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Large language models

2
episodes
2
thinkers
7h
of conversation
13
books & papers
5
terms defined

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

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From foundational to frontier

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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.

    The Piraha language lacks exact counting words, challenging assumptions about language universality.
    Dependency grammar emphasizes short dependencies between words, which simplifies language comprehension and production.
    Gibson argues that large language models excel at form but struggle with understanding meaning.
    Legalese complexity is largely due to center embedding, which significantly hinders comprehension.
    Gibson suggests that language evolution is driven more by ease of production than listener comprehension.
    Stephen Wolfram argues that ChatGPT's language generation is 'wide and shallow,' contrasting with Wolfram Alpha's deep computation.
    Wolfram posits that computational irreducibility limits predictability, even with complete knowledge of a system's rules.
    AI's potential to automate political manipulation and education personalization could reshape societal roles.
    Wolfram suggests that large language models democratize access to computation, but with risks of producing plausible inaccuracies.

    Voices on large language models

    9 standout quotes from across the corpus.

    Go read

    13 books and papers cited across these episodes.

    For the specialist

    What experts find new

    6 expert-level takeaways for a specialist reader.

    At the frontier

    Still unresolved

    3 open questions flagged across these conversations.

    The thinkers

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

    All guests

    Adjacent ideas