Well it depends. It doesn't have arms and legs so can't physically experiment in the real world, a human is currently a proxy for that, we can do it's bidding and feedback results though, so it's not really an issue.

Most of the time that data is already available to it and they merely need to a prove a thereom using existing historic data points and math.

For instance the Black-Scholes-Merton equation which won the Nobel economics prize was derived using preexisting mathematical concepts and mathematical principles. The application and validation relied on existing data.

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adamzwasserman 2 days ago | parent [-]

The Black-Scholes-Merton equation wasn't derived by rearranging words about financial markets. It required understanding what options are (financial reality), recognizing a mathematical analogy to heat diffusion (physical reality), and validating the model against actual market behavior (empirical reality). At every step, the discoverers had to verify their linguistic/mathematical model against the territory.

LLMs only rearrange descriptions of discoveries. They can't recognize when their model contradicts reality because they never touch reality. That's not a solvable limitation. It's definitional.

We're clearly operating from different premises about what constitutes discovery versus recombination. I've made my case; you're welcome to the last word

	▲	KoolKat23 2 days ago \| parent [-]
		I understand your viewpoint. LLM's these days have reasoning and can learn in context. They do touch reality, your feedback. It's also proven mathematically. Other people's scientific papers are critiqued and corrected as new feedback arrives. This is no different to claude code bash testing and fixing it's own output errors recursively until the code works. They already deal with unknown combinations all day, our prompting. Yes it is brittle though. They are also not very intelligent yet.