The term is used loosely; not everything marketed as a “world model” qualifies in the strict architectural sense.
The bet, and the reason LeCun rejects video-generators like Sora, is that a model trained on how a system behaves rather than how it looks, an architecture he calls JEPA, will generalize better to the physical world. It is not a product category but an architecture that could take AI from fluent at language but with no real model of the physical world, to a grounded understanding of how that world behaves.
If they are right, this is more than another commercial AI cycle. It is the period in which the substrate of the next AI gets built, and what gets built now, by whom and on what data, will shape what AI can do for years. The potential for solving problems in climate, oceans, the biosphere, and the biology of disease is vast.
What AI has already accomplished for the Earth
I started my career as a climate scientist at NASA running ocean-atmosphere simulations on supercomputers. I later co-wrote, with the World Economic Forum and Microsoft’s chief environmental officer, two of the earliest reports on AI and the Earth system. A lot of what we predicted has happened.
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