① 他说过的话

15 条

但我确实认为，拥有自己的智能这个理念真正的核心在于灵活性和控制权。
But I do think the idea of owning your intelligence really is about flexibility and control.
—— Yash · [02:58]

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我们的总体看法是，你的数据越偏离分布，后训练就越有可能真正给你带来那种能力提升。
Our general take has been like the more out of distribution your data is, the more likely that post training is actually going to give you that capabilities lift.
—— Yash · [08:30]

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那实际上将会是大多数企业把他们的判断专长固化的方式——基本上就是模型用得越多，它就变得越好。
That is actually going to be how most enterprises codify their judgment expertise by basically the more they use the model, the better that it gets.
—— Yash · [10:04]

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阻碍持续学习的，基本上就是从稀疏奖励中做到极其省数据的训练，这是一个未解决的问题。
What’s blocking continual learning is basically, like, extremely data-efficient training from sparse rewards, which is an unsolved problem.
—— Yash · [13:36]

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是的，我非常有信心，未来看起来像一组非静态的权重。
Yeah, I think we are pretty confident that the future looks like a non-static set of weights.
—— Yash · [14:59]

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如果每个人都用同样的模型，那么伟大的模型为大家设定了下限，但接下来你如何去优化那些模型并构建真正出色的 AI 系统，那才是设定上限的东西。
If everybody is using the same model, like great models sort of set the floor for everybody, but then how you go and optimize those models and build really amazing AI systems, that’s what’s going to set the ceiling.
—— Yash · [20:51]

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不，我觉得我们在 RL 上真正拥有的，本质上是一台爬山机器。
No, I think it’s actually what we have with RL is we essentially have a hill climbing machine.
—— Yash · [25:30]

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特定于你的业务运作方式的东西，并且你想让你的模型在这上面变得非常强，那么不告诉其他所有人好和坏长什么样，其实是对你有利的，这样别人就无法把他们的东西在那方面做得非常强。
Particular to how your business operates and you want to make your models really good at that, it’s actually to your advantage not to tell everybody else what good and bad looks like so people can go and make their things really good at that.
—— Yash · [26:03]

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但实际上，推理才是大部分价值捕获发生的地方。
But really, inference is actually where most of the value capture happens.
—— Yash · [27:39]

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所以我们的观点是，后训练实际上赢得推理。
And so what our view is is that the most post-training actually wins inference.
—— Yash · [29:24]

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后训练是这个技术栈里被严重忽视的一部分。
Hey, post-training is a massively underlooked part of the stack.
—— Yash · [36:10]

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前沿模型很了不起，但我没想到人们会如此在意真正地把成本优化好，为正确的任务使用正确的模型。
Frontier models are amazing, but I didn’t expect how much people would care about really cost-optimizing and using the right model for the right task.
—— Yash · [43:57]

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把框架和设计搞对，比任何实际的编码都重要得多。
It’s much more important to get the frameworks and design right than any of the actual coding.
—— Yash · [48:45]

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你不能把自己的思考委托出去、把它当作拐杖，因为那样你会得到这些庞大的、你根本解释不了的垃圾代码库。
You can’t delegate your thinking away and basically rely on it as a crutch because then you get these massive slop code bases that you can’t actually explain.
—— Yash · [48:59]

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所以对数据公司来说，我认为最需要擅长的事情就是转型，也就是从一个范式转到下一个范式。
So for data companies, I think the main thing to get really good at is pivoting, like going from each paradigm to the next.
—— Yash · [51:43]

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② 出现在这些集

2 集

• 《一封邮件睡出一万七千美金：Every 的 Builder Pack 内幕》 — 作为主持
• 《每家公司都该有自己的AI模型吗？》 — 作为主持

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