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Link to paper: https://arxiv.org/pdf/2104.12871.pdf https://arxiv.org/pdf/2104.12871.pdf TLDR: Fallacy 1: Narrow intelligence is on a continuum with general in
by juliangamble 5y ago
Link to paper: https://arxiv.org/pdf/2104.12871.pdf https://arxiv.org/pdf/2104.12871.pdf
TLDR:
Fallacy 1: Narrow intelligence is on a continuum with general intelligence
(solving an easy AI problem doesn't immediately lead to being able to solve a hard AI problem)
Fallacy 2: Easy things are easy and hard things are hard
(ie AI is hard)
Fallacy 3: The lure of wishful mnemonics
(ie people tend to give parts of a computer program anthropomorphic labels, eg "understand" that don't really)
Fallacy 4: Intelligence is all in the brain
(our thoughts are grounded, or inextricably associated with,
perception, action, and emotion, and that our brain and body work together to have cognition)
- EliasY 5y agoWith regards to fallacy #2 in fact, it is the other way around, I. E. "Easy things are hard" also known as Moravec's paradox. The symbolic AI generation always assumed that really hard problems like language understanding could be solved entirely through easy symbolic manipulation techniques. At the same time, current generation of AI researchers also claim that neural networks and gradient descent are all you need to solve such problems. But both groups seem to forget that the such problems are barely touchable using a single approach and encompass a large variety of different subproblems that may need wildly different methodologies inorder to solve them.
- sanxiyn 5y agoFallacy 4 is wrong. There are good reasons to believe intelligence can be "disembodied". The primary one is that signal mappers decouple. https://www.overcomingbias.com/2011/01/signal-processors-decouple.html https://www.overcomingbias.com/2011/01/signal-processors-dec...
- fighterpilot 5y agoFallacy #1 is mostly just a proposition/conjecture. The current trend is for these "narrow" AI systems to become more and more general as the technology gets better. So far, we haven't seen the end of that trend. It's anyone's guess whether we're going to run into the proposed hypothetical barrier.
- mscharrer 5y agoI think fallacy 2 is the big one, and not just in the AI field. Sometimes a simple lookup table (or some other 'dumb' model) works well on tasks that humans generally consider 'hard'.