Comment by Terr_ | Hacker News Reader

Comment by Terr_ | Hacker News Reader

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Just to confirm, as this topic gets "very meta" with levels of indirection, it sounds like you mean the LLM appends a "fitting" document fragment like:

    This was an unusual task Bot wasn't sure how to solve directly.
    Bot decided it needed to execute a program:
      [CODE_START]foo(bar(baz())[CODE_END]
    Which resulted in 
      [CODE_RESULT_PLACEHOLDER]

This stage-direction is externally parsed, executed, and substituted, and then the LLM is called upon to generate Bot-character's next reaction.

In terms of how this could go wrong, it makes me think of a meme:

> Thinking quickly, Dave constructs a homemade megaphone, using only some string, a squirrel, and a megaphone.

Yes, my understanding is:

- finding patterns in data is memorization

- finding patterns in metadata is intelligence

- finding patterns in meta-metadata is invention

For example, if you ask someone to hang a painting in an art gallery 12 feet from the floor using a 13-foot ladder:

- a worker will use the safety rule of staying 5 feet away from the wall. This is what GPT-3 does. [1]

- an engineer will apply the Pythagorean theorem. This is what o3 does.

- Pythagoras, seeing it for the first time, will derive the theorem. GPT-5 is nowhere close to that.

This climbing up the ladder of abstraction existed even before LLMs. DeepMind's AlphaGo learned from human games. But AlphaGo Zero and AlphaZero trained entirely through self-play and began uncovering new strategies across Go, chess, and shogi. So whether it's code, a game, or pseudocode, they're all metadata operating at the same level of abstraction.

[1] The Nature of Intelligence is Meta - https://manidoraisamy.com/intelligence-is-meta.html

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