I guess things are slowing down at DeepMind. I have tremendous respect for David Silver and his work on AlphaZero and Richard Sutton as a pioneer in RL. But the cynic in me is that this paper is just a result of Goodhart's law with publishing count as a metric. Any proof of the type of emergent behaviors that they mention from RL with an actual RL experiment would go a long way. Showing an RL agent developing a langu…
It might be a stretch but some people say that the weights learned by a neural network is somewhat like a language. For example if you look at the weights of a random middle layer it would seem like gibberish. Much like how aliens would react when looking at humans making gibberish noises (aka talking) to each other. In both cases they are just compressing signals based on learned primitives.
Not sure if there is any case where this thought is useful. The only thing this says is the primitives are correlated and we don’t understand them. It’s similarly not useful to think about atoms “talking” when they exchange heat.
"A sufficiently powerful and general reinforcement learning agent may ultimately give rise to intelligence and its associated abilities. ... We do not offer any theoretical guarantee on the sample efficiency of reinforcement learning agents." OK. This basically says "evolution works". But how fast? Biology took tens of millions of years to boot up. An related question is how much compute power does evolution, viewed…
We just want AI to be able to think. We do not need an AI with an autonomic nervous system, or many of the functions in the central nervous system. We do not need AI to be very power efficient. If it takes several megawatts of electricity to get our first strong AI working, so be it. So, we do not have as many constrains as life did.
That is the most impressive use of the word 'just' in a long time. Note that all the other bits are solved, and have been solved since the 60's. It's the 'just think' bit that has proven to be a little bit harder than we thought it would be.
Sufficiently large boolean satisfiability also enough to reach general AI.
I kid, but these sorts of papers are theoretical position papers and do not account practical considerations e.g., for how many suns of energy must be expended.
Some Bozo who has heard all this many times before is suspicious of claims from places like Deep Mind who have a financial incentive to make them (keep funding) where there aren't working machines to back that claim up. Some 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 opin…
Said anonymous account on HN... If you're going to question other people's credentials, reputation, track record and claims make sure your own are solid. Those who live in glass houses shouldn't throw stones. Finally, if you're going to attack someone's article: attack the article, not the person that wrote it. This is the lowest level of attack possible: the personal one. It's as ad-hominem as it gets.
If I read it right harry8 is referring to themselves as the Bozo.
Saying RL is sufficient to (eventually) achieve AGI is a bit misleading. One might similarly state that biological evolution is sufficient to (eventually) achieve biological general intelligence. Both statements are probably true, but the parenthetical (eventually) is doing an awful lot of heavy lifting.
That is if you believe biological general intelligence is the end goal of evolution, which I believe is highly unlikely. Intelligence is simply a special side-product of evolution, there is nothing general about general intelligence. Many organisms can thrive without it. There is also a non-negligible chance that all organisms would die out before reaching intelligence. We are fortunate to live in a world that produc…
> That is if you believe biological general intelligence is the end goal of evolution, which I believe is highly unlikely.
I would agree, but might add that evolution doesn't have 'goals'.
Some Bozo who has heard all this many times before is suspicious of claims from places like Deep Mind who have a financial incentive to make them (keep funding) where there aren't working machines to back that claim up. Some 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 opin…
I'll bet a sum of real money that Some Bozo is correct. Bozo has the hindsight of history and philosophy going for him, while Deep Mind has a huge financial temptation to sell snake oil.
while Deep Mind has a huge financial temptation to sell snake oil
I don't know, isn't the DeepMind founder that guy in the Go documentary? I read about him after watching the doc and he seemed to be pretty cautious about taking in investment, and he didn't seem the type to try to cash out.
Edit: sorry just realised you’re making the same point as me more or less. Putting yourself in third person. I’ll let my comment stand anyhow :) Screwing my face up, looking at this sideways … but it seems as though you’re saying that the Bozos of HN have nothing useful to contribute to this discussion based on … [rereads] … their lack of academic credentials in the area… you could say this about just about any HN po…
Not quite the same point. Yep some bozo is me but needn't be. There's plenty who share that suspicion of AI research but have little else in common. And all of us may be wrong for different reasons. The vague point was to show someone with zero reputation, credentials, specific expertise in the field or anything much seems to be pretty convincing in response to this hugely funded ivory tower exercise by spitting, coc…
I’ve a minor in psych so I like to think I have a bit of a non-techy perspective on this, and what’s being pushed now, forms just a segment of the overall topic of AI. It just so happens to be the segment that benefits from the technology we suddenly have a rapid increase in. There’s been great successes in areas where a degree of inference is required but this hardly qualifies as even mere intelligence, and in cases where neural nets have been deployed in more human centered tasks, or even well designed symbolic systems the results speak for themselves. What even is intelligence? I think we’re going backwards because we’re investing all this talent in this simple segment I fear largely to fatten the chip makers share price while neglecting tried and true approaches that deliver far better results but perhaps crucially have a higher operating cost … who remembers google of 2010 from whom the Internet in all her glory leapt forth, or iPhone spell check of 2015 where you could confidently batter out your messages with little fear it would make a fool of you; you’re not going to nurture a nascent intelligence if you’re going to be continually hobbling it for business reasons. I’m certain we will get there eventually if we don’t destroy ourselves before then but I don’t think the current trends portray a picture of how it will be. I think we have a long way to go ourselves before we can be worthy of creating our successor, but when/if it comes it will be a beautiful thing and we will embrace it as we would our own child.
Wow, I had no idea that Yann LeCun was also this based. I've figured that it was relatively rare to hear people advocate for the superiority of unsupervised methods - but I guess it isn't if a titan like him does. It's good to hear because epistemologically I just do not believe that most learning is anything but unsupervised. There are very few good labels for our data relative to how much data we process in an info…
> It's good to hear because epistemologically I just do not believe that most learning is anything but unsupervised. I have a feeling that the lines between the supervised and unsupervised categories will get increasingly blurred, with semi-supervised, self-supervised (eg. like self-attention) and adversarial (eg. GANs) approaches mixing together in strange ways.
I used to think that given enough time, more people would also learn that there are no substantial differences between supervised and unsupervised learning. However, I have come to believe that this might not happen any time soon. The supposed difference between supervised and unsupervised can be easily explained (label / no label -- duh?!). It is much harder to explain, why that distinction is ultimately a mirage. Couple this with a million low quality blog posts on SEO steroids by data grand wizards and machine learning architects, I doubt that even a good text book jointly written by Bengio, Hinton, and LeCun would convince the ML hype train otherwise. But there is always hope!
RL can provide amazing results (AlphaGo, AlphaStar (Starcraft 2 agent), etc) but it requires a well modeled world to work with.
Games like Go and Starcraft are well modeled worlds. If you want something akin to AGI to operate in the "real world" you will need a high quality data model of the real world for the RL system to work off of.