
Ask HN: AI winter coming in next few years for AGI research? - ai_future
It seems that today&#x27;s state-of-the-art in AI&#x2F;Deep Learning&#x2F;Machine Learning&#x2F;etc has some useful practical applications for multiple industries (image&#x2F;face recognition, language translation, youtube&#x2F;music recommendations, stock trading, etc)<p>However, for AGI (Artificial General Intelligence) research, I think we are nowhere near something that approaches the final goal (mimicking the general intelligence level of a human across multiple tasks). Current approaches (such as RL or Deep RL) are very brittle, not well suited to multiple tasks, too slow to learn, and do not scale to real-world-complexity problems, among the various issues they have.<p>As a result, it seems to me that all the recent AI research hype will die down, people who are using AI for practical applications will continue to do so, but the funding and hype about AGI will die down, leading to the next AI winter.<p>Not sure how long it will take but I think it&#x27;s coming in the next few years, depending on how deep the pockets are of the current front-runners.<p>Your thoughts?
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nabla9
AI winter is not coming because we are not getting artificial general
intelligence. Most of the research is more mundane.

AI winter comes when the overall return on investment for AI research is too
low for prolonged time.

Even if the AI research would advance steady pace and produce results, it's
just normal that hype will catch in 'sexy' field and too much money is spent
at once. When investors get burned, sentiment changes and money goes elsewhere
for a period of time and there may underinvestment. Then hopefully there is
new 'Canadian Mafia' working somewhere outside the limelight and delivers new
breakthrough that moves the field forward.

Big players like Google etc. will probably continue research after cutting
some overgrow.

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imh
It's way overhyped, but there's still a ton of potential. People are making
progress on a ton of fronts, and there's lots of incredibly lucrative not-so-
sexy stuff happening you won't see on HN. There's way too much hype on the
promise of sci-fi like "AI" but people are coming up with novel ML/stats all
the time. If there are practically useful AI-ish breakthroughs (the kind we
may not see coming), that's cool, but not necessary to keep motivating
investors/grant-writers to throw money at all it all.

As for deep learning, it doesn't feel like the well is starting to dry up or
anything.

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colorincorrect
Its very hard to say as no one can really predict when a research drought will
come unless you actually do the research. Though I must say that most of the
ML researchers I've come across aren't directly concerned with AGI. (either
they outright dont care, or they think its a step by step thing) If AI winter
comes it's probably because of disappointment of progress due to
misunderstanding/misalignment with the general public / rich investors, so now
you know who to blame.

The state of cognitive science right now is basically a bunch of scientists
saying: "yeah to be honest I have no idea really how the mind does this, but
if you ignore the edge cases then this model I have here works pretty well".
But it also seems to be that those edge cases are where human cognition truly
shines. (ex. naturalized categorization, metaphor in language, novel problem
solving) There is some progress, but at this stage its unclear how to import
the philosophical discussions to an actual theory.

I'll add that it's very easy to be an "amateur cognitive scientist" because
you just need some self-awareness to be able to construct some folk theory of
the mind that works most of the time. But a model that "kinda works" isn't
going to cut it for AGI because eventually as you push it down the line
further your misalignment will get worse and worse. AGI would probably need
some massive conceptual breakthrough in cognitive science and not in
computational methods (though they are obviously interrelated)

cf:

[https://www.youtube.com/watch?v=EUjc1WuyPT8](https://www.youtube.com/watch?v=EUjc1WuyPT8)

(tbh I haven't read the bottom two, but I personally never thought that modern
NN methods can achieve AGI, so I didn't bother to read their rationale asides
from a skim)

[https://srconstantin.wordpress.com/2017/02/21/strong-ai-
isnt...](https://srconstantin.wordpress.com/2017/02/21/strong-ai-isnt-here-
yet/)

[https://arxiv.org/abs/1604.00289](https://arxiv.org/abs/1604.00289)

I am: a cognitive science student that has /some/ understanding in recent ML
methods

P.S. Still, my dream to be an AGI researcher! I have 0 prior experience but if
someone out there is reading is also doing AGI research or something similar,
contact me! I have absolutely no official credentials I must add however.

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shahbaby
My personal feeling is that although we still have a long way to go, we're on
the right track now to reaching true AGI.

