🔥为什么 GPT 都能画画、写代码了,机器人连端盘子都端不稳?
看了
@huang_biwei 博士讲的“相关性”和“因果”,我终于理解了。
✔️ 现在的大语言模型,本质上是在海量文本里学习“什么经常一起出现”,是一种概念推测。
看到 define,后面大概率是 function;
看到一张图,后面大概率是某种风格的生成。
✔️ 可机器人不一样。
机器人真需要能理解物理规律、因果关系和行动后果的 AI 世界模型。
· LLM 解决的是相关性智能。
· 机器人需要的是因果智能。
Aether AI,便是致力于困果智能的研究。
成功拿到巨额融资。
I've spent over a decade working on causal discovery and causal AI. A lot of late nights, a lot of papers, and a lot of open questions.
Today we're putting something into the world. Aether AI has raised $20M to build causal world models that understand mechanisms. We believe the next leap in AI will come not from scaling existing architectures, but from a paradigm shift in how machines learn, reason, and interact with the world.
If you care about causality and want to build, we're hiring!
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