advantages of AI-accelerated organic synthesis is its ability to make vas
 t chemical data accessible and predict promising candidate synthesis paths
 \, potentially leading to breakthrough discoveries. Overall\, AI is poised
  to revolutionise the field of organic synthesis\, enabling faster and mor
 e efficient drug development\, catalysis\, and other applications.\n\nAGEN
 DA:\n17.30 Opening\n17.45 Lecture\n18.30 Aperitif\n\nREGISTRATION: bit.ly/
 3L7x5GU\n\n© 2023 EPFL\n
LOCATION:MA B1 11 https://plan.epfl.ch/?room==MA%20B1%2011 https://epfl.zo
 om.us/j/67791404669
STATUS:CONFIRMED
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