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Comment by solid_fuel | Hacker News Reader

> to the detriment of the whole club of stochastic parrot folk

What an interesting and pointless way to refer to “experts who understand what an LLM actually is”

The people who refer to LLMs as stochastic parrots generally do so to imply significant limits on an LLMs ability, not as an abstract statement about the underlying mechanism of how they work. Probably the defining thing that is surprising about LLMs is that they do in fact gain significantly more capability than you would expect from such a simple underlying mechanism!

The concept of "stochastic parrot" is that an LLM merely parrots its training data with some randomness.

We now know that isn't true - LLMs build complex internal models and output based on that.

See for example https://arxiv.org/html/2505.23323v1

Also, you are commenting on a post where a LLM made significant progress on the Riemann hypothesis. Even the most extreme interpretation of these results, ie claiming that it was "only linking existing literature" goes well beyond a "stochastic parrot" - it had to be able to link disparate insights across multiple fields.

only if you don't understand the difference between metaphor and analogy

> Also, you are commenting on a post where a LLM made significant progress on the Riemann hypothesis.

Actually you're commenting on a post where an LLM used existing insights to make a small improvement to the bounds of the Riemann Hypothesis by applying the existing insight to an existing theoretical approach. This is the core problem and missing it betrays your lack of understanding: an LLM was used to apply existing work to an existing approach, there was no innovation on the part of the parrot.

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