There are 2 main approaches to AI (symbolic vs connectionism), and they are very different in how they think about producing intelligence in the machine. One approach believes in programming what we know about the world into the machine, and the other ignores any pre-existing knowledge by relying on large datasets and correlation.There is a long-standing debate between which approach is best, despite only one of these approaches having much success. The reason this debase still exists is because it gets to the heart of a deeper discussion on the role knowledge plays in intelligence. In this episode I use the AI debate to uncover what I believe is a deeper problem in how people think about learning, and relate this to implications for our everyday lives.Support the showBecome a premium member to gain access to premium content, including the Techniques and Mindsets Videos, visual concept summaries of each episode, community forum, episode summary notes, episode transcripts, q&a/ama sessions, episode search, watch history, watch progress and support.Join Now at nontrivialpodcast.com or patreon.com/8431143/join

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