大卫· Shim 和拉坎娜·雷勒：Adobe 人工智能首席执行官与人工智能原生产品的产品设计副总裁，探讨如何增强创意工作，而非取代它

我们相信AI将成为一个创意伙伴。

We believe AI will be a creative partner.

因此，消除大多数创意人士不得不面对的隐性工作，无论是流程末端的制作，还是流程前端的环节，AI都应作为创意构思的伙伴，但绝不会自主完成任何任务。

So removing the hidden work that most creatives have to go through, whether it's production of work at the far end or even during the front end of the process, being an ideation partner, if you will, but never doing things autonomously.

今天，我们邀请了来自两家不同公司的两位嘉宾，他们有着共同的信念。

Today, we have two guests from two different companies who have one shared conviction.

当AI增强人类而非取代人类时，它才能发挥最佳作用。

AI serves us best when it amplifies people, not replaces them.

今天，我们有幸邀请到Adobe人工智能原生产品副总裁兼产品设计负责人Rachana Rele，以及David Shim。

Today, we're joined by Rachana Rele, VP of Product Design for AI native products at Adobe, and David Shim.

他是Read AI的联合创始人兼首席执行官。

He's the co founder and CEO of Read AI.

他们正在打造截然不同的产品，但都怀有相同的愿景：让AI消除创意工作中的繁琐事务，为真正重要的思考腾出空间。

Together, they're building very different products, but they share a vision of AI that removes the drudgery from creative work, makes room for the thinking that actually matters.

在我们的对话中，我们将深入探讨一些可能真正改变你对工作认知的理念。

In our conversation, we'll dig into some ideas that could genuinely change how you think about your work.

大卫谈到了‘智能存储’的概念，即你的知识、会议记录，甚至你的工作方式都可以被捕捉并转化为一种数字分身，即使你不在场，它也能持续工作。

David talks about a concept of storage of intelligence, the idea that your knowledge, meeting history, even your working style could be captured and made available as a kind of digital twin that keeps working even when you're not in the room.

拉坎娜分享了Adobe如何将AI视为一个协作伙伴，而不是一个一次性生成创意内容的机器，它能帮助团队突破自身的盲点。

And Rachana shares how Adobe is thinking about AI not as a one shot creative output machine, but as a collaborative partner that helps teams break out of their own blind spots.

我们还向他们提出了更棘手的问题。

We also push them on the harder questions.

当前科技行业真实存在的工作焦虑，记录工作生活带来的监控担忧，以及他们各自在这些问题上的底线。

This job anxiety that's real right now in tech, and the surveillance concerns that come with recording your work life, and where they each personally draw the line.

欢迎收听《更好的设计》，我们探索设计与技术交汇处的创造力。

This is Design Better, where we explore creativity at the intersection of design and technology.

我是亚伦·沃尔特。

I'm Aaron Walter.

我是埃利·伍利里。

And I'm Eli Woolery.

在《更好的设计》，我们的主要使命是创作有助于像你这样的人精进技艺、提升协作能力，并从他人的创意过程中获得启发的内容。

At Design Better, our primary mission is to produce work that helps people like you refine your craft, improve your collaboration skills, and get inspired by the creative process of others.

如果你喜欢我们在这里做的内容，支持我们的最好方式是在 designbetterpodcast.com/subscribe 成为高级订阅用户。

If you enjoy what we do here, the best way to support us is to become a premium subscriber at designbetterpodcast.com/subscribe.

欢迎 Rachana Rele 和 David Shim 做客 Design Better。

Rachana Rele, David Shim, welcome to Design Better.

谢谢你们邀请我们。

Thank you for having us.

所以我会在这里。

So I'll be here.

你知道，你们俩真是个有趣的组合。

You know, you're an interesting pairing.

我们把你们配对在一起，就像美酒配佳肴，因为你们两人正以不同的方式探索人工智能与未来工作场所的愿景。

We've paired you together like a fine wine and a fine meal, because both of you are working on a vision for what AI and the workplace looks like in different ways.

Rachana，你在 Adobe，刚参加完 Adobe MAX，可能还在从这场热闹的会议带来的疲惫中恢复。

Rachana, you're at Adobe, coming off of Adobe MAX and probably trying to shake off some of the fatigue of the fun conference.

David，你在 Read 公司，是联合创始人兼首席执行官。

David, you're at Read, where you're cofounder and the CEO.

我们先从你开始，大卫。

Let's start with you, David.

你对人工智能将如何改变我们的工作方式有什么愿景？

What's your vision of how AI is going to change the way that we work?

我认为在未来一两年内，我们将朝着‘智能存储’这一概念发展。

I think where we're moving towards in the next year or two is this concept of storage of intelligence.

这意味着你所做的所有工作都可以被存储起来。

And this is the idea that all the work that you do can be stored.

这种智能存储将变得极其有价值，不仅对你自己，而且从多人协作的角度来看也是如此。

And that storage of intelligence becomes incredibly valuable, not just for yourself, but from a multiplayer aspect.

所以当你思考未来的工作时，真正关键的是能够分享你的知识、团队的知识，而不是主动地去说：‘我来发给你这份报告。’

So when you think about the future of work, the ability to actually share your knowledge, to share your team's knowledge, and not do it proactively where you're going and saying, Hey, I'm going to forward you this report.

我来给你这个见解。

I'm going give you this insight.

而是让这些知识始终存在，就像你使用ChatGPT一样，你可以随时提问，比如：‘最近100次客户访谈都说了什么？’

But rather, it's there that you could start to, just like you do with Chatty Patista, to ask questions to go in and say, Hey, what were the last 100 customer interviews?

给我汇总一下他们的反馈内容。

Give me an aggregation of what their feedback was.

现在，能把这些和取消服务的人的数据对比一下吗？

Now, can you bump that up against people who canceled the service?

这样我就知道了哪些人取消了服务以及原因，从而可以深入理解实际发生了什么。

So now I know people who canceled the service and the reason why, and I can start to dive into understanding what's actually happening.

而今天要做到这一点非常罕见，因为获取所有这些信息很难。

And that's really rare to do today because it's hard to get all that information.

如果你的团队分布在东京、伦敦、西雅图和纽约，你就不知道该联系谁。

If you've got teams in Tokyo, if you've teams in London, Seattle, New York, you don't know who to reach out to.

这些数据并不容易获取，而且未来会更多地采用主动推送而非被动查询的方式。

That data isn't readily available, and it's going to be more pushed than it is going to be pulled.

它会像TikTok动态一样主动推送到你面前。

It is going to get pushed to you just like a TikTok story.

它会以某种方式推送给您，比如知道你周日喜欢加密货币，周五喜欢讨论去吃饭，然后它就会学会这些并主动把相关信息发给你。

Somehow gets pushed to you that you like cryptos on Sundays, and on Fridays, you like to talk about going to dinner, and it's just gonna learn that and send you that information.

我最兴奋的是AI扮演调解者和创意伙伴的角色。

What I'm most excited about is AI playing a role of a mediator and a creative partner.

特别是在团队环境中，如今的AI技术主要针对个人的生产力提升。

Especially in a team setting, today's AI technologies are meant for a singular person individual productivity.

我期待一个未来，AI能成为更好的团队伙伴，通过与我们共同创作、在团队协作环境中促进更佳的实践，让我们不至于陷入自身能力的局部最优，而是能真正发挥与同事协作的潜力。

I would love a future where we go towards more around AI that makes us better teammates through being a creative partner with us, through mediating better practices inside a team collaborative environment so that we don't sort of hit this local maxima, if you will, of our own capabilities, but rather tap into capabilities of people we work with.

所以，拉坎娜，在Adobe MAX上展示的一些内容，我想我们观众中的创意人士以及更广泛的群体都担心AI可能会取代他们的工作或部分工作，但Adobe似乎更关注如何扩展人的能力？

So, Rachana, at Adobe MAX, some of the things that were featured, I think there's worry amongst the creative folks in our audience and all around that AI might replace their jobs or some portion of their jobs, but it looks like the focus for Adobe is largely how do you extend people's capabilities?

如何充当一个合作伙伴？

How do you act like a partner?

你能再多谈谈这一点吗？

So maybe you could talk a little bit more about that.

是的。

Yeah.

如果你看过许多Mac的主旨演讲和我们在台上及侧厅展示的演示，就会发现我们真正想强调的是将AI作为增强技术，而非替代技术。

So if you see many of the Mac's keynotes and the demos that we did on stage and also on the side stages, it was really about using AI as a augmentative technology rather than a replacement technology.

一个例子是使用AI为Photoshop中的图层自动命名。

An example of that is using AI to auto name your layers in Photoshop.

这完全是增强，而不是自动化。

That is completely, you know, augmentation as opposed to automation.

所以，如果你看看MAX的主题以及我们发布的内容，核心其实是消除人们最厌烦的繁琐工作。

So if you look at the theme of Max and theme of what we've released, it's really around removing that drudgery that people are most excited about.

对吧？

Right?

这并不是给你一次性的创意输出。

It's not about giving you this one shot creative output.

这并不是我们的受众想要的，也不是我们正在打造的东西。

That's not what our audience wants, and that's not what we are building.

我们正在朝着一个AI将成为创意伙伴的未来努力。

We are building towards a future where we believe AI will be a creative partner.

因此，我们要消除大多数创意工作者不得不面对的隐形工作，无论是过程末端的生产任务，还是过程初期的创意构思，AI都作为合作伙伴，但从不自主行动。

So removing the hidden work that most creatives have to go through, whether it's production of work at the far end or even during the front end of the process, being an ideation partner, if you will, but never doing things autonomously.

大卫，这种减少繁琐和单调工作的理念，与里德对职场的看法有很强的重叠。

David, there's a strong overlap in that idea of reducing the drudgery and the mundane in the way that Read thinks about the workplace too.

你正在收集大量数据，我认为你甚至在工作空间中提出了数字孪生的概念。

You're gathering a lot of data, and I think you even have this idea of a digital twin in the workspace.

你们是如何解决工作中的繁琐事务的？

How are you solving for that drudgery of work?

我认为最基本的一点是，如果你参加过面对面的电话会议或会议，通常被指派做记录的人往往是房间里资历最浅的，而你根本无法参与讨论。

I think the most basic thing is if you've ever been on a call or a meeting in person, the person who's assigned to take the notes is probably the most junior person in the room, and you're not going to contribute.

你除了做记录和分发记录外，无法在会议中发挥任何作用。

You're not going to take any part in the meeting outside of just taking the notes and then distributing them.

而通常情况下，这个人并不想承担这个角色。

And what typically happens with that is that person doesn't want to do the role.

这个人也做不好这个工作。

That person doesn't do a great job.

有时候他们会遗漏某些事实等等。

Sometimes they miss certain facts, etcetera.

当涉及到会议记录时，AI已经消除了这项工作。

That job is now eliminated when it comes to meeting notes with AI.

因此，通过Read，我们会加入通话。

And so with Read, we join a call.

我们会观察一些细节，比如人们是否在点头，因为这非常有趣？

We look at things like, are people nodding their head because that's really interesting?

或者他们是否在激烈地摇头表示不同意？

Or are they shaking their head violently because they disagree?

这种测量所有信号的方法能够生成更优质的会议记录，而且没有人抱怨过。

So that kind of approach of measuring all those signals enables for better meeting notes, and no one's actually complained.

从来没有谁回来对我们说：‘你夺走了我的工作。’

No one has ever come back to us and said, You cost me my job.

我再也无法做这件事了。

I can't do this anymore.

这更像是：‘哦，这太棒了。’

It's really more like, Oh, this is great.

我不必再为这个特定任务操心了。

I don't have to worry about this specific task.

因此，这带来了巨大的价值回报。

And so that's been a great value return.

然后它开始涉及一些类似跟进的事情。

Then it starts to go into things like, Hey, following up.

通常，你会让某人跟进，比如项目经理或产品经理去联系对方，问：‘你能给我更新一下这个项目的进展吗？’

Normally, you would have someone follow-up, a project manager or a product manager follow-up with someone and say, Hey, would you be able to give me an update on this project?

这个项目现在进展如何？

What's the status on this?

现在你可以获得这些自动更新，它们在后台默默运行。

Now you can actually get those automatic updates where it's working in the background.

它知道项目进展到了什么程度。

It knows how the project has progressed.

我们有一个很好的例子，针对销售人员，最大的问题就是让他们定期更新 Salesforce 或 HubSpot。

A great example that we've got is for salespeople, the biggest problem is getting them to update Salesforce or HubSpot on a regular basis.

所以你根本不清楚有哪些交易正在进来，哪些会成交。

So you don't understand what deals are coming in, what's going to close.

情况已经糟糕到首席营收官不得不亲自介入，说：‘除非你定期更新你的Salesforce或HubSpot商机，否则你拿不到佣金。’

And it's gotten so bad that chief revenue officers will go in and say, Hey, you're not going to get paid your commission unless you update your Salesforce opportunity, your HubSpot opportunity on a regular cadence.

现在我们已经做到了：连接你的邮件、消息、Slack和Teams，这样你就能看到所有这些信息，并迅速推进工作——比如AI告诉你，这个商机应该从25%提升到50%，因为客户要求了报价。

Well, we've now gone in and said, Hey, connect your emails, connect your messages, connect your Slack, connect your Teams, and with that, you're able to actually go in and see all of that information and move things forward very quickly to go in and see, hey, AI is telling me that this opportunity should go from 25 to 50% because the person asked for a quote.

当有人签署并表示‘我们继续推进’时，它应该从50%提升到75%，现在正朝着100%前进。

It should go to 50 to 75% because someone actually signed it and said, let's move forward, and now it's moving to 100.

这一切现在都已自动化，我们大约三个月前推出了这个功能，已经有超过一亿美元的交易通过AI完成，且AI主动触发了这些状态变更。

And so that's all automated now where we launched that about three months ago, and we've already had a $100,000,000 of deals go through that AI where AI initiated the chance for the change.

我们发现，平均而言，这比人工操作快了三到四天。

And what we've learned is, on average, it's about three to four days faster than if a human did it.

但同样，它消除了一份没人想做的工作。

But again, it's eliminating a job that nobody wanted.

没人愿意去清理他们的CRM系统。

Nobody wants to clean up their CRM system.

没人愿意更新他们的CRM系统。

No one wants to update their CRM system.

我对数字孪生这个概念很好奇，当你收集了足够多关于你工作以及你所做事情的信息，还有人们即使在你缺席时也能与之互动的方式时，我认为这在某些方面会带来巨大的突破，尤其是如果你身处高管职位的话。

I'm curious about this idea of a digital twin, and when you collect enough information about your work and just the things that you're doing and how people could interact with that, even when you're absent, I see that as being like a huge unlock in some respects, especially if you're in an executive role.

高管工作的很大一部分就是不断在各个团队之间穿梭，传达愿景，说明我们正在做什么。

So much of what executive work is, is going from team to team to team to say, here's a vision, here's what we're doing.

有没有什么方法可以让AI帮助促进团队之间的这种交叉协作，以及应对那些常见的问题类型？

Are there ways where AI could help with that cross pollination between teams and the queries that are kind of common types of questions people might have?

是的。

Yeah.

在我们这边，我们正在研究数字孪生，它整合了超过20个集成系统，收集所有相关信息，以了解一个人是谁、如何回应事物、对什么感兴趣、对什么不感兴趣，同时也整合了团队的相关信息。

On our side, what we are looking at with the Digital Twin is, we've got over 20 integrations that it brings in all that information to understand who they are, how they respond to things, what they're interested, what they're not interested in, as well as bringing in the information about the team.

但它还整合了诸如日历这样的基本信息。

But it's also bringing in things like basic things like calendar.

所以如果我给某人发邮件说：嘿，我们能安排个会议吗？

So if I email somebody and say like, hey, can we schedule this meeting?

在内部，我们有一个名为AIDA的数字孪生系统。

Internally, we have this Digital Twin called AIDA.

借助AIDA，我们可以直接说：‘嘿，给这三个人安排个会议吧’，它会自动完成。

And with AIDA, we can go in and say, hey, let's schedule a meeting across these three people, and it'll just do that automatically.

我也会用它来安排外部会议。

I use that for external meetings as well.

AIDA会自动进入并无缝安排这些会议，因为它能访问我的日历，了解我什么时候最空闲、最投入。

And what AIDA does is it actually goes in and schedules those meetings seamlessly because it has access to my calendar, understands what blocks of time I'm most available, that I'm most engaged.

我会安排好这场会议。

I will schedule that meeting.

很多时候，最终用户会直接回复说：‘嘿。’

And what happens a lot times is the end user will just reply back and say like, hey.

这太棒了。

This is great.

非常感谢。

Really appreciate it.

我完全没想到你在晚上11点35分发邮件后五分钟就回复了。

Totally surprised you're replying back five minutes after I sent the email at 11:35PM.

然后我不得不插一句：嘿。

And then I have to jump in and say like, hey.

非常感谢。

Appreciate it.

顺便提一下，这是Ada。

And just as a heads up, this is Ada.

她是我的数字孪生体。

It's my Digital Twin.

她负责为我安排日程。

It's doing my scheduling.

我们现在进一步扩大了她的使用范围：当我向董事会发送投资者信件时，他们会收到一封提及她表现的信，我还会在信中加入AIDA，他们可以直接向她提问，而AIDA会自动调取答案并回复，我已经设置了自动响应。

We've actually opened it up now a little bit more to when I send my investor letters to the board, they'll get the letter that talks about her performance, but I'll also go in and include AIDA, and they could actually ask questions, and AIDA will actually pull in the answers, and I've got it set to auto respond.

因此，我们对投资者保持透明，我们会说：请随意提问。

So, we're transparent with our investors, so we're like, Go ahead.

任何你想问我的问题，你都可以点击我的知识页面，它会立即回复你。

Any question that you want to ask me, you can tap my knowledge page, and it will immediately answer back.

因此，这已经达到了让投资者更加信任的程度，他们会说：大卫没有什么隐瞒的。

So that's actually gotten to the point where it gives more trust to the investors to go and say, David's not hiding anything.

AI正在提取这些信息。

The AI is actually pulling that information in.

它能立即给出我的回答。

It's giving my answer immediately.

而且很多时候，它给出的答案比我更好，因为我并不了解各个团队正在做什么，但它们已经给了我访问它们信息的权限。

And a lot of times, it's giving a better answer than I can because I don't have context on what certain teams are working on, but they've given me access to their information.

因此，这种填补空白、成为一个更博学（不一定是更聪明）的人的能力，让我可以说：我有这些信息的访问权。

So that ability to fill in and be a more knowledgeable, not necessarily smarter, but more knowledgeable person can go in and say, I have access to this information.

让我来回答这个问题。

Let me answer this question.

我们看到的即时影响将体现在你不在办公室的时候。

And where we see the immediate impact is going to be on things like you're out of office.

如果你休假一周，突然发生紧急情况，通常你会收到通知，得接电话，这样一来你就从度假的心态中被打断，而对方也会感到愧疚。

If you're out of office for a week and there's a fire drill, normally, you would get a page and you'd have to pick up the phone, and then you get out of the mindset of being on vacation and the other person on the other side feels bad.

想象一下，如果你的数字分身可以替你应对。

Imagine if your digital twin can fill in for you.

嘿，你为什么决定这么做？

Hey, why did you decide to do this?

你什么时候提交了这个代码？

When did you check this in?

他们可以回答说：哦，这是因为这个bug。

And they can say, oh, it was because of this bug.

事情是这样的。

This happened.

现在你就能掌握完整的上下文，从而解决这个问题。

And now you've got full context that you can go solve that problem.

想象一下，你正在休产假或陪产假，不想完全脱离工作，但当你回来时，人们已经忘了你是谁，转而依赖其他人了。

Imagine you're on maternity or paternity leave where you don't want to be out of commission where all of a sudden when you come back, people have forgotten who you are, and they've gone and they rely on other people.

现在想象一下，你的数字孪生体介入并说：嘿，我建议我们这样做。

Now imagine if your digital twin steps in and says, Hey, I would recommend we do this.

这是我的设计偏好。

This is my design preference.

我认为客户会想要这样的东西。

This is what I think the customer would want.

它会在你不在的时候继续这场对话，并填补空缺。

And it continues that conversation for you, and it fills in while you're out.

我认为这就是这种延伸的意义所在——它是在增强你本身，而不是取代你。

I think that's where that extension comes in, where it's about augmenting who you are, not necessarily replacing you.

这个概念很有趣，实际上我们之前也遇到过。

This concept's interesting, it actually came up.

我们正在开展一些人工智能与设计思维工作坊，并试图为管理者开发一个。

We're doing some AI and design thinking workshops, and we're trying to develop one for managers.

在与我们的一个客户合作时，他们提出想尝试类似这种数字孪生体的东西。

And with one of our clients, it came up that they wanted to experiment with something like this Digital Twin.

现在市面上有一个叫Delphi的工具，它可以收集你线上所有的内容，基本上是你所有的文字和演讲，然后创建一个你的数字版本。

And there is a tool out there called Delphi, which can go and funnel in all the content that you have online, essentially all your writing, all your talks, and then create a sort of digital version of yourself.

我们有个朋友叫詹姆斯·巴克豪斯，他就有这样一个数字分身，它的功能相当令人印象深刻。

A friend of ours, James Buckhouse has one of these, and it's pretty impressive what it can do.

你可以随时呼叫它，并向它提问。

You can go and essentially call it up and ask it questions.

我对它有一个开放性的问题是：如果我是一名普通员工，想和我的经理沟通，但经理正在度假，人们会怎么反应？

I guess one open question I have about it is how are people gonna react to that if I'm an IC and I wanna talk to my manager, they're off on vacation?

我会不会觉得和这个数字分身交谈很自在？还是说会有某些限制？

Am I gonna be comfortable talking to this Digital Twin or are there guardrails around

是的。

it?

就像使用ChatGPT一样，就像任何自动安排会议或记录会议内容的工具一样，人们都会有一些犹豫。

Just like with ChatGPT, just like with anything that does automatic scheduling with meeting notetakers, there's gonna be a little bit of hesitation.

但当他们开始发现，比如可以问这个问题，而经理不会因为我在重复问同一个流程问题而生气——因为我之前已经问过三次了，只是忘了该怎么做。

But as they start to see, oh, can ask this question, and my manager's not gonna get annoyed because I'm asking a question about process that I've asked three other times before that that I just forgot what to do.

经理非常喜欢这一点，因为他们想：好吧，我不用因为被反复问同一个问题而感到烦躁，因为我本就想帮助他们，但他们还是不断来问。

Manager loves that because they're like, okay, I don't have to get annoyed that I'm getting asked this question because I wanna help them, but they're still asking me the same question.

AI可以填补这个空缺。

The AI can fill in.

AI实际上可以推动事情进展。

The AI can actually move things forward.

它还能减轻经理的负担，让他们不必再做这些事了。

And it also takes things off the plate of the manager where they don't have to do that anymore.

他们可以去说：嘿，如果是关于流程的简单问题，就去联系我的数字分身，必要时抄送我。

They can go in and say, Hey, if it's a basic question about process, go in and ping my Digital Twin and potentially CC me.

或者数字分身可以直接说：嘿，这是Eli提出的一个问题。

Or the Digital Twin can go in and say like, Hey, this is a question that came up from Eli.

他想对这件事多了解一些背景信息。

He wanted a little bit more context on this.

这就是我之前说的。

This is what I said.

如果你想跟进，随时可以这样做。

If you want to follow-up, feel free to do that.

所以它会成为你的延伸，我认为人们会逐渐习惯这样做，就像使用搜索一样。

So it becomes an extension of you, and I think people will get more comfortable in doing that, just like with search.

很多人会先去查阅内部维基、Atlassian、Jira、Confluence等他们用来查找信息的系统，而不是去打扰别人，因为大家通常都很体贴，会先试着自己找答案。

A lot of people will first go to their internal wiki, their internal Atlassian, Jira, Confluence, whatever that they have to search for that information rather than bother somebody Because people are generally thoughtful, and they will go in and say, Let me try to find it on my own.

但那样会花很长时间。

But that's gonna take a long time.

可能要花一两个小时，而不是直接去打扰你的老板。

Might take you an hour or two versus like, I can go in and bother my boss.

我可以很快得到答案，但我又觉得这样不太好。

I can get that answer very quickly, but I feel bad about that.

那中间的解决方案是什么？

What's the intermediary?

是人工智能。

It's the AI.

这是一个数字孪生体，它可以介入并给我提供答案。

It's the digital twin that can go in and step in and give me that answer.

拉查娜，你是如何看待这些东西和智能代理的？

Rachana, how do you think about this stuff and agents?

这是否在Adobe的关注范围内？

Is that something that is on Adobe's radar?

我们看到数字孪生体的一个应用场景，不是在个人层面，而是在团队层面，那就是在实际审阅设计时，比如要将设计发送给客户。

One place that we see for digital twins, not at a individual level, but again, at a team level to be useful, is when you are actually reviewing designs, right, from a standpoint of, you know, send this to a client.

我经常与这位客户合作。

I constantly work with this client.

这位客户有一些固定的模式。

This client has certain patterns.

所以在将新设计发送给同一客户之前，让我先看看这位客户在评论中给出的模式，以及他们通常关注的共同主题，这样我就可以在发送设计或方案之前避免重复犯错。

So before I send off my new designs to the same client, let me just go and see the patterns at this client level on the comments that they've given, this common themes that they touch upon usually so that I don't make the same mistakes before sending these designs off or the deck off to the client.

所以我认为，在团队层面，它可以作为第一道检查，虽然不是万能的，但能帮助你完成60%的工作，确保基本反馈已被纳入，同时客户也不必重复表达意见。

So I think at that level, at a team level, it can be tremendously helpful as the first check, not as end all be all, but helps you get 60% there with respect to sort of making sure the baseline feedback is incorporated and yet the client doesn't have to repeat themselves.

我们看到的第二个应用场景是在协作场景中，例如。

And then the second place we are seeing is also in cases of collaboration, for example.

如果我作为一个员工有自己特定的设计风格，而我的同事想借鉴我的风格，或者学习我通过AI生成的规范化工作流程，该怎么办呢？

What if I have a specific style as an individual working for a company, and a colleague of mine wants to call upon that style or learn from my style or learn from the codified workflows that I might have had generated through AI.

因此，我们看到了这类应用场景：比如，作为我的同事，你可以这样说，嘿。

So we see users and use cases for that sort of work where, I don't know, as you, as my colleague can say, hey.

或者直接调用Rachana的图形设计智能体。

Slash Rachana's agent on graphic design, particularly.

我相信，通过这种广义的‘数字孪生’概念来提升生产力，确实有其价值，而不只是局限于狭义的数字孪生技术。

So I do believe that there is goodness in improving productivity through this sort of general concept of twinning as opposed to specifically about digital twins.

你知道吗，Max大会上刚刚发布的一个功能特别有意思，那就是在Firefly中，你可以输入设计系统或设计风格，比如品牌指南等。

You know, there's one thing that's particularly interesting with what just was released at Max, and that's in Firefly that you can feed like a design system or design styles, like brand guidelines and so forth.

大型公司面临的一个重大挑战是，有太多不同的人在为各种平台、不同渠道制作内容。

And one of the big challenges in larger companies is you've got so many different people who are making so many different things for different platforms, different channels.

而他们不可避免地会偏离品牌指南。

And inevitably, they go astray from brand guidelines.

我亲自见过这种情况，简直一团糟。

And I've seen this firsthand, it's a mess.

然后你不得不去和人进行一些尴尬的对话，说：嘿，你不能这么做。

And then you have to go have uncomfortable conversations with people and say like, hey, you can't do that.

马上停下来，我们来修正这个问题，因为你代表公司的形象出现了偏差。

Pull that right now, and let's go fix that because you're representing our company the wrong way.

你能稍微谈谈 Firefly 在这方面做了些什么吗？

Could you just talk to us a little bit about what Firefly is doing in in that respect?

是的。

Yeah.

我们发布了一项名为自定义模型的功能，这个功能在市场上已经有一年半左右了。

So we released something called the custom models, which has been in the market for, I would say, over a year and a half.

它的作用是，你可以使用 Firefly 训练一个模型，针对你特定的设计、风格和构图，然后在企业内部发布，供其他人基于该模型创建新的设计。

What it is is you can train a model using Firefly on your specific designs, your specific style, your specific composition, and use that, release that within your enterprise for other people to sort of build upon and generate net new designs based on that specific model.

因此，未来你可以想象这样一种场景：我在创作新设计时，可以直接调用来自同事的模型，比如来自市场团队或某个特定活动的模型——从这个角度看，你可以拥有多个自定义构建的模型。

So going forward, you can imagine a world where I actually invoke a model while I'm creating new designs from a colleague from, let's say, marketing studio team or on a specific campaign for that matter that you could have multiple custom built models from that standpoint.

这就是我们在 Firefly 上为自定义模型所做的工作。

So that's how we are doing it for custom models on Firefly.

我们发布的另一项服务是非常定制化的，我们称之为 Foundry，即 Firefly Foundry。

And then the other thing that we released is very bespoke kind of services we are calling Foundry, Firefly Foundry.

它的作用是为那些希望基于自身知识产权构建专属自定义模型的大型公司提供支持。

And what it is is for large companies who want to have bespoke custom models built on their own IP.

因此，这专门面向希望使用自身知识产权训练模型的大型品牌。

And so that's specifically for large brands who want models trained on their own IP.

大卫，我一直在用 Read 做很多显而易见的事情，比如记笔记。

David, I've been using Read a lot for obvious things like note taking.

我发现它另外特别有用的地方是，我和亚伦有很多对话，不只是像这样的播客对话，还包括与赞助商的交流。

The other things that I found that's really helpful with is, you know, Aaron and have a lot of conversations, not just podcast conversations like this, but with sponsors.

即使你的笔记做得很好，时间久了也可能忘记某次对话发生的具体场合。

And over time, even if you have pretty good notes, you might lose track of where a conversation took place even.

所以其中一个有趣的功能是，它能帮你稍微理清思路，让你在想起‘我记得有人说过这件事’时，能快速找回当时的情境和出处。

And so that's one of the interesting things is that it can kinda help you kinda like organize your brain a bit and help you get context on things where you're like, I remember somebody said this thing about this thing, but I don't remember when or where that conversation took place.

所以我认为，所有这些对话都在 Read 上进行，这带来了一个有趣的效果。

So I think that's kind of an interesting effect of having all of these conversations on Read.

完全正确。

A 100%.

这种完整的记忆功能就在于，当你被某件事触发时，它能唤起你的联想。

And that full memory is the thing where it's like you've got something that triggered something in your brain.

我做过几次这样的事：比如，几周前我们聊过关于优化某件事的什么内容来着？

I've done this a couple of times where it's like, what's the thing that we talked about a couple weeks ago that was about, you know, optimizing something and something?

然后它就会弹出来说：嘿。

And then it would go in and say, hey.

那这四件事呢？

What about these four things?

哦，这太棒了。

And it's like, oh, this is great.

我马上就想起来我们在说什么了。

I know exactly what we're talking about.

我们关注的是主动推送其中一些内容。

Where we're focusing in on is around proactively pushing some of those things out.

所以，如果你现在有会议，而这些是出现的五个关键问题，我们让你能够搜索这些问题的答案，但我们希望主动把这些内容推送给相关人员。

So now if you do have a meeting and these are the five key questions that come up, we enable you to search for those answers, but we want to proactively push those to people.

在人工智能时代，我们真正看到的是搜索——就像你使用ChatGPT时，你让它帮你构建某物，或查找某物，然后缩小范围，说：‘我喜欢这个结果，但你能这样调整一下吗？’

That's what we've really seen in this age of AI is search is kind of where we're at today, where you think about ChatGPT, where you ask it to build something, where you ask it to find something, narrow it down to go in and say like, Hey, I like that result, but can you adjust it this way?

我认为你将很快看到一种向推送模式的快速转变，这种模式更像TikTok加Tinder，它会主动说：‘我注意到你在做什么。’

I think what you're going to see is a very quick evolution into more of a push system where it's more TikTok meets Tinder, where it's going to go in and say, Hey, I see what you're doing.

你不需要做任何提示。

You don't have to prompt anything.

我会向你推送我们认为相关的内容，无论是不同项目的更新，还是我们认为你应该采取的行动，而你只需左右滑动来触发这些操作。

I'm going to deliver content to you that we think is relevant, either updates on different projects or actions that we think you should take, and you're going to go swipe right or swipe left to actually trigger that action.

然后你可能会做一些编辑，但接着你会去执行它。

And then you're going to go in and maybe do a couple of edits, but then you're going to activate against it.

我认为这种交互方式将很快出现。

And I think that type of motion is what we will see very shortly.

而这正是消费者今天已经在做的事情。

And it's kind of the motion that consumers are already doing today.

如果你看一下内容消费方式，现在主要是通过抖音和Instagram短视频进行的。

If you look at consumption of content, it is through things like TikTok and Instagram Reels now.

不再是从搜索中找到某样东西，然后阅读一篇相关的文章。

It is no longer through doing search, finding something, and then reading an article about it.

更像的是，我希望内容能主动推送到我面前。

It's more like, Hey, I want the content served to me.

我想了解正在发生什么。

I want to figure out what's going on.

这种模式如何转移到工作场景中会很有趣，但我认为这就是我们未来的方向。

And it is going to be interesting on how that switches to work, but I think that's where we're going to go.

这一切的最终结果是什么？

What's the net of all of this?

我们可以做很多事情来提升生产力。

So there's tons of things that we can do to improve productivity.

事实上，自工业时代之初，我们就一直在努力提高生产力，增强我们的能力。

In fact, it's something we've been doing since the beginning of the industrial era, is we wanna try to be more productive, improve our capabilities.

但当你思考你们两人所描述的近期未来可能性，并将这种趋势延伸到五到十年的远期——在人工智能时代，这已经是很长的时间了。

But when you think about what's possible in this near term future that you're both describing, and then we push that out to maybe like five to ten years, a farther term, which is a long time in an AI age.

那么公司会是什么样子？

What does a company look like?

当所有这些工具，以及一些你们今天可能无法与我们分享的愿景成为现实时，公司会有什么不同？

How is it different when all of these tools and some of the visions of what maybe you can't share with us today, what does a company look like?

它会有什么不同？

How is it different?

在我们看来，智能的存储将是带来变革的关键。

On our side, we think that storage of intelligence is what's going to make it different.

它将像设计、组织知识、团队经验一样，成为你的长期知识产权。

It becomes your long term IP in the same way that design was an IP, that institutional knowledge, tribal knowledge, whatever you want call it.

所有这些正是今天公司价值的来源。

All of that is what values the company today.

存储这种智能将变得更加有价值，我认为你会开始看到公司和财报开始说：嘿，我们正在以这种方式存储智能。

The storage of that intelligence is what's going to be more valuable, and I think you're going to start to see companies and earnings reports start to say, Hey, we're storing the intelligence this way.

这是我们如何利用它的方法。

This is how we're activating against it.

事实上，我们不会取代这些岗位，因为我们知道现在已经建立了一套流程。

This is where, honestly, Hey, we're not going to replace these jobs because we know we've got a process that's now in place.

所以我认为这将是一次转变。

And so I think that is going to be a shift.

而且我认为这并不是十年后的事。

And I don't think it's ten years from now.

我认为只需要四五年，甚至更短的时间，就能看到这种智能存储如何提升特定实体的价值。

I think it's going to be four or five or even less than that to go in and see that shift of storage of intelligence valuing that specific entity.

我觉得一个很好的类比是，我有一位朋友是全球最大的对冲基金之一的早期员工，他曾经说：嘿，在AI出现之前，我们就已经有AI了，那时的模型在主导一切。

In the same way where I think the great comparable that I've had is like one of my friends who is a early employee at one of the largest hedge funds in the world, he went in and said, Hey, we had AI before AI existed, where the models were running things.

它们告诉我们该做什么、不该做什么，并处理所有这些信息。

They were telling us, Do this, do that, and processing all this information.

但始终有一个中间的人，综合所有可用的知识、模型和学习成果，来决定究竟是否进行这笔交易。

But there was always a human in the middle that took all that knowledge that was available, all the models, all the learnings, etcetera, that still decided on what to do to say, Do I make this trade or do I not make this trade?

因此，这个角色仍然会存在。

So that role will still exist.

你不会让人工智能完全自由运行。

You're not going to let the AI totally run free.

我认为，总会有一个协调层存在。

There will always be kind of an orchestration layer, is my guess.

但与此同时，你不需要50个人来完成这个协调工作。

But at the same time, you don't need 50 people to do that orchestration layer.

它被简化为只需要一个人。

It simplifies it down to one.

就像在面向更多消费者和更多设计时，我会说，嘿。

In the same way where for more consumers and more design, I would go in and say, hey.

还记得MapQuest刚推出的时候吗？

Remember when MapQuest first came out?

希望观众都知道MapQuest是什么，以前开车时，你会用纸质地图规划路线。

Hopefully, audience knows what MapQuest is, but that was where it's like, you used to have maps when you drove, you'd have physical maps that you map out where you're gonna go.

后来你用MapQuest，打印出来或者手抄下来。

Then you went to MapQuest, you printed it out, or you wrote it out.

现在我们的手机里就有了电脑，可以直接输入目的地，系统就会告诉你正确的方向。

Now we've got computers on our phones right here where we're able to go in and say, this is the right direction.

尽管我明明知道不对，它还是让我右转，而我竟然真的穿越了九条车道，只为在30英尺外完成那个右转，然后在那儿停60秒。

And against all my better knowledge, it's gonna tell me to go right and I will cross nine lanes of a freeway to go in and make that right turn that's 30 feet away so I can say for sixty seconds.

这就是AI，这就是机器学习——你的智能手机正在告诉你如何操控一辆两吨重的汽车，穿越多条高速公路车道，面对生死攸关的场景，而你却乖乖听从。

That's AI, that's machine learning, that's going in and saying like, this smartphone is telling you how to move a two ton car across multiple lanes of freeway with life and death scenario, and you're listening to it.

但没人会对这件事产生疑虑，因为我们已经深深习惯了这种与技术互动的方式。

But no one has second thoughts about that because we've now become ingrained in this is how we interact with this technology.

我认为企业级AI也会发生同样的事情。

I think it's the same thing that's going to happen with AI on the enterprise level.

而拉奇纳提到的一点很有趣，那就是系统会提供模型，让你输入自己的信息、公司数据，但我认为会出现一种分化。

And the one thing that will be interesting that, you know, Rachana, you talked a little bit about was like, it's going in and giving you the models where you can feed in your information, your corporate information, but I think there is going be a split.

我认为再过一两年，就会有人表示：我想带着自己的模型和训练数据去下一家公司。

I think in about a year or two, you're going have people that say, I want to take my own model, my own training data to the next company I go to.

如果我是个设计师，我有自己的某些元素和风格。

If I'm a designer, I have certain elements, certain style.

是的，我为公司贡献了这些，这些属于公司广义上的知识产权。

Yes, I've contributed that to the company and that's company IP for the broad work that I've done.

但当我去下一家公司时，我希望这些信息能跟着我，不是那些机密知识产权，而是我的工作方式，这样我就能加载之前提到的创意元素。

But if I go to the next organization, I want that information to follow me, not the secret IP, but the way that I work because then I can go in and load up the creative elements that we talked about.

然后我可以对新公司说：

And I can go and say, this is the new company.

这些是我的创意元素。

These are the creative elements.

这是风格指南。

This is style guide.

这是我喜欢的工作方式。

This is how I like to work.

这就是我的设计方式。

This is how I design.

现在当我把这些东西结合起来时，上手时间从三到六个月缩短到了三到四个小时，因为所有数据都已经就位了。

And now when I combine those things together there, the ramp up time goes from, like, three to six months to three to four hours where all that data is there.

是的。

Yeah.

我同意你的观点，大卫。

I agree with you, David.

我认为现在人们在出售股票。

I think people today are selling stock.

股票市场已经非常普遍了。

Stock marketplaces were such a commonplace.

我认为在未来，非常近的未来，人们将会出售自己的智能代理。

I think in the future, very near future, actually, people will sell their own agents.

我相信，他们工作流程的数字化将成为他们独有的知识产权，并能在市场上出售。

It's the codification of their workflows that will become their own unique IP that they will be able to sell on marketplaces, I believe.

但如果我们从远景的视角来看待智能代理，可以说我们当前所处的远景是代理为我们调用工具的阶段。

But thinking about agents through the lens of horizons, you can say that the horizon that we are in right now is the horizon where agents summon tools to us.

我们很快将在一两年内看到的远景是代理为我们调用成果的阶段。

The horizon we'll see very quickly in a year or two is where agents summon outcomes.

再进一步推演一下。

And then push that a little bit further.

未来将是代理调用目标导向系统的阶段——作为员工，你只需说明你的目标是优化某个级别的ARR或营销活动成果，系统就会自动为你完成这些工作。

It will be about agents summoning goal oriented systems where you just, as an employee, you say what your goal is is to optimize for this level of ARR or campaign outcomes and the systems go and do that work for you.

当然，你仍会处于这个过程的核心，但未来的一切都将高度以目标为导向。

And of course, you'll be in the middle of it, but it's very much goal oriented in the future.

因此，我相信这就是我们前进的方向，而设计师将在其中扮演非常重要的角色。

So I believe that's where we are going and designers will have a very, very strong role to play in that.

所以，你知道，许多岗位正在被压缩，这在新闻中屡见不鲜，许多科技公司正在大规模裁员，设计师或其他科技岗位的人们都对自己的未来感到担忧。

So, that, you know, a lot of roles are compressing and it's obviously in the news, a lot of those tech companies are laying off a lot of people and a lot of folks are just concerned about their future if they're a designer or any other role in tech.

但或许存在另一种愿景，我想知道你们每个人如何看待岗位的变化，以及人们该如何调整自己，以在科技领域或当前从事的任何科技相关工作中保持竞争力。

But perhaps there's a different vision, and I'm curious what each of you think about how roles are changing and how people might position themselves to remain relevant in tech or in whatever tech related job that they're in currently.

在我看来，人们对于AI这种新技术的抵触情绪比以往少了很多。

I would say on my side, you're seeing less of the pushback that you normally see for new technologies when it comes to AI.

我认为实际的采用率已经相当高了。

I think the adoption's actually been pretty high.

我们一半的用户实际上来自新兴市场，这一点在我们公司三年前、四年前刚成立时是完全没有预料到的。

Half of our users are actually in emerging markets, and that's unexpected when we initially started the company three years ago, four years ago.

现在，我们在南美洲已经成为使用人数第一的会议记录工具。

Now we're seeing markets like we're the number one meeting notetaker in South America.

这原本并不是我们的规划重点，但因为产品带来了显著回报，采用率却出乎意料地高。

That wasn't necessarily part of our roadmap, but the adoption rate was so high because it was delivering returns.

归根结底，它带来了切实的成果，而且完全不需要用户编写任何代码。

It was delivering outcomes at the end of the day, and it was doing it in a way that didn't require you to program anything.

也不需要你去学习新的语言或新的设计软件。

It didn't require you to learn a new language and new design software.

它开箱即用，直接就能工作。

It just works right off the shelf.

因此，从采用角度来看，这一点确实非常有趣。

And so that's really been kind of interesting from an adoption perspective that we saw.

我认为趋势是向前发展的。

I think it's leaning forward.

别太担心你的知识产权。

I think Don't worry about your IP so much.

别太担心你的知识。

Don't worry about your knowledge.

去采用这项技术吧，就像当初人们担心谷歌会索引你的内容一样。

Go in and adopt the technology first in the same way where people used to be freaked out that Google was indexing your content.

现在人们却因为谷歌没有索引内容而起诉它。

Now people are suing Google because they're not indexing the content.

他们没有让内容变得可被发现。

They're not making that discoverable.

因此，如果说因为想保护知识产权就不参与这场人工智能的下一波演进，我认为这种想法是合理的。

And so to go in and say, I'm not gonna participate in this next evolution, this new age of AI because I wanna protect my IP, I think it's a reasonable thing to have in mind.

但你所冒的风险是，知识产权现在甚至更像一种商品，股票是商品，石油是商品，人工智能也是商品，但你必须能够参与这个市场。

But what you're risking is the fact that IP is now even more of a commodity, and stocks are a commodity, oil is a commodity, AI is a commodity, but you have to be able to participate in that marketplace.

如果你选择忽视这一点，我认为你会被边缘化，就像有人会说：‘我不会在AI方面使用编码辅助工具，因为它们还不够好。’

And if you choose to ignore that, I think you're gonna get passed over in the same way that if someone went in and said, Hey, I'm not gonna use coding assistance when it comes to AI because they're not as good.

三年前、两年前、一年前，这完全正确。

Totally true three years ago, two years ago, a year ago.

但今天，你现在看到资深工程师的效率提升了20%到30%。我曾与一家财富500强公司的首席信息官交谈，他们表示：‘我们实际上在放缓招聘，因为我们不需要那么多应届毕业生了，因为我们的资深工程师通过使用这种每月可能只需500美元、并附加编码功能的工具，获得了更高的投资回报。’

But today, now, you're seeing senior engineers get amplified by 20% or 30% where I've talked with a Fortune 500 company CIO, and they went in and said, Hey, we're actually slowing down hiring because we don't need as many college students coming in because our senior engineers are actually getting better ROI by using this tool that costs maybe $500 a month with additional coding elements.

我认为保持相关性的方法是真实的，我们每天都能看到这种焦虑，那就是去实验、保持好奇心。

I believe the way to stay relevant and the anxiety is real, we see it every day, it's to experiment and stay curious.

对吧？

Right?

比如，我们甚至在自己的设计团队中也在推行这一点，就是推动AI工具的采用，让你了解这些工具的局限在哪里，以及作为设计师、研究员或内容撰写者，你如何能发挥独特且更具战略性的角色。

Like, that is one thing that we are instituting even within our own design teams is just to get the adoption of AI tools going just so that you understand where the limits are and where you as a designer or a researcher or a content writer can play a unique and more strategic role.

这正是我一直在向各方人士强调的基本观点。

That is the baseline aspect that I've been saying to people all across.

只要了解市场正在发生什么，而且它正在非常、非常快速地演变，非常灵活。

Just know what is happening in the market, and and it's evolving very, very fast, very fluidly.

因此，跟上这一点需要极大的自律，去找到时间，进行这些实验性原型开发，或者尝试不同的提示词等等。

So staying on top of that just takes a lot of discipline of finding that time and doing these experimental prototypes or playing around with prompts or what have you.

让我对科技行业感到沮丧的一点是，我们看待未来时总是戴着玫瑰色眼镜，这既是我们的超能力，也是我们的致命弱点。

So one thing that frustrates me about the tech industry is that it's our superpower and our kryptonite that we see the future with rose colored glasses.

我们只看到可能发生的好事，而过去正是这种心态让我们陷入困境，比如2010年、2011年时，我们认为社交媒体将民主化一切。

We see the positive things that can happen, and that's gotten us into trouble in the past, thinking about 2010, 2011, social media, it's gonna democratize everything.

它会让我们的世界变得美好。

It's gonna make our world wonderful.

其中一些确实实现了，但更多我们未曾预料到、或选择忽视的负面影响却接踵而至。

And some of that came to pass, but far more came to pass that was negative that we did not anticipate or we chose not to consider.

当你在开发提升工作效率、促进协作、增强记忆持久性的工具时，底线在哪里？

As you develop tools for the workplace to make us more productive, and help us collaborate better, and help our memories be more persistent, where are the red lines?

我们不会跨越这条线。

We will not cross this.

这会导致我们不希望看到的反乌托邦未来。

This leads to the dystopian future we don't want.

我认为这里最大的问题和机遇在于AI如何进行递归学习。

I think the biggest problem and an opportunity here is how recursively AI learns.

那么，你如何将人类置于决策的核心？

And so how do you put human at the center of making decisions?

因此，对我们而言，这真正关乎合作，而非自动化。

And that's why for us, it is really about partnership as opposed to automation.

你们在设计这些系统时使用了哪些指导原则和设计原则？

What are the guiding principles and design principles you're using to design these systems?

你们是

Are you

负责任地设计吗？你们是否在为以人类为中心的业务建立信任？

designing responsibly, and are you building trust with human beings who are at the center of your business?

是的。

Yeah.

我认为其中之一是让人们意识到它正在被使用。

I think one is awareness that it's being used.

所以，如果你要部署AI来介入并说：我们要上线它，但我们不会告诉员工。

So if you're gonna roll out AI to go in and say, We're going to roll it out, but we're not going to tell the employees.

我们不会获得他们的同意。

We're not going to give them consent.

我们不会给他们选择启用它的权利。

We're not going to give them the choice to enable it.

这是错误的做法，我认为这是一条红线：当我们加入通话时，我们会通过录音通知告知所有人。

That's the wrong approach, and I think that's a red line that we live in where when we join a call, we go in and we notify people with a recording notification.

我们会把‘Read AI正在评估此次通话’的信息发到聊天中。

We go in and put it in the chat that Read AI is measuring the call.

当我们说：你是否希望退出？

When we go in and we say, Do you want to opt out?

你可以直接输入并选择退出，我们会离开会议并删除所有数据。

You can actually type and opt out, and we'll leave the meeting and delete all the data.