Simulating everything, sort of: The promise and limits of world models
Experts explain how they work, what they can do, and what's still unsettled.
Over the past few years, many of us have gotten a crash course in what we now call artificial intelligence—but really, it has mostly been a crash course in large language models. Increasingly, however, LLMs are no longer the only category of AI drawing high expectations, massive funding rounds, and significant research and product development.
Over the past year, we've seen a plethora of new announcements in a category labeled "world models," and you'll likely see more movement there in the coming months and years.
Instead of or in addition to working with language, world models aim to lay the groundwork for AI systems that are capable of simulating the physical world, or at least a useful approximation of it.
This story was first published by Ars Technica. Read the original report