AI-Accelerated Organic Chemistry

  • TH Department Seminar
  • Datum: 14.07.2023
  • Uhrzeit: 11:00
  • Vortragende(r): Prof. Philippe Schwaller
  • Laboratory of Artificial Chemical Intelligence (LIAC), Institute of Chemistry and Chemical Engineering at Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
  • Ort: https://zoom.us/j/99592653591?pwd=ajhiV2s1a1hGOWdlblViZlV0MUNjQT09
  • Raum: Meeting ID: 995 9265 3591 | Passcode: 282379
  • Gastgeber: TH Department
AI-Accelerated Organic Chemistry
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 chemical databases to rapidly design and discover new compounds, predict the outcome of reactions, and help optimise chemical reactions. One of
the key advantages of AI-accelerated organic synthesis is its ability to make vast 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 more efficient drug development, catalysis, and other applications.

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