Arjun Karanam
① 他说过的话
8 条
这些模型越来越聪明，但当你和它们交谈时，总感觉像是它们上班的第一天。
指向原始笔记的链接
These models are smarter and smarter, but always feels like when you’re talking to them, it’s their first thing on the job.
—— Arjun Karanam · [01:23]
所以我们有这个与智商正交的经验轴，它的重要性远超我们的想象。
指向原始笔记的链接
And so we have this orthogonal axis of experience that is much more important than we think in conjunction with IQ.
—— Arjun Karanam · [01:44]
但更令人兴奋的是，它能让你达到这个目标：随着使用而复利增长的系统。
指向原始笔记的链接
But more excitingly, it gets you to this goal of systems that compound with use.
—— Arjun Karanam · [02:58]
在理想世界里，我能在你的 UI 上做的每一件事，你的智能体也能通过一次工具调用做到。
指向原始笔记的链接
In an ideal world, every single thing that I can do on your UI, your agent can do via a tool call as well.
—— Arjun Karanam · [09:34]
所以开始适应在开放权重上运行，因为那才是打开大门、让你拥有自己的权重并在此基础上持续改进的关键。
指向原始笔记的链接
So start getting comfortable running on open weights, because that is what unlocks the door to owning your weights and then continually improving on top of them.
—— Arjun Karanam · [10:52]
我们有一个非常非常核心的信念：这种拥有自己智能的能力，不应该在很多情况下都需要外包咨询。
指向原始笔记的链接
A really, really core belief we have is that this capability, this ability to own your own intelligence should not be something that you need to consult away a lot of the times.
—— Arjun Karanam · [12:43]
因为如果你做过后训练，你知道会有五千万个东西出问题、五千万个旋钮要拧，全靠研究人员的直觉，注册商标，星号，不管那是什么意思。
指向原始笔记的链接
because if you’ve post-trained, you know there’s like 50 million things that go wrong, 50 million knobs to turn, and it’s all researcher intuition, trademark, asterisk, whatever that means.
—— Arjun Karanam · [13:28]
但我们在一些客户那里看到的情况是，用户提出一些需求，模型勉强能做到，然后在训练过程中它学会了怎么做，之后用户就能做到以前做不到的事情了。
指向原始笔记的链接
But what we’re seeing with some of our customers are cases where users ask for things, the model can barely do it, but then during training it learns how to do it and then the user can now do this thing they couldn’t do before.
—— Arjun Karanam · [21:25]
② 出现在这些集
1 集
- 《经验差距：让智能体越用越聪明》 — 作为联合主持
③ 他谈到的
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