MrDreamster t1_iw08jan wrote on November 11, 2022 at 10:50 PM

Reply to comment by AdditionalPizza in 2023: The year of Proto-AGI? by AdditionalPizza

Yeah I understood what you meant about consiousness after seeing your other comments.

My estimate is not based on a personal definition of proto-AGI but if I had to define it I'd say proto-AGI would basically be an AGI that can do like 10 different "simple" tasks just as well as a skilled human (Drawing, writing, speaking, coding, singing, solving problems, editing video, controling a car, creating music, and detecting diseases) while still being a single AI and not just an amalgamation of smaller narrow AIs.

An actual AGI would be able to do really anything a skilled human could do instead of just a small amount of various simple tasks and should be able to learn new concepts and how to perform new tasks by itself, and it should be able to edit its own code to improve.

An ASI would basically be an AGI after it has evolved enough time so it can do anything as well as, at least, the collective minds of all the experts on earth on each field imaginable, and will then evolve way beyond what we can imagine right now.

By that logic, we should wait way less time between now and AGI than between AGI and ASI, and I just have a gut feeling that we'll reach ASI by 2035, nothing more, so I have to be a little conservative with how much time we'll reach proto AGI because if we reach proto AGI next year it should already kickstart the creation of an actual AGI which in turn will kickstart its evolution into a proper ASI and it would fast forward my estimates by around 10 years.

AdditionalPizza OP t1_iw0ctks wrote on November 11, 2022 at 11:23 PM

Oh interesting, you think the timeframe between proto-AGI and AGI is shorter than AGI to ASI?

I think by your definition we nearly have that with 2020 language models. We certainly could do it right now. I think 2023 is when we will do that, but it will require a few steps that need to be solved, at least so far as us in the general public assume it needs solved. They're working on it and I would be surprised if our next gen models in 2023 haven't at least been able to solve things like memory. Reinforcement Learning in the pretraining phase has massive potential to bridge the gap between a current narrow scope general AI and full blown generally capable AI that I'd define as proto-AGI.

But I think "strapping" together multiple models would fit the bill too. They aren't narrow AI, they're just not broadly general or capable enough to cover enough bases. We will see how it unfolds though.