LLMs are just math.
It’s reasonable to scope one’s interest down to easily predictable, simple systems.
But most of the value in math and computer science is at the scale where there is unpredictability arising from complexity.
It’s reasonable to scope one’s interest down to easily predictable, simple systems.
But most of the value in math and computer science is at the scale where there is unpredictability arising from complexity.
But a lot of the trouble in these domains that I have observed comes from unmodeled effects, that must be modeled and reasoned about. GPZ work shows the same thing shown by the researcher here, which is that it requires a lot of tinkering and a lot of context in order to produce semi-usable results. SNR appears quite low for now. In security specifically, there is much value in sanitizing input data and ensuring correct parsing. Do you think LLMs are in a position to do so?
In the hands of an expert, I believe they can help. In the hands of someone clueless, they will just confuse everyone, much like any other tool the clueless person uses.