Simulating everything, sort of: The promise and limits of world models
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.
Reported by 1 outlet — Ars Technica. See all sources ↓
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.Read full article Comments
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- What's the story?
- 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.
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- 1 outlet, average source rating 7.0/10.
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Simulating everything, sort of: The promise and limits of world models
Sources1TypeCoverageArs Technica