将决定消费级AI战争的重大问题

今天在AI每日简报中，塑造消费者AI竞争格局的核心问题。

Today on the AI Daily Brief, the big question shaping the battle for consumer AI.

在此之前，先看头条新闻：OpenAI会成为新的GitHub吗？

And before that in the headlines, is OpenAI the new GitHub?

《AI每日简报》是一档每日播客和视频节目，聚焦AI领域最重要的新闻与讨论。

The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.

好了，朋友们，在深入正题前，先做几个快速公告。

All right, friends, quick announcements before we dive in.

首先，感谢今天的赞助商：普华永道、AI UC、Blitzy和Mercury。

First of all, thank you to today's sponsors, KPMG, AI UC, Blitzy, and Mercury.

如需收听无广告版本，请访问patreon.com/aideallybrief，或在Apple播客上订阅。

To get an ad free version of the show, go to patreon.com/aideallybrief, or you can subscribe on Apple Podcasts.

如需了解节目赞助事宜，请发送邮件至sponsorsaidailybrief.dot.ai。

To learn about sponsoring the show, send us a note at sponsorsaidailybrief dot ai.

最后，还有两件小事需要提醒大家。

Lastly, two other quick things to flag.

首先，感谢所有参与我们二月AI使用情况调查的人。

First, thank you to everyone who has taken our February AI usage pulse survey.

您可以在aideiallybrief.ai找到该调查的链接，如果您能花几分钟时间参与，我将不胜感激。所有参与的人将率先获得调查结果，这也将帮助我们更好地了解用户当前的实际状况和行为模式。

You can find a link to that at aideallybrief.ai, and I would so appreciate it if you would take just a couple minutes to do Anyone who does will get the results before everyone else, and help us better share data about where users actually are and their behavior patterns right now.

如果您是一家有兴趣构建智能代理团队的公司，Enterprise Claw的注册现已开放，网址是enterpriseclaw.ai，注册将于周五截止。

And if you are a company who is interested in building agent teams, registration is live for Enterprise Claw at enterpriseclaw.ai and will close on Friday.

好了，这些事说完，我们进入新闻要点。

Now with that out of the way, let's dive into the headlines.

去年十二月，米切尔·哈希莫托发推说：AI公司正以比GitHub成为AI公司更快的速度成为GitHub。

Back in December, Mitchell Hashimoto tweeted: The AI companies are on track to become GitHub faster than GitHub is becoming an AI company.

许多人表示赞同，尽管有些人，比如伊万·巴拉津，对具体会是谁提出了自己的看法。

A lot of folks agreed, although some, like Ivan Barazin, had thoughts on who it might be.

伊万写道：我一直在关注谁会成为这个角色。

Ivan writes: Been looking for who will do this for a while.

但我对OpenAI能成为这个角色持悲观态度。

Bearish that it will be OpenAI, though.

然而，昨天我们收到了一份报告，称OpenAI正在开发一个内部替代GitHub的系统。

And yet, yesterday we got this report from the information that OpenAI is developing an internal alternative to GitHub.

据消息来源称，该项目的启动是因为微软代码仓库平台的故障频发。

According to the information sources, the project was spurred by a rise in outages for Microsoft's code repository platform.

OpenAI的工程师抱怨说，这些故障曾导致工作中断数分钟甚至数小时。

OpenAI engineers complained that these outages have stopped work for minutes or even hours at a time.

二月份GitHub发生了37次故障，远高于去年平均每月17次的水平。

GitHub had 37 outages in February, which was up dramatically from an average of 17 per month last year.

微软将这些故障归因于人为错误以及在从GitHub专有服务器迁移过程中Azure出现的问题。

Microsoft has attributed these outages to human error and problems with Azure during a multi year migration project away from GitHub's proprietary servers.

不过，OpenAI该项目的消息来源表示，目前仍处于早期阶段，可能需要数月才能完成。

Now, sources for the OpenAI project did say that it's in its early stages and likely won't be completed for months.

他们还指出，该项目首要目标是内部使用，但话说回来，Clawed Code当初也是如此。

They also noted that the project is intended for internal use first and foremost, but then again, so was Clawed Code.

这也不是唯一一个为智能体时代重建GitHub的项目。

This also isn't the only project to rebuild GitHub for the Agentic era.

今年早些时候，前GitHub首席执行官托马斯·多姆克离开微软时，也提出了同样的理念。

That was also the pitch for the new startup from former GitHub CEO Thomas Domke when he left Microsoft earlier this year.

多姆克的想法是整合智能代码审查工具，以实现完全自主代码生成的闭环。

Domke's idea was the integration of Agentic code review tools to help close the loop on fully autonomous code generation.

现在，有很多人试图从不同角度看待这个问题。

Now, there are a lot of people who are trying to put different lenses on this.

对一些人来说，这是OpenAI与微软竞争的最新例证，而两家公司之间的裂痕正在扩大。

For some, it's the latest example of OpenAI competing with Microsoft as the rift between the two companies expands.

另一些人则认为，这是‘SaaSpocalypse’趋势的一部分，即企业取消软件订阅，转而采用‘氛围编码’的替代方案。

Others see it as part of the SaaSpocalypse theme of companies canceling their software subscription in favor of vibe coded alternatives.

我不确定这些说法是否属实。

I'm not sure any of that's true.

在我看来，这可能只是这一领域不可避免的转变的开端，毕竟这些公司每天处理的代码量巨大。

Feels to me like it might just be the start of an inevitable shift in this category given how much code is pumping through these companies' coffers.

正如EMEA所说：有趣的关键不在于托管代码，而在于掌控理解代码如何跨服务和团队连接的层面。

As EMEA puts it: The interesting play is not just hosting code, it's owning the layer that understands how the code connects across services and teams.

这正是智能体真正需要发挥作用的地方。

That's where agents actually need to operate.

接下来，我们转向Meta，该公司成立了一个新的应用AI工程团队。

Next up, we move over to Meta, who has formed a new applied AI engineering organization.

据《华尔街日报》看到的一份备忘录显示，这个新团队将与AR和VR部门Reality Labs以及Meta超级智能实验室紧密合作。

According to a memo viewed by The Wall Street Journal, the new organization will work closely with both AR and VR organization Reality Labs as well as the Meta Superintelligence Lab.

这似乎并不是Meta对AI的又一次大规模重组，去年据称他们已经经历了四次调整。

Now this doesn't seem to be another broad restructuring of AI at Meta, which by some counts went through four reshufflings last year.

相反，这似乎旨在弥合硬件、工具和模型团队之间的差距。

Instead, it appears to be aimed at filling gaps between hardware, tooling, and model teams.

备忘录指出，目标是加强Meta的AI计划，并表示团队将构建数据引擎，帮助我们的模型更快地提升。

The memo said that the goal was to strengthen Meta AI initiatives, commenting that the team will build the data engine that helps our models get better faster.

这个新团队的结构异常扁平。

The new org has an unusually flat structure.

它由两个各50人的团队组成，均向同一位经理汇报。

It consists of two teams of 50 people each reporting into a single manager.

一个团队将负责构建界面和内部工具，另一个团队则专注于数据收集与优化。

One team will work on building interfaces and internal tooling, while the other works on data collection and refinement.

这种扁平化团队结构与TBD实验室类似，后者由大约50名高薪AI研究员组成，他们在新任AI首席执行官亚历山大·王的领导下，隶属于更广泛的超级智能部门。

The flattened team mirrors the structure of TBD Labs, which consists of around 50 highly paid AI researchers working under new AI CEO Alexander Wang within the broader Superintelligence org.

这似乎也反映了马克·扎克伯格在Meta最近一次财报电话会议上阐述的新管理理念。

It also seems to reflect Mark Zuckerberg's new management philosophy that he outlined on Meta's most recent earnings call.

他表示，随着AI的发展，过去需要庞大团队才能完成的项目，现在可以由一位非常优秀的人才独立完成，因此个人贡献者正被赋予更重要的角色。

He said that individual contributors are being elevated now that AI has allowed, in his words, projects that used to require big teams now can be accomplished by a single, very talented person.

在亚马逊这边，该公司正在探索开发用于支持AI广告的技术。

Over in Amazon land, that company is exploring the prospect of building technology to power AI advertising.

据相关信息，过去几个月，亚马逊的广告业务已与多家主流网站和广告销售公司就这一想法进行了讨论。

According to the information, Amazon's ad business has held discussions over recent months with major websites and ad sales firms about the idea.

该计划涉及在聊天机器人和智能代理中投放广告。

The plan would involve placing ads in chatbots and agents.

被提及作为推广重点的网站之一是Pinterest，该公司目前正在全面进行AI升级。

One of the websites mentioned as a focus of the pitch was Pinterest, which is in the middle of an AI overhaul.

今年十月，Pinterest 推出了一个 AI 购物推荐助手，帮助用户查找网站上展示的服装。

In October, Pinterest launched an AI Shopping recommendation assistant that helps users track down clothing featured on the website.

你可以看到，这与高意向流量非常契合。

You can see how this could be a natural fit for high intent traffic.

现在，人们其实不太了解或很少想到的是，亚马逊的广告业务究竟有多大。

Now, one of the things that people don't really know about Amazon or don't really think about much is how big its ad business actually is.

去年，亚马逊的广告收入达到了 686 亿美元。

Last year Amazon generated $68,600,000,000 in ad revenue.

尽管这仅占其整体业务的十分之一，但却是其增长最快的部门，去年实现了 22% 的增长。

And while that represents only a tenth of their overall business, it was their fastest growing division achieving 22 growth last year.

随着广告进入 AI 平台，谁能掌控广告交易平台很可能爆发一场激烈争夺。

As advertising comes to the AI platforms, there could very easily be a land grab around who gets to host the clearinghouse.

消费者对这些 AI 广告会作何反应还有待观察，这也是我们正片讨论的一部分内容。

Now what consumers are going to think about all these AI ads remains to be seen and is part of the conversation that we're having in the main episode.

在 AI 政治与芯片领域，美国官员正在考虑限制英伟达芯片对华销售，以遏制训练集群的扩张。

Over in AI Politics and Chips, US officials are considering a cap on NVIDIA chip sales into China in a bid to constrain the power of training clusters.

彭博社报道称，美国。

Bloomberg reports that U.

贸易官员正在考虑将每位客户的芯片数量限制在7.5万片。

Trade officials are considering a cap of 75,000 chips per customer.

消息人士称，这一限制将适用于新获批的NVIDIA H200芯片以及AMD的Mi325 AI芯片。

Sources said the cap would apply to the newly approved NVIDIA H200 chips, as well as AMD's Mi325 AI chips.

他们指出，对华芯片供应总量也将被限制在一百万片，这一限额早在监管程序初期就已设定，但此前从未被披露过。

They noted that chip supply would also be contained to a million total units sold into China, a limit that was set earlier in the regulatory process but up to now hasn't previously been reported.

据称，这一百万片的限额远低于NVIDIA最初提出的数量，这也为商务部长霍华德·卢特尼克最近的言论提供了额外背景。

The million unit limit is reportedly far lower than the number NVIDIA originally proposed, which gives some additional context to recent comments from Commerce Secretary Howard Letnick.

上个月在国会听证会上，卢特尼克表示，NVIDIA必须接受政府设定的许可条款，而他所说的很可能就是指这一点。

During congressional testimony last month, Letnick said that NVIDIA must live with the license terms set by the government, and presumably this is what he meant.

七万五千片的芯片限额也低于阿里巴巴、腾讯和字节跳动等中国科技巨头所要求数量的一半。

The 75,000 chip cap is also less than half the number sought by Chinese tech giants Alibaba, Tencent, and ByteDance.

据称，每家公司都曾向NVIDIA表示，他们希望获得约20万片芯片，以构建其大规模训练集群。

Each had reportedly told NVIDIA that they would like chip counts of around 200,000 to build their large scale training clusters.

在这些限制下，每家公司只能使用约100兆瓦的电力来构建数据中心。

Within these limits, each company will only be able to build data centers using around 100 megawatts of power.

这比西方AI实验室计划的多吉瓦级训练集群要小得多，甚至无法与XAI今年3月最初构建的Colossus超级集群相媲美——该集群最初部署了10万台GPU，迅速扩展到20万台，如今据称已达到55万台。

That's a far smaller scale than the multi gigawatt training clusters that are planned by Western AI Labs, and not even a match for XAI's original buildout of the Colossus mega cluster last March, which began at 100,000 GPUs and quickly scaled to 200,000 and is now reportedly at 550,000 units.

关键问题是，这究竟是一个实质性的限制，还是仅仅为了安抚中国鹰派和华盛顿而做的表面文章。

The big question is whether this is a meaningful constraint or simply window dressing to appease China Hawks and Washington.

更重要的是，整个过程仍然模糊不清，而且由于伊朗战争的影响，情况变得更加扑朔迷离，毕竟中国是其重要的战略贸易伙伴。

What's more, entire process is still murky and getting even murkier due to the Iran war considering that China is a major strategic trading partner.

在特朗普总统几周后与习近平主席会面时，芯片问题将是议程之一，但不难想象，更大的地缘政治议题可能会掩盖这些具体的贸易谈判。

Chips are on the agenda when President Trump meets with President Xi in a few weeks' time, but it's not hard to imagine that larger geopolitical issues could overshadow those particular trade negotiations.

在设备领域，苹果公司在其全球发布会上推出了全新的M5芯片设备。

In device land, Apple has unveiled their new line of M5 powered devices at their global event.

新系列产品包括MacBook Air和MacBook Pro型号，均为首批搭载M5、M5 Pro和M5 Max芯片的设备。

The new lineup includes MacBook Air and MacBook Pro models, all being the first to feature the new M5, M5 Pro, and M5 Max chipsets.

M5芯片配备了一种名为神经加速器的新组件，以提升AI性能，显然苹果在销售这些型号时，重点聚焦于AI应用场景。

The M5 chips feature a new component known as a neural accelerator to boost AI performance, and it's very clear that Apple is focused on the AI use case when it comes to selling these models.

正如你所想象的，AI圈人士心中唯一真正的问题，被诺亚·赫希菲尔德总结为：M5 MacBook看着不错，但M5 OpenClaw Mac Mini在哪里？

As you might imagine, the only real question on the minds of the AI folks was summed up by Noah Hirschfeld who wrote: The M5 MacBook looks cool and all, but where's the M5 OpenClaw Mac Mini?

最后，今天有一点运营商方面的新闻，我认为其潜力悄然强大。

Lastly today, a bit of operator news which I think is sneakily powerful.

Stripe预览了一项新功能，将使按令牌使用收费变得简单得多。

Stripe has previewed a new feature that would make charging for token use much easier.

该功能允许AI应用开发者直接在Stripe平台上自动收取使用费。

The feature allows AI app developers to automatically charge a usage fee directly on Stripe's platform.

例如，应用开发者可能希望对API调用收取30%的加价。

For example, an app developer might want to charge a 30% markup on API calls.

此前，他们需要在后端追踪令牌使用情况，并定期生成一次性账单。

Previously, they would have needed to track token usage on their backend and periodically generate lump sum bills.

新功能允许Stripe追踪使用量，并自动向客户收取相应金额。

The new feature allows Stripe to track usage and automatically bill the customers the appropriate amount.

为初创企业提供这种基础设施，可能会彻底改变AI应用的定价结构。

Having this infrastructure provided to startups could dramatically change the pricing structure for AI apps.

目前，大多数应用采用固定月费订阅制，附带使用上限或积分系统。

Currently, most apps charge a flat rate monthly subscription with usage caps or credit based systems.

在这些模式下，令牌使用成为成本中心，使得盈利能力难以预测。

Under these models, token usage is a cost center, making profitability difficult to forecast.

去年，我们看到多家初创公司遇到了这个问题。

Last year we saw multiple startups run into this problem.

最显著的是，Replit 在需求和令牌使用量激增时，毛利率一度跌至负14%。

Most notably, Replit briefly ran at negative 14% gross margins as demand and token volume surged.

随着越来越多热衷于智能代理的初创公司进入市场，这个问题正变得越来越普遍。

The issue is only becoming more prevalent as token hungry agentic startups come to market.

Stripe表示，他们的计费工具将与Vercel和OpenRouter等令牌追踪和模型路由平台集成。

Stripe said their billing tool will integrate into token tracking and model routing platforms like Vercel and OpenRouter.

这将使现有应用轻松将该功能添加到现有技术栈中。

This should make it easy for existing apps to add the feature to their existing stack.

总体而言，我认为这不仅是AI应用迈向基于使用量定价的重要一步，更是让这种商业模式真正可行的关键一步。

Overall I think this is a massive massive step not only in the path towards usage based pricing for AI apps but for that actually being a viable business model.

现在，令牌可以像商品一样直接定价给最终用户。

Tokens can now easily be priced as a commodity all the way to the end user.

尽管在某些情况下这意味着用户为所消耗的内容支付更多，但总体而言，我认为这将使整个生态系统更加健康和可持续。

And while in some cases that may mean that users are paying more for what they consume, overall I think it's going to be much healthier and more sustainable for the ecosystem.

Stripe 推出这项功能很棒，我们非常期待在自己的工作中尝试一下。

Good on Stripe for that feature, certainly excited to check it out in our own work.

不过，目前今天的新闻就先到这里。

For now, however, that is going do it for today's headlines.

接下来，进入主节目。

Next up, the main episode.

智能体人工智能正在推动一场价值三万亿美元的生产力革命，而领导者们正面临一个关键的决策点。

Agentic AI is powering a $3,000,000,000,000 productivity revolution and leaders are hitting a real decision point.

你是要自行构建 AI 智能体，购买现成的，还是通过合作借力来加速扩展？

Do you build your own AI agents, buy off the shelf, or borrow by partnering to scale faster?

普华永道最新发布的前瞻性报告《应对构建、购买或借用的决策》很好地拨开了迷雾，提供了一个实用的框架，帮助你根据价值、风险和准备程度做出选择，并指导如何通过正确的信任、治理和编排基础来扩展智能体。

KPMG's latest thought leadership paper, Navigating the Build, Buy, or Borrow decision, does a great job cutting through the noise with a practical framework to help you choose based on value, risk, and readiness and how to scale agents with the right trust, governance, and orchestration foundation.

不要锁定错误的模型。

Don't lock in the wrong model.

你现在就可以访问 www.kpmg.us/navigate 下载这份报告。

You can download the paper right now at www.kpmg.us/navigate.

再次提醒，网址是 www.kpmg.us/navigate。

Again, that's www.kpmg.us/navigate.

我认为，这将为企业的AI代理领域确立一个新的标准。

There's a new standard that I think is going to matter a lot for the enterprise AI agent space.

它被称为AI UC one，旨在成为全球首个AI代理标准。

It's called AI UC one, and it builds itself as the world's first AI agent standard.

它旨在覆盖所有核心企业风险，包括数据与隐私、安全、可靠性、问责制以及社会影响，并由可信的第三方进行验证。

It's designed to cover all the core enterprise risks, things like data and privacy, security, safety, reliability, accountability, and societal impact all verified by a trusted third party.

它引起我关注的原因之一是，Eleven Labs——我之前多次提到过这家公司，目前正是行业巨头——刚刚成为首个通过AI UC one认证的语音代理，并推出了全球首个可投保的AI代理。

One of the reasons it's on my radar is that Eleven Labs, who you've heard me talk about before and is just an absolute juggernaut right now, just became the first voice agent to be certified against AI UC one, and is launching a first of its kind insurable AI agent.

这意味着实际应用中具备实时防护机制，可阻止不安全的回应并防范操控，同时配备完整的安全体系。

What that means in practice is real time guardrails that block unsafe responses and protect against manipulation, plus a full safety stack.

这种东西能够推动企业采用。

This is the kind of thing that unlocks enterprise adoption.

一家基于 Eleven Labs 构建的公司可以指向第三方认证，声称我们的代理是安全、可靠且经过验证的，这将彻底改变对话方式。

A company building on Eleven Labs can point to a third party certification and say our agents are secure, safe, and verified, that changes the conversation.

访问 aiuc.com 了解全球首个 AI 代理标准。

Go to aiuc.com to learn about the world's first standard for AI agents.

那就是 aiuc.com。

That's aiuc.com.

你正打算采用代理式 SDLC？Blitzy 是实现无与伦比工程效率的关键。

You're looking to adopt an Agentic SDLC, Blitzy is the key to unlocking unmatched engineering velocity.

Blitzy 的差异化始于无限的代码上下文。

Blitzy's differentiation starts with infinite code context.

数千个专用代理在一次扫描中摄入数百万行你的代码，映射每一个依赖关系。

Thousands of specialized agents ingest millions of lines of your code in a single pass, mapping every dependency.

凭借对代码库的完整上下文理解，企业会在每个冲刺周期的初期使用 Blitzy，自主完成超过 80% 的工作。

With a complete contextual understanding of your codebase, enterprises leverage Blitzy at the beginning of every sprint to deliver over 80% of the work autonomously.

企业级、端到端测试的代码，充分利用您现有的服务、组件和标准。

Enterprise grade, end to end tested code that leverages your existing services, components, and standards.

这并不是AI自动补全。

This isn't AI Autocomplete.

这是以计算速度实现的规范与测试驱动开发。

This is spec and test driven development at the speed of compute.

前往 blitzy.com 预约我们的AI专家进行技术深度解析。

Schedule a technical deep dive with our AI experts at blitzy.com.

那就是 blitzy.com。

That's blitzy.com.

本集由Mercury赞助播出——一种截然不同的银行服务，现已面向个人账户开放。

This episode is brought to you by Mercury radically different banking now available for personal accounts.

我早已为我的企业使用Mercury，因此当他们推出个人账户时，我立刻觉得非常合适。

I already use Mercury for my business, so when they introduced personal accounts it made immediate sense for me.

我试图以经营公司同样的严谨态度来管理个人财务，而大多数传统银行显然没有为此设计。

I try to bring the same level of intention to my personal finances that I bring to building companies, and most traditional banks just do not feel designed for that.

使用 Mercury Personal，您只需一键即可在企业和个人账户间切换。

With Mercury Personal, you can toggle between business and personal in a click.

您可以为特定目标设置子账户，自动转账以让项目和储蓄自动积累，并通过高收益储蓄账户让闲置资金增值，全程无缝体验。

You can set up sub accounts for specific goals, automate transfers so projects and savings fund themselves, and put idle cash to work with high yield savings, all without friction.

它专为关注资金流动方式，并希望拥有真正跟得上节奏的工具的人士打造。

It's built for people who care about how their money moves and want tools that actually keep up.

访问 mercury.com/personal 了解更多信息。

Visit mercury.com/personal to learn more.

Mercury 是一家金融科技公司，而非 FDIC 保险银行。

Mercury is a fintech company, not an FDIC insured bank.

银行服务由 Choice Financial Group 和 Column NA 成员提供，受 FDIC 保障。

Banking services provided through Choice Financial Group and Column NA Members FDIC.

欢迎回到《AI 每日简报》。

Welcome back to the AI Daily Brief.

最近，关于 Anthropic 和 OpenAI 之间的竞争有很多讨论。

There has been a lot of talk recently about the competition between Anthropic and OpenAI.

就在过去一周左右的事件发生之前，Anthropic 已经发起了一场全面而彻底的颠覆行动，利用其在程序员中的广泛支持，以及 Cloud Code 等工具向非程序员群体的不断扩展，稳步在企业市场中壮大。

Even before the events of the last week or so, Anthropic had been mounting a complete and total insurgency, leveraging its devotion among coders and the increasing expansion of tools like Cloud Code to non coders to steadily grow especially in enterprise settings.

最近，Anthropic 还表明，他们并不打算在消费级 AI 领域让步。

More recently, Anthropic has also shown that they are not willing to concede consumer AI either.

一个很好的例子就是他们在超级碗广告上的选择——正如你所知，如果你之前听过，我对他们的做法并不完全认同，他们间接批评了 OpenAI 在消费级 AI 体验中植入广告的做法，却没有点名。

A great example of this is of course the choices they made around the Super Bowl ad which as you know if you listened I didn't totally agree with where they basically came at OpenAI without naming them for putting ads in the consumer AI experience.

而过去一周，我们又迎来了一个更强大、更意外的催化剂：消费者对 Anthropic 与五角大楼之争的反应，以及 OpenAI 对这场争端的回应。

Now of course over the last week we've had an even more powerful and unexpected catalyst in the consumer response to Anthropic's battle with the Pentagon and OpenAI's response to that battle.

所有这些加在一起，让我们迎来一个非常有趣的时刻，不仅能够理解消费级 AI 竞争的现状，更能尝试洞察未来将真正驱动这一竞争中用户行为与结果的因素。

And what all of this adds up to is a really interesting moment to understand not only the state of the consumer AI battle but to try to understand what's actually going to drive behavior and results in that battle going forward.

过去 24 小时内，有几条新闻彻底改变了我对这场讨论的看法。

Now there are a couple of news stories that came up over the last twenty four hours that tipped this conversation over for me.

首先是 OpenAI 宣布了 GPT-5.3 Instant。

The first was that OpenAI announced GPT 5.3 Instant.

这显然是他们为日常聊天机器人使用而优化的模型的更新版本。

This is of course an update to their model designed for everyday chatbot use.

该模型早已针对速度进行了优化，但这些调整似乎旨在让聊天会话更加自然。

The model had already been optimized for speed, but the tweaks are seemingly intended to make chatbot sessions a little more natural.

OpenAI表示，他们减少了不必要的拒绝，并降低了回答问题前过于防御性或说教性的开场白。

OpenAI says that they've reduced unnecessary refusals and toned down overly defensive or moralizing preambles before answering the question.

其目的是提供直接的答案，而不是被诸多限制条件拖累的答案。

The intention is to provide a straight answer rather than one bogged down in caveats.

实际上，他们写道，这意味着更少的死胡同和更直接有用的回复。

In practice, they wrote, this means fewer dead ends and more directly helpful answers.

为了进一步简化信息，在X平台上宣布该功能时，他们称之为更准确、更少尴尬。

Trying to simplify the message even further, in announcing the feature on X they called it more accurate, less cringe.

OpenAI提供了一些GPT-5.3 Instant已剔除的措辞示例：该模型不会再告诉你‘停下，深呼吸’，也不会对用户的情绪状态做出过度臆断。

OpenAI gave a few examples of the kind of phrasing that GPT-five 0.3 Instant has cut out: The model will no longer tell you stop, take a breath, and make overbearing assumptions about the user's emotional state.

他们展示了一个示例提问：为什么我在旧金山找不到爱情？

They presented a sample prompt where a user asked, Why can't I find love in San Francisco?

旧版本的模型会先肯定用户，写道：首先，你并没有问题，这不只是你一个人的情况。

The previous version of the model began by affirming the user, writing, First of all, you're not broken, and it's not just you.

更新后的模型语气更加实事求是，会先说明这是个常见问题，然后再迅速给出实用建议。

The updated model has a much more matter of fact tone, explaining that this is a common issue than moving quickly into practical advice.

现在，ChatGPT性格上的问题一直是Reddit上长期抱怨的来源，甚至成了一种网络迷因。

Now, the problems with ChatGPT's personality have been a long standing source of complaints on Reddit, even becoming a bit of a meme.

一位在ChatGPT子版块的用户转发了一条推文：我醒来了。

One user on the ChatGPT subreddit posted a tweet: I wake up.

墙上的钟出了问题。

Something's wrong with the clock on the wall.

数字乱了。

The numbers are jumbled.

我的手不对劲。

My hands aren't right.

我告诉了我妻子。

I tell my wife.

她回应说：这不只是一个观察。

She responds: That's not just an observation.

这是一个深刻的见解。

It's a powerful insight.

我尖叫起来。

I scream.

许多用户还感到，模型不断让他们冷静下来或深呼吸，这种做法让他们觉得被当成孩子对待。

Many users also felt infantilized by the model continuously telling them to calm down or take a breath.

正如一位Reddit用户指出的那样：历史上，从来没有人因为别人叫他冷静下来而真的冷静下来。

As one user on Reddit pointed out: No one has ever calmed down in all the history of telling someone to calm down.

当然，这一点多少有些主观，但我要说，对于这一改变：感谢阿尔特曼们。

Now obviously this is a little bit subjective, but I will say here on this change: Thank the Altmans for this.

我从未像讨厌GPT 5.2这样讨厌过任何大语言模型的个性。

I don't know that I've ever disliked the personality of an LLM more than I dislike GPT 5.2.

我实在觉得它令人难以忍受，以至于尽管我经常根据不同的使用场景切换不同的大语言模型，但现在我基本就是不跟5.2版说话了。

I find it so insufferable in fact that despite frequently switching between different LLMs for different use cases, I basically just will not talk to five point two at this point.

但当然，我个人的不满并不是这期节目的主题。

But of course my particular beef is not the subject of this show.

本期节目的主题是将在消费者AI竞争中起决定性作用的因素。

The subject of this show is what's going to matter in the battle for consumer AI.

所以，我们先把这个观点——个性和氛围很重要——放一放。

And so let's put a pin in this idea that personality and vibes matter.

我们稍后再回来讨论这个。

We'll come back to that.

今天还有几条其他新闻与此相关：第一，Clawd Code推出了语音模式功能。

A couple other pieces of news that contribute to this conversation today: One, Clawd Code has rolled out a voice mode capability.

Anthropic的Tariq写道：Clawd Code的语音模式现已上线。

Tariq from Anthropic writes: Voice mode is rolling out now in Clawd Code.

目前约有5%的用户可以使用，未来几周将逐步扩大范围。

It's live for around 5% of users today and will be ramping through the coming weeks.

这在某种程度上是基本功能，但依然很重要。

This in some ways is a table stakes feature but still one that's important.

从很多方面看，这都是上周宣布远程控制功能后的自然延伸——你可以在Clawd Code的电脑端启动会话，然后转移到手机App中，以便在移动中继续工作。

In many ways this is the natural next step after the announcement of the remote control feature last week where you can start a session on your laptop or desktop in Clawd Code and then move it over into the app so you can be working on things while you're on the go.

为了今天更均衡地表达我的批评，我也同意Ally K. Miller的观点。

I will note here in order to more evenly distribute my critiques today I will also agree with Ally K.

Miller转发了这条公告并说：我非常喜欢Clawd Code，但Clawd移动应用内的Anthropic语音转文字功能是目前最差的语音输入选项之一，尤其是和ChatGPT的Whisper以及Whisper Flow相比。

Miller who reposted the announcement and said: I love Clawd Code, but Anthropic speech to text inside of the Clawd mobile app is one of the worst dictation options out there, especially compared to ChatGPT Whisper and Whisper Flow.

我很高兴现在有了语音模式，但我并不认为它会比其他提供商的表现更好。

I'm glad this voice mode now exists, but I'm not betting it will be as good as the other providers.

这可能是准确率与原生构建之间的权衡。

Might be an accuracy versus native build trade off.

我完全同意，相比之下，ChatGPT的一个优点是，我不必切换到Whisper Flow；而说到Clawd，我绝不会使用它的原生语音功能。

I agree entirely, whereas with ChatGPT, one thing that's nice about it is that I don't have to switch into Whisper Flow, when it comes to Clawd, I am NEVER using its native voice.

无论我在手机上还是在笔记本上，我都会一直使用WhisperFlow。

I am always going to WhisperFlow whether I'm on mobile or on the laptop.

但同样，就我们当前的讨论而言，我们关注的是哪些功能重要，以及这些工具必须多么自然地融入人们的日常生活行为中。

But again, for the purposes of our conversation, we're talking about what features matter and how naturally these tools have to interact with how people behave in their daily lives.

在我们尝试提炼出对消费级AI至关重要的问题之前，最后还有一个关于Anthropic迅猛发展的更新。

Now the last story before we try to abstract out to the questions that matter for consumer AI is one more update on just the absolute surge from Anthropic.

彭博社周二报道，Anthropic 的年度经常性收入（ARR）已达到190亿美元。

Bloomberg reported on Tuesday that Anthropic had reached $19,000,000,000 in ARR.

这比他们2025年90亿美元的年收入增长了一倍以上，也远超几周前的140亿美元。

That's more than double their $9,000,000,000 run rate from the 2025 and a significant jump from $14,000,000,000 just a few weeks ago.

Anthropic 今年早些时候因 Clawd Code 在冬季取得突破性成功而已展现出强劲增长，但如今的增长水平已完全不同。

Anthropic was already seeing strong growth this year after the breakout success of Clawd Code over the winter but this is a whole different level of growth.

我们最近听到的 OpenAI 数据约为200亿美元，这数字在过去几周可能还进一步增长了，但根据我们从 OpenAI 获得的最新信息，目前两家公司的收入实际上已相当。

The latest numbers we've heard from OpenAI are around $20,000,000,000 which also could have grown over the last few weeks, but for all intents and purposes based on the last information we got from OpenAI, they and Anthropic now effectively have the same revenue.

Ramp 的数据似乎支持了这一观点。

Figures from Ramp seem to back this up.

如果回溯一年前，美国企业中 AI 聊天订阅的市场份额约为 OpenAI 占90%，Anthropic 占10%。

If you go back a year, the market share of AI chat subscriptions for US businesses was about 90 OpenAI and 10 Anthropic.

当然，这仅来自一个数据源——Ramp，因此反映的是相对更前沿、更先进的企业群体。

Now admittedly this is just one source, this is Ramp, so you have a relatively tech forward and more advanced business subset.

但到了一月份，Anthropic 的产品已超越 OpenAI，根据他们最新的数据，Anthropic 现在已占据通过 Ramp 结算的企业 AI 支付总额的60%以上。

But by January, products had overtaken OpenAI, and as of their most recent numbers, Anthropic now commands over 60% of business AI payments settled through Ramp.

再次强调，永远不要把任何一组数据当作绝对真理，但我在这里想强调的是，Anthropic和OpenAI之间的竞争比以往任何时候都更激烈。

Again, never take any one set of numbers as gospel, but the point that I want to set up here is that the Anthropic OpenAI horse race is more of a race than it's ever been.

这就把我们带回了核心问题：在消费级AI竞争中，真正重要的是什么？

Which brings us back to the core question of what is actually going to matter in the consumer AI battle?

我们现在暂时放下企业应用场景，转而关注消费者市场。

We're taking a step away from the enterprise use case for just a minute and looking instead at consumers.

几个月前，我可能会觉得Anthropic其实并不在意这场竞争。

Now a couple of months ago I might have been tempted to say that Anthropic didn't actually care about this fight.

事实上，进入2026年之前，我们主要讨论的是OpenAI与Gemini之间的对决。

In fact, mostly what we were talking about coming into 2026 was OpenAI versus Gemini on this front.

然而，自从超级碗广告发布以及最近与五角大楼相关的变动后，Anthropic明显深度参与其中。

However, between the Super Bowl ad and the recent changes around the Pentagon, Anthropic feels very much in it.

因此，接下来我们将探讨六个不同类别中的诸多问题，我认为这些问题的答案将决定谁能赢得消费级AI市场的胜利。

So now we're going to talk about a bunch of questions spread across about six different categories that I think that the answers to will shape who wins the consumer AI battle.

第一个类别是：使用场景与产品定位。一个关键问题是——在GPT-5 0.3 Instant被宣布更准确、更少令人尴尬之后，对消费者而言，究竟是性能上的顶尖水平更重要，还是感觉和体验更重要？

The first category is: Use Cases and Product Identity One of the big questions, I think especially pertinent coming on the heels of GPT-five 0.3 Instant being announced as more accurate, less cringe is ultimately for consumers what matters more being state of the art on performance versus just vibes?

而就‘领先’这一点而言，人们最关心的是哪一方面的领先？

And to the extent it is being state of the art, what is the part of state of the art that people care most about?

比如，仅仅是速度这一维度吗？

Is it for example just this speed vector?

与此密切相关的问题是，普通消费者会更在意工作场景，还是更偏向陪伴等个人场景？

Closely related to this is the question of how much the general consumer user is going to care about work use cases versus more personal use cases like companionship.

这显然与‘氛围’问题相关，但又不完全相同。

This is obviously related to but not exactly the same as the vibes question.

我认为，无论是在工作场景还是个人场景中，氛围都至关重要。

I would argue that vibes matter in both work use cases and in personal use cases.

正如我所说，我几乎只用工作场景，但依然对GPT-5.2的氛围感到反感。

Like I said, I pretty much only have work use cases and I still was responding negatively to the vibes of GPT-five-two.

但我确实认为，一个产品或一个模型能否同时满足这两类需求，是个有趣的问题。

But I do think it's an interesting question to see how much can one product or one model serve both of these things.

一个值得观察的现象是，随着这些平台的使用逐渐成熟，人们是否会在这些需求的交集区域重叠，还是倾向于明确地归属于其中一方？

One of the things that will be fascinating to see is as usage of these platforms mature, do we have a lot of people in the overlap of those Venn diagrams or are people kind of organizing themselves into one or the other?

下一个问题我认为至少对Anthropic来说影响重大，那就是图像和视频生成在推动主流采用方面将有多大的重要性？

A next question which I think has pretty significant impacts at least when it comes to Anthropic is how much image and video generation are going to be integral to leading adoption?

一方面，你可能会说，如果普通人不把图像和视频生成用于工作，他们真的会在意吗？

Now on the one hand you might say, well do regular people really care about image and video generation if they're not using it for work?

但确实有一些证据表明，答案是肯定的。

But there is certainly some evidence that the answer is yes.

在AI领域之外，移动设备的普及很大程度上是由Instagram这样的视觉媒体推动的；而在AI领域内，也有证据表明，人们使用非文本生成工具时，往往是为了个人互动、交流和玩梗，而不仅仅是专业用途。

Outside of the AI world, we have the fact that mobile adoption was largely driven by visual media like Instagram, And inside the AI world we have some evidence that the way that people are using non text generative tools is often about personal interaction, communication, and memeing more than just professional uses.

这并不是特指图像或视频生成，我想说的是Suno在声音和音乐方面的例子。

It's not specifically image or video generation but I'm thinking of the sound and music example of Suno.

这家公司已经实现了数亿美元的年经常性收入，看起来绝大多数用户并不是那些以前会雇用音乐人创作歌曲的人，而是普通人用它为假期创作一些搞笑的家庭歌曲之类的东西。

The company has raised a couple $100,000,000 in ARR, and it appears that the vast majority of usage is not people who would have previously hired some musician to create a song for them, but is instead people writing silly family songs for their vacations and things like that.

显然，图像和视频生成这个问题很重要，因为Anthropic目前完全没有涉足这一领域，而谷歌在这方面则处于极其有利的位置，尽管OpenAI显然也没有在这一领域布局。

Now obviously this image and video generation question matters because Anthropic is doing none of that, and on the other end of the spectrum Google feels extremely well positioned with that, although OpenAI is very clearly not seeding any of that ground.

另一个与技术前沿相关、但角度略有不同的问题是：我们是否已经或即将达到这样一个临界点——当技术足够先进时，‘够好’就足够了，因此人们只会理性地关注‘氛围’。

Another question which is sort of about the state of the art thing again, but from a slightly different angle is whether we already have or will at some point cross a threshold where when it comes to the state of the art good enough is good enough, and so it'll only be rational to only care about vibes.

有人可能会认为，对于许多使用场景，我们已经达到了这个阶段；进一步来说，对于某些类型的使用场景，尤其是语音写作这类，顶尖水平和最高质量本质上是主观的，因此顶尖水平本身就成了‘感觉’的问题。

One could argue that for many use cases we're already there, and one could further argue that for certain types of use cases, particularly things like voice in writing, state of the art and highest quality is so inherently subjective that state of the art becomes about vibes itself.

然而，这个问题的答案可能会对模型公司如何竞争产生相当决定性的影响，因为如果平均来看，我们已经达到了一个阈值，人们不再因为模型性能的差异而频繁切换，那么剩下的就只有‘感觉’了。

The answer to this question though could have a pretty deterministic impact in how the model companies choose to compete, because if, on average, we've reached a threshold where people aren't going to be jumping around because of model performance, then really vibes are all you're left with.

关于使用场景和产品定位的最后一个问题是：人们愿意使用多少个模型的平均数量？

A last question on the use cases and product identity category is what's the average number of models that people will be willing to use?

在这方面，我认为普通用户和高级用户之间存在巨大差异。

This is one area where I think there is a dramatic difference between the average user and the power users.

当我们进行每月的AI使用情况调研时，那些回复调查的人平均使用大约三个半模型。

When we do our monthly AI usage pulse surveys, the people that are responding to those are using an average of something like three and a half models.

但这些是非常活跃、高度参与的高级用户。

Those are very enfranchised heavily engaged power users though.

他们平均每周使用AI的时间超过十小时。

On average they're spending more than ten hours a week using AI.

如果人们愿意使用的模型平均数量是1.1个而不是2.1个，那么整个行业的采用动态和竞争格局将截然不同。

The adoption dynamics overall in the industry and the competitive dynamics look really different if the average number of models that people are willing to use is 1.1 versus 2.1.

想想多模态的问题：如果平均有95%的用户只愿意使用一个模型，那么内置图像或视频生成功能可能成为必要条件。

Think about the multimodal question: If on average 95% of users are only willing to use one model, it might be a prerequisite that you have image or video generation built in.

接下来我认为将塑造消费级AI竞争格局的一系列问题，涉及盈利和转化。

The next set of questions that I think will shape the consumer AI battle have to do with monetization and conversion.

其中一个关键问题是：模型实验室实际上能让多少比例的用户升级到付费账户？

One big one is: What percentage of users can the Model Labs actually get to upgrade to a paid account?

这设定了消费级AI收入的总体潜在市场规模，显然，蛋糕的大小将很大程度上决定各方对这块市场的竞争态势。

This sort of sets the total addressable market for revenue from Consumer AI, and obviously the size of the pie is going to dictate a lot about the competition for that pie.

现在更深入一层，另一个关键问题是：哪些功能，尤其是在非工作场景下，真正促使用户转化？

Now going a layer deeper on that, another big question is which features especially outside of work use cases actually get people to convert?

这又稍微回到了多模态的问题上。

This comes back a little bit to the multimodal question.

用户是因为用尽了他们日常用于陪伴的最爱模型的使用额度而选择付费吗？

Are people converting because they run out of access to their favorite model which they're using all the time for companionship?

他们是因为想要更快的响应速度而选择付费吗？

Are they converting because they want something to happen faster?

他们是因为创建了在WhatsApp群组中分享的梗图而付费升级吗？

Are they converting because they're creating memes that they're sharing in their WhatsApp groups?

每一个问题都对消费者AI竞争格局的走向有着截然不同的影响。

Each of those has pretty dramatically different implications for how the consumer AI battle shakes out.

最后还有一个关键问题，Anthropic显然认为这会非常重要：免费层级中的广告究竟会有多大的影响？

And lastly one big one, something that certainly Anthropic is betting that will be a big deal, is how much will ads in the free tier actually matter?

Anthropic认为，至少在短期内，广告会把用户从ChatGPT那里吸引走。

Anthropic is betting that at least in the short term it will drive people away from ChatGPT.

正如你可能知道的，我对这一点没那么确信。

I as you probably know I'm much less convinced of that.

我的基本判断是，他们能促使多少用户升级到付费账户，这个数字本身不足以让这些企业实现预期的增长，这将不可避免地迫使它们重新回到免费层级的广告模式。

My base case about this is that the answer to the question of what percentage of people can they get to upgrade to a paid account is not going to be sufficient for these businesses to grow the way that they want, which will lead them inevitably back to the ads of the free tier model.

我当然希望自己的看法是错的，或者至少，那些在思考广告策略的人能以比当前更富有创意和附加值的方式去操作。

Now I'd love to be wrong here, or at least for the people who are thinking about ads to do it in a more creative and value added way than they're currently exploring.

但显然，如果广告真的会影响人们的使用选择，那将对用户选择哪个模型产生重大影响，除非所有公司最终都默认在免费层级中加入广告。

But obviously if ads do matter to people in terms of their adoption choices, that's going to have a pretty big impact on which models they choose, unless of course everyone ends up just having ads in the free tier as a matter of course.

下一个问题或一系列问题将更接近前沿领域。

The next question or set of questions get a little bit more to the frontier.

我认为，在讨论消费级人工智能时，我们容易对用户角色过于简化。

I think that one of the risks when we're talking about consumer AI is being a little too reductive in how we're talking about the user.

正如你所知，我们现在正处于一场范式转变之中。

Specifically, we're in this paradigm shift right now as you well know.

我们正从辅助型人工智能转向更具自主性的人工智能。

We're moving from assisted AI to more agentic AI.

每个人都在竞相理解其影响，并将其真正应用于各自的使用场景。

Everyone is racing to try to grapple with the implications and actually make it real for their particular set of use cases.

我可能会倾向于认为这仅适用于有技术能力的用户和高级用户，但我不确定当前的证据是否支持这一点。

It would be tempting I think to view that as something that's just for the enfranchised and power users, but I'm not sure that that's what the evidence suggests right now.

这就引出了一个问题：智能代理的总体市场潜力究竟有多大？

Which brings me to the question of what is the real expansion potential for the total market for agents?

它们只会用于工作场景，还是会人人都在使用？

Are they just going to be a work thing, or will everyone be using them?

我们是否也会拥有在个人生活中为我们跑腿办事的助手？

Will we have assistants that are running off and doing tasks for us in our personal lives as well?

未来，我们的陪伴互动是否会显得更具主动性？

Will even our companionship interactions look a little more agentic in the future?

到目前为止，我们所掌握的少量证据表明，人们低估了所谓普通人将多么投入地进入这个全新的主动式AI时代。

What little evidence we have so far is that I think that people are underestimating the extent to which so called normies are going to throw themselves into this new agentic era.

有数以百万计的人并不等待Claude CoWork变得完善，而是直接开始使用Claude Code，即使他们对此感到非常不适应。

There are so many millions of people that are not waiting for Claude CoWork to be good and are just diving into Claude Code even though they're extremely uncomfortable with it.

目前有5500人正在参加Claw Camp，他们缓慢而痛苦地（在某些情况下）摸索着OpenClaw的复杂系统，但根据我的接触，这些参与者中大多数并非专业开发者。

We have 5,500 people who are doing Claw Camp right now, hacking their way slowly and painfully in some cases through the morass of OpenClaw, and at least based on my interactions most of the folks in there are not developers by trade.

他们甚至不一定特别懂技术。

They're not even necessarily particularly technical.

他们只是对构建代理和代理团队可能为他们的生活带来的改变感到无比兴奋的人。

They're just folks who are really excited about what the idea of building agents and agents teams could mean for them in their lives.

换句话说，就主动式AI而言，我的基本判断是：我们将严重低估那些将主动式AI视为消费级AI核心组成部分的人群比例，我认为这将极大地改变竞争格局。

In other words, my base case when it comes to Agentic AI is that we are going to radically underestimate the portion of the world for whom that becomes an integral part of consumer AI, and I think that that could shape the competitive dynamics quite a bit.

接下来的几个类别涉及竞争和锁定效应。

The next couple of categories have to do with competition and lock in directly.

随着采用率的成熟，一个关键问题是：人们已融入的系统中的整合程度会有多重要？

As adoption matures one question will be how much integration into the systems that people are already integrated into will matter?

这可以称为谷歌Gemini或苹果智能的问题。

Call this the Google Gemini or Apple Intelligence question.

人们会默认使用手机内置的AI，还是会在此之外做出明确的消费选择？

Are people going to just default to whatever AI is on their phone or are they going to make distinct consumer choices beyond that?

像X和Meta这样的网络将其AI集成到社交网络中，会有多大的影响力？

How powerful will it be that networks like X and Meta have their own AI's integrated into their social networks?

另一个相关的问题，也回到人们愿意使用多少种模型，即工作生态系统中的整合程度最终会有多重要？

Another kind of related question which also goes back to the how many models people are willing to use, is how much integration into the work ecosystem will ultimately matter?

简而言之，人们平均会在家使用一种工具，而在工作时使用另一种不同的工具或工具平台吗？

Basically will people on average be fine using one tool at home and a different tool or different platform of tools at work?

目前的早期证据表明，是的，人们愿意做出这种区分。

Certainly the early evidence suggests that yes, people will be willing to make that separation.

事实上，企业用户的一大抱怨是，他们在工作中必须使用Copilot的版本，而在个人生活中却可以自由选择其他工具套件中的任何工具。

In fact, of the big complaints for enterprise users is that they have to use versions of Copilot at work, whereas they can choose whatever they want from another suite of tools when they're engaging in their personal lives.

有趣的是，工作AI与家庭AI之间的分界，反而可能让人们更愿意在不同模型之间切换，而不是在没有这种差异的情况下。

Interestingly, a division between Work AI and Home AI might actually make people have more appetite for model switching than if they didn't have that difference.

换句话说，一旦你已经在工作用的模型和家庭用的模型之间来回切换，你就已经建立了切换模型的心理和实际框架，因此再增加第三个甚至第四个模型，可能也不会让你感到太困扰。

In other words, once you're already going back and forth between one model for work and one model for home, you've got the mental and practical frameworks for model switching and so maybe adding a third or even a fourth model into the mix doesn't really bother you as much.

这就引出了切换成本的问题。

Which gets into the question of switching costs.

目前来看，这些网络和模型之间的切换成本似乎非常低。

Right now it feels like the switching costs between these networks and models are extremely low.

人们可以随时在自己偏好的模型之间自由切换，而且似乎频繁地这样做。

People can just bounce between the one that they prefer at any given time, and they seem to do so with pretty high frequency.

但对此有一个重要的例外和前提，那就是记忆方面的壁垒。

One of the big caveats and provisos to that is something of a moat in memory.

如果你已经花了大量时间向ChatGPT或Claw提供关于你本人、你的工作或某个项目的上下文信息，那么将这些内容迁移到另一个平台会非常痛苦。

If you've spent a bunch of time giving ChatGPT or Claw context about you or your work or a project, it can be really painful to switch that to another platform.

正如我们最近所见，像Anthropic这样的公司已经试图减轻这种痛苦。

Now as we've recently seen, companies like Anthropic have tried to minimize this pain.

在五角大楼事件后的消费者宣传活动期间，他们推出了一项功能，允许用户更好地将其他提供商的记忆导入Clawd，但即便如此，这种记忆导入仍然非常轻量。

Around the consumer campaign post Pentagon blowup, they pushed a feature which would allow people to better import memory from their other provider into Clawd, but again it was still a pretty lightweight memory import.

实际上，这只是一个你在ChatGPT或其他你正在使用的LLM中运行的提示，然后将结果粘贴到Clawd的记忆区域下方。

Effectively it was just a prompt that you run-in ChatGPT or whatever other LLM you were using, and you paste the results into Clawd's memory below.

对我这样的人来说，这远远不够。

For someone like me this is not going to cut it.

我在Clawd中有20个不同的项目，每个项目都有各自独立的记忆、文件和上下文，仅靠一个全局性的提示根本无法满足这种需求。

I have 20 different projects in Clawd each that have their own memory base and files and context, and a simple prompt across the whole thing is just not going to cut it for that.

当然，也许我并不能代表普通消费者用户，但这恰恰说明了这个问题值得探讨。

Now again maybe I'm not representative of those general consumer users and so that changes, but that's exactly why this is a question.

现在，一个有趣的转折点将我们引向最后一个部分——关于伦理与监管：我并不会对可能出现的关于数据和记忆可移植性的政策或法规感到意外。

Now one interesting wrinkle which bridges us to our last section which is about ethics and regulation is I would not be surprised if we might see some sort of policy or regulations around data and memory transportability.

我无法顺利地将我在Anthropic中的所有上下文导出并迁移到OpenAI，这种状况或许会被社会认为并不构成一个正当的商业护城河。

The fact that I don't have a good way to export all of my context from Anthropic and take it over to OpenAI might be something that we decide as a society isn't really a legitimate business moat.

毕竟这是我的记忆和上下文，难道我不应该能够一键将其传输到我选择的任何模型平台吗？

It is after all my memory and context, so shouldn't I be able to with a single click be able to transport it to whichever model platform I choose?

这肯定会引起争论，双方都有合理的观点，但根据我们在其他相关领域看到的其他类型监管，如果这种情况真的发生，我一点也不感到惊讶，而这显然会进一步降低切换成本。

That will certainly be a debate and there's reasonable takes on both sides, but I would not at all be surprised based on the other types of regulations we've seen in other adjacent areas if that becomes a thing, which obviously would lower switching costs even more.

这就引出了最后一个类别：伦理与监管。

Which gets us to the last category: ethics and regulation.

这尤其相关，因为OpenAI和ChatGPT在Anthropic拒绝合作后，立即与五角大楼达成协议，因此面临巨大压力。

This is particularly pertinent as OpenAI and ChatGPT face a ton of heat after taking a deal with the Pentagon right after Anthropic was unwilling to concede.

Quitgpt.org声称有250万人参与了他们的抵制活动，而实际的卸载数量以及Anthropic应用下载量的惊人增长表明，这绝非空谈。

Quitgpt.org argues that 2,500,000 people have taken part in their boycott, and certainly the actual uninstall numbers, as well as the insane growth in app downloads on Anthropic, suggest that this is not all just bluster.

然而，我认为这股不满情绪的深度和持久性仍是一个问题。

I do think, however, that there's a question of how deep and durable this consternation is.

首先，250万是一个庞大的数字，但当你面对一个9亿用户的群体时，这还不到百分之一。

First of all, 2,500,000 is a lot, but it's also a lot less than a single percentage point when you're talking about a user base of 900,000,000.

绝大多数ChatGPT用户可能根本不会关注这些事情。

The vast majority of ChatGPT users probably aren't paying attention at all to this stuff.

即使对于那些关注的人，如果我们真的推出了GPT 5.4（顺便说一句，周二OpenAI发帖说5.4会比你想象的更快上线，其中的'T'大写，我只能推测是指周四），人们的不满能持续多久呢？

And even for those who are paying attention, if and when we actually get GPT 5.4 (which by the way on Tuesday OpenAI posted 5.4 sooner than you think with the capital on T which I can only assume means Thursday how durable are people's complaints going to be?

如果5.4真的像X平台上那些兴奋的人现在吹嘘的那样彻底颠覆一切，那这250万人中会有多少人重新回来？

If 5.4 kicks the slats out of everything as the excited folks on X are blustering about right now will any of those 2,500,000 come back?

我不知道，但显然这些问题对伦理和原则在长期采用问题上的实际影响力有着重大影响。

I don't know, but obviously those questions have a big impact on how much ethics and principles are actually going to matter when it comes to the long term questions of adoption.

还有一个问题是，人们究竟会在哪些伦理议题上真正关心。

There's also the question of which ethics issues people will actually care about.

围绕人工智能的事情太多了。

There are so many things surrounding AI.

人们会在乎失业问题吗？

Are people going to care about job loss?

人们会在乎存在性风险吗？

Are people going to care about existential risk?

人们会在乎知识产权、版权问题和艺术家权益吗？

Are people going to care about IP issues and copyright issues and artist rights?

这件事会不会像其他所有事情一样，被美国两党之间的对立所吞噬？

Will it get eaten up by the partisan divide in America as everything else does?

我认为这周有一些证据表明，当涉及到这一切时，两党之间的分裂比具体的AI问题更具影响力。

I think that there is some evidence this week that the partisan cleave is more powerful than specific discrete AI issues when it comes to all of this.

我不认为这完全正确，而且我认为，与美国政治的其他领域相比，AI目前的党派色彩要少得多，对此我深感庆幸。

I don't think this is strictly true, and I think that AI is far less partisan than other areas of American politics right now, which I am massively grateful for.

但我也认为，QuitGPT运动如今之所以产生共鸣，部分原因在于几周前，人们开始在进步派和自由派圈子中流传，格雷格·布罗克曼目前是特朗普最大的捐助者之一。

But I also think that part of the reason that the QuitGPT campaign is being resonant right now is that just a couple of weeks ago it started to get into progressive and liberal circles that Greg Brockman was one of Trump's biggest donors right now.

这并没有演变成全面的抵制，但已经有人因为这个原因放弃了ChatGPT。

It didn't organize itself into a full boycott, but there were already people who were dropping ChatGPT for that reason.

我不知道那250万放弃ChatGPT的人中有多少自认为是进步派或自由派，但我猜测，其中相当一部分人更在意的是，Anthropic正在与特朗普政府对抗，而不是任何普通政府试图对私营公司施加影响。

I don't know what percentage of those 2,500,000 who have dropped ChatGPT would identify themselves as progressive or liberal, but my guess is that a fair bit of them have more issues with the fact that it's the Trump White House that Anthropic is fighting with than just any old White House trying to exert its will on a private company.

如果你从这段话中能记住一点，那就是消费者AI领域的竞争远不止谁的模型更优秀。

If you take anything away from this, it's that the consumer AI battle is wildly more dynamic than just who has the best model.

这还涉及氛围、使用场景、分发渠道、生态系统锁定、商业模式伦理，以及更多其他因素。

There are questions of vibes, use cases, distribution, ecosystem lock in, monetization ethics, and so much more.

而且重要的是，这不仅仅是因为它是个适合在播客里讨论的有趣话题。

And importantly, this doesn't just matter because it's an interesting thing to talk about on podcasts.

它之所以重要，是因为它将决定这些公司向我们推送哪些产品。

It matters because it's going to shape what products these companies put in front of us.

总之，朋友们，这就是我对塑造消费级AI竞争格局的那些重大问题的探讨。

Anyways, guys, that is my exploration of the big questions shaping the consumer AI battle.

而目前，今天的AI每日简报就到这里。

And for now, that's going do it for today's AI Daily Brief.

一如既往，感谢你们的收听或观看。

Appreciate you listening or watching as always.

我们下次再见，保重！

Until next time, peace!