The Padverb Podcast with KMO

016 Differential Outcomes with James Fodor


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James Fodor is a science podcaster, an essayist, and currently, a PhD candidate in computational neuroscience and computational linguistics at the University of Melbourne (Australia). His intellectual and research interests cover such diverse areas as cognitive science, computer science, philosophy, theology, and economics.

In this conversation, KMO and James discuss:

  • 02:07 – A brief history of "The Science of Everything"
  • 10:08 – How neural networks learn vs how humans learn
  • 12:52 – The uncomfortable question of back-propagation
  • 16:00 – Acquiring language and concepts
  • 19:52 – Why and when machines' way of learning is important
  • 23:22 – Illogical language models and the Internet lurking behind
  • 25:52 – Conversation starters and GPT's talking to one another
  • 27:45 – Modeling the mind vs the "just a neural network" cop-out
  • 33:08 – A space of possible minds and complementing human intelligence
  • 36:50 – Idiot chat bots and fearing AI
  • 38:15 – The near-term future of AI
  • 41:38 – Predicting the prosperity of nations

  • James Fodor:

    • The Science of Everything Podcast : fods12.podbean.com
    • The Godless Theist Blog: thegodlesstheist.com
    • James on YouTube: youtube.com/c/JamesFodor/

    • KMO:

      • Twitter: @Kayemmo
      • en.padverb.com/kmo

      • Padverb:

        • The Padverb Telegram Channel:
        • t.me/padverbpodcast

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          The Padverb Podcast with KMOBy Padverb