The Current State of Consumer AI
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A16Z播客，由埃琳娜·伯杰主持，并邀请了奥利维亚·摩尔和乔什·埃尔曼，深入探讨了他们《消费者AI应用百强报告》的第七版，重点关注个人AI代理、消费者支出和新兴趋势的演变格局。
奥利维亚·摩尔强调了几个关键要点：尽管AI产品的流量显示出一定程度的稳定（在网页和移动端综合榜单上仅有11款新产品），但收入数据引入了重要的新变量。在按消费者支出排名的50款产品中，有29款未出现在任何流量榜单上，这表明这是一个“超级用户游戏”，即一小部分用户群体带来了可观的收入。大约一半的美国人表示使用AI，但只有约4.5%的美国消费者为AI订阅付费。这种支出高度集中：前1%的用户每月个人在AI上花费903美元，而中位数是25美元。这些高消费者主要使用开发者工具、生产力工具和创意工具进行构建、创作和销售，这体现了“创作者”的心态。
讨论转向了最有趣的新趋势：个人代理，它们正在将消息应用转变为更具对话性的体验。小组成员指出，AI已从一种生产力工具转变为一个“完成任务”的助手。像OpenClaw这样的早期先行者（尽管其流量后来有所下降）启发了这一转变。近期的消费者助手，如Muse和Instinct，正迅速增长，尽管它们尚未触及科技社区以外的主流用户。Muse在发布后的前12天内获得了50万次下载和25万活跃用户，这令人印象深刻，但与Threads等现象级应用相比，其普及度仍较低。
个人代理面临的一个重大挑战是隐私和信任。代理越有用，它对用户的了解就越深入，这在分享个人信息方面造成了紧张关系。主持人讨论了是平台能力还是消费者意愿会更快解决这一问题，他们总结认为技术进步的速度超过了用户的舒适度。服务代理用户的高成本（对于超级用户来说，每月数百或数千美元）是另一个障碍，特别是当大多数用户仍在使用代理进行编码等技术任务，而非日常琐事时。
随后，对话探讨了商业模式，指出当前消费者AI的收入主要基于订阅（网络榜单产品中占85%），这与大多数成功的消费互联网公司采用的广告驱动或交易费模式相比，是一种“不自然的颠倒”。OpenAI报告的广告年化收入达到10亿美元被强调为一个重要进展，这表明了广告在AI领域的潜力，特别是在用户密度大以及由于对用户深入了解而具备卓越的定向能力的情况下。小组成员强调，为了让AI实现大规模普及，随着推理成本的降低，商业模式必须超越订阅模式实现多元化。
对比主要的实验室，ChatGPT在使用量和收入方面都保持主导地位。在美国，Claude在付费订阅用户数量上已经超越了Gemini，这对Anthropic来说是一个显著的成就，尤其值得注意的是，其7.5%的订阅用户使用的是每月100美元以上的套餐（相比之下，ChatGPT和Gemini的这一比例为1%）。
创意工具也呈现出有趣的模式。尽管OpenAI等实验室在图像生成方面表现出色，但像Eleven Labs和Suno这样的专业音频工具通过专注于实验室因复杂性或知识产权问题而未优先考虑的利基领域，取得了成功。在视频领域，中国公司因数据访问权限而具有优势。小组成员强调，“软件层”——定制的用户界面和产品体验——正日益成为价值所在，而不仅仅是底层模型。
展望未来，除了生产力工具和搜索替代品之外，AI创新仍存在巨大的“空白领域”。约会、招聘、社交AI、游戏、娱乐、购物和购房等类别都已成熟，等待颠覆。这些通常需要“多人”或“消磨时间”的产品，与许多当前AI工具“节省时间”的导向形成对比。人们相信，随着模型的改进和产品体验的完善，下一波AI公司将通过在丰富的、社区驱动的软件层中利用模型来涌现，为人们提供引人入胜的参与和创造新方式。
The A16Z podcast, hosted by Elena Berger and featuring Olivia Moore and Josh Ellman, delves into the seventh edition of their Top 100 Consumer AI Apps Report, focusing on the evolving landscape of personal AI agents, consumer spending, and emerging trends.
Olivia Moore highlights key takeaways: while traffic to AI products shows some stabilization (with only 11 new products on the combined web and mobile lists), revenue data introduces significant new variables. Of the 50 products ranked by consumer spend, 29 were not on any traffic list, indicating a "power user game" where a small segment drives substantial revenue. About half of Americans report using AI, but only around 4.5% of U.S. consumers pay for an AI subscription. This spending is highly concentrated: the top 1% of users spend $903 per month personally on AI, while the median is $25. These top spenders primarily use developer tools, productivity tools, and creative tools for building, making, and selling, demonstrating a "maker" mindset.
The discussion pivots to the most interesting new trend: personal agents, which are transforming messaging apps into more conversational experiences. The panelists note that AI has shifted from being a productivity tool to an assistant that "gets things done." Early pioneers like OpenClaw (though its traffic has since declined) inspired this shift. Recent consumer assistants like Muse and Instinct are seeing rapid growth, though they haven't yet reached mainstream users outside the tech community. Muse saw 500,000 downloads and 250,000 active users in its first 12 days, impressive but still less widespread than a phenomenon like Threads.
A significant challenge for personal agents is privacy and trust. The more useful an agent becomes, the more intimately it knows the user, creating a tension about sharing personal information. The hosts debate whether platform capabilities or consumer willingness will resolve this sooner, concluding that technological advancements outpace user comfort. The high cost of serving agent users (hundreds or thousands of dollars per month for power users) is another hurdle, especially when most users are still using agents for technical tasks like coding, not everyday errands.
The conversation then explores business models, noting that current consumer AI revenue is largely subscription-based (85% of web list products), which is "an unnatural inversion" compared to the ad-driven or transaction-fee models of most successful consumer internet companies. OpenAI's reported $1 billion annual run rate from advertising is highlighted as a significant development, demonstrating the potential for ads in AI, especially with large user density and superior targeting capabilities due to intimate user knowledge. The panelists stress that for AI to reach mass adoption, business models must diversify beyond subscriptions as inference costs decrease.
Comparing the major labs, ChatGPT remains dominant in both usage and revenue. Claude has surpassed Gemini in paid subscribers in the U.S., a notable achievement for Anthropic, particularly with 7.5% of its subscribers on $100+ per month plans (compared to 1% for ChatGPT and Gemini).
Creative tools also show interesting patterns. While labs like OpenAI have excelled in image generation, specialized audio tools like Eleven Labs and Suno have found success by focusing on niche areas where labs haven't prioritized due to complexity or IP concerns. In video, Chinese companies have an advantage due to data access. The panelists emphasize that the "software layer"—bespoke interfaces and product experiences—is where value is increasingly sitting, not just the underlying models.
Looking ahead, vast "white space" exists for AI innovation beyond productivity and search replacement. Categories like dating, recruiting, social AI, gaming, entertainment, shopping, and home buying are ripe for disruption. These often require "multiplayer" or "spend time" products, contrasting with the "save time" orientation of many current AI tools. The belief is that as models improve and product experiences are refined, the next wave of AI companies will emerge by leveraging models within rich, community-driven software layers, offering compelling new ways for people to engage and create.
摘要
a16z Editorial Partner Elena Burger sits down with investing partners Olivia Moore and Josh Elman to unpack the seventh edition of a16z’s Top 100 Consumer AI Apps, including a new dimension this time: what consumers are actually paying for.
The data reveals a striking power-user economy. Only a small share of consumers currently pay for AI, but among those who do, spending is heavily concentrated at the top. Olivia and Josh discuss why developers, creators, and other power users dominate spending today, and why subscriptions may not be the business model that ultimately brings consumer AI to everyone.
They also dig into the rise of personal agents, the different trajectories of ChatGPT, Claude, and Gemini, how ads could reshape AI economics, and the enormous amount of consumer white space still left to build, from shopping and entertainment to social, dating, and marketplaces.
Timestamps:
00:00 - Intro
00:56 - Inside the 7th edition
05:55 - Muse and Instinct's launch numbers
09:14 - The privacy wall for personal agents
14:39 - 4.5% pay, $903/month at the top
20:20 - Why subscription is the wrong model
23:51 - OpenAI's $1B ad run rate
29:21 - ChatGPT vs Claude vs Gemini
32:30 - Where creative tools still win
45:12 - The white space: dating, shopping, entertainment
Resources:
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GPT-4正在为你翻译摘要中......
中英文字稿 
最有趣的新趋势是在个人助手方面。我们如今生活在一个因ChatGPT将事物转变为对话而感到兴奋的世界中。现在，这些助手可以在我们的消息应用程序中转变为更多的对话。这是一种令人难以置信的新模式。大约一半的美国人报告说他们使用人工智能，约有4.5%的美国消费者为人工智能产品支付订阅费用。顶级的1%用户每月在他们的个人信用卡上花费903美元来购买人工智能服务。实际上，人们正在构建软件，他们正在创建这些非常丰富的产品。他们可能使用助手来编写一些代码，但当他们向用户提供整个体验时，这远不只是模型上的一个过渡。OpenAI通过广告实现的增长速度说明了什么？过去，即便在推出广告产品后，这也需要公司花费多年时间才能达到。
▶ 英文原文 ⏱
The most interesting big new trend is in personal agents. We're in this world where we're so excited by what Chatsubuti did with turning things into conversation. And now these agents, we can get in our messaging apps to turn them into more conversation. There's this incredible paradigm. About half of Americans report using AI. Around four and a half percent of U.S. consumers are paying a subscription to an AI product. The top one percent user is spending $903 per month personally on their personal credit cards on AI. The reality is people are now building software. They're building these really rich products. They may be using their agents to write some of that code, but when they're delivering this whole experience to a user, it is much more than just a shim on the model. Run rate that OpenAI has reached through advertising. What does that tell us? That would previously take a company years and years and years to get to, even after launching an ads product.
让我来翻译一下这段文字，并尽量使其表达的意思简明易懂：
在广告产品的发展过程中，我非常好奇的一点是。欢迎收听A16Z播客。我是Elena Berger，今天与我一起的是Olivia Moore，她是我们持续发布的《前100名消费者AI应用报告》的作者，还有我们消费者团队的Josh Ellman。今天，我们要深入探讨这份报告的第七版：谁在为AI买单？为什么大型助手们在走不同的方向，以及私人助理是否能将日常琐事转变为下一个大型消费者业务。团队，感谢你们的参加。非常感谢邀请我们。Olivia，我们就直接开始吧。我很想听听你对这份报告的主要看法。
▶ 英文原文 ⏱
What I'm fascinated to see in terms of the evolution of the ads product is. Welcome to the A16Z podcast. I'm Elena Berger, and I'm joined by Olivia Moore, who's the author of our ongoing Top 100 Consumer AI Apps Report, and Josh Ellman on our consumer team. Today, we're digging into the seventh edition of this report, Who's Paying for AI? Why the big assistants are heading in different directions, and whether personal agents can turn everyday errands into the next big consumer business. Team, thanks so much for joining. Thanks so much for having us. Olivia, let's just get right into it. I would love to hear your top takeaways from this report.
好的。这是我们第七次制作这个榜单。第一次的时候，我们仅仅通过访问量（例如网站点击量）对所有的全球AI原生网站进行了排名。这在当时行得通，因为几乎所有人使用AI的方式都是通过浏览器中的一个提示框产品。随着AI的扩展，近几年我们对榜单做了很多调整。所以这次的榜单是迄今为止最全面的。我们首次加入了收入数据，并合作使用了EBIT数据，专门获取了消费者信用卡支出数据，因此不包括企业或中小企业的财务数据。我们按消费者实际支付的产品进行了排名。我觉得从这份报告中最大的收获是，从流量的角度来看，很多这些产品似乎逐渐趋于稳定。
▶ 英文原文 ⏱
Yeah. So this is the seventh time we've done this list. The very first time, we only ranked all global websites that were AI native by just traffic, like hits on the website. And that worked then, because the way that almost everyone was using AI was like a prompt box product in a browser. We've had to evolve that a lot over the last few years as AI expands. So this list is our most expansive yet. We added revenue data for the first time. So we worked with the EBIT data to get specifically consumer card spend data, so non-accounting for enterprises or SMBs. And we ranked products by what consumers are actually paying for. I think for me, the biggest takeaways from this report is on a traffic basis. It looks like a lot of these products are kind of settling.
我们在网络和移动端的列表中只有11款新产品，这是我们系列过去几版中最少的一次。但支出数据却引入了很多新变量，因为在支出排行榜上的50个产品中，有29个并不在流量榜单中。这也反映或连接到报告的另一个重要结论：现在AI的消费者真的是一个超级用户游戏。是的，这确实很有趣。我们最近发布了市场状况报告，其中Sarah Wang直接评论说：“现在有一个强者恒强的游戏正在发生，不仅在企业层面，也在消费层面。”
▶ 英文原文 ⏱
We only had 11 new products across the web and mobile list combined, which is the least we've had in any of the prior editions of the series. But the spend data really introduced a lot of new variables, because of those 50 that ranked for spend, 29 of them were not on either traffic list. And that also, I think, kind of works towards or connects into the other big conclusion of the report, which is just how much of a power user game consumer AI is right now. Yeah. Yeah. That's something that's funny. We also recently released our state of markets, and something that Sarah Wang actually commented directly on is she said, "Hey, there's such a power law game happening now, it's happening at the enterprise level, and it's happening at the consumer level."
所以，有一点值得注意的是，我们这次名单上的新来者数量是最少的，看起来这个领域正在僵化。不过，我觉得过去几个月里情况有所好转，其中一个最有趣的新趋势是个人代理的发展。那么，你看到了什么？正在发生的重大变化是什么？是的，有趣的是，我们上次做的报告，恰好在OpenClaw流量进入的截止时间之前结束。因此，在发布报告之前，我们做了一次回顾，发现如果包括OpenClaw的话，它会在排名中名列前茅。
▶ 英文原文 ⏱
So, one thing that's probably notable is, yeah, we have the fewest number of newcomers on this list, and it seems like the space is ossifying. But I think the past few months, things have actually been picking up a little bit more, and I think the most interesting big new trend is in personal agents. So, what are you seeing? What are the big shifts that are happening? Yeah. It's funny, the last report that we did, um, it ended right before the cutoff of when OpenClaw traffic would come in. So, we had done kind of like a retro before we published the report, and we had found that it would have been very high up in the rankings.
这次，事实上，OpenClaw在排名中根本看不到，因为其流量已经完全下降。我认为这是因为团队被OpenAI收购了，所以他们可能在致力于开发代理助手产品。但是，我觉得它也被一些其他产品超越了。不过，在消费端，我们终于看到了一些我觉得可以放心推荐给家人使用的产品。因为，如你所言，这种消费者助手趋势实际上是过去三周到一个月才出现的，所以很多这些产品还没有出现在排名中，但我们还是提取了数据来了解它们的情况。
▶ 英文原文 ⏱
And this time, actually, OpenClaw is nowhere in the rankings, because the traffic has completely declined as-- I think that the team was acquired by OpenAI, so they're probably working on, you know, the agent assistant products there, but also it's kind of been overtaken, I think, by some of the-- But also, on the consumer side, we're finally seeing things that I would feel comfortable giving to a family member and telling them that they can safely use. Most of those also, because, to your point, this consumer assistant trend has literally been the last three weeks to a month, a lot of those didn't appear on the ranks yet, but we did pull the data to see what's happening with them.
这段话翻译成中文是：
“嗯，可以说发展非常迅速，但尚未完全进入主流用户群。我认为我们正处于一个非常有趣的时代，这一变化确实发生在去年年底和今年年初，因为 OpenClaw 的出现，人工智能从我们用来提升生产力的工具，或是帮助我们更快搜索信息的工具，变成了一种能够为我们真正完成任务的东西。我认为 OpenClaw 在这方面是一个非常了不起的先锋，而且我知道他们通过开源基金会继续在这方面做很多工作。不过，这确实让很多人开始重新思考，这些产品到底能实现什么。”
▶ 英文原文 ⏱
And it's been, um, very, very fast growth, and yet still not quite reaching the mainstream users, is what I would say. And I think we're in this really interesting era that did really change at the end of last year, beginning of this year with OpenClaw, that AI went from something that we were using as a tool to enhance our productivity, to maybe search for us faster, something that would actually get things done for us. And I think OpenClaw was an incredible pioneer to do this, and I know they're still doing a lot of work through their open source foundation to continue to advance that. But it really turned a lot of heads on, wait, what can these products actually be?
我们看到人们购买 Mac mini，运行他们自己本地的 OpenClaw，需求非常旺盛。这种新的可能性带来的能量确实让人鼓舞。就像大多数趋势一样，这种火花需要一些时间来发展，最初的产品需要一些时间才能够构建出来，随后才能积累动力，在市场上发布，让用户看到。
▶ 英文原文 ⏱
And we were seeing people buying Mac minis, we were seeing people run all their own data with their own local OpenClaw, and there was a huge run on that. But it was really inspiring to kind of feel this new energy of what is possible. And, you know, like most trends, you know, that spark happens, it takes a little while for those first products to get built, it takes a little while for the momentum to then start getting those even released in the market, for users to see them.
这份报告在某些方面很好地展示了我们在硅谷的播客中经常讨论的话题。不过，它实际上也很好地反映了全球范围内正在发生的事情。我确实认为，人工智能确实已经渗透到各个领域。即使没有很多新进入者，所有现有的参与者也都在迅速壮大。
▶ 英文原文 ⏱
And so, you know, in some ways, though, this report is showing, like, that's what we're talking a lot about, you know, on our podcast in Silicon Valley. But this really does a great job representing what's happening in the broader world, and that, you know, I do think the truth is AI really is showing up everywhere. Even if there's not a lot of new entrants, all the entrants are all getting so much bigger.
好的。在我们讨论纯粹的消费者辅助时，我认为可能最重要的发展是Muse和Instinct。尽管我们的报告中还列举了许多其他非常出色的产品，比如说，Polk是这里的一个早期先锋。没错。而Tomo拥有非常庞大的受众，并且表现非常出色。
▶ 英文原文 ⏱
Yeah. No. I think probably the biggest things on, when we talk about pure consumer assistance, the biggest developments have been Muse and Instinct, I would say. Although there's many other fantastic products that we kind of list in the report that have also, you know, Polk was a very early pioneer here. They were a pioneer of this, yeah. Exactly. Tomo has a very big audience and is doing incredibly well.
好的。Instinct 宣布他们的用户数量达到 10 万，并且每天增长 10%。他们还表示，在前 3 周内，有 40% 的用户绑定了信用卡，而且这些用户在第一个月的平均消费超过了 1,000 美元。Muse 也很有趣，因为它在很多方面取得了非常成功的发布，尤其是在科技界。我记得他们在发布的前 12 天达到了大约 50 万次下载和 25 万名活跃用户。
▶ 英文原文 ⏱
Yeah. Instinct had announced, like, 100,000 users growing 10% day over day. They'd announced, like, 40% of users connected a credit card in the first three weeks, and they were spending, you know, over $1,000 on average in their first month. Muse is interesting because, uh, in many ways, very successful launch, especially within the tech community. I think the number was, like, 500,000 downloads and 250,000 active users in the first 12 days or so.
但如果你将其与Threads进行比较——这是另一个最近由Meta推出的大型项目——就会发现，对普通非技术行业的人来说，它的吸引力仍然逊色不少。
▶ 英文原文 ⏱
But if you look at it versus Threads, which was another, you know, somewhat recent big, splashy meta launch, um, it just, it still pales in comparison, in terms of appeal to the average person who doesn't work in tech.
好的。如果你查看下载量，Muse 应用仍然主要在美国和加拿大被下载，所以我们只统计了 Threads 应用在美国和加拿大的下载量。在大约前22天内，Threads 的下载量大约是1600万，而同一时期内，Muse 的下载量仍然在500万左右。
▶ 英文原文 ⏱
Yeah. So if you look at the downloads, um, Muse is still in the U.S. and Canada, so we grabbed the Threads, U.S. and Canada downloads only. In the first 22 days or so, Threads had had about 16 million downloads, and Muse is still sitting around 5 million over that same time period.
分发机制不同吗？我记得 Threads 是和你的 Instagram 账户绑定的，因此有一种非常自然的分发方式。那么他们在 Muse 上是否尝试类似的策略，还是采用了不同的分发策略？我很好奇 Josh 的看法，不过从我的角度来看，Muse 的策略肯定没有那么激进，而且部分原因是服务这些用户的成本相对较高，所以他们不希望用户量增长得太快。
▶ 英文原文 ⏱
Is the distribution mechanism different? Like, I remember with Threads, it was already tied to your Instagram account, and there was kind of this, like, very natural distribution. Is, are they trying a similar strategy with Muse, or is it just a different distribution strategy, too? I mean, from, I'd be curious what Josh thinks, but from my point of view, it's not as aggressive, for sure, uh, and also part of that is because there's a much higher cost to serve these users, so they don't want it to get too big, too fast.
好的，我认为 Threads 确实受到临界质量效应的影响，也就是说如果没有很多人在上面快速交流，就无法真正形成一个新的网络。- 是的。- 而 Muse 仍然是一个非常个人化的工具，他们正在推动它的发展。即使在这个早期阶段看到人们开始使用并体验它，也让人感到非常振奋。
▶ 英文原文 ⏱
Well, and I also think Threads very much had a critical mass effect, which is if they didn't get a lot of people on it communicating quickly, you don't actually get to that leverage of a new network starting to form. - Yeah. - Whereas Muse is still such a personal tool that, you know, they're pushing it, and it's very exciting to kind of even see this early just adoption and people having these experiences.
如果你在今年一月份使用OpenClaw，那么当Crock-Bot在这个夏天或春天首次推出时，你一定有过非常棒的体验。现在，我们看到的是，就像Olivia所说的，我们的妈妈、家人，还有那些不总是紧跟科技和AI发展的人们，也开始接触和使用这些技术。
▶ 英文原文 ⏱
And again, if you were using OpenClaw in January, you were having an incredible experience of using Crock-Bot when that first launched earlier this summer or spring, you were having these incredible experiences. And now we're seeing, as, you know, I think Olivia said, you know, our moms, our families, you know, people who don't just live on the tech, what's next in AI cycle.
我认为这就是这个消费者真正令人兴奋的地方。我预计下次我们再这样做时，会看到大规模的采纳。但我觉得在早期，并不需要太费力去推动这种网络效应。不过，我也在思考是什么能让这些东西长久存在，那将会是网络效应、市场，以及你能与那些代理进行互动的所有业务。
▶ 英文原文 ⏱
And I think that's what's really exciting about this consumer. I assume when we do this again next time, we're going to see massive adoption, but I think it hasn't needed to push as hard to have that early network effect. But then I also think about what's going to make these things stick around for a long time, and it is going to be things like network effects and marketplaces and all the businesses you can interact with those agents.
- 是的。
- 这也将带来真正的变革。
- 是的。关于消费者代理和助手，这是我们经常讨论的一个话题。我认为它们正在经历搭建平台的复合效果，至少在其他应用程序的生态系统中，这些应用程序对代理更容易使用，我们似乎能看到这种效果。
- 我们也看到这种情况带来的不同结果。比如说，亚马逊表示不允许Muse在他们的网站上浏览和购买产品。但同时，Muse已经与数百种不同的产品建立了合作关系，比如Shopify，让用户可以在Shopify上购买东西。
- 没错，是的。我仍然觉得没有任何助手产品能够激发人际网络效应。而这其中的一个原因是，这些软件通过电子邮件理解我们的程度，比过去任何产品都要深入。但同时，我发现自己也会对AI倾诉非常个人的事情。
▶ 英文原文 ⏱
- Yeah. - That's going to be really transformative, too. Yeah. This is one of the things we talk about a lot when it comes to consumer agents and assistants, which is, I think they are getting kind of the compounding effects of building out a platform, or at least it seems like they are in terms of the ecosystem of other apps that are available and more easily usable by the agent. We've seen that cut both ways. Like Amazon is like, we're not going to allow Muse to kind of browse and purchase products on our site. But also, you know, Muse has already hundreds of other partnerships with different products. Shopify, you know, to be able to buy things on Shopify. Exactly, yes. I still don't feel like any of the assistant products have unlocked person-to-person network effects. And part of this for me is like, this software knows us more intimately than any other product in the past, based on email. But also, like, I find myself telling extremely personal things to my AI.
这段文字讨论了一个自然存在的紧张关系：产品对你越有用，它就越了解你。但这样一来，你是否愿意在其他场合与其他人分享这些信息呢？比如，很多人有一个专门用于工作的 ChatGPT 账户和一个个人账户，但目前还没有人真正解决这个问题。在谈到消费者和人工智能时，隐私、安全和保障正变得越来越重要。人们总体上相信人工智能对世界是有益的，这种趋势在一定程度上影响了人工智能的采用和对这些产品的热情。然而，从个人层面来看，如果你不信任一个应用程序，却将你的电子邮件、生活隐私或信用卡信息交给它，而它可能会做出一些意想不到的事情，或与其他人分享你的信息，这将是这些应用程序成为大众消费产品的最大障碍。
▶ 英文原文 ⏱
And so there's kind of this natural tension between the more useful the product is to you as the consumer, the more it knows about you. And like, then do you really want to introduce that into other contexts with other people? It's the same thing as like many people have a separate ChatGPT work account and personal account, and no one has quite cracked that yet. No. And I think, you know, as we talk about consumers and AI, privacy, safety, security are becoming more and more important. I mean, there's obviously the overall trends of, you know, trust in AI and this kind of belief that AI is good for the world that is in some ways, you know, affecting adoption and affecting some of the excitement around these products. But on a very personal level, if you don't trust the thing that you're giving it your most intimate access to your email or your life or your credit card, and it might do rogue things that you wouldn't expect or share things with other people you wouldn't expect, you know, that's going to be the biggest impingement on these things really growing as massive consumer apps.
我们现在处于一个非常有趣的时代，我们都在学习这些新的规范。这些规范其实我们作为人类非常擅长掌握。我们很清楚自己愿意分享什么信息，别人给我们的信息我们是否愿意传递给其他人，或者这些信息我们应该自己保留。而现在，我们突然希望软件也具备这种能力。这是一套非常有趣的新事物，我们正在学习。
你们刚刚提到了两个有趣的方面：一个是内在的力量，也就是各种平台以及它们允许用户如何与之互动；另一个是外在的力量，比如我在使用过程中感到多么舒适。可能我把内在和外在力量混淆了，一个在外一个在内。不过我们理解你的意思。
▶ 英文原文 ⏱
So it's a we're in a fascinating time where we're all learning these new norms. And these are norms that like as people are actually very good at it. We're very good at knowing what information we're comfortable sharing, what information if somebody gives it to us, what information that we're trusted to be able to pass on to somebody or should be protecting and keeping ourselves. And we're just like all of a sudden expecting software to do this, too. It's a it's a very, you know, interesting new set of things we're learning. Yeah, well, you you both just brought up like two interesting sort of facets of this one is like there's this endogenous force, which is all of the platforms and how they allow agents to interact with them. And then there's more like this exogenous force of like how comfortable am I using this and how maybe I mixed up endogenous and exogenous. One is on the outside and one is on the inside. We knew what you meant, yeah.
一个是平台在做什么，另一个是你对其感受如何或你对助手的感受如何。我很好奇你认为哪个问题会更早得到解决，而解决这些问题的责任应该由谁来承担？我认为平台的能力提升速度比消费者真正愿意使用的速度要快，这在目前的人工智能发展中已经体现出来了。有趣的是，很多人看到这些助手产品的创始人发布的数据，发现每月为一个用户服务的成本竟然高达几百或几千美元，大家都觉得不可思议。我也很困惑，不过我一直在和David Paulon合作，他负责Assistant Benchmark，非常优秀。他最近还参加了一期播客节目。
▶ 英文原文 ⏱
One is what the platforms are doing and one is how you feel about it or how you feel about the agent. And I'm curious which which do you think is going to get resolved sooner and and who's like whose onus is that like whose whose responsibility is resolving those kinds of questions? I think what the platforms are capable of is improving faster than true consumer willingness to use them, which we've seen kind of throughout AI so far. It's interesting because a lot of people are like seeing these numbers that founders of these assistant products are posting that it costs like hundreds or thousands of dollars a month to serve a user. And like, how is that possible? Um, and I was stumped as well, but I have been working with David Paulon, who runs Assistant Benchmark, who's fantastic. And there's a recent podcast with him.
好的，他真的很厉害。他创建了一个网站，用来追踪大约170多名代理。我昨晚查看的时候大概是这个数量，今天早上可能已经有200多了。他让用户使用这些代理，然后根据不同任务的成功率对它们进行评分。不过，他做的另一件很有趣的事情是他组织了一些群聊和早期使用这些代理的社区。他大概有1500多名用户，并为我们收集了一些很有趣的数据，比如他们用代理做什么，以及他们在讨论如何使用代理。绝大多数人目前的首要用途仍然是编程和技术自动化，即使是对于那些消费者助手产品，比如Muse和Instinct也是如此。在这一背景下，理解这些产品的成本就变得理所当然了。那些面向主流消费者的代理或助手产品的月费用是几十美元，而不是成千上万美金。
▶ 英文原文 ⏱
Yeah, he's great. So basically what he's done is he's created a website where they track, I think, over 170 agents. I checked it last night, it's probably like 200 something this morning and they he has users kind of use them and then rank them on success on different tasks. But the other really interesting thing that he does is he hosts kind of group chats and communities of early adopters of these agents. So he has a group of I think it's 1500 plus users and he pulled some cool data for us, which is like, what are they doing with agents? What are they talking about doing with agents and the vast majority still the number one use case was coding and technical automation, even for these consumer assistant products like just like Muse and Instinct. And so under that framing, it's like, oh, of course it costs that much. This is like when we talk to some agent or assistant products that are aimed towards the more mainstream consumer, they're seeing costs in the tens of dollars, not the thousands of dollars a month.
我认为这可能反映了消费者要对这些产品感到舒适，还有很长的路要走。我认为那些从事编程和人工智能工作的人，它们已经为他们的工作提供了极大的帮助，这在很多数据中都有体现，比如这里的前100个榜单。这真的很了不起。从事这些工作的人在生活中的其他方面也有了很棒的想法。但是，当你把这些东西交给刚接触的人时，他们可能会觉得无从下手，就像面对一个空白的盒子，不知道该做什么。或许会有一些例子，比如预订餐厅或机票。但是如果你不是在主动寻找餐厅或预订机票的需求时，就很难弄清楚如何去个性化使用它。
▶ 英文原文 ⏱
So I think that is maybe a representation of the fact that we have a very long way to go in terms of consumers getting comfortable with these products. And I think, you know, I think people who've been coding and have been working with AI, I mean, it's been such an incredible enhancer and that shows up in a lot of the data, you know, on the on the top 100 here. Like, it's incredible. And then we people who've been able to do that have had these great ideas for all the other things in their life. But when you just hand this to somebody new, it feels like a blank box and it feels like, what should I do with this? And maybe there's examples of getting a reservation or booking a flight. But if you're not actively seeking a reservation or booking a flight, it's hard to figure out how to personalize it.
我们作为人类，大部分时候都是从他人那里学习，获取一些很棒的想法，然后尝试别人告诉我们的其他事情。社交媒体的运作方式也是如此，人们在社交媒体上发布内容，其他人看到后就会去尝试，然后这会引发连锁效应，我尝试后做了一些小改动，然后这些改动就像滚雪球一样不断扩大。这就是伟大创意的传播方式。而在人工智能领域，由于其个性化的特点，这种传播我们还没有完全看到，除了在编程和提高工作效率等领域。在所有的创作工作中，比如我制作了一个很棒的视频，人们会问我是怎么做到的？我用了人工智能。有很多这样的工具正在发展，并且已经出现。
▶ 英文原文 ⏱
And so much of what we do as people is we learn from others and we get these great ideas and we try the other things people tell us. So much of how social media has worked is people put things on social media and other people see that and they try the same thing. And then it kind of spawns these effects where I try they make a little riff on it and then those riffs become, you know, cascading snowballs. And that's how great ideas flourish. And with AI, because so much of it's so personal, we haven't even seen any of that flourishing yet, you know, outside of areas like coding and productivity, you know, all of the creative work. You know, I, I created this incredible video and how'd you do that? I use AI, you know, and there's so many tools that do that, that, that are, you know, been growing and are here.
但有趣的是，现在我们需要想办法如何将这一技术普及到不仅仅是数以百万计的人（他们已经在使用并支付费用），而是数以十亿计的人之中。从当前广泛的使用数据来看，大约一半的美国人报告称自己在使用人工智能，大约25%的美国人认为他们几乎每天都在与人工智能互动。但消费支出数据则更加集中，这取决于数据来源。根据我们的YIPI小组调查，大约不到5%，可能是4.5%的美国消费者正在为某种人工智能产品支付订阅费用。而其他一些来源称这一比例可能低至2%或2.5%，或者稍高一些。
▶ 英文原文 ⏱
But it's so interesting that, you know, now we have to figure out how to mainstream this for not the, you know, millions and millions of people who are using these and paying and everything, but for the, you know, tens, hundreds and, you know, hundreds and hundreds of millions. If you look at broad usage data now, about half of Americans report using AI and about 25% of Americans think they're interacting with AI probably on close to a daily basis. But the spending data is much more concentrated, so it depends on the source. Our YIPI panel shows probably sub five percent, around four and a half percent of U.S. consumers are paying a subscription to an AI product. Some other sources say as low as two or two and a half, or maybe a little bit higher.
它正在扩大，这意味着相比一年前规模翻了一番，但这些支出仍然非常集中。即使在那4.5%有支出的人群中，前10%的用户贡献了超过一半的收入，而最顶尖的1%贡献了20%的收入。而相对而言，底部50%的用户仅贡献了16%的收入。因此，可以说，前10%的用户推动了这个市场。这段收入数据还揭示了另一个有趣的现象：我们能够以几乎逐个用户的方式查看数据，了解是谁在花钱购买AI。排名前1%的用户每月在个人信用卡上花费903美元用于AI，而中位数支出为25美元。而以上所有数据都仅限于那4.5%的有支出用户。
▶ 英文原文 ⏱
It is expanding, so that's like doubled from a year ago, but that spend is still extremely concentrated. So even within that top 4.5% of people who do spend, the top 10% of those are like more than half of the revenue and the top 1% are 20% of the revenue. Whereas the bottom 50% are like 16%, right? So like the top 10% of users are driving this market. This was the other interesting thing about revenue data is we were able to look at it kind of like on a almost person by person basis. What it looks like, who are these people who are spending on AI? The top 1% user is spending $903 per month personally on their personal credit cards on AI. And the median is spending $25. And again, all of this is within the only the 4.5% that are spending at all.
YIPI对我们也很有帮助，因为我们可以看到用户实际上在花钱购买哪些产品，尤其是从个人角度来看。大多数情况下，不出所料的是，用户主要购买开发者工具、生产力工具、创意工具，这些都是用于构建、制作和销售的东西。像N8N、Granola、Higsfield、Manus这些工具，在顶级花费者中都特别受欢迎。这其实很酷。虽然这些数据并不代表所有人，但我们正在支持新一代创作者，他们不仅在工作中使用这些工具，还使用个人信用卡去编写以前从未编写过的代码，创作艺术、制作视频和内容，从而真正拥有创造的力量。
▶ 英文原文 ⏱
YIPI also was helpful for us because we could see what products are they actually spending on, like on a personal basis. And probably unsurprisingly, it was mostly developer tools, productivity tools, creative tools, things used to like build, make, sell. Things like N8N, Granola, Higsfield, Manus. Those all were way overrepresented amongst the top spenders. I mean, in a way, this is actually really cool. I mean, even though these numbers aren't everybody yet, like we're enabling this whole new generation of makers of people who are, you know, not just using this for work, but actually using their personal credit cards to code things they never coded before to make art, make videos, make content and, you know, really have this power of making.
其实，在某种程度上，尽管一切仍处于初期阶段，这种创造活动的热情是很酷的，人们愿意花钱去投入其中。比如说，如果你每月花费900美元使用一套人工智能工具，那么你肯定是希望利用这些工具来更快更好地实现创意，燃起更多的灵感火花。这就像我在观察创造力和编程这两个领域时感受到的——希望这真的非常强大。
▶ 英文原文 ⏱
And so it's actually in some ways, you know, while it's all still so early, it's actually really cool how much making is going on that people are actually so excited they're willing to spend. I mean, if you're spending $900 a month on a set of AI tools, you're really using that to like hopefully make things faster, better, have more ideas in your head coming to life than ever before. Yeah. That's kind of like when I, when I was looking at these categories between creativity and coding, like, you know, that's actually hopefully really, really powerful.
好的，我认为这是一个非常重要的观点，即开发者和程序员天生具备一种思维模式，他们会不断问自己如何才能获得更大的影响力，如何开发出可以有效利用自己时间的产品。显然，人工智能极大地增强了这种能力，但这是一种特定的思维模式，也是一种特定的世界观。而且我认为部分原因在于这种世界观目前还只存在于一小部分人中。因此，关键问题是如何扩展这种世界观？如何帮助人们认识到，有哪些方法可以让他们更好地利用自己的时间和生活？
▶ 英文原文 ⏱
Yeah, well, I think this is a point that's really important, which is I think developers and coders are people who are naturally attuned to sort of ask, how do I get leverage over this thing? How do I build a product that allows me to get leverage over my time? And AI obviously supercharges that, but it's, it is a specific kind of mindset. I think it's a specific kind of worldview and I think part of, part of my understanding of these numbers is it's still a worldview that gets reflected only among a small, smaller group of people. And the question might be just like, how do you expand that worldview? How do you help people understand, like, here are all the ways you can get leverage over your time and over your life?
我们在这份报告中稍微讨论了一下，关于我们还没有看到原生AI初创公司出现的领域，或者还没有出现的类别。嗯，我们的一位投资组合CEO Eugenia 经营着一家公司，叫Wabi，非常出色。她有一句很棒的话，我可能会说得不太准确，但大概是这样：大多数人并不是在寻找省时间的方法，而是在寻找如何花时间的方式。这就是为什么社交媒体、娱乐、Netflix、TikTok、YouTube这些都是我们使用最多的消费产品。我认为，到目前为止，我们在AI领域看到的许多东西，正如你所说，就像是：我怎样能让这件事做得更快、更简单、更令人印象深刻。
▶ 英文原文 ⏱
We talked about this a little bit in this report in terms of areas where we have not yet seen AI native startups pop up or categories where we haven't. Um, Eugenia, who's one of our portfolio CEOs, runs a company called Wabi, which is fantastic. She has this great quote, I'm probably gonna botch it, but it's something like people, most people aren't looking to save time, they're looking for ways to spend their time. Um, like, this is why social media, entertainment, Netflix, TikTok, all of these, YouTube are so, are the most used consumer products that we have. And I think that much of what we've seen in AI thus far, to your point, is like, how do I do this thing a little bit faster, a little bit easier, a little bit more impressively?
这对大多数人来说，并不是一个非常有吸引力的日常或每小时活跃价值主张。我认为，节省时间仍然对那些专注于工作和创意的高效生产力人群非常重要。但我也看到下一波人群的出现，他们可能曾是程序员，现在不再是，或者是那些想制作视频但从未真正掌握Pro Tools或Adobe Premiere等工具的人。这些人突然间能够注册这些工具，并将他们头脑中的想法变为现实。
▶ 英文原文 ⏱
And that's not an incredibly compelling daily or hourly active value proposition for most people. No, I think, I think this, you know, saving time is still very, you know, hyper productivity, people who are focused on, you know, work being creative, but I'm also seeing this next wave of people who are maybe used to be coders. They're no longer maybe people who, you know, want to make videos, but never quite mastered the, you know, Pro Tools and Adobe Premiere or something else, where they're all of a sudden able to sign up for these things and take the ideas in their head and make them happen.
所以，我确实认为，我们开始看到这些变化的出现。再说一次，你知道，我查看所有这些数据时觉得我们还处于非常早期的阶段。是的，事实上我们能走到今天并讨论那些已经很大的公司，以及1%的人每月花费900美元这些事情，我把这些视为未来的预兆。随着越来越多的人感到有能力，越来越多的人觉得他们可以创造，这不仅仅是为了节省时间，而是为了享受将想法变为现实的乐趣。
▶ 英文原文 ⏱
So I do think, you know, we're starting to see these rise up. And again, as, you know, I look at all these numbers as we're still so early. Yes. And, and the fact that we're even here and that we're talking about how, you know, big some of these companies are and that 1% of people are spending $900 a month. Like I see these as harbingers of what's to come as more people feel empowered, as more people feel like they can create where it doesn't, it's not necessarily about saving time. It's about spending the joy of like actually willing this thing into reality.
你知道，当时有很多笑话，说大家在第一次使用他们的开源软件时，都处于那种热潮期。他们会到处携带他们的电脑和笔记本，必须保持开机状态。他们说，他们不睡觉，只是不断地编写代码，创造比以前更多的东西。我认为这种现象已经开始在数据的某些顶端展现出来，并且可能开始在各个领域都出现。
▶ 英文原文 ⏱
You know, we, there, there were all these jokes of, you know, oh, when people were in this, like the peak phase of everybody's using their open cloth for the first time, their agents, they'd walk around with their computers and their laptops and they had to keep them open. And they, and they were like, I'm not sleeping, I'm coding and I'm making things, you know, more than I ever have. And I think that's starting to, you know, again, shows up at the top of the data, but I do think it's starting to show up sort of everywhere.
是的，实际上，我并不一定希望直接支付AI产品费用的4.5%的用户数量增加。这可能会引起争议，因为我自己投资于消费者AI产品，而且我是一名消费者AI产品的极端支持者。但我这样说的原因是，到目前为止，消费者AI的收入几乎全部来自直接订阅。比如，我们查看了这份清单，发现大约85%的网络用户是通过订阅获利的，另有62%的用户通过额外的积分或代币使用支付来获利。
▶ 英文原文 ⏱
Yes, I actually don't necessarily want to see that 4.5% of people paying for AI products directly expand, which is maybe controversial because I'm like invested in consumer AI products and I'm a consumer AI maximalist. But the reason I say that is because substantially all of the consumer AI revenue thus far has come from direct subscriptions. Like on this list, we looked and it was like, you know, 85% or something of our web list monetized via subscriptions, another 62% monetized via kind of credits or token extra usage payments.
只有大约13%的情况是通过广告或其他方式来盈利，而不是让你为产品付费。而从消费互联网的历史来看，这样做是相当不寻常的。如今几乎所有大型消费科技公司，其主要收入来源是广告或交易手续费，而不是订阅费用。因为事实上，并不是每个人都在寻找能帮助他们创业、创造或销售产品的编码工具。
▶ 英文原文 ⏱
Only like 13% had ads or other options where like you are the product instead of paying for the product. And that's like a, if you look back at the history of the consumer internet, that's like a pretty unnatural inversion. Like almost all of the really big consumer technology companies that we have now, make the vast majority of their revenue from ads or from transaction fees, not from subscriptions. Because I think the truth of it is most similar to the fact that not everyone is looking for a coding tool to help them, you know, start a business or create and sell a product.
大多数人没有资金，或者不想把资金花在软件上。如果你看看全球排名前20的消费者订阅产品，ChatGPT已经赫然在列，这在短短三年半的增长过程中是非常惊人的。几乎所有其他产品都是媒体公司或大平台，比如亚马逊或者优步，这些都是人们经常进行购买的服务。因此，我坚信我们需要转变。
▶ 英文原文 ⏱
Most people don't have the funds or don't want to spend their funds on software. If you look at the top 20 consumer subscription products globally, ChatGPT is already on there, which is crazy in like three and a half years of growth. Almost all the other ones are media companies or big platforms like Amazon or even Uber, things like that, where you have a very frequent purchase behavior. So I actually am a big believer that we need to move.
我们已经超越了让每个人都购买AI订阅的需求，现在我们需要看到其他商业模式的回归。目前，AI推理成本的下降仍处于早期阶段，人们也仍在寻找运行低成本模型以打造优秀产品的方法。当他们做到这一点时，互联网上一直存在的许多其他商业模式，比如交易费用和广告，都会开始有效运作。我们需要这样的变化发生。
▶ 英文原文 ⏱
We have transcended the need for everyone to buy a subscription to AI and we need to see these other business models come back. We're still at the early days of inference costs coming down. We're still at the early days of people finding ways to run lower cost models, to build great products. And as they do that, you know, a lot of the other business models that have always been on the internet from, you know, transaction fees and ads will finally start working. We need that to happen.
这就是我认为我们仍然面临的问题，有很多东西需要学习，而且有很多事情是这样的：如果服务成本太高，至少让我通过收费来让人们为此付钱，这成为了一种早期的默认选择。是的，您可能通过观察过去多个消费者互联网领域的发展对此有发言权，但至少对我作为消费者投资者而言，如果一家公司在头五年内就开始赚钱，我会感到很惊讶。过去的规则是：让我们先建立用户密集度，因为服务成本接近于零，我们可以等到拥有足够的流动性和用户密度后，通过广告赚钱或开始对交易收费。然而，由于当前的商品成本（COGS）很高，这种情况已经不再适用。
▶ 英文原文 ⏱
And that's, I think, where we're still, you know, there's so much learning and so, so much that like, well, if it's going to cost me a lot to serve, at least let me just charge money so that people pay for it became sort of an early default. Yes. I mean, you can probably speak to this from seeing many prior areas of the consumer internet, but like it used to be, at least for me as a consumer investor, if a company was making money in the first five years, it was like, whoa, what's happening? The rule was like, let's build density of users. And because they cost near zero to serve, we can then wait and make money via ads or start charging for transactions once we have liquidity and density. And that just isn't the case given how high COGS are.
不，我觉得这个成本问题是一个非常有趣的挑战，公司有时会害怕增长过快。是的，如果它们增长过快，却没有明确的收费标准，就可能导致失控的开销，这将非常难以管理。因此，这导致了我们现在在前100名应用中看到的非常不同的格局，无论是流量还是其他方面。但同样的，我们仍处于非常早期的阶段，还有很多需要构建、学习的地方，需要降低成本，提高价值，并引入广告和其他方式来增加收入。
▶ 英文原文 ⏱
No, I think, I think this cost thing is a, is a really interesting challenge and companies get afraid of growing too fast. Yeah. Like they actually, if they grow too fast and they don't have meters on how they're charging for it, you can actually have out of control spend that can be very, very hard to manage. So, you know, it's created this, this very different shape of what we see in the top apps in the top 100, you know, traffic and everything right now. But again, this is again, we're all still so early, so much to build and learn and bring costs down and bring value up and introduce advertising and introduce other ways to, to spend money.
顺便说一下，如果我们订阅了这些我们喜爱的服务，并且它们确实能为我们持续带来价值，那也很了不起。我觉得这是一个很好的切入点来谈论广告。是的，你们的消费者百强报告里有一个非常有趣的事实，那就是OpenAI通过广告获得的年度收益达到了什么水平。他们现在的广告年收入已达到十亿美元。这告诉了我们什么呢？另外，这个数字是八月份的，所以很可能即便过了一个月左右，这个数字已经有了增长。
▶ 英文原文 ⏱
And by the way, if, if it is, we subscribe to these services we love, and that's actually what we get continual value from. That's amazing too. I think this is a great transition to talk about ads. Yeah. Your, uh, consumer, uh, top 100 report had a really, really interesting fact in there, which was the run rate that OpenAI has reached through advertising. Yeah. They're at a billion dollars now in, in annual run rate on, on advertising. And what does that tell us, you know? Again, the number was from August, and so there's probably a chance that it's reasonably higher, even a month or so later.
是啊，但我觉得他们推出广告的速度一直很慢，用的是一种合作伙伴网络的方式。不过，他们的年化营收已经达到十亿美元。这以前要一个公司花好几年、甚至多年才能达到，就算推出了广告产品也需要很长时间。所以，我觉得有两点很有趣。首先，他们现在确实有很高的用户密度。据前几天刚报道的数字显示，他们拥有12亿的每周活跃用户，这就是真正的用户密度。
▶ 英文原文 ⏱
Yeah. But they have been very slowly, I would say, rolling out ads, um, with kind of a network of partners. And they're already at, you know, a billion, a billion in, in annualized run rate. Like that would previously take a company years and years and years to get to, even after launching an ads product. So, I think there's two interesting things there, one, they have real density now. So I think the last reported number a few days ago was 1.2 billion weekly active users, which is like a real density.
其次，我对广告产品的发展非常感兴趣。理论上，他们应该能够收取更高的费用并具有更高的转换率，因为他们对作为用户的你了解得更多。而且，ChatGPT已经推出了一些功能，比如用ChatGPT登录，我认为钱包等功能也将在未来推出。这样一来，你可以想象，这对广告商来说是一个非常吸引人的价值主张。这也会进一步推动广告业务的发展。不过，这一切还处于非常早期的阶段，我们拭目以待。
▶ 英文原文 ⏱
And then the second thing, and what I'm fascinated to see in terms of the evolution of the ads product is, hypothetically, they should be able to charge more and have higher conversion rates because they just know so much more about you as the user. And ChatGPT has launched things like login with ChatGPT, I think a wallet is coming, things like that. And so you could imagine that, um, it becomes a much more compelling value prop for the advertisers. And then that just like juices the ad business even more. Uh, but we'll see. It's very early days there.
这还只是个开始。我觉得，已经有一些关于广告和人工智能的搞笑对话。如果你正在和这个极其个人化的事物交流，然后突然说：“让我告诉你一些健康知识，并介绍一个能帮你快速减肥的神奇产品。” 这样做并不会让人对人工智能产生信任感。我认为另一个有趣的问题是，我们作为一个生态系统，如何应对这些如此不同且比以往任何时候都更加个人化的产品。
▶ 英文原文 ⏱
It's early days. And I think, you know, there've been some really funny conversations about ads and AI. If you are talking to this incredibly personal thing and then it's like, let me tell you about health and let me introduce you to this like crazy product that can help you, you know, lose weight fast. Like that's not building trust with AI. And so I think the other really interesting thing is like, how do we as an ecosystem, these products are so different. They're so much more personal than ever before.
他们会根据你正在做的事情、提问的话题以及他们对你的了解，为你量身定制答案。而且，广告的植入做得非常巧妙。当我偶尔看到广告时，OpenAI 投放的广告让我印象深刻。广告标示得非常清楚，并且在我与聊天内容的对话中，广告显得十分自然。另外，人们开始越来越多地依赖 ChatGPT 来解决各种问题，这是另一个正在发生的趋势。
▶ 英文原文 ⏱
They're giving you answers that are custom tailored to what you're doing and what you're asking about and what it knows about you. That actually introducing ads has been done very deftly. I've actually been really impressed with the open AI rollout of ads when I've actually ever seen an ad. It's very clearly labeled and it actually feels like a natural ad to the conversation that I'm having. And I think we're also, you know, one of the other shifts is people are starting to rely on, you know, ChatGPT a lot more for a lot more queries.
过去，人们可能主要是用它来查找事实、了解某件事情的历史或者帮助完成作业。那些不一定涉及解决问题和我们正在宣传的内容。但现在，人们使用它是为了寻求实际的建议，比如购物或者确定自己想去哪里、想做什么。当你处于探索模式时，那些情况是很好的机会，此时广告实际上往往是一个帮助解决问题的好答案。
▶ 英文原文 ⏱
It might've used to have been like, look up a fact or tell me the history of this thing or help me with my homework. Not necessarily problem solving and things we're advertising, but now people are going into it for real advice or shopping or trying to figure out exactly, you know, where they want to go or what they want to do. And those are great opportunities when you're in a discovery mode where ads are actually often a great answer to help you solve that.
因此，很多这类商业查询和商业意图也促成了这一点。但这必须非常巧妙地完成，而不是像我正在经历的这种奇怪且让人不悦的个人体验，把广告强行塞到对话中。我很想知道广告的单位经济效益是如何运作的，比如它可能是一种成本较低的问题，相较于编程或图像生成这样的技术。所以，对于OpenAI来说，他们在广告上的利润率是怎样的，这是一个非常有趣的问题。
▶ 英文原文 ⏱
And so a lot more of these commercial queries and these commercial intent creates that too. But again, it has to be done very, very deftly. Not this weird, interruptive, very personal experience I'm having that ads just get shoved into the conversation. Yeah, I'd be super curious to how the unit economics on ads work, like presumably it's a lower cost question or lower cost compared to, you know, the coding or something like that or image gen. So, so for open AI, you know, what, what kinds of margins are they seeing on ads is a super interesting question.
嗯，我也很好奇，Josh，你看到的是哪种广告？因为我完全没有看到任何广告。我想是因为我用的是企业版本，你用的是专业版，对吧？企业版所以我们没有广告。你知道吗，我最近在做旅行研究，要在纽约待几天，然后就开始看到一些关于纽约活动的广告，看到这些我可能会感兴趣的活动对我来说真的很有用。
▶ 英文原文 ⏱
Yeah. Um, I curious also, Josh, but what kind of ads do you see? Because I, I don't get any ads, I guess, I, I, I guess I use enterprise. You're on a pro plan, yeah. Enterprise, so, so we don't, yeah, yeah. You know, I, I was doing a bunch of travel research recently and, um, was, was going to be in New York for a few days. And I just started seeing some ads for a couple of things that were going on in New York that I might have wanted to do. And I just found that really useful.
我已经开始更多地将它用于商业购物。我当时在寻找一种特别的钥匙扣，这种钥匙扣可以很方便地分离出代客泊车钥匙。但是，我在谷歌上找这个东西时遇到了一些困难。最后，我想，不如去问问ChatGPT。我跟它来回描述了一下我想要的东西，它给我提供了一些很好的例子。最后，我还说希望能找到一个在美国制造的钥匙扣。结果，我发现了一款非常棒的选择，是来自底特律一家工厂的产品，这家工厂还制作了很多其他金属制品，真是为我找到了一个很酷的钥匙扣。
▶ 英文原文 ⏱
And like, I've started using it more for commercial shopping. I was looking for a, a special, um, key chain that would have a really easy separation for a valet key. And I was having trouble finding this actually on Google. And I finally was like, let me just go ask Tachi BT. And I went back and forth and I was describing what I wanted and start giving me some really good examples. And at the end, I was like, great. And I'd also love one that's made in America. And I actually found this incredible, like, option from a factory in Detroit that often makes a lot of other metal work and other stuff that had this, like, really cool key for me.
这件事很有趣，如果我没有机会来回交流并真正进行那次对话的话，这可能不会发生。在那次对话中没有出现任何广告，但如果有广告的话，它们可能会帮助我找到一些东西。最后，我访问了一个网站，并且之前从未听说过这家公司，这次经历非常棒，非常有趣。
▶ 英文原文 ⏱
And it, like, it was one of those things that if I had never had that chance to really go back and forth and actually have that conversation. And if there had been other ads that, no ads were presented in that conversation, but it was entirely open for ads that they would have helped me find stuff. And eventually I went to this website and eventually I had never heard of that company before, um, and it was a great experience. So interesting.
我觉得我们可能会看到，随着他们投入更多精力，OpenAI的精准定位能力会变得非常强，甚至可能超过之前被认为是行业佼佼者的Meta。Meta之所以厉害，是因为他们对你的了解非常多，而OpenAI好像是和你进行实时对话。我确实认为这会帮助ChatGPT，同时也会支持很多更专注的、几乎是行业细分的消费者AI产品。
▶ 英文原文 ⏱
I feel like we may see, as they lean into it, open AI, uh, being able to do crazy good targeting, uh, like even better than I think Meta, which previously was like best in class for this just because they knew so much about you. But like you're having this live conversation with them. I do think that it'll help ChatGPT, but also I think it will also support a lot of these more focused, almost verticalized, to use the enterprise term, consumer AI products.
另一家公司在广告方面取得了早期成功，这家公司叫做Open Evidence，它是一个面向医生的 AI 产品。目前，该产品已经覆盖了美国50%到60%的医生。这种对高价值观众的高度覆盖率非常有利，因为用户都是医生，所以广告投放可以非常有针对性。我认为这样的情况会越来越多，而且这是应该发生的趋势。
▶ 英文原文 ⏱
So, another company that has seen early success in ads is Open Evidence, which is, um, an AI product for doctors. And it already has 50, I think the most recent numbers were 50 to 60% density of US, all, of all US physicians on the product. And so when you have that kind of density of a really valuable audience, and it's like a targeted audience because you know they're physicians, you can, I think, advertise really effectively. And there will be and should be more of those, I think.
这段话提到是否值得暂停一下，讨论有关OpenAI、Anthropic和Gemini这些公司。这些公司和实验室几乎从一开始就在名单上。我们有没有看到人们支付这些产品的方式有任何演变？我们能推测出这三者的不同用户类型有什么区别吗？非常好奇你发现了什么。
▶ 英文原文 ⏱
Is it worth talking and taking a step back and talking about, uh, Open AI, Anthropic, and Gemini and sort of, these are companies, these are labs that have been on the list pretty much since the beginning. Um, are we seeing any kind of evolution in the way people are paying for these products? Um, what can we surmise about the different kinds of users of all three? Uh, super, super curious what you're, what you're seeing.
是的，完全正确。从我们第一次做这个报告开始，主要结论就是：在消费者方面，ChatGPT在使用量和收入上都是全球领先的。这一点依然是真实的。在ChatGPT之下的产品似乎有更多的变化和动荡。现在，ChatGPT在网络使用方面，领先于Claude大约6倍，领先于Gemini大约2倍。考虑到许多活跃用户都是付费用户，未来在收入方面的数据可能更有参考价值。
▶ 英文原文 ⏱
Yeah, absolutely. Um, from the very first time we did this report, the main conclusion was, like, ChatGPT is the dominant global user by both usage and revenue on the consumer side. That continues to be true. Everything below ChatGPT has seen, I think, more movements and more shakeups. So, ChatGPT is now ahead of Claude, um, around 6x on the web, around 2x, uh, ahead of Gemini on the web. Probably going forward, given a lot of usage is concentrated in these power users who are paying, um, the revenue numbers could be even more useful here.
嗯，也许这份报告中让我感到最惊讶的一点是，我们看到在美国用户中，Claude的付费订阅用户数量实际上已经超过了Gemini。这有点不可思议，因为Gemini拥有更大的安装和用户基础，还有像Google这样的自然分发机制。我认为这对于Anthropic来说无疑是一个重大的成就。
▶ 英文原文 ⏱
Um, and probably that's one of the biggest surprises to me in this report was we got a panel of U.S. spenders, and Claude has actually passed Gemini in terms of number of paid subscribers. Which is kind of crazy given Gemini has a much bigger install base and user base overall, and it also has, like, the natural distribution mechanism of something like a Google. I think that's a big, you know, accomplishment, of course, for Anthropic.
我认为这是因为他们在过去几个月推出了一系列非常成功的产品，比如Claude Design。此外，他们也获得了更多媒体的关注，尤其是从他们与国防部相关的事情开始，大概是在二月份。我还想说，这些产品在变现方式上也存在主要区别。当然，ChatGPT在变现方面还是遥遥领先。他们在美国的付费用户比Gemini和Claude加起来多三倍左右。然而，Anthropic则非常著名地表示不做广告，所以他们对订阅非常积极。大约有7.5%的用户选择每月100美元以上的最高订阅计划，而ChatGPT和Gemini这两个平台的类似用户仅占1%左右。因此，即便是在付费用户群中，这些用户看起来也有所不同，他们在产品上的使用方式亦有所不同。
▶ 英文原文 ⏱
I think it's come on the wave of a bunch of very successful products that they've launched over the last few months, like Claude Design. Uh, it's also come from a lot more press that they've had, starting with the Department of War stuff all the way back in, I think it was February. Um, the other main difference, I would say, in how these products are monetizing, and again, ChatGPT is still far in the lead by monetization. They have around three times more paid consumer subscribers in the U.S. than both Gemini and Claude. Um, but Anthropic has said, very famously, no ads. So they're much more aggressive about subscription. They have around seven and a half percent of subscribers on the hundred dollar plus per month, like the max plan. And that's like one percent for both ChatGPT and Gemini. And so those users naturally look different and are doing different things on the product, even in that paid user base.
我们该谈谈创意工具吗？当然。嗯，我觉得有趣的一点是所有大型实验室在创意工具方面都做得很好。是的。实际上，像Anthropic这样一个团队，虽然曾经以没有参与这方面而闻名，但最终还是成功地实现了，这就是创建图像模型或视频模型。不过，如今人们也在利用编码来创建图像和视频，因为编码在制作图像和视频方面表现得非常出色。所以有趣的是，他们并没有构建一个扩散模型，却仍然能够生成图像。关于纯粹的创意工具，那些在该领域垂直发展的公司，我们可以看到什么呢？创意工具在谁在哪里取得成功方面分布得非常有趣。
▶ 英文原文 ⏱
Should we talk about creative tools? Yeah. And, um, I think one thing that's interesting is actually all of the big labs have gotten really good at creative tools. Yes. And one thing that actually, like, Anthropic kind of famously abstained from, but then somehow achieves anyway, was like creating an image model or video model. But now people are making images and videos because coding is so good at creating, like, images and videos. Um, so it's interesting that, you know, they didn't build a diffusion model. Yeah, they're still capable of doing, uh, image gen. But about the pure creative tools, the companies that have kind of, like, verticalized in that category, what are we seeing? Creative tools is very interestingly distributed in terms of who is succeeding where.
有几类创作者工具，或者说“形式”可能更合适，是实验室因为很多原因没有集中精力和注意力的方面。其中很多都与音频相关，比如文本转语音和音乐。Eleven Labs 和 Suno 在我们的访问量榜单上排名非常靠前，并且在支出榜单上也名列前茅。实验室有很多事情要做：他们在构建编程代理，他们在开发通用人工智能。在这个时候，是否合理让他们处理 Suno 遇到的所有知识产权问题，并推出一个竞争性的音乐模型？我不确定。与此同时，Suno 已经能够跑出一个非常强劲的领先优势。而且，我坚信实验室会继续做他们的事情，并不断成长。
▶ 英文原文 ⏱
So there's a few categories of creator tools, or maybe modalities is the better term, where the labs have not focused energy and attention for many reasons we could discuss. Uh, a lot of those are around audio. So, like, text-to-speech, music. Eleven Labs and Suno are now very reliably near the top of our traffic lists and are also ranked very highly in our spend list. The labs have so many things to do. They're building coding agents, they're building AGI. Does it make sense at this point for them to deal with all of the IP headaches that Suno has had to go through and launch a competing music model? I don't know. And in the meantime, Suno has been able to kind of run away with a really strong lead. And, you know, I'm a big believer that, you know, the labs are going to do what they're going to do and they're going to keep growing.
它们显然是所有事情的良好基准。但在许多市场中，你会发现一些非常专业化的产品，这些产品非常专注于了解自己的受众和需求，从而能够打造出真正定制化的东西。比如说，如果你只是想为乐趣或者认真制作音乐，Suno 是一个不可思议的工具，从你开始使用到结束，它都能给你带来良好的体验。如果你在制作中需要加入语音和音频，Eleven Labs 拥有一种完全不同的交互和工作方式。当你观察众多视频工具，或者即使是像 Figma 这样的设计工具时，它们都是为了帮助你深刻地表达自我而精心设计的。
▶ 英文原文 ⏱
And they obviously are great baselines for everything. But in so many of these markets, you're seeing really specialized products that are really focused, knowing who their audience is and what they're doing, that's able to build really custom things. You know, if you want to make music just for fun or for something that you're really producing, Suno is an incredible tool and it speaks to you from the moment you start using it through the end. You know, Eleven Labs, if you need voice and audio within the product that you're making, it just has a way of working and interacting with it that feels completely different. When you look at a bunch of the video tools, you know, when you look at design tools, even like Figma, like they're so designed to use deeply for the thing you're trying to express yourself.
它针对的是设计师，而不是那些想要跳过设计步骤的人。我认为，我们会从这些真正定制化的界面中看到更多的价值。这些界面的软件层不仅限于模型，还涵盖你能做的事情、你能保存的内容以及与你互动的方式，这才是真正的价值所在。 是的，这是我认为的第二类创意工具，也就是与音频不同的图像和视频。关于图像，正如你所说，OpenAI 在图像方面确实表现得相当出色。比如图像2.0在图像创建和编辑方面都非常优秀。当然，谷歌通过各种版本的Nano、Banana和Vio，坦白说，已经吸引了大量本来会使用这些独立图像生成器的高层次消费者流量。
▶ 英文原文 ⏱
And it speaks to designers, not to people who, you know, want to just skip that step. And I think we're going to see so much more value from these really bespoke interfaces where the software layer of all the things you can do and the things you save and the way you interact with it become really where the value sits, not just the models. Yes. So this is the second category, I think, of creative tools, which is images and video that looks different from audio. On images, I think to your point, like OpenAI has really leaned into images quite successfully. Like images 2.0 is very, very good, both for image creation and editing. And then of course Google with the various iterations of Nano, Banana and Vio, I think they have candidly taken away a lot of the high level consumer traffic that was previously going to these standalone image generators.
因此，MidJourney 在我们的首次排名中相当靠前。但现在在流量排名中已经完全跌出了榜单。不过，就你提到的核心用户而言，如果你看收入排名，MidJourney 又回来了。这说明核心用户仍然希望选择他们觉得有品味、有审美，并且能够以非常具体的方式进行调整的模型。这就引出了视频这个话题，在我看来，这有点像是一个未知的领域，因为中国公司可以使用任何数据进行训练，确实有很大的优势。视频的生成非常复杂，包括视觉、声音、视觉和声音的同步及其外观。因此我认为，训练数据越多，效果就越好。
▶ 英文原文 ⏱
So like MidJourney was fairly high on our first ever rankings. It has fallen off the traffic rankings completely. But to your point in power users, if you look at the revenue rankings, MidJourney is back. So the power users still want the model that they feel has taste, has an aesthetic sense, and that they're able to tune in a really specific way. And then that brings us to video, which to me is kind of like a wild frontier right now because Chinese companies that can train on any data and do have a real advantage. Video is just so complex to generate with like the visual, the sound, the visual and the sound synced and looking a specific way that I think like the more data you have to train the better.
他们在那里一直以来都很成功。我认为在创意工具方面，更广泛而言，我很好奇你们俩是否有类似的经历。我最近开始让Astra和其他强大的模型为我生成或编辑创意作品，这些模型做得非常出色，它们可以从互联网上的其他地方获取工具。所以我认为那些对代理友好并易于访问的创意工具，将会越来越受到支持。是的，是的。事实上，这真的很神奇，你只需让一个代理去做，告诉它可以安装任何它想要的东西。我实际上让Astra和5.5正面较量，为我制作了一些动画，它们就好像立即知道该怎么做。没错。
▶ 英文原文 ⏱
They've been successful there thus far. I think more broadly in creative tools, I'd be curious if either of you have experienced this, but I have recently been asking Astra and other really powerful models to generate or create, generate or edit creative for me. And it does a very, very good job and it will go tool call to elsewhere on the internet. And so I think that creative tools that are agent friendly and agent accessible are gonna increasingly see really compelling tailwinds. Yeah. Yeah. It's actually crazy what you can do if you just like empower an agent and just say like, yeah, install whatever you want to install. Um, I had it, I actually had, uh, Astra and 5.5 go like head to head and animating some stuff for me and like, it was just like I knew exactly what to do. It's like, yeah. So.
我喜欢的是，那些善于钻研的创新者正在探索这些功能。在接下来的一年里，我们将打造一些新产品，这些产品将在这些榜单上出现，因为它们能够将复杂的功能打包，使其非常易于使用。 是的，当我想到所有AI与消费者AI之间的差距时，正是这种把复杂功能打包并创造优秀产品体验的趋势，真正让AI成为持久的技术。
▶ 英文原文 ⏱
And what I love about this is, you know, this is the tinkerers, the people at the edge are figuring out these capabilities and we're gonna build products over the next year that are gonna show up on these lists because they're gonna take all of this complexity of what you can do and package it up in a way that makes it really easy to use. Yeah. And like that's this, you know, when I think of this gap of like all AI versus consumer AI, it's exactly this, this movement of packaging these up and building great product experiences. Yeah. That really turns it into, into these things that sustain.
好的。好的。好的。我想大概事情都是从那些爱折腾的发明家开始的，然后他们把自己的创意发布在X（可能是一个社交平台）上。然后，大约六个月后，我们就能看到一个成熟的产品或者一家创业公司从中诞生，或者说，有十几家创业公司在竞争。除了网络方面的产品之外，还出现了许多成熟的产品，比如Granola, Whisper Flow, Superhuman等等。你在这方面看到了什么？还有那些存在于聊天和消息领域的产品。
▶ 英文原文 ⏱
Yeah. Yeah. Yeah. And I guess it has to start with the tinkerers and then they post on X and then, you know, six months later we get a real like product and startup out of it or like, you know, 12 different startups all competing. Outside of the web window, there have been a, a big proliferation of, of mature products. So there's granola, there's whisper flow, there's superhuman. Um, what, what are you kind of seeing there? And then obviously the ones that exist in chat and messaging.
好的，那么一种直觉。嗯，当谈到分销时，您看到了什么？以及当谈到他们接触的产品类型和用户时，您看到了什么？我认为这里可能有两个有趣的线索可以探讨。首先，我写了一个可能在六到九个月前的文章，标题是“大扩张”，基本上探讨的是为什么消费类公司如此迅速地转型为企业公司。比如CREA、Replit、Eleven Labs、Gamma这些产品，以前像Canva这样的公司花了六年多的时间才真正获得团队和企业收入。
▶ 英文原文 ⏱
Yeah. So an instinct. Um, what are you seeing when it comes to distribution and what are you seeing just when it comes to the kinds of products and users that they're approaching? Yeah. I think there's two maybe interesting threads to pull on here. One, I, I wrote this piece called maybe six, nine months ago called the great expansion, which is basically like, why are consumer companies becoming enterprise companies so quickly? Uh, like things like, uh, CREA, you know, Replit, um, Eleven Labs, Gamma, these products previously, like Canva took six plus years to have real team and enterprise revenue.
他们通过PLG（产品驱动增长）取得了巨大的成功。Whisper Flow和Granola就是很好的例子。由于它们与工作效率相关，它们很快被企业所采用。于是创始人们就意识到，他们需要添加隐私、安全和团队计划功能，但这种策略非常有效，成本也很低。这种方法对那些既可以个人使用，又与工作相关的软件工具非常有用。我认为，像Whisper Flow、Granola和Superhuman这样的产品很好地体现了一种普遍趋势，即现有企业不愿意或无法改变和发展他们现有的产品界面。
▶ 英文原文 ⏱
And what's happening is that they're very successful in growing via PLG. Whisper flow and granola are another great examples there. And then because they are kind of work productivity related, they get pulled into enterprises. And then the founders are like, oh, we got to add privacy and security and team plan, but it's very effective, very low cost distribution. And again, it works really well for these tools that are, can be used personally, but are like work adjacent. Um, I think things like whisper flow and granola and superhuman are another good example of this trend we've seen in general, which is incumbents being unwilling or unable to cannibalize their existing interfaces.
这方面的典型例子就是谷歌。就像我们并没有真正看到他们在AI时代重新发明文档、Gmail或日历。我认为OpenAI和Anthropic也面临类似的情况，他们在推出不属于现有的ChatGPT、Codex或Cloud等界面之外的产品时，成功率要低得多。而且，我知道他们中的许多人都尝试孵化出能颠覆这些领域的初创公司，但我觉得从产品角度来看，在他们已经有很多事务要处理的情况下，要想突破创新是很困难的。
▶ 英文原文 ⏱
The classic example of this is Google. Like we haven't really seen them reinvent docs or Gmail or calendar for the AI age. I think it's even happening with OpenAI and Anthropic where they have been much less successful in anything that is not a launch within their existing ChatGPT or Codex or Cloud or Cloud Code interfaces. Um, so, and I know many of them have, you know, attempted to incubate killers for these many startups, but I think it is, um, difficult from a product perspective for them to innovate beyond that, especially when they have so many other things on their plates.
我的意思是，我认为这些都是真的。我觉得，随着我们逐渐习惯一些界面，我们仍然处于一个令人难以置信的重塑时期。过去一年到一年半的增长很多是因为模型变得更好了。是的，模型变得更好了。因此，那些花时间创造出这些易于使用、自然且方便分享的界面的人，现在的工作变得更加重要。像whisper flow和granola这样的工具，真的很容易上手，也很容易让你的团队参与进来。
▶ 英文原文 ⏱
I mean, I think all that's true. And I think, you know, we now, as we get used to some interfaces, we're just still in such a period of incredible reinvention. Like a lot of the reason we've seen so much growth over the past year, year and a half is the models got so much better. Yeah. And the models got so much better. So the people who had been spending time creating these incredible interfaces that were easy to use, that were, that were natural, that were, you know, easy to share and get a bunch of your team on and, you know, whisper flow and granola were just so easy to get started with.
你可能会说，天哪，随着模型变得越来越好，产品的性能和实用性也得到了极大的提升。这样一来，我们就处于一种奇妙的状况下：你构建了一件很棒的东西，但它可能无法完全实现你想要的所有功能，因为当时模型的能力还不够强。然后，随着模型的进步，你的产品需求和实用性也随之爆发式增长，这种良性循环让一切都有所提升。因此，认为只有一两家公司能构建这种体验层的看法，我认为这份报告已经推翻了。
▶ 英文原文 ⏱
You then would say, oh my gosh, now they've gotten so much better as the models have gotten better that the products, the utility gets so much better too. And so we're kind of this, this incredible, you build something great, but it may not do everything you want because the model capabilities weren't quite there. Then the models get better and your product gets to explode in demand and utility and this kind of rising tide lifts everything. And so to think that, you know, we only have one or two companies that can build that experience layer, I think is what this sort of report sort of debunks.
这确实是一些在这些普遍应用案例中的顶尖公司，但我们可以看到，许多其他事物正在快速增长的原因在于，很多界面正在被重新发明，而且整体发展促进了所有事物的进步。基础设施的价值可能仍会流向模型提供者，或者流向为推理服务的其他事物，这里有很多值得讨论的地方。但消费者采纳的，是那些对他们有用并且容易使用、能融入他们生活的产品。是的，也许为了继续为创业公司辩护，像OpenAI和Anthropic在很多方面也是创业公司，但它们已经成功到成为拥有上千名员工的大公司。就像一艘大船，更难以转向或快速调整。
▶ 英文原文 ⏱
Now those are certainly some of the top companies in these very general use cases, but it's, you know, the reason that so many other things are growing is there's so many interfaces that get to be reinvented and, and the sort of rising tide lifts everything. And then, you know, the infra value may still go to the model providers or may go to the other things that are serving inference. And there's a whole different conversation there, but what consumers are adopting are things that work for them and are easy to, to use and bring into their lives. Yeah. Maybe to also make the, to continue to make the case for startups here, OpenAI and Anthropic in many ways are startups, but they have been so successful that they have become big companies with thousands of people. And there are just so many extra considerate, like a larger ship is harder to kind of steer or to turn around.
我认为这次在我们的收入名单上的公司之一是Plod，这是一种人工智能记录设备。它最初在中国和东亚开始，现在已经进入美国市场。你可以购买这款设备，也可以购买订阅服务。OpenAI 也能并将会做硬件设备，但正如我们看到的，对于大公司来说，事情往往需要更长的时间，因为需要与其他现有产品整合，还需要经过更多的审核和平衡。因此，我确实认为那些大型实验室会继续非常成功，并且还有许多事情可以做。同时，我认为创业公司将继续能够找到这些相当大的机会窗口。
▶ 英文原文 ⏱
And so I think that's like one of the companies on our revenue list this time is Plod, which is an AI note taker device. Um, that started kind of in China in the East and now has come to the U.S. and you buy the device and you can also buy a subscription. Um, opening AI can and will do a hardware device, but as we've seen with them, it just, everything takes longer. When you're a big company, uh, you have to integrate with maybe other existing products. There's more checks and balances. It has to go through. So I do think that the big labs will continue to be very, very successful and there's a lot more for them to do. And I think that startups will continue to be able to find these quite big windows of opportunity.
是的，是的。听起来对于初创公司来说，关键问题在于如何打造一种随着模型的进步而提升的产品，同时又能避免被模型的进步所"吞噬"。这确实是一个有趣的平衡点。我几个月前加入Andreessen Horowitz（安德森·霍洛维茨）时非常兴奋，部分原因是我相信现在的价值确实回到了软件层面。因为我们拥有了这些令人惊叹的模型，并能加以利用，因此可以构建能够充分利用这些模型的丰富产品。而且还有像TypeSafe的Jev这样的新创新，即使开发者也可以用全新的方式来构建产品。
▶ 英文原文 ⏱
Yeah. Yeah. And it also sounds like the, the question for startups is how do you build a product that as you said, Josh, gets better as models get better, but doesn't get cannibalized as models get better. Yes. Um, which is, you know, what it like, like an interesting kind of sweet spot to exist in. I mean, part of the reason that I was so excited to join Andreessen Horowitz a couple months ago was this belief that the value really now is moving back to the software layer. That now that we have these incredible models at our, you know, capabilities and we can access them, you can build really rich products that leverage the models to do it. You know, and there's new innovations like, you know, Jev from TypeSafe that allows even developers to build things in even new ways.
当你能够使用这样一个快速、易于集成并能够提供代码和结构化答案的模型时，我们还没有看到所有可以实现的令人难以置信的新想法。因此，创造力又回到了体验、你可以构建的网络、你能够服务和团结众多人的方式，这些都可以通过模型变得更加强大，而背景和社区真正成为了资产。有如此多的创新机会，我认为几乎每个类别都有机会被重新发明。一些大公司能够顺利转型，并在人工智能时代成为其行业的重要公司，但并不是所有公司都能做到。这就是初创公司发挥作用的地方，它们可以抢先一步，真正创造出最佳的新体验。
▶ 英文原文 ⏱
And we haven't even seen all the incredible new ideas that can be done when you have access to a model like that, that's fast, that's easy to integrate, that, you know, gives you code, you know, are very structured answers back. Um, and so because of that, now the creativity is back to the experience, the network you can build, the ways that you can serve a lot of people and bring them together using the models to be something powerful, but the context and the community really becomes the asset. And there's so much invention. And I think almost every category has the chance to be reinvented. And, you know, some big companies are going to be able to make the leap and become the relevant company for their sector in the AI era, but not all of them will. And that's where startups come in to kind of beat them to that punch and really be the best new possible experience.
是的。是的。我赞同这一点，我常常思考如何积累个人价值，并希望最终实现多用户价值的积累，这些价值将锁定在某些初创产品中。我举一个例子，比如 Towne，它更倾向于面向专业消费者的助理工具。Towne 能够连接到你的所有系统，比如 Slack、电子邮件、Google Drive，理解你和你的组织的背景，然后为你执行任务。我用它来撰写很多邮件，协助完成许多报告。我知道人们很容易就把这些工具看作是一种包装，只不过现在这种包装有了一个稍微不那么贬义的称呼："外壳"。
▶ 英文原文 ⏱
Yeah. Yeah. I think to that point, I think a lot about compounding personal value and hopefully eventually compounding multiplayer value that becomes like a lock in to some of these startup products. One example I would give is Towne, which is more on the prosumer end of the agent assistant. It can connect into all your systems, Slack, email, Google Drive, understand kind of the context of you and your org, and then do things for you. Like I use it to write a lot of my emails, helped with a lot of this report. And I know it's easy for people to dismiss things like this as like, oh, it's just a harness, which is now the slightly less derogatory term for wrapper, I guess.
好的，但Towne已经建立了关于我的个性和风格的“剧本”，这是其他产品所没有的，而且我很难将其轻松地迁移到未来可能出现的其他产品上。因为一封听起来99.9%像我写的邮件和一封听起来85%像我写的邮件之间的差别，是只需花10秒钟来修改与花10多分钟来修改的区别。因此，我认为我们会看到更多像Towne这样的产品，它们能很好地收集上下文并利用这些信息来围绕用户创建“剧本”，这些产品将会继续取得成功。是的，我完全同意这一点。
▶ 英文原文 ⏱
Yeah. But Towne has built these playbooks of who I am, what I sound like, that no other product has, and that I cannot easily take and migrate over to something that comes along tomorrow. Because the difference between an email that is 99.9% sounds like me and even an email that's 85% sounds like me is the difference between spending like 10 seconds to fix it and like 10 plus minutes. And so I think that we'll see more products like Towne that do a really good job of collecting context and acting on that context to build playbooks around you continue to be successful. No, I think that's totally right.
我尽量避免使用"工具"和"包装器"这样的词汇。是的，因为我认为，现在人们正在开发软件；他们构建的是非常丰富的产品。他们可能会用智能代理来编写部分代码，但当他们将整个体验交付给用户时，实际上远不仅仅是给模型加个简单的外壳或工具来提供一些背景信息。事实上，这是一种非常丰富的产品和体验，而模型只是使其得以实现的一部分。我认为这正是令人兴奋之处，也是我们在名单中将要看到的方向。许多公司已经在这样做，而我们认为下一波浪潮中，这些公司会创造出更多的价值，模型只是其中的一部分。
▶ 英文原文 ⏱
And I try to avoid using words like harness and wrapper. Yes. Because I think the reality is people are now building software and they're building these really rich products and they're, you know, they might be using their agents to write some of that code, but they're actually, when they're delivering this whole experience to a user, it is much more than just a shim on the model or a harness that brings some context to the model. It's actually a really rich product and an experience that happens to now use a model as part of what makes them able to deliver that. And I think that's really the excitement of where that's going to, you know, what we're going to see on this list, you know, many of these already are doing that. And we think really the next wave, they're all going to be these companies that have built so much more value. And the model is something that is, you know, just one piece. Yeah.
Olivia，我认为你之前提到过这个图表，但或许我们可以再看看，它展示了在Web 2和前AI时代仍然存在的所有产品类别中的空白。也许你可以讲一讲这些类别以及其中的巨大机会在哪里？目前，大多数普通消费者基本上还在使用AI替代搜索产品，比如谷歌。特别是在教育应用方面，孩子们可能用它来写论文，这就稍微扩大了一些使用范围。更多是帮助做作业，而不是完全替代作业。是的，不能完全替代作业。还有人用在工作场合写邮件。但如果你看看这个图表，你会发现，迄今为止大多数成功的初创企业都围绕着完成任务这一主题展开。
▶ 英文原文 ⏱
Olivia, I think you referenced this, this chart that you made, but maybe we can bring it up is all of the white space that still exists for, you know, just all the product categories that exist in Web 2 and the pre-AI age. And maybe you can just talk through some of these categories and where are the big opportunities? Yeah. The vast majority of pure consumers are basically using AI still as a replacement for search products. Things like Google. Maybe, especially as you get into education use cases, kids are using it to write essays. A little bit more of an expansive use case. Homework health. Not homework replacement. Exactly. Not homework replacement. Yes. Or people in the workplace to write emails. But if you look at this chart, which will show almost all of the kind of areas where we've seen startups succeed thus far have been in and around that theme of getting things done.
就像生产力、照片和视频设计与编辑、搜索和问答等领域。有很多类别的市场尚未饱和。我会说，其中许多类别可以称为网络类别，因为它们需要多用户产品。比如说，我们还没有看到在约会领域的突破。目前确实有一些初创公司正在尝试，我希望并相信它们将来会被纳入我们的关注名单，但现在还没有人在约会领域入选。招聘也是一个类似的例子。在我看来，约会和招聘其实有些相似，都是需要进行匹配的网络。至于社交AI，我们还没有看到什么真正起飞的项目。大多数所谓的社交AI，只是人们在现有社交平台上发布AI生成的内容。
▶ 英文原文 ⏱
So like productivity, photo and video design and editing, search and answers. So many categories are wide open. And many of those categories are, I would say, I would call them network categories where you need a multiplayer product. You know, dating is one we haven't seen. There are certainly startups there that I hope and believe will make future additions of the list, but there's no one on the list doing dating now. Recruiting is another one. I think of dating and recruiting as somewhat similar networks, actually, in terms of trying to make matches. Social AI, we really haven't seen anything take off. Most of social AI is people posting AI-generated content on existing social platforms.
然后，我认为还有其他一些类别，这些类别可能更像是过去的市场，比如购物、买房以及零售业。我们需要观察这些类别是否会融入像Instinct或Muse这样的代理中，或者作为独立的产品存在。接下来的发展方向可能有很多，可能会是独立产品，也可能是两者的结合。或者将来你的代理可能会联系AI原生的市场。因此，我对这些事情非常期待。我还认为，像游戏和娱乐这样的类别也很有潜力。目前，模型还不足以制作出大众喜欢观看的内容，除了正在流行的AI微型剧可能是个例外。但我认为这也是即将到来的趋势。
▶ 英文原文 ⏱
And then I think there's all of these other categories that are, look maybe more like marketplaces did, like shopping, home buying, you know, retail. We'll have to see if those end up living in agents like Instinct or Muse or living as standalone products. The next ones. Or the next ones, which there will be many. Or living as standalone products or perhaps a mix of both. Perhaps your agent is calling the AI-native marketplace. So I'm very excited about those things. I think also categories like gaming and entertainment. The models just have not been good enough to produce content that the average person likes to watch, which may be the exception of AI micro dramas, which are blowing up. But I think that is coming soon, too.
不，我认为这完全正确。我觉得我们现在处在一个很激动人心的时代，比如Chatsubuti通过把事情变成对话的方式引起了我们的极大兴趣。现在，我们的消息应用中可以有这样的智能助手，让它们变得更加互动。这是一个不可思议的新模式。但是，当你在购物时，你希望能够目视地查看选项、探索并定制，这样你可以说“我很喜欢这个，但是希望它的领子上有一些滚边”之类的话。AI可以帮助你实现这些愿望，甚至可能为你定制制作。我喜欢购物，因为其中充满了许多创意和革新。
▶ 英文原文 ⏱
No, I think that's exactly right. And I just think we're in this world where, you know, we're kind of like so excited by what Chatsubuti did with turning things into conversation. And now these agents, we can get in our messaging apps to turn them into more conversation. It's an incredible paradigm. But when you're shopping, you want to visually see options and explore and have things customized for you and be able to say, I really like that, but I wish it had some piping on the collar or something. And actually have AI helped you both realize that and maybe even get it made for you. I like shopping and have so much invention there.
娱乐。我认为我们才刚刚开始探索讲述更好故事的能力，以及赋予人们成为更优秀的故事讲述者的方式，从而创造出这些令人惊叹的故事消费网络。你知道，抖音就是一个绝妙的平台，人们在这里聚集，只需制作一些小视频。你会看到世界各地的人们，你现在可以观看他们，但仍有很多想法在人们脑海中，如果他们能更好地表达这些想法，将会对他们有帮助。我们将拥有一个非凡的新网络。因此，我觉得我们正处于所有这些领域的临界点，我们需要更好的模型来实现这一点。
▶ 英文原文 ⏱
Entertainment. I think we've barely started scratching the surface of the ability to tell better stories of the way to empower people to be better storytellers that then creates these incredible networks of people consuming stories. You know, TikTok was this incredible place where people came together and just create little videos. You see people around the world that you're now watching, but there's still so much capturing people's heads that if only they could express their ideas even better, it is going to help them. We're going to have an incredible new network. So I feel like we are just at the cusp of all these categories and we've needed the models to get better.
这样你就可以开始涉足这些想法并进行创新。但在未来几年内，随着新模型功能的出现，我仍然认为价值最终会体现在软件层和产品上。对我来说，这又回到了我们之前讨论过的话题，即产品是帮助人们节省时间还是消磨时间。在我们看到的几乎所有消费级人工智能中，都是在节省时间。
▶ 英文原文 ⏱
So that you could start to dabble in some of these ideas and invent them. But as that happens over the coming years and with the new model capabilities, I still think the value is going to end up in this software layer and the products. Yeah. To me, this gets back to what we were talking about of products that help people save time versus spend time. Almost everything we've seen in consumer AI is saved time.
那些投入时间和精力的公司，往往最终成为最大型的企业之一，甚至是最大的一家。是的。因此，我们需要这样的存在。我相信现在一定有许多创业者正在努力创新。完全同意。我认为这是一个很好的结束语。非常感谢你们的加入。
▶ 英文原文 ⏱
And that spend time, those end up often actually being amongst the biggest companies, if not the biggest ones. Yeah. And so we need that to exist. And many, many builders, I'm sure, are tinkering away on that right now. Absolutely. Absolutely. I think that's a great note to end on. Thank you both so much for joining.
一定要查看《消费者AI应用程序Top 100》第七版。谢谢。是的，谢谢邀请我们。我们会在第八版见到你。是的，是的。
▶ 英文原文 ⏱
And absolutely make sure to check out the Top 100 Consumer AI Apps, 7th Edition. Thank you. Yes. Thanks for having us. We will see you for Edition 8. Yes. Yes.