扬·勒昆

“You're not going to be able to do this with generative models.”

你无法用生成式模型来实现这一点。

“The reason we can do this is because the world is incredibly more complicated and richer in terms of information than text.”

我们之所以能（在语言上）成功，是因为世界在信息复杂度和丰富度上远超文本。

“Open source enables diversity, and that's the inevitable direction of history.”

开源实现了多样性，而这是历史的必然方向。

“If you're really interested in human-level AI, abandon the idea of generative AI.”

如果你对达到人类水平的AI真正感兴趣，那就放弃生成式AI的想法。

“We're going to have systems that are as smart as a cat, and then we're going to walk our way up to make those things more intelligent.”

我们将先拥有像猫一样聪明的系统，然后逐步让它们变得更智能。

“It's quite possible that intelligence is just statistics, it's just statistics of a particular kind.”

智能很可能只是统计，但是一种特定类型的统计。

“The essence of intelligence is the ability to predict, and everything the brain does is trying to predict everything from everything else.”

智能的本质在于预测能力，大脑所做的一切都是试图用一切来预测一切。

“The big challenge of AI for the next decade is how do we get machines to learn pretty accurate models of the world that deal with uncertainty and deal with the real world in all its complexity.”

未来十年AI的重大挑战在于，如何让机器学习能够应对不确定性及现实世界所有复杂性的、相当精确的世界模型。

“I believe in grounded intelligence. I don't think we can train a machine to be intelligent purely on text, because the amount of information about the world that's contained in text is tiny compared to what we need to know.”

我坚信具身智能。我不认为仅靠文本就能训练出智能的机器，因为文本中包含的世界信息量与我们所需知道的相比微不足道。

“We've been writing laws for millennia, and that's exactly what it is.”

我们已经制定了数千年的法律，而这（设计目标函数）正是它在做的事。

“Machine learning is the science of sloppiness really.”

机器学习本质上是一门关于“粗糙”的科学。

“We have predictive models of the world that include the ability to predict under uncertainty.”

我们拥有对世界的预测模型，其中包括在不确定性下进行预测的能力。

“We're not going to have autonomous intelligence without emotions.”

没有情感，我们无法拥有自主智能。

“Intelligence is inseparable from learning.”

智能与学习密不可分。