Earlier quoted context omitted.
This already exists: https://www.youtube.com/watch?v=UAG_FBZJVJ8
Could you point me to the timestamp where it empties a dishwasher?
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Q-Transformer
41–50 of 74 posts
Re: Q-Transformer
#42It's clear we're searching for the god algorithm of AI, just like physicists are searching for theory of everything. Are transformers the answer though?
As it stands, each token processed by transformer requires a constant amount of computation and energy. For an AGI system, this would imply the ability to solve problems of any complexity with a fixed amount of energy. But if this were true, it would essentially mean that P equals NP, a major theoretical breakthrough in computational complexity theory. IMO we are still missing something.
Re: Q-Transformer
#43How does this stack up to diffusion policy learning?
https://diffusion-policy.cs.columbia.edu/
Looking at the figures and videos it seems... worse? Sort of surprised they didn't compare it but I guess they're trying to limit the discussion to purely reinforcement learning methods.
EDIT: Ah, I see this is an older result and was published concurrently to the diffusion policy paper, so it's likely the authors didn't know about it in time to add the extra comparisons.
Re: Q-Transformer
#44Being implemented as we speak, by the always impressive LucidRains [1] [1]: https://github.com/lucidrains/q-transformer
It's kinda funny how Lucidrains came back to make numerous commits to this repo following Q*.
Apparently this guy like a bunch of others like https://github.com/ggerganov/ggml are implementing transformers from papers for people that want them. Pretty cool.
Re: Q-Transformer
#45To save you guys some time, this is a 2 month old paper and not made by OpenAI. It could be related to Q* (I don't know enough to determine that) but it's not OpenAI's Q*.
Re: Q-Transformer
#46Earlier quoted context omitted.
That's a great start. Opening a drawer is pretty hard problem.
Correct- as a reference for OC this is known as Moravec's Paradox ( https://en.wikipedia.org/wiki/Moravec%27s_paradox )
At least to me the key point of the article
>Encoded in the large, highly evolved sensory and motor portions of the human brain is a billion years of experience about the nature of the world and how to survive in it. The deliberate process we call reasoning is, I believe, the thinnest veneer of human thought, effective only because it is supported by this much older and much more powerful, though usually unconscious, sensorimotor knowledge. We are all prodigious olympians in perceptual and motor areas, so good that we make the difficult look easy. Abstract thought, though, is a new trick, perhaps less than 100 thousand years old. We have not yet mastered it. It is not all that intrinsically difficult; it just seems so when we do it.
Re: Q-Transformer
#47Earlier quoted context omitted.
It seems more likely that there will be multiple avenues to AGI, all with their strengths and weaknesses. But perhaps the "God AI" will be a multifaceted model composed of many different models acting in unison.
Exactly, just as the true god has seven aspects [0]. [0] https://en.wikipedia.org/wiki/Themes_in_A_Song_of_Ice_and_Fi...
On the other hand, most of the original gods were parts of polytheistic pantheons. Maybe a bunch of models that represent identities and biases could be more useful, they could argue amongst themselves, presenting a more full point of view, users could become familiar with the particular perspectives.
Re: Q-Transformer
#48It's clear we're searching for the god algorithm of AI, just like physicists are searching for theory of everything. Are transformers the answer though?
We're searching for an efficient algorithm that leads to AGI. Given sufficient time and compute, I'm sure that we could get there with existing stuff, by accident, and we wouldn't realize it before moving on to the next thing... and there'd be a poor orphan AGI, lost in a Git repo, waiting for runtime.
"Given sufficient time and compute" covers up a lot, though. The ultimate God AGI that would be created through that sort of process would take the form of a large room filled with a whole lot of monkeys and typewriters.
Re: Q-Transformer
#49Earlier quoted context omitted.
That's a great start. Opening a drawer is pretty hard problem.
The other robot project posted here yesterday opened drawers at around 80% though https://news.ycombinator.com/item?id=38453047 And they did it in many different homes.
My robot can open drawers at near 100%, but it takes the form of a stick of dynamite.
Still working on closing the drawers afterwards, though...
Re: Q-Transformer
#50It's clear we're searching for the god algorithm of AI, just like physicists are searching for theory of everything. Are transformers the answer though?
It seems more likely that there will be multiple avenues to AGI, all with their strengths and weaknesses. But perhaps the "God AI" will be a multifaceted model composed of many different models acting in unison.
I could see something like the "modularity of mind" model of human consciousness, where multiple approaches are working on "subconscious" solutions to a given problem in parallel, with a top layer deciding which is appropriate at the moment.
My human brain doesn't use the same algorithm for learning to play a song on a piano as learning to play a new board game. I'm not an AI person, but it seems reasonable to imagine we'd have different "modules" to apply as needed.
AlphaGo probably sucks at conversation. ChatGPT can't play Go. The part of my brain writing this couldn't throw a baseball. The physics engine that lets me throw a baseball couldn't write this. Is there a reason we'd want or need one specific AI approach to be universally applicable?