This podcast is basically a remix of the first and second episodes of Learning Machines 101 and is intended to serve as the new introduction to the Learning Machines 101 podcast series. The search for common organizing principles which could support the foundations of machine learning and artificial intelligence is discussed and the concept of the Big Artificial Intelligence Magic Show is introduced. At the end of the podcast, the book After Digital: Computation as Done by Brains and Machines by Professor James A. Anderson is briefly reviewed. For more information, please visit: www.learningmachines101.com
LM101-006: How to Interpret Turing Test Results
LM101-005: How to Decide if a Machine is Artificially Intelligent (The Turing Test)
LM101-004: Can computers think? A mathematician.s response
LM101-003: How to Represent Knowledge using Logical Rules
LM101-002: How to Build a Machine that Learns to Play Checkers
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