A 'world foundation model' (WFM), as used in this article, is a "model that can accurately simulate and predict outcomes in physical, real-world environments to enable the next generation of physical AI systems." Think of a WFM as similar to a large language model (LLM) except that instead of modeling patterns in language, these model patterns in real-world environments. Unlike in language, causation matters in real world environments, and so WFMs are expected to be able to predict real-world events much more accurately. "They can imagine many different environments and can simulate the future, so we can make good decisions based on this simulation." It's a pretty lightweight article for a pretty important concept, but I guess we have to start somewhere.
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