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I have a hunch when they decide who to hire for upper management, they select for whoever promises the moon. The person making the promises may not even believe it.
I really wonder what the next AI winter will be like. Edit: Perhaps OpenAI becomes a major tech player and we just see a cooling off of other AI investments as LLM becomes a known in terms of its strengths and weaknesses. Its abilities reach a natural limit which is still generally very useful. Or maybe folks realize the degree of lies/mistruths inherent in its content is actually unmanageable and can’t be improved.…
>we just see a cooling off of other endeavors as LLM becomes a known in terms of its strengths and weaknesses and it’s abilities reach a natural limit which is still general useful. This is my prediction If the training set is just the internet, it will be not much different than someone who spends all their lives in their room in front of their computer.
It's not that I'm especially smart; many others could tell you ways to do the same thing now that there's an initial proof-of-concept. It's that these things are new enough no one has had those five years yet. GPT4 came out two months ago, ChatGPT maybe seven months ago, and GPT3 three years ago.
I can't predict if these things will level off, grow linearly, grow exponentially, Moore's Law style, or explode off into the singularity.
I can say GPT4 is nowhere close to the limit.
I predict that the fight will be more about defining intelligence than inventing it. No one knows what AGI is. There isn't going to be some switch that flips to take us from AI to AGI. These tools we have today will just keep getting incrementally better, and some new ones will pop up, and at some point we'll have to stop and say "yeah, this is good enough to qualify". And everyone will have their own opinion on what…
There are reasons Ray Kurzweil used the term "spiritual" in the Age of Spiritual Machines. Among those reasons is that "spiritual" is much more difficult to define with any consensus among experts.
And indeed, there's an inflection point coming. What this is, is not at all clear. However, I'd predict that the answer lies with the realization that, given the limits of conversing with LLMS and GPT, the implication is that there's a human-computer sensemaking loop:
https://www.efsa.europa.eu/sites/default/files/event/180918-...
The difference with this HCI is that you'd not hire a human collaborator who lied to you with or without being aware of their own lack of veracity. Here, we'll burn fields full of GPUs at massive cost to get an answer, even though the outcome may be advertising the fact that the AI is wrong. There is learning, but it's going to be costly and painful.
Several comments have touched on this, but wouldn't you define an AGI as something that could learn to drive a car? I think every (reasonable ( person understands self driving is >10 years away. So shouldn't AGI be?
It's possible that we're limited on the hardware / modality front.
The other few things possible in next few years for past few years are: 1. Fusion 2. Self driving cars. 3. Ubiquitous, generally available and stable 8192 bit quantum computers. 4. High energy density grid scale batteries. Just few more "this maybe the... what could revolutionize..." articles away. What we forget is that it is in these people's business interest (executives making such statements) to state the exagge…
But there's still time for robo-taxis!
Several comments have touched on this, but wouldn't you define an AGI as something that could learn to drive a car? I think every (reasonable ( person understands self driving is >10 years away. So shouldn't AGI be?
Earlier quoted context omitted.
>we just see a cooling off of other endeavors as LLM becomes a known in terms of its strengths and weaknesses and it’s abilities reach a natural limit which is still general useful. This is my prediction If the training set is just the internet, it will be not much different than someone who spends all their lives in their room in front of their computer.
I don't think that's a limit. If you give me $10M and 5 years, I can tell you a half-dozen ways to train models better than GPT4, primarily by having them do richer tasks than text completion, by having them evaluate themselves in richer ways, by having workflows around them, and by having shared models perform multiple types of tasks (e.g. text, image, controls, etc.). It's not that I'm especially smart; many others…
I think we’ll learn to compose models for more diverse and capable outputs, validate those outputs better, and do all of it more efficiently. The end result seems like it could be far greater than the sum of its parts.
Several comments have touched on this, but wouldn't you define an AGI as something that could learn to drive a car? I think every (reasonable ( person understands self driving is >10 years away. So shouldn't AGI be?
AGI is about inventing the brain, while the car is an entire body.