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SUMMARY:Large Language Models and Graph Neural Networks for Intelligent Ma
 nufacturing Systems - Fan Mo\, University of Cambridge
DTSTART:20250924T120000Z
DTEND:20250924T130000Z
UID:TALK235645@talks.cam.ac.uk
CONTACT:Pietro Lio
DESCRIPTION:Artificial intelligence is moving beyond domain-specific tasks
  toward systems that integrate perception\, reasoning\, and action across 
 modalities. In this talk\, I present recent work on hybrid AI frameworks t
 hat combine graph neural networks\, knowledge graphs\, and large language 
 models to strengthen reasoning and interpretability. Building on these fou
 ndations\, I will discuss advances in multi-modal fusion and embodied inte
 lligence\, with case studies in robotics and manufacturing\, including dec
 ision-making for reconfigurable systems and runtime adaptability. These re
 sults demonstrate how combining symbolic structure with neural flexibility
  enables more autonomous and resilient AI for complex industrial environme
 nts.
LOCATION:Zoom (Meeting ID: 360 910 4394\, Passcode: P5F18G)\, Computer Lab
 oratory\, William Gates Building\, Room SS03.
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