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I'm quite sure that the Winter[1] is coming again, especially if this scifi-level AGI hype continues. We've seen this many times, and I don't think there's any
by jampekka 3y ago
I'm quite sure that the Winter[1] is coming again, especially if this scifi-level AGI hype continues. We've seen this many times, and I don't think there's any fundamental development that would bring about such a "qualitative" change in "machine intelligence".
The improvement in technical capabilities of neural netwoks (and RL somewhat too) has been wild and ANNs have jumped from silly toys to practical applications very quickly. But I think we are still deep in the Moravec's paradox[2].
The thing is that we tend to assess intelligence based on how human individuals are thought to differ in intelligence. Anybody can walk/drive, so walking/driving must be easy. Few master chess/painting/writing, so they must be hard.
But e.g. DeepBlue showed clearly that actually chess isn't that hard, people just suck at it. And conversely the failure of self driving cars showed that driving is actually hard, but humans are just very good at it.
I think it's the same thing with e.g. LLMs. People think that writing well is hard because humans who do it tend to have fancy degrees and high salaries. But writing/language is more likely closer to chess than it is to walking/driving. We just suck at it.
Before we have machines that run in a forest and make a sandwitch in a random kitchen, I'm not too worried about AGI overlords.
[1] https://en.m.wikipedia.org/wiki/AI_winter https://en.m.wikipedia.org/wiki/AI_winter
[2] https://en.m.wikipedia.org/wiki/Moravec%27s_paradox https://en.m.wikipedia.org/wiki/Moravec%27s_paradox
- Yizahi 3y agoOh, we will definitely have AGI in about 5 years. The problem is that term will be as meaningless as AI term today. After assigning "intelligence" to some pattern matching script essentially, we have devalued it into the ground so the AGI had to be invented to denote "true intelligence, this time honestly". But what will happen when OpenAI marketing team will become bored with incrementing version numbers? Exactly, the rebranding into AGI will inevitably happen. :)
- jampekka 3y agoI'm not so sure this is gonna happen, or at least catch on. No matter how much they try to hype the intelligence, the failures will be so spectacularly stupid that it's impossible maintain the illusion. The current systems do these all the time but they're just ignored due to the marvel. With AVs that was already sort of tried, but when the Superhuman Eternally Vigilant Driver slams full speed into a truck that was plainly visible from a kilometer afar, it's hard to keep many people on the hypetrain.
- famouswaffles 3y agoReasoning and persuasion trumps sensorimotor and physical perception skills by a large margin. If Moravec's paradox is why you aren't worried bout "AGI" then you have no imagination.
- jampekka 3y agoOn what criterion? It's not (just) the sensorimotor skills. It's that the Moravec's paradox hints strongly to current machine approaches having fundamental limitations in how they generalize from "one trick ponies" to adaptive and robust behavior that I think would be needed for an "AGI". Of course all sorts of horrors can be and are accomplished by new technologies, but this doesn't make them intelligent in AGI sense.
- famouswaffles 3y agoThe idea that the machine needs to be physically present to alter the physical world is laughable. all you need to do that is communication with humans who could alter it for you. It doesn't hint at anything like that all. That's like saying humans being unable to fly or intuitively sense electromagnetic fields to divine locations says anything about how humans can generalize. There are millions of humans who are disabled and can't drive or walk and will never be able to. are they not still general intelligences ? are they automatically less intelligent ?
- jampekka 3y agoThat idea is of course laughable, but I didn't say anything of the sort. It's not the physicality, but the messiness, ambiguity and harsh consequences of the natural environment. Current machines operate in environments that are deliberately designed to be highly structured with clear goals and where consequences of errors are highly mitigated. Machine learning has made some more messiness possible, but it still depends quite a bit on predefined structure.
- famouswaffles 3y ago