Do you think we would have to embody AI as OpenAI is doing with Figure? Or just create realistic worlds using something like the unreal engine to simulate physics and just let it play around in there?
In David Siver course on reinforcement learning there is an autonomous helicopter flying; they probably crashed thousands of virtual helicopters until the machine learned to pilot the real one.
Completely agree. I’ve always thought that different queries should ping different parts of the model / architecture.
For example, the query “is the sky blue” ideally would only fire up a small language model since its not very complex and would require less compute and energy.
For a query about protein synthesis, fire up the large language model since it’s a more complex prompt.
For image / video generation use diffusion with reinforcement learning (Sora architecture)
And for agency use JEPA.
I don’t think many people grasp the implications of OpenAis new Omni-model. It combines many modalities we’ve been talking about into a single interface.
We’re still at the foundational layer and most of the applications have yet to be built.
Think the future is super bright and I’m so glad we can both be a part of it!
I agree with this prediction
Thank you Meng! 🤝
You have to embed IA in artificial worlds. The construction of training worlds for AI is the only way to arrive to AGI.
https://forum.effectivealtruism.org/posts/uHeeE5d96TKowTzjA/world-and-mind-in-artificial-intelligence-arguments-against
Do you think we would have to embody AI as OpenAI is doing with Figure? Or just create realistic worlds using something like the unreal engine to simulate physics and just let it play around in there?
The cheap solution is to create virtual realities, that probably will be valuable in themselves, and allow for ultra fast training.
That’s fascinating and I think has a lot of potential
In David Siver course on reinforcement learning there is an autonomous helicopter flying; they probably crashed thousands of virtual helicopters until the machine learned to pilot the real one.
https://m.youtube.com/watch?v=2pWv7GOvuf0
Minute 15
Super cool: my friend does this kind of thing. Allows you to simulate whatever you want and when you think you have a winner, create a real life mvp
Great explanatory piece from Matthew. I do have a question; do you all think we have entered a new chapter of human progress?
We had the first industrial revolution (1750), followed by the second (1870), followed by the IT revolution (1960).
Does 2020 mark the beginning of an AI revolution that is separate and distinct from the IT revolution?
I think so, the future is already here, it’s just not evenly distributed yet. And it will become increasingly obvious once we get agentic AI
Thanks for your well thought out response!
Completely agree. I’ve always thought that different queries should ping different parts of the model / architecture.
For example, the query “is the sky blue” ideally would only fire up a small language model since its not very complex and would require less compute and energy.
For a query about protein synthesis, fire up the large language model since it’s a more complex prompt.
For image / video generation use diffusion with reinforcement learning (Sora architecture)
And for agency use JEPA.
I don’t think many people grasp the implications of OpenAis new Omni-model. It combines many modalities we’ve been talking about into a single interface.
We’re still at the foundational layer and most of the applications have yet to be built.
Think the future is super bright and I’m so glad we can both be a part of it!