“A very distinguishing aspect of interacting with an LLM is they are turn-based.” Meaning, users type some text, there’s a pause, and then they get a block of text back. By contrast, he sees a world model as a synchronous, real-time system.
“Something that would define a world model is the degree of freedom that you have . . ."
Fei-Fei Li, the computer vision pioneer who co-founded World Labs, one of the new companies working on world models. In a Substack post late last year, she wrote:
Today, leading AI technology such as large language models (LLMs) have begun to transform how we access and work with abstract knowledge. Yet they remain wordsmiths in the dark; eloquent but inexperienced, knowledgeable but ungrounded. Spatial intelligence will transform how we create and interact with real and virtual worlds—revolutionizing storytelling, creativity, robotics, scientific discovery, and beyond. This is AI’s next frontier.
LeCun and Li’s ventures are built on these ideas, so it’s not surprising they’d say these things. But you’ll also see similar sentiments from some prominent figures still working primarily with LLMs.
“I think we’re in an LLM bubble, and I think the LLM bubble might be bursting next year,” said Clem Delangue, the CEO of Hugging Face—a platform that hosts repositories of LLMs of all stripes.
“But ‘LLM’ is just a subset of AI when it comes to applying AI to biology, chemistry, image, audio, [and] video,” Delangue added, speaking at a conference. “I think we’re at the beginning of it, and we’ll see much more in the next few years.”
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