▲ | kokanee 10 days ago | ||||||||||||||||||||||||||||||||||
Tomorrow, LLMs will be able to perform slightly below-average versions of whatever humans are capable of doing tomorrow. Because they work by predicting what a human would produce based on training data. | |||||||||||||||||||||||||||||||||||
▲ | herval 10 days ago | parent | next [-] | ||||||||||||||||||||||||||||||||||
This severely discounts the fact that you’re comparing a model that _knows the average about everything_ to a single human’s capabilit. Also they can do it instantly, instead of having to coordinate many humans over long periods of time. You can’t straight up compare one LLM to one human | |||||||||||||||||||||||||||||||||||
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▲ | steveBK123 9 days ago | parent | prev [-] | ||||||||||||||||||||||||||||||||||
It's worth considering 1) all the domains there is no training data Many professions are far less digital than software, protect IP more, and are much more akin to an apprenticeship system. 2) the adaptability of humans in learning vs any AI Think about how many years we have been trying to train cars to drive, but humans do it with a 50 hours training course. 3) humans ability to innovate vs AIs ability to replicate A lot of creative work is adaptation, but humans do far more than that in synthesizing different ideas to create completely new works. Could an LLM produce the 37th Marvel movie? Yes probably. Could an LLM create.. Inception? Probably not. |