As we know, one of the godfathers of AI recently left Meta to found his own lab AMI and the the underlying theme is his longstanding focus on world modelling. This is still a relatively underexplored concept however the recent surge of research suggests why it is gaining traction.
For example, Marble demonstrates how multimodal models that encode a sense of the world can achieve far greater efficiency and reasoning capability than LLMs, which are inherently limited to predicting the next token. Genie illustrates how 3D interactive environments can be learned and simulated to support agent planning and reasoning. Other recent work includes SCOPE, which leverages world modelling to match frontier LLM performance (GPT-4-level) with far smaller models (millions versus trillions of parameters), and HunyuanWorld, which scored ~77 on the WorldScore benchmark. There are also new models being developed that push the boundaries of world modelling further.
It seems the AI research community is beginning to recognize the practical and theoretical advantages of world models for reasoning, planning, and multimodal understanding.
Curious, who else has explored this domain recently? Are there emerging techniques or results in world modelling that you find particularly compelling? Let us discuss.
ps: See the comments for references to all the models mentioned above.
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