Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

DeepMind says reinforcement learning is ‘enough’ to reach general AI

venturebeat.com

Post reply on HN
Print view View original

221–230 of 312 posts

Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI

#221

Post by JamilD »

scythmic_waves wrote: post #169

/r/MachineLearning discussion: https://www.reddit.com/r/MachineLearning/comments/nplhy3/r_r... I'm with most of the comments there. This paper is ridiculously hand-wavey.

Many of DeepMind's opinion style papers are like this. Another example of the "handwavy" DeepMind paper: https://arxiv.org/pdf/2102.03406.pdf

It's also worth it to note as well that this isn't a homogenous organization, many DeepMind employees have different opinions on issues like this and an individual paper isn't representative of the entire organization.

Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI

#222

Post by LesZedCB »

the paper postulates that "reward is enough" but what is the alternative? rewards plus what?

the "cybernetic feedback loop" aka reinforcement learning has kinda always been the idea, no?

i believe that architecture is important. yes, at one level the human is a rewards machine, but the neocortex produces a lot of "self-reflection" that doesn't really generate reward in itself, at least i don't know if it does. maybe meditations create a general dopamine spike?

Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI

#223

Post by [deleted] »

flylikeabanana wrote: post #218
criddell wrote: post #211

Earlier quoted context omitted.

Does AGI imply human-level intelligence, or would the intelligence of a housefly qualify?

AGI implies it can pass a Turing test, which means it has a better-than-average chance of acting more "human" than a competing human.

[deleted]

Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI

#224

Post by ronsor »

candiodari wrote: post #128
rich_sasha wrote: post #110

Basically, any problem with a solution fits into RL: reward of 1 if you are AGI and 0 otherwise. Go learn. This setting on its own is meaningless! The “how” of the RL agent is not even 99% of the problem, it is all of it. Given our understanding of both DL and neuroscience, it is not even clear to me that we can say with confidence that Neural Networks are a sufficiently expressive architecture to cover an AGI. The h…

I assure you 99% of the problem of any RL project is the simulator. Generally you can't let an RL algorithm control anything real from the start, so you have to implement a reasonably reliable simulator for whatever you want done. This is the big challenge in practice.

Correct me if I'm wrong, but wouldn't that mean the entire world would have to be simulated? Or at least some subset of society?

Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI

#225

Post by robrenaud »

xamuel wrote: post #213
webmaven wrote: post #3

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.

I thought it was a fun position paper, if not exactly groundbreaking. They did avoid one common pitfall at least. They are (intentionally?) vague about which number systems the rewards can come from, apparently leaving it open whether the rewards need be real-valued or whether they can be, say, hyperreals, surreals, computable ordinals, etc. This avoids a trap I've written about elsewhere [1]: traditionally, RL rewar…

There are more real numbers than programs. Computers cannot represent the vast majority of real numbers. AFAICT, it's not even clear that the universe is continuous rather than discrete.

I really don't believe that using approximations of real numbers is going to be the bottleneck for AGI.

Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI

#226

Post by Blikkentrekker »

8ytecoder wrote: post #215
criddell wrote: post #211

Earlier quoted context omitted.

Does AGI imply human-level intelligence, or would the intelligence of a housefly qualify?

I'm assuming you are aware of the difficulties for machines to do even the most basic of things that a living being can do with a brain the size of a pea. A housefly can fly and navigate effortless through most complex scenarios that it evolved to navigate (even though the same fly can get stuck behind a glass window and eventually die). So yeah, even getting that level of intelligence would be a huge win. However, m…

> even if it's one narrow specialization.

Obviously that already exists even with g.o.f.a.i.s so that is not that impressive.

The impressive thing is something more general than that.

Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI

#227

Post by enkid »

xamuel wrote: post #213
webmaven wrote: post #3

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.

I thought it was a fun position paper, if not exactly groundbreaking. They did avoid one common pitfall at least. They are (intentionally?) vague about which number systems the rewards can come from, apparently leaving it open whether the rewards need be real-valued or whether they can be, say, hyperreals, surreals, computable ordinals, etc. This avoids a trap I've written about elsewhere [1]: traditionally, RL rewar…

How do you even have reinforcement learning with non-real numbers? The point is to maximize a score. It seems to me, any benefit you'd get from using an alternative number system could be replicated by using an algorithm to convert multiple real number scores into a single value.

Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI

#228

Post by YinLuck- »

robrenaud wrote: post #225
xamuel wrote: post #213

Earlier quoted context omitted.

I thought it was a fun position paper, if not exactly groundbreaking. They did avoid one common pitfall at least. They are (intentionally?) vague about which number systems the rewards can come from, apparently leaving it open whether the rewards need be real-valued or whether they can be, say, hyperreals, surreals, computable ordinals, etc. This avoids a trap I've written about elsewhere [1]: traditionally, RL rewar…

There are more real numbers than programs. Computers cannot represent the vast majority of real numbers. AFAICT, it's not even clear that the universe is continuous rather than discrete. I really don't believe that using approximations of real numbers is going to be the bottleneck for AGI.

I thought the whole point of quantum mechanics was to prove the universe was discrete and thus not continuous, no?

Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI

#229

Post by mjburgess »

criddell wrote: post #211
webmaven wrote: post #3

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.

Does AGI imply human-level intelligence, or would the intelligence of a housefly qualify?

It's a very interesting question.

Personally I take mammalian intelligence as the relevant standard we're actually aiming at.

So I'd say mouse+.

Houseflys, I think, are closer to non-intelligent than intelligent.

Re: DeepMind says reinforcement learning is ‘enough’ to reach general AI

#230

Post by mensetmanusman »

FredPret wrote: post #176
zcw100 wrote: post #151

Earlier quoted context omitted.

Really? I created two GI's and it wasn't very hard and was actually quite fun. Training them is a bit of a pain though. I'm willing to bet that based on total calories consumed they are amazingly efficient compared to their hypothetical AGI counterparts.

Yes but can they: - live forever - grow their own mental capabilities exponentially over that unlimited lifespan - turn themselves into universe-eating von Neumann probes

My three-year-old said yes to all questions
Post reply on HN