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The emphasis should be on "general". The easiest way to understand this is by thinking of the opposite: we can already build AI systems that are very good at on
by dauertewigkeit 3y ago
The emphasis should be on "general". The easiest way to understand this is by thinking of the opposite: we can already build AI systems that are very good at one specific task: folding proteins, playing Chess, detecting cats in images, translating from one language to another, detecting market inefficiencies...etc
But a human, the same human, can do all those things. A human has a sort of general intelligence. This is the goal of AGI. One can think of it as a some kind of unification theory for AI systems. One model that can be capable of excelling at vastly different tasks.
AGI has nothing to do with surpassing human intelligence. However, the idea is, once you have a general intelligence running on a computer, you could easily scale it to create a super human level intelligence.
- AnimalMuppet 3y ago> However, the idea is, once you have a general intelligence running on a computer, you could easily scale it to create a super human level intelligence. I question that. I expect that "intelligence" (however defined) will not be a linear function of the scale of the system. It will be considerably less than linear. If it's log-log scaling, say, and you already had to go to a large scale just to get human-equivalent intelligence, how easy is it to scale to superhuman levels of intelligence? Don't assume that scaling will be easy. It very well might not be.