Grading AI: The Hits and Misses

Grading AI: The Hits and Misses

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December 01, 2021

Murray Shanahan, professor of cognitive robotics at Imperial College London and a senior research scientist at DeepMind, joins Azeem Azhar to discuss AI: where developments have exceeded expectations, where they have fallen short, and what the next steps are towards an artificial general intelligence (AGI).

They explore the hurdles that stand in the way of truly intelligent computer programs: why an AGI might need to exist in a body that can sense the world around it to reach its full potential, whether we can teach computers common sense, and what it means for a self-driving car to “think.”

They also discuss:

  • What the future of AI may have in common with the aeronautical ingenuity of the Wright brothers.
  • The pros and cons of the various approaches to AI from symbolic models to convoluted neural networks, transformers, and generative models.
  • Why huge salaries for commercial deep learning engineers might actually hinder research.

@mpshanahan
@exponentialview
@Azeem

Further resources:

AI’s Competitive Advantage (Exponential View podcast, 2021)

How To Practice Responsible AI (Exponential View podcast, 2021)

‘Conscious exotica’ (Murray Shanahan, Aeon, 2016)

State of AI Report 2021 (Nathan Benaich and Ian Hogarth)

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