3 ms·
Roughly speaking, the whole point of an LLM is to create plausible sounding text, without regard to the truth (which it cannot determine or derive), so it's a t
by dkjaudyeqooe 3y ago
Roughly speaking, the whole point of an LLM is to create plausible sounding text, without regard to the truth (which it cannot determine or derive), so it's a tool that is perfectly suited to this sort of malfeasance.
- SV_BubbleTime 3y agoI’ve read this over and over, and believe it - but it’s so easy to forget when it absolutely nails something like debugging or suggesting a CMake edit or finding 5 letter combinations that are reversible with a vowel in the middle, or etc. It’s just still mind blowing I can get a sarcastic summary of an email in the theme of GlaDOS from Portal and in the same screen get an email proofread. It’s funny how far “what should the next word be” can go.
- lazystar 3y agoa billion humans typing on a billion keyboards for a few decades... just needed someone to come along and categorize each of the outputs.
- SV_BubbleTime 3y agoI like that. And the numbers are way higher than a billion.
- strogonoff 3y agoIt might seem that there are cases where the ability to generate heaps of plausibly sounding text on demand is helpful, and there are cases where it is pretty much the worst possible capability to have.
- gardenhedge 3y agoIt's really worth watching this: https://news.ycombinator.com/item?id=38388669 https://news.ycombinator.com/item?id=38388669
- carlorolland56 3y agoi don't agree. The way that most LLMs currently generate response might be through this modality. But the purpose of LLMs is to get closer to simulating how human minds and languages operate. A lot of models have been trying to overcome the problem of fabrications. GPT bots like SciSpace's ResearchGPT are trying to do precisely that.