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DeepMind: A Generalist Agent

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Re: DeepMind: A Generalist Agent

#81

Post by beaconstudios »

ajmurmann wrote: post #32
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…

> a world where AI is indistinguishable, or far superior, to human intelligence I think the part about being "indistinguishable from human intelligence" is potentially a intellectual trap. We might get to it being far superior while still underperforming at some tasks or behaving in ways that don't make sense to a human mind. An AI mind will highly likely work completely differently from humans and communicating with…

Computers are already exponentially more intelligent than humans in constrained domains, like executing mathematics. Presumably we'll just keep expanding this category until they're better at everything than us, all the while reaping industrial benefits from each iterative improvement.

Re: DeepMind: A Generalist Agent

#82

Post by password54321 »

chilmers wrote: post #8

This sounds exciting, but the example outputs look quite bad. E.g. from the interactive conversation sample: > What is the capital of France? > Marseille And many of the generated image captions are inaccurate.

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

Re: DeepMind: A Generalist Agent

#83

Post by dougabug »

PaulHoule wrote: post #49
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 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…

Sure, but GPT-3 was trained by self-supervised learning on only static text. We see how powerful even just adding captions to text can be with the example of DALLE-2. GATO takes this further by letting the large scale Transformer learn in both simulated and real interactive environments, giving it the kind of grounding that the earlier models lacked.

Re: DeepMind: A Generalist Agent

#84

Post by adamsmith143 »

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…

>People seem to model it like a smart person rather than something that thinks truly magnitudes faster than us.

Exactly, the right model is probably something like it will be in relation to humans as humans are to frogs. Frogs can't even begin to comprehend even the most basic of human motivations or plans.

Re: DeepMind: A Generalist Agent

#85

Post by ben_w »

bradleykingz wrote: post #68
digitcatphd wrote: post #62

Earlier quoted context omitted.

To be fair, his point is you can't fix a black box and the human mind is still more a discipline of philosophy than modern science.

Maybe we'll end up creating an artificial mind.

I suspect we will. I hope we don’t give it e.g. a dark triad personality disorder when we do, though I fear we may — I suspect there more ways to make a broken mind than a healthy one.

Re: DeepMind: A Generalist Agent

#86

Post by gitfan86 »

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?

Re: DeepMind: A Generalist Agent

#87

Post by logifail »

PaulHoule wrote: post #49
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 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.

Re: DeepMind: A Generalist Agent

#88

Post by adamsmith143 »

chrisco255 wrote: post #35
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…

How do we prepare for super human intelligence? Do you think that the AI will also develop its own motives ? Or will it just be a tool that we're able to plug into and use for ourselves?

A lot of people at MIRI, OpenAI, Redwood Research, Anthropic etc. are thinking about this.

I think one possibility is that even a sufficiently strong Narrow AI is going to develop strong motivations because it will be able to perform it's Narrow task even better. Hence the classic paperclip maximizer idea.

Re: DeepMind: A Generalist Agent

#90

Post by adamsmith143 »

dekhn wrote: post #47
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…

we have been using ML to solve useful problems in biology for more than 3 decades. However, it was usually called "advanced statistics and probability on large data sets" because, to be honest, that's what most modern ML is.

Of course there's no evidence that this isn't just what Human Brains are doing either.
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