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DeepMind: A Generalist Agent

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Re: DeepMind: A Generalist Agent

#101

Post by ninjinxo »

gonehome wrote: post #27
axg11 wrote: post #22

Slowly but surely we're moving towards general AI. There is a marked split across general society and even ML/AI specialists between those who think that we can achieve AGI using current methods and those who dismiss the possibility. This has always been the case, but what is remarkable about today's environment is that researchers keep making progress contrary to the doubter's predictions. Each time this happens, th…

The closer we get, the more alarming the alignment problem becomes. https://intelligence.org/2017/10/13/fire-alarm/ Even people like Eric Schmidt seem to downplay it (in a recent podcast with Sam Harris) - just saying “smart people will turn it off”. If it thinks faster than us and has goals not aligned with us this is unlikely to be possible. If we’re lucky building it will have some easier to limit constraint like…

What is an ant to man, and what is man to a god; what's the difference between an AGI and an (AIG) AI God?

The more someone believes in the dangers of ai-alignment, the less faith they should have that it can be solved.

Re: DeepMind: A Generalist Agent

#102

Post by twofornone »

phyalow wrote: post #100

Isnt this a general reinforcement learning agent with a transformer as the policy discriminator? Very cool, but not necessarily a giant leap forward, more like a novel combination of existing tools and architectures. Either way impressive.

I haven't read the paper yet but it looks like the breakthrough is that it uses the "same weights" for tasks in completely different domains.

Which implies that it can draw from any of the domains it has been trained on for other domains. Speculating here but for example training it on identifying pictures of dogs and then automagically drawing on those updated weights when completing text prompts about dog properties.

If my interpretation is correct then this is a pretty big deal (if it works well enough) and brings us a lot closer to AGI.

Re: DeepMind: A Generalist Agent

#103

Post by PaulHoule »

logifail wrote: post #87
PaulHoule wrote: post #49

Earlier quoted context omitted.

I have been impressed with what I've seen in the last six months but it still seems that GPT-3 and similar language models greatest talent is fooling people. The other day I prompted a language model with "The S-300 missile system is" and got something that was grammatical but mostly wrong: the S-300 missile system was not only capable of shooting down aircraft and missiles (which it is), but it was also good for sho…

> I see the problem is that people look at the output of these things that are (say) 70% correct and in their mind they fill in the other 30%. Q: Is there also some element of survival bias in the mix? If you prompt GPT-3 with something and the answer is garbage, you probably don't write it up on your blog. If you get something that makes sense, then you do.

That's true for most people. It's the opposite for me!

Re: DeepMind: A Generalist Agent

#104

Post by password54321 »

phyalow wrote: post #100

Isnt this a general reinforcement learning agent with a transformer as the policy discriminator? Very cool, but not necessarily a giant leap forward, more like a novel combination of existing tools and architectures. Either way impressive.

2nd page: "Gato was trained offline in a purely supervised manner"

Re: DeepMind: A Generalist Agent

#105

Post by solveit »

davesque wrote: post #73
axg11 wrote: post #22

Slowly but surely we're moving towards general AI. There is a marked split across general society and even ML/AI specialists between those who think that we can achieve AGI using current methods and those who dismiss the possibility. This has always been the case, but what is remarkable about today's environment is that researchers keep making progress contrary to the doubter's predictions. Each time this happens, th…

I generally agree that AI continues to impress in very specific ways but, to be fair, some of the points you make are debatable. For example, I would argue that the development of GANs and other algos do no necessarily disprove the statement "ML models can't perform creative work." They definitely represent meaningful steps in that direction, but I don't think it's hard to find flaws with generated content. On the ot…

> I don't think it's hard to find flaws with generated content

I do wonder if you were to apply the same level of scrutiny to individual humans, you wouldn't also conclude that most people cannot do creative work.

Re: DeepMind: A Generalist Agent

#106

Post by password54321 »

chilmers wrote: post #96
password54321 wrote: post #82

Earlier quoted context omitted.

Yeah they put that example for a reason. Read the paper and stop acting like this is some great insight that you discovered.

What exactly did I say that implied I was acting as this was a “great insight I’d discovered”? That’s a rather rude and unfair insult I’d say.

When someone only mentions a fault with nothing else to add it comes off dismissive which is a common theme for comments on AI research.

Re: DeepMind: A Generalist Agent

#107

Post by robitsT6 »

TaupeRanger wrote: post #97
axg11 wrote: post #22

Slowly but surely we're moving towards general AI. There is a marked split across general society and even ML/AI specialists between those who think that we can achieve AGI using current methods and those who dismiss the possibility. This has always been the case, but what is remarkable about today's environment is that researchers keep making progress contrary to the doubter's predictions. Each time this happens, th…

And yet, the only thing that really matters out of your entire list is the 1st one: that AI solves problems that actually improve the human condition. And Alpha Fold has not done that at all. It may be very nice for people interested in protein folding, but until it actually helps us find something that we wouldn't have found otherwise, and that discovery leads to (for example) an ACTUAL drug or treatment that helps…

But there have been quite a few scientific papers that have used discoveries from AlphaFold already. There have been many scientists who have been stuck for years, who are suddenly past their previous bottlenecks. What gives you the impression that it hasn't helped us?

Re: DeepMind: A Generalist Agent

#108

Post by tsimionescu »

gitfan86 wrote: post #86
axg11 wrote: post #22

Slowly but surely we're moving towards general AI. There is a marked split across general society and even ML/AI specialists between those who think that we can achieve AGI using current methods and those who dismiss the possibility. This has always been the case, but what is remarkable about today's environment is that researchers keep making progress contrary to the doubter's predictions. Each time this happens, th…

Tesla FSD is quickly becoming less of a software problem and more of a problem of semantics. If the car drives someone to and from work 30 days in a row without a problem, is it truly FSD? What about 300 days? Where do you draw the line? 1000x safer than the average human? Same thing here will AI. How many conversations with GTP-X need to happen without a stupid response from GTP before we call it real world AI?

How about first getting to "as safe/performant as a non-drunk, non-sleep-deprived, non-brand-new driver with 0 human intervention" before asking more advanced questions?

Tesla FSD is definitely nowhere near that level.

Re: DeepMind: A Generalist Agent

#109

Post by davesque »

solveit wrote: post #105
davesque wrote: post #73

Earlier quoted context omitted.

I generally agree that AI continues to impress in very specific ways but, to be fair, some of the points you make are debatable. For example, I would argue that the development of GANs and other algos do no necessarily disprove the statement "ML models can't perform creative work." They definitely represent meaningful steps in that direction, but I don't think it's hard to find flaws with generated content. On the ot…

> I don't think it's hard to find flaws with generated content I do wonder if you were to apply the same level of scrutiny to individual humans, you wouldn't also conclude that most people cannot do creative work.

I was thinking more about things like the weird, blurry, dream-like artifacts that you see in some GAN-generated content. Things that look like work done by someone who was both severely impaired yet somehow still extremely meticulous. Things like that seem characteristically un-human.

Re: DeepMind: A Generalist Agent

#110

Post by jackblemming »

axg11 wrote: post #22

Slowly but surely we're moving towards general AI. There is a marked split across general society and even ML/AI specialists between those who think that we can achieve AGI using current methods and those who dismiss the possibility. This has always been the case, but what is remarkable about today's environment is that researchers keep making progress contrary to the doubter's predictions. Each time this happens, th…

>Each time this happens, the AGI pessimists raise the bar (a little) for what constitutes AGI.

Why does this need to be repeated in every discussion about AI? It’s tired.

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