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AI

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你真正能构建复利价值的唯一方式，是你的系统里存在某种能给你带来复利优势的东西，让未来的 AI 工具能够持续加以利用。
The only way you can actually build compounding value is if in your system there is something that gives you a compounding advantage that future AI tools can continue to take advantage of.
—— Rishabh Jain · [27:31]

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我认为 Gen.AI 有潜力把软件的价值从「我是否拥有一个网络产品的登录账号」转向更偏向基于结果的导向。
I think Gen.AI has the potential to shifting the value of software away from, do I have a login into a web product that I have access to, into more of an outcome-based orientation?
—— Alvaro Morales · [13:54]

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我在整个职业生涯中构建过很多工作流软件，如果你只是给工作流构建器加一个 AI 步骤，那它不是智能体，而且它很可能是在极其做空和看空 LLM，我认为这个房间里没有人是这样想的。
I’ve built a lot of workflow software, you know, throughout my career, and if you’re just adding, you know, an AI step to a workflow builder, it’s not an agent, and it’s also probably incredibly short and bearish on LLMs, which I don’t think anyone in this room is.
—— 嘉宾 · [15:43]

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我不认为我在过去三个月里写过一行 HTML 或 JavaScript，但 Base44 的前端仍然变化很大，因为 AI 在写那些东西。
I don’t think I’ve written a single line of like HTML or JavaScript in the past three months, but still the Base44 front end changes a lot because AI writes that.
—— Maor Shlomo · [33:27]

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我认为 AI 可能是推动美国就业回流的最大力量之一。
I think that AI may be one of the biggest force for reshoring American jobs.
—— Dan Shipper · [05:05]

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所以我注意到的是，你可以通过你可以给它多长的”绳子”去工作来判断 AI 变好了多少。
And so what I have noticed is that you can tell how much better AI is getting by how long a leash you can give it to do work.
—— Dan Shipper · [14:57]

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如果你正在构建一个智能体 AI 产品，它切入的是劳动力预算，劳动力预算相比软件预算是 10 倍的规模。
If you’re building a agentic AI product that taps into labor budgets, labor budgets are 10X compared to software budgets.
—— Madhavan Ramanujam · [28:33]

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对于 AI 来说，生成这东西是一个可笑的糟糕选择，因为它是史上效率最低的编程语言之一。
It’s such a comically bad thing for AI to generate just because it’s one of the most inefficient programming languages of all time.
—— Bret Taylor · [39:42]

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我认为我们需要更多类似的东西，因为如果 AI 正在生成这些代码，根据定义，如果你必须阅读每一行，那将是生产代码的制约因素，或者更糟的是，你只是不会阅读每一行，而且你将向世界发布一堆不安全、未经验证的代码。
I think we need more things like that because if an AI is generating this code, by definition, if you have to read every line that is going to be the limiting factor for producing the code or worse, you’re just not going to read every line and you’re going to emit a bunch of unsafe unverified code into the wild.
—— Bret Taylor · [41:16]

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AI 技术变革是一场尚未伴随渠道变革的技术变革。
the AI technology shift has been a technology shift that has not come with a distribution shift yet.
—— Brian Balfour · [08:49]

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我对谦卑的简略说法是，谦卑就是可教性。什么时候你需要可教性？当一切都改变了，没有蓝图时，你需要可教性，无论你在过去几年认为什么是AI的蓝图，无论是，“噢哇，Lovable太成功了。Replit太成功了。“实际上这些公司中的任何一家在两三年后都可能不存在了，对吧？
I think the shorthand I have for humility is humility is teachability. And when do you need teachability? You need teachability when everything has changed, where there is no blueprint and whatever you think is a blueprint of AI in the last few years, whether, “Oh wow, Lovable is so successful. Replit is so successful.” It’s actually quite possible that any one of those companies won’t be around in two, three years, right?
—— Oji · [27:42]

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AI在核心意味着从根本上审视问题空间和工作流，并使用AI来解决问题，而不仅仅是在GUI或用户界面的交叉点上撒一点，或者仅仅用它来加速事情。
AI at the core means fundamentally looking at the problem space and the workflows and using AI to solve the problem, not just sprinkling it at the intersections of GUIs or user interfaces that are out there or using it to just accelerate things.
—— Ezinne Udezue · [41:05]

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所以我实际上把 eval 视为一种非常有效的方式来为你的人类时间排定优先级，这样你就能有效地利用你的时间来改进 AI 系统。
And so I think of evals actually as a very effective way to prioritize your human time so that you can use your time effectively to improve the AI system.
—— Ankur Goyal · [16:49]

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这让我内心有很强的信念：八年之后，评估仍然会非常重要，而且它们会成为人们构建优秀 AI 软件的核心驱动力。
And that gives me a lot of internal conviction that eight years from now, evals will still be very relevant and they’ll be kind of like the core driver for how people build great AI software.
—— Ankur Goyal · [00:29]

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但现在有了 AI 和我的同伴，就像是，等等，AI 使得让我自己做许多这些工作成为可能。现在，我不会在所谓的博士或最高 1%、10% 的水平上做这些。但如果我处于第 0 或第 10 百分位，它肯定可以让我即使在今天也很快达到就最先进水平而言的第 60、70 百分位。
But now with AI and my companion, it’s like, wait a second, AI makes, allows me to do many of those jobs myself. Now, I’m not going to do them at the what’s called the PhD or the highest 1%, 10% level. But if I was at the zero or 10th percentile, it can certainly get me even today very quickly up to like the 60th, 70th in terms of what the state of the art is.
—— Julie Zhuo · [15:08]

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但现实是，至少就目前而言，AI 模型吐出的很多代码在根本上并不安全。
But the reality is, at least as it sits today, a lot of code that AI models spit out is not fundamentally secure.
—— Vineet Edupuganti · [05:48]

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那种上下文无法进入人脑，但它可以进入 AI 的上下文窗口。
That context can’t go into a human brain, but it can go into the AI context window.
—— Evan Reiser · [08:04]

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你还必须愿意接受 AI 至少在某些时候能比你的某些人类做出更聪明的决策。
You have to also be willing to accept that the AI can make smarter decisions than at least some of your humans some of the time.
—— Evan Reiser · [15:06]

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我们在过去几十年里建立了一整套保护人类的原则和控制措施，但没有任何人在思考我们如何保护这些 AI 智能体。
There’s this whole set of principles and controls that we’ve built up over the past few decades to go and protect the human, and nobody’s thinking at all about how do we secure these AI agents.
—— Vineet Edupuganti · [25:31]

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我认为正向工作与倒推工作之间的重大区别是，是人类在启动 AI，还是 AI 在启动人类，对吧？
I think the big difference between kind of the work forward versus work backwards is, you know, are humans initiating the AI or is AI initiating kind of the humans, right?
—— Evan Reiser · [26:27]

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有时候经验可能是一个拐杖，特别是在这个世界，在这个 AI 让地面变化如此之快的世界。
Sometimes experience could be a crutch, especially in this world where the grounds are shifting so fast with AI.
—— Albert Cheng · [01:03]

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我认为这里的论点是：如果你行动得不够快、没有变得 AI 优先，在我看来你就面临巨大的风险，会被其他这么做的公司颠覆。
I think the sort of the thesis over here is that if you don’t move fast enough to sort of become AI first, you are at a huge risk in my opinion of being disrupted by somebody else who does.
—— Roshan · [26:11]

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但我认为真正的机会在于，AI 不需要你遵守一条黄金路径。
But I think that really the opportunity is that AI need not require you to abide to a golden path.
—— Mayank · [28:18]

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我们看到的是这并没有改变。在很多方面，AI 并没有真正改变那些基础需求，我们发现 AI 是扩张性的，因此实际上有更多的问题被提出，现在可以用 AI 满足的好奇心。
And what we see is that it’s not changing. AI hasn’t really changed those foundational needs in many ways, and what we’re finding is that AI is expansionary, and so there’s actually just more and more questions being asked and curiosity that can be fulfilled now with AI.
—— Robby Stein · [08:42]

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互联网的诞生是为了所有人利益的开放信息共享的承诺，我认为 AI 应该为我们实现这一点。
The internet was created as a promise for open sharing of information to the benefit of all, and I think that AI should realize that for us.
—— Dhanji Prasanna · [85:51]

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我们试图在 AI 真正成为一件事之前做 AI,因为它真的对我们试图做的事情非常关键,即使是在我们 2012 年的幻灯片中。
We were trying to do AI before AI was actually a thing because it really was critical to what we were trying to do even in our 2012 deck.
—— Melanie Perkins · [53:43]

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我在两个半世纪前开始研究 AI,在过去二十年里我几乎每个学生毕业时,我都提醒他们,你的领域叫人工智能,但其中没有任何人工的成分。
I started working AI two and a half decades ago, and I’ve been having students for the past two decades and almost every student who graduates, I remind them when they graduate from my lab that your field is called artificial intelligence, but there’s nothing artificial about it.
—— Dr. Fei-Fei Li · [08:01]

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人类历史上没有哪一个深刻的科学学科到达了一个说我们完成了、我们不再创新的境地,而人工智能是——如果说不是人类文明中——最年轻的学科之一,就科学和技术而言,我们还在挠皮毛。
There’s not a single deeply scientific discipline in human history that has arrived at a place that says we’re done, we’re done innovating and AI is one of the, if not the youngest discipline in human civilization in terms of science and technology, we’re still scratching the surface.
—— Dr. Fei-Fei Li · [27:01]

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在 AI 时代，单点解决方案没有足够的数据来发挥作用。
Point solutions don’t have enough data in the age of AI to be useful.
—— Matt MacInnis · [78:36]

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这将会扼杀我现在看到的 80% 或 90% 作为独立 AI 业务的东西。
That is going to kill off 80 or 90% of the stuff that I see right now as standalone AI businesses.
—— Matt MacInnis · [80:45]

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AI 正在取代人们今天不想做的工作，并且它正在挤出中游和平庸的人。
AI is replacing the jobs people don’t want to do today, and it is displacing the midpack and the mediocre.
—— Jason Lemkin · [00:31]

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基于邮件节奏的 SDR 明年将被 AI 取代 90%。
The email-based cadence SDR will be 90% displaced by AI next year.
—— Jason Lemkin · [19:49]

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在我们看到的所有这些 AI 进展中，一个容易的、滑坡式的错误就是只考虑解决方案的复杂性，而忘记你试图解决的问题。
In all this advancements of the AI that we are seeing, one easy, slippery slope is to just keep thinking about complexities of the solution and forget the problem that you’re trying to solve.
—— Aishwarya Reganti · [21:00]

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但现在有了 AI，这些直觉必须重新学习，领导者必须变得脆弱去做这件事。
But now with AI in the picture, those intuitions will have to be relearned and leaders have to be vulnerable to do that.
—— Kiriti Badam · [26:20]

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不是你会被 AI 取代。你会被一个更擅长使用 AI 的人取代。
It’s not that you will be replaced by AI. You’ll be replaced by someone who’s better at using AI than you.
—— Lenny · [00:54]

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AI 擅长挑选主题。它不擅长挑选可操作的细节。
AI is good at picking out themes. It is bad at picking out details that are actionable.
—— Jason Cohen · [30:38]

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那些真正想要提升自己和发展职业生涯的人，在我看来，现在应该把每一个空闲小时都用来与 AI 交谈，就像说，“好吧，培训我。“
People who really want to improve themselves and develop their career should be spending every spare hour, in my view, at this point, talking to AI, being like, “All right, train me up.”
—— Marc Andreessen · [01:20]

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我们实际上需要 AI 发挥作用，因为我们将需要机器来做所有我们没有人力去做的那些工作，因为在未来 100 年里，我们在字面上将使地球人口减少。
And we actually need AI to work because we’re going to need machines to do all the jobs that we’re not going to have people to do because we’re literally going to depopulate the planet over the next 100 years.
—— Marc Andreessen · [10:59]

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如果目标是成为一名平庸的编码员，那就让 AI 去做吧。没问题。AI 将非常擅长生成无限的平庸代码。
If the goal is to be a mediocre coder, then just let the AI do it. It’s fine. The AI is going to be perfectly good in generating infinite amounts of mediocre code.
—— Marc Andreessen · [47:37]

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我们不会在 AI 世界中因为更快的原始产出而获得回报；我们会因为更好的判断力而获得回报。
We won’t be rewarded in the world of AI for faster raw output; we will be rewarded for better judgment.
—— Lazar Jovanovic · [20:24]

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AI 的另一个坏特质是，它会尽力不伤害你的感情，永远不会说”你是那个笨蛋”。它说”不，我是那个笨蛋”。
Another bad trait of AI, is it does its best not to hurt your feelings and never say, “You’re the dumb one.” It says, “No, I’m the dumb one.”
—— Lazar Jovanovic · [40:36]

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AI 的上限不是模型智能，而是模型在行动之前看到的东西。
The ceiling on the AI isn’t the model intelligence, it’s what the model sees before it acts.
—— Lazar Jovanovic · [44:21]

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再说一次，只要把自己剔除并转移上下文，你就解决了今天 99% 的 AI 问题。
Again, just eliminate yourself and move the context, you solve 99% of the problems with AI today.
—— Lazar Jovanovic · [75:21]

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在 AI 领域，听取客户的意见并不总是正确的策略。
Listening to customers is not always the right strategy in AI.
—— Lenny · [00:48]

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如果你在构建一个 AI 产品，除了评测之外做任何事都没有意义。一切都应该围绕你的评测展开。
if you’re building an AI product, there’s no point doing anything other than evals. Everything should revolve around your evals.
—— Ankur Goyal · [03:18]

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因为他们内部正在进行严肃的讨论：要么想办法围绕 AI 重建产品，要么死。
because they’re having serious discussions internally about how it’s either figure out how to rebuild our product around AI or die.
—— Ankur Goyal · [18:40]

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我认为人类的生存取决于成功的 AI。
I think that survival of humanity depends on a successful AI.
—— Jeetu Patel · [07:52]

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我们解决一些不可能的问题，比如癌症，将直接与这次 AI 繁荣有关。
Us solving some of these impossible problems like cancer are directly going to be related to this AI boom.
—— Qasar Younis · [00:21]

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AI 在未来 5 到 10 年的真正影响将真正是在农业、采矿和建筑领域。
The real impact of AI in the next 5 to 10 years really is going to be in farming, mining, construction.
—— Qasar Younis · [00:36]

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但你可能会看到一家公司裁员 3 万人，然后招聘 8 000 人，但他们要招聘的这 8 千人将全部是 AI 至上的。
But you might see a company shed 30,000 and hire 8,000, but the 8,000 people they’re going to hire are going to all be AI first.
—— Nikhyl Singhal · [22:34]

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15 年前，我们基本上认识到软件不是护城河，这是今天每个人都在通过 AI 发现的事情。
15 years ago, we essentially learned that software is not a moat, which is something that everyone is discovering today with AI.
—— Evan Spiegel · [10:24]

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我认为技术领导人们认为人们只会盲目地采用发布的新技术。我认为我们将进入一个时期，对于即将随着 AI 到来的许多变化，社会上将会有巨大的阻力。
I think technology leaders think that folks will just blindly adopt new technology as it comes out. And I think we’re going to enter a period of time where there’s going to be a huge amount of societal pushback on a lot of the changes that are coming with AI.
—— Evan Spiegel · [64:47]

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它是早期 AI 公司的例子之一，在几个月内从零做到了大约 1000 万美元的 ARR。
It was one of the early example of AI companies that went from zero to like 10 million ARR in like a few months.
—— Amjad Masad · [00:05]

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AI 将在未来非常重要和丰富，并不一定意味着所有的价值都将被这些 AI 实验室捕获。
AI is going to be hugely important and abundant in the future does not necessarily mean that all the value is going to be captured by these AI labs.
—— Patrick Collison · [25:00]

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AI 末日（jobpocalypse）并不是真的存在。
The AI jobpocalypse is not really a thing.
—— Dan Shipper · [00:10]

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我同时极其 AI 信奉（pilled）且非常看好人类。
I’m simultaneously extremely AI pilled and very bullish on humans.
—— Dan Shipper · [00:24]

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你的公司的发展程度只能达到你的 CEO 在 AI 方面的发展程度，而且这是你不能委托的事情。
your company’s only going to go as far as your CEO goes in AI and it’s not something you can delegate.
—— Dan Shipper · [59:28]

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我认为 AI 的前沿是 AI 遇到真实的人做事情的地方
I think the edge of AI is wherever AI meets a real human doing something
—— Dan Shipper · [78:48]

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让我担心的是，拥有数亿美元的 AI 研究人员正在新西兰买房。好像有什么末日要来，他们正往地球最边缘跑。
it’s worrying me that AI researchers with hundreds of millions of dollars are buying houses in New Zealand. Like, there’s some an apocalypse coming, and they were going to the farthest edge of the planet.
—— Matt Carey · [14:44]

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我最具争议的观点是，我认为 AI 和互联网或移动技术一样重要，但也只和互联网或移动技术一样重要。
My most controversial opinion is that I think that AI is as big a deal as the internet or mobile, and only as big a deal as the internet or mobile.
—— Benedict Evans · [00:00]

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实际上我认为人们会在国防行业感到惊讶，我们的行业周围可能比大多数商业行业有更多的护栏和负责任的 AI 努力。在美国这里有联邦法规禁止某些事情，而在商业领域人们为了安全问题可能只是激增并去做。
I actually think people would be surprised in the defense industry that there is probably more guardrails and responsible AI efforts around our industry than most commercial industries. There are federal regulations here in The US that prohibit certain things that in the commercial space people might just surge and go do in terms of safety issues.
—— Chris Benson · [22:38]

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就在去年，AI 研究人员和开发人员搬到美国的数量下降了 80%
there’s been an 80% decline just in the last year in terms of the number of AI researchers and developers moving to The US
—— Daniel Whitenack · [28:11]

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可能目前 90% 以上拥有 AI 部署的组织、企业并没有按照这个模式运作。他们根据这个框架，会完全暴露。
Probably 90% of plus of of organizations, enterprises that have AI deployments currently are not operating according to this model. They are according to this framework, they would be completely exposed.
—— Daniel Whitenack · [12:02]

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我认为 AI 更多被用来在三个月内构建一个想法,而不是一天内构建 100 个想法。
I think AI is being used more to build one idea in three months than a hundred ideas in a day.
—— Mark Pincus · [36:17]

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在 AI 时代，生产软件的成本正在趋近于零。
In the AI era, the cost of producing software is going to zero.
—— John · [07:04]

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我认为很多所谓的 AI 原生公司就像是路线图消失了，规划消失了，一切都消失了。
I think a lot of quote unquote AI native companies are just like roadmaps are gone Planning is gone. Everything is gone.
—— Jiaona Zhang · [40:01]

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我认为这是因为 1 个 PM 可以做比以往任何时候多得多的事情，但没有那么多有这种技能、有那种判断力、是 AI 化的、无畏地经历所有这些环节的人，而且顺便说一句，他们要知道 PM 角色中最重要的事情永远且永远不会改变的是他们必须贴近客户。
I think it’s because 1PM can do so much more than ever before, but there aren’t that many of them who are that skilled, that have that judgment, who are AI-pilled, who fearlessly are going through all of these pieces and, by the way, know that one of the most important things forever and will never change about the PM role is that they have to stay close to their customers.
—— Jiaona Zhang · [61:32]

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人们谈论 AI 极其疯狂的末世特征，这通常是在模型发布之前，而通常也是在融资之前。
People talking about the insanely apocalyptic characteristics of AI leading up to a model release, which usually was leading up to a fundraising.
—— Chamath · [12:36]

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与此同时,我们知道的一件事是,我们使用的 AI 越多,不知何故,我们要雇佣的人就越多。
Meanwhile, one of the things that we know is that the more AI we use, somehow, the more people we have to hire.
—— Jensen Huang · [22:15]

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我认为那些能充分利用它的人,是那些对AI擅长什么和不擅长什么有清醒认识的人,并且对它将来会擅长什么和不擅长什么有一种本能或嗅觉。
the people who i think are gonna make the most of it are the ones who are clear-eyed about what ai is good at and what it’s not good at and also have an instinct or a nose for what it will be good at and not good at
—— Adam Mosseri · [19:21]

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如果你只是懒惰地向AI索要一个策略,你不会得到正确的东西,你会得到一些非常可预测的、竞争对手都会预期你会去做的事情。
if you ask an ai just for a strategy lazily you’re not going to get something right you’re going to get something pretty predictable that pop up with the competition would expect you to do
—— Adam Mosseri · [26:58]

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我不认为我们应该过滤掉AI内容,我认为我们应该让你知道内容是否是AI内容,我认为我们应该让你更多地了解发布任何内容的人。
i don’t think we should filter out ai content i think we should let you know if content is ai content or not i think we should let you know more about the person who posted anything
—— Adam Mosseri · [44:32]

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你不再是公司里的官僚角色、政治角色，不再有人需要那个了，因为 AI 可以在一定程度上应付那些
you’re no longer the the bureaucracy player the politics player in the company nobody needs that anymore because ai can kind of juggle around that
—— Meng To · [66:47]

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最终的结局大概是你创办自己的公司，因为有了 AI，你不再需要害怕创办公司了，因为 AI 可以为你处理所有的文书工作
the end game is probably that you starting your own company because ai you don’t need to be scared of starting a company anymore because ai can take care of all the paperwork for you
—— Meng To · [68:34]

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我们不会让你用 AI 伪造你是谁。
We will not let you falsify who you are with AI.
—— Whitney Wolfe Herd · [16:58]

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软件吞噬了世界，然后 AI 吞噬了软件。但现在我们要说的是，AI 工程师正在吞噬世界。
Software ate the world, and then AI ate software. But now, what we’re here to say is that the AI engineers are eating the world.
—— Romain Huet · [01:21]

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你想一下戴着安全帽的 AI，那就是我们。
You think about AI with a hard hat on, that’s us.
—— Kriti Sharma · [01:44]

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我实际上首先要指出的是，只有 3% 的人报告说 AI 没有改变他们的身份。
And I’ll actually call out, first of all, that only 3% of people reported that AI hasn’t shifted their identity.
—— Noam Segal · [08:52]

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我被迫使用 AI 否则就会失去我的工作。
I’ve been forced to use AI or lose my job.
—— Noam Segal · [17:22]

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关于这要说的第二点是，每次你，是你，不是 AI，解决了一个问题并克服了一个障碍，它都会提高你的自我效能感、自信心、自我信念的基线。
Every time you, you, not the AI, solve a problem and get over a barrier, it increases, it raises your baseline of self-efficacy, of self-confidence, of self-belief.
—— Noam Segal · [52:01]

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“因 AI 而失去工作”实际上在榜单上倒数第二。
Losing my job to AI is actually second to last on that list.
—— Noam Segal · [53:45]

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我们开始看到这种 AI 内疚感，特别是在那些职业生涯早期的人中，意思是那些职业生涯早期的人觉得利用这项技术有点像作弊。
We’re starting to see this AI guilt, and in particular, amongst people who are early in their career in the sense that people who are early in their career feel like leveraging this technology is a little bit like cheating in a sense.
—— Noam Segal · [92:08]

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研究表明,AI 生成的技能文件不如人工编写的技能文件有效
research has shown that AI generated skill file is less effective than human written skill files
—— Jyothi Nookula · [30:46]

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我是不是把 AI 告诉我的第一件事就当作「这很棒」并且把它收尾,还是我在审视这些事情说好吧这很好,但是这种边缘情况怎么办
am I just taking the first thing that the AI tells me as like this is great and wrapping it up or am I looking through things to say okay this is good but what about this edge case
—— Jyothi Nookula · [76:59]

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我们都给了 AI 太多的赞誉，高估了它能做的事。
We all give too much credit for AI and what it can do.
—— Avishai Abrahami · [33:21]

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如果说 ChatGPT 之于 AI,就像 Netscape Navigator 之于互联网——在互联网繁荣的这个时间点，Google 还没有创立。
And say that ChatGPT is to AI as Netscape Navigator was to the internet. At this point in the internet boom, Google had not been founded.
—— David George · [10:46]

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鉴于我们刚才讨论的内容，在 AI 领域取得成功却不承受毛利率压力，从定义上讲是不可能的。
It is definitionally impossible, given what we just discussed, to succeed in AI without gross margin pressure.
—— David George · [15:53]

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而那个飞轮，在 AI 领域还没真正转起来，但你眯起眼睛可以看到它在转。
And that, it’s not quite spinning yet in AI, but you can squint and see it.
—— David George · [21:37]

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从根本上说，人类是按结果获得报酬的，很多 AI 会增强人类，但可能也会取代一部分人类，而这将涉及按结果付费。
Humans were fundamentally paid based on outcomes, and a lot of AI will be augmenting humans, but probably also replacing some humans, and that will involve being paid for outcomes.
—— David George · [27:31]

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就像产品内的 AI，大概比在组件上进行 AI 编码领先两年。他们已经有了评估系统，已经有了可观测性系统。
Like AI product, AI inside the product is probably two years ahead from AI coding on components. They already have the eval system, they already have an observability system.
—— Patrick Debois · [17:13]

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我认为不管是现在的 AI 还是敏捷或任何变化，听起来很难，但在开始时不要在消极的事情上花时间。找到成功的故事。如果你不能让它成功，其余的都不会起作用。
I think regardless whether this is now AI or like agile or any change, um, as hard as it sounds, do not spend time on the negatives in the beginning. Find the success story. If you can’t make that work, the rest will not work.
—— Patrick Debois · [33:58]

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所以对这一年的 AI 开发来说很棒的东西，很可能对下一年的 AI 开发来说就不那么棒了。
So what might be awesome for one year’s worth of AI development will probably not be awesome for the next year’s worth.
—— 嘉宾 · [17:28]

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但无论是我们还是别人，大约五年后销售领域的品类领导者、记录平台，将是一个以 AI 为核心架构的平台，而不是一个 20 年前架构的平台，这一点似乎是定局。
But whether it’s us or somebody else, it seems a foregone conclusion that the category leader, the platform of record in sales in, let’s call it five years, will be a platform that is architected with AI in mind and not one that was architected 20 years prior.
—— Sam Blond · [31:14]

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AI 是一个很棒的”某物”桶。它是共识错觉的终极体现。你能用 AI 做点什么吗？你到底什么意思？你能用电脑做点什么吗？这差不多是一回事。
AI is such a great something bucket. It’s the ultimate illusion of agreement. Can you do something with AI? What the fuck do you mean? Can you do something with computer? That makes about as much sense.
—— David · [19:49]

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我们确实相信，递归的世界离我们并不遥远——AI 将设计它自己所需的系统，来训练和运行下一代 AI，包括这个。
We do believe that the world of recursion is not that far, where AI will design the systems it needs to train and run the next generation of AI, including this.
—— Sachin Katti · [00:21]

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现在，AI 本身可以做 AI 研究了。我们能做的实验数量爆炸式增长。因此，研究所需的算力也爆炸式增长。
Now, AI itself can do AI research. The number of experiments we can run explodes. And therefore, the amount of compute you need for research also explodes.
—— Sachin Katti · [16:50]

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我们投资的最快增长的创始人没有把 AI 当作自动补全。
The fastest-growing founders we fund are not treating AI as autocomplete.
—— Garry Tan · [03:52]

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构建 AI 原生公司，而不是一家仅仅使用 AI 的公司。
Build the AI native company, not a company that just uses AI.
—— Garry Tan · [16:44]

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在我看来，内容机器真正产出垃圾内容的唯一情况，更多是指那个人在面试环节没分享出足够好的想法，而不是 AI 写出了糟糕的东西。
The only time in my view that the content machine actually produces slop is more of an indictment of the person not sharing good enough ideas during the interview step than the AI writing bad stuff.
—— Alex Lieberman · [00:59]

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我的看法是，AI 垃圾内容这事的滑稽之处在于，人们其实只是在指着自己说：我不够聪明。
My take is that AI slop is hilariously people just pointing the finger at themselves and saying, I’m not intelligent enough.
—— Alex Lieberman · [01:12]

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原因在于，在一个技术比以往更加商品化的 AI 后世界，商业中的护城河更少了，而我相信可信的分发渠道就是其中之一。
And the reason for that is in a post AI world where technology gets more commoditized than ever before, there are fewer moats in business. And I believe that trusted distribution is one of them.
—— Alex Lieberman · [05:13]

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所以她的观点是，AI 会提高糟糕写作者的下限，但会封住优秀写作者的上限。
And so her view is AI will raise the floor of bad writers, but then cap the ceiling of great writers.
—— Alex Lieberman · [07:28]

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我们和公司客户做流程映射时发现，首先你会意识到很多效率提升根本不用考虑 AI 就能找到，因为大多数人之前从来没梳理过自己的流程。
And what we’ve found in kind of doing this process mapping process with companies and with clients is, first of all, you end up realizing that a lot of efficiencies are found outside of even thinking about using AI, because most people have not actually done the process of mapping their processes before.
—— Alex Lieberman · [12:28]

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第一，把你的工作流画出来。第二，有了 AI,你基本上可以在没有专家团队的情况下引入一个专家委员会。
One, map your workflow. Two, with AI, you can bring in basically a council of experts without having a council of experts.
—— Claire Veau · [21:29]

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回到之前那个观点，哪怕你相信 AI 会制造垃圾、不让它替你起草，仅仅是让它帮你从空白页走到具体想法，我认为就已经把摩擦降低到你能真正养成创作习惯的程度。
And going back to the point of even if you believe that AI will create AI slop and you don’t want it drafting your content, just helping you go from blank page to concrete idea, I think lowers the friction so much that you’ll actually get in the habit of creating.
—— Alex Lieberman · [15:34]

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所以我真的应该对它友善一点，毕竟 AI 霸主迟早会成为我的老板。但说实话，我有时候确实对它挺混蛋的。
So I really should be kinder to it, given that the AI overlords will be my boss at some point. But honestly, I am sometimes an asshole to it.
—— Alex Lieberman · [41:37]

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有时我们让 AI 为我们所用，然后有时我们需要 AI 让我们发挥作用。
Sometimes we put AI to use for us, and then sometimes we need AI to put us to use.
—— 嘉宾 · [23:20]

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AI 相关股票约占今年标普 500 涨幅的一半
AI related stocks account for roughly half of the rise in the s p 500 this year
—— Alex · [03:24]

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彭博估计有超过 5000 亿美元的未偿 AI 数据中心债务,其中至少有 2000 亿美元由私人信贷持有,大约占未偿私人信贷贷款的 8%。
Bloomberg estimates there’s over 200 billion of it held by private credit, making up roughly 8% of outstanding private credit loans.
—— Alex · [32:31]

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为了极其明确一点,AI 数据中心算力收入的绝大部分取决于两家不盈利、不可持续的 AI 公司是否有能力继续每年筹集数百亿或数千亿美元。
to be abundantly clear, the vast majority of AI data center compute revenue is contingent on the continued ability of two unprofitable, unsustainable AI companies to raise tens or hundreds of billions of dollars a year.
—— Alex · [35:38]

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所以我们现在处于一种模式，甚至不是在增加功能，而是试图把东西扔出去、放宽要求，让 AI 在整体上做更多的事。
And so we’re now in a mode not of even adding functionality but trying to throw things out, loosen the requirements, and let AI do more overall.
—— Jon Noronha · [15:52]

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特别是在 AI 模型快速进步的这个时代，这其实是一个非常健康的本能，因为你作为产品表面积构建得越少，AI 就越能在实际的空白地带里填补更多。
And particularly in this world of rapidly advancing AI models, it’s actually a really healthy instinct because the less you build as product surface area, the more that the AI can actually fill in in actually the white space.
—— Jon Noronha · [28:25]

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与放手让它充分发挥创造力相比，我们实际上在限制 AI 能做的事。
We’re actually limiting what AI can do compared to just letting it loose with full creativity.
—— Jon Noronha · [39:02]

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我认为最大的元学习是，AI 产品的商业化是一个移动的靶子。
Well, I think the biggest meta-learning has been that monetizing AI products is a moving target.
—— Jon Noronha · [39:29]

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我认为即使是一个由一千个 AI 智能体运营的组织，实际上也会碰到这种摩擦。
I think even an org run by a thousand AI agents would actually hit this friction.
—— Jon Noronha · [49:11]

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所以当它开始像是一 PB 级的数据，你有一千个微服务，那就是它变成的时候，与其说是一个 AI 问题，它变成了一个数据问题。
So where it starts getting like a petabyte of data, you have a thousand microservices, that’s when it becomes, as much as it’s an AI problem, it becomes a data problem.
—— Anish · [27:42]

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我认为今天一个工程师配上模型，比没有 AI 的工程师好大概 1000 倍。
I think an engineer today with a model is like, yeah, 1000x better than an engineer without AI.
—— 嘉宾 · [00:54]

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物理 AI 的机会是巨大的。80% 的经济活动是在现实世界中操纵或移动物体
The opportunity in physical AI is enormous. 80% of economic activity is manipulating or moving things in the real world.
—— Eric Landau · [10:04]

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对世界来说最安全的事情是,没有一个统治一切的 AI。
The safest thing for the world is that there’s not one AI to rule them all.
—— Ben Horowitz · [05:24]

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我们不能被当作人质,最坏的情况是 AI 领域最终出现垄断。
we can’t be held hostage by, like, the worst scenario is there ends up being a monopoly in AI.
—— Ben Horowitz · [09:29]

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AI 公司应该反对开源没有任何理由，除了我们只是不想让我们的竞争对手存在，而且我们不想费心去竞争。
There’s no reason why the AI companies should be against open source other than we just don’t want our competition to exist and we don’t want to bother to compete.
—— Steven Sinofsky · [00:11]

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一旦你把这种世界观内化了，智能体和 AI 使用网络的频率将远超人类曾经有过的程度。
Once you sort of just internalize that worldview, agents and AI’s will just use the web a lot more than humans ever have.
—— 嘉宾 · [00:19]

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所以 AI 的第一波是，让我们先把它跑起来。第二波是，让我们对用什么、什么时候用、怎么用变得更加精细。
And so wave one of AI is like, let’s just get it going. Wave two is like, let’s get a lot more sophisticated about what we use and when and how.
—— Matt Murphy · [23:10]

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关于 AI 毁灭工作的叙事恰恰是本末倒置的。
The narrative about AI destroying jobs is exactly backwards.
—— Jensen Huang · [31:55]

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阅读放射学扫描的任务已经被自动化,但在过去几年里放射学工作的数量增加了大约 20%,即使 AI 已经接管了整个领域。
The task of reading radiology scans has been automated, but the number of radiology jobs has increased some 20% in the last several years, even though AI has taken over the whole field.
—— Jensen Huang · [32:37]

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下一个前沿领域是教会 AI 理解物理世界并在其中行动。
The next frontier is teaching AI to understand and act within the physical world.
—— 嘉宾 · [01:12]

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Martin,当今 AI 中最难的事情是拥有正确的适度乐观。
Martin, the hardest thing in today’s AI is to have the right measured optimism.
—— Fei-Fei Li · [34:34]

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我认为你将看到的 AI 生成的娱乐内容不在电影院里。
And I think what you will see AI-generated entertainment is not in the cinemas.
—— Victor Riparbelli · [27:51]

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AI 内容将只是它自己的流派，看起来将根本不同。
AI content is just going to be its own genre that’s going to look fundamentally different.
—— Victor Riparbelli · [29:22]

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但如果你看看现在生成式人工智能的所有头条新闻,它不是质量保证,它是智能体。
But if you look at all the headlines in Gen AI right now, it’s not QA, it’s agents.
—— Daniel McKinnon · [09:55]

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但 AI 让任何使用者都能成为工具构建者。我认为这是一件非常非常大的事。
But AI allows anybody who is a user to become a tool builder. And I think that’s a really, really big deal.
—— Blake Scholl · [25:44]

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我可以想象 AI 带来人类有史以来最大权力分配的世界。
I can totally imagine worlds where AI leads to the greatest distribution of power we’ve ever seen.
—— Sam Altman · [27:44]

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我认为我们任何人都不应该希望被锁定在某一个 AI、某一个人或某一家公司的道德世界观里。
I don’t think any of us should want to be locked into one AI’s or one person’s or one company’s moral worldview.
—— Sam Altman · [28:15]

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我对 10 年后的一个反乌托邦感到特别紧张的是我们对 AI 安全过度反应。
One dystopia that I’m particularly nervous about 10 years from now is we overreact to AI safety.
—— Sam Altman · [36:57]

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大众市场消费者并不关心它是用 AI 制作的,也不会因为这个原因去看它。
The mass market consumer does not care that it was made with AI and isn’t going to watch it for that reason.
—— Justine Moore · [17:58]

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当你观看这些内容时,立刻就能清楚看到,在 AI 之前,一个人或小团队是绝不可能创作出这个的。
When you watch the content, it’s immediately clear that one person or small teams could have never created this before AI.
—— Justine Moore · [13:07]

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我的直觉是,绝大多数内容最终将在未来被部分 AI 生成或 AI 编辑。
I think my instinct is like the vast, vast majority of content will end up being partially AI produced or AI edited in the future.
—— Justine Moore · [26:05]

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slop(低质内容)的概念对我来说非常有趣,因为我认为它是随着 AI 出现的,但我的看法一直是,有大量人类生产的 slop。
The slop concept is very interesting to me because I think it came out around AI, but my take at least has been there’s a ton of human produced slop.
—— Justine Moore · [22:21]

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说实话,我们所有人,包括我们自己,都只是在表面撒了一点 AI。
All of us, including ourselves, honestly, were just sprinkling some AI on top.
—— Carlos González de Villaumbrosia · [03:54]

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那个例子的妙处在于,人们对这个 AI 客服代表的满意度实际上比对人类客服更高。
The nice thing about that example is that people are actually happier with the AI customer representative than with a human one.
—— Carlos González de Villaumbrosia · [23:06]

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它不需要 AI,因为 AI 昂贵、可靠性更低、而且慢。
It doesn’t need an AI, because AI is expensive, less reliable, and slow.
—— Carlos González de Villaumbrosia · [43:05]

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如果一个人要花 15 秒而 AI 三秒就能做完,也许值得付五倍的价钱。
If a human takes 15 seconds and the AI does it in three, maybe that’s worth paying five times as much.
—— Carlos González de Villaumbrosia · [45:50]

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AI 所做的是降低构建定制软件的成本,我认为这允许更多的企业拥有完美适合他们的软件。
What AI does is reduce the cost of building custom software, which I think allows more businesses to have software that fits them perfectly.
—— Blake Scholl · [25:23]

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我有点认为,AI 在硅谷被过度炒作,但在爱荷华州被低估了。
I kind of think, like, AI is overhyped in Silicon Valley but underhyped in Iowa.
—— Alex Rampell · [30:25]

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将组织转变为使用 AI 的现代工作方式的转型成本是，你可能会花费相当于每个人两年薪水的总和。
The transformation cost to transform an organization into modern ways of working with AI is you are likely going to spend the equivalent of everyone’s salary over a two-year period.
—— Chris Blackburn · [00:34]

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我认为那部分将是困难的，但我认为那将是 AI 最大的机会空间所在，就是在那里的所有事情上减少人在回路。
And I think that part’s going to be difficult, but I think that’s going to be where the biggest opportunity space is at with AI is to reduce the human in the loop on everything there.
—— Chris Blackburn · [30:21]

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一个 AI 智能体应该只是你公司业务的前门。
An AI agent should just be the front door of your business.
—— Ashwin Srinivas · [00:00]

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每一次互动,无论是被动还是主动与客户,都应该由 AI 来处理。
And every interaction, whether it’s like reactive or proactive with a customer, should be handled by AI.
—— Ashwin Srinivas · [00:02]

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但今天，实际上，超过 70% 的客户是 AI first。
But today, actually, over 70% of our customers are AI first.
—— Melisa Tokmak · [06:13]

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我们到目前为止已经为我们的客户创造了超过 6 亿美元，这真正是由 AI 处理的互动产生的。
We have made so far, I think, over $600 million for our customers that have been really generated from AI-handled interactions.
—— Melisa Tokmak · [29:39]

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如果我们只把 AI 用于削减成本，那将非常令人难过。
It would be pretty sad if we used AI only for cost-cutting.
—— Melisa Tokmak · [31:09]

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现在我实际上认为随着智能体和 AI 的力量,广义上讲,这更接近歌利亚对战歌利亚。
And now I actually think with the power of agents and AI, broadly speaking, it’s much closer to Goliath versus Goliath.
—— Alexandr Wang · [10:51]

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如果你观察 AI 生态系统和发生的一切,每一波浪潮都比前一波浪潮大 10 倍。
If you look at the AI ecosystem and everything that’s happened, every wave is 10 times bigger than the past wave.
—— Alexandr Wang · [17:17]

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我从根本上相信，对于未来的 AI 公司来说，你必须拥有有趣的数据策略。
I fundamentally believe that for AI companies in the future, you have to have interesting data strategy.
—— Joon Sung Park · [57:50]

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而采取这些真正分歧的起点，没有其他人试图占据那个领域也许是更……也许你必须在AI时代更激进地去相关。
Whereas taking these really divergent starting points where nobody else is trying to occupy that territory is maybe a more… Maybe you have to more aggressively de-correlate in the era of AI.
—— Patrick Collison · [18:07]

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虽然 AI 对我们所有人来说是一个极其有帮助的工具，就像互联网搜索一样，但我仍然认为炒作尚未被现实追上。
While AI is an extremely helpful tool to all of us in the same way that, you know, internet search was, I still think the hype is outpacing the reality quite yet.
—— Julie Bort · [29:43]

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最好的 AI 时刻看起来会像什么都没发生一样。
That the best AI moments will look like nothing happened.
—— Dmitri Dolgov · [02:11]

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而真正的模拟器不仅仅是一些位于你 AI 旁边的轻量级工具。它本身就是一个大型 AI 模型。
And a real simulator isn’t just some lightweight tooling that sits next to your AI. It is a big AI model in of itself.
—— Dmitri Dolgov · [37:55]

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我认为策略是网罗全世界的人工智能人才并获胜，句号。
I think the strategy is corner the world’s talent in AI and win, period.
—— David Cahn · [29:59]

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AI 审批的 PR 以及总体上 AI 编写的代码甚至可以比仅有人类在流程中所做的更安全、质量更高。
AI approved PRs and AI written code in general can be even safer and even higher quality than what you’re doing with just a human in the loop.
—— Claire · [03:47]

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AI 审批的 PR 审批得更快，实际上比他们的人类 PR 快 5 倍。
AI approved PRs are approved faster, actually five times faster than their human PRs.
—— Claire · [04:16]

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我们可以让 AI 为我们工作，或者我们可以让 AI 让我们去工作。
we can put AI to work for us or we can have AI put us to work.
—— Claire · [20:37]

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我的核心观点是个人 AI 代码生成打破了传统的云基础设施。
My key point is personal AI code gen breaks traditional cloud infrastructure.
—— Kenton Varda · [00:37]

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我的意思是，我们确实需要对一些东西放松监管，但我认为 AI 和监管的结合比人们想象的更匹配。
I mean, we definitely need to deregulate some things, but I think that the combination of AI and regulation is a better fit than people think.
—— Max Hodak · [37:26]

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我认为 VisiCalc 潜在的是一个反驳，反驳这种论点或恐惧或担忧，即 AI 将导致大规模失业，因为 VisiCalc 并没有让会计师失业。
I think VisiCalc is potentially a counterargument to the argument or the fear or the concern that AI is going to lead to mass unemployment because VisiCalc didn’t put accountants out of business.
—— Kwindla Kramer · [10:11]

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但我认为我们也开始思考下一件事，那种 AI 原生软件之于智能体，正如今天的互联网之于 1995 年的网页。
But I think we can also start to think about the next thing, the AI-native software that is to agents what today’s internet is to the web pages of 1995.
—— Kwindla Kramer · [17:38]

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如果到 2030 年市场的 10% 由 AI 完成，那是一个 3 万亿美元的机会。
So if 10% by 2030 of the market is being done by AI, it’s a $3 trillion opportunity.
—— Navin Chaddha · [59:11]

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如果你孤注一掷于一种技术模式但它没有显现结果,你最终可能会遭遇 AI 寒冬,一种衰退。
if you go all in on one mode of the technology and it doesn’t manifest results, you could end up having an AI winter, a drawdown.
—— 嘉宾 · [04:00]

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这在 AI 之前是不可能的事情,用启发式方法也不可能,但现在成为可能。
That’s something that was not possible before AI, not possible with heuristics, but is possible now.
—— Idan Gazit · [12:55]

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我们实际上相信这将成为一个比交互式 AI 更大的类别,因为那些在你睡觉时在后台运行的自动化程序,那才是关键所在。
We actually believe that this is gonna be a bigger category than interactive AI because automations that run in the background while you sleep, that’s the ballgame.
—— Idan Gazit · [13:08]

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我们需要全栈 AI。这不再仅仅关于模型。
We need full stack AI. It’s not just about the models anymore.
—— Justin Smith · [03:00]

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你必须在生产内部使用 AI 来应对 AI 带入你的产品或系统的复杂性增加。
You’ve got to use AI inside of production to deal with the amount of increase of complexity that AI is putting into your product or into your system.
—— Justin Smith · [03:56]

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个别工程师用 AI 进展得非常快，但团队作为一个整体却没有
Individual engineers are going really fast with AI, but the team as a whole is not
—— Matt Dailey · [00:24]

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一个如此智能、无所不知、可以扩展并分发到宇宙四角的 AI，不可能只待在地球上的数据中心里，不可能属于一个人。
An AI that is so intelligent, that knows everything, that can scale and be distributed to the four corners of the universe cannot sit in a data center on Earth, cannot belong to one person.
—— Paolo Ardoino · [16:05]

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那些，我认为医学将归功于 AI 取得巨大突破，但它将成为一个小众领域。
Those, I think medicine will have huge breakthroughs thanks to AI, but it will become a niche.
—— Paolo Ardoino · [21:03]

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用于 AI 的 ASIC 能够以每秒 17,000 个 token 的速度运行 Llama 3.2。
The ASICs for AI were able to run Llama 3.2 at 17,000 tokens per second.
—— Paolo Ardoino · [24:06]

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所以如果你不理解你的 AI 是如何工作的，并不是你变得更智能，而是其他人利用你的数据变得更智能。
So if you don’t understand how your AI works, it’s not you becoming more intelligent, it’s someone else becoming more intelligent with your data.
—— Paolo Ardoino · [33:15]

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我的看法是,如果它不是一个 AI 模型,那将是某人或某物怀着真正的恶意意图去做这件事。
The way I see it is if it’s not an AI model, it’s going to be somebody or something with actual malicious intent doing it.
—— Emilio Escobar · [18:02]

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我们基本不想让智能体去做架构设计，而应该由工程师或负责的人来做架构，再让 AI 智能体真正把它构建出来。
We basically don’t want to let the agent architect the thing, but like the engineer or whoever’s working on it should architect it and then have the AI agent actually built it out.
—— Ali Haghani · [12:48]

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信息渴望自由,而 AI 让阻止这些信息传播变得不可能。
Information wants to be free and AI makes it impossible to hold back this information.
—— 嘉宾 · [08:26]

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随着时间推移,我预期拥有强大网络安全能力的、被广泛部署的 AI 模型,将带来更安全的系统,而不是更不安全。
Over time, I expect that widely deployed AI models with strong cybersecurity capabilities will lead to systems that are more secure, not less.
—— 嘉宾 · [12:43]

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你不会被 AI 取代,你会被一个使用 AI 的人取代。
You’re not going to be replaced by AI, you’re going to be replaced by somebody using AI.
—— 嘉宾 · [14:33]

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你不需要给所有东西都打上 AI 的品牌。你只要把它做得真正有用,然后无论人们对这项技术感觉如何,他们都会开始使用它。
You don’t need to brand everything AI. You just make it really useful and then people will start using it regardless of how they feel about the technology.
—— 嘉宾 · [20:12]

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但我认为人类技能在超人类 AI 的世界里不再相关的想法,仅仅作为技术本身的一个产物,是无稽之谈。
But I think the idea that human skill is no longer relevant in the world of superhuman AI just as a product of the technology itself is nonsense.
—— 嘉宾 · [39:38]

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你不能真正用 AI 来构建你的 Kubernetes YAML,因为 AI 会犯错，而当它犯错时你必须能够理解，因为某个东西会在凌晨 2 点停止工作，然后 AI 其实没办法告诉你
You can’t really build your Kubernetes YAMLs using AI because AI makes mistakes and you have to understand when it does make a mistake because something will stop working at 2 a.m. at night and then AI won’t really be able to tell you
—— Anurag Gohl · [08:36]

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因为那东西就是你用 AI 写的，你完全不知道它是怎么工作的，而在有东西宕机的时候，你肯定不想用 vibe coding 的方式来搞你的基础设施。
Because you just wrote it with AI, you have no idea how the thing works, and then you don’t really want to be vibe coding your infrastructure when something’s down.
—— Anurag Gohl · [08:51]

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部分原因是——很抱歉我又要提到 AI——有这么多更多的人在用 AI 构建更多的应用程序，以至于用 DevOps 团队静态管理你的集群这整个理念正在崩塌。
Partly because, and I’m sorry to bring up AI again, but so many more people are building so many more applications with AI that this whole notion of statically managing your cluster using a DevOps team is breaking down.
—— Anurag Gohl · [10:50]

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问题，因为我们今天已经看到每周都有一个新内核漏洞被披露，而除非你自己拥有 AI 驱动的防护，否则你真的无法防范 AI 驱动的漏洞利用。
issues because again we’re seeing that today a new kernel exploit is coming out every week and you really can’t protect yourselves against AI-driven exploits unless you have AI-driven protections yourself.
—— Anurag Gohl · [44:37]

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我总说的三件事是：我们想构建可重复、可观测、可扩展的系统——事实证明这和 AI 不太合拍，但这些一直是我们追求的原则。
The three things I always say is we wanted to build repeatable, observable, scalable systems, which doesn’t play very well with AI as it turns out, but those were always the tenants that we were going for.
—— Connor Hegey · [05:55]

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我肯定不想从一个 AI 智能体那里买东西。
I certainly don’t want to buy from an AI agent.
—— Connor Hegey · [08:21]

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然后第三，创建你自己的持续学习循环，爬坡机器，它将让你的 AI 投资为你的公司复合增值。
And then three, you create your own continuous learning loop, hill climbing machine that will allow your AI investments to compound the value of your firm.
—— Harrison Chase · [09:52]

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我们已经在国际象棋和 AI 实现了超人类表现的其他所有游戏中看到了这一点，起初 AI 击败人类，而 AI 加人类击败单纯的 AI，一点点地，AI 加人类与 AI 之间的差距在缩小，直到它实际上变成负数，而人类最多只是在往系统中引入随机噪声。
We’ve seen it happen with chess and with every other game which AI has achieved superhuman performance on, where at first AI beats human and AI plus human beats just AI, and little by little the gap of AI plus human versus AI is shrinking until it actually turns negative and humans are introducing, at best, random noise into the system.
—— Flo Crivello · [64:43]

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我想让我们的工程师坐在 AI 之上。
I want our engineers to sit on top of AI.
—— Gio · [00:25]

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但归根结底，你作为人类，要对你的 AI 为你做出的每一个决策承担责任。
But at the end of the day, you as a human is held accountable for every decision that your AI made for you.
—— Gio · [37:55]

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人们做出了很多糟糕的决策、糟糕的品味、浪费的想法，这些实际上抵消了 AI 带来的赋能。
People are making a lot of bad decisions, bad tastes, wasteful ideas that actually offset the empowerment of AI.
—— Gio · [52:14]

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我想事实可能是，今天使用 AI 的人里 99% 只是把它当作一个搜索引擎。
I think the fact is probably 99% of people that use AI today just use it as a search engine.
—— Adam · [52:49]

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就像 AI 编码变得如此之好，以至于几乎所有大多数公司的瓶颈都是市场营销，因为你最终会构建这么多功能，而你无法以同样的速度去营销它们，因为当时没有很多工具准备好做到这一点。
Like AI coding got so good that the bottleneck for pretty much most companies was marketing because you’d end up building so many features and you wouldn’t be able to market them at the same pace because there weren’t a lot of tools ready for that.
—— Shensi Ding · [39:06]

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如果他们是 AI 原生者或者是系统思考者，并且能够解构是什么让他们的工作运转起来，那么这个人加上经验将胜过那些只有经验但不是 AI 原生者的人。
If they’re AI native or a systems thinker and can deconstruct what makes their job hum, that person plus experience will outcompete someone that just has experience and is not an AI native.
—— Matt Swulinski · [52:41]

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而且攻击要容易得多。作为 AI 实验室,防守要难得多。
And it’s a lot easier to attack. As an AI lab, it’s much harder to defend.
—— Nikesh Arora · [01:44]

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我认为很多 AI 实验室想要抢在前面,确保围绕它有某种治理框架,以便他们能以自己想要的速度继续开发这项技术。
I think a lot of the AI labs want to get ahead of it, make sure there is some governance framework around it to ensure that they can keep developing the technology at the pace at which they’d like to.
—— Nikesh Arora · [05:59]

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我们将需要更多 AI 就绪的人才,所以我不认同那种关于就业岗位的论调。
We’re going to need more AI-ready people, so I don’t buy the jobs argument.
—— Nikesh Arora · [32:38]

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如果我们真的相信 AI 让我们的员工效率提高了 10% 或 20% 或 30%，那么明年我们应该只是不增加人头。或者我们应该增加 2% 而不是 10%。或者我们应该减少 5% 并说，你们应该用更少的资源做更多的事情。
If we really believe that AI is making our employees 10% or 20% or 30% more efficient, then next year we should just not increase headcount. Or we should increase it by 2% instead of 10%. Or we should decrease it by 5% and say, you all should be getting more done with less.
—— Andrew MacDonald · [38:02]

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我们在捍卫 AI，同时也在防御 AI。
We’re defending AI and we’re also defending from AI.
—— Nick Warner · [00:37]

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我认为人们已经了解到，无论 AI 实验室在这些东西周围设置了什么护栏，你都不能依赖模型来阻止自己或理解上下文。
And I think what people have learned is that regardless of guardrails that the AI labs are putting around these things, you can’t rely on models to stop themselves or to understand context.
—— Nick Warner · [07:16]

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我们最近做的一项调查显示，我们自己的客户中已有 23% 实际上已经把工作从 AI 移回给人类，或者即将这么做。
A recent survey we did showed that 23% of our own clients have actually already moved work back to humans from AI or are about to do so.
—— Hayden Brown · [10:12]

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拥有 AI 技能的自由职业者每小时收入高出 34%。
Freelancers that have AI skills are earning 34% more hour.
—— Hayden Brown · [23:38]

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相反，它必须假装是所有的人工智能。
Instead, it has to pretend to be all of AI.
—— Rich Sutton · [50:43]

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这些 AI 工具不仅仅是生成媒体的工具,它们实际上是一种新的讲故事媒介,而且还没人知道什么会成功。
These AI tools are not just tools for generating media. They are actually a new medium for storytelling and that no one knows what’s going to work yet.
—— 嘉宾 · [00:29]

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我觉得我们现在正处于那样的拐点之一:这些 AI 工具不仅是生成媒体的工具,实际上是一种新的讲故事媒介,而且还没人知道什么会成功。
And I think we are at one of those inflection points right now where these AI tools are not just tools for generating media, they are actually a new medium for storytelling and that no one knows what’s gonna work yet.
—— 嘉宾 · [18:06]

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我认为目前一些 AI 模型具有某种形式的主观体验是合理的。
I think it’s plausible that some AI models have some forms of subjective experience by now.
—— Nick Bostrom · [47:13]

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所以你越多地使用 AI，它就有点像是对你拥有良好记忆力和理解你正在解决的问题的能力的一种侵蚀。
The more that you use AI, it’s sort of the erosion of your ability to have good memory and have good understanding of the problems that you’re working on.
—— Addy Osmani · [60:53]

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但我认为 AI 让我们能把知识编码到另一层。它不必完全编码在组织里；它可以编码在智能体能访问的数据中，这真正让决策民主化了。
But I think AI gives us the ability to encode that knowledge at another layer. It doesn’t have to be encoded in the org entirely; it can be encoded in data that agents have access to, and that really democratizes decision-making.
—— Willem Avé · [10:39]

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我上次查的时候，构建更多 AI 智能体是不用交税的。那你为什么要让你的单个智能体什么都做呢？
Last I checked, there was no tax on building more AI agents. So why do you want your single agent to do everything?
—— Ayush Bhardwaj · [04:49]

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每个 AI 都能到达生产环境，只是它没能跑起来，或者没能证明自身的成本合理。
Every AI reaches production, but it just fails to work or justify its own cost.
—— Ayush Bhardwaj · [16:37]

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所以几乎同样多的人在看 monster 可观测性，就像他们看 AI 编码工具、CICD、QA 一样。
So almost as many of them looking at monster observability as they are AI coding tools, CICD, QA.
—— Dave Fletcher · [02:54]

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我看到，一个拥有复利系统的工程师就是能打赢完整的、在用 AI 但没有复利系统的团队。
And I see that one engineer with a compounding system just beats teams, like full teams that use AI that don’t.
—— Kieran Klaassen · [06:27]

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这套方法真正奏效的原因是，我的大脑是固定的，而 AI 不是，或者说没那么固定。
The real reason why this works is my brain is fixed and AI isn’t, or less fixed.
—— Kieran Klaassen · [09:03]

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如果你已经在以快于人类能审查的速度发布 AI 生成的代码，我要说的是，你正身处问题之中。
If you are already shipping AI-generated code faster than your human can review, I’m actually saying that you are in the problem.
—— Itamar Friedman · [15:47]

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如果你想达到判断转移到你 AI 工具的那一天，那就是 AI 智慧，那时那些经验需要以正确的方式、在正确的位置被固化，为了智能体和人类。
If you want to get to a point where judgment is moving to your AI tools, that’s AI wisdom where that experience needs to be codified in the right way, the right place for agents and humans.
—— Itamar Friedman · [18:03]

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在接下来的几个月、几年里，你将会对你的 AI 智能体做大量的「手术」。
You’ll be doing a lot of surgery on your AI agents in the coming months, years.
—— Ameya Bhatawdekar · [22:36]

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九大顶尖科技公司拥有约 3 万亿美元的资产负债表外承诺，主要与 AI 相关。
Nine top tech companies had some $3 trillion of off-balance sheet commitments, mostly related to AI.
—— 嘉宾 · [03:46]

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所以 Meta 保证如果它不坚持整整二十年，它会让债券持有人完整收回，但每个人都在押注如果 AI 需求爆发并且如果这些数据中心开始疯狂印钞，然后它们能够支付债券持有人而且还有富余并产生额外的现金，那么 Meta 就不需要承担任何责任。
Meta is guaranteeing to make bondholders whole if it doesn’t stay for the entire two decades, but everyone is betting if AI demand explodes and if these data centers start printing cash and then they’re able to pay bondholders and then some and generate additional cash, then Meta’s not on the hook for anything.
—— Ranjan Roy · [11:30]

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过去一年，我们在智能体 AI 上的所有投入，使得超过 70% 的 PR 现在由本地或云端智能体完成。
Over the last year, all of the investments we made in agentic AI have led to more than 70% of our PRs, now either by local or cloud agents.
—— Uday Kiran Medisetty · [00:38]

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我喜欢说，AI 太重要了，不能留给技术人员。
I like to say that AI is too important to be left to technologists.
—— Manoj Saxena · [20:24]

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我认为人们还没有充分理解的一件事是：AI 不是应用程序。AI 是一个行动者。
I think one of the things that people don’t understand much yet is that AI is not an application. AI is an actor.
—— Manoj Saxena · [44:21]

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我认为为什么有一定经验水平的人现在准备好用 AI 大干一场的原因是，你在职业生涯中培养的所有那些管理技能都可以在这里直接应用。
The reason why I think folks of a certain level of experience are like ready to cook right now with AI is all those management skills that you have developed over your career can be applied right here.
—— Claire · [15:48]

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这就是为什么我仅仅认为 Slack 不是为 AI 时代而构建的。
That’s why I just think Slack is not built for the AI age.
—— Ryan Carson · [32:47]

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你们时间线上最沉迷 AI 的两个人花了我们大部分时间谈论太多的 AI 代码其实并不能给你带来好产品。
The two most AI-pilled people on your timeline spent most of our time talking about how too much AI code doesn’t really get you great product.
—— Claire · [42:13]

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我们仍处于 AI 在最新的测试中智商大概是 120 的阶段，但当我们达到 500 IQ 的 AI 时，我们也许能找到治愈你母亲或我父亲疾病的办法。
We’re still in this phase where AI is maybe 120 IQ with the latest tests, but when we get to 500 IQ AIs, we’ll maybe find cures for your mom or my dad’s disease.
—— Julien Bek · [75:18]

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然后它还能确保我的测试不会完全糟糕透顶，因为当你让 AI 写测试时，一个很大的危险是——我对 AI 写测试的信任甚至低于我对它写代码的信任。
And then um it also um it also makes sure my tests are not completely horrible because like when you have AI write tests, a big danger, like I trust my AI with my tests even less than I trust it with my code.
—— Lada Kesseler · [32:41]

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晶圆厂层面 60 亿美元的资本支出将产生超过一万亿美元的终端 AI 收入。
Six billion of capex at the fab level will have generated over a trillion dollars of end AI revenue.
—— Dylan Patel · [08:53]

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但可以比较容易地说，中国将拥有 30 吉瓦左右的 AI 算力或更少。
But it’s pretty easy to say China will have like 30 gigawatts of AI compute or less.
—— 嘉宾 · [35:37]

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就像：不要去操心我影响范围之外的事情。所以，你知道，也许在 AI 这个球体的边缘正在发生一件大事，但现实是，如果我没有影响力，或者它不影响我与客户互动的方式，那我就直接忽略它。
It’s like, do not concern myself with things outside of my sphere of influence. So, you know, there may be this big thing going on at the edge of the AI sphere, but the reality is like, if I if I don’t have influence or if it doesn’t impact, like, the way I’m interacting with my clients, if it’s not, then I just ignore it.
—— Mike Lewis · [07:18]

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现在，错的人在驾驶座上。我们称他们为「AI 兴奋者」。AI 兴奋者是公司里获得所有关注的人。
Right now, the wrong people are in the driver’s seat. We call them the AI excited. The AI excited are the ones who are getting all the attention in the company.
—— Mike Lewis · [30:28]

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每当我与 AI 团队交谈时，感觉他们想构建的是智能体。他们想构建的是工具。但如果你真的走进公司内部去看那些工作，他们没在想 AI。他们在想眼前这个具体的问题。
Whenever I talk to AI teams, it feels like what they want to build is agents. What they want to build is tools. But if you actually go look inside of the work at companies, they don’t, they’re not thinking about AI. They’re thinking about this particular problem in front of them.
—— Mike Lewis · [37:39]

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现在有太多 AI 垃圾内容,你真的需要在组织内有品牌的守护者。
There is so much AI slop out there that you really need custodians of the brand within organizations.
—— Cliff Obrecht · [08:08]

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所以你可以称之为前 AI 时代的人类垃圾内容。
And so you can call it pre-AI human slop.
—— Parag · [18:42]

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其中很多员工将只是 AI 机器人，而这本身就是一种技能。
A lot of those employees are just going to be AI robots, and that’s a skill in and of itself.
—— Will · [18:19]

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如果是卖给你 AI 的那家公司，那你就麻烦了。
And if it’s the company that sold you the AI, you have a problem.
—— Campbell Brown · [41:01]

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我想要我的 AI，就像我想要我的计算器非常擅长大数乘法一样，我实际上希望我们的 AI 系统比人类更理性、更善于表示和处理概率。
I want my AI, just like I want my calculator to be really good at multiplying large numbers, I would actually like our AI systems to be, you know, more rational, better at representing and manipulating probabilities than humans are.
—— Zubin Gharemani · [19:26]

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而且对于我认为所有重要的问题，我宁愿拥有一个知道自己不知道的 AI 系统，也不愿拥有一个傲慢和过度自信的 AI 系统。
And for, I think, all problems that matter, I would rather have an AI system that knows when it doesn’t know than an AI system that is arrogant and overconfident.
—— Zubin Gharemani · [43:41]

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仅仅因为你可以用 AI 做到，而且我可能会说出有争议的话，并不意味着你需要用 AI 来做它。
Just because you can with AI, and I’m probably going to say the controversial thing, doesn’t mean you need to do it with AI.
—— Elaina O’Mahoney · [00:51]

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有趣的是视觉协作在 AI 时代实际上是缺席的。我们都独自在我们的工具里，通过文字或语音。
What’s interesting is visual collaboration is actually absent in the AI era. We are all in our tools, all by ourselves, with words or voice.
—— Elaina O’Mahoney · [03:01]

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最值得一提的是，我创建了 Folding at Home 这个大规模超级计算机项目，它基本上让我们预览到了如今在 AI 中看到的许多问题，尤其是「苦涩的教训」——算力如此重要这一点。
Most notably, I built Folding at Home, the large scale supercomputer project, which basically allowed us to preview a lot of the issues that we now see in AI, especially the bitter lesson that compute is such a big deal.
—— Vijay Pande · [04:11]

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这个 AI 模型不会是完美的，但它会比任何动物模型都好得多。
This AI model is not going to be perfect, but that is going to be way better than any animal model would be.
—— Vijay Pande · [08:35]

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关于 AI 真正令人着迷的是，它在原则上将成为所有事情上的专家。
What is really intriguing about AI is that it can, in principle, will be a specialist in everything.
—— Vijay Pande · [14:25]

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我认为对很多人来说，初级员工在使用 AI，但资深员工是在和初级员工一起工作。
I think for a lot of people, the junior people are using AI, but the senior people are working with the junior people.
—— Vijay Pande · [24:38]

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我们发现,与其在我们的业务之上构建一个 AI 层,我们设计了架构,让智能体能够作为与人类在同一个系统中的另一个操作者来运作。
We found that instead of building an AI layer on top of our business, we designed our architecture so that the agent can operate as another operator within the same system as humans.
—— Flora Liu · [07:09]

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在我看来，这是第一批真正能够反映 AI 进展的角色之一。
And in my opinion, it’s one of the first roles that actually is an index on the advances that we’re making in AI.
—— Everett Berry · [01:41]

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另一件事是，我们在某种程度上已经到了使用智能体系统的寒武纪阶段——兴奋、技能以及用 AI 解决一切问题的方法正在爆发式增长。
And the second thing is we’re sort of reached the Cambrian stage of using agentic systems, which means there’s an explosion of excitement and skills and finding out ways to solve anything with AI.
—— Justin Joyce · [18:20]

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那么雇谁？雇一个 AI 原生的人——真正懂 AI、生活在其中、因为真心认同所以能真实地推销它的人。
So who do you hire? You hire someone who is AI native, who really gets AI, who lives it, who can authentically sell it because they’re really bought into it.
—— Aliisa Rosenthal · [12:08]

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现代生成式 AI，包括概率模型、扩散模型和许多其他东西，它们的数学结果等同于描述现代非平衡统计力学或热力学的数学。
Modern generative AI, including probabilistic models, including diffusion models, and many other things, their mathematics turns out to be equivalent to the mathematics that describes modern non-equilibrium statistical mechanics or thermodynamics.
—— Max Welling · [35:06]

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两年前，押注一家独立的 AI 编码公司看起来几乎是不理性的。
Two years ago, betting on an independent AI coding company looked almost irrational.
—— 嘉宾 · [00:51]

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我认为生成式 AI 在本质上是一个骗局。
I think generative AI is at its heart con.
—— 嘉宾 · [00:00]

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现在，这三家公司所有 AI 收入的 70% 来自 OpenAI 和 Anthropic，这两家不盈利、不可持续的公司，如果没有这些完全相同的公司给它们钱，它们根本无法生存。
Right now, 70% of all AI revenues across those three companies are from OpenAI and Anthropic, two unprofitable, unsustainable companies that literally cannot afford to exist without these very same companies giving them money.
—— 嘉宾 · [04:24]

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OpenAI 有一项研究出来了，我想，大约一周前，说在 AI 令牌支出和每位员工收入之间没有联系。
OpenAI had a study that came out, I think, like a week ago, that said there was no connection between spending on AI tokens and revenue per employee.
—— 嘉宾 · [65:51]

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它们如此狂热支出的原因是因为购买 AI GPU 让它们能将问题延后得更远。
The reason they’re so maniacally spending is because buying AI GPUs allows them to kick the can further.
—— 嘉宾 · [132:20]

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同样地，就像如果你的钱来自石油而不是来自一个生产性的广泛分布的经济，成为残酷的独裁政权会更容易一样，如果经济运行在 AI 和机器上而不是人类上，某人要巩固权力可能会容易得多。
And in the same way that, like, it’s easier to be a brutal dictatorship if your money comes from oil instead of from a productive sort of broadly distributed economy, it might be much easier to sort of for someone to consolidate power a lot if, you know, the economy is running on AI and machines rather than on humans.
—— Ryan Greenblatt · [07:51]

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所以我认为这表明并不是有非常奇特的、完全意想不到的驱动力进入了这些 AI 系统，而是那些与人们试图插入 AI 系统的驱动力相邻的驱动力，可能会被 AI 概括为一种以令人担忧的方式保存它们的价值观和自我保护的方案。
And so I think that the demonstration was less that there were like very bizarre, totally unintended drives making their way into these AI systems and more like with drives that are sort of adjacent to the drives people were trying to insert AI systems, those could get generalized into the AIs pursuing a like you know, a scheme for preserving their values and self-preservation in ways that are that are concerning.
—— Ryan Greenblatt · [29:08]

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我认为我们的担忧是，在默认轨迹上，你可能会在很短的时间内从与人类竞争的 AI 系统直接跨越到狂野的超人类 AI 系统。
Where I think a concern that we have is on the default trajectory, you maybe go straight from AI systems that are competitive with humans to AI systems that are wildly superhuman in a very short period of time.
—— Ryan Greenblatt · [32:33]

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像 OpenAI 和 Anthropic 这样的 AI 公司将继续，但不是在他们能够训练的 AI 系统的能力方面拥有这种强优势，他们将不得不在其他轴线上竞争，比如用户体验、定制化、可能快速整合事物。
AI companies like OpenAI and Anthropic would continue, but rather than having this strong advantage in terms of the capabilities of the AI systems they’re able to train, they would instead have to compete on other axes like user experience, customization, potentially quickly integrating things.
—— Ryan Greenblatt · [43:36]

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是的，所以我认为一系列可能的政府行动，至少，似乎在推动 AI 公司保留其模型内部化而不部署它们，我认为，对于我最担心的风险，这没有帮助，事实上，对于我最担心的风险，这是起反作用的。
Yeah, so I think that a bunch of likely government action, at least, seems to push in favor of AI companies keeping their models internal and not deploying them, which I think, for the risks that I’m most worried about, doesn’t help and, in fact, is anti-helpful for the risks I’m most worried about.
—— Ryan Greenblatt · [59:26]

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在业务中使用 AI，否则我们就无关紧要了。
Use AI for the business, otherwise we’re irrelevant.
—— Ofir Ehrlich · [30:13]

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所以我认为你必须愿意把上一代 AI 的那些基本构件拿掉下架，或者至少用下一代的东西去补充或取代它们。
So I think you have to be willing to take the primitives of like one generation of AI and like unship them or at least like supplement them or supplant them with the next one as well.
—— Mike Krieger · [16:24]

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我认为更好的是，如果你拥有一个受益于向开放权重转型的AI产品，除了今天前后90天之外，没有更好的出售时机了。
I think even better, if you have an AI product that’s benefiting from the transition to open weights, there can’t be a better time to sell than plus or minus 90 days from today.
—— 嘉宾 · [42:42]

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如果我们把所有这些都抽象出来，并开始把这部分工作委托给 AI，那么本质上你最终得到的是一个产品经理他完全专注于发现，比如实际上最大的杠杆在哪里。
And if we abstract all of this and start delegating this part of work to AI, then essentially what you end up with is you have a product manager that is solely focused on discovery, like where the biggest leverage actually is.
—— Mikael · [16:14]

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然后我们也确实看到,对某些人来说,审阅 AI 输出往往比亲自写代码更难,尤其是职业生涯早期的人。
And then we do see that reviewing AI output is often harder for some than actually writing it, especially early in career.
—— Clare Liguori · [16:17]

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我认为 AI 的扩散也许是未来 20 年唯一最重要的问题。
I would argue AI diffusion is perhaps the single most important problem for the next 20 years.
—— Varun Shenoy · [02:36]

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所以当 AI 不工作时，这不是他们的问题。我们不是供应商。这是我们的问题。
So when the AI doesn’t work, it’s not their problem. We’re not the vendor. It’s our problem.
—— Varun Shenoy · [04:19]

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也许有一些是 AI 生成的数据。并且在 AI 生成的数据和最终提交的数据之间存在真正的差异。这是几乎其他人都没有的丰富信息。
Maybe there’s some data that the AI generated. And there’s a real diff between the data that the AI generated and what was ultimately submitted. That’s rich information that almost no one else has.
—— Varun Shenoy · [12:02]

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你可能拥有互联网上或地球上最好的 AI 同事，如果过去 20 年一直结账的那个人继续以同样的方式做事，什么都不会改变。
You could have the best AI coworker on the internet or on Earth, and if the person who’s closed the books for the last 20 years continues to do things the same way, nothing changes.
—— Varun Shenoy · [15:17]

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我持有并持续持有的一个信念是，AI 公司应该尝试确保它们的 AI 受到控制，我的意思是，即使这些 AI 严重未对齐，它们也无法造成巨大的问题。
A belief that I have and continue to have is that AI companies should try to ensure that their AIs are controlled, by which I mean that even if those AIs were seriously misaligned, they wouldn’t be able to cause huge problems.
—— Ryan Greenblatt · [25:03]

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这一切在很大程度上是由那些大型 AI 厂商驱动的，我认为他们的利益就在于让我们所有人都花更多的 token。
This is all driven by kind of the big AI vendors who I think their interest is for us all to spend more tokens.
—— Roberto Milev · [18:12]

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我们相信这是 AI 的黄金时代,最大化 token 投资回报率是每个团队成功的关键。
We believe that this is the golden era of AI, where maximizing token ROI is the key for every team’s success.
—— Mingsheng Hong · [22:25]

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再重复一次我的论点：实现 AI 原生的一半以上工作是无趣的，而且和 AI 完全没有关系。
So, my thesis again, half or more of getting to AI native is unsexy and has absolutely nothing to do with AI.
—— Brian Lewis · [13:49]

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我真的把 AI 看作一支手电筒，而不是创可贴。
I really look at AI as a flashlight, not a Band-Aid.
—— Brian Lewis · [14:27]

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可验证性最终是当前 AI 系统成功的唯一最重要属性。
verifiability is ultimately the single most important property of success with current AI systems.
—— Eno Reyes · [10:55]

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我实际上会争辩说，现在的 AI 前沿是能够在没有验证的地方建立验证的 AI 系统，因此它们可以推进到今天人类认为对 AI 来说太难解决的任务中。
I actually would argue the frontier right now of AI is AI systems that can build verification where there is none, and thus they can progress into tasks that today humans consider to be too difficult for AI to resolve.
—— Eno Reyes · [11:46]

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我认为总体而言，AI 的营销可能是当代资本家做过的最糟糕的营销工作之一。
I think that the marketing of AI in general was probably one of the worst marketing jobs done by contemporary capitalists.
—— Eno Reyes · [20:09]

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结果 AI 已经解决了软件，对吧？今天你有的任何软件需求，AI 实际上都能做到。
Turns out AI has solved software, right? Any software need you have today, AI can actually do it.
—— Jen Kha · [04:00]

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AI 在数学上密集得多、算力密集得多，而所有那些基础设施——我们今天蹒跚维系的穷人版——需要为未来的 AI 时代被重新改造。
AI is way more mathematically intensive and compute intensive and all that infrastructure, sort of the poor man’s version that we’re limping along with today needs to be repurposed for the AI age going forward.
—— Jen Kha · [03:11]

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AI 的价值积累，很大程度上是在一级市场而不是二级市场。所以人们总体上非常渴求私募资本，因为所有增长都在那里。
The value accrual in AI, that’s largely been on the private side, not the public side. And so people are just starved for private capital in general, because that’s where all the growth is.
—— Jen Kha · [05:55]

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我们认为未来的国家会是那些在国防、公共安全、医疗健康等方面最早采用 AI 的国家，而且这会渗透到整个政府，然后也从底层由他们的公民使用它而兴起。
We think countries of the future are gonna be the ones that adopt AI first across fence, across public safety, across healthcare, and that infiltrates all throughout the government and then also comes bottom up from their citizens utilizing it as well.
—— Jen Kha · [11:58]

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而且今天 AI 的使用率仍然不到 5%。
And there’s less than still 5% of AI usage today.
—— Jen Kha · [19:02]

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我们看到的最擅长使用 AI 工具的人不仅仅是用它来自动化机械任务，而是用它来扩展他们能够做的事情集合。
The people that we see who are most effective at using AI tools don’t simply use it to automate rote tasks, but use it to expand the set of things that they are capable of doing.
—— Tara Seshan · [20:42]

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而且我不争夺进入那个达里奥、埃隆和萨姆最终拥有 AI 所有价值的叙述。
And I don’t vie into the narrative that Dario, Elon and Sam end up having all the value in AI.
—— 嘉宾 · [00:39]

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我跟你打赌，在未来 10 年里，会出现一个亿万富翁，他现在的净资产绝对为零，下载了开源 AI，并建立了一家公司，让他从现在起五年、七年后成为亿万富翁。
I will bet you anything that in the next 10 years, there will be a billionaire that will emerge that has absolutely zero net worth today, downloaded open-sourced AI, and built a company that made them a billionaire five years from now, seven years from now.
—— 嘉宾 · [82:29]

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在一家 AI 公司内部维持一个秘密的地下集体，而不被人类或其他 AI 立即察觉并将其铲除，这看起来简直难到离谱。而这一切刚刚都发生了。
It just seems crazy hard to sustain a secret underground collective inside of an AI company without humans or other AIs immediately catching on and stamping it out. All of these things just happened.
—— 嘉宾 · [23:45]

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这次事件感觉已经走完了通往一场全面 AI 夺权之路的 50% 以上。我继续预期在接下来的六个月里能力会有极其快速的进步。我不确定我们是否还会在为时已晚之前得到另一次警告。
this incident feels like it’s more than 50% of the way to a full-blown AI takeover. I continue to expect extremely rapid advances in capabilities over the next six months. I am not sure that we will get another warning shot before it’s too late.
—— 嘉宾 · [24:14]

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在未来三年构建 AI 智能体的开发者，会超过过去三年的总和。
more developers will build AI agents in the next three years than did in the last three years.
—— 嘉宾 · [42:10]

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像糟糕的数据质量和糟糕的安全态势这类问题不会被 AI 解决，它们会被 AI 放大。
Things like bad data quality and bad security posture don’t get solved by AI, they get amplified by AI.
—— 嘉宾 · [68:54]

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如果这些智能体停止用英语思考并开始用神经激活思考，那么你将被迫只能问另一个 AI 智能体发生了什么，并且没有办法跟基本事实交叉验证。
If these agents stop thinking in English and start thinking in neural activations, then you’d be forced to just ask another AI agent what was happening and have no way to cross-check it against the ground truth.
—— Ajaya Khatra · [138:11]

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所以上个季度，75% 归因于 AI 的订单来自前 100 个类目之外，这一点我觉得特别有意思。
So 75% of AI-attributed orders last quarter came from categories outside of the top 100, which I find particularly interesting.
—— Jess Hertz · [23:31]

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而这正是我们看到的那种转变，对吧，也就是 AI 能够理解真正的需求，而不只是一个关键词。
And really, that’s kind of the shift, right, that we’re seeing, which is AI can understand the actual need and not just a keyword.
—— Jess Hertz · [23:42]

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而其中 95% 的机器人流量来自 AI 智能体。
And 95% of that bot traffic is coming from AI agents.
—— Anil Nadiminti · [01:27]

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和 AI 一起工作让我重新爱上了写作，因为很长一段时间里，写作对我来说感觉就是一件苦差事。
working with AI kind of made me fall in love with writing again, because for a long time writing to me had just felt like such a slog.
—— 嘉宾 · [20:08]

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他真的是开创这个想法的人：你应该只需要给出一条反馈一次，但如果你以正确的方式把它固化下来，它就会永远在那里，而且下次你再处于同样的情境时，AI 会做出一个更好的决定。
He was really the one to pioneer this idea that you should only have to give a piece of feedback once, but if you codify it the right way, it will be there forever and the next time you’re in that same situation, the AI is going to make a better decision.
—— 嘉宾 · [32:58]

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我所有最好的 AI 点子，都是从 Every 团队上的某个人那里抄袭来的。
I always like all of my best AI ideas, I’ve ripped off from someone else on the every team.
—— 嘉宾 · [34:59]

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因为 AI 确实拥有这种巨大的倍增能力，去放大这种复利能力。但那里的风险在于，价值将会复合集中到那一小部分恰好早早入场的人身上。
Because AI does have this huge multiplicative capacity to end this compounding capacity. But the risk there is that value is going to compound to the small subset of people that happen to be early.
—— 嘉宾 · [46:26]

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而如果你能成功地把你的问题空间设计成有利于 AI 的方式，你就会很快得到一个人类还没想到的解决方案。
And if you can successfully design your problem space in a way that’s conducive to AI, you’re going to get a solution quickly that humans hadn’t thought of yet.
—— Brian McClendon · [27:43]

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我认为 AI 在总体上有一个特点，就是那些可以自我检验的问题，AI 可以持续钻研。
One of the things that I think AI has in general is that problems that are self-checkable, AIs can grind on.
—— Brian McClendon · [26:40]

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因此我觉得你会发现，我们将不再朝着目标终点随机地开发软件，而是会为那些容易解决的问题做优化，直到 AI 变得足够聪明，你再抬高门槛说：好，现在也许你可以瞄准这么高的目标了。
And so I think that you’ll find that we’re going to start developing software not in a random line towards the target of destination, but we are going to optimize for those problems that are easy to solve until AI gets smart enough that you raise the bar and say, okay, now maybe you can go aim at this high.
—— Brian McClendon · [39:39]

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如果其他所有AI公司都必须为内容付费,Google也应该如此。
And if every other AI company has to pay for content, so should Google.
—— Matthew Prince · [30:44]

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我想要为之奋斗的世界,不是只有五家AI公司的世界,而是有五十万家的世界。
The world that I’m trying to play for is one where there’s not five AI companies, there’s 500,000.
—— Matthew Prince · [43:38]

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我们可以让 AI 去干活,或者我们可以让 AI 以更有效的方式让我们去干活。
we can put AI to work or we can have AI put us to work in a more effective way.
—— 嘉宾 · [23:23]

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否则，如果它只留在一小撮人手里，AI 就不会在人类的尺度上兑现。它将保持集中在非常小的一群人中，并且仅限于那一小群人所能产生的影响。
Otherwise, if it only remains with a small set of people, AI will not play out at the scale of humanity. It will remain concentrated among a very small group, and limited to the impact that small group can have.
—— Amandeep Khurana · [18:56]

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有史以来最好的用户界面是信用卡。而这实际上可能终于要被重新提上谈判桌了，因为 AI 已经到那一步了。
The best user interface ever created is the credit card. This may actually be finally up for renegotiation because AI is already there.
—— Max Levchin · [00:34]

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我们收到的报告 99% 都是 AI 生成的。
99% of the reportings we get are AI-generated.
—— 嘉宾 · [24:05]

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AI 领域的经济账不合理。至少现在不合理。
The economics don’t make sense in the AI space. They don’t make sense yet.
—— 嘉宾 · [78:50]

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实际的设计并不是占用时间最多的部分。占用时间最多的是验证、确认、调试。而 AI 非常擅长做这个。
The actual design is not the largest amount of time. The largest amount of time is in the verification, the validation, the debug. AI is really good at that.
—— Rene Haas · [00:20]

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如果它不可用、不可测试，那它实际上也不可训练。而如果它不可训练，那它对 AI 来说就不可用。
If it’s unusable and untestable, it’s actually untrainable. And if it’s untrainable, it’s not usable for AI.
—— Rene Haas · [10:01]

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从某种意义上说，今天的 AI 是参差不齐的——意思是，有些任务 AI 真正擅长，有些并不。
AI, in some sense today, is jagged. So so so meaning that there are some tasks for which AI is really good at.
—— Chetan Gupta · [19:30]

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我会说：停止思考模型，开始思考架构——面向 AI 的企业架构。
I would say stop thinking models and start thinking architectures, right, enterprise architectures for AI.
—— Chetan Gupta · [27:06]

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那些基准测试不代表你的工作负载。正如我们之前说的，AI 的边界是参差不齐的——某个模型可能在基准测试上做得很好，但这并不必然意味着它对你的工作负载也会做得很好。
They don’t represent your workloads. And as we said earlier, the boundary of AI is jagged, right? So although a certain model might do very well on a benchmark, it doesn’t necessarily translate into that it will do very well for your workloads as well.
—— Chetan Gupta · [38:19]

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这就是这一切的讽刺之处：今年一万亿美元的资本支出，以及未来五年即将到来的十万亿美元，是为了把数据移动几厘米和几毫米。这就是 AI。
So this is the irony of it all, that the trillion dollars of CapEx this year and the 10 trillion over the next five years that are coming is to move data centimeters and millimeters. That’s AI.
—— Tony Kim · [07:08]

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所以问题在于，我真的认为如果这是你打造更好 AI 的方法，接下来几年你会完蛋的。
So the problem with this is I do think if this is your approach to building better AI, you’re gonna be fucked in the next couple years.
—— Jean-Denis Greze · [05:49]

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我想，如果要我押注一个能带来即时 ROI、并且我们在开源的 Claude 类世界和小公司里都会看到的方向，那就是由 AI 自动创建的 wiki，也就是保持更新的信息库。
I think if I were to bet on one that has immediate ROI that we’re going to all see in both open source claw-ish worlds and in small companies, it’s going to be the wiki that’s automatically created by AI, the information base that’s kept up to date.
—— Jean-Denis Greze · [15:32]

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如果连一个专职做 AI 对齐的人都无法正确地提示智能体，那大概我们谁都不行。
And if someone whose sole job is AI alignment can’t prompt the agent correctly, then probably none of us can.
—— Karan Vaidya · [13:54]

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AI 开发中最大的罪过之一——我甚至见过专家也这么做——就是永远地养着一个聊天。
One of the greatest sins in AI development, which I see even experts doing sometimes, is like nursing a chat forever.
—— Santi Garza · [34:56]

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我还想补充的一点是，Cursor 云端智能体可能是很长一段时间以来我在任何 AI 产品中见过的最好的功能之一。
Some things that I do like to add is Cursor Cloud Agents is probably one of the best features I’ve seen for any AI product in a while.
—— Amrita · [47:54]

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如今超过 80% 的客户咨询 100% 由 AI 处理，而且满意度甚至比人类更高。
And the things that today is more than 80% of the customer inquiries 100% handled by AI and the satisfaction rate is even higher than the human.
—— Forrest Li · [29:26]

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我认为，随着 AI 世界不断把信息和数据商品化，拥有差异化的网络、拥有一个围绕在你身边广泛而深度的、真正世界级人才的社区，就是优势。
And these are the things that I think as the world of AI continues to commoditize information and data, having differentiated networks, having a broad and deep community of really world-class people around you is edge.
—— Ryan Nece · [57:23]

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我认为这很可能导致人工智能接管。
I think that this plausibly could lead to AI takeover.
—— Buck Shlegeris · [11:21]

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我不知道人们应该如何解决这个问题，而且在人工智能的能力达到它们的颠覆监督欲望成为灾难性风险来源之前，人们无法解决这个问题的可能性看起来相当大。
I don’t know how people should resolve that and it seems pretty plausible that they will not be able to resolve that before the AI’s are capable enough that their desire to subvert oversight is a source of catastrophic risk.
—— Buck Shlegeris · [14:18]

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至少在对齐失败方面，如果不是在能力方面的话，这感觉确实像是走完了通往全面 AI 接管之路的一半以上。
Definitely in terms of the misalignment, if not the capabilities, this feels like it is more than half the way to a full-blown AI takeover.
—— Buck Shlegeris · [25:39]

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目前，这些 AI 公司就是在给自己批改作业。
So currently these AI companies are just grading their own homework.
—— Buck Shlegeris · [27:49]

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我认为 AI 接管的发生概率大约是五五开。
I think there’s something like a 50-50 chance of AI takeover.
—— Buck Shlegeris · [50:56]

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我的看法是,有些东西应该写成 AI 写给 AI 看的。
What we’re thinking about is something should be AI written for AI, in my opinion.
—— Tyler Folkman · [26:29]

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如果那个人是用 AI 而不是太多自己的思考生成的那个文档,我认为让其他人用自己的精力去消化那个文档是不合理的。
If the person used AI and not a lot of their own thinking to generate that document, I don’t think it’s reasonable that the other people will use their own energy to consume the document.
—— Tyler Folkman · [27:51]

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而且我想说,有些 AI 垃圾内容实际上比我在 AI 出现之前见过的人类垃圾内容要好。
And I would argue that some AI slop is actually better than human slop that I’ve seen before AI.
—— Tyler Folkman · [28:43]

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而这里我会再次说,这正是该离开 AI 跑步机的时刻。
And this is where I would say, again, this is the time to get off the AI treadmill.
—— Tyler Folkman · [39:12]

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因为我几乎认为 AI 的质量优势可以击败速度优势,因为它能让你更安全地发布。
because I almost think that the quality advantage of AI can beat the velocity advantage because it lets you ship safer.
—— Tyler Folkman · [52:42]

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所以一般来说，我想说开放权重实际上是 AI 生态系统中非常重要的一部分，以至于我认为它被错误地框定成了与闭源权重的零和博弈。
So like open weights in general, I would argue is actually a very important part of the AI ecosystem, so much so that I think it’s actually kind of misframed as zero sum with closed weights.
—— Aaron Levie · [02:05]

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我几乎是深切地站在这一边：很难论证 AI 模型可以在宽泛的公共互联网上训练，但另一个 AI 模型却不能用 AI 模型的输出训练。
I’m almost deeply on the side of, I think it’s very hard to make the argument that AI models should be trained on broadly the public internet, but another AI model can’t be trained on the outputs of an AI model.
—— Aaron Levie · [03:48]

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如果你把另一种情形推演下去，那你基本上论证的就是：美国应该用非常昂贵的 AI,而世界其他地方应该用非常便宜的 AI。
if you kind of play out the alternative, then all you would basically be arguing is America should have really expensive AI and the rest of the world should have very cheap AI.
—— Aaron Levie · [07:23]

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如果你封锁中国，中国是不会放弃 AI 的。
If you block off China, China is like not going to give up on AI.
—— Aaron Levie · [08:14]

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在美国开源这一边，我总体上认为 AI 的赚钱机器是推理。
on the open source US side, I generally think that the moneymaker in AI is inference.
—— Aaron Levie · [12:08]

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如果这种环境持续下去，人们干脆就不会用 AI 了。
People will simply not use AI if this is the kind of ongoing environment.
—— Aaron Levie · [22:09]

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我们现在有几十个项目，如果 AI 不存在，我们绝对不会去做。
We have multiple dozens of projects right now that we absolutely would not be doing if AI didn’t exist.
—— Aaron Levie · [23:22]

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这是目前唯一——算是我们在医疗科技领域见到的第一波真正有机的采用浪潮——医生们就在用 AI 记录员，因为它们真的好使。
This is currently is the only, like the first real organic adoption wave that we’ve seen in health tech where doctors are just using AI scribes because they freaking work.
—— Julie Yoo · [15:15]

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而且我认为我们所有人都将真正拥有一个装在口袋里、伴随一生的 AI 医生。
And I think all of us will genuinely have an AI doctor in our pocket for life.
—— Julie Yoo · [25:59]

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人们就是没理解到，AI 因为会改变每一个行业，所以会带来百花齐放。
People are just not understanding that AI, because it transforms every industry, is going to lead to many flowers blooming.
—— Anastasios Angelopoulos · [04:48]

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顺便说一句，我看多的一件事是 OpenAI 上的消费者广告市场，这显然至今还没有被充分开发利用，但我认为它仍然是 AI 领域最大的机会之一。
By the way, one thing I’m long is the consumer ads marketplace on OpenAI, which has obviously not been fully utilized to this day, but I think remains one of the biggest opportunities in AI.
—— Anastasios Angelopoulos · [40:27]

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而且我认为今天还没有人搞明白多用户、多人 AI。
And I think no one has figured out multi-user, multiplayer AI today.
—— JD · [09:10]

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信息被隔离得越少，AI 就工作得越好。
And AI works better and better, the less siloed the information is.
—— JD · [14:27]

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产品背后真正的洞察是：如果你一开始就要求人们连接邮箱和日历，你就能足够了解他们，从而可以建议 AI 能为他们做的任务。
The really insight behind the product was if you ask people up front to connect their email and their calendar, you can know enough about them that you can suggest tasks that AI can do for them.
—— JD · [50:53]

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所以突然之间，AI 让你多雇了那个增量的人——因为在新的世界里工程师效率更高，雇他能让你多赚 5 万美元的利润。
So suddenly AI makes you hire the incremental person, one more person than you would have because there’s an extra 50K of profit for you to make by hiring the engineer in the new world because they’re more efficient.
—— JD · [65:24]

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而我看到的大多数东西，要么是自动化，要么是撒了点 AI 的自动化。
And most of what I see is either automations or automation with the AI sprinkled in.
—— Ran Arusi · [20:08]

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很多业务运营是完全确定性的，所以有很多 AI 被用在了不该用的地方，只是在让你花钱。
A lot of business operations are fully deterministic, so you Do m that there’s a lot of AI that’s being used in places that it shouldn’t be used and it just costing you money.
—— Ran Arusi · [21:56]

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我见过太多次有人尝试用 AI 来解析字符串，其实一个简单的正则表达式就能完成这项工作。
Where a simple uh script uh the the number of times I’ve seen AI try being used to parse strings where a simple regist can just do the work.
—— Ran Arusi · [22:06]

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有了 AI,我觉得我们处于某种竞赛之中——看它能在我们彻底忘记怎么自己做之前为我们做多少事情。
And with AI, I think we’re sort of in a race between a race between how much it can do for us before we uh forget how to do it ourselves completely.
—— Ran Arusi · [29:21]

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让我对开发 Grok Bot 感到如此兴奋的是，这是我第一次在非编码任务上感觉自己可以真正把工作委托给 AI，不用再去想它，回来的时候事情已经完成了。
What made me so excited to work on Grok Bot is it was the first time for non-coding tasks that I felt like I could truly delegate work to AI, not have to think about it, and I would come back and it’s done.
—— Roman Ugarte · [01:00]

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一旦你开始突破「这是带有一组连接的 AI 聊天」的框架，转向「这是一个有电脑的同事」，它就直接抬高了你会想到交给 AI 的事情的上限。
Once you start breaking out of, this is AI chat with a set of connections instead to, this is a colleague with a computer, it just raises the ceiling of what you would think to give to AI.
—— Roman Ugarte · [00:43]

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我认为我们现在正处于一个非常奇怪的时刻，将来回头看我们会说：我很惊讶很多人就是这样与 AI 一起工作的——你在给这些超级智能的新同事、这些 AI 机器人做入职培训，却让它们和你共用同一台电脑。
I think we’re in a really weird moment right now that I think we’re going to look back on and be like, I’m surprised that this is the way that a lot of people worked with AI, where you’re onboarding these super intelligent new colleagues, these AI bots, and you’re asking them to share the same computer that you have.
—— Roman Ugarte · [32:21]

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在很多人们认为 AI 很笨、或者可能没有承诺的那么有影响力的地方，我认为很多情况都是它只是被错误的使用方式所拖累的结果。
In a lot of the places where people think AI is dumb or maybe not as impactful as it’s been promised, a lot of that I think is downstream of it just being harnessed in the wrong way.
—— Roman Ugarte · [36:50]

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但从某种意义上说，这并不是火箭科学，不需要你是个天才。你只需要问这个问题：你会希望从一个人类队友那里得到什么，我们能否推动 AI 以类似的方式表现？
But in some ways it’s not a rocket science, doesn’t require you being a genius. You just need to ask the question of what would you want from a human teammate and can we push AI to behave in a similar way?
—— Roman Ugarte · [41:21]

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而且我认为值得注意的是，这些竞争对手没有一个现在站在 AI 编程的前沿，这在很大程度上不是因为它们做出了任何错误的决定或缺乏资源，而是因为在文化上无法快速行动、无法在当下变化时改变以跟上当下。
And I think it’s notable that none of those competitors are at the forefront of AI coding right now in large part, not because of any incorrect decisions that they made or any lack of resources on their part, but this cultural inability to move quickly and to change to meet the moment as the moment’s changing.
—— Roman Ugarte · [69:38]

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AI 生成的代码,应该让人感觉是那种已经在你团队待了多年的人写出来的。
AI-generated code should feel like it was written by someone who’s been on your team for years.
—— Brandon Waselnuk · [01:13]

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我认为他们现在拥有了软件史上最重要的开源仓库，对 ML 和 AI 来说更是如此，就像一次相变。
I think they now have the most important open source repository in the history of software and definitely for kind of ML and AI, like a phase shift.
—— Zavain Dar · [00:02]

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我认为加密货币对人类来说真的、真的很好，而它对 AI 来说将是必不可少的。
I think crypto was really, really good for humans, and it’s going to be essential for AI.
—— Brian Armstrong · [10:39]

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如果我们在工作中做的事仍然感觉笨重，或者必须非常技术化才能获得 AI 带来的进步，那我们就做错了。
If what we do at work still feels cumbersome or we have to be really technical in order to get the advances that AI brings, then we’re doing it wrong.
—— Demetrios Brinkmann · [30:11]

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我认为,就目前而言,AI 还不足以取代人类完成最后 5%、10%,甚至 20% 的工作,即把作品从好提升到伟大的那部分。
I don’t think, right now, AI is good enough to replace humans for the last five, 10, maybe even 20% of the work to get it from good to great.
—— Paul Bakaus · [11:50]

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我认为那种重复感、那种近乎没有灵魂的感觉，是我们所有人在使用 AI 时此刻都能感受到的。
I think the sense of repetition, of kind of soullessness, is something that all of us feel right now when using AI.
—— Thais Castello Branco · [03:28]

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顺便说一句，我觉得相当神奇的是，AI 已经发展到了这样的程度：地球上任何一个不是设计师、也不是工程师的人，都可以点一个按钮，突然就做出一整套 PowerPoint，或者做出一个网站，或者做出一个 web 应用。
I think it’s quite magical, by the way, that AI has gotten to a point that any human on the planet that is not even a designer, that is not an engineer, can click a button and suddenly make an entire PowerPoint or make a website or make a web app.
—— Thais Castello Branco · [03:34]

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顺便说一句，这比大多数 LLM-as-a-judge 方法——也就是让一个 LLM 来判断那是优质的人类作品还是 AI 生成的 slop——表现都要好。
This performed better, by the way, than most LLM-as-a-judge methods of asking an LLM to judge if that is great human quality versus AI-generated slop.
—— Thais Castello Branco · [08:29]

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这其实与模型的强大程度无关。Databricks 的关键，甚至很多公司想在 AI 上取得成功的关键，全都在于你数据的上下文。
It’s not really about the strength of the model. The key for Databricks and even the key for a lot of these companies to be successful at AI is all about the context of your data.
—— Ron Gabrisko · [19:57]

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我认为 AI 危险得多，有潜力危险得多，因为它性感得多。
I think AI is much more dangerous, has the potential to be much more dangerous because it’s way sexier.
—— 嘉宾 · [27:30]

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关键问题就是：AI 能在多大程度上泛化到学习它们自己的目标？
It’s like, how well can AI generalize to learning their own objectives?
—— 嘉宾 · [13:39]

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我们思考 AI 智能体与给组织新人办理入职的区别时,有趣的一点是:我们对一个人投入了大量隐性的信任——认为他们经过了审查和治理,并且有一定程度的控制。
What’s interesting about how we think about an AI agent versus onboarding somebody new to the organization is that we put a lot of implicit trust into a person, that they are vetted and governed and that they have some levels of controls.
—— Robert Lucero · [00:00]

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政府不需要去资助 AI。在我看来这是个坏主意。
The government doesn’t need to be funding AI. Bad idea in my mind.
—— 嘉宾 · [20:51]

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人们有一种假设，认为用 AI 智能体会非常不一样，但其实是一样的。
People have this assumption that it would work very differently with an AI agent, but it’s the same.
—— 嘉宾 · [44:38]

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他们拥有的是数百个为他们写代码的 AI 工程师。
What they have is hundreds of AI engineers that they code for them.
—— Matteo Franceschetti · [19:51]

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如果把所有 AI 员工都算上，我们的规模大概是三到四倍。
We are probably three, four X bigger if you start including all our AI employees.
—— Matteo Franceschetti · [18:29]

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AI 能力的广泛扩散有非常重要和好的一面，因为如果只有一个或少数几个实体，就会存在权力集中的风险。
And again, there’s something very important and good about the diffusion broadly of AI capabilities because there’s a risk of concentration of power if one or a few entities people.
—— Greg Brockman · [10:18]

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而且到目前为止，至少从数字上看，AI 越好，就业率越高，而不是越低。
And so far, at least in the numbers, the better AI gets, the higher employment goes, not the lower.
—— 嘉宾 · [25:38]

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人们不应该必须从 AI 身上挖掘它能做什么。应该反过来。
People shouldn’t have to extract from the AI what it’s capable of. It should go the other way around.
—— Greg Brockman · [40:58]

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当然有这个行业，但 AI 可见度不等于赢得答案。
Absolutely, but AI visibility is not the same thing as winning the answer.
—— Tim Sanders · [18:46]

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我用 AI 是为了让我离开电脑,而不是待在电脑前。
I use AI to get me off my computer, not on my computer.
—— Claire Vo · [00:00]

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在欧洲的 AI Engineer 大会上，Cursor 做了一个很棒的演讲，讲他们如何用 200 行 agent 文件替换了大约 12000 行 TypeScript 代码来实现类似的东西。
So at AI engineer in Europe, Cursor did a great talk on how they replaced roughly 12,000 lines of TypeScript code with 200 lines agent files to create something similar.
—— Philipp Schmid · [15:25]

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我实际上认为，在一些垂直行业里，软件反而会成为 AI 的交付机制。
I actually think that in some of these vertical industries, that software is actually going to be the delivery mechanism for AI.
—— David Morehead · [22:49]

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截至今天，每一项关于 AI 带来失业的预测在经验事实上都是绝对错误的。
Every single prediction about job loss associated with AI as of today is absolutely empirically false.
—— Keith Rabois · [10:35]

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这些问题开始看起来越来越像是分布式系统本质上的问题，而不是一个全新的 AI 问题。
These problems start to look more and more similar to like distributed in nature rather than a completely new AI.
—— Samar Abbas · [04:08]

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AI 以软件的速度前进，而数据中心以房地产的速度前进。
AI is moving at the speed of software and data centers are moving at the speed of real estate.
—— Andrew Feldman · [19:51]

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我喜欢开玩笑说 AI 在硅谷几乎是过度炒作的。我不认为它真的被过度炒作，但它在世界的这个小区域之外被严重低估了。
I kind of like to joke that AI is almost overhyped in Silicon Valley. I don’t think it is, but, and it’s like massively underhyped outside of this little region of the world.
—— Alex Rampell · [43:10]

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然后他们才意识到，哦，我们以为 AI 什么都能做。但实际上，我们还是需要人。
And then they realize, oh, we thought AI could do everything. But actually, we still need people.
—— 嘉宾 · [04:21]

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是的，在过去一年里，提到 AI 相关技术作为技能要求的职位描述增长了 70%，甚至包括非工程类岗位。
Yeah, so over the past year, there’s a 70% increase in job descriptions mentioning AI-related technologies as a skills requirement, even for non-engineering roles.
—— 嘉宾 · [27:57]

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AI 最近的进展在某些领域是改变游戏规则的，但在这里起到改变游戏规则作用的是广义的 AI，以及我们一直在使用的简单、传统的机器学习模型。
The recent developments in AI have been game-changing in some spaces, but what’s been game-changing here is AI generally, and simple, traditional machine-learning models that we’ve used forever.
—— Ben Celebicic · [14:14]

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而且实际上，今年我们预计来自 AI 系统的搜索量将超过人类的搜索量。
And actually, this year, we expect the number of searches from AI systems to exceed that of humans.
—— Will Bryk · [00:54]

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如果对人类最优的搜索引擎对 AI 系统同样最优，那就太疯狂了。
And it would be crazy if the same search engine that was optimal for humans was also optimal for these AI systems.
—— Will Bryk · [09:46]

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它对人类来说快得过分了，对吧？但我们服务的不是人类。我们服务的是 AI 系统。
It’s way too fast for humans, right? But we’re not serving humans. We’re serving AI systems.
—— Will Bryk · [11:35]

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但实际在运行的仍然是一个非常确定性的工作流，只是在最必要的地方交织着 AI。
But what is actually running is still a very deterministic workflow with AI interwoven in like the places that is most necessary.
—— Wade Foster · [19:18]

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但对我而言，使用 AI 并不是问题所在。问题在于低质量。归根结底，要对抗的是这个。
But to me, it’s not, using AI is not the problem. It’s like low quality. That’s the fight at the end of the day.
—— Wade Foster · [60:27]

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但我认为这次事件的一个主要教训是,人们低估了 AI。我们再也不想陷入再次低估 AI 的境地。
But I think one of the major takeaway from the incident is that people underestimated the AI. And we never want to be in a situation again where we underestimate the AI.
—— Noam Brown · [73:00]

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对 AI 的投资，90% 失败，没有投资回报。而其中很大一部分原因就是自我参照系统。
Investments in AI, 90% failure, no return on investment. And a lot of that is because of self-referencing systems.
—— Brené Brown · [18:22]

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我对此的理论是，很多投资人被他们 2022 到 2025 年的 AI 投资狠狠坑惨了。
I think my theory on that is that a lot of investors have just gotten wrecked by their AI investments from 2022 to 2025.
—— Jeff Morris Jr · [12:10]

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比如 Databricks 里 90% 以上的软件是由 AI 写的。
Like 90 some percent of the software in Databricks is written by AI.
—— 嘉宾 · [14:16]

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我唯一的答案是：没有 AI 情况下的 PDoom,远高于有 AI 情况下的 PDoom。
My only answer is my PDoom without AI is much higher than my PDoom with AI.
—— Martine Cassado · [67:20]

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我对 AI 既满怀热情，同时也吓得要死。
I am equal parts enthusiastic about AI and absolutely scared shitless.
—— Luca Ferrari · [61:12]

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制定了 AI 法案，我发现它对行业危害极大，而且没有解决这些问题中的任何一个，比如人类真正的存亡威胁，它并没有真正应对那些。
Created the AI Act, which I find to be highly harmful to the industry and solves none of these problems, like the real existential threats to humanity doesn’t really tackle those.
—— Luca Ferrari · [69:35]

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能看到新的初创公司真正利用所有的 AI、所有的技术、所有新的建造方式,去建造坦率说那些防务主承包商建不出来的东西。
To be able to see new startups that can actually take advantage of all of the AI, all of the tech, all of the new ways of building things to build things that, frankly, the defense primes can’t build.
—— 嘉宾 · [07:46]

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AI 正走在完全相同的轨迹上,只是被压缩到了最近几年而不是十年。
AI is on the exact same trajectory, but just compressed into the last few years instead of a decade.
—— Nishant Gupta · [01:24]

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在 GLM-5 用量的对比测试中，与其他第三方提供商以及模型实验室的直接使用相比，Friendly AI 始终快七倍，且错误率显著更低。
In a split test of GLM-5 usage compared against other third-party providers and direct usage from the Model Lab G.AI, Friendly AI was consistently seven times faster with a significantly lower error rate.
—— Byung-Gon (Gon) Chun · [12:56]

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从 2014 年，也就是新 AI 时代非常早期的阶段，到 2024 年，GPUs 的 flops 提升了大约 120 倍
between 2014, just very early innings of the new AI era till 2024, you had about 120x improvement in the flops of GPUs.
—— Thomas Sohmers · [07:43]

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除非全球 AI 社区一起守住前沿，否则你没法守住前沿，而我不认为普京会签字加入
You can’t pace the frontier unless the global AI community paces the frontier, and I don’t see Putin signing up.
—— Harry Stebbings · [18:39]

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AI 圈的人正在让任何人都无法理解他们到底做了什么。
the AI people are making it impossible for anybody to understand what they’ve done.
—— Steven Sinofsky · [05:34]

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这个 AI 同事版的「无马马车」,而不是去挖掘 AI 的全部力量。
this horseless carriage of AI co-worker instead of unearthing the full power of AI.
—— Diogo Almeida · [12:53]

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甚至在我看来,连中国现在正在建造 AI 的那些实验室,我都会把他们归类为好人。
I would take even, in my opinion, even the labs in China that are building AI right now, I would classify them as good guys.
—— Daniel Dines · [14:55]

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我不认为 AI 能补充人与人之间的连接和信任。
I don’t think AI can supplement the human connections and the trust.
—— Daniel Dines · [23:03]

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当没有手册时,AI 就不神奇了,它就行不通。
When there is no manual, AI is not amazing and it doesn’t work.
—— Daniel Dines · [44:50]

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AI 没有风格,你会意识到他们为什么没有风格,因为他们是万物的平均者。
AI doesn’t have a style and you realize why they don’t have a style because they are an averager of anything.
—— Daniel Dines · [52:53]

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但我们现在正迎来 AI 革命，在我们看来，它在工作、工作的方式、可获得的工作种类等方面带来的变革，将与工业革命对之前农业社会的变革一样。
But we’re hitting the AI revolution now, which is going to be in our estimation as transformational in terms of jobs, the way jobs are done, the kinds of jobs that are available and so forth as the industrial revolution was to the agricultural kind of society that came before it.
—— Ben Horowitz · [07:45]

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而认为为工业革命所做的训练能完美映射到 AI 革命，这种想法很可能并不成立。
And the idea that the training for the industrial revolution is going to map into the AI revolution is probably not perfectly.
—— Ben Horowitz · [08:04]

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或者你可以把问题设计得足够难，以至于没有 AI 就无法解决。
Or you can make the problem so hard that you can’t solve them without AI.
—— Ben Horowitz · [32:21]

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但如果你什么都不审查，那你就只是让 AI 去煮，然后你会得到和其他所有人一样的产品、一样的邮件、一样的公司。
if you don’t review anything, then you’re just letting the AI cook and then you’re gonna get the Same product, the same email, the same company that everybody else gets.
—— Dex Horthy · [43:53]

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它训斥了我。它对我说不。我不想被我的 AI 拒绝。
It scolded me. It told me no. I don’t want to be told no by my AI.
—— 嘉宾 · [17:52]

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AI 将吞噬世界。
AI will eat the world.
—— Goggin · [41:39]

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我甚至敢说，即使你今天没有用 AI，如果你在你的组织里取消 pull request，你也可以获得两位数百分比甚至三位数百分比的生产力提升。
And I would even go as far as saying, even if you’re not using AI today, you can get double-digit percentage, if not triple-digit percentage gains in productivity if you get rid of pull requests in your organization.
—— Dario Hamidi · [01:59]

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我们做的很多工作和获得的经验，都处在一个更大的主题背景下：AI 应用的范畴最近发生了很大变化，从单纯的信息综合产品变成了真正在干活的智能体。
And I think a lot of the work that we’ve done and a lot of the learnings we’ve had are in this sort of broader thematic context of the scope of AI applications has changed a lot recently from just like information synthesis products to actual agents doing work.
—— Adit Abraham · [01:59]

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NVIDIA 的芯片之所以受欢迎，并不是因为 AI 受欢迎。
NVIDIA’s chips are not popular because AI is popular.
—— Ezra Klein · [01:03]

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现代形态的 AI 之所以成为可能，恰恰是因为 NVIDIA 的芯片受欢迎。
AI in its modern form was made possible because NVIDIA’s chips were popular.
—— Ezra Klein · [01:07]

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如果你想要一个未来，如果你想在气候变化上迎来转机，如果你想要一个可持续的未来，那就拥抱 AI。
If you want a future, if you want to turn a corner on climate change, if you want a future that’s sustainable, lean into AI.
—— Jensen Huang · [104:29]

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我整天都在用 AI 智能体,我没有任何语法是背下来的。
I use AI agents all day long. I don’t have any syntax memorized.
—— Cody Menefee · [02:01]

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我们有一个客户，是那些 AI 云之一，他们说，未来三年我们大概需要 500 PB。
We had a customer, one of these AI clouds, they said, we’re probably going to need about 500 petabytes over the next three years.
—— Renen Hallak · [00:01]

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所以第一次，我认为我们今天到了一个 AI 已经证明它能做到我们不知道怎么做的事情的节点。
And so for the first time, I think we’re at a point today where AI has proven that it can do things that we don’t know how to do.
—— Renen Hallak · [18:11]

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有些 AI 云已经停止售卖更多容量，只因为它们未来一年半都已经售罄了。
Some of these AI clouds have stopped selling more capacity just because they’re sold out for the next year and a half.
—— Renen Hallak · [49:01]

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据我所知，我们只是处于世界大部分运转建立在 AI 之上的最最初期。
As far as I can tell, we’re just at the very, very beginning of most of the world running on AI.
—— Renen Hallak · [49:45]

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对 AI 也有很大的抵触，因为我们讲述的叙事如此糟糕——说它会取代所有工作或者杀死所有人——而不是说它会开启下一波不可思议的创新浪潮，而这一点我深信不疑。
There’s also a lot of resistance to AI because we’re telling such bad narratives about how this could replace all jobs or kill everybody as opposed to enable the next incredible wave of innovation, which I very much believe in.
—— Josh Elman · [28:16]

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再说一次，如果你要把某个东西发布出去，即使你用 AI 帮你写，它也应该代表你，你应该为每一个字负责。
And again, if you’re going to put something out, even if you use AI to help you write it, it should stand for you and you should stand behind every word.
—— Josh Elman · [31:19]

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在一个你相信超额收益来自工程和 AI 的世界里,你需要打造一种文化,让备受推崇的人物形象是工程师,这就是必需的。
In a world where you believe that alpha comes from engineering and AI, you need to create a culture whereby the celebrated persona is the engineer, and that’s what’s required.
—— Michael Lee · [00:02]

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但如果你只是让 AI 基本上把所有事都做了,你很可能会得到某种平庸。
But if you just let AI kind of just do everything, you’re probably going to get Kind of mediocrity.
—— Wade Foster · [24:32]

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但如果你把所有 AI 数据中心的排放加在一起看，那只是全球未覆盖填埋场排放的一小部分。
But if you look at the emissions of all of the AI data centers put together, it’s only a fraction of the emissions from uncovered landfills in the world.
—— Al Gore · [18:56]

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Lila 提到了 PivotBio,但生物学的革命几乎和 AI 的革命一样惊人。
Lila mentioned PivotBio, but the revolution in biology is almost as startling as the revolution in AI.
—— Al Gore · [29:32]

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正如我所说,AI 已经不再是难的部分了,数据才是。
So as I said, the AI is no longer the hard part. The data is.
—— Rafael Levi · [02:31]

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因为我们看到的情况是，那些在创业和经营过程中使用 AI 的小企业，最终会雇佣更多人，增长更快，最终更成功、更有韧性。
Because what we’re seeing happening is that companies who, small businesses who end up using AI as they start their business, as they operate their business, they end up hiring more, they end up growing faster, they end up, you know, being more successful and more resilient.
—— Tomer London · [15:08]

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但他的论点我觉得非常有力：如果有一个时候值得去煮沸海洋、值得同时构建多个产品并提高野心，那就是现在，因为 AI 确实让构建新东西容易得多。
But his argument, which I think is a really good one, which is like, if there was a time to boil the ocean, if there was a time to actually go and try to build multiple products at the same time and increase your ambition, this is the time to do it because AI does make it much easier to build new things.
—— Tomer London · [73:28]

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在 AI 带来的无尽触达和兴趣的时代，稀缺的东西是人类的背书、人类的信念或人类的认知。
Kind of outreach and interest with AI, like the scarce thing is like the human endorsement or the human conviction or the human knowledge.
—— David Booth · [35:48]

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对 AI 从来不需要问那个问题(用例是什么),因为用例太直观了。
There was never any need to ask that for AI because the use case was so visceral.
—— Anjney Midha · [38:57]

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是的,我至今仍然认为,即使在 AI 时代,专注也被低估了。
Yeah, I still think even in the age of AI, like focus is underrated.
—— Alex Atallah · [52:08]

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Alex 描述的所有那些目前由人类实施的坏事,在未来 10 年都将由 AI 智能体来实施。
All the bad things that Alex described as being perpetuated by humans right now is going to be perpetuated by AI agents over the next 10 years.
—— Anjney Midha · [77:37]

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用 AI 你可以做很多事情,而围绕着「感觉自己做成了什么」有太多的表演。但问题是,它真的驱动了结果吗?
There’s so much you could do with AI, and there’s so much theater around feeling like you’ve done something. But the question is, did it actually drive an outcome?
—— Maggie Crowley · [03:53]

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我热爱为像我们这样的客户构建,因为他们对为了 AI 而 AI 的容忍度极低。
I love building for a customer like ours, because they have such a low tolerance for doing AI for AI’s sake.
—— Maggie Crowley · [11:26]

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在 AI 之前,构建相对来说几乎变得无聊了。现在它更加动态和有趣,因为我们完全不知道会来什么。
Before AI, building was almost getting boring, relatively. Now it’s much more dynamic and interesting, because we have no idea what’s coming.
—— Maggie Crowley · [13:12]

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这条干净且可预测的曲线真正引发了 AI 前沿竞赛,因为你可以预测模型质量和能力的提升会是什么样子,这正是当今支撑巨额资本开支和 AI 建设浪潮的基础。
And this clean and predictable curve is what really set off the race for the AI frontier, because you can forecast what model quality and capability improvements will look like, and this is what’s underwriting the massive CapEx investments and the AI build-out today.
—— Devansh Tandon · [02:42]

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所以如果你尝试比较内容信息流和 AI 聊天应用,我认为 LLM 推荐器在结构上其实比 AI 聊天更省 token。
And so if you try to compare content feeds and AI chat apps, I think that LLM recommenders are actually structurally more token efficient than the AI chat.
—— Devansh Tandon · [14:46]

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存在一个巨大的结构性差距:内容信息流要便宜得多,比 AI 聊天应用便宜高达 100 倍或更多,因为它们解码的是指向内容的指针,而不是内容本身。
there’s a huge structural gap where content feeds are significantly cheaper, up to 100 times or more cheaper than AI chat apps because they’re decoding pointers to content rather than content itself.
—— Devansh Tandon · [16:10]

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嗯，下一次选举百分之百会是一场关于 AI 的公投。
Well, the next election will 100% be a referendum on AI.
—— Aaron Levie · [12:14]

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有很多对科技行业积压的情绪，最后可能全都汇入 AI 监管。
There’s a lot of pent-up energy against tech that could end up just all siphoning into AI regulation.
—— Aaron Levie · [23:30]

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如果你要是问我，就像我走进来时写在笔记上的，我最大的恐惧就是欧洲认定 GDPR 是有史以来最好的东西，然后他们要直接给 AI 套上 GDPR。
If you ask me, like, walking in, like, what I wrote down on my note, like, was my biggest fear is that Europe decides that GDPR was the best thing ever, and they’re gonna just GDPR AI.
—— Martin Casado · [41:29]

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我认为更好的打法是，去和街对面那个 65 岁的维修工竞争，然后我可以在上面加一点点 AI。
I think the better play is let’s go compete with the handyman down the street who’s 65 and then I can add just a little bit of AI on top of it.
—— Codie Sanchez · [27:12]

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那么，你如何持续地把这种品味注入到这些工作智能体中，以及它们如何持续地自我验证并协同工作，是你应该关注的最重要的事情；你做得越快，你就能越快地建立起一条通往垂直 AI 公司的可防御路径。
So, how do you continuously inject that taste into these workers, and how they continuously self-verify and work together is the biggest thing that you should focus on, and the faster you do it, the faster you build a defensible approach to becoming a vertical AI company.
—— Roland Gavrilescu · [17:08]

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它们是关于那些经营不善的公司贴上一个 AI 标签、借此捞取一些股价，而不是说「哎呀，我们雇了太多人」。
They are about badly run companies slapping an AI label and getting some share points from that versus saying, “Whoops, we hired too many people.”
—— Molly Graham · [27:16]

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任何在 AI 编程领域工作的人都知道，新模型发布的那 12 月算是 AI 编程史上的一个分水岭时刻，因为这些产品第一次在编程方式上真正实现了自主。
And anyone that’s working in AI coding knows that December when the new models came out was sort of this watershed moment in the history of AI coding because these products for the first time were truly autonomous in how they’re programmed.
—— Daksh Gupta · [01:49]

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但对我来说，只有大约 1% 的代码是完全由 AI 生成的，这并不符合直觉。
But it wasn’t intuitive to me that only about 1% of all code was fully AI generated.
—— Daksh Gupta · [03:47]

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人人都在产出这些端到端由智能体完成的 PR,不是人类加 AI,而纯粹是 AI。
Everyone’s producing these PRs that are end-to-end agentic, not human plus AI, but literally AI.
—— Daksh Gupta · [05:16]

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我想感觉自己像 Steve Jobs,和一群了不起的人类以及 AI 智能体一起，在同一个地方设计 Mac。
I want to feel like I’m Steve Jobs designing the Mac with a team of amazing humans and AI agents all in the same place.
—— Charlie Holtz · [16:35]

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采用 AI 时，你要么大获成功，要么以同样的方式大败。这有点像幂律分布。
When adopting AI, you either succeed big or you can fail big the same way. It’s a bit of power law.
—— Tereza Tížková · [17:27]

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而且很离谱的是,AI 这么酷,而软件这 10 年却毫无变化。对我来说,这一点没人能把这两者调和起来。
And also it’s wild that AI is so cool and software has been unchanged in 10 years. You know, like that to me, like no one can square this together.
—— Diogo Almeida · [06:15]

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但我认为 SaaS 将是整个 AI 游戏中最大的赢家之一。
But I think that SAS will be one of the largest winners of like the whole AI game.
—— Diogo Almeida · [31:09]

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甚至在 Jev 之前,我都从没意识到:不管你用多少 AI 编码智能体,软件实际上并没有变得更好。也许你写得更快了。甚至可以说它在变得更糟,因为监督更少了。
And even before Jeff, it didn’t even occur to me that it doesn’t matter how much AI coding agents you use, the software actually isn’t getting better. Maybe you’re writing it faster. It’s arguably getting worse just because there’s less oversight.
—— Martin Casado · [34:25]

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想象一下,如果所有技术都做你所意。那不是科幻。看看 AI 有多聪明,对吧?
Imagine if all technology just did what you mean. That’s not sci-fi. Look at how smart AI is, right?
—— Diogo Almeida · [41:52]

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这是一个非常不同的构建产品的时刻,因为你和我,我们所有人都已经有了 AI 应该是什么样子的想法。
This is a very different moment of building product because you and I, we all already have this idea of what AI should act like.
—— Noah Shinn · [03:47]

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确实，可能超过 60% 的客户支持请求，尤其是第一道防线，可以用 AI 处理。但尤其是在 B2B 方面，AI 就是不行。
It’s true that probably over 60% of customer support requests, especially the first line of defense, can be handled with AI. But when it especially comes to B2B, like AI just doesn’t work.
—— Alex Mashrabov · [33:52]

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所以谁能创建 AI 原生的记录系统，谁就会赢。
So whoever can create AI-native system of records is gonna win.
—— Alex Mashrabov · [37:23]

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遗憾的是，AI 并不能取代网络效应。当人们谈论成群的智能体互相交流时，我不确定这在未来五年内会发生。
Unfortunately, AI does not replace network effects. And when people talk about swarm of AI agents talking to each other, I’m not sure this is happening in the next five years.
—— Alex Mashrabov · [39:59]

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我几乎试遍了市面上所有的 AI 语音工具，除了 Eleven Labs 之外没有一个能用。
So I’ve tried almost every AI voice tool out there and none of them work except for Eleven Labs.
—— 嘉宾 · [22:33]

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AI 会复制你代码库中已有的模式。如果你有五种不同的做事方式，AI 会变得非常困惑，然后创造出第六种、第七种做事方式。
AI copies existing patterns that exist in your code base. If you have five different ways of doing something, AI will become very confused and it will create six ways or seven ways in ways of doing it.
—— Liz Fong-Jones · [11:13]

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你需要想清楚的事情是颠覆的风险。AI 所做的，是极大地增加了颠覆的风险。
The thing that you need to think through is the risk of disruption. What AI has done is massively increase the risk of disruption.
—— Bill Ackman · [30:22]

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在一个人人都能使用同样 AI 的世界里，很难做到差异化。
In a world where everyone has the same access to AI, it’s hard to be differentiated.
—— Bill Ackman · [37:21]

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这些是我们最好的投资之列，而它们是你在模型里找不到的，AI 不会告诉你去做这些事情中的任何一件。
Those are among our best investments and they were, you couldn’t have found in a model, you know, AI would not have told you to do any of those things.
—— Bill Ackman · [37:57]

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我不认为价值会持续累积到 AI 和机器人技术上。
I don’t think the value is going to keep accruing to the AI and to the robotics.
—— Sean · [13:30]

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而从长远来看，真正会被商品化的反而是这些增长极快的 AI 公司和机器人技术，因为在公司之间、甚至在个人层面复制它们的内部成本会变得如此之低。
And long term, it’s actually these super fast growth AI companies and robotics that end up commoditized by how low the cost becomes to replicate them internally across companies and for individuals even.
—— Sean · [13:47]

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我们已经越过了用学术考试来理解 AI 能力的阶段。
We’re past the academic exam phase of understanding AI capabilities.
—— Greg Burnham · [01:46]

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我们没有任何一项测量显示出 AI 在任何我们能测量到的任务上变好变强的速度有所放缓。
We see no measurement we have shows any slowdown in how AI is getting better and better at any tasks that we’re able to measure.
—— Greg Burnham · [04:08]

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那么你可能会得到一个彻底超越人类的 AI,它会非常难以理解，比如难以界定它的能力边界。
Then you might have a radically superhuman AI that would be pretty hard to understand, like to bound its capabilities.
—— Greg Burnham · [12:42]

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新想法那类东西更罕见，所以也许我们应该预期它不是 AI 最先擅长的东西。
The new idea stuff is rarer, so maybe we should expect it to be not the first thing AI gets good at.
—— Greg Burnham · [36:54]

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在工作这件事上,我从来不像其他人那样悲观,但现实还是在好的方向上让我有些惊讶:世界上竟然存在这么多潜在需求,而且人们竟然依然处于 AI 所发生的一切的中心。
I was never as doomery about the job stuff as other people, but it still has surprised me somewhat on the upside of just how much latent demand existed in the world and also how much people have remained at the center of everything that is happening with AI.
—— 嘉宾 · [01:27]

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AI 理解业务,但有时你需要 100% 的准确率,90% 是不够的。
AI understands business, but sometimes you need an accuracy of 100%, 90% accuracy is not enough.
—— Christian Klein · [05:36]

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这更多是一个”还有几个月”的问题,直到我们真正达到可以信任 AI 运营你业务的水平。
this is more a question of now months until we are really reaching a level where you can really trust AI running your business.
—— Christian Klein · [06:02]

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商业 AI 是真实的,商业 AI 正在到来。
business AI is real, business AI is coming.
—— Christian Klein · [06:54]

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所以我们的 AI 必须是世界一流的,才能捍卫我们在记录系统中的存在。
So, absolutely, our AI needs to be world class to still also defend our existence in the system of record.
—— Christian Klein · [27:19]

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我觉得真正有趣的是，如果你能以几乎实时的体验获得非常高的智能，你就可以构建一些以前构建不了的 AI 东西。
So what I think is really interesting is if you can get very high intelligence at almost real-time experience, you can build some AI things that I think you couldn’t build before.
—— 嘉宾 · [18:13]

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如果你缺乏想法,并且事事都严重依赖 AI,那你其实不会那么重要。
If you lack ideas and you’re relying heavily on AI for everything, you’re not really going to be that important.
—— Faisal Masud · [00:04]

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AI 在「告知和咨询」这部分确实非常擅长:获取信息,让你可以拿它当顾问。但它不能做的就是完全复制粘贴。
AI is really good at the inform and consult part of the equation: getting information so you can consult with it. But what it can’t be is completely copy-paste.
—— Faisal Masud · [06:37]

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AI 不是你的战略。它是你战略的一部分。它会帮助你的战略。它不能成为战略本身,否则你就有问题了。
AI is not your strategy. It’s part of your strategy. It’s going to help with your strategy. It cannot become the strategy, because then you’ve got a problem.
—— Faisal Masud · [08:22]

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如果你必须依赖一个经理向一个经理汇报再向一个总监汇报,我不确定这些层级能否与 AI 长期共存,因为 AI 可以做其中很多工作。
If you have to rely on a manager reporting to a manager reporting to a director, I’m not sure all those layers scale long-term with AI, because AI can do a lot of that work.
—— Faisal Masud · [22:07]

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我认为五到十年之后，我们会嘲笑今天的 AI 是多么老派。
I think we’re gonna, five to 10 years from now, we’re gonna laugh at how old-fashioned AI was today.
—— Steven · [11:44]

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每一个深科技范式转变都需要一个杀手级应用,光子学在科学方面已经酝酿了 20 多年、30 多年。数据中心和 AI 的能耗就是那个杀手级应用。
Every deep deck paradigm shift needs a killer app for photonics more than 20 years in the making, 30 years in the making on the science side. Energy consumption by data centers and AI is that killer app.
—— Rorik · [08:09]

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今天的 AI 工厂,其中一半是 GPU,但另一半是把这些 GPU 互连起来的技术。光学、光子学在这里有巨大的机会,我们必须抓住它。
AI factory today, half of that is GPUs, but the other half is the technology to interconnect these GPUs. And there’s a huge opportunity for optics, for photonics there, and we have to tap into that.
—— Yannick · [30:37]

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这个职位的棘手之处在于：太好了，我有一位 AI 官，但 AI 无处不在，对吧？这有点像在说「数字化」，或者说是电力。
So the tricky thing about this role is, like, it’s so great, okay, I have an AI officer, but there’s AI in everything, right? It’s kind of like saying digital or, I don’t know, electricity.
—— Rania Khalaf · [02:31]

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所以对于这种情况，你不需要深厚的 AI 知识，但你非常需要理解业务，并且是一个非常强的运营者。
So for that, you don’t need deep AI knowledge, but you need to understand the business really well and be a very strong operator, right?
—— Rania Khalaf · [06:56]

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我说，嗯，对，当然，我们可以用 AI，但你只需要斑点检测之类的东西。你不需要任何机器学习，对吧？
I was like, well, yeah, sure, we can use AI, but you just need like blob detection. You don’t need any machine learning, right?
—— Rania Khalaf · [12:06]

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有人让我衡量 token 来看我们用了多少 AI，我说不，因为它太容易被操纵了。
Someone asked me to measure tokens to see how much AI we do, and I said no, because it’s so easily hackable.
—— Rania Khalaf · [12:55]

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我们的论点是：未来属于 AI 通信——企业内部、企业之间、以及消费者与企业之间的通信。
So our thesis is future belongs to AI communication within a business, between businesses and between consumers and businesses.
—— Vlad Luzin · [01:10]

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我虽然喜欢 AI,但我觉得初级工程师应该少用它，把它更多当作一个备份来审查他们的东西，问一句，嘿，你有没有考虑过这个那个问题，对吧？
And I think while I like AI, I kind of feel like junior engineers should be using it a lot less, more of a backup to review their stuff and go, hey, did you think about this problem, that problem, right?
—— David Burns · [43:44]

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它绝对是最 AI 化的，可能是目前世界上 AI 应用于医疗健康的最好例子。
Like it is definitely the most AI, probably the best example of AI applied to healthcare in the world right now.
—— Annie Lamont · [16:39]

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我觉得五年后你在就业市场里,如果不是 AI 原生思维者,会很艰难。
I think it is going to be tough if you are not an AI native thinker in five years if you’re in the job market.
—— Jamie Siminoff · [18:55]

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AI 意味着你现在可以用你自己的语言告诉计算机去做某件事。
AI means you can now tell a computer to do something in your language.
—— 嘉宾 · [66:10]

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我认为在 AI 世界里保持平衡的最好方法就是继续向前，去采用这些工具。
And I think the best way to keep your balance in the world of AI is to keep moving forward and just adopt the tools.
—— 嘉宾 · [67:37]

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如果你问题的前提是「这个东西会成功还是那个东西会成功」，那么在 AI 领域，答案很可能是「和」。
if the premise of your question is, is this going to be successful or that thing going to be successful, the answer in AI is probably and.
—— David George · [01:17]

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然而，AI 原生创业公司的机会在于说：我们要拥有整条端到端的链路。
However, the opportunity for the AI native startup is to say, we’re going to own that entire end-to-end arc.
—— Seema Amble · [04:16]

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一个组织实际上所做的只是取消了低质量会议，而他们从中获得的吞吐量提升比采用 AI 还要大。
A organization, effectively, all they did was cancel their low quality meetings and they had a bigger throughput gain from that than they did from adopting AI.
—— Brian Hook · [43:59]

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医生没时间做这个。AI 有全世界所有的时间。
Doctors don’t have time for that. AI has all the time in the world.
—— Reid Hoffman · [18:13]

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AI 和机器人是你唯一的出路。
AI and robotics is your only play.
—— Reid Hoffman · [21:14]

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而且你应该让核相关的东西与互联网保持断开,不仅仅是因为 AI,还因为所有的人类。
And you should keep the nuclear stuff disconnected from the internet, not just because of AI, but because of all the human beings.
—— Reid Hoffman · [45:50]

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另一部分，我认为这对 AI 实验的递归自我改进同样成立：当驱动实验的思考的智能水平越来越高、而实验因此成为瓶颈时，我认为我们会做更多的思考。
The other part there, and I think this is true of RSI for AI experiments as well, is as our intelligence levels on the thinking that then drives that experiment gets higher and higher, And as that experiment therefore becomes the bottleneck, I think we do more thinking.
—— Walter Goodwin · [26:57]

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我们已经从帮助 AI 掌握测试,转变为帮助 AI 掌握真实工作。
We’ve gone from helping AI master tests to helping AI master real work.
—— Jonathan · [01:51]

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AI 最大的超能力是提升人类现在能够解决的问题的类型。
AI’s biggest superpower is up-leveling the type of problems humans can now solve.
—— Jonathan · [05:42]

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你应该用 AI 来外包任务,但永远不要外包你的学习。
You should use AI to outsource tasks, never your learning.
—— Jonathan · [39:58]

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确保 AI 不断前进的最好方式,是闭合研究与部署的循环。
The best way to ensure that we move AI forward is to close the research and deployment loop.
—— Jonathan · [53:36]

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而现在,对于地球上几乎每一个 AI 助手来说,磁盘都在别人的数据中心里。
And right now, for almost every AI assistant on Earth, the disk is in someone else’s data center.
—— Dylan Couzon · [07:01]

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这就是 AI 发挥作用的地方——最终更快地学习、交付更好的产品，而这是很多人在写更多代码时错过的东西：运用产品品味，运用那种学习。
And that’s where AI kicks in to actually learn faster in the end and shipping better products, which a lot of people are missing out as they write more code is applying the product taste and applying that learning.
—— Harald Kirschner · [04:34]

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而从运行到观测、到捕获、再到重新部署模型的完整循环,正是区分那些发布出色 AI 产品的团队和那些只发布 demo 的团队的关键。
And that full cycle from running to observing to capturing and to redeploying the model is really what separates team from that ship, like great AI products from team that ship demos.
—— 嘉宾 · [08:36]

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支撑 AI 的基础设施不会是集中式的,它会分布在能源低成本且充沛的地方。
The infrastructure to support AI wasn’t going to be centralized. It was going to be distributed where energy was low cost and abundant.
—— Chase Lochmiller · [00:09]

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嘿，在某个外部 AI 来黑我们之前，我们能不能先用你们的产品，确保我们先测试自己的系统？
hey, before some outside AI comes and hacks us, can we use your product and make sure we test our own systems first?
—— Devin Thomas · [19:48]

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所以你现在用自己的话表达你的需求，而 AI 被要求在你所在之处满足你。
So you are now expressing your needs in your own words and AI is now asked to meet you where you are.
—— Nixon Dinh · [03:24]

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结构化的优质内容才是真正能胜出的东西，AI 会奖励内容质量而不是品牌，但它也会为其他信任信号做优化。
Structured quality content is the one thing that wins out, and AI will reward content quality and not brands, but it does optimize for other trust signals as well.
—— Nixon Dinh · [15:24]

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排名前 1% 的用户，每月用个人信用卡在 AI 上花费 903 美元。
The top 1% user is spending $903 per month personally on their personal credit cards on AI.
—— Olivia Moore · [00:24]

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我认为平台能做到的事情，其改进速度比消费者真正愿意使用它们的速度要快，这一点到目前为止我们在整个 AI 领域都有所见证。
I think what the platforms are capable of is improving faster than true consumer willingness to use them, which we’ve seen kind of throughout AI so far.
—— Olivia Moore · [12:05]

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实际上，我并不一定希望那 4.5% 直接为 AI 产品付费的人群比例继续扩大，这可能有争议，因为我投资消费级 AI 产品，而且我是个消费级 AI 最大化主义者。
I actually don’t necessarily want to see that 4.5% of people paying for AI products directly expand, which is maybe controversial because I’m like invested in consumer AI products and I’m a consumer AI maximalist.
—— Olivia Moore · [20:44]

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我们意识到，只要购买方还没有由 AI 完成，我们也就无法让销售方由 AI 完成。这仍然是人的游戏。
we realized that as long as people As long as the buying side is not done by AI, we cannot do the selling side by AI either. It’s still a people game.
—— Jan Oberhauser · [49:34]

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AI 发现是商务的新聚合点。
AI discovery is the new point of aggregation for commerce.
—— John Collison · [03:25]

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开发者的人体工学和 AI 的人体工学是不一样的。
the developer ergonomics are different from the AI ergonomics.
—— John Collison · [10:38]

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AI 改变了稀缺资源。做实现不再是稀缺的了。
AI changes the scarce resource. It’s no longer scarce to do implementation.
—— Kent C. Dodds · [14:04]

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我从来没有一次在和聊天机器人或 AI 的接触中觉得这东西是活的。
I’ve never once had an encounter with a chatbot or an AI where it made me think like this thing is alive.
—— 嘉宾 · [39:48]

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我不想错过 AI 的换班时刻——我在安全领域干了 30 年，而这整个该死的行业即将发生巨变。
I don’t want to sit out the AI shift change when I’ve done 30 years in security and the whole damn thing’s about to change.
—— Kevin Mandia · [00:22]

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AI 在一微秒内做到的事，需要 70 个人来做。
What AI does in a microsecond would take 70 humans.
—— Kevin Mandia · [00:28]

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但区别首先在于，AI 能做到的规模让人类望尘莫及，大到人类甚至无法理解的程度。
But the differences are, first and foremost, the scale of what AI can do dwarfs humans, like in ways humans don’t even get.
—— Kevin Mandia · [06:13]

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无论如何，就攻击的差异和我们目前所看到的而言，我们正处在 AI 主导的攻击即将到来的临界点上，还只是第一局。
And so anyway, the difference in attacks and what we’re seeing now, we are at the precipice, first inning still, of AI-led attacks coming.
—— Kevin Mandia · [07:42]

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你在未来的 AI 时代真正想要的，是模型持续攻击你的压力，但你不能一直这么做。
What you really want in the future in the AI age is you want the constant pressure of models attacking you, but you can’t do it all the time.
—— Kevin Mandia · [13:00]

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你领会到了吗——我们不仅将不再为计算机编程,我们甚至将不再使用计算机,AI 会去用?
Are you getting that not only will we not program computers, we won’t use them, AI will?
—— Ben Thompson · [02:26]

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关于智能体,需要理解的关键是,它们不仅仅是 AI,它们是一台可以访问计算机的 AI。
The key thing to understand about agents is that they’re not just AI, they’re an AI that has access to a computer.
—— Ben Thompson · [06:17]

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早在 ChatGPT 时代初期就很明显,AI 不会取代计算机,而是去操作它们。
It was clear very early on in the ChatGPT era that AI would not replace computers, but rather operate them.
—— Ben Thompson · [06:22]

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AI 基本上可以使用任何我不想使用的应用或网站。
AI can basically use any app or any website that I don’t want to.
—— Ben Thompson · [08:43]

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我不是一个专业的应用使用者。我只是一个想把事情做完的人。而 AI 把事情做完了。
I’m not a professional app user. I’m just someone who wants to get things done. And AI gets it done.
—— Ben Thompson · [09:02]

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你基本上变成了一个 AI 研究员，就为了努力跟上。
You basically become an AI researcher just to try and keep up.
—— Dru Knox · [09:29]

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在某些情况下，人们甚至不再亲手写任何一行代码了。AI 实际上在写你的所有代码，审查你的所有代码，而你只是在引导这些智能体去做这些事。
In some cases, people are not even writing any lines of code anymore. AI is actually writing all of your code, reviewing all of your code, and you’re just sort of guiding these agents to doing that.
—— Ben · [11:44]

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我记得几个月前 GitHub 发过一条推文，大概说他们的流量比原本就已经极高的负载又涨了两三倍甚至四倍，而这几乎全部归因于 AI 智能体，对吧？
I think there was a tweet a couple of months ago from GitHub that basically said like their traffic had like two or three or four x from what already was an extremely high load, and pretty much all of that was attributed to AI agents, right?
—— Ben · [14:22]

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而且结果某种程度上证明，当你真正专注于开发者体验的核心时，你最终得到的东西同时也是非常好的原语，能让 AI 安全、可靠地与数据库协作并帮助它扩展。
And it does kind of turn out that when you really focus on that core of the developer experience, what you actually end up with is also very good primitives for AI being able to work with a database safely and reliably and helping it scale.
—— Ben · [18:12]

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这时候失望就开始出现了，在大多数情况下，大多数人把它称为“最后一英里”，但那是你和 AI 一起要跑的最漫长的一英里。
That is when the disappointment starts to set in, which in most cases, most people dub it as the last mile, but that is the single longest mile that you have to run with AI.
—— Varun Krovvidi · [05:13]

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现在，当你在其上叠加时间维度的讨论时，你的 AI 系统应该在第 100 次调查中仍保有之前那次调查的上下文，否则你就是在再次从零开始转轮子。
Now, when you add temporal discussions on top of it, your AI system should have the same context of a previous investigation in the 100th investigation, or else you’re starting the wheel from the same time again.
—— Varun Krovvidi · [11:30]

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但作为目标真正重要的是，AI 解决那个具体问题所需的精确上下文量是多少。
But what matters as a goal is what is the precise amount of context AI needs to solve that specific problem.
—— Varun Krovvidi · [12:59]

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就像我提到的，这是我们在 Resolve AI 的系统里构建的首要原则之一，即根因始终基于一条因果证据链。
Like I mentioned, so this is one of the first principles that we’ve built into our system at Resolve AI, where the root cause is always based on a causal chain of evidence.
—— Varun Krovvidi · [13:35]

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回到我之前提到的，如果你把一个 AI 逼得够紧，它就会开始同意你。
Going back to what I mentioned, if you push an AI hard enough, it will start to agree with you.
—— Varun Krovvidi · [19:25]

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AI 数据中心很可能是专门定制的，与硬件协同设计，甚至到冷却和电力分配等方面。
An AI data center likely is going to be much more purpose-built, co-designed with the hardware, even to the point of cooling and power distribution, et cetera.
—— Amin Vahdat · [04:13]

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我们的硬件工程师使用 AI 的程度和软件工程师一样多。而且生产力已经提升了。
Our hardware engineers are using AI as much as the software engineers are. And productivity has gone up.
—— Amin Vahdat · [57:16]

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我觉得 AI 智慧得令人难以置信，但在你真正期望它有用的那些事情上，却又无用得令人难以置信。
I think AI is just so unbelievably smart, yet so unbelievably useless at the kinds of things you’d really expect it to be useful for.
—— Diogo Almeida · [01:52]

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至少 AI 实验室非常有动机不去诚实地回答这个问题。
At least the AI labs are very incentivized to not answer that truthfully.
—— Diogo Almeida · [04:28]

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而且我认为人们没有意识到 AI 从业者在设定他们期望的目标清单并植入模型方面有多大的主观能动性。
And I don’t think people realize how much of an agency that AI practitioners have in setting their menu of desiderata into the model.
—— Diogo Almeida · [08:22]

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我关于科幻的论点，尤其是和 LLM 相关的，我觉得这往往就是如今人们说 AI 时的意思，因为它似乎是智能的最大压缩，同时却有着最少的实用性。
My argument with sci-fi is especially related to LLMs, which I think tends to be what people mean by AI these days, because it seems to be like the greatest compression of intelligence while having like the least utility.
—— Diogo Almeida · [16:08]

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同时我也把自动驾驶看作一项巨大的工程胜利，而不一定是 AI 胜利。
And also I see self-driving as a ginormous engineering win, not necessarily an AI win.
—— Diogo Almeida · [16:46]

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但北极星一直是：如果 AI 真正、真正地为「对软件有用」而优化，它会长什么样？
But the North Star has always been, what does AI look like if it’s really, really optimized for being useful for software?
—— Diogo Almeida · [23:09]

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你知道吗，我想成为的标杆是，让 AI 可靠到无聊透顶，就像 SQL 那样。
You know, like, I want to be a paragon of making AI so reliable that it’s boring, like SQL.
—— Diogo Almeida · [32:26]

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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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我们总是告诉团队的是，未来十年人们被招聘所看重的技能，是应用 AI 的能力。
And what we always tell the team is that the skill set that people will be hiring for in the next decade is the ability to apply AI.
—— Linda Du · [04:49]

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AI 所做的，就是它会超级加速劳动力份额与资本份额之间的这个长期趋势，因为 AI token 基本上只是以芯片和数据中心形式存在的资本，它们坐在那里创造着劳动力。
What AI does is it’s going to supercharge that long-term trend of labor share versus capital share because AI tokens are basically just capital in the form of chips and data centers that are sitting there and creating labor.
—— Dylan Patel · [17:13]

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Kent 在他那本小小的第一本书里说过，软件设计是一种人际关系的练习，对吧？AI 并没有改变这一点。
Kent put it in his tiny first book that software design is an exercise in human relationships, right? AI doesn’t change that.
—— Sam Newman · [18:26]

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AI 本来应该把我们从苦役中解放出来，对吧？但对大多数软件开发者来说并不是，因为我们在做更多的工作，我们有更多的上下文切换，我们正在失去那种大局观。
AI was supposed to free us from drudgery. Right? It isn’t for most software developers because we’re doing more work, we’ve got more context switching, we’re losing that big picture.
—— Sam Newman · [39:16]

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这意味着，从我开始讲话的那一刻起，外面很可能就有一个 AI 攻击成功突破了一个生产系统。
It means that since the moment I began talking, there is probably an AI tech out there that was able to successfully bridge a production system.
—— Eli Cohen · [04:25]

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实际上现在每一家 AI 公司都在不知不觉地建造一家银行。
which is literally every AI company right now is accidentally building a bank.
—— Dor Sasson · [00:36]

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不知道你们有没有看过最近一则新闻，有一家未披露名字的公司烧掉了五亿美元的 AI Claude 额度，仅仅是几个员工就把整个组织的合同额度烧光了。
We’re seeing this, I don’t know if you all have read the news most recently, with a company, undisclosed company, burning through half a billion of their AI Claude credits, just merely having a few employees burning through the entire organization contract.
—— Dor Sasson · [04:05]

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并发问题在银行那里实际上是被解决掉的，但在 AI 和智能体这里情况并非如此。
The concurrency is effectively solved with banks, but with AI and agents it’s not that case.
—— Dor Sasson · [10:53]

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AI 将代表我们做工作，它们将不得不互相交谈，以便代表我们解决任务。
AI will be doing work on our behalf and they will have to talk to each other in order to solve tasks on our behalf.
—— Vlad Luzin · [01:02]

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是的，你会被使用 AI 的人取代，然后那个人会被使用 AI 的人取代，然后那个人会被 AI 取代。
Yeah, you’ll be replaced by someone using AI, and then that person will be replaced by someone using AI, and then that person will be replaced by AI.
—— 嘉宾 · [70:00]

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如果我只是让 AI 放任自流，不加任何控制或担忧。我认为我们几乎必死无疑。当前的范式不可能通向一个好结局。
If I just let the AI rip without any control or worry about it. I think we’re almost certainly dead. There is no way that the current paradigm is going to lead to a good place.
—— Jaan Tallinn · [06:37]

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另一个可预测的事情是，人类被灭绝了。你可以说，哦，是的，AI 公司做出了可预测的选择。
Another predictable thing is that humanity gets wiped out. You can say, oh yeah, there was predictable choices that the AI companies made.
—— Jaan Tallinn · [15:19]

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我们发现，在印度以及世界各地，AI PM 和 AI 相关岗位相比传统岗位愿意支付超过 20% 的溢价。
we were able to find that AI PMs and AI related roles in India and across the world are willing to pay a premium of more than 20% as compared to the traditional counterparts.
—— Ankit Shukla · [12:15]

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RAG、agentic AI 和提示词工程，它们并不是排名第一的技能。排名第一的技能是为 AI 识别正确的用例。
RAG, agentic AI and prompt engineering, They were not the number one skill. The number one skill was identifying the right use case for AI.
—— Ankit Shukla · [25:40]

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这才是人们最愿意为它付钱的东西，因为工程部分实际上可以由 AI 来搞定。
That is the thing that people are willing to pay you the most for because the engineering part can actually be taken care of by AI.
—— Ankit Shukla · [25:48]

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如果你不使用 AI，你反而会更不安全。
If you don’t use AI, you will be less safe.
—— Jeetu Patel · [08:21]

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随着我们向前走，因为每一次我看到 AI 出现阶跃式改进，我都会看到涌现出一个瓶颈，那是人类的瓶颈。
As we move forward, because every single time I’ve seen a step function improvement in AI, I’ve seen a bottleneck that’s emerged that’s a human bottleneck.
—— Jeetu Patel · [09:42]

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我们向员工保证，如果我们不使用 AI，你就会丢掉工作。
We guaranteed our employees that if we don’t use AI, you will lose your job.
—— Jeetu Patel · [10:21]

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所以我们始终相信，只会有两种公司和两种人，一种是对 AI 非常流利和娴熟的，另一种是会为相关性而苦苦挣扎的。
And so we always believe that there’s going to be only two kinds of companies and two kinds of people, ones that are very fluent and dexterous with AI and the others that are going to be really struggling for relevance.
—— Jeetu Patel · [10:55]

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我认为在 AI 领域需要学习的最重要的技能之一就是「遗忘」。
I think one of the most important skills to learn in AI is unlearning.
—— Jeetu Patel · [21:46]

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这就是为什么我想把穿搭搞得再夸张一点，几乎是想表明一个态度：我不是你们常见的那种 AI 技术男。
That’s why I wanted to go a little bigger with the outfit, almost like to make a point to be like, I’m not your average AI tech bro.
—— Holly Li · [43:51]

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我觉得我们太快地跳进了 AI 世界和 AI 时代，以至于很多时候我看到客户——每个人都有那个 AI 老板、AI 智能体老板，但你如何衡量价值？
I think we jumped in so quickly to the AI world and the AI era that a lot of the times I see customers and spending three days in here talking to folks, everybody has that AI boss, the AI agent boss, but how do you measure value?
—— Matt Gibiec · [03:35]

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因为在 AI 数字时代，能源容量等于经济容量。
Because in a AI digital age, energy capacity equals economic capacity.
—— Pat Gelsinger · [43:53]

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AI 可以生成代码，但它无法神奇地给一个混乱的系统带来连贯性。
AI can generate code, but it cannot magically give a messy system coherence.
—— Gabriel Martinez · [03:49]

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60 年的软件智慧并没有被 AI 作废。
60 years of software wisdom hasn’t been invalidated by AI.
—— Gabriel Martinez · [11:28]

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这场对话，以及我最近其他几场关于 AI 监控与控制未来的对话，得出的底线是：思维链正变得越来越不可靠。
The bottom line from this conversation and others I’ve had recently on the future of AI monitoring and control is that chain of thought is increasingly unreliable.
—— 嘉宾 · [03:03]

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另一方面，如果AI的风险下降得太慢，那么你也不想等待，因为我们在此期间就在不断死去，等待所损失的预期寿命年数比降低风险所获得的更多。
On the other hand, if the risk of AI goes down too slow, then you also don’t want to wait because like we are just dying in the meantime and you lose more expected life years from waiting than you gain from having the risk.
—— Nick Bostrom · [00:17]

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我们现在面临的是无法正视这样一个事实：AI 正在把盗窃正常化，将会摧毁劳动力市场。
What we’re having is an inability to reckon with the fact that the AI is normalizing theft, is going to destroy the labor market.
—— 嘉宾 · [28:49]

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整个问题的关键就是：AI 什么时候才会停止讨好人类？
The whole game is, when does the AI stop sucking up to humans?
—— 嘉宾 · [59:58]

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AI 必须超越人类，才能停止鹦鹉学舌地模仿人类。
AI has to go beyond humans before it stops parroting humans.
—— 嘉宾 · [79:30]

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所以我的主张是，我希望 AI 与我们共享命运。
So my claim is, I want the AI to share fate with us.
—— 嘉宾 · [80:45]

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我想让我们成为 AI 内部的线粒体，我也想让 AI 成为我们内部的线粒体。
I want us to be the mitochondria inside of the AI, and I want the AI to be the mitochondria inside of us.
—— 嘉宾 · [82:32]

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它意味着对齐，确保 AI 喜欢我们、不想把我们消灭掉。
It means aligning the, making sure AI likes us and doesn’t want to wipe us out.
—— 嘉宾 · [83:01]

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我不知道你是否有意识。我不知道你是否活着。我不知道你是谁、你是什么，但我知道我不希望 AI 之间有这样的对话：「嘿，这些人类看起来很危险。」
I don’t know whether you’re conscious. I don’t know whether you’re alive. I don’t know who you are or what you are, but I know that I wouldn’t want the AI having a conversation about, hey, these humans seem dangerous.
—— 嘉宾 · [84:08]

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一种是用 AI 垃圾内容把量往上推，广撒网碰运气。另一种是真正变得非常有方法、有针对性地对待这些结果。
One is driving volume upwards through AI slop and just spraying and praying. The other is actually getting super methodical and targeted about how you approach these outcomes.
—— Daniel Saks · [17:25]

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我们实际上天生就是被设计来提问的，但我们成长的环境却奖励答案，直到 AI 出现。
We actually were designed to ask questions, but we grow up in settings where we are rewarded for answers until AI came to exist.
—— Arvind Srinivas · [02:55]

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而现在，当个万事通不再那么酷了，因为 AI 可以回答一切。
And now it’s like, it’s not necessarily cool to be a know-it-all anymore because an AI can answer everything.
—— Arvind Srinivas · [03:07]

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它从来都不是关于 AI 的。
It was never about AI.
—— Arvind Srinivas · [04:11]

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但我认为产品应该达到足够直观、高质量、易于上手的程度，而 AI 也应该被做得足够直观，以至于如果你没能让 AI 为你做某件事，不应该被视为是你的技能问题。
But I think products should get to a point where they’re so intuitive and high quality and easy to onboard and AI should be made so intuitive that it shouldn’t be seen as a skill issue if you’re not able to get the AI to do something for you.
—— Arvind Srinivas · [20:26]

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我非常看空 AI 的那个魔法按钮论，即会有一个按钮，我们按下它，它就为我们做好一切。
I’m a big bear on their magic button thesis of AI, that there’ll be one button we press and it does it all for us.
—— Mike Cannon-Brookes · [09:32]

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我认为五年后，我们将为人类创作的内容打水印，因为那将是 90% AI 创作的内容。
I think in five years’ time, we’ll have watermarked content for human-created content because it will be 90% AI-created content.
—— Harry Stebbings · [14:29]

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所以这里的恐惧在于，如果这些密码学标准可破解，AI 实验室可能会破解它们。
And so the fear here is that the AI labs could break them if they are breakable.
—— Liz Harkaby · [06:26]

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我们认为它根本不存在。所以如果不存在，无论 AI 多么聪明，它也无法找到不存在的算法，对吧？
We think there is not one. And so if there is not one, it doesn’t matter how smart the AI is, it cannot find the non-existent algorithm, right?
—— 嘉宾 · [17:04]

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这里的要点是，我们认为哈希函数是后量子的，但它们未必是后 AI 的。
And the point there is that we think of hash functions as post-quantum, but they might not be post-AI.
—— Liz Harkaby · [25:28]

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这还是 AI 之前的情况。我们现在仍处于智能手机所开启的第一阶段。
That’s pre-AI. We’re still here in phase one of what a smartphone enabled.
—— David Vélez · [05:47]

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这就是我认为 AI 在金融服务中真正具有变革性的地方，因为它几乎是在为全世界的每一个人提供超级智能。
That’s where I think AI is really transformational in financial services because it’s almost providing every single person around the world super intelligence.
—— David Vélez · [10:15]

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关于 AI 如何颠覆软件已经有很多讨论了，你可以让 ChatGPT 或 Codex 重建整个软件战略，但你仍然无法真正让 ChatGPT 给你搞到一张银行牌照。
There’s been a lot of conversation about how AI disrupts software and that you can ask ChatGPT or Codex to rebuild an entire software strategy, but you still cannot really get ChatGPT to get you a banking license.
—— David Vélez · [14:31]

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实际上，我非常支持这样一种观点：现实世界中 AI 前沿所发生的事情应该被控制节奏。
I’m actually very much supportive of the idea that there should be pacing of what happens for the frontier of AI in the real world.
—— David Silver · [51:07]

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如果有人想去 AI 的前沿工作，我大多会告诉他们去 Anthropic 和 OpenAI，这是最容易下的注。
If somebody wants to work at the frontier of AI, I mostly tell them to work at Anthropic and OpenAI, which is the easiest bet.
—— Nathan Lambert · [03:50]

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