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SUMMARY:Reconciling Deep Learning with Symbolic AI
DESCRIPTION:Speaker Biography\nMurray Shanahan is a senior research scienti
 st at DeepMind and Professor of Cognitive Robotics at Imperial College Lon
 don. Educated at Imperial College (BSc(Eng) computer science) and Cambridg
 e University (King’s College\; PhD computer science)\, he became a full 
 professor at Imperial in 2006\, and joined DeepMind in 2017. His publicati
 ons span artificial intelligence\, robotics\, machine learning\, logic\, d
 ynamical systems\, computational neuroscience\, and philosophy of mind. He
  is active in public engagement\, and was scientific advisor on the film E
 x Machina. He has written several books\, including “Embodiment and the 
 Inner Life” (2010) and “The Technological Singularity” (2015).\n \n
 Talk Abstract\nIn spite of its undeniable effectiveness\, conventional dee
 p learning architectures have a number of limitations\, such as data ineff
 iciency\, brittleness\, and lack of interpretability. One way to address t
 hese limitations is to import a central idea from symbolic AI\, namely the
  use of compositional representations based on objects and relations. In t
 his talk I will discuss neural network architectures that learn to acquir
 e and exploit relational information\, which are a step in this direction\
 , and will present recent work carried out at DeepMind on learning explici
 tly relational representations.\n 
URL:https://www.imperial.ac.uk/events/96895/reconciling-deep-learning-with-
 symbolic-ai/
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LOCATION:United Kingdom
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