World-models are *the* crucial missing piece for AGI. Not just physics or graphics, but accurate models of economics and interpersonal relations are essential for AI to have any concepts of facts, goals, interests or plans, as well as for AI to have any way to evaluate the reliability of inputs, significance of events (including counterfactuals), and quality of outputs. Further, to align AI with each user (the only possible real alignment, alignment with abstract people is undefinable), there have to be not only common base world-models but forked versions for each group, further customized for each user and even task.
The problem is getting the AI to use the world-model (or tools in general) consistently. It may well require retraining from scratch, though it may be possible to largely replace fine-tuning and even some RL with direct editing of model weights using representation-engineering and related "mindspace navigation" techniques.
Thank you for sharing such valuable content. With this content, I learned that Shlomi is part of the paper: GameNGen. Now I'm learning more about his approaches for real-time world generation.
World-models are *the* crucial missing piece for AGI. Not just physics or graphics, but accurate models of economics and interpersonal relations are essential for AI to have any concepts of facts, goals, interests or plans, as well as for AI to have any way to evaluate the reliability of inputs, significance of events (including counterfactuals), and quality of outputs. Further, to align AI with each user (the only possible real alignment, alignment with abstract people is undefinable), there have to be not only common base world-models but forked versions for each group, further customized for each user and even task.
The problem is getting the AI to use the world-model (or tools in general) consistently. It may well require retraining from scratch, though it may be possible to largely replace fine-tuning and even some RL with direct editing of model weights using representation-engineering and related "mindspace navigation" techniques.
Thank you for sharing such valuable content. With this content, I learned that Shlomi is part of the paper: GameNGen. Now I'm learning more about his approaches for real-time world generation.