Brain Inspired

BI 007 Daniel Yamins: Infant AI and CNNs


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Mentioned in the show:

  • Dan’s Stanford Neuroscience and Artificial Intelligence Laboratory:
  • The 2 papers we discuss
    • Performance-optimized hierarchical models predict neural responses in higher visual cortex
    • Learning to Play with Intrinsically-Motivated Self-Aware Agents
    • ImageNet as one of the most important things to stimulate research in AI, developed by these folks.
    • Ventral visual stream (as opposed to the Dorsal stream).
    • Retinotopy
    • Convolutional neural networks were inspired by Kunihiko Fukushima’s Neocognitron
    • 2 modern of approaches to solve the ImageNet database:
      • Google’s NASNet architecture, with about 12 layers
      • Microsoft’s super deep ResNet.
      • Object permanence and some video examples
      • The distinction between the intrinsic motivation of Dan and colleagues’ AI agent and the reinforcement learning motivation of the OpenAI 5 team
        ...more
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        Brain InspiredBy Paul Middlebrooks

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