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AI

AI

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本站收录 17 集 · 302 条金句 · 关联 10 个

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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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