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World Labs联合创始人：空间智能的'新视角预测'是AI完备的原始任务
World Labs联合创始人Justin Johnson和Fei-Fei Li在访谈中提出，空间智能的'新视角预测'（new-view prediction）类似于LLM的'下一token预测'，是AI完备的原始任务。Johnson引用Ilya的例子说明下一token预测的AI完备性，并认为Atlas中的生成式新视角预测同样AI完备。Fei-Fei指出进化通过运动解决新视角预测问题，强调其重要性。
AI推荐理由 World Labs联合创始人Justin Johnson和Fei-Fei Li阐述空间智能的'新视角预测'与LLM的'下一token预测'类比，提出AI完备性概念，观点新颖且具理论深度，但为访谈性内容，缺乏实证数据。
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World Labs 联合创始人 Justin Johnson 和 Fei-Fei Li 博士表示，LLM 使用下一个词元预测，但空间智能有其自身的等价物：
Justin：“AI 完备性的软定义是存在一个作为 AI 任务的基本原语。但如果我能以最全面、最广泛的方式解决这个 AI 任务，它将解决任何智能问题。”
“LLM 中的经典例子是下一个词元预测是 AI 完备的……我想从 Ilya 那里听到：有一本神秘小说，必须读完整本小说，最后一句话是‘凶手是’。预测下一个词元。你基本上可以把任何智能任务都框定在这个框架中。”
“所以显然下一个词元预测是人们相信是 AI 完备的。”
“新视角预测，我们在 Atlas 中拥有的这个原语，尤其是生成式新视角预测，也是 AI 完备的。”
“我想要一个世界，Martin 在黑板上写黎曼猜想的证明，然后镜头摇到下一个白板。”
Fei-Fei：“进化必须通过让动物移动来解决新视角预测问题。大自然给了动物眼睛，但没有给树眼睛。为什么？因为当你移动时，你会看到一个新的视角……我们坚信下一个视角预测等同于下一个词元预测。”
@jcjohnss @drfeifei @martin_casado
查看原文（中文正文为 AI 翻译）
World Labs co-founders Justin Johnson and Dr. Fei-Fei Li say LLMs use next-token prediction, but spatial intelligence has its own equivalent:
Justin: "The soft definition of AI-completeness is there's this fundamental primitive that's an AI task. But if I could solve this AI task in its full, broadest generality, it would solve any intelligence problem."
"The classic example in LLMs is that next-token prediction is AI-complete... I think from Ilya: there's a mystery novel, the thing has to read the whole novel, and the final sentence is, 'And the killer was.' Predict the next token. You could basically frame any kind of intelligence task in terms of that."
"So clearly next-token prediction is something people believe is AI-complete."
"New-view prediction, this primitive that we have in Atlas, especially generative new-view prediction, is also AI-complete."
"I want to have a world where Martin is writing a proof of the Riemann hypothesis on the blackboard, and then the camera pans over to the next whiteboard."
Fei-Fei: "Evolution had to solve new-viewpoint prediction by making animals move. Nature gave animals eyes, but nature didn't give trees eyes. Why? Because when you move, you see a new viewpoint... We do believe very strongly that next-viewpoint prediction is the equivalent of next-token prediction."
@jcjohnss @drfeifei @martin_casado