DeepMind says reinforcement learning is ‘enough’ to reach general AI
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Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI
#12This article is interesting, I even skimmed through their paper. But I think still the question remains: How to find the unified reward function? Or in other words, how to find answer to life? [It cannot be 42].
It talks a lot about having a rich enough environment for learning which makes sense, if a computer lives only in a Go board it can only learn go playing itself.
How do you simulate a rich enough environment purely in software (or do you sense input from the "real" environment) and what reward do we define in this complex environment.. It seems to ask those 2 questions in the discussion but kind of glosses over them imo.
Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI
#13Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI
#14Wait isn’t any Turing complete programming language sufficient to eventually reach general AI
Like the notion that all of natural language can be modeled fully if you just use enough finite state machines — surely true; just a wee bit inefficient.
Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI
#15A 2018 article about the challenges of reinforcement learning: https://www.alexirpan.com/2018/02/14/rl-hard.html
Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI
#16As far as I can tell, they're not actually proposing how to achieve this. I can't access the article without a host institution it seems (is there another link?), so I only have the article to go by. RL has been the basis for all robots engaging with the world, and that engagement with the physical world modeled using RL has been promised to make robots that can act like a 2 year old for a long time (see Cynthia Breazeal's work, for example). Yet AFAIK, we haven't actually achieved this as we don't know how to efficiently model the problem to have learning rates that reach anywhere near what we're able to do with DNNs today.
Perhaps someone who has access to the paper can say why this is a milestone? If Patricia Churchland suggests it is, then something new must be happening here.
Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI
#17I'm more in Yann LeCun's camp who called unsupervised learning the cake, supervised learning the icing and reinforcement learning the cherry on top of the cake.
Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI
#18Some Bozo has no credentials, no reputation, no track record of publications and barely supports the claim they're making with anything much. Some Bozo has no financial incentives or otherwise to opine either way. Some Bozo doesn't even work in the field at all.
Bets: Some Bozo or Deep Mind turn out to be closer to being correct in the passing of some finite amount of time? 5 years? 10 Years? 25 Years?
Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI
#19I'm more in Yann LeCun's camp who called unsupervised learning the cake, supervised learning the icing and reinforcement learning the cherry on top of the cake.
Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI
#20Everything old is new again. As far as I can tell, they're not actually proposing how to achieve this. I can't access the article without a host institution it seems (is there another link?), so I only have the article to go by. RL has been the basis for all robots engaging with the world, and that engagement with the physical world modeled using RL has been promised to make robots that can act like a 2 year old for…
After having read the paper, I am very disappointed in the output. Nothing concrete was shown, just hypothesis and reads more like philosophy. That being said, I would say that the paper is carefully worked out and does provide insight if you haven't thought about RL before.