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本站收录 4 集 · 245 条金句 · 关联 10 个

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245 条

为我提供针对我当下要解决的问题集的最佳可能方案——这就是每一个消费者体验将会有的感觉。
And therefore providing me with the best possible solution to the sets of things that I’m trying to solve for right now is how every consumer experience is going to feel like.
—— Rishabh Jain · [30:22]

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作为房间里工程方面的声音之一,不得不对业务团队说不,真的非常不舒服——就是那种:好主意,但这需要我六到八个月去重新架构并重构我们在业务定价上做的每一个假设。
I found it really uncomfortable to be one of the engineering voices in the room, having to tell no to business teams on like, you know, fantastic idea, but it’s going to take me six to eight months to re-architect and refactor every assumption we’ve made around pricing in the business.
—— Alvaro Morales · [04:48]

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每一次重大的平台转移,不仅催生了一代提供重大创新的公司,也颠覆了软件的商业模式。
Every major one has not only resulted in just a generation of companies providing significant innovation, it’s also disrupted the software business model.
—— Alvaro Morales · [13:23]

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我们真正在构建的是一个数据平台,能够独特地把每一个产品使用单元连接到收入。
What we’re really building is a data platform that can uniquely connect every unit of product usage to revenue.
—— Alvaro Morales · [29:15]

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Bash 本质上是相当危险的，并且它能以意想不到的方式改变系统状态。但与此同时如果你必须手动批准每一条 bash 命令，作为一名工程师这超级烦人，而且你无法真正提高生产力，因为你只是在不断地批准每一条命令。
Bash is inherently pretty dangerous and it can change system state in unexpected ways. But at the same time if you have to manually approve every single bash command, it’s super annoying as an engineer, and you can’t really be productive because you’re just constantly approving every command.
—— Boris · [24:21]

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我认为 Anthropic 大约 80% 的人员是技术人员，每天都使用 Claude Code。
I think about 80% of people at Anthropic that are technical use Claude Code every day.
—— Boris · [27:08]

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但我认为从那个说法到说，比如，好吧，地球上的每一件事物都将在区块链上运行，这就是我的警报开始响起的地方。这就像，好吧，它可能是一项很棒的技术，并且可能非常成功，而不必征服世界
But I think going from that to saying like, okay, every single thing on the planet is going to run on the blockchain, that’s where some of my alarms start to go off. And it’s like, well, it can be a great technology and it can be very successful without having to take over the world
—— Sebastian Barrios · [43:44]

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他有一句话是，「你必须问为什么，为什么个人计算是在 1960 年代末在北加州开始的，当时这个国家的每一家主要科技公司都在东海岸。答案是因为斯坦福大学周围有很小的一群人，他们将软件视为一种与电影、音乐和书籍同等地位的新型媒体。」
And he has this quote that is, “you have to ask why it is personal computing got started in Northern California in the late 1960s when at the time every major tech company in the country was on the East Coast. And the answer is because there was a very small group of people in and around Stanford University that saw software as a new form of media on par with movies, music and books.”
—— Bob Baxley · [55:16]

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所以基本上，对于每一个工作单元，你应该让下一个工作单元更容易做。
So basically, for every unit of work, you should make the next unit of work easier to do.
—— Dan Shipper · [42:10]

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这有点好笑，因为这个叙事每六个月左右出现一次，而且从未成真，所以我有点希望人们看到它时脑子里能有一个废话探测器。
It’s kind of funny because this narrative comes out every six months or so and it’s never been true, and so I kind of wish people would have a little bit of a bullshit detector in their heads when they see this.
—— Benjamin Mann · [08:06]

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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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世界上每个工程师都知道这是衡量生产力的愚蠢方式。
Which every engineer in the world knows is an idiotic way to measure productivity.
—— Bret Taylor · [67:11]

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我是说，我们评估过的每一个开箱即用的评分体系都很烂。
I mean, every out-of-the-box stack that we’ve evaluated sucks.
—— Ankur Goyal · [21:34]

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所以一个每周进步 1% 的团队与一个每月进步 1% 的团队相比，即使是从一个低得多的基线开始，也会在非常短的时间内胜过那个没有变好的团队。
So a team that just gets 1% better every week compared to a team that gets 1% better a month. is even if they start off at a much lower baseline is going to outperform in a very short amount of time, the team that doesn’t get better.
—— Julie Zhuo · [58:34]

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我现在就可以告诉你，我管理的每一位经理当他们说我觉得这不是个好主意时，我能想到没有任何一种情况是那个项目最终变得极其成功的。
I can tell you right now, every single manager I’ve ever managed where they’re like, I don’t really think this is a good idea. There’s no case where I can think of the project somehow turned out to be like wildly successful.
—— Julie Zhuo · [72:01]

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我相信每个方向都有无限。所以这让我对几乎任何人说的话都相当持相反意见。所以如果有人像在 Twitter 上说什么，我有时和自己玩这个游戏，就是在什么语境下那实际上不成立？
I believe that there’s infinity in every direction. So that makes me pretty contrary on pretty much everything that anyone says. So if someone says something like on Twitter, I sometimes play this game with myself, which is in what context would that actually not be true?
—— Julie Zhuo · [80:20]

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所以我们的目标之一是确保，每当我们收到来自客户的反馈，它都能在 24 小时内进入我们的代码库。
So one of our goals is to make sure that, like, every time we cut feedback from customers, that gets to our code base in 24 hours.
—— Evan Reiser · [27:06]

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这相当于每周从零开始完整重做两次 Stack Overflow。
This is the equivalent of doing Stack Overflow completely from scratch twice every week.
—— Roshan · [17:51]

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并不是每一件伟大的事情都会由你发明。
Not every great thing is going to be invented by you.
—— Robby Stein · [31:26]

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你会在每个系统中达到这些边际收益递减的点，感觉就像你可以在这个项目上放 50 个人，但它不会显著地移动指针。
You get to these points of just diminishing marginal return in every system where it feels like you could put 50 people on this project, it’s just not going to dramatically move the needle.
—— Robby Stein · [41:00]

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我真正推动团队去思考的事情之一是，如果每一次发布，删除整个应用并从头开始重建它，我们的世界会是什么样子？
one of the things I’m really pushing our teams to think about is what would our world look like if every single release, RM minus RF deleted the entire app and rebuilt it from scratch?
—— Dhanji Prasanna · [35:21]

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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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因为对他来说，每一个错误都是他可以收集的宝石，他实际上可以成为一个优秀的滑雪者。
Because to him, every one of those was a gem that he could collect, and he could actually become a good skier.
—— Stewart Butterfield · [48:23]

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但每次你将决策能力或自主权移交给智能体系统时，你都在某种程度上放弃了一些你的控制权。
But every time you hand over decision-making capabilities or autonomy to agentic systems, you’re kind of relinquishing some amount of control on your end.
—— Kiriti Badam · [10:12]

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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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当你真正接受它时，你会意识到你在评测上投入的工作，不会在你每次尝试新模型、改一些措辞或稍微改变用例时就蒸发掉。
When you really embrace it, you realize that the work that you put into doing evals doesn’t evaporate every time you try a new model or you change some wording or you change your use case a little bit.
—— Ankur Goyal · [06:00]

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你为公共消费撰写东西的每一分钟，都没有把你有非常有限的时间集中在你的客户和产品上。
Every minute you’re writing something for public consumption, you’re not focusing your very limited time that you have on your customers and your product.
—— Qasar Younis · [42:11]

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99% 的时间他们会告诉你除了真实原因之外的每一个原因。
99% of the time they will tell you every reason except the real reason.
—— Keith Rabois · [53:02]

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自动化是个谎言，从某种意义上说，每次你自动化某样东西时，为了确保自动化运行良好，你需要一个人在上面确保它运行良好。
Automation is a lie, in the sense that every time you automate something, in order to make sure the automation is working well you need a human on top of it making sure that it’s working well.
—— Dan Shipper · [39:15]

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我喜欢行业中每一个新的混乱时期，因为那是学习正在发生的地方。
And I love every new chaotic period in the industry because that’s where the learning is happening.
—— Patrick Dubois · [00:30]

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良好的变更管理并承认每次你例如替换智能体中的 LLM 时，它的行为都会不同。如果你不在你的治理中考虑到这一点，你的最终用户将承担其后果。
Good change management and acknowledging that every time you, for example, replace the LLM in an agent, it will behave differently. And if you don’t take that into account in your governance, your end users will bear the burden of that.
—— Emil Lassen · [20:09]

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很难想象单一提供商、单一公司如何能在其中的每一个组件中都做到业内最佳，对吧？
It just seems hard to imagine how a single provider, a single company could be best in breed at every single component that goes into that, right?
—— Andrew · [32:47]

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那个仪表图总是告诉我们，大约每四个月，智能体能够自主运行的时间量大约会翻倍。
So the the meter chart always shows us that roughly every four months, the amount of time that agents are able to run for autonomously is like doubling.
—— Lamus Mukta · [15:52]

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所以这就是为什么我认为这对每个人来说都很重要，要意识到我们有能力把一个天才级别的联合创始人放到每个人身边，男人、女人、小孩，无论年龄、信仰、国家、性取向如何。
So this is why I think it’s so important for everybody to realize we have the ability to put a genius level co-founder beside every single human, man, woman, child, independent of age, creed, country, sexual orientation.
—— Chamath · [08:39]

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我现在能想到的每一份工作，我都可以提出理由说它绝对有可能被取代。
every job I can currently think of, I could make a case, potentially, that it could absolutely be replaced.
—— Dan · [17:03]

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我宁愿每隔几年遇到那样的抵制,但继续进化并保持相关性,也不愿选择另一种方案,那就是我们没有视频,没有私信,没有快拍,没有排名。
i would much rather have backlashes like that every couple years but continue to evolve and continue to stay relevant than the alternative which would have been like we didn’t have video we didn’t have dms we didn’t have stories we didn’t have ranking
—— Adam Mosseri · [58:31]

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每次航班起飞，大约有 400 条生命处于危险之中。
Every time a flight takes off, about 400 lives are at stake.
—— Kriti Sharma · [14:56]

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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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但每个创业者在心里都知道那其实就像造一架通往月球的梯子。所有这些创可贴,他们讨厌它,他们都讨厌它。
But every entrepreneur knows in their hearts that that’s actually like building a ladder to the moon. All these band-aids, they hate it, they all hate it.
—— Astro Teller · [14:59]

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但如果我让你去月球,而你向我展示你每天都离月球近一英尺,没意思。大概有一架通往月球的梯子,而我担心有很多 Product Market Fit 是如此孤岛化。那就是在造一架通往月球的梯子。你也许能造一架相当高的梯子,但你不会以那种方式到达月球。
But if I ask you to get to the moon, and you show me that you’re a foot closer to the moon every day, not interesting. There’s probably a ladder to the moon and I worry that there’s a bunch of Product Market Fit that is so siloed. It’s just building a ladder to the moon. You might build a pretty tall ladder, but you’re not going to get to the moon that way.
—— Astro Teller · [44:28]

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每个个体客户都有关于他们自己的场景、情况、现实和视角的重要事情要说，这对他们来说都有价值。但我们必须为广大的客户群构建产品。
Every individual customer has an important thing to say about their own scenario, their own situation, their own reality, their own perspective, and it’s all valuable for them. But we have to build a product for the customer base at large.
—— Jason · [01:06]

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每一项新技术出现时,你一开始都是拿你已经在做的事情,用新技术做得更多、更快,并强迫新技术去适应旧的做事方式。
With every new technology, you start by taking the thing you’re already doing and doing it more and faster with the new technology and forcing the new technology to fit the old way of doing it.
—— Benedict Evans · [15:41]

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你得想明白:当每四到六周排行榜榜首就出现另一个新模型时,可持续的竞争差异化路径到底是什么?
You’ve got to work out, well, what is the path to sustainable competitive differentiation when every four to six weeks there’s another model at the top of the leaderboard?
—— Benedict Evans · [49:34]

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人类建立过的每一个机构，每一个清单，每一个组织结构图，每一个档案柜，都是针对这个限制的假肢。
And every institution humanity has ever built, every checklist, every org chart, every filing cabinet is a prosthetic for that limit.
—— Garry Tan · [11:22]

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因为对于脓毒症来说，基本上每延迟治疗一小时，死亡率就会增加大约 12%。
Because with sepsis, basically every hour that you don’t treat somebody is about a 12% increase in mortality.
—— Fred Turner · [14:08]

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嗯，我认为这对我们来说是一个领先指标，过去六七个月我们的 Anthropic 成本每月增长 6 倍。
So, I mean, this is one of the, I think, the kind of leading indicators for us is that our Anthropic cost over the last six or seven months has 6X’d every month
—— Fred Turner · [50:02]

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我认为现在，当前这一代模型可以完成我们在 Curative 的所有后台任务。
I think today, the current gen models can do every back office task we have at Curative.
—— Fred Turner · [79:08]

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我们把每一次模型部署都视为「一人适配」。它只对你的工作负载是独特的。
We think about every single model deployment as one size fits one. It’s unique for your workload only.
—— Lin Qiao · [18:59]

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我真的看到，每一家公司都会把拥有自己的智能视为一种必需品。这不是可选项。
I really see people will own their, every single company will own their own intelligence as a must-have. It’s not optional.
—— Lin Qiao · [73:21]

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所以每一位 CIO 都需要回答:每多一个 token,我们该把它放在哪里?
So every CIO is going to need to answer, for every incremental token, where do we put it?
—— Matan Grinberg · [26:09]

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如果你真的能坐在每个客户旁边，说，这是我想给你看的，你会做什么？那是我的黄金标准。
If you could literally sit next to every single customer and go, here’s what I want to show you, what would you do? And that’s the gold standard for me.
—— 嘉宾 · [03:36]

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然后我意识到，每次你在设想未来或活在未来时，你只是在加速你在这里拥有的时间，你在加速走向死亡。
And then I realized every time you’re picturing the future or living in the future, you’re just accelerating your own time that you’ve got here and you’re accelerating towards death.
—— Kareem Amin · [07:15]

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我是说，这就是为什么我们现在有一场「SaaS 大末日」，因为它在质疑每一家软件公司的护城河。
It is, I mean, this is why we have a SaaSpocalypse now, is it’s kind of questioning every software company’s moat.
—— Jon Noronha · [25:15]

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LLM 就像一个从来没出过门、从未离开过自己出生的那个房间的人，但几个世纪以来每天读遍所有的书。
LLM is like someone who has never gone outside, never left the room they were born in. But read all the books every day for centuries and centuries.
—— Alex · [08:02]

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不，这不会让我恼火，因为我们每个周末银行里的钱都会多出几百万，对吧？
It doesn’t annoy me, no, because we end every week with millions more in the bank, right?
—— Osvald Nitski · [35:43]

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在 anthropic 之上构建已经相当危险了,因为每次一个应用类别开始做得很好时,他们就会进入那个类别。
it’s been already fairly dangerous to build on anthropic because every time an application category starts to do well, they move into that category.
—— Ben Horowitz · [14:35]

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我认为这对艺术来说将是一次小小的文艺复兴,因为每次我们拥有一项新技术,我们就会获得新种类的艺术。
I think it’s going to be a little bit of a renaissance for art in that like every time we have a new technology, we get new kinds of art.
—— Ben Horowitz · [28:48]

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每个问题的答案都是一个模型。你很想为它写一大堆代码？不。
The answer to every problem is a model. You’re tempted to write a bunch of code for it? No.
—— 嘉宾 · [00:00]

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对于那些不是在构建智能体产品、但在使用 Claude Code 的人:每六个月,删掉你的 Claude MD。
And for people that aren’t building agentic products, but you’re using Claude Code, every six months, delete your Claude MD.
—— Boris Cherny · [06:56]

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可控制性可能是我们在每个层面上对智能体需要的单一最大的突破。
Controllability is probably the single biggest breakthrough that we need for agents at every single level.
—— Jensen Huang · [23:20]

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因为我可以使用本地智能体一天产出 20 个 PR,但如果政策说每个 PR 都需要人工审查，那我的团队就得去审 20 个 PR。
Because I can churn out 20 PRs in a day using a local agent, but if we have a policy where every PR needs a human review on it, well then my team needs to go review 20 PRs.
—— Rob Willoughby · [11:06]

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你很容易作弊:一个自动化可能每分钟运行一次,每次「节省」十分钟,但这并不意味着它真的为你省下了天文数字的时间。
You can cheat very easily: an automation might run every minute and “save” ten minutes each time, but that doesn’t mean it saves you crazy amounts of time.
—— Carlos González de Villaumbrosia · [41:12]

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每家初创公司和现有巨头之间的战斗归结为初创公司是否在现有巨头获得创新之前获得了分发。
The battle between every startup and incumbent comes down to whether the startup gets the distribution before the incumbent gets the innovation.
—— Alex Rampell · [25:49]

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是的，我认为这是一个好问题，对开发者来说宽容的看法是，如果有一件事你真的不想搞乱，那就是预训练，因为它只是比你做的其他任何训练过程都要昂贵几个数量级。
Yeah, I think it’s a good question and the charitable take for developers is that if there’s one thing you really don’t want to mess with, it is pre-training because this is just orders of magnitude more expensive than every other training procedure that you do.
—— Adam Gleave · [74:22]

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所以突然间，你的产品路线图对每个单个客户来说完全是一堆雪花，这是行不通的。
So suddenly your product roadmap is a complete snowflakes for every single customer, which is not going to work.
—— Lindsey Scrase · [10:52]

指向原始笔记的链接

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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如果机器人要做我们今天与这些公司正在做的事情，那么每一栋建筑都需要是 3D 打印的或者是完全标准化的。
If robotics is going to do what we’re doing with these companies today, every single of those buildings need to be either 3D printed or completely standardized.
—— Melisa Tokmak · [11:45]

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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]

指向原始笔记的链接

然后对于每一个好公司,都有这种邪恶的双胞胎,那个海外的替身,复制了所有功能但不做合规。
And then for every one, there’s kind of this evil twin, you know, the doppelganger offshore that sort of copies all the features but doesn’t do the compliance.
—— 嘉宾 · [21:43]

指向原始笔记的链接

所以我们能做的是每一天，我们可以生成数万个假设。
So what we can do is every single day, we can be generating tens of thousands of hypotheses.
—— Joon Sung Park · [20:25]

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一个有趣的思想实验是,如果你试图使用可能每天有 20 个错误而不是每百万年一个错误的晶体管构建一个系统,会发生什么。
an interesting thought experiment is what would happen if you tried to build a system out of transistors that might have 20 errors per day rather than one every million years.
—— Jeff Dean · [38:29]

指向原始笔记的链接

这就是为什么每一个炒作周期都会产生一波绝对精彩的演示，却很少有真正的产品。
And that’s why every hype cycle produces a wave of absolutely spectacular demos and very few real products.
—— Dmitri Dolgov · [14:02]

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但我们能控制的是这场演出。如果规则由我们来定——比赛的规则、演出的规则——人们就可以每晚离开时都玩得非常开心。
But what we can control is the show. And if we build the rules, we make the rules of the game, we make the rules of the show, people can leave and have a great time every single night.
—— Jesse Cole · [10:21]

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现在，我想你可以称之为生产性偏执。我每天都有这种偏执：我们的节目必须再好一点点。
And now it’s, I guess you can call it productive paranoia. And I have that every day that our show has to get a little bit better.
—— Jesse Cole · [19:50]

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你教给智能体的每一个技能都是外在化的你。
Every skill you teach an agent is you, externalized.
—— Garry Tan · [29:38]

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如果你每周都能学到一件事，而有一个竞争对手每个月才学到一件事，那他们永远不会有影响力。
if you can learn one thing every week and there’s a competitor that’s learning a thing every month, they will never matter.
—— Max Hodak · [18:59]

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感觉上，公司就像在不断地缓慢死于一种金钱癌症，我们每隔几年靠融资把它打到缓解期，但它最终会回来，我想让这种感觉结束。
It feels like, I mean, the company is kind of constantly dying slowly of this money cancer that we can beat into remission every couple of years with the fundraising, but then it eventually comes back and I want that feeling to be over.
—— Max Hodak · [45:17]

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在游戏的每一刻，都有数百个推理调用正在发生，即使是一年前我们也无法构建任何这样的东西。
At every moment in the game, there are hundreds of inference calls happening, and we couldn’t have built anything like this even a year ago.
—— Kwindla Kramer · [19:25]

指向原始笔记的链接

把我们庞大的软件行业想象成前工业时代是很可笑的,但在某种程度上确实是,因为到目前为止我们拥有的唯一自动化就是启发式的,比如确保每行末尾有一个分号。
It’s funny to think about our giant software industry as being pre-industrial, but on some level it is, because until now the only automations that we had were heuristics, like make sure there’s a semicolon at the end of every line.
—— Idan Gazit · [02:57]

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我温和的观点，不是激进的观点，我的温和观点是每个招聘人员都应该是人才工程师。
my warm take, not a hot take, my warm take is every recruiter should be a talent engineer.
—— Adam Ward · [80:12]

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你雇佣的每一个你曾经一起工作过的优秀的人，都会让这个地方对你曾经一起工作过的人更有吸引力。
Every good person that you hire that you used to work with makes the place more attractive to the people that you used to work with.
—— Colin Zima · [47:01]

指向原始笔记的链接

如果你能每周学到一件事,而有一个竞争对手每月才学到一件事,他们就永远无关紧要了。
if you can learn one thing every week and there’s a competitor that’s learning a thing every month, they will never matter.
—— Max Hodak · [18:59]

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所以那个,你必须修复你环境中的每一个 CVE 到现在你将在你的环境中获得一千倍的更多 CVE。
you must fix every CVE that’s in your environment to now you’re going to get a thousand X more CVEs in your environment.
—— Emilio Escobar · [20:15]

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你每达成一天的计划，你就在摧毁股权价值。
Every single day that you are hitting your plan, you are destroying equity value.
—— Eric Vishria · [21:16]

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但我认为找到某种形式的持续学习——这里的终局不是让我们构建最好的法律模型，而是帮助每家律所或企业客户把它定制成他们所做工作的类型。
But I think figuring out some form of continual learning is I think the endgame here is not for us to build the best legal model. It’s for us to help every law firm or enterprise customer customize it to the type of work they’re doing.
—— Gabe Pereyra · [26:15]

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我认为任何把这些当作等待开始的借口的人，都将远远落后，因为一切都会变得更便宜，一切都会变得更有能力，每一年都是如此。
I think anyone who is using those as excuses to wait to get started are going to be super behind because everything’s going to get cheaper and everything’s going to get more capable every year.
—— Kevin Scott · [24:32]

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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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在理想世界里，我能在你的 UI 上做的每一件事，你的智能体也能通过一次工具调用做到。
In an ideal world, every single thing that I can do on your UI, your agent can do via a tool call as well.
—— Arjun Karanam · [09:34]

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主要是因为每增加一个复杂度维度都是乘性的，而不是加性的。
Largely because every added dimension of complexity is multiplicative instead of additive.
—— Connor Hegey · [40:03]

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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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技术迭代非常快，你必须对你已有的东西保持谦逊，并且要明白，如果技术跑得比你开发的还快，你就得扔掉手上的东西，重新做架构、重建，而且这种情况大概每几年就会发生一次，未来甚至更快。
Technology moves really fast, and you’ve got to be humble about what you have and know that if technology goes faster than what you’ve developed, you’ve got to throw away what you have and re-architect it, rebuild it, and it’s probably going to happen every couple years or even faster in the future.
—— Adam · [09:38]

指向原始笔记的链接

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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每个 Frontier 实验室大概每一个半月而不是每六个月发布一次模型。
Each Frontier lab is releasing models every month and a half or so instead of every six months.
—— Shensi Ding · [47:37]

指向原始笔记的链接

每次你启动一个新智能体，它就像你在这家公司的第一天。
Every time you spin a new agent up, it’s like you on day one at that company.
—— Dennis Pilarinos · [03:34]

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目前,市场在为每家公司的完美执行定价。
At the present, the market is pricing in perfect execution for every company.
—— Nikesh Arora · [52:03]

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我们似乎正在速通之前发生过的每一个技术周期。
We seem to be speedrunning every technology cycle that’s ever happened before this one.
—— Joel de la Garza · [00:51]

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那是一场灾难。字面上搞砸了产品中的每一个指标。
It was a disaster. Tanked literally every metric in the product.
—— Elliot · [25:26]

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我想大约每 25 分钟，世界各地就会发生大约相当于 9-11 规模的死亡。
I think every 25 minutes or so there is like a kind of 9-11 worth of deaths happening around the world.
—— Nick Bostrom · [35:01]

指向原始笔记的链接

你知道，每当我们让创建软件变得更容易时，我们就指数级地创造了更多的软件。
Every time that we’ve made it easier to create software, we’ve exponentially created more of it.
—— Addy Osmani · [75:53]

指向原始笔记的链接

我们不是每个问题都需要前沿级别的智能。
We don’t need frontier-level intelligence for every problem.
—— Chaitanya Asawa · [18:49]

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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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但在这个市场中，他们能够全力以赴，或者因为找不到更好的词，背负那些艰难的毛利率故事，然后找到一个买家，他不仅愿意看透这一点，而且实际上完全有能力解决它。
But in this market, they were able to go balls out, for lack of a better word, have those tough gross margin stories, and then find a buyer who not only was willing to look through it, but actually had every ability to solve it.
—— Jason Lemkin · [09:37]

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我觉得我们生活在一个这样的世界里：每个年轻人都能接触到一位超人类的软件工程师、数学家、医学专家、物理学专家——全都同时拥有。
I think we live in a world where every young person has access to a superhuman software engineer, mathematician, expert in medicine, physics, all at the same time.
—— 嘉宾 · [64:50]

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而我会说，你必须把你的初创公司当作这是你这辈子唯一能看到的一笔钱来对待，每一笔开支都是，包括你的时间，因为我常这么说，时间是我们最宝贵的资产。我买不到它，存不住它，也换不回来。
And I’m like, you have to treat your startup like this is the only money you’re ever gonna see in your life, and that every single expense, including your time, because and I say this time is our most valuable asset. I can’t buy it, I can’t store it, can’t replace it.
—— AJ Loiacono · [53:23]

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我是说在这种情况下，如果你像，我想详尽无遗地探索每一种蛋白质组合，我们可以直接把它变成一个金钱问题。
I’m saying in this case, if you’re like, I want to exhaustively explore every protein combination, we can just turn that into a money problem.
—— Martin Casado · [61:58]

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每一次模型迭代——我们称之为数据飞轮——理解模型的差距在哪里、如何贡献数据、训练它,这整个工程实践基本上由工程团队掌握,而他们并没有业务接触。
Every model iteration, which we call data flywheel, understanding where the model gaps are and how to contribute data, train it, the whole engineering practice is pretty much owned by the engineering team who actually do not have the business exposure.
—— Emily Hsu · [08:35]

指向原始笔记的链接

你得到的每一份数据都在某种程度上被人的解读、人的观点、偏见,以及他们自己的抱负等等所遮蔽。
Every bit of data you got was also sort of clouded with human interpretation, human opinions, biases, sort of like their own ambitions.
—— Cliff Obrecht · [35:29]

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而如果你真的必须思考你做的每一个决定，你哪里也去不了。
And if you had to really think about every decision you make, you’d get nowhere.
—— Jason · [12:24]

指向原始笔记的链接

每个供应商都增加了一跳,这种滞后导致我们基于过时的数据行动,这意味着我们在基于昨天的世界做自动化。
Every vendor added a hop, and this lag was causing us to act on stale data, and that meant we were automating on yesterday’s world.
—— Flora Liu · [04:51]

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因为九个月后我们终于发布企业版产品时，几乎每一家我去谈的公司都说：可你们从来没回复过我。然后我就出去买了 Microsoft Copilot。
Because when we finally did launch our enterprise product nine months later, almost every company I went out and talked to said, well, you never got back to me. And I went out and I brought Microsoft Copilot.
—— Aliisa Rosenthal · [05:20]

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顺便说一句，每一个骗局和骗局都始于催促你。
Every single scam and con starts with rushing you.
—— 嘉宾 · [71:45]

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我注意到的一点是，六个月前，甚至没有人跟我讨论过。但几个月前，我遇到的几乎每个人，公司的每位领导者都告诉我，要么他们害怕这种事发生在自己身上，要么这件事就发生在跟我说话的那个人身上。
Something that I noted is that six months ago, no one even discussed with me. But a few months ago, pretty much every person I meet, every leader in a company tells me either they are afraid of that happening to them or it personally happened to that person who was speaking with me.
—— Ofir Ehrlich · [17:01]

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而且我们不再处于 token 最大化（token maxing）的时代了。我们试图实际上为我们拥有的每一个 token 获取价值，因为它变得越来越贵。
And we’re not in the time of token maxing anymore. We’re trying to go to actually getting value for every token that we have, because it becomes more and more and more expensive.
—— Ofir Ehrlich · [27:18]

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智能体就像新员工。每当你开始一个新任务时，它们的知识都会重置。
Agents are like new employees. They reset their knowledge every time you start a new task.
—— Peter Werry · [01:54]

指向原始笔记的链接

你可以把一个智能体想象成一位专家级软件工程师，但每次都是第一次入职的新员工。
You can think of an agent like an expert software engineer who’s a new employee onboarding for the first time every time.
—— Peter Werry · [02:03]

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硅谷每三年就会忘记一件事，那就是普通美国人并不追求效率。
Silicon Valley forgets every three years that the average American is not trying to be efficient.
—— 嘉宾 · [72:14]

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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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但每个人都想聊我们顺带发布的那个小东西。每一个人,每一场讨论都是:哦,是的,挺酷的,所有这些复杂的东西真的很酷,但那个你把它叫做 architect 的小东西才是我真正想要的。我怎么才能搞到它?
But everybody wants to talk about that one little thing that we launched on the side. Every single person, every single discussion was like, oh, yeah, it’s cool, all of these complicated things, it’s really cool but that little thing that you’re calling the architect is really, really, really what I want. How can I get my hands on that?
—— Andrew Antos · [03:10]

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我们发布那个东西之后头六周里签下的头十二、十四笔交易,每一单的定价模式都完全不同,因为我们在通过那些对话不断迭代。
The first twelve or fourteen deals that we signed in the first six weeks after we launched that thing. Every single one had a completely different pricing model because we were iterating through it, through those conversations.
—— Andrew Antos · [03:58]

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你可以把这些护栏直接内置到钱包里，而你作为人类不必逐笔批准每一笔交易，因为那样根本无法扩展
You sort of build these guardrails into the wallet, and you don’t have to, as a human, approve every single transaction, because that would just not scale
—— Harshal Bhangale · [09:32]

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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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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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这就像有一个实习生时不时拍拍我的肩膀
It’s just like having an intern who taps me on the shoulder every now and then
—— 嘉宾 · [23:39]

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每一次合作都应该为我们产出几样东西。第一，对产品的反馈。第二，它需要创造出某种蓝图或打法手册，这样我们就不必再做那种类型的合作了。
Every engagement should produce a couple of things for us. One, feedback into product. Two, it needs to create some sort of blueprint or playbook, so we don’t have to do that type of engagement again.
—— Amandeep Khurana · [12:20]

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我要说，没有一个模型能在所有类别中都获胜。
And I’ll say that no one model wins every category.
—— Santi Garza · [17:23]

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随着时间推移，这实际上会让你花钱，因为每一轮都在喂入所有这些来自失败尝试和出错轮次的额外上下文。
That is actually going to cost you money over time because every turn is feeding all this extra context from failed attempts, turns gone wrong.
—— Santi Garza · [28:12]

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每次我都在透露游戏开发的一个小秘密：你去玩一款新游戏时，大多数时候你觉得在跟真人玩，但作为新玩家，你很可能是在跟机器人玩。
Every time I’m telling a little secret of the game development, you go to play a new game and most of the time you feel you are playing with another human, a people, but actually as a new gamer, high chance you are going to play with a bot.
—— Forrest Li · [31:43]

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如果你是一位正在听这个的创始人，你应该得到的教训是：每次你需要更多资本时，都必须有一些实打实的东西，理想情况下是你能摸得到的、可以展示你做出来的实物。
If you’re a founder listening to this, the learning that you should have is every time you need more capital, there needs to be something material, ideally something physical you can touch that you can show that you’ve made.
—— 嘉宾 · [05:50]

指向原始笔记的链接

看看现在正在发生的事，技术栈的每一部分都不止两个相关玩家，而是二十个。
If you look at what’s happening now, it’s like every part of the stack there’s not even two relevant players, there’s 20.
—— Anish Acharya · [04:10]

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理由很简单：对几乎每一个经济上有用的问题，我们已经跨过了智能阈值，超过那个阈值的任何东西都只是浪费。
Which is simply that we’ve crossed an intelligence threshold for almost every economically useful problem, and anything beyond that threshold is simply waste.
—— Anish Acharya · [25:49]

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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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我们应该尽量减少每天必须主动做出这些选择的人数，它应该自动为他们做正确的事。
We should try to minimize the number of people who have to actively make these choices every day, and just it should do the right thing for them.
—— Sharadh Krishnamurthy · [09:25]

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我们已经越过了人类会阅读每一行代码的时间点。
We’ve passed the point where humans will read every line of code.
—— JD · [39:57]

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我想说的每一点怀疑，都是确实让我夜不能寐的东西，但我认为有穿过黑暗森林的路，路的尽头有一份巨大的宝藏，只有一两条龙守着，所以必须冲一把。
Every bit of skepticism, I would say, is something that does keep me up at night, but I think there are paths through the dark forest and there’s a giant treasure with only one or two dragons at the end of it, so gotta go for it.
—— JD · [68:11]

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一个是我们会有泛化能力更好的系统，因为每当你增加一个搜索引擎、或向量数据库(它就是一种搜索引擎)、或某种步骤间的路由逻辑，这种人工整理就真的限制了系统做很多不同事情的能力。
One is we will have systems that can generalize better because every time you add a search engine or a vector database, which is a search engine, or some conditional logic to route between the steps, this human curation really limits the ability of that system to do a lot of different things.
—— Alexander Whedon · [30:24]

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我们想把算法范式的更替从每九年一次，缩短到每 12 个月一次。
We want to move from shifting the algorithmic paradigm every nine years to doing it every 12 months.
—— Alexander Whedon · [49:15]

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如果我们作为公司不能每六个月彻底重塑自己——最近感觉甚至比那更短——对我们优先事项、核心产品、用户感受进行非常重大的彻底重塑，我们就会输。
And if we as a company can’t completely reinvent ourselves every six months, which recently it’s felt even shorter than that, of complete very significant reinventions of our priorities, the core product, what users feel, we’re going to lose.
—— Roman Ugarte · [68:49]

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即使你的模型每天都在改进，别人也可以每天都在蒸馏它。这些循环可以以同样的节奏运转。
Even if your model is improving every day, people could be distilling it every day. So the loops could just operate at the same pace.
—— 嘉宾 · [19:57]

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看看现在正在发生的事：技术栈的每一层，都不止两个相关玩家，而是大约 20 个。
If you look at what’s happening now, it’s like every part of the stack, there’s not even two relevant players, there’s like 20.
—— Anish Acharya · [04:50]

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所以两年的路线图在三个月内完成。而我们最难的其实是往路线图里加什么——顺便说一句，这简直是每个 PM 的幻想。
So two years of roadmap happens in three months. And we’re actually, our hardest problem is knowing what to add to the roadmap, which by the way, is like every PM’s fantasy.
—— Anish Acharya · [10:12]

指向原始笔记的链接

你使用的每一个废话词，都会稀释那些重要的词。
Every filler word that you use dilutes the ones that matter.
—— 嘉宾 · [05:51]

指向原始笔记的链接

每个创始人都会至少经历一次非常惨痛的教训：时间会杀死交易。
Every founder will at least once experience the very painful lesson that time kills deals.
—— 嘉宾 · [10:27]

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我或我的公司所取得的每一项重大进步，都是演进而非革命性的。
Every significant advance I or my company’s ever made has been evolutionary rather than revolutionary.
—— 嘉宾 · [16:02]

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而且拥有那份信心去知道，无论你的文档说你的产品是什么，你都可以确信它实际上就是那个样子，因为本质上每隔几个小时我们就有智能体重新验证这一点。
And it’s really powerful to have the confidence to know that whatever your documentation says your product is, you can be sure that it actually is that because essentially every few hours we have agents revalidating that.
—— Charles · [51:00]

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你基本上是在向公司里的每个人传达：每个职位都是可以争取的，没有任何一个职位是他们只要足够努力、足够有才华就无法填补的。
You’re basically communicating to everyone in the company that every position is up for grabs, that there’s no position that if they work hard enough and if they’re talented enough, they won’t be able to fill.
—— 嘉宾 · [33:47]

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每一次都想着没有什么事是难到无法实现的，我想这也体现在我们的格言里，因为我们的格言是「不可能？也许吧」。
Every time thinking nothing is too hard to be achieved, which I think is also in our motto because our motto is impossible maybe.
—— Vali · [63:05]

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与其每张桌子上一台计算机， 我们能不能做到每张桌子上一个智能体？
instead of a computer on every desk, could we potentially have an agent on every desk?
—— Andrew Qu · [02:05]

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你要为你正在构建的那个智能体判断真实世界的影响，因为一个每次试图清理构建文件夹就崩溃的安全工具，是一个会被关掉的、什么也抓不到的工具。
for the agent that you’re building because a security tool that crashes every time it tries to clean a build folder is a tool that gets turned off and one that catches absolutely nothing.
—— Sarah Sanders · [18:36]

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很大比例——我想说可能高达约 50%——的 Shopify 的 pull request（每次改动生产系统时写的东西）现在不是由传统意义上做工程工作的工程师创建的，而是来自我们公司公共聊天里的对话。
It’s that a very large percentage, I want to say it’s probably up to about 50% of pull requests in Shopify, which again, pull requests every time you change the production system, you write a pull request, are created now not by engineers doing engineering work in the traditional sense, but out of conversations in our common company chat.
—— Tobi Lütke · [07:31]

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那就是每十年里两年半的时间，被我浪费在我不想做或者不该做的事情上。
That’s two and a half years out of every decade that I pissed away doing things I don’t want to do or shouldn’t be doing.
—— Jim VandeHei · [10:50]

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你掌控的每一个小时，如果你在做你不需要做的事、不想做的事，你就是在挥霍一种非常、非常宝贵且有限的资源。
So every hour of the time that you control, if you’re doing something you don’t need to be doing, don’t want to do, you’re just frittering away what is a very, very precious and finite resource.
—— Jim VandeHei · [15:15]

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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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早期,我们的延迟从两秒漂移到了大约两秒半,而那半秒钟几乎让产品里的所有指标都崩了。
Early on, our latency drifted from two seconds to about two and a half seconds, and that half second tanked basically every metric in the product.
—— Paula Dozsa · [03:39]

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延迟不只是你最后检查的一个数字,它实际上就是产品,我们把管线的每个阶段分开来测量,因为「感觉慢」是没有用的。
Latency isn’t just a number you check at the end, it’s actually the product, and we measure every stage of the pipeline separately because it feels slow is useless.
—— Paula Dozsa · [04:54]

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这话很难说出口：这么多销售每天都在用它，但我们毫无定价权，因为数据不是我们的。
That’s tough to say that we had all of these AEs using it every day, but we had no pricing power because it wasn’t our data.
—— Keith Parris · [07:53]

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我们的态度是，数据是你的，你想怎么用都行，我们会努力工作，每天都去赢得你生产力的那份权利。
I think our take is, you know, it’s your day to do what you want, and we’re going to work hard to earn the right to your productivity every day.
—— Keith Parris · [30:40]

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他们真的每次都是刚醒来，而且每次你开启一个新会话，他们就像上班第一天的应届新员工。
They really start to wake up, and every time you start your session, they’re like a new hire on their first day on the job.
—— Edo Liberty · [04:36]

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连 OpenAI 也不再发布针对工具的最佳实践了，因为他们说，每次发布最佳实践，模型就会变得更好，这些实践就过时了。
Even OpenAI, they don’t publish best practices for tools anymore because they say that every time they publish best practices, the models become better and these practices become obsolete.
—— Liad Yosef · [14:26]

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所以每年你都能看到它们能完成的任务有大约 10 倍的增长,衡量标准就是一个人类数学家做这些任务需要多长时间。
And so every year you’re seeing this like 10x increase in the task they’re able to do in terms of like length of how long it would take a human mathematician to do it.
—— Noam Brown · [25:11]

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但每次你基于对思维链的观察进行干预,你都在隐式地施加一点压力,让模型之后隐藏它的思维链。
But every time you intervene based on your observations of the chain of thought, you are implicitly applying a tiny bit of pressure for the model to then hide its chain of thought.
—— Noam Brown · [70:17]

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如果你要列一个从不害怕的勇敢领导者名单，别把我列进去。我每天都在害怕。
If you’re going to make a list of brave leaders who are never afraid, don’t put me on the list. I’m afraid every day.
—— Brené Brown · [04:43]

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这相当于在美国每年终结一场乌克兰战争的死亡规模。
That’s like ending a Ukraine war every year in the United States.
—— Brad Gerstner · [00:36]

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事实证明，每年心脏病发作的人中有一半的胆固醇处于正常区间。
It turns out that half of the people who have heart attacks every year have cholesterol in the normal zone.
—— Brad Gerstner · [21:24]

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我觉得大概每六个月就降为十分之一，诸如此类。
I think it’s going down by one-tenth every six months or something like that.
—— Martine Cassado · [42:08]

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所以如果每个月有五亿人在使用这些产品还叫坟墓，那行，我们就这么叫它。
So if half a billion people using these products every month is a graveyard, then sure, let’s call it that.
—— Luca Ferrari · [08:08]

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我觉得紧迫感和行动偏好与长期思考的结合，这就是我的三对矛盾修辞，每一只优秀 PM 身体里的三对狼。
I think that combination of urgency and bias for action with long-term thinking, those are my three oxymorons, the three pairs of wolves inside every great PM.
—— Peter Sellis · [79:57]

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他说，我低估了山姆的一点是，他身上有一种压倒一切的东西，促使他每天进步。
He says, the thing that I underestimated about Sam is that he has an overriding something in him that causes him to improve every day.
—— 嘉宾 · [29:09]

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你可以读遍所有关于如何打橄榄球的书，但如果你进入一场 NFL 比赛并且你在打四分卫，书里没有任何东西能教会你如何应对一个 300 磅的怪物朝你冲过来，而你还正在试图搞清楚该把球传给谁。
You know, you can read every book ever written on how to play football, but like if you get into an NFL game and you’re playing quarterback, like nothing in a book is going to teach you to deal with like somebody, some 300 pound monster rushing at you while you’re trying to like figure out who to throw the ball to.
—— Ben Horowitz · [35:47]

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如果你在你的软件工厂里交付了坏代码，它会降低未来每一件经过那个工厂的工作的质量，因为模型会看到更多坏模式。
if you ship bad code in your software factory, it degrades every future piece of work that goes through that factory because there’s more bad patterns for the model to see.
—— Dex Horthy · [38:30]

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我们有一个客户拥有 2200 万台设备，它们全都在发出读数，每几秒一次、每秒一次，有些甚至是亚秒级的。
We have one customer that has 22 million devices and they’re all emitting readings every few seconds, every second, in some even sub-second as well.
—— Brandon Purcell · [05:34]

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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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用大模型来调度一支更小模型的舰队，我认为这是我们相当坚定信奉的范式，它已经被证明是编码系统的运作方式，而且我认为在未来一年它会进入几乎每一个智能体。
Over a fleet of smaller models is I think a paradigm that we believe in quite firmly and it’s already proving out to be how coding systems will work and I think it’ll find its way into almost every agent over the coming year.
—— Hamad Bashir · [24:29]

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每一个投入生产的视频生成模型,在底层都用了一条复杂的提示词补全流水线。
every single video generation model in production uses a complex prompt completion pipeline under the hood.
—— Anastasis · [22:39]

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这个范式令人兴奋的地方在于,大部分算力是在所有产品表面之间共享的,所以你不必为每个产品表面从头训练单独的模型。
The exciting thing about this paradigm is most of the compute is shared across all of the product surfaces, so you don’t have to train individual models from scratch for every product surface.
—— Devansh Tandon · [09:24]

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但有一个大问题摆在这里，基本上就是我每天睡前都在想的事情：基准测试、评估、智能体、以及你怎么配置它们，全都是协变的。
But one big problem presents itself, which is basically the thing that I go to bed thinking about every day, which is benchmarks, evaluations, the agents, and how you configure them are all covariant.
—— Zubin Aysola · [01:32]

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所以从根本上说，生产环境的每一次失误、也包括每一次亮眼表现——因为我认为朝正向爬坡也很有用——都会变成我们智能体框架的一个任务。
So fundamentally, every production miss or every production goodness as well, because I think it’s useful to hill climb in a positive direction, becomes a task for our agent framework.
—— Zubin Aysola · [12:21]

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所以如果我们把这个推向极端，那就是：为什么不把每一种数据——编程、计算机使用、自我中心视角——都喂给同一个模型？我认为这就是我们如何得到最强机器人使用智能体的路径。
So if we take this to the extreme, it’s like, why not feed every kind of data, coding, computer use, egocentric, into the same model? I think that’s how we get to the most capable robot use agent.
—— Ham · [25:00]

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你不可能以我们的节奏前进，还让你想做的每个决定都要 300 个人参与意见。
You can’t move at our pace and get, you know, 300 people to weigh in on every decision that you want to make.
—— Maggie Landers · [31:50]

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这位员工比你聪明十倍，而我要你把你所知道的每一件事都倾倒给这位员工，然后他们将在六个月内抢走你的工作。
This employee is 10 times smarter than you. And I want you to pour every single thing that you know into this employee and then they’re going to take your job in six months.
—— Molly Graham · [26:42]

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而是，「如果你相信你的工作将永远存在，只是每六年就会变得完全不同，你会怎么做？」
It was, “What would you do if you believed your job was always going to exist? It was just going to look completely different every six years.”
—— Molly Graham · [28:28]

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所以我们不需要一个人在整个生命周期的每一步都在牧羊式地引导这个智能体。
So we don’t need a human to be shepherding this agent through every single step of the life cycle.
—— Ryan Cooke · [08:00]

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每次会话,模型都像《初恋 50 次》里的德鲁·巴里摩尔一样醒来——才华横溢,却没有昨天的记忆。
Every session, the model wakes up like Drew Barrymore in 50 First Dates, brilliant and no memory of yesterday.
—— Andrew Orobator · [17:34]

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而且我预测，每家公司、每个开源项目，核心处都会有一个软件工厂，就像 CI/CD 变成「哦，你当然得有那个」一样。
And I predict that every company, every open source project, will have at its core a software factory, kind of like the way that CICD became just like, oh, of course you have that.
—— Zach Lloyd · [08:43]

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我感觉可靠性的每一个九都会对所有人极其有价值,即使从市值角度看它不是最有价值的东西,因为它会直接启用新的应用。
I feel like every nine of reliability is going to be so valuable for everyone, even if it’s not the most valuable thing market cap wise, because it will just enable new applications.
—— Diogo Almeida · [26:11]

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到 42 岁，他的产品被当前活着的人口中每 2.3 人中的一人使用。
By 42, his products are used by one out of every 2.3 people currently breathing.
—— 嘉宾 · [17:46]

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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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我的意思是，从软件工程这方面来说，我们今天完全可以停下来，去复现每一个现有的诺贝尔奖，至少物理学的。
I mean, I think from the software engineering side, we could literally stop today and find every existing Nobel Prize, at least from the physicals.
—— Doj Chubuk · [51:40]

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而且我认识的每个工程师都有点精疲力尽，因为你同时在打两份工。
And every engineer I know is like kind of exhausted because you’re doing two jobs at once.
—— Thariq Shihipar · [74:06]

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从对世界的经济影响来看,我认为每个工程师速度提升 2 到 4 倍对人类社会来说都将是变革性的。
I mean, if you think about it, like in terms of like economic impact in the world, I think every engineer going 2 to 4x faster would be transformational to human society.
—— Dex Horthy · [22:01]

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到那个时候,我是在做你工作中每一个重要的部分。
And at that point, I’m doing every part of your job that matters.
—— Dex Horthy · [32:03]

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如果你每一千行就检查一次,交付一万行代码会容易得多。
Because like, it’s a lot easier to ship 10,000 lines of code if you check it every thousand lines.
—— Dex Horthy · [39:31]

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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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这背后有多种原因，但确实值得一提：每多一行代码，就多一个潜在的 bug、一个潜在的漏洞。
So there’s multiple reasons for this, but it really bears mentioning that every extra line of code is a potential bug, a potential vulnerability.
—— Justin Reock · [08:00]

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而一个每个智能体都是远程的多智能体系统，基本上就是一个微服务的分布式系统，只不过每个微服务都是非确定性的。
And multi-agent system where every agent is remote is basically a distributed system of microservices where each microservice is non-deterministic.
—— Vlad Luzin · [07:51]

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在我们所生活的这个世界里，媒体的其他方方面面几乎都被新式的、几乎算是寡头的人所控制，拥有这样的存在并且知道它存在，是非常有力量的。
And in a world that we live in where literally every other aspect of media is controlled by the new kind of almost oligarchs of the world, it’s powerful to have that and to know it exists.
—— Jennifer Ferro · [20:32]

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每天都在变得更好，但他们现在极其高效，比没有他们的实验室高效一百倍。
It’s getting better every day, but they’re incredibly productive right now, like a hundred times more productive than a lab without them.
—— Annie Lamont · [11:55]

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我想让每一个 Ring 用户都感觉,自己有一个在他们家干了 30 年的安保团队。
I want every ring neighbor to feel like they have a security team that has worked at their house for like 30 years.
—— Jamie Siminoff · [34:16]

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我相信,世界上每家公司的 CEO 都会梦想拥有这样的能力——基于某个决定改变他们单位和员工的优先级,而这个决定第二天早上或一小时内就开始生效。
I believe that every CEO of every company in the world will be dreaming about having such possibility to change the priorities of their units and their employees based on this decision that start to work tomorrow morning or within one hour.
—— Andrii Hrytseniuk · [24:23]

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那里的每一个字节、每一个字符都经过了 40 年的优化，只传达最重要的信息。
Every byte, every character there is optimized over 40 years to convey only the most important information.
—— Jan Čurn · [08:55]

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而连续性正是每家大厂都在试图打包起来再卖回给你的东西。
And continuity is exactly what every major lab is trying to package up and sell back to you.
—— Dylan Couzon · [04:46]

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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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所以现在 Traversal 是 American Express 每一起被创建的事故的第一响应者。
And so now Traversal is the first responder to every single incident that’s created at American Express.
—— Eric Schwartz · [13:38]

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通常，按我们带立场的观点来说，代码覆盖率对世界上除 Meticulous 之外的每一个工具来说都是一个糟糕的指标。
Typically, I would say that code coverage in our opinionated view is a terrible metric for every tool in the world apart from meticulous.
—— Gabriel Spencer-Harper · [09:26]

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但在 Meticulous,这两者实际上近似相等，因为我们做了一件非常不寻常、非常激进的事：我们在整个流程中每一个可能的时刻都截取一张截图。
But with meticulous, it actually is approximately the same because we do this really unusual and radical thing, which is we’re taking a screenshot at every possible moment throughout a flow.
—— Gabriel Spencer-Harper · [09:48]

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这个智能体根本不可能改进。就像是每次我试图做出改进，结果大约一周后我就不再看它的输出了。
And it’s just like impossible to improve this agent. Like it’s like every time I try to make an improvement, I end up like ignoring its output about a week later.
—— Alex Atallah · [21:26]

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如果你的智能体无法直接使用你的应用、你的产品来获得「一切是否正常」的反馈循环，那么这是一项非常值得的投资，每次你做 UI 工作时都会有回报。
If your agent cannot use your application, your product directly to get this feedback loop of is it all working, then that’s a really big investment that pays off every time you work on UI.
—— Harald Kirschner · [08:48]

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而且或许比这里任何其他事情都更重要的是，每天都有智能体发现新的漏洞。
And maybe more important than anything else here, there are new vulnerabilities being uncovered by agents every single day.
—— Dan Adler · [03:43]

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你用过的每一个仪表盘，每一种被写出来的奇怪、冷门的查询语言，都是你和你数据之间的翻译装置，因为另一端的机器无法理解你真正想要什么。
Every dashboard you’ve ever used, every weird, obscure query language ever written was a translation device between you and your data because the machines on the other end cannot understand what you actually wanted.
—— Sarah Simionescu · [02:15]

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每次对话都是从零开始。它不记得昨天在 Slack 里把链接格式搞砸的事，所以今天它只会再搞砸一次。
Every conversation starts from zero. It has no memory of how it fumbled formatting links properly in Slack yesterday, and so it’s just going to fumble again today.
—— Sarah Simionescu · [03:53]

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所以 MCP 给了智能体一扇通往每个应用的门，却让它们站在成千上万个彼此隔绝的房间里，没有地图，也没有曾到过那里的记忆。
And so MCP gave agents a door into every app, but it left them standing in thousands of separate rooms with no map and no memory of ever being there.
—— Sarah Simionescu · [04:45]

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我们把你每天生活在其中的所有那些杂乱、文档稀疏、不断变化的 API,翻译成智能体真正爱用的东西。
We translate messy, sparsely documented, ever-changing APIs from all the apps that you live in every day into something that agents really love to use.
—— Sarah Simionescu · [06:56]

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我问他们打算用什么标准来评估这家公司,我的一般建议也许是错的,但我的观点是,和创始人的关系可能比清单上其他所有东西重要十倍。
And I ask them like what your priorities are for like how you’re going to evaluate the company, my general advice maybe is wrong, but my advice, my opinion is the relationship with the founder is maybe 10 times more important than every else, everything else on the list.
—— Juven · [30:27]

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字面意义上，全世界每天有一场 N8N 社区活动。
There’s literally one NNN community event worldwide every day.
—— Jan Oberhauser · [05:57]

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我甚至仍然亲自合并每一个 PR。
I literally still merged every PR.
—— Jan Oberhauser · [55:17]

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如果你是 CEO，每一个问题都是你的问题，这意味着你每天醒来心都像要跳出胸口，因为总有什么东西不灵了。
every single problem is your problem if you’re a CEO, which means you’re always waking up with that heart, like beating out of your chest because inevitably something’s not working.
—— Pablo Srugo · [15:33]

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我感觉每个周期里，先出现创新者，然后出现模仿者，最后出现蠢货。
I feel like in every cycle, you get the innovators, then you get the imitators, and then you eventually get the idiots.
—— Venky Ganesan · [15:28]

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你要成为的是不可阻挡的人，你什么都会做，从报税到谈判保密协议，从注册 LLC 到做工资单。
What you want to be is unstoppable, that you can do every single thing, from your taxes to negotiating a non-disclosure agreement, from starting an LLC, doing your payroll.
—— Jason · [17:48]

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它来自前沿实验室，他们已经发现，每当他们发布一个版本，说他们的产品强大得不可思议、能入侵系统等等，他们的使用量就会上升。
It’s coming from the frontier labs who have learned that every time they put a release out, that their products are incredibly powerful and can hack a system, et cetera. Their usage goes up.
—— Jason · [34:40]

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你说根据调查，大约每解决一小时就要付出三小时的协调。
And, and you say that there’s roughly from the survey, three hours of coordination for every hour of resolution.
—— Craig · [25:24]

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所以我们认为工厂的每一个组件不可能都由单一公司做到业界最佳。
So we don’t think every component of a factory is going to be best in class with a single company.
—— Dru Knox · [16:13]

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一旦你在乎性能，它就是有状态的，而这几乎是所有情况。
It’s stateful once you do care about performance, which is pretty much every case.
—— Charles Frye · [20:03]

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你必须每六个月把那硬件生成 token 的能力翻一倍。而其中来自软件的部分会和来自硬件的部分一样多，甚至更多。
You have to double the capability of that hardware to generate tokens every six months. And as much or more of that is going to come from software as it is from hardware.
—— Amin Vahdat · [13:33]

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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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如果你真的认为这东西会杀死你，你不必用自杀来证明——我们是在拿着一颗星球玩俄罗斯轮盘赌，而每一枪没打死我们，都可能让我们变得更强。
If you really think that this thing is going to kill you, you don’t have to suicide in order to demonstrate that we are pulling trigger on this Russian roulette with a planet, and every shot that doesn’t kill us will make us stronger, potentially.
—— Jaan Tallinn · [00:45]

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我是说，每个吹哨人都应该，如果他们想做一件好事，就应该试着高效地做成这件好事。
I mean, every whistleblower should, if they’re trying to do a good thing, they should try to do this good thing efficiently.
—— Jaan Tallinn · [21:12]

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所以我们正在扣动扳机，就像用整个星球玩俄罗斯轮盘赌。而且每一次没杀死我们的射击都可能让我们更强、更富有、境况更好。但你什么时候才停止扣扳机，对吧？
So we are pulling a trigger on this like Russian roulette with a planet. And every shot that doesn’t kill us will make us stronger potentially and wealthier and better off. But when do you stop pulling the trigger, right?
—— Jaan Tallinn · [29:31]

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每个月都有故事说某个智能体删了点东西，导致别人丢了生产数据库。
Every month there’s a story where someone lost their production database because the agent deleted something.
—— Andy Pavlo · [00:03]

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而在一年之内，几乎每一个数据库厂商都有了他们自己的向量索引。现在这已经变成了某种意义上的标准入场筹码。
And within a year, pretty much every single database vendor had their own vector index. And now it’s become sort of standard table stakes.
—— Andy Pavlo · [03:35]

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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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每当有人建议我们应该增加复杂性，无论是流程中的一个步骤、一个功能、一个团队、一个团队的人头数，随便什么，系统的任何元素，举证责任都在提出建议的人身上。
Every time someone recommends that we should add complexity, whether it’s a step in a process, a feature, a team, headcount to a team, you name it, any element of the system, the burden of proof is on those making that recommendation.
—— Luca Ferrari · [54:28]

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但我们心中始终坚守的一个关键原则是：每一条落到上下文图谱上的数据点，都必须扎根于一个硬事实。
But one key principle that we had in mind always was every single data point that landed on the context graph always had to be grounded down in a hard truth.
—— Kamalakannan Nandagopal · [05:34]

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认知开销是每个工程师在做出有意义的改动之前都必须支付的一笔税。
Cognitive overhead is a tax every engineer has to pay before they can make a meaningful change.
—— Gabriel Martinez · [13:23]

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每个伟大的创业者身上都有某种糟糕透顶的缺陷，但这没关系。
Every great entrepreneur has got something like horribly wrong with them, but that’s okay.
—— Ben Horowitz · [00:34]

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每一个伟大的创业者身上都有一些糟糕透顶的问题，但这没关系。
Every great entrepreneur has got something like horribly wrong with them, but that’s okay.
—— Ben Horowitz · [22:39]

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我的论点是：每家公司都需要开始像 Labs 团队一样思考和运作。
My thesis is that every company needs to start thinking and operating like a Labs team.
—— Lenny · [00:00]

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更多是：如果你真的是在和另一个人交谈，你会怎么处理这件事？而我认为这在我们不得不做的几乎每一个决定上，都起到了极大的澄清作用。
It was more like, how would you handle this if you were actually speaking with another person? And that was immensely clarifying, I think, in almost every decision that we had to make.
—— Alex Cornell · [05:00]

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而且说实话，每次我大喊大叫时，这对智能体和在现实生活中都一样。通常是我自己的问题，不是它们的问题。
And to be honest, every time I’m yelling, it is true to agents as it is in life. It’s usually a me problem. It’s not a them problem.
—— Claire Vo · [36:17]

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我们的 做法 基本上成为了市面上所有其他聊天机器人的蓝图。
We did it in a way that essentially became the blueprint for every other chatbot out there.
—— Arvind Srinivas · [00:13]

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每一项伟大的发明都是关于提出一个问题。
Every great invention is about asking one question.
—— Arvind Srinivas · [06:26]

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当每个人都想要个人智能体，或者每个企业都想要自己的、全天候 24-7 持续在线并运行大量自动化的个人智能体时，上下文窗口比内存中的模型权重更重要。
When everybody wants personal agents or every business wants its own personal agents that’s always on and working 24-7 and running a lot of automations, the context window matters even more than the model weights in the memory.
—— Arvind Srinivas · [30:26]

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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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人们每天都在蒸馏我的产品。他们拿走它，把它拆解成原始部件，这就叫竞争。
People distill my products every single day. They take it, they strip it down to its raw parts, and that’s called competition.
—— 嘉宾 · [00:21]

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所以，不是以一个人的身份去做合伙，几乎就像我在与我见过的每一个技术创始人合伙。
So there was, instead of partnering as one person, it’s almost like I’m partnering with every technical founder I’ve ever met.
—— 嘉宾 · [22:53]

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从来没有哪个时期能像现在这样，每周都有这么多新可能的东西。
There’s never been a time where there’s more newly possible stuff every week.
—— 嘉宾 · [47:52]

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我想我的最大区别在于它实际上是在你的电脑上运行的。我目前看到的所有东西都在云端运行。它可以做几件事。如果你在电脑上运行它，它可以做每一件该死的事情。
I think my big difference is that it actually runs on your computer. Everything I saw so far runs in the cloud. It can do a few things. If you run it on your computer, it can do every effing thing.
—— Peter Steinberger · 来自原文

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