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Brain simulation

1
episodes
1
thinkers
2h
of conversation
11
books & papers
3
terms defined

The neighbourhood: brain simulation and the ideas it travels with. Drag to roam, click a star for the episode, click a neighbour to travel.

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The lexicon

Every term the guests lean on, in plain language. Read one in full, or filter to find it.

    What the corpus says

    The throughline across every conversation that touches this idea.

    Dilip George criticizes the Blue Brain project for simulating brain structures without understanding their functions, limiting its effectiveness.
    The Recursive Cortical Network (RCN) model achieved 95% accuracy on MNIST with minimal data, highlighting the power of feedback connections and recursive inference.
    Convolutional neural networks (CNNs) differ from the brain's visual cortex, which lacks translation invariance and relies on local receptive fields.
    GPT-3's lack of world models and feedback mechanisms limits its potential for achieving AGI, despite its 175 billion parameters.
    Connecting brains to machines could lead to intense experiences due to neuroplasticity and the brain's adaptation to new inputs.

    Voices on brain simulation

    5 standout quotes from across the corpus.

    Go read

    11 books and papers cited across these episodes.

    For the specialist

    What experts find new

    3 expert-level takeaways for a specialist reader.

    At the frontier

    Still unresolved

    2 open questions flagged across these conversations.

    The thinkers

    Who takes this idea on, by how often they return to it.

    All guests

    Adjacent ideas