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Couldn't agree more. How about this -- I think we've already reached AGI. Let me know if this tracks: Pick a set of tasks that can be considered AGI tasks. Pro
by upghost 3y ago
Couldn't agree more. How about this -- I think we've already reached AGI. Let me know if this tracks: Pick a set of tasks that can be considered AGI tasks. Provided the task sequences can be compared as closer to AGI or further from AGI, we can create a reward model using the same techniques as were used by ChatGPT via RLHF. Thus, for any definition of AGI that is meaningful and selectable, even if subjectively selectable or arbitrarily preferential, we can create a reward model for it.
You might say, well thats not AGI, AGI must also do such and such. Well, we can get arbitrarily close to that definition as well via RLHF.
Another objection might be: well, if thats the definition of AGI, that seems really underwhelming compared to the hype train. This says nothing about autonomy, sentience, free will -- exactly. Those concepts can or should be orthogonal to doing productive work.l, IMHO.
So, there it is. We can now make a reward model for folding socks, and use gradient descent with RL to do the motion planning.
Maybe thats AGI and maybe its not, but I'd really love it if we had a golden period between now and total enshittification that involved laundry folding robots.
- AnimalMuppet 3y agoWell... humans have different mental "spaces" (not intended as a technical term). Let's say I'm deep in a coding problem. A co-worker comes by and says "How did your team do in the game yesterday?". I say, "Um, uh... sorry, my head's not there right now." It takes us time to swap between mental "spaces". So, if I have an AGI (defined as having a trained model for almost everything, even if that turns out to be a large number of different models), if it has to load the right model before it can reason on that topic, then that's pretty human-like. (As long as it can figure out which model to load...) The one thing missing is that (at least some) humans can figure out linkages between different mental "spaces", to turn them into a more coherent holistic mental space, even if they don't have (all of) each space at front-of-mind at any moment. I'm not sure if this flavor of an AGI could do that - could see the connections between different models.
- pixl97 3y agoThe power of analogy is one of the most important things that humans seem to have. Humans typically use the toolset they've seen along the way to solve problems (hence if you have a hammer all problems become nails statement). When you get people that are multi-disciplinary they commonly can solve a complex problem in one field by bringing parts of solutions from other fields. Hence if you have more life experiences (especially positive/learning ones) you are typically better off then a person who does not. Also I think this is where a lot of interest in Q* learning after the OpenAI thing occurred, as this would be a means of allowing an AI to explore problem spaces and enlist specialist AI and tools for it to do so.
- upghost 3y agosolid points. As a D&D nerd, might I offer that this is more along the lines of AGW (Artifical General Wisdom) than Artificial General Intelligence? Intelligence seems mode closely related to "IQ" as in (mechanical) "ability to solve a problem". But wisdom is knowing when to solve the problem and maybe when not to solve it, or which problem to solve. And of course, those times when instead of solving it, way better to talk about it with your fellow nerds on HN!!
- FrustratedMonky 3y agoExactly. 5 years ago, we would have said what GPT-4 is doing now would be AGI. Now it is here and it's like "No, what we really meant is it has to be the next Einstein". People are forgetting how stupid people are. GPT is already better than average human. Most people can't do what we claim GPT must be capable of to qualify as AGI. The only logical conclusion is that many people are also not conscious and don't qualify as being able to reason.
- krainboltgreene 3y ago> Exactly. 5 years ago, we would have said what GPT-4 is doing now would be AGI. okay, and 500 years ago we would have said it was magic, that doesn't make it magic. people who don't understand the thing often are confused about the thing. as soon as you explain how the whole mechanism works it's obvious that it's not that thing. > People are forgetting how stupid people are. GPT is already better than average human. Most people can't do what we claim GPT must be capable of to qualify as AGI. The only logical conclusion is that many people are also not conscious and don't qualify as being able to reason. citation massively needed, this sounds like it was written by someone who thinks idiocracy was a documentary and not a comedy.
- FrustratedMonky 3y agoIdiocracy wasn't a documentary? Have you worked with people? This sounds like someone sitting in their study, by the fire, smoking a pipe, adjusting their monocle and saying "hmm, Indubitably". Think you are taking extreme opposite view, like humans have some holy essence that can't be understood or duplicated. Which is also not correct. Of course, technology that is not-understood can appear as magic. But nobody said anything of the sort. The discussion was around AGI, will AI be as 'intelligent(loaded term)' as human. And I'm saying, a lot of people aren't doing anything that takes much 'intelligence' and current AI is already good enough to replace a large chunk of humans. Right now it is fragmented, there is AI that can beat GO, there is AI that can outfly an F-16 and beat human pilots, there is AI GPT/LLMs. It wont take much to start tying together technologies and have something that 'appears' human. And if it is indistinguishable, then how can we prove it isn't conscious, or opposite, prove that we are.
- pshc 3y agoIt tends to boil down to semantics, but as I interpret it, a threshold for AGI has to involve some breakthrough in generalizable, adaptable intelligence. So, yeah, I would invoke the "that's not AGI" move. An AGI should be able to solve any creative problem a human could, with drive and knowing purpose and coherent vision. The LLMs are still narrowly focused and require human supervision. We might well get there with chained AIs automatically training new reward models for each new problem, or by some other paradigm, but I don't feel like we're past the threshold yet.