ChatGPT – The Super Assistant Era | BG2 Guest Interview

频道: BG2Pod with Brad Gerstner and Bill Gurley
视频: https://podcasters.spotify.com/pod/show/bg2pod/episodes/ChatGPT--The-Super-Assistant-Era--BG2-Guest-Interview-e3gf7om
原文语言: en
统计: 共 81 轮 · Nick Turley 75 · Apoorv Agrawal 6

[0:00] Nick Turley

ChatGPT originally was entirely free, and the reason for that was that it was intended to be a demo,and we were going to wind it down after a month.We then realized that the demo went viral, and people loved the demo, and it was actually a product.But we realized that to be a product, you can't take the product down every time you're at capacity.So we shipped subscriptions simply because it could shape the demand.It was a way of gracefully turning users away, and we had to turn away someone.You guys are at 900 million weekly active users now, and that growth has been incredible.The next billion users, where are they going to come from?

Nick： ChatGPT 最早是完全免费的，原因是它本来只打算做个 demo（演示），我们准备上线一个月之后就把它关掉。后来我们发现这个 demo 病毒式传开了，大家很喜欢它——它其实是个产品。但我们意识到，要成为一个产品，你就不能每次容量满了就把产品下线。所以我们上线订阅制，纯粹是因为它能塑造需求（shape the demand）——这是一种体面地把用户挡在门外的方式，而当时我们确实必须挡掉一些人。

Apoorv： 你们现在有 9 亿周活跃用户（WAU，weekly active users），这个增长实在惊人。下一个十亿用户会从哪里来？

[0:35] Nick Turley

We've got about 10% of the world coming to us now, 90% left to go, right?There's so much more opportunity.Well, Nick, so excited to have you here.Thank you for having me, Aparav.You've had quite the journey from Germany to the U.S. from Brown.That's true.More recently at Instacart, delivering groceries in 30 minutes to now delivering AGI to billions.I'm sure that was a plan all along.Yeah, clearly total master plan.Well, tell us about your journey.How did you get to OpenAI?

Nick： 现在全世界大概有 10% 的人会来用我们，还剩 90% 没覆盖，对吧？机会还大得很。

Apoorv： Nick，特别高兴请到你。

Nick： 谢谢你邀请我，Apoorv。

Apoorv： 你这一路挺精彩的——从德国到美国，从布朗大学（Brown）……

Nick： 确实。

Apoorv： ……后来在 Instacart 做「30 分钟送到家的生鲜」，现在是给几十亿人递送 AGI（通用人工智能）。我相信这一切都是你早就计划好的。

Nick： 是啊，显然是个天衣无缝的大师计划。

Apoorv： 说说你的经历吧，你是怎么进 OpenAI 的？

[1:11] Nick Turley

I know it's a fun story.And you're three and a half years or so at OpenAI.How have they gone?The only thrill ride in how many sort of employment decisions has been entirely people-based.So I don't claim any credit for joining OpenAI.We're predicting ChatGPT or anything like it.But I hit up someone who I admire a lot, who I got to know at Dropbox.I got to know at the time, Joanne, who worked here at the time.And I asked her to get off the Dolly 2 waitlist.And she told me I had to interview if I wanted to get off the waitlist.So I took the bait and got totally nerd sniped in the process.And here I am.There you go.The Dolly 2 waitlist will get you.Great recruiting tool.Nice.Nice.We should do more waitlists, probably.Yeah.Yeah, yeah.Well, you know, the big super cycle we're in is ChatGPT.Now, I assume over a billion users on the monthly side, 900 million weekly active users recently reported,up from zero, three and a half years ago.You could have, if I imagine what the dashboard of Nick Turley looks like,it could have users, it could have paying subscribers, it could have daily active users,it could have retention, engagement.I mean, there's like 15 things, maybe all of them.What is your North Star?

Apoorv： 我知道这故事挺好玩的。你在 OpenAI 三年半左右了，这三年半过得怎么样？

Nick： 这一路是趟惊险刺激的旅程，而我历次的就业决定，说到底全都是因为「人」。所以加入 OpenAI 这件事我一点功劳都不敢领——我们当时并没有预测到 ChatGPT 或者任何类似的东西。但我当时联系了一个我非常敬佩的人，是我在 Dropbox 认识的 Joanne，她那时候在 OpenAI。我找她，想让我从 DALL·E 2 的等待名单里放出来。结果她跟我说：你要想从等待名单里出来，就得来面试。于是我上钩了，整个过程被彻底「书呆子狙击」（nerd sniped，被一个有趣的技术难题勾住、彻底陷进去出不来）了，然后我就在这儿了。

Apoorv： 就是这样。DALL·E 2 的等待名单能把你搞定，真是绝佳的招聘工具。

Nick： 我们大概应该多搞点等待名单。

Apoorv： 我们正处在的这个大超级周期就是 ChatGPT。现在我估计月活超过 10 亿，最近公布的周活是 9 亿，而三年半前是零。如果让我想象 Nick Turley 的仪表盘长什么样，上面可能有用户数、付费订阅数、日活、留存、参与度……大概有 15 个指标，也许全都有。你的北极星指标（North Star）是什么？

[2:30] Nick Turley

How do you, what are you optimizing for?What is Nick looking at in his daily dashboard?It's funny, right?Because it's such a young product.It's been, to your point, three and a half years.And this kind of question, it kind of changes as you evolve and you grow up and you ask yourself,you know, what are we really building here?

Apoorv： 你在为什么优化？Nick 每天盯着的仪表盘里到底是什么？

Nick： 这问题挺有意思的，因为这产品还很年轻——像你说的，才三年半。而这类问题会随着你自己的成长而变化，你会不断问自己：我们到底在造什么东西？

[2:53] Nick Turley

And to this day, right, I want to build a super assistant that can actually help people achieve their goals.And ultimately, the thing we care about is like, is our product doing that?Is it actually helping you do the thing that you're, you know, coming to the product to do?

直到今天，我想造的是一个超级助理（super assistant），它能真正帮人达成自己的目标。归根到底我们在意的是：我们的产品有没有在做这件事？它有没有真的帮你完成你打开它时想做的那件事？

[3:07] Nick Turley

And it's so different for different people, right?Some people are trying to get healthy.Other people are trying to start a company, learn a new topic, do their taxes.There's all the different things that you might be doing.And the true measure of success is whether or not we're helping you do that.And obviously, we look at WAU in particular because, you know, we want to know if you're coming back to the product.We look at retention.But we, you know, we look at all kinds of stuff in aggregate because really there isn't like this one single thing that you can optimize for.If you were to allocate 100 units of points to these metrics, which metric, can you distribute the 100 units across these metrics in order of importance for you right this second?

Nick： 而这对不同的人差别巨大。有人想变健康，有人想创业、学一个新领域、报税——你可能在做的事千差万别。真正衡量成功的标准，是我们有没有帮你把那件事做成。当然我们也特别看 WAU（周活跃用户），因为我们想知道你会不会再回来用；我们也看留存（retention，用户隔天/隔月还回不回来用）。但我们会看一大堆汇总指标，因为真的不存在某个单一指标可以拿来优化。

Apoorv： 如果让你把 100 分分配到这些指标上，你会怎么按重要性把这 100 分派下去？就此时此刻。

[3:49] Nick Turley

It's a good question.I care a lot about long-term retention.And I would put all my points there because I'm really proud of the retention stats we have.Huge.But ultimately, the sign of durable values, whether or not people are coming back in three months because that means you're really solving their problems.And I think things like revenue, they follow from that versus, you know, trying to go on those things directly.And we've had a lot of success making very principled decisions on this stuff.Like one good example is GPT-4 used to be behind a paywall because we couldn't serve it to everyone.And then we had GPT-4, which was a total breakthrough in our ability to inference it.And so we just gave it away for free.And that ended up being totally revenue positive and retention positive because it just provided access to the tech.And I think when you make your decisions that way and you focus on the customer, you end up with a great product and revenue obviously falls too.Phenomenal.Yeah.Well, it shows up in the numbers.You know, I posted this chart yesterday on the data that we have, you know, from a third party.The retention curves for ChadGPT are smiling.Look at that, just like that.

Nick： 好问题。我非常在意长期留存，我会把所有的分数都押在那儿，因为我们的留存数据我真的很自豪。归根到底，「有没有持久价值」的标志，是人们三个月后还回不回来——因为那意味着你真的解决了他们的问题。而像收入这样的东西，是从留存里长出来的，而不是你直接去追它。我们在这件事上做过很多很有原则的决定，收获很大。一个很好的例子是：GPT-4 曾经放在付费墙后面，因为我们没法给所有人提供服务；后来我们有了 GPT-4o，那是我们推理（inference，模型对外提供服务时的算力开销）能力上的一次彻底突破，于是我们干脆免费送了出去。结果那件事在收入和留存上都是正向的，因为它就是让大家能用上这项技术。我觉得当你这样做决策、聚焦在用户身上时，你最后会得到一个很棒的产品，收入自然也会跟上。

Apoorv： 太漂亮了。而且这确实反映在数据上。我昨天发了一张图，用的是我们拿到的第三方数据——ChatGPT 的留存曲线是「微笑曲线」（smile curve，留存不但不衰减、后期还往上翘）。你看，就是这样。

[4:55] Apoorv Agrawal

And that is a rare, that is a very rare occurrence, you know, as we know.And why do you think, like if you were to give us a narrative on that smile curve, what is the, why do these smile curves exist?

这非常罕见，我们都知道这有多罕见。如果让你给这条微笑曲线一个叙事，你觉得这种微笑曲线为什么会存在？

[5:08] Nick Turley

What are you seeing in ChadGPT that has people who have maybe turned off for a couple of weeks or months coming back?And why are they coming back?Look, there isn't one single thing.You know, the way that you build a retentive product is lots and lots of little things and really trying to make it better systematically.I will say that, you know, with AI and in particular ChadGPT, I found that it takes people some time to really understand all the parts of their life they can delegate.Right.And I think many users for that, it's a multi-month process for them to understand how can this thing help me and what are all the different ways that I can plug ChadGPT into my life.And, but, you know, when I think about some of the breakthroughs and levers we've had, things like search and personalization, they have helped solve those user problems because, you know, search provides way more daily value to you.It used to be that ChadGPT was a pretty worky product.You know, we'd see usage go down on the weekend.We'd use it, you know, go down during the summer months when a lot of people were off from work.And today, you know, we're mobile first.The vast majority of us is mobile.And we see all these personal use cases.

Apoorv： 你在 ChatGPT 里看到了什么，让那些可能停用了几周、几个月的人又回来了？他们为什么回来？

Nick： 没有单一的某一件事。你要做出一个高留存的产品，靠的是无数件小事，以及真正系统性地把它一点一点做好。不过我要说，在 AI 上、尤其在 ChatGPT 上，我发现人们需要一段时间，才能真正搞明白自己生活里有哪些部分可以委派出去。对很多用户来说这是个好几个月的过程——搞清楚这东西能怎么帮我、我能把 ChatGPT 插进生活的哪些地方。但回想我们有过的一些突破和杠杆点，像搜索（search）和个性化（personalization），它们正好解决了这些用户问题：搜索让 ChatGPT 每天能给你的价值大得多。以前 ChatGPT 是个挺「工作向」的产品——周末使用量会掉下去，暑假很多人不上班的时候也会掉。而今天我们是移动优先（mobile first），绝大部分使用量来自手机，而且我们看到各种各样的个人生活场景。

[6:18] Nick Turley

And I think search was a big investment that got us there.And personalization makes ChadGPT so much more relevant for you, right, because it gets to know you over time.You get to know it.And those are two things that have materially moved the way that, you know, people come back to the product.But there's lots more to do.Yeah.And, you know, as I mentioned, I'm not resting on our retention stats, even though we're obviously very proud.Nice, nice, nice.And, you know, the other thing that I got wrong about ChadGPT was this is two and a half years ago.And I was like, well, you know, let's look at who's going to win this consumer AI race.Typically, these consumer markets are winner take most.Winner take all.Look at search.Google has near 90% plus market share, three and a half, four trillion in market cap.Mobile, same thing with Apple.Social, same thing with Meta.I was like, well, AI, Meta has all the distribution.Google's got all the distribution.They've got three, four billion users.Well, it would be a flick of a switch for them to roll out their AI.But I was wrong.That's not what happened.ChadGPT turns out, you know, you guys are at 900 million weekly active users now.And that growth has been incredible.

Nick： 我觉得搜索是把我们带到这一步的一笔大投资。而个性化让 ChatGPT 对你的相关性高得多，因为它会随时间慢慢了解你，你也慢慢了解它。这两件事实质性地改变了人们回访产品的方式。但要做的还多得多。就像我说的，我不会躺在留存数据上，尽管我们显然很自豪。

Apoorv： 另一件我看走眼的事发生在两年半前。我当时想：好，我们来看看谁会赢下消费级 AI 这场竞赛。通常这类消费市场是赢家通吃（winner take most / winner take all）。看搜索，Google 有近 90% 以上的份额、三万五千亿到四万亿美元市值；移动端，苹果也一样；社交，Meta 一样。我当时想，AI 嘛，Meta 有全部的分发渠道，Google 有全部的分发渠道，他们有三四十亿用户，只要一按开关就能把自己的 AI 推出去。但我错了，事情不是这么发生的。结果是 ChatGPT——你们现在 9 亿周活，这个增长实在惊人。

[7:27] Apoorv Agrawal

Clearly, distribution was not enough, right?So the same question for distribution.What are the levers for us that have gotten us to the scale?Is it model quality?Is it, you know, product quality?Is it, you know, features?

显然光有分发是不够的，对吧？所以同样的问题：把我们推到这个规模的杠杆到底是什么？是模型质量？是产品质量？是功能？

[7:40] Apoorv Agrawal

Is it the experience or product improvements like memory and personalization or search?Like, same question.Like, what would you say drove historical growth and success?We've got about 10% of the world coming to us now.90% left to go, right?

Apoorv： 还是体验，或者像记忆（memory）、个性化、搜索这样的产品改进？同样的问题：你觉得是什么驱动了历史上的增长和成功？

Nick： 现在全世界大概 10% 的人会来找我们，还剩 90%，对吧？

[7:55] Nick Turley

There's so much more opportunity to reach more people and introduce them to the way that AI can benefit them, right?But when I look backwards, and I only say that because, like, the next billion users might be very different in terms of, like, how you engage and reach and provide value.But when I look backward, it's been roughly a sort of one-third, one-third, one-third between sort of classic friction removal type of work.Like, one of the biggest moments when you look at pure impact was, you know, removing the authentication wall.And Sam will say, I told you so, because I think that was his feedback from, like, day one.It was like, you can't, you shouldn't have to log into the ChatGPT.But it's stuff like that that you do for any product.And it does matter.Some things never change, right?

还有太多机会去触达更多人、让他们认识 AI 能怎么帮到自己。不过当我往回看的时候——我特意说「往回看」，是因为下一个十亿用户在参与方式、触达方式、价值提供方式上可能非常不一样——往回看，大致是三分之一、三分之一、三分之一。第一份是经典的「消除摩擦」类工作。比如纯粹论影响力，最大的时刻之一就是去掉登录墙（authentication wall）。Sam 会说「我早就跟你们说过」，因为这从第一天起就是他的意见：你不该为了用 ChatGPT 还得先注册登录。这种事任何产品都要做，而且确实管用。有些东西是永远不变的。

[8:46] Nick Turley

But, you know, then, you know, another third or so is, you know, are what I would sort of sort of core product investments.And they're really typically things that we've done together between research and product.So search and personalization are really good examples of that where we came together and we figured out not just UI, UX evolution, but also how to post-train these changes into the model.And it was really the moments when we came together.Another recent example is, like, we have these writing blocks that render when you, you know, ask about queries where you're, you know, trying to write with the model.And, like, putting really good craft into those experiences really matters.And, you know, our users love it.And then another third of the growth has been just model improvements.Like, both step changes, like going from GPT 3.5 back then to GPT 4, then going from GPT 4 behind a paywall to 4.0, suddenly available to everyone, right?

然后另外三分之一，是我称之为核心产品投入的东西。这类东西通常是研究（research）和产品（product）一起做出来的。搜索和个性化就是很好的例子——我们坐到一起，搞清楚的不只是 UI/UX 怎么演进，还有怎么把这些变化后训练（post-train）进模型里。真正起作用的，正是我们坐到一起的那些时刻。最近一个例子是「写作块」（writing blocks）：当你问的是那种「想跟模型一起写点东西」的问题时，界面会渲染出这种写作块。把很好的手艺（craft）投进这类体验里，真的有用，我们的用户很喜欢。再另外三分之一的增长，纯粹来自模型本身的进步。既有阶跃式的变化——比如从当年的 GPT-3.5 到 GPT-4，再从付费墙后的 GPT-4 到 GPT-4o、突然人人都能用；

[9:41] Nick Turley

But a lot of it is also the iteration that isn't splashy, that doesn't warrant, like, you know, a named release.I'm really excited about the updates we just made with 5.3, 5.4, et cetera.Because that is when we, like, take a lot of user feedback and we, you know, methodically address it.And obviously that shows up in our retention as well.So sort of one-third, one-third, one-third between classic friction removal and access, core product investments, and then pure model improvements.And so the question that I've really been waiting to ask you is how do we get the next billion?

Nick： ……但也有很大一部分来自那些不出彩、不值得单独起个发布代号的迭代。我对我们刚做的 5.3、5.4 这些更新特别兴奋，因为那正是我们大量吸收用户反馈、然后有条不紊地逐条解决的时候，这显然也体现在留存上。所以是：三分之一消除摩擦与可及性、三分之一核心产品投入、三分之一纯模型进步。

Apoorv： 那我一直等着问你的问题就是：我们怎么拿下下一个十亿？

[10:17] Apoorv Agrawal

And, you know, talk about that a little bit.There's a lot of, it seems like, at least from the outside fog of war, if I was a consumer today in the market to pick my super assistant, you would have a couple of great options.You know, Claude out there, they're having some great traction the last couple of weeks.Gemini, mega distribution, Uber distribution, and us, by the leading product today, at least in user numbers, the next billion users, where are they going to come from?

聊聊这个吧。从外面的战场迷雾里看，好像……如果我今天是个消费者、要挑我的超级助理，会有好几个很不错的选择：Claude 在那儿，最近几周势头很好；Gemini 有超级分发、巨无霸级的分发；还有我们，按用户数今天是领先产品。下一个十亿用户会从哪里来？

[10:49] Nick Turley

First of all, just to contextualize that goal, we care about two things at the end of the day.Obviously, reaching more people is really important.It's a direct manifestation of our mission to the world, where the more people we can introduce to the benefits of AI, the better that is.But we're also really excited to go deeper.And that means taking the same billion users that find value in ChatGPT today and actually providing more meaningful value in the world, like actually helping them achieve their goals, not just answering questions, right?

首先给这个目标定个语境：说到底我们在意两件事。显然，触达更多人非常重要，这是我们使命最直接的体现——我们能让越多人认识到 AI 的好处越好。但我们同样很兴奋的是往深里走：让今天已经在 ChatGPT 里找到价值的那十亿人，真正在现实世界里获得更有分量的价值——真的帮他们达成目标，而不只是回答问题。

[11:22] Nick Turley

So I'll talk about how we get to more scale.But I think it's important to remember that, you know, the way this technology is evolving is, you know, we're going to go beyond pure chatbots pretty fast.Exciting.I think on scale, it's shocked me how many people have found value in ChatGPT as it works today, because I don't think delegation is a natural skill for most.And ChatGPT is a pretty, you know, it's a power tool, right?

Nick： 所以我会讲怎么把规模做大，但我觉得重要的是记住：这项技术演进的方式决定了，我们很快就会走出纯聊天机器人（chatbot）的形态。

Apoorv： 令人兴奋。

Nick： 在规模这件事上，让我震惊的是：有这么多人在 ChatGPT 现在这个样子上就找到了价值——因为我并不认为「委派」对大多数人来说是件自然的技能。而 ChatGPT 是个挺硬核的工具（power tool，专业电动工具），对吧？

[11:50] Nick Turley

You come to it, it doesn't tell you what it's for.You kind of have to discover it on your own, and you have to use it, and then you'll learn about this prompt that was really cool, and then maybe you're on Twitter and you learn about another one, or you're on Instagram and you learn another one.But the product, it's like a raw appliance.And I think for two, you know, one thing we really need to nail as we, you know, reach the next set of users is a product that has a bit more of an affordance.Because I think for most people, they're very, very busy.And everyone, I think, in the world has intelligence-constrained problems, like problems that more intelligence could help with.But you need to frame that to people.And I still feel like we're a little bit too much like a computer terminal, and it needs to feel more like software, like an operating system of software.So that's one thing.Another thing that gets at the same constraint is beginning to be proactive.In a world where a lot of folks are too busy to delegate their problems to AI or don't quite know where to start, I think being able to help you proactively is really, really important as well.But, you know, I think all of these are product evolutions that we could make on top of the current tech.

你打开它，它不会告诉你它是干嘛用的。你得自己去发现，得去用，然后你学到一个很酷的提示词，也许在 Twitter 上又学到一个，或者在 Instagram 上再学一个。但这个产品就像一台裸机电器。我觉得在触达下一批用户时，我们必须做对的一件事，是让产品带上更多的示能（affordance，产品自己提示你它能干什么、该怎么用）。因为大多数人都非常非常忙。而我认为世界上每个人都有「受智能约束」的问题——就是那些更多智能能帮上忙的问题。但你得把这件事框给人看。我还是觉得我们太像一个计算机终端了；它需要更像软件，像一个软件构成的操作系统。这是一件事。另一件针对同一个约束的事，是开始变得主动（proactive）。在一个很多人忙到没空把问题委派给 AI、或者根本不知道从哪儿下手的世界里，能主动帮你，我觉得非常非常重要。不过我认为这些都是我们在现有技术之上就能做出的产品演进。

[13:00] Nick Turley

And the thing that gets me particularly excited is productizing our next generation tech or reasoning models.Because the truth is, when you look at reasoning in ChatGP2 today, it's relevant to a very small group of people.It's relevant for the people who are trying to get the most out of ChatGP2.But I fundamentally believe that reasoning, it's transformative.And if you can figure out how to productize reasoning in a way that works on people's behalf without them even knowing.And that looks very much like, you know, the model doing long-horizon tasks on your behalf.It doesn't mean you encounter the concept.It just means it's benefiting you, right?

而真正让我特别兴奋的，是把我们下一代技术、也就是推理模型（reasoning models）产品化。因为事实是，你看今天 ChatGPT 里的推理，它只跟一小撮人有关，只跟那些想从 ChatGPT 里榨出最多价值的人有关。但我根本上相信推理是变革性的。如果你能想明白怎么把推理产品化，让它在用户完全不知情的情况下替他们干活——那看上去就很像模型在替你执行长周期任务（long-horizon tasks）。这不意味着你要接触到「推理」这个概念，只意味着你在从中受益。

[13:35] Nick Turley

So there's so much work to do.And, you know, the product certainly has to evolve to be relevant for this kind of skill.Yeah.Yeah.One of the things that I've been hoping for a while, and, you know, Brad made a bet two years ago,when can ChatGP2 help me take actions?

Nick： 所以有太多事要做。产品当然也必须演进，才配得上这种能力。

Apoorv： 有件事我盼了挺久——Brad（Brad Gerstner）两年前打过一个赌：ChatGPT 什么时候能帮我采取行动（take actions）？

[13:55] Apoorv Agrawal

When can ChatGP2 help me be more proactive?And I think his bet expired end of last year.So we were very curious.When is that coming out?I'll frame that for you because, you know, with search engines and Google, you know, two decades ago,you could have gotten the 10 blue links.You could have spent an hour getting the answer.You can now get the answer instantly with ChatGPT.And it feels like the next step is actions.100%.And it feels like the next step is, you know, with, you know, Pulse is a great proactive product.That feels, you know, I have a Pulse that runs weekly.But what I would really like is, like, hey, Nick spoke about something.And just find me.Make sure I know that Nick spoke about this.Or, like, hey, this XYZ thing happened that I cared about a lot.When is that going to get proactive?

Apoorv： ChatGPT 什么时候能帮我更主动？我记得他那个赌去年年底就到期了，所以我们非常好奇：这个什么时候出来？我给你框一下：二十年前有了搜索引擎和 Google，你能拿到 10 条蓝色链接，你可能得花一个小时才拿到答案；现在用 ChatGPT 你能立刻拿到答案。感觉下一步就是行动。

Nick： 百分之百。

Apoorv： 而且感觉下一步是——Pulse 是个很好的主动型产品，我有一个每周跑的 Pulse。但我真正想要的是：嘿，Nick 讲了某件事，帮我找出来，确保我知道 Nick 讲了这个；或者说，我很在意的某件事发生了。这什么时候能变主动？

[14:42] Nick Turley

What is the modality going to look like?Yeah.Yeah.So there's two concepts, I think.There's ChatGPT doing stuff rather than just answering.And then there's ChatGPT being proactive.And I think when you put them together, you start feeling like it feels like a super assistant.Because I think these things compound.On the action-taking piece, strictly speaking, ChatGPT can do stuff today.The action space is just very limited, right?

Apoorv： 那个形态会长什么样？

Nick： 我觉得这里有两个概念。一个是 ChatGPT 去做事，而不只是回答；另一个是 ChatGPT 变主动。当你把这两个放到一起，你就开始觉得它像个超级助理了，因为这两件事是复利叠加的。在「采取行动」这一侧，严格说 ChatGPT 今天就能做事，只是**行动空间（action space）**非常有限。

[15:10] Nick Turley

It can search the web, which means it can use a search tool or a browser in the same way that a human would.It can make images.It can do all these things, right?But it clearly doesn't have the same action space that a human with a computer would have.And that is what we aim to build.And if you, timing is everything on these bets, right?

它能搜网页，也就是说它能像人一样使用搜索工具或浏览器；它能生成图片；这些它都能做。但它显然还没有「一个人加一台电脑」所拥有的那种行动空间。而那正是我们要造的东西。而且在这类下注上，时机就是一切。

[15:26] Nick Turley

And I don't pretend to be great at timing either.When I look at past attempts that we've made, like the ChatGPT agent, for example, which kind of has capabilities like this, it was just slightly too early.The models weren't quite good enough to hit real escape velocity.And the problem is if you don't have escape velocity is that users don't learn to trust it.They don't even try.So when you look at a lot of things people were doing in the original version of ChatGPT agent, it was the things that happened to work.Like migrating your file server into the cloud or something like that.Useful stuff, but very niche.Yeah.And as this stuff gets better, we just have to get it to a point where people try to use it for real meaningful problems in their life.Because then we can start hill climbing.And this has been the magic of ChatGPT.Where ChatGPT upon launch was good enough to get real attempts at use cases, even if they didn't initially work.Like ChatGPT was a pretty bad writer originally.It was a bad software engineer.But people tried and got enough value out of it that we could take those use cases and make them great.And I do think we're about to get to that point with general purpose agents where it works well enough that you get at least partial credit.

我也不敢说自己擅长把握时机。回看我们过去的尝试，比如 ChatGPT agent，它其实有类似的能力，只是稍微早了那么一点点——模型还不够好，达不到真正的逃逸速度（escape velocity）。而没有逃逸速度的问题在于：用户学不会信任它，他们连试都不会试。所以你去看第一版 ChatGPT agent 上人们做的很多事，都是那些「碰巧能跑通」的事，比如把文件服务器迁到云上之类——有用，但非常小众。随着这些东西变好，我们只需要把它推到一个点：人们愿意拿它去解决自己生活里真正有意义的问题。因为到那时候我们就能开始**爬山（hill climbing，顺着反馈一小步一小步往上优化）**了。这正是 ChatGPT 的魔力所在：ChatGPT 刚上线的时候就已经足够好，好到人们愿意拿真实场景来试，哪怕一开始并不成功。ChatGPT 最初写作很差，做软件工程也很差，但人们试了，而且拿到了足够的价值，于是我们就能把这些场景接过来做到极好。我确实觉得，**通用智能体（general purpose agents）**快要到那个点了——它工作得足够好，至少能拿到部分分数。

[16:36] Nick Turley

And because you're getting partial credit, you get really good tasks back.And then the magic begins because once you have a set of use cases that you can climb the hill on, we can make them awesome.So on tasks, I think we're close.But I think even people inside of OpenA would have had a hard time predicting exactly when this gets good.We've been excited about it for a while.On proactivity, Pulse was a really great first step because what we wanted to build was a form factor where you're not prompting the model.Like the model is prompting you.For the reasons that I described earlier, which is, you know, it's so hard for people to delegate and to figure out what their problems are.What if the AI understood your goals and the things you're interested in and just could start being proactive on your behalf?

而正因为你能拿到部分分数，你就能拿回非常好的任务样本。然后魔法就开始了：一旦你有了一组可以爬山的用例，我们就能把它们做得很棒。所以在任务这件事上，我觉得我们很接近了。但我觉得就算是 OpenAI 内部的人，也很难准确预测这东西什么时候会变好——我们期待它很久了。在主动性上，Pulse 是非常好的第一步。我们当时想造的是一种形态：不是你去提示模型，而是模型来提示你。原因就是我前面说的：人们太难去委派、太难搞清楚自己的问题到底是什么。那如果 AI 理解你的目标和你关心的东西，能主动替你做点什么呢？

[17:24] Nick Turley

Pulse is limited in the value it can provide for you because it's not connected to your life and it can't take action.So it's producing information for you.And people love that.You know, I love that.I've got mine running too.But I think the magic begins when you have actions and proactivity because then it can begin speculatively actually, you know, detecting, hey, you just landed where you were supposed to go.You know, I'm going to call a cab for you.Or, you know, if you're at work, it's like, hey, I proactively ran this analysis because I saw your metrics dropped.So I think these things really compound and we need to nail multiple of the building blocks to really achieve the transformation of the form factor that we hope for.As you were answering those questions, I now have 15 more questions for you.So I hope you have 15 more minutes.But, okay, one by one, we'll start with what you said on actions and tasks.Got it on timing.Tough to say.But is there a shape or ordinality of tasks or agents that you think, hey, this is the kind of thing that's likely to come first whenever it does?

Nick： Pulse 能给你的价值是有限的，因为它没有连到你的生活里，也不能采取行动，它只是在给你产出信息。人们很喜欢这个，我自己也很喜欢。

Apoorv： 我也开着一个。

Nick： 但我觉得，当你同时拥有行动和主动性的时候，魔法才开始——因为那时候它可以带点推测性地去做事：嘿，你刚落地到你该去的地方了，我给你叫辆车；或者你在上班，它说，嘿，我看到你的指标掉了，我主动跑了这个分析。所以我觉得这些东西是复利叠加的，我们需要把好几块积木都做对，才能真正实现我们期待的那种形态跃迁。

Apoorv： 你回答这些问题的时候，我又多了 15 个问题，所以希望你还有 15 分钟。好，我们一个个来。先从你说的行动和任务开始——时机没法说，明白了。但有没有某种形状或者次序上的任务/智能体，你觉得「这类东西大概率会最先到来」？

[18:29] Nick Turley

I mean, the thing that's already come first is the domain-specific agents, right?If you look at what's happening in code, we're fully there.You know, it's mind-bending.But we've got so many engineers who don't open their IDE, like, ever.And for me, as someone who used to code and then unfortunately got very, very busy, it's brought me back in the game.So Codex and products like it is clearly a product that has escape velocity where people are absolutely using it for all kinds of agentic work.And if you just take what people are doing and make it work even better, you kind of get all the way there.You know, I won't be surprised if you see this happen for other forms of sort of quantitative knowledge work.Just because it happens to have the properties that Codex has.It's testable.You know if it worked or not.It's very RL friendly.But the domain-specific ones already work.I think the thing everyone's working for is, you know, general purpose agents that just kind of work for anything.And that's why I think you need to win a consumer because it's very hard to train people into like, okay.It can work.Deep Research was a consumer product and it really was our first agentic thing out there.

已经最先到来的，其实是领域专用智能体（domain-specific agents）。你看代码这块，我们已经完全到了，简直匪夷所思——我们有那么多工程师根本就不打开 IDE 了。对我这种以前写代码、后来不幸忙到没时间的人来说，它把我又带回了游戏里。所以 Codex 以及类似的产品，显然是已经达到逃逸速度的产品，人们确确实实在用它做各种智能体式的工作。而你只要把人们正在做的事拿过来、让它跑得更好，你基本上就一路到位了。我不会惊讶于这件事在其他形式的定量知识工作上重演，因为它们碰巧具备 Codex 具备的那些性质：可测试，你知道它到底成没成，非常适合强化学习（RL）。领域专用的已经能用了。我觉得所有人都在攻的，是那种「什么都能干」的通用智能体。这也是为什么我觉得你需要在消费端取胜——因为你很难把人重新训练成某个样子。它是能跑通的：Deep Research 就是个消费级产品，而且真的是我们放到外面的第一个智能体式的东西。

[19:48] Nick Turley

But I think what consumers want is I can just ask at anything and we'll do what needs to be done without any sort of retraining.And we'll get there.Just a matter of time.At least the psychological goal is flight bookings.Totally.The restaurant bookings.Shopping.All this stuff.There are so many consumer problems.And those are just the type of things that you would kick off, right?

Nick： 但我觉得消费者想要的是：我可以问任何事，它就把该做的事做掉，不需要我做任何再训练。我们会走到那一步的，只是时间问题。

Apoorv： 至少心理上的目标是订机票。

Nick： 完全是。

Apoorv： 订餐厅、购物，所有这些。

Nick： 消费者的问题太多了，而这些正是你会「一键甩出去」的那类事，对吧？

[20:12] Nick Turley

Yeah.The minute you have productivity, there's things you don't even think of as agentic tasks.Like you're trying to get in shape.You don't think of that as a task you would delegate.Yeah.Unless you have a trainer.In which case you do.But most people don't.Right?

Nick： 而一旦有了主动性，就会有一些你根本不会觉得是「智能体任务」的事。比如你想练出好身材，你不会觉得那是一件你可以委派出去的任务。

Apoorv： 除非你有私教。

Nick： 那样的话你确实会委派。但大多数人没有，对吧？

[20:26] Nick Turley

But if the AI knew that, it could totally start working in the background for you over very long periods of time and getting you, you know, here's your fitness plan.Okay.I actually signed you up for this thing.You could imagine it being quite helpful if it's aligned with your long-term interests.You're going to give Ozempic a run for the money.We've got to be careful what businesses we get into.But hopefully we can help.That'll be great.Cannot wait.Cannot wait.The second thing you said was, you know, proactive users.And that might require us to go beyond chatbots.What's an example of a modality that might take ChatGPT beyond a chatbot?

Nick： 但如果 AI 知道这件事，它完全可以在后台替你长期地干下去，然后告诉你：这是你的健身计划——另外我已经帮你把那个项目报名了。你可以想象，只要它跟你的长期利益一致，这会相当有用。

Apoorv： 你们这是要让 Ozempic（司美格鲁肽减肥药）不好过了。

Nick： 我们得小心别进错行。但希望我们能帮上忙。

Apoorv： 那太好了，等不及了。你说的第二件事是主动性，而那可能要求我们走出聊天机器人。有没有什么例子，是能把 ChatGPT 带出聊天机器人的新形态？

[21:02] Nick Turley

So chat will always be close to my heart.It's the way we grew up.And it's an important modality to stay.Like I think it's less about chat and more about natural language to me where, you know, it's the fact that you can express yourself to the machine in ways that are very natural to you.Whether or not that's text.Whether or not that's voice.Whether or not that is, you know, structured UI that is rendered by the model.That is just very, very powerful.And that's here to stay.But I think the thing.SA Server.That's right.For those who don't know, that's the name of our code base.Short for Super Assistant Server.Because, you know, it's proof that this was always the vision and it's always the vision.But, you know, the thing that will change, I think, is that chat is a great way of expressing your intent.It's a good way of communicating with the machine.But it's not a great output.Where in many cases, what you want back is an artifact.Like, here's your plan for your trip.Here is the analysis.Here is, you know, an outcome that I delivered for you.You know, I just made you five bucks.Like, this is what I want my AI doing for me, right?

Nick： 聊天永远是我的心头好，我们是这么长大的，它也是会长期留下来的重要形态。不过对我来说，与其说是「聊天」，不如说是「自然语言」——你能用对你来说非常自然的方式向机器表达自己，不管是文字、语音，还是由模型渲染出来的结构化界面。这非常非常强大，而且会一直留下来。

Apoorv： SA Server。

Nick： 没错。给不知道的人解释一下，那是我们代码库的名字，是 Super Assistant Server（超级助理服务器）的缩写。因为这证明了这一直是我们的愿景，而且始终是。但我觉得会变的是：聊天是表达意图的好方式，是跟机器沟通的好方式，但它不是一个好的输出。很多情况下你想拿回来的是一个产物（artifact）：这是你的旅行计划、这是那份分析、这是我替你交付的一个结果——「我刚帮你赚了五块钱」。这才是我想要我的 AI 替我做的事，对吧？

[22:09] Nick Turley

Yeah, totally.I mean, this is what people care about, right?And I think chat will always be there as the way that you sort of disambiguate your intent and you kick off the task.But I don't think it's necessarily the final deliverable.And I think that's the way in which we can evolve.So hopefully that's a very graceful transition because I'm very lucky and it's hard earned, you know, to have a billion people coming to you weekly for a thing that they love.But I think it's a great jumping off point because we have so much unsatisfied intent from people where they're clearly trying to do something and ChatGPT is helpful enough.But it could be so much more helpful.And I think that's where we evolve.Yeah.And you must be sitting on so much of this data where people are showing up to ChatGPT and attempting.As you said, three years ago, they were at least making the attempt.Yeah.So you might have at least a frequency histogram of like, hey, here are all the things that people want to achieve with us.We do.We have like really awesome, you know, classifiers that run automatically.It's fully privacy preserving, but gives us a sense of, you know, what use cases people have.And it's important, right?

Apoorv： 完全同意，这才是人们真正在意的。

Nick： 我觉得聊天会一直在，作为你厘清意图、启动任务的方式，但它不一定是最终交付物。我觉得这就是我们能演进的方向。希望这是一个非常平滑的过渡，因为我很幸运——而且这是辛苦挣来的——每周有十亿人来找你用一个他们喜欢的东西。但我觉得这是很好的起跳点，因为我们手上有大量未被满足的意图：人们明明想做成某件事，ChatGPT 帮上了忙，但它本可以帮上大得多的忙。我觉得这就是我们要演进的地方。

Apoorv： 你手上一定坐着海量这样的数据——人们来 ChatGPT 想尝试做的事。像你说的，三年前他们至少愿意去试。所以你至少有一张频次直方图：这是人们想用我们达成的所有事情。

Nick： 我们确实有。我们有非常棒的分类器（classifiers）在自动跑，完全保护隐私，但能让我们知道人们有哪些使用场景。这很重要。

[23:11] Nick Turley

Because when you make a new model, we make a model update.You want to know what use cases just got better or what use cases got worse.Yeah.And that's not always trivial to figure out unless you have really good analytics on the system.But so much of my learning is actually qualitative where I will just, you know, have a habit of reaching out to a fairly random set of users who just figure out what they're doing.And I've never worked on a product where three and a half years later, you're still learning every time.Because usually by that time, you know what the use cases are that your product can, you know, deliver on.But our tech is so unusual in the fact that I keep learning about something crazy I didn't know was possible.Wow.That's awesome.But basically a billion users, I suspect a small fraction of them are power users who are getting maybe thousands, maybe tens of thousands of value on their $200 subscription.Yeah.The vast majority is, you know, middle of the pack.And a few, call it casual users, who are, you know, start using chat GPT as search maybe.Yeah.Or teach me about AI or help me with my homework.What is your focus?

Nick： 因为当你做一个新模型、发布一次模型更新时，你想知道哪些用例刚变好了、哪些变差了。而这件事如果没有非常好的系统级分析能力，并不容易搞清楚。但我学到的东西里有很大一部分其实是定性的：我有个习惯，会去联系一批相当随机的用户，搞清楚他们在干什么。我从没在别的产品上遇到过——三年半之后你每一次还在学到新东西。因为通常到那个时候，你已经知道你的产品能覆盖哪些用例了。但我们这项技术太不寻常了，我不断学到一些我压根不知道居然可能的疯狂用法。

Apoorv： 哇，太棒了。不过在十亿用户里，我猜有一小部分是重度用户（power users），他们从 200 美元的订阅里也许拿到了几千甚至几万美元的价值。

Nick： 是的。

Apoorv： 绝大多数是中间层；还有一部分算休闲用户，可能就把 ChatGPT 当搜索用。

Nick： 是的。

Apoorv： 或者「教教我 AI 是什么」「帮我做作业」。你的重心在哪儿？

[24:19] Nick Turley

Like maybe in those constituents, power users, casual users, and early users, or however you frame it.What is our focus on for each of those three factions?Yeah.Yeah.Well, first of all, I feel accountable to our entire user base.And in fact, our non-users too.Because, you know, products like chat GPT can have real externalities on all humans.Yeah.But when I think about sort of the way we build, it's really useful to imagine the extremes.One extreme being a user who doesn't care about AI at all, who has a busy life, and needs to be convinced of the value that we can provide.Because that forces you to really nail the interface and to expose the capabilities that are hidden in the model in a way that people can actually rock.And then the other useful extreme is, you know, our power user base.Because power users are the users who teach us what's possible.It's actually impossible for us to do all the product discovery on our own.Simply because of how empirical this technology is.And how much you actually learn post-launch.So building, you know, for each of those extremes can be valuable.But our user base is incredibly diverse.And people have so many different use cases.And this is why, you know, I like to look at all kinds of different segmentations.

Apoorv： 在重度用户、休闲用户、新用户这几类人里——不管你怎么划分——我们对每一类的重心是什么？

Nick： 首先，我对我们整个用户群都有责任感，其实对非用户也有，因为像 ChatGPT 这样的产品对所有人都可能产生真实的外部性（externalities）。但当我想我们怎么造产品时，去想象两个极端非常有用。一个极端是完全不关心 AI 的用户，他生活很忙，需要被说服我们能提供什么价值——因为这会逼着你把界面做到位，把藏在模型里的能力用人们真能理解的方式暴露出来。另一个有用的极端是重度用户，因为重度用户是教我们「什么是可能的」的人。我们不可能靠自己完成所有的产品发现（product discovery），单纯因为这项技术太经验主义（empirical）了，而且你在发布之后才学到那么多东西。所以为这两个极端造东西都很有价值。但我们的用户群极其多样，人们的使用场景太多了，所以我喜欢看各种不同的分层方式。

[25:43] Nick Turley

Not just frequency, but also, you know, what use cases are you coming to us for.But definitely huge variety in the attached to the user base.Yeah.I look up to macOS, for example, as an example.Where it really works for people who don't understand technology at all.It's entirely magical.But if you are a power user, you've got terminal, you've got settings, you can configure almost anything in macOS.And it's really beautifully done where the complexity is progressively disclosed.So you can interact with it and love the simplicity of it all.But you can also have all the knobs and developers love it, right?

不只是频次，还有你来找我们做的是什么用例。用户群的差异确实巨大。我把 macOS 当作一个仰望的例子：它对完全不懂技术的人也很好用，简直像魔法；但如果你是重度用户，你有终端、有设置，几乎什么都能配。它做得非常漂亮，复杂度是**渐进披露（progressively disclosed）**的——你可以享受它的简洁，也可以拧遍所有的旋钮，开发者很爱它，对吧？

[26:15] Nick Turley

And so I think this is kind of the inspiration for how we want to be in ChatGPT.That doesn't mean we always live up to it.But it means that building for power users is extremely important.And, you know, that's not just a property that I think is sort of aesthetically exciting.It's also really important in AI because it's the power users who show you what's possible.They are actually doing the product discovery.Because it would be impossible for us with such an empirical tech to do all the product discovery on our own.So the type of user who subscribes to ChatGPT Pro, who used Codex before it quite worked, who is now the strongest advocate of tools like Togits and teaching us what's possible.That is an incredibly valuable member of the community.And it might not show up in your, you know, weekly active users.It's just one number, right?

所以这大概就是我们希望 ChatGPT 长成的样子的灵感来源。这不代表我们总能做到，但它意味着为重度用户造东西极其重要。而且这不只是一个我觉得「审美上很兴奋」的性质，它在 AI 里也真的很关键——因为是重度用户告诉你什么是可能的，他们实际上在替你做产品发现。对这样一项经验主义的技术，我们不可能靠自己完成所有的产品发现。所以那种会订 ChatGPT Pro、在 Codex 还不太好用的时候就在用、如今成为这类工具最有力的拥护者、并且在教我们「什么是可能的」的用户，是社区里极其宝贵的一员。而他可能根本不体现在你的周活里——那只是一个数字，对吧？

[27:07] Nick Turley

But this is exactly why there isn't like a single North Star.And you really need to take these different segments very seriously.So I love building for power users.And, you know, you asked on, you know, token consumption, et cetera.It's so fascinating to see.There's people who get incredible value out of these products.And watching what they do is very informative.Okay.So you're very focused on the entire user base.Learn a lot from the power users.You know, the other thing I might say is the power users right now are getting a lot of value.Almost too much value.And a lot of...No such thing.No such thing.The analog that is most common is the Uber and Lyft of the 2015 era, right?

Nick： 但这恰恰是为什么不存在单一的北极星指标，你必须非常认真地对待这些不同的分层。所以我很喜欢为重度用户造东西。你刚问到 token 消耗之类的，看着特别有意思：有些人从这些产品里获得的价值高得惊人，看他们在干什么非常有启发。

Apoorv： 好。所以你关注整个用户群，同时从重度用户身上学到很多。我可能还想说的是：重度用户现在拿到的价值非常多，甚至可以说太多了。而且很多……

Nick： 没有「太多」这回事。

Apoorv： 没有这回事。最常见的类比是 2015 年那个时代的 Uber 和 Lyft，对吧？

[27:55] Apoorv Agrawal

And, you know, it took a while.But I know you were thinking about it a lot.I know you guys are thinking about pricing quite a bit.Yeah.Maybe tell us a little bit about pricing.You know, right now pricing is pretty simple.Is there a path for folks who are getting a lot of great value to price that product differently?

那确实花了一段时间。但我知道你在这件事上想了很多，我知道你们在定价上想了不少。能不能讲讲定价？现在的定价挺简单的。对那些拿到巨大价值的人，有没有可能用不同的方式给这个产品定价？

[28:13] Nick Turley

And, you know, meet them where they are and the other way on the other side?And pricing is...There's no world in which pricing doesn't significantly evolve when the technology is changing this quickly.Yeah.Right?

Apoorv： ……在他们所在的地方满足他们，另一边也一样？

Nick： 定价这件事——在技术变化这么快的时候，不可能存在「定价不发生重大演进」的世界，对吧？

[28:26] Nick Turley

ChatGPT originally was entirely free.And the reason for that was that it was intended to be a demo.Yeah.And we were going to wind it down after a month.And we then realized that the demo went viral and people loved the demo.And it was actually a product.But we realized to be a product, you can't take the product down every time you're at capacity.So we shipped subscriptions simply because it could shape the demand.It was a way of gracefully turning users away when we had to turn away someone.And it felt like the fairest and most equitable way of doing so is saying,hey, you know, if you really need this product, pay a subscription fee and you got it.But then we figured out how to make the product stable and we had the choice of,do we keep the subscription thing or do we go back to free?

ChatGPT 最早完全免费，原因是它本来只打算做个 demo，我们准备一个月之后就把它关掉。后来我们发现这个 demo 病毒式传开了，人们很喜欢它——它其实是个产品。但我们意识到，要成为一个产品，你就不能每次容量满了就把产品下线。所以我们上线订阅，纯粹因为它能塑造需求——这是一种在不得不挡人的时候、体面地把用户挡在门外的方式。当时感觉最公平、最公道的做法就是说：如果你真的需要这个产品，付个订阅费，你就有了。后来我们搞定了产品的稳定性，于是面临选择：是继续留着订阅，还是回到免费？

[29:04] Nick Turley

And we realized we had consistently more tech that we couldn't scale,GPT-4 being the first example because we had way too many free users to serve GPT-4and we put it behind the plus plan.And so, you know, the way we stumbled into subscriptions was sort of accidentalby trying to just solve for the user.And it felt like the right way at the time to provide maximal access to our tech.Since then, we've had so many other breakthroughs, including test time compute,

结果我们发现，我们手上总是有「服务不过来」的新技术，GPT-4 是第一个例子——免费用户太多了，没法给他们都提供 GPT-4，于是我们把它放进了 Plus 计划。所以我们撞进订阅制的方式其实相当偶然，出发点只是想解决用户的问题。在当时，那感觉是让大家最大程度用上我们技术的正确方式。从那以后我们又有了很多突破，包括测试时计算（test time compute，模型在回答时多花算力去「想」）——

[29:34] Nick Turley

where you can scale up intelligence kind of as much as you want, more or less.And, you know, it took us, you know, in the entire industry,a little bit of time to turn that into product value.But we're here now where, you know, our power users want to use more and more and more intelligence.And, you know, it's possible that, you know, in the current era,having an unlimited plan is like having an unlimited electricity plan.You know, it just doesn't make sense because, like, you know,people may need a lot, a lot of electricity and they're getting a lot of value out of that.There's a reason you can't buy that, right?

——有了它，你基本上想把智能拉多高就能拉多高。整个行业都花了一点时间，才把它转化成产品价值。但我们现在到了这一步：我们的重度用户想用越来越多、越来越多的智能。在当下这个时代，有一个「无限量套餐」，可能就像有一个「无限量用电套餐」一样——它讲不通。因为人们可能真的需要非常非常多的电，而且他们从中获得了很多价值。这也是为什么你买不到那种套餐，对吧？

[30:11] Nick Turley

So obviously I want to be really thoughtful about the way that we evolve our plans and SKUs and subscriptions.But, you know, I'd be incredibly, you know, surprised if it didn't change given the magnitude and profoundness of the technical breakthroughs that we've hadand the product breakthroughs that follow.Yeah.And, you know, relatedly, so I imagine you're going to have something for the power users.What about the other side?

Nick： 所以我显然想非常慎重地对待我们的套餐、SKU 和订阅怎么演进。但考虑到我们经历的技术突破的量级与深刻程度、以及随之而来的产品突破，如果定价不变，我会非常非常吃惊。

Apoorv： 相关地，我猜你们会为重度用户准备点什么。那另一边呢？

[30:38] Nick Turley

How do we get the casual users into the wheel and still monetize them?As mentioned, you know, our business model will evolve in the North Star's access.We would like to pick a way of providing an offering.We want to provide an offering that maximizes the number of people who can access our most powerful tools.I think for the longest time that has been subscriptions.Subscriptions have the downside of the fact that, you know, in many markets people don't have credit cardsor they don't use credit cards to subscribe to software.And we're interested in other ways that can maximize access of the tech.Our ads pilots are in that spirit.You know, we really view it as a tool of bringing ChatGPT and our intelligence most broadly to anyone around the world.And it is an example of how we constantly need to evolve and figure out the best way to, you know,bring the demand in line with what we are able to offer.Makes sense.Makes sense.You know, the ads piece has been a tricky one because, you know, Sam has historically expressed reluctance about ads.And, you know, you've got to maintain a lot of trust while delivering that.So, I guess, what changed?

Apoorv： 我们怎么把休闲用户拉进这个飞轮，同时还能变现他们？

Nick： 像我说的，我们的商业模式会演进，而北极星是可及性（access）。我们想选一种能让最多人用上我们最强工具的供给方式。很长时间以来那就是订阅。订阅的缺点是，很多市场的人没有信用卡，或者他们不用信用卡订阅软件。所以我们对其他能最大化技术可及性的方式很感兴趣，我们的**广告试点（ads pilots）**就是这个精神。我们真的把它看作一个工具——把 ChatGPT 和我们的智能最广泛地带给全世界任何人。它也是一个例子，说明我们需要不断演进、找出把需求和我们的供给能力对齐的最佳方式。

Apoorv： 有道理。广告这块一直挺微妙的，因为 Sam 历史上表达过对广告的抵触，而且你们必须在做广告的同时维持住大量信任。所以我想问：什么变了？

[31:59] Nick Turley

I think we've talked about this several times in my history at OpenAI.And every time it came up, we said if we were to do ads, we'd have to be really thoughtful about the way we do it.So, the first thing we did, you know, starting, you know, end of last year was to really engage the company on if we put ads in ChatGPT,how should we approach it, what should the principles weigh, how do you preserve the things that are magical about ChatGPT,while getting the benefits of ads, which, you know, is our ability to bring our most advanced tech to anyone, regardless of their ability to pay.And I really love where we ended up on the principles side.On the experience side, we're very, very early.But on the principles side, I feel really proud because, you know, it's very important that the answer of ChatGPT be independent, as an example.Respecting user privacy is very important.And there's a lot to learn from, you know, the way that tech has evolved over the last few years, or really last decade.And I like that the principles are out there before we've even really gotten started.Like, we're very early with our pilots.You know, it's kind of interesting.I was obviously very anxiously and eagerly looking at our support in bounds and data.

我在 OpenAI 这几年，这件事我们聊过好几次。每次提起，我们都说：如果我们要做广告，就必须对做法非常慎重。所以我们做的第一件事，是从去年年底开始，让全公司认真讨论——如果我们在 ChatGPT 里放广告，我们该怎么做？原则该怎么权衡？怎么保住 ChatGPT 那些有魔力的东西，同时拿到广告带来的好处，也就是让我们能把最先进的技术带给任何人、不管他付不付得起钱。我很喜欢我们在原则这一侧的落点。在体验这一侧，我们还非常非常早。但在原则这一侧我很自豪，因为有些事非常重要：比如 ChatGPT 的回答必须保持独立；尊重用户隐私非常重要。过去几年、其实是过去十年科技演进的方式，有很多可以吸取的教训。我喜欢的是，在我们真正开始之前，这些原则就已经公开了——我们的试点还非常早。挺有意思的是，我当然非常紧张又急切地盯着我们的客服工单和数据。

[33:19] Nick Turley

And the most common inquiry about ads is not, you know, how do I disable ads or turn off ads, but it's like, how do I run an ad?Because the entire ecosystem is really excited to be part of the story and to figure out a way to talk to ChatGPT users.So there's a lot more to come, but I'm very eager to get this right.Yeah.Yeah, I'm sure you guys will.Switching gears, Nick, something you and I have spoken about a little bit is, you know, distribution and partnerships.

Nick： 而关于广告最常见的咨询，不是「我怎么关掉广告」，而是「我怎么投广告」。因为整个生态都非常兴奋想参与进这个故事，想找到跟 ChatGPT 用户对话的方式。所以后面还有很多，但我非常想把这件事做对。

Apoorv： 你们肯定能做好。换个话题，Nick，我们聊过一点的是分发和合作伙伴。

[33:52] Nick Turley

There's a couple of big partnerships last year.Apple Reliance with Gemini.Those are two big user bases, right?A lot of India, a lot of the iOS users.Doc, tell us a little bit about how you think about partnerships for ChatGPT to meet the user base, and maybe specifically on those two as well.Look, I think partnerships are a great way to bring two products together and to, you know, expose something like ChatGPT to people who might not otherwise have encountered it.The thing that I care about most when considering something like a partnership is what is the user experience and can we make it amazing?

Apoorv： 去年有几个大合作：苹果、印度信实（Reliance）跟 Gemini 签了。那是两个巨大的用户群，对吧？大量印度用户，大量 iOS 用户。跟我们讲讲你怎么看 ChatGPT 的合作伙伴策略、怎么触达用户群，也许特别说说这两家。

Nick： 我觉得合作是把两个产品放到一起、把 ChatGPT 这样的东西暴露给本来可能碰不到它的人的好方式。考虑合作时我最在意的是：用户体验是什么？我们能不能把它做到惊艳？

[34:40] Nick Turley

Yeah.Because at the end of the day, when you look at what's going on in the market, you can get users to click on things.You can get them to tap any sort of product, especially if it looks like a product they recognize, et cetera.But if the experience isn't truly awesome, people will churn or they will, you know, at least not retain in the way that, you know, we've been lucky to retain them on ChatGPT.So for that reason, you know, I'm super interested in tasks like that, but it needs to be great.It needs to accrue to the user.We are very lucky to have a great brand and a recognizable product for many, many folks.And I want to make sure that anything we do is accretive to all that.Nick, you are a master of trade-offs.You must be making a lot of trade-offs right now.Tell us about some of the trade-offs you're making.Tell us about, you know, a trade-off that you might be making that people don't appreciate from the outside.There are a lot of trade-offs indeed and for different reasons, right?

Nick： 因为说到底，你看市场上正在发生的事——你可以让用户点击某个东西，可以让他们点开任何产品，尤其是它长得像他们认识的产品的时候。但如果体验不是真的很棒，人们会流失，或者至少不会像我们在 ChatGPT 上有幸留住他们那样留下来。所以出于这个原因，我对这类事非常感兴趣，但它必须很棒，必须让用户真的得利。我们非常幸运，有一个很好的品牌和一个很多人都认得的产品，我想确保我们做的任何事都是给这一切加分的。

Apoorv： Nick，你是权衡取舍的大师，你现在一定在做大量取舍。跟我们讲讲你正在做的一些取舍吧，讲一个外人不太能体会的取舍。

Nick： 取舍确实很多，而且理由各不相同，对吧？

[35:48] Nick Turley

The one I encounter a lot is trading off, delivering on the people, on the use cases that exist in the product today and making them better versus productizing, you know, step change technology that's going to generate a whole other set of use cases.

我最常遇到的取舍，是在「把产品里今天已经存在的用例做得更好」和「把阶跃式的新技术产品化、从而催生出一整批新用例」之间做权衡。

[36:06] Nick Turley

Because when you think about how ChatGPT came to be, it was a totally open-ended product.It was basically a user experience around a technical breakthrough.And we couldn't have told you all the ways that people find it valuable.But putting it out there was really important because it allowed us to discover in the world to discover what you can do.And then post-ChatGPT, we can obviously very systematically go and improve on the things that people actually want to use it for.And when you're at a company in this moment where you both have such amazing traction with what exists today and the most mind-bending breakthroughs on the research side,the balance you have to strike is making the core product you have better today with all the things that matter, latency, reliability,making the use cases really great that people come to with providing access to the step change.And we try to get the balance right, but we're a small team and we don't always get it right.And for that reason, that's one of the most difficult tradeoffs that I have to do with.Nick, I imagine one of the hardest tradeoffs you guys make here is those GPUs that are melting.Between ChatGPT, between Codex, research, how do you guys allocate the GPUs?

Nick： 因为你想想 ChatGPT 是怎么来的——它完全是个开放式的产品，本质上是围绕一个技术突破做的用户体验。我们当时根本说不出人们会用它做哪些有价值的事，但把它放出去非常重要，因为那让世界去发现「你能拿它做什么」。而在 ChatGPT 之后，我们显然可以非常系统地去改进人们真正想用它做的那些事。当你身处这样一个时刻——既对现有产品有惊人的势能，研究侧又有最令人瞠目的突破——你必须拿捏的平衡就是：一边把手上的核心产品在所有要紧的地方做得更好，延迟（latency）、可靠性（reliability），把人们真正来用的场景做到极好；一边又要提供通往阶跃式新能力的入口。我们努力把这个平衡拿捏好，但我们是个小团队，也不是每次都对。所以这是我要处理的最难的取舍之一。

Apoorv： Nick，我猜你们做的最难的取舍之一，是那些烧得发烫的 GPU。在 ChatGPT、Codex、研究之间，你们怎么分配 GPU？

[37:26] Nick Turley

That is a very good question, and I'll let you know when I figure it out.Just kidding. We've gotten a lot better at this.I really hope, by the way, to be at a point one day, and I've yet to reach that point,where we don't have to face this tradeoff because it's really painful to have real user demand for products that you can't serve.If you only ever worked in software, that's an entirely unusual dynamic, right,where you are limited by this zero-sum resource out there.The marketplaces have it, but I think pure software doesn't really have the dynamic, right?

这是个很好的问题，等我想明白了告诉你。开玩笑的，我们在这件事上已经好多了。顺便说一句，我真心希望有一天我们不必再面对这个取舍——我还没到那一天——因为「有真实的用户需求，你却服务不了」这件事真的很痛苦。如果你只做过软件，这是一个完全陌生的动态：你被一个零和资源卡住。市场型的生意有这种动态，但纯软件通常没有，对吧？

[38:03] Nick Turley

Yeah.So one thing we try to do, obviously, we prioritize our existing users first.We want to provide a fast, reliable product, and that is critical and table stakes.Then when you look at new capabilities, the sort of naive business school thing to do would be to probably look at revenue,incremental revenue per GPU or something like that.But this is where it's more an art than a science because we often have new breakthrough capabilities that are entirely zero to one.Deep research was one of those.We couldn't have told you is there going to be consumer demand for a research product,but if you don't productize it to find out, you will never know.So this is where we have to be a little bit thoughtful on how we balance things that are no-brainers,that people are really going to love, with things that are brand new ideas.And then obviously on the research side, there's a reason that Mark has the job he hasbecause a big part of his job is figuring out what research to fund.And, you know, obviously GPU is a big part of that.So very nuanced topic that we're continuously getting better at.But for me, the priority is always on our users.Yeah.The other takeaway that I had is you don't have line of sight to a time when you won't have that problem.

Nick： 所以我们努力做的一件事是：显然我们优先保障现有用户。我们要提供一个快速、可靠的产品，这是关键、是最低要求。然后当你看新能力时，商学院式的天真做法大概是看收入——每块 GPU 的增量收入之类。但这恰恰是「艺术多于科学」的地方，因为我们经常有全新的、从零到一的突破性能力。Deep Research 就是其中之一：我们当时说不出一个「研究型产品」到底有没有消费需求，可你不把它产品化去试，你永远不会知道。所以这里我们必须稍微用点心，去平衡那些「一看就会被喜欢的稳妥选择」和「全新的点子」。当然在研究侧，Mark（Mark Chen）坐在那个位置上是有原因的，因为他工作的一大部分就是决定资助哪些研究，而 GPU 显然是其中很大一块。所以这是个非常微妙的话题，我们在持续变好。但对我来说，优先级永远在用户身上。

Apoorv： 我的另一个体会是：你看不到一个「不再有这个问题」的时间点。

[39:20] Nick Turley

It's been so fascinating because, you know, we obviously have been incredibly lucky to encounter more and more userswho want to use our technology, but then the value that we're able to provide for each user is going up as well.And, you know, GPU consumption correlates pretty well with that value.And when you just look at token consumption per user, especially in the enterprise too,which is, you know, a massive opportunity, you see a lot of very GPU hungry workflows.And, yes, demand keeps going up even as prices go down.This is a fascinating insight.People used to think that humans were, you know, you can't kind of make more humans.Well, it takes nine months and then 19 years.But you're saying, well, that's actually a more and less finite resource than GPUs.Yeah.I mean, on the human side, you can hire more humans.And obviously, we've been doing busy doing that and bringing the best talent across functions to OpenAI.In the world with agents, you can also get more leverage per human.You can make your humans very effective at their job to do more.But GPUs are zero sum.And if you don't have more GPUs, you really have to figure out how do you make very, very hard trades.And I hate making hard trades for our users.

Nick： 这非常有意思。我们显然非常幸运，遇到越来越多想用我们技术的用户；但与此同时，我们能为每个用户提供的价值也在上升。而 GPU 消耗跟这个价值的相关性挺高的。当你看每用户的 token 消耗，尤其在企业侧——那是个巨大的机会——你会看到很多非常吃 GPU 的工作流。而且是的，就算价格在降，需求还是一直在涨。

Apoorv： 这是个很有意思的洞察。人们过去觉得人是没法「多造」的——造一个人要九个月，然后再花 19 年。但你其实是在说，跟 GPU 比起来，人反而是个没那么有限的资源。

Nick： 在人这一侧，你可以多招人，我们显然一直在忙着招，把各职能最好的人才带进 OpenAI。而在有智能体的世界里，你还能让每个人的杠杆更大，让你的人在工作上更高效、做更多事。但 GPU 是零和的。如果你没有更多 GPU，你就真的必须想清楚怎么做那些非常非常难的取舍。而我讨厌为我们的用户做艰难取舍。

[40:45] Nick Turley

Yeah.Hence the desire to have more GPUs.But it's useful to start with the most zero sum trade off when you do your planning.So I think starting working backwards from GPUs is usually a pretty good idea.Yeah.You know, we have all these external data sources for charts of users and usage and activity and retention and all those things.What we don't have is tokens per user over time.And I bet that chart is like a sweet line going this way.I think internal is pretty good.Our internal employees is a pretty good indicator for what's about to happen.And yes, the charts are mind-boggling.Yeah.Yeah, yeah.Fascinating.Okay.A couple of quick ones on the present before we go into the landscape, which is, you know, shopping.You know, we just moved into a new house.We took some photos and we were hoping that all our furniture would magically appear that ChadGPD helped us paint.But, you know, a lot of recent updates on ChadGPD shopping.Tell us about it.What are you thinking on ChadGPD as a shopping assistant?

Nick： 所以才想要更多 GPU。但在做规划的时候，从最零和的那个取舍开始是有用的。所以我觉得从 GPU 往回倒推着排，通常是个不错的主意。

Apoorv： 我们有各种外部数据源，能看到用户数、使用量、活跃度、留存这些图。我们没有的是「每用户 token 消耗随时间的变化」，我打赌那张图是一条这样往上冲的漂亮曲线。

Nick： 内部数据挺好看的。我们内部员工是个很好的先行指标，能预示接下来会发生什么。而且是的，那些图令人难以置信。

Apoorv： 好，在进入行业格局之前，先问几个关于当下的小问题——购物。我们刚搬进新房子，拍了些照片，本来还指望所有家具能像 ChatGPT 帮我们选漆那样自动变出来。ChatGPT 购物最近有不少更新，跟我们讲讲吧。你怎么看 ChatGPT 作为购物助理？

[41:50] Nick Turley

Shopping is one of those use cases that exist organically in ChadGPD today.And they work.You can ask ChadGPD about any purchase you might be planning and get pretty excellent advice.But it's also one of those cases where the experience that exists in Chad today, it's not the perfect experience that you would want.Because shopping is very visual, for example.So you're going to want to actually see products and images and be able to compare and contrast, not just read, you know, walls of text.People care about the sources of, you know, where can I learn more about, you know, a given product, et cetera.And so there's a lot of work to do to make this discovery really, really good in allowing people to use ChadGPD as an assistant to find the right product to buy.And that's where our focus lies.It's making that really great and making that really great in a way that works for our retail partners as well.Because, as I mentioned earlier, there's a huge appetite from the ecosystem to be part of the ChadGPD journey.And nailing the discovery piece has been the most promising focus area to date.Nick, on ChadGPD, you must see a breadth of information.You must see a breadth of use cases that people are doing with ChadGPD.

Nick： 购物是那种今天在 ChatGPT 里自然生长出来的用例之一，而且它是能用的：你可以就任何一笔打算做的采购问 ChatGPT，得到相当出色的建议。但它也是那种「今天在聊天里的体验不是你真正想要的完美体验」的用例。因为购物非常视觉化——你会想真的看到产品和图片、能对比，而不只是读一大堵文字墙。人们还在意来源：我在哪儿能了解更多关于某个产品的信息。所以要把这个「发现」环节做到非常非常好、让人们能把 ChatGPT 当成找到该买什么的助手，还有很多工作要做。这就是我们的重心所在：把它做好，而且是以一种对我们零售合作伙伴也行得通的方式做好。因为我前面提到，生态对参与 ChatGPT 这段旅程的胃口非常大。而把「发现」这一环做对，是迄今为止最有希望的重点方向。

Apoorv： Nick，在 ChatGPT 上你一定看到极其广的信息面、极其广的用例。

[43:11] Nick Turley

And tell us something about, you know, what does the world underestimate about ChadGPD that you have maybe been surprised by or a listener might be surprised by?There's been a real change in the way that people think of ChadGPD over the last year or so, where it's increasingly like a true thought partner to people.It's not just a thing that, you know, answers your question, but it's a thing that you can, it's a sparring partner that you can actually think things through with.And that shows up in all kinds of demands ranging from life advice, where, you know, if you've got a relationship problem, you can actually get a lot of value to ChadGPD just helping you think through how to handle it and how to talk to your partner about it.All the way to a work setting where, you know, you're working on an analysis or you're like trying to figure out how to frame something or you're, you know, trying to build something.And ChadGPD really shows up as a second brain of sorts.And I think that's qualitatively different in terms of how the mental model it occupies with people.And you see it in the usage patterns in these cases that exist.And I think the more we nail things like, you know, proactivity, which we talked about earlier in tasks, et cetera, I think the more it's going to feel like a teammate in the workplace and like a super assistant at home.

Apoorv： 跟我们讲讲：关于 ChatGPT，世界低估了什么？有什么是让你自己吃惊、或者会让听众吃惊的？

Nick： 过去一年左右，人们看待 ChatGPT 的方式有了实质变化：它越来越像一个真正的思考伙伴（thought partner）。它不只是一个回答你问题的东西，而是一个你可以拿来对练、把事情想透的陪练（sparring partner）。这体现在各种各样的需求上：从人生建议——比如你有感情问题，你真的能从 ChatGPT 那里获得很多价值，帮你想清楚该怎么处理、怎么跟伴侣沟通；一直到工作场景——你在做一份分析，或者你在琢磨怎么把某件事讲清楚，或者你在造点什么。ChatGPT 真的是以某种「第二大脑」的身份出现的。我觉得这在它所占据的心智模型上是质的不同，你在这些场景的使用模式里能看到。而我觉得，我们越是把主动性、任务这些前面聊到的东西做对，它就越会像职场里的一个队友、家里的一个超级助理。

[44:32] Nick Turley

Yeah.And I think that's going to meaningfully change the use cases that people come for.Yeah.You know, I've been, the most high stakes thing I do with ChadGPD is we have a new baby.And when the baby's crying at three in the morning, ChadGPD, you know, what's going on?

Nick： 我觉得这会实质性地改变人们来找它做的事。

Apoorv： 我用 ChatGPT 做过的最高风险的事，是我们家新添了一个宝宝。凌晨三点宝宝哭的时候，我就问 ChatGPT：这是怎么回事？

[44:51] Nick Turley

First of all, congrats.Second of all, I've heard this from all parents in my life.The ChadGPD has become indispensable as a thought partner.And it makes sense, right?If you have a really specific scenario or you think it's a specific scenario to you, ChadGPD really comes through and can, you know, help you, you know, build confidence.And I think that's such an empowering thing, right?

首先恭喜。其次，我生活里所有当爸妈的人都跟我说过这个——ChatGPT 作为思考伙伴已经不可或缺了。这也讲得通，对吧？如果你遇到一个非常具体的情境，或者你觉得这情境很独特，ChatGPT 真的能顶上，能帮你建立信心。我觉得这是件特别赋能的事。

[45:14] Nick Turley

Like, and I imagine new parents aren't always the most confident about what is the right thing to do.And if ChadGPD can make you, you know, feel like you are, you have agency and control and, you know, you know, I think that's really valuable.Yeah.It's huge.Well, thank you for making ChadGPD.It's literally getting me an extra hour of sleep every day.It took a village.But that is a great metric.You know, that should be the North Star metric is like incremental hours of sleep.That's a great one.Incremental hours of sleep, incremental hours of joy.There you go.I mean, you joke, but like we talk about this a lot.And because spiritually that is pretty close to what we hope we can do, right?

Nick： 而且我想，新手爸妈往往对「怎么做才对」没那么有把握。如果 ChatGPT 能让你觉得自己有主动权、有掌控感，我觉得那真的很有价值。

Apoorv： 太重要了。谢谢你们做出 ChatGPT，它真的让我每天多睡了一个小时。

Nick： 那是一整个村子的功劳。不过这确实是个很好的指标。

Apoorv： 北极星指标就该是「增加的睡眠小时数」。

Nick： 那是个好指标。

Apoorv： 增加的睡眠小时数、增加的快乐小时数。

Nick： 就是这样。你在开玩笑，但我们真的经常聊这个。因为从精神内核上说，那确实非常接近我们希望能做到的事，对吧？

[45:51] Nick Turley

Is help you reach whatever you consider self-actualization.Yeah.Whether or not that's sleep or joy or any other goal you might have.Yeah.Yeah, yeah, yeah.Well, thank you for, thank you to the village.We're going to switch gears and talk about the landscape.Sure.There's a lot going on on the field.And, you know, how would you frame ChadGPD's differentiation to people out there?

Nick： ……就是帮你达成你所认为的自我实现（self-actualization），不管那是睡眠、快乐，还是你可能有的任何别的目标。

Apoorv： 好，谢谢你，也谢谢那一整个村子。我们换个话题聊聊行业格局。

Nick： 好。

Apoorv： 场上事情很多。你会怎么向外界描述 ChatGPT 的差异化？

[46:18] Nick Turley

There's a lot of different products out there.Look, it's the best time in history to be a consumer of technology.It is indeed.Because you've got options.Yeah.The competition is intense.Yeah.And I think that's beautiful.And it's actually good for us, too, because if you were to pre-mortem why a company like OpenAI does not achieve its mission, it's probably focus.Because of the sheer number of opportunities that become possible when you approach AGI, right?

Apoorv： 外面有很多不同的产品。

Nick： 我觉得这是历史上做科技消费者最好的时代。

Apoorv： 确实是。

Nick： 因为你有得选。竞争非常激烈，而我觉得这很美好。这对我们其实也是好事——因为如果你给 OpenAI 这样的公司做一次事前验尸（pre-mortem，提前假设我们失败了、倒推是什么害死了我们），那么它没能完成使命的原因，最可能就是失焦。因为当你逼近 AGI 的时候，变得可能的机会实在太多了，对吧？

[46:45] Nick Turley

And having competition and options out there, I think it forces us to focus on our customers, too.Yeah.And on things that really matter.Yeah.Which aren't always the most flashy things, right?Sometimes it's latency, reliability, the quality of the user experience.Yeah.So I think it's a really good thing.Yeah.I think the biggest differentiation of Jatchabita is the team behind it because we're not static, right?

Nick： 有竞争、有选择，我觉得也会逼我们聚焦在客户身上、聚焦在真正要紧的事情上。

Apoorv： 是的。

Nick： 而那些事往往不是最花哨的：有时候就是延迟、可靠性、用户体验的质量。所以我觉得这是件很好的事。我觉得 ChatGPT 最大的差异化是它背后的团队，因为我们不是静止不动的，对吧？

[47:08] Nick Turley

Anything we build will get copied.And sometimes in ways that are high craft, sometimes in ways that are sort of checkboxes.And it's really important to us that we evolve the category and build the super system that we've always imagined.And I think the reason that I have confidence that that's possible at a speed that outpaces the dynamic of being copied is that we have an amazing team.And that we have an amazing team across research and engineering and design and all the different functions that it takes to make something amazing.And I think our unique ability has been to bring those functions together to build something that is sort of at the intersection of useful and possible right in that moment.So, you know, my best answer for you is we keep pushing forward and we hope to be expanding what people think of this product as.You know, last winter we had obviously, you know, what was called Code Red.Google had a great model.There was a lot of, you know, talk about it.Mark Benioff switching very vocally to Gemini and us delaying ads and health agents and shopping.Basically hit pause on everything, making Jatchabita better.Talk to us about that moment, both about what led to that and what was happening in that moment.

Nick： 我们造的任何东西都会被抄。有时候抄得很有手艺，有时候只是打个勾。而对我们非常重要的是：我们要把这个品类往前推，造出我们一直设想的那个超级系统。我之所以有信心这能以「快过被抄」的速度发生，是因为我们有一支了不起的团队——横跨研究、工程、设计和所有需要的职能。我觉得我们独特的能力，就是把这些职能拉到一起，造出在那个当下处在「有用」与「可能」交叉点上的东西。所以我最好的回答是：我们不断往前推，并且希望不断拓宽人们对这个产品的想象。

Apoorv： 去年冬天你们显然经历了所谓的「Code Red（红色警报）」：Google 出了个很好的模型，外面议论很多，Marc Benioff 非常高调地转投 Gemini，而你们推迟了广告、健康智能体和购物，基本上把一切都按了暂停，专心把 ChatGPT 做得更好。跟我们讲讲那个时刻——是什么导致的，当时发生了什么。

[48:31] Nick Turley

Yeah.So first off, Code Reds are a tool we use to create focus.And as you can imagine, when you're in a place like OpenAid, this is what makes us special to work here, is there are so many different things going on.It's a research lab.We are pursuing many different ideas, right?

首先，Code Red 是我们用来制造聚焦的工具。你可以想象，在 OpenAI 这样的地方——这也正是在这儿工作特别的原因——同时进行的事情太多了。它是个研究实验室，我们在追很多不同的想法，对吧？

[48:49] Nick Turley

And there's been these moments where we've wanted the company to come together to solve a problem across boundaries, you know, no matter what your project might have been.And at the end of last year, we had one of those moments where we felt like we need to show up for our users.We need to focus the things, focus on the basics, like reliability, performance, the way that talking to the model feels, making personalization really great.All these elements that our users care about.And I loved it because it was really an opportunity to work with a bunch of folks who I don't normally get to work with on making the product great.And we just exited the Code Red, which we knew we would with the launch of 5.3, which, you know, is a great model for the everyday user.It's great to talk to.And 5.4, which is a workhorse if you're trying to do real knowledge work.And, you know, undoubtedly, we're going to continue to use the tool of a Code Red whenever we want to create focus.But I'm excited because I think ChatGPT is in a great spot.Yeah, so Code Red is over now.That's correct.It's not the new normal.It's not the new normal.We want it to be a special thing, but it is a tool I suspect we will continue to use.

Nick： 而总有那么一些时刻，我们希望全公司跨越边界聚到一起解决一个问题，不管你原来的项目是什么。去年年底就是这样一个时刻：我们觉得我们得为用户站出来，得聚焦在基本功上——可靠性、性能、跟模型对话的感受、把个性化做到位，这些用户真正在意的元素。我很喜欢那段时间，因为那真的是一个机会，跟一群平时合作不到的人一起把产品做好。我们刚刚退出 Code Red，这也是我们早就知道会发生的——随着 5.3 的发布，那是个对日常用户非常好的模型，聊起来很舒服；还有 5.4，如果你要做真正的知识工作，它是一匹主力马（workhorse）。毫无疑问，只要我们想制造聚焦，我们还会继续用 Code Red 这个工具。但我很兴奋，因为我觉得 ChatGPT 现在状态很好。

Apoorv： 所以 Code Red 现在结束了。

Nick： 没错。

Apoorv： 它不是新常态。

Nick： 不是新常态。我们希望它是个特别的东西，但它确实是一个我猜我们还会继续用的工具。

[50:05] Nick Turley

That's great.That's great.And maybe tangibly, if you were to point out, how did Code Red change ChatGPT or maybe the ops or how team operates?The thing I try to get, you know, foster with the team is focus.Yeah.So we have certainly more focus than we were six months ago on, you know, the things we really want to nail.And some of those things are very behind the scenes, like latency, reliability, those kind of things.Okay.And some of those things are, like, very conservative efforts, like involving ChatGPT into the Super Assistant.And so focus is the main lasting artifact.And as you imagine, it's hard to stay focused sometimes when there's so much going on in the space.But that's the hard job.And you asked me about tradeoffs earlier.Yeah.Getting the team to focus on the things that really matter to users is certainly one of them that's always worth it.Yeah.You know, in the back of my mind that I asked you that question is all the other founders that are in the arena right now.And just a reminder that, hey, Code Red is a tool for you.So wartime at Palantra, as we used to call it, is a tool.Yeah.I think, you know, every company does it differently in terms of how you get stuff done.But I think it's really valuable to have terminology that, you know, means something.

Apoorv： 很好。具体一点说，如果让你指出来，Code Red 怎么改变了 ChatGPT，或者改变了运作方式、团队的工作方式？

Nick： 我努力在团队里培养的东西是聚焦。所以我们现在比六个月前，在「真正想做成的事情」上聚焦得多。其中有些事非常幕后，比如延迟、可靠性这类；有些则是很有分量的努力，比如把 ChatGPT 演进成超级助理。所以聚焦是留下来的主要产物。你可以想象，在这个领域这么热闹的时候，保持聚焦有时候很难——但那正是这份工作难的地方。你刚问我取舍：让团队聚焦在对用户真正要紧的事情上，绝对是其中之一，而且永远值得。

Apoorv： 我问你这个问题时，脑子里想的是所有此刻还在竞技场里的创始人，想提醒他们一句：嘿，Code Red 是你们也可以用的工具。就像我们以前在 Palantir 说的「战时状态」，那是一个工具。

Nick： 我觉得每家公司把事情做成的方式都不一样，但我觉得有一套「真的有含义」的术语非常有价值。

[51:22] Nick Turley

Yeah.That, you know, signals to people it's okay to drop your other stuff.And it's okay to, you know, focus on this thing together, even if that wasn't your original job.Yeah.So I think it works really well at a place like OpenAI.But I imagine startups would have an equivalent.Yeah.You know, one of the things that caught everybody's imagination on our team was what Peter was doing at OpenClaw.Mm-hmm.Incredibly potent to put all the tools together.Obviously, Peter is a great builder.Congrats on bringing on Peter to the team.Tell us a little bit about what Peter is working on.And when might the billions on ChatGPT have something to see there?

Nick： 因为它向大家发出信号：可以放下你手上其他的事，可以大家一起聚焦在这件事上，哪怕这本来不是你的活儿。所以我觉得它在 OpenAI 这样的地方效果很好，但我想创业公司也会有等价的做法。

Apoorv： 我们团队里所有人都被 Peter 在 OpenClaw 上做的事抓住了想象力——把所有工具拼到一起，威力太大了。显然 Peter 是个很棒的建造者。恭喜你们把 Peter 招进来。跟我们讲讲 Peter 在做什么，以及 ChatGPT 上的数十亿用户什么时候能看到点东西？

[51:59] Nick Turley

Well, first of all, I'm very excited for Peter to be here.I was excited to have another German speaker in the house.Oh, I'm a true person.Yeah.He's Austrian.I'm German.So we're exchanging guten Morgens.But the OpenClaw is so inspiring because it brought to life in many ways a vision that we'd had in different forms, admittedly, around this kind of AI that is fully embodied, that exists across different UIs, that can do stuff for you, that has state, that has an interaction pattern that feels a little bit more like talking to a human.Because OpenClaw allows you to interact in a very, very natural way where you can send many texts back and forth, and it's very curt.So there's a lot of elements of OpenClaw that I think were very clarifying to folks across the industry.But the best, you know, I'm super excited to just learn from Peter and bring it into the company and figure out what we can do together.So there's a lot more to come.All right.So now on to the most fun section.Rapid Fire.All right.You ready?

Nick： 首先，我非常高兴 Peter 来了。我很高兴家里又多了一个说德语的人。

Apoorv： 哦，同乡啊。

Nick： 他是奥地利人，我是德国人，所以我们互道 guten Morgen（早上好）。OpenClaw 特别有启发，因为它在很多方面把一个我们以不同形式设想过的愿景带到了现实：那种完全「具身化」的 AI，存在于不同的界面之中，能替你做事，有状态（state），交互模式更像在跟一个人说话。因为 OpenClaw 让你能用非常非常自然的方式互动，你可以来回发很多条短消息，而且它回得很简短。所以 OpenClaw 有很多元素，我觉得对整个行业的人都很有澄清作用。但最好的是，我特别期待向 Peter 学习，把这些带进公司，看看我们能一起做出什么。所以后面还有很多。

Apoorv： 好，现在进入最好玩的环节——快问快答。准备好了吗？

[53:15] Nick Turley

Sure.We'll start with my favorite game, which is long short.Pick an idea, a startup, a business, a product that you love, you think you're very bullish on.If I was starting a company today, I'm really excited about these companies that are going into companies and getting extremely hands-on and doing effectively professional services with AI because we've saturated all the evals.And you need to get proximate to the problems.So it's those companies that I'm paying attention to.Fascinating.Fascinating.So this is, you know, this is an example.This would be like, hey, you're going and either acquiring or going inside an operating form that has scale and a humming engine.Exactly.And making that a more efficient engine.Yeah.Or just like, you know, you're doing contracts for customers that have really hard problems.And you're actually going in and committing to solving the problem.And doing outcomes.Yeah.Because, like, you know, there's a reason I think that we've made so much progress on math and coding, but not on many other domains.Because those are domains we are proximate to, we as people who work in labs.And there's all kinds of other domains that we are not as proximate to.And if you get proximate, I think you can, you know, build something transformative.

Nick： 当然。

Apoorv： 先来我最喜欢的游戏：做多/做空（long short）。挑一个你很喜欢、非常看多的想法、创业公司、生意或产品。

Nick： 如果我今天要创业，我很兴奋的是那些「深入到企业内部、极其亲力亲为、实质上是用 AI 做专业服务」的公司。因为我们已经把所有的评测（evals）都刷饱和了，你需要靠近问题本身。所以我在关注的是这类公司。

Apoorv： 太有意思了。举例来说，就是你去收购、或者进到一个已有规模、引擎已经在轰鸣的运营主体里面。

Nick： 正是。

Apoorv： 然后把那个引擎变得更高效。

Nick： 是的。或者就是给那些有真正难题的客户做外包合同，你真的进去，承诺解决问题、交付结果。因为我觉得我们在数学和编程上进展这么大、在很多别的领域却没有，是有原因的：那些是我们——我们这些在实验室工作的人——离得近的领域。还有各种各样我们离得不近的领域。而如果你能靠近，我觉得你能造出变革性的东西。

[54:30] Nick Turley

And I think this is more important now precisely because, you know, the easy problems have been solved.Yeah.The obvious problems have been solved by the models.Credit where credit is due.I think Notebook LM is awesome and differentiated and helps me learn new stuff.I think it's great.It's so good.Yeah.It's so good.I think this is the example of you can innovate and you can build something totally different.It's awesome.Yeah.Yeah, yeah.It's so good.Particularly for, I found it for some more technical learning to be a very approachable way to learn.Totally.And it's really cool.I feel like AI, an underrated capability of AI is to just transform things into a different medium.Mm-hmm.And I think that's so important for learning.We just launched these, like, dynamic math blocks, which allow you to visually understand math inside chat.Gpt.Learning is obviously a big use case for us, too.That's right.And I think just being able to transform things from text to visual, you know, soon from visual to video and, like, all these different media is amazing because people have such different ways of processing information.And some people are, like, auditory learners.Some people are visual.Some people, like, reading.

Nick： 而我觉得这件事现在更重要，恰恰因为容易的问题已经被解决了。显而易见的问题已经被模型解决了。该给的赞誉要给：我觉得 NotebookLM 很棒、很有差异化，而且真的帮我学新东西。我觉得它很好。

Apoorv： 太好用了。

Nick： 真的很好用。我觉得这就是「你可以创新、可以造出完全不同的东西」的范例，很了不起。

Apoorv： 尤其我发现，它在偏技术的学习上是一种非常好上手的学习方式。

Nick： 完全同意，而且很酷。我觉得 AI 一个被低估的能力，就是把东西转换成另一种媒介，我觉得这对学习太重要了。我们刚上线了「动态数学块」（dynamic math blocks），可以让你在 ChatGPT 里直观地理解数学。学习显然对我们也是个大用例。能把东西从文字转成视觉、很快从视觉转成视频、以及各种不同媒介之间转换，是很了不起的事，因为人们处理信息的方式差别太大了——有人是听觉型学习者，有人是视觉型，有人就喜欢阅读。

[55:39] Nick Turley

So I think that's really magical and a great, great angle to take.Yeah.Amazing.Amazing, amazing.You know, one of the things I think about a lot is education and education for kids now in school.The world's changing so fast.I'm not sure our education system is changing that fast.Yeah.What advice would you have for students who are in school now, you know, who might have to adapt faster than the system around them might adapt?

Nick： 所以我觉得这非常神奇，是个很好很好的切入角度。

Apoorv： 太棒了。我经常想的一件事是教育，是现在还在上学的孩子的教育。世界变化太快了，我不确定我们的教育系统在以那个速度变化。你会给现在还在学校里、可能必须比周围体系适应得更快的学生什么建议？

[56:11] Nick Turley

It's a really good question and something that I've thought a lot about myself.And, you know, I think the most important PERMA skill in this era is curiosity, I think, because if the machine can answer all your questions, you better have good questions.And the only way to have good questions, I think, is to pursue the things you were actually excited about from an early age and throughout your entire life.Yeah.And I reflect on this because the only reason I'm here and working on this stuff is because I thought it was neat when I got, you know, nerd-sniped in the interview process, right?

这是个很好的问题，我自己也想了很多。我觉得这个时代最重要的长青技能（perma-skill，永不过时的那种技能）是好奇心。因为如果机器能回答你所有的问题，你最好得有好问题。而我觉得，拥有好问题的唯一办法，就是从小、并且一辈子都去追那些你真正兴奋的东西。我反思过这件事：我之所以在这儿做这些事，唯一的原因就是我在面试过程中被「书呆子狙击」了，觉得这玩意儿真酷。

[56:55] Nick Turley

And it's like, this is so cool.And so no matter what you're doing, I think that's an important skill is to be curious and learn to stay curious.And I think I'm confident that if you foster that skill, you will know how to adapt to, you know, an evolving landscape of tools and AIs and jobs.So that would be my advice.Yeah.Curiosity has always been the PERMA skill.Our friend Bill Gurley wrote about it in his book, Running Down a Dream.But curiosity.You're going to have to check that out.Yeah.What is a job that gets more valuable, not less, as AI gets better, as AGI arrives?

Nick： 就是那句「这太酷了」。所以不管你在做什么，我觉得一项重要的技能就是保持好奇、学会一直好奇。我有信心，如果你养出这个技能，你就会知道怎么去适应一个不断演变的工具、AI 和岗位的格局。所以这就是我的建议。

Apoorv： 好奇心一直都是那个长青技能。我们的朋友 Bill Gurley 在他的《Running Down a Dream》里写过。

Nick： 我得去看看。

Apoorv： 有哪个职业会随着 AI 变强、AGI 到来，反而变得更值钱而不是更不值钱？

[57:37] Nick Turley

Well, I think maybe the easy answer is being an entrepreneur because it's the best time to build ever in terms of, like, being able to self-actualize your idea.Yeah.But maybe one that is maybe non-obvious is I think writing, actually, is very important.And it's not because the AI can't write.You know, AI will become amazing at writing just like any other domains.But because I think the skill of writing forces you to be very clear on what you have to say.And even though prompt engineering is obviously going to go away and has gone away to much extent, the idea of expressing what you want to a machine requires you to be a pretty good writer and a very precise writer.So I would say that that is a, you know, in any profession that involves very clear writing and therefore thinking, I think, is well set up.Yeah, 100%.Honestly, I mean, this is the whole thing about Sloth, right?

Nick： 简单的答案大概是创业者，因为从「能把你的点子自我实现出来」这个角度看，这是有史以来最好的建造时代。但也许一个不那么显然的答案是：我觉得写作其实非常重要。不是因为 AI 不会写——AI 会像在别的领域一样变得极其擅长写作——而是因为我觉得，写作这项技能会逼着你把「你到底要说什么」想得非常清楚。哪怕提示词工程（prompt engineering）显然会消失、而且很大程度上已经消失了，「把你想要什么表达给机器」这件事，仍然要求你是个相当好、而且非常精确的写作者。所以我会说，任何涉及非常清晰的写作、因而也是清晰思考的职业，处境都不错。

Apoorv： 百分之百。老实说，这就是关于「AI 垃圾内容（slop）」的整件事，对吧？

[58:41] Nick Turley

There's just so much AI.That's the other thing.I think there's going to be a permanent need for high quality, trusted, authoritative content.And tools like ChatGPT can help you discover that content.Yeah.But I think the need for amazing content is also here to stay.And final question.What has been your AGI, feel the AGI moment?

Apoorv： 外面 AI 生成的东西实在太多了。

Nick： 还有一点：我觉得对高质量、可信、权威的内容会有一种永久性的需求。而像 ChatGPT 这样的工具能帮你发现那些内容。但我觉得，对优质内容的需求同样会一直存在。

Apoorv： 最后一个问题：你的「感受到 AGI（feel the AGI）」时刻是什么？

[59:02] Nick Turley

When did you feel it?I've had so many, honestly.And it's definitely not stopped.A few weeks or so after I joined OpenAI, GPT-4 had finished training.And I remember trying it out.And it actually, it didn't impress me at all.Nor anyone else that week.Because it kind of didn't work.And it's because we hadn't figured out how to post-train it.And I think seeing it go from kind of, wait, is this really a thing?

Apoorv： 你什么时候感受到的？

Nick： 老实说我有过太多次，而且完全没有停过。我加入 OpenAI 几周之后，GPT-4 训练完了，我记得我去试了试——结果它一点都没让我惊艳，那一周谁也没被惊艳到，因为它当时基本上跑不动。原因是我们还没搞明白怎么给它做后训练（post-train）。而看着它从「等一下，这真的是个东西吗？

[59:39] Nick Turley

Or was GPT-3 kind of it?To, wow, actually this is an entire step change.With what felt to me at the time, who didn't understand much about AI at all,as like just some tweaks or some little bit of final stretch work,was profoundly humbling.Because you can realize that it might not look like we are close to really powerful, useful AI.But we probably are.And then the moment that, you know, really, you know, there was two things that GPT-4 did that felt like AGI to me.One is it could do poetry.And I didn't think it was possible for an analogy of poetry.It's just kind of fundamental, philosophically.It just didn't feel like in scope.And then the other one was it could produce code that actually worked and compiled.And then my next moment where I stared at the ceiling just in awe was when I realized GPT-4 could just simulate an entire computer terminal.Like a full computer with commands, etc.And I'm like, wait, how would this be imbued in a language model?

还是说 GPT-3 差不多就到头了？」变成「哇，这真的是一次完整的阶跃」——而在当时那个对 AI 几乎一无所知的我看来，中间发生的仿佛只是一些微调、一点收尾的活儿——这件事让我深感谦卑。因为你会意识到：表面上看我们好像离「真正强大、真正有用的 AI」还很远，但其实我们很可能已经很近了。然后有两件 GPT-4 做到的事让我觉得像 AGI。一件是它能写诗。我原本不觉得这种事是可能的，从哲学上讲那太根本了，感觉根本不在范围之内。另一件是它能写出真的能跑、能编译的代码。而下一个让我盯着天花板发呆的时刻，是我意识到 GPT-4 可以直接模拟一整个计算机终端——一台完整的电脑，能敲命令等等。我心想：等等，这怎么可能被灌进一个语言模型里？

[1:00:40] Nick Turley

And there's been so many moments since then, honestly.Like reasoning was a moment.One of the moments was when I think Mark and I were giving a demo of reasoning in front of the whole company.And this was a moment where we were still trying to kind of find use cases that were hard enough for the reasoning to, you know, make a difference.We're way past that point.We know.But at the time, you know, I think we were having to do a puzzle in front of everyone.And I think one of the moments that maybe totally feel the EGI is like we were in the middle of the demo and everyone started laughing.I was like, wait, what is funny?

从那以后还有太多这样的时刻，老实说。比如推理就是一个时刻。其中一次，是我记得 Mark（Mark Chen）和我在全公司面前演示推理。当时我们还在努力找那种「足够难、难到能让推理体现出差别」的用例——我们早就过了那个阶段了，我知道。但在当时，我们得在所有人面前做一道谜题。而我觉得其中一个「彻底感受到 AGI」的时刻是：演示演到一半，所有人突然笑了起来。我心想：等等，什么这么好笑？

[1:01:16] Nick Turley

And then I stared at the screen because we're showing this chain of thought as it was streaming out of the model.And the model swore and said, like, oh, damn it.May I have to adjust because they realized I had made a mistake in the puzzle.And the fact that it did that, but particularly the fact that it did that in a way that was entirely emergent from the, you know, RL process.Completely blew my mind and, you know, made me, you know, feel quite humble about what else these models might be able to do.So that was one of those moments.Yeah.And then most recently, watching people use codecs.Like watching people have walk around with their computer open because they don't want the task to end.Watching people who have never coded in their life make stuff and bring ideas to life.That feels like an AGI.So honestly, it's just accelerating for me and it doesn't wear off at all.And everyone has a different thing, obviously, but those are some of mine.Yeah.You know, it's 10 years ago, there was a product called Kite.I don't know if you remember.It was for software engineers.It was like an AI coding product.Mm-hmm.That's when I felt the hunger for personal AI.And nothing happened for 10 years and then everything happened in the last 10 months.

Nick： 然后我盯着屏幕看——因为我们把模型流式输出的**思维链（chain of thought）展示了出来。模型骂了一句，说「哦，该死」，因为它意识到自己在那道谜题上犯了个错，得调整。它做出了这个行为，而尤其是它做出这个行为的方式是完全从强化学习（RL）过程中自发涌现（emergent）**出来的——这彻底把我震住了，也让我对这些模型还可能做到什么感到相当谦卑。所以那是其中一个时刻。还有最近，看着人们用 Codex——看着人们抱着开着的电脑走来走去，因为他们不想让任务中断；看着这辈子从没写过代码的人做出东西、把想法变成现实。那种感觉就像 AGI。所以老实说，对我来说这只是在加速，而且完全没有褪色。每个人显然都有自己不同的那个时刻，但这些是我的一些。

Apoorv： 十年前有个产品叫 Kite，不知道你还记不记得，是给软件工程师用的、类似 AI 编程的产品。那时候我就感受到了对个人 AI 的渴望。然后十年里什么都没发生，接着在过去十个月里一切都发生了。

[1:02:33] Nick Turley

The timing thing is really hard because it's actually quite possible to predict where things will end up, I think,in terms of the kind of product and form factors you're going to have.But to know when it happens, it's really hard for me to make statements on anything between sort of eventually and in three months.Yeah.Because of all the ambiguity around, you know.Well, that's a tight enough window.You know, now in three months is a tight enough window.Three months is pretty okay.Try to stick to the three-month plan more or less.Yeah.Though, you know, my team would probably tell me we don't, but I try.But, yeah, anything in between three months and eventually is difficult.Yeah.Yeah, yeah.Well, thanks for doing it.You've got a lot going on.This was a total treat.We're so excited to see all the great products you release for us.If we can do anything to be of help, let us know.Awesome.Thanks very much.Thanks for having me.Of course, man.This was fun.Bye.As a reminder to everybody, just our opinions, not investment advice.

Nick： 时机这件事真的很难。因为我觉得「事情最终会走到哪里」其实相当可预测——就产品和形态而言。但要知道它什么时候发生，非常难。除了「终将会」和「三个月内」这两端，中间任何时间尺度我都很难下判断，因为有太多模糊性。

Apoorv： 那这窗口已经够紧了。「现在到三个月内」已经是个够紧的窗口了。

Nick： 三个月还行。我尽量守着三个月的计划，虽然我团队大概会说我们并没守住，但我尽力。不过是的，三个月到「终将会」之间的任何东西都很难说。

Apoorv： 好，谢谢你抽时间。你事情很多，这次太享受了。我们非常期待看到你们为我们发布的所有好产品。如果我们能帮上什么忙，告诉我们。

Nick： 太好了，非常感谢。谢谢你邀请我。

Apoorv： 当然，兄弟，很好玩。再见。提醒大家一句：以上只是我们的个人观点，不构成投资建议。