人工智能能力过剩

今天在AI每日简报中，我们将探讨AI能力过剩及其应对之策。

Today on the AI daily brief, the AI capabilities overhang and what to do about it.

在此之前，先看头条新闻：为什么Clog代码正式进入主流视野。

Before that in the headlines, why Clog code is officially breaking into the mainstream.

《AI每日简报》是一档每日更新的播客和视频节目，聚焦AI领域最重要的新闻与讨论。

The AI daily brief is daily podcast and video about the most important news and discussions in AI.

好了，朋友们。

Alright, friends.

在正式开始之前，先做几个快速公告。

Quick announcements before we dive in.

首先，感谢今天的支持方：Zencoder、Landfall IP、Robots and Pencils 和 Super Intelligent。

First of all, thank you to today's sponsors, Zencoder, Landfall IP, Robots and Pencils, Super Intelligent.

要获取无广告版本的节目，请前往 patreon.com/aidailybrief，或在Apple播客订阅。

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

无广告版本每月仅需3美元。

Ad free is just $3 a month.

我真的很努力地定价，让那些真的不想听这些广告的人，现在花不到一杯咖啡的钱就能获得无广告版本。

I really tried to price it in a way where anyone who really doesn't wanna hear those ads can get it for less than the price of a cup of coffee at this point.

但如果你在另一端，有兴趣赞助这个节目，请发送邮件至 sponsors@aideallybrief.ai。

But if on the other end of the spectrum you are interested in sponsoring the show, send us a note at sponsors@aideallybrief.ai.

最后，在我们深入之前，再快速提醒一下大家去查看 aidbintel.com。

Lastly, before we dive in, another quick call to check out aidbintel.com.

本周稍晚时候，注册的人将开始了解到这个看起来很酷的图表究竟是什么。

A little later this week, people who sign up are going to start finding out what this cool looking chart is.

我向你保证，你绝对不想错过。

I promise you, you won't want to miss it.

再次提醒，是 aidbintel.com。

Again, that's aidbintel dot com.

好了，这些都说完，我们开始吧。

With that out of the way, let's dive in.

欢迎回到《AI每日简报》新闻版，五分钟内为你呈现所有你需要的每日AI新闻。

Welcome back to the AI Daily Brief headlines edition, all the daily AI news you need in around five minutes.

今年一月以来，主流观点逐渐稳定下来，认为能力格局正在发生转变，焦点集中在Opus五、Claude Code，以及最近更受关注的Claude Cowork上。

The story of this January so far has been the slow but steady settling in of the notion of a shift in capabilities, centered upon Opus five, Claude Code, and now more recently Claude Cowork.

事实证明，这种变化并不仅仅局限于X平台上那些资深AI用户。

Turns out the change is not just among the highly enfranchised AI users on X.

《华尔街日报》上周末宣称，Claude正在席卷AI界，甚至连非技术人士都感到震惊。

The Wall Street Journal declared over the weekend that Claude is taking the AI world by storm, and even non nerds are blown away.

《华尔街日报》写道，人们称之为‘被Claude赋能’。

The WSJ writes, They call it getting Claude pilled.

这是软件工程师、高管和投资者将工作交给Anthropic的云AI，然后见证一台具有惊人能力的思考机器出现的时刻，即便在如今强大AI工具泛滥的时代也是如此。

It's the moment software engineers, executives, and investors turn their work over to Anthropix Cloud AI and then witness a thinking machine of shocking capability, even in an age awash in powerful AI tools.

文章指出，社交媒体上涌现出巨大的正面浪潮，许多非技术人员借助Cloud Code，在完全不懂编程的情况下开发出了自己的第一段软件。

The article noted the huge wave of positivity on social media, with many non technical people using Cloud Code to develop their first piece of software without knowing the first thing about coding.

文章还提到，Claude Code已被应用于其他多种用途，包括健康数据分析和费用报告整理。

It also noted that Claude Code is being deployed for a range of other use cases including health data analysis and expense report compiling.

《大西洋月刊》也有类似观点，写道：‘让位吧，ChatGPT。’

The Atlantic had a similar take, writing Move over ChatGPT.

文章称，尽管Claude Code在技术上是一个AI编程工具，因此得名，但这个机器人还能完成各种计算机任务，比如预订剧院票、处理购物退货或下单DoorDash。

The article says, Though Claude Code is technically an AI coding tool hence its name the bot can do all sorts of computer work book theater tickets, process shopping returns, or order DoorDash.

人们正在用它来管理个人财务和种植植物。

People are using it to manage their personal finances and to grow plants.

我不知道《大西洋月刊》为什么第一个例子是预订剧院票，但这确实如此。

I don't know what it says about The Atlantic that the first example they reached to is book theater tickets, but there you go.

作者提到，为了撰写这篇文章，他们首次使用了氛围编程工具，并惊讶地发现自己在没有任何编程知识的情况下，几分钟内就创建了一个全新的个人网站。

The author remarked that they used vibe coding tools for the first time in preparation for the article and was astonished that they could create a new personal website in minutes without any coding.

接下来的几天里，他们又启动了十几个额外的项目。

They went on to spin up a dozen additional projects over the next few days.

他们发信息给朋友尝试一下，朋友回复说：它真的能干各种事。

They texted a friend to try it out and received the response, It just does stuff.

ChatGPT就像修车工给你提供关于你汽车的建议。

ChatGPT is like if a mechanic just gave you advice about your car.

Claude Code则像修车工亲自把车修好了。

Claude code is like if the mechanic actually fixed it.

说实话，我觉得这么说还远远不够贴切。

To be honest, I don't really think that does it justice.

我觉得更准确的说法是，使用Claude Code就像你把车送去维修时，可以要求换一辆别的车，几分钟后，那辆车就会直接停在那里等你。

I think it's more like Claude code is like if when you dropped off your car at the mechanic you could request any other car, and all of a sudden a few minutes later, it would just be there waiting for you.

这篇文章中提到了一位名叫亚历克斯·利伯曼的用户，他声称，就其影响而言，这甚至比‘Chat Chippy Tea’时刻还要重大。

A user named Alex Lieberman was profiled for the piece and claimed that in terms of implication, this was even bigger than the Chat Chippy Tea moment.

然而，他补充说，潘多拉的盒子对世界其他地方来说还尚未打开。

However, he added Pandora's box hasn't been opened for the rest of the world yet.

不过，这种情况可能不会持续太久，因为各大媒体现在都在盛赞Anthropic的产品系列。

That might not be the case for long, however, with major publications now raving about Anthropic's product lineup.

Claude Code的创作者博里斯·切尔尼谈到这场一夜成名的背后是多年积累，他说：‘很高兴看到Claude Code终于开始崭露头角。’

Claude Code creator Boris Cherny remarked on the overnight success that was years in the making, saying, Glad to see Claude Code starting to break through.

这一年我们付出了巨大的努力，而我们才刚刚开始。

It's been a year of very hard work, and we're just getting started.

阿吉尼·米达写道：‘今天《华尔街日报》的头版报道的是普通人使用命令行界面。’

Ajni Mida writes, The front page of The Wall Street Journal today is about everyday people using a command line interface.

如果你是一名企业领导者，却不重新审视关于这个世界的重要运营假设，那你就是在严重辜负自己和依赖你的人。

If you are a business leader and not revisiting major operating assumptions about the world, you are doing yourself and the people who depend on you a massive disservice.

还有另一个关于Anthropic的故事，他们最近的融资进展如何？

One other Anthropic story the latest on their reported fundraising?

我们之前听说的那轮估值高达3500亿美元的融资，现在似乎被扩大到了高达250亿美元，其中包括来自微软和英伟达的约150亿美元，以及来自风投和其他投资者的另外100亿美元。

That round that we've been hearing about that values Anthropic at $350,000,000,000 is apparently getting supersized up to potentially $25,000,000,000 That includes about 15,000,000,000 from Microsoft and Nvidia, and another 10,000,000,000 from VCs and other investors.

这些风投中显然包括红杉资本。

Among those VCs is apparently Sequoia.

感觉我们可能再过几周就会看到这笔交易完成，所以我相信很快就会有更多消息。

Feels like we're probably within a few weeks of this closing, so I'm sure we'll get more news soon.

尽管《华尔街日报》对Claude赞不绝口，但美国用户显然对这项技术整体仍持担忧态度。

Now despite The Wall Street Journal writing so glowingly about Claude, US users clearly remain concerned about the technology overall.

根据谷歌委托益普索进行的一项新调查，如今使用AI的人已占多数。

According to a new survey commissioned by Google and conducted by Ipsos, AI users are now in the majority.

66%的受访者表示，他们在过去12个月内使用过AI，而2024年调查中这一比例为48%，2023年则为28%。

66% of respondents said they had used AI in the past twelve months compared to 48% in the 2024 poll and 28% in 2023.

这是这项纵向调查的第三年，调查于去年九月下旬进行，因此数据相对最新。

This was the third year of the longitudinal survey which was conducted in late September last year, so relatively up to date.

该调查在21个国家各采访了约1000名成年人。

The survey polled around 1,000 adults from each of 21 countries.

在AI对就业的影响方面，受访者意见均分：50%的人认为AI在职场将创造就业机会，另外50%认为AI将消除工作岗位。

Respondents were evenly split when it comes to AI job disruption, with 50% saying AI in the workplace will create jobs and fifty percent saying it will eliminate jobs.

尽管如此，大多数调查参与者支持推动AI发展，占比58%，而希望保护可能受AI冲击的行业的受访者占41%。

Still, the majority of survey participants were in favor of fostering advancements using AI at 58% compared to 41% who wanted to protect industries that might be disrupted by AI.

不出所料，对AI的乐观态度与AI使用程度密切相关。

Not surprisingly, AI optimism was closely tied to AI use.

70%表示使用过AI的人对其益处持乐观态度。

70% who said they've used AI are optimistic about its benefits.

而在经常使用AI的人群中，有86%的人感到兴奋。

And of those who use AI a lot, 86% were excited.

AI使用率高的国家与乐观情绪高的国家之间也存在强烈关联。

There's also a strong correlation between countries with high levels of AI use and high levels of optimism.

然而，美国在AI使用率和乐观程度上都排名较低。

The US, however, ranked low on both use and optimism.

仅有40%的美国受访者表示过去一年使用过AI，这是唯一一个没有多数人使用AI的国家。

Just 40% of US survey participants said they have used AI in the past year, which was the only country without a majority of AI users.

作为对比，英国为56%，墨西哥为66%，而阿联酋、尼日利亚和印度的使用率均超过80%。

As a point of comparison, The UK was at 56%, Mexico was at 66%, while The UAE, Nigeria, and India were all north of 80%.

只有33%的美国受访者表示对这项技术感到非常兴奋，这是调查中最低的国家结果，远低于整体57%的水平。

Only 33% of US respondents said they were mostly excited about the technology, the worst national result in the survey, and vastly beneath the overall result of 57%.

实际上，我认为这是一个重大的国家问题。

Now I actually think this is a major national issue.

其影响不仅关乎OpenAI和Anthropic的用户数量，更关乎人们是否认真对待这项技术可能带来的颠覆，并为此做好准备。

The implications are not just the user numbers for OpenAI and Anthropic, it's about seriousness with which people are taking the potential disruption for this technology and preparing themselves for it.

我相信，仍有一部分人希望坐等观望，回到过去的世界，而我显然不认为这会实现。

I believe there continues to be a strand of people who are hoping to just wait it out and return to the world that once was, and obviously, I do not think that that's going to happen.

接下来谈谈已成为AI政治话题一部分的问题——数据中心，xAI的Colossus II现已达到一吉瓦的算力，成为首个突破这一阈值的训练集群。

Moving over to an issue that has become part of the political cannon fodder around AI, which is of course data centers, xAI's Colossus II has now reached one gigawatt of capacity, becoming the first training cluster to cross that threshold.

这个数据中心的耗电量现在已经超过了旧金山市。

The data center is now drawing more power than the city of San Francisco.

作为对比，第一个Colossus集群的总容量为300兆瓦，而OpenAI最近披露，其整个训练和推理集群的总容量已达1.9吉瓦。

For comparison, the first Colossus cluster has a total capacity of 300 MW, while OpenAI recently disclosed that they have 1.9 GW across their entire training and inference fleet.

建设始于三月，因此这一里程碑的达成历时九个月。

Construction began in March, so this milestone was nine months in the making.

目前唯一接近的集群是Anthropic和亚马逊的新Carlyle数据中心，预计在今年第一季度内达到1吉瓦。

The only other cluster that's close is Anthropic and Amazon's new Carlyle data center, which is expected to hit one GW sometime in the first quarter of this year.

OpenAI的Stargate Abilene预计将在今年夏天上线。

OpenAI's Stargate Abilene is expected to come online over the summer.

目前，xAI是唯一一家能获得如此大规模算力的公司，这正是我们之前讨论过的、可能为Grok带来未来竞争优势的重大机会。

For now, xAI is the only company with access to this much compute, which is exactly what we discussed as the big potential opportunity that could translate into differentiation for Grok in the year to come.

Colossus II还采用了Blackwell GPU，使其成为首批运行NVIDIA最新硬件的训练集群之一，也是目前唯一达到这一规模的集群。

Colossus two is also using Blackwell GPUs, making it one of the first training clusters to run NVIDIA's latest hardware and the only one at this scale.

据称，该集群当前配置包含55万台GPU。

The cluster reportedly contains 550,000 GPUs as currently configured.

正如阿马特奥·卡普兰所说，吉瓦级的Grok已经到来。

As Amateo Kaplan put it, Gigawatt Grok has arrived.

现在让我们回到马斯克的世界，埃隆·马斯克在针对OpenAI和微软的诉讼即将开庭之际，寻求高达1340亿美元的赔偿。

Now staying in Musk world for a moment, Elon Musk is seeking up to $134,000,000,000 in damages from OpenAI and Microsoft as his lawsuit heads to a trial.

庭审日期已定于四月下旬，而在周五的一次听证会上，马斯克的律师量化了这些赔偿金额。

A trial date has been set for late April, and during a hearing on Friday, Musk's lawyers quantified the damages.

他们的论点是，由于马斯克在2015年向该非营利组织捐赠了3800万美元，他有权获得OpenAI当前5000亿美元估值中的一部分。

Their argument is that Elon is entitled to a portion of OpenAI's current $500,000,000,000 valuation due to the $38,000,000 in seed funding he donated to the nonprofit in 2015.

马斯克的律师在法庭文件中写道：正如一家初创公司的早期投资者可能获得远超其初始投资许多倍的收益，OpenAI和微软所获得的非法收益也远大于马斯克先生的贡献。

Musk's lawyer wrote in court filings: Just as an early investor in a startup company may realize gains many orders of magnitude greater than the investor's initial investment, the wrongful gains that OpenAI and Microsoft have earned and which Mr.

马斯克现在有权追回的收益，远比马斯克先生的初始投入要大得多。

Musk is now entitled to disgorge are much larger than Mr.

马斯克的初始投入。

Musk's initial contributions.

这其实是一种非常法律术语的说法，意思是：如果当初那3800万美元是投给一家营利性初创公司，到今天它的价值早就远不止3800万美元了。

Which is a very legalese way of saying, if that $38,000,000 had been an investment into a for profit startup, it would have been a heck of a lot more than $38,000,000 by now.

文件还指出，马斯克计划寻求惩罚性赔偿以及一项未具体说明的禁令。

The filing also says that Musk plans to seek punitive damages as well as an unspecified injunction.

OpenAI的律师驳回了这一方法，称其方法论是编造的，结果无法验证，方法本身也承认是前所未有的，而且他提出的结果——将数十亿美元从非营利组织转移给一位转为竞争者的捐赠者——从表面上看就是不可信的。

OpenAI's lawyers rejected the approach, stating that his methodology is made up, his results unverifiable, his approach admittedly unprecedented, and his proposed outcome, the transfer of billions of dollars from a nonprofit corporation to a donor turned competitor, implausible on its face.

OpenAI方面则在法庭外继续否认诉讼的前提。

OpenAI, for their part, continued to deny the premise of the lawsuit outside of the courtroom.

在一份声明中，他们表示，马斯克先生

In a statement, they said, Mr.

马斯克的诉讼仍然毫无根据，是他持续骚扰模式的一部分，我们期待在庭审中证明这一点。

Musk's lawsuit continues to be baseless and a part of his ongoing pattern of harassment, and we look forward to demonstrating this at trial.

这一最新不严肃的要求仅仅是为了进一步推进这场骚扰活动。

This latest unserious demand is aimed solely at furthering this harassment campaign.

现在在X平台上，讨论集中在格雷格·布罗克曼私人笔记的页面上，这些内容在新提交的文件中被披露。

Now on X, the discussion centered around pages from Greg Brockman's private notes that were revealed in the new filing.

2017年的一段特别频繁被分享的文字写道：这是我们摆脱埃隆的唯一机会。

One especially frequently shared passage from 2017 read: This is the only chance we have to get out from Elon.

他是我会选择的那位光辉领袖吗？

Is he the glorious leader that I would pick?

我们真的有机会让这件事成真。

We truly have a chance to make this happen.

从财务上讲，什么能让我赚到十亿美元？

Financially, what will take me to $1,000,000,000?

Menlo Ventures的DV Das表示：归根结底，这真的关乎钱。

DV Das of Menlo Ventures said, Deep down, it really is about the money.

现在，文件中的其他几段引述将OpenAI描绘得非常不堪。

Now several other quotes from the filing paint OpenAI in a very poor light.

引述内容：Altman说，Elon在挑选某些内容来让Greg显得糟糕，但完整的故事是，Elon一直在推动一种新结构，而Greg和Ilya花了大量时间试图弄清楚是否能满足他的要求。

The quotes: Altman said, Elon is cherry picking things to make Greg look bad, but the full story is that Elon was pushing for a new structure, and Greg and Ilya spent a lot of time trying to figure out if they could meet his demands.

Altman继续说：我记起了很多这些事，但这里有一部分我之前忘了。

Altman continued, I remembered a lot of this, but here is a part I had forgotten.

Elon说他想积累800亿美元，用于在火星上建立一个自给自足的城市，并且他需要且理应获得多数股权。

Elon said he wanted to accumulate $80,000,000,000 for a self sustaining city on Mars and that he needed and deserved majority equity.

他说他需要完全控制权，因为过去他曾因缺乏控制权而受挫；当我们讨论继任问题时，他出人意料地提到他的孩子将掌控通用人工智能。

He said that he needed full control since he'd been burned by not having it in the past, and when we discussed succession, he surprised us by talking about his children controlling AGI.

阿尔特曼在引述之后继续说：我欣赏人们坦诚表达他们的想法，因为这有助于人们解决问题或认清分歧，但埃隆声称他想要上述这些，这对格雷格理解自己真正想要什么至关重要。

Altman continues after that quote, I appreciate people saying what they want and think it enables people to resolve things or not, but Elon saying he wants the above is important context for Greg trying to figure out what he wants.

由于审判不到三个月就要开始，这个故事不幸将成为OpenAI在关键一年中执行计划的重大负担。

With the trial less than three months away, the story is unfortunately going to be a big overhang for OpenAI as they try to execute on a pivotal year.

正确的信号是，这会让很多人显得贪婪又丑陋。

Right signal, this is going to make a lot of people look greedy and ugly.

希望我们不必在这上面花太多时间。

Hopefully we won't have to spend too much time on this.

我可能会开始只分享那些真正重大的亮点，当这些内容成为无法回避的热议话题时——就像过去几天那样。

I'll probably start to air on only sharing the really big highlights where it becomes a major inescapable point of conversation as it has been for the last couple of days.

然而，这个节目不会变成一场事无巨细的法庭剧，尽管它可能非常有趣且充满八卦。

This show, however, will not become a play by play court drama, as interesting and salacious as it might be.

目前，今天的头条新闻就先说到这里。

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

接下来是主节目。

Next up, the main episode.

如果你用AI来编程，问问自己：你是在开发软件，还是只是在玩提示轮盘赌？

If you're using AI to code, ask yourself: Are you building software, or are you just playing prompt roulette?

我们知道，非结构化的提示一开始有效，但最终会导致AI垃圾和技术债务。

We know that unstructured prompting works at first, but eventually it leads to AI slop and technical debt.

接下来是ZenFlow。

Enter ZenFlow.

ZenFlow帮你从随意编码转向AI优先的工程实践。

ZenFlow takes you from vibe coding to AI first engineering.

它是首个将纪律引入混乱的AI编排层。

It's the first AI orchestration layer that brings discipline to the chaos.

它将自由形式的提示转化为规范驱动的工作流和多智能体验证，让智能体相互交叉检查以防止偏离。

It transforms freeform prompting into spec driven workflows and multi agent verification, where agents actually cross check each other to prevent drift.

你甚至可以指挥一组并行智能体，同时实现功能和修复漏洞。

You can even command a fleet of parallel agents to implement features and fix bugs simultaneously.

我们已经看到团队的交付速度提升了2到10倍。

We've seen teams accelerate delivery 2x to 10x.

别再拿提示词赌博了。

Stop gambling with prompts.

开始有条不紊地协调你的AI。

Start orchestrating your AI.

在 zenflow.free 上将原始速度转化为可靠、符合生产标准的成果。

Turn raw speed into reliable, production grade output at zenflow.free.

如果你正在听这段内容，你已经知道AI正在多快地为创新、颠覆和价值创造制定规则。

If you're listening to this, you already know how fast AI is writing the rules for innovation, disruption, and value creation.

而这个新时代需要一种新型的专利律师事务所。

And this new era demands a new kind of patent law firm.

Landfall IP 从零开始构建，旨在以不同方式运作，协调人类专业知识与AI协同工作，以创始人速度生成更优质的专利。

Landfall IP was built from the ground up to operate differently, orchestrating how human expertise and AI work together for better patents at founder speed.

Landfall IP 由顶尖专利律师创建，他们看到了更好的方法：让AI执行重复性工作，而律师则专注于创造非凡成果。

Created by world class patent attorneys who saw a better way, Landfall IP lets AI execute the repeatable while attorneys elevate to create the exceptional.

Landfall 不是适应 AI，而是为 AI 而生。

Landfall isn't adapting to AI they were built for it.

有新点子吗？

Have a new idea?

免费试用 Discovery Agent。

Try the Discovery Agent for free.

这是一款保密工具，帮助创新者整合他们的发明，并立即获得可专利的洞察。

It's a confidential tool that helps innovators synthesize their inventions and instantly see patentable insight.

访问 landfallip.com 了解更多信息。

Visit landfallip.com to learn more.

就是 landfallip.com。

That's landfallip.com.

本期节目由 Robots and Pencils 赞助，这是一家快速增长的公司。

Today's episode is brought to you by Robots and Pencils, a company that is growing fast.

作为一家高速发展的 AWS 和 Databricks 合作伙伴，他们正在寻找精英人才，期待在 Velocity 实现真正的影响。

Their work as a high growth AWS and Databricks partner means that they're looking for elite talent ready to create real impact at Velocity.

他们的团队由天生适应AI的工程师、战略家和设计师组成，他们热衷于解决难题，并推动AI在真实产品中的应用。

Their teams are made up of AI native engineers, strategists, and designers who love solving hard problems and pushing how AI shows up in real products.

他们借助Roboworks这一智能代理加速平台快速推进，使团队能在数周内而非数月内交付切实成果。

They move quickly using Roboworks, their agentic acceleration platform, so teams can deliver meaningful outcomes in weeks, not months.

他们不组建庞大的团队。

They don't build big teams.

他们打造的是高效且灵活的团队。

They build high impact, nimble ones.

那里的员工极其聪慧，拥有专利、发表的研究成果，并参与过塑造整个品类的工作。

The people there are wicked smart with patents, published research, and work that's helped shape entire categories.

他们工作在专注于目标、有明确方向的Velocity小组和工作室中。

They work in velocity pods and studios that stay focused and move with intent.

如果你准备好从事能定义职业生涯的工作，与那些既挑战你又支持你的同行共事，Robots and Pencils就是你的不二之选。

If you're ready for career defining work with peers who challenge you and have your back, Robots and Pencils is the place.

前往robotsandpencils.com/careers了解开放职位。

Explore open roles at robotsandpencils.com/careers.

那就是 robotsandpencils.com/careers。

That's robotsandpencils.com/careers.

本期节目由Super Intelligent赞助。

Today's episode is brought to you by Super Intelligent.

Super Intelligent是一个平台，简单来说，它的目标是帮助你的公司弄清楚如何更好地使用AI。

Super Intelligent is a platform that, very simply put, is all about helping your company figure out how to use AI better.

我们部署语音代理来采访公司内部的员工，结合其他公司成功经验的专有洞察，为你提供一套关于应用场景和变革管理举措的建议，从而形成一份能帮助你从AI中获取价值的AI路线图。

We deploy voice agents to interview people across your company, combine that with proprietary intelligence about what's working for other companies, and give you a set of recommendations around use cases, change management initiatives that add up to an AI roadmap that can help you get value out of AI for your company.

但现在，我们希望为公司内部负责这一转型的人员提供一个更直接的平台。

But now we want to empower the folks inside your team who are responsible for that transformation with an even more direct platform.

我们即将推出的AI战略指南工具现已准备就绪，可以开始测试。

Our forthcoming AI Strategy Compass tool is ready to start to be tested.

这是任何负责公司内部AI采用或AI转型人员的强力工具。

This is a power tool for anyone who is responsible for AI adoption or AI transformation inside their companies.

它将让你能够完成我们在Super Intelligent所做的许多工作，但方式更自动化、更自主，并且成本结构完全不同。

It's going to allow you to do a lot of the things that we do at Super Intelligent, but in a much more automated, self managed way, and with a totally different cost structure.

如果你有兴趣试用，请访问 aideiallybrief.aicompass，填写表格，我们会尽快与你联系。

If you are interested in checking it out, go to aideallybrief.aicompass, fill out the form, and we will be in touch soon.

欢迎回到《AI每日简报》！

Welcome back to the AI Daily Brief!

今天，我们要讨论一个叫做‘AI能力过剩’的概念。

Today, we are talking about something called AI capabilities overhang.

这是我经常思考的问题，但这个概念的具体背景源于一篇与OpenAI宣布ChatGPT将推出广告相关文章。OpenAI表示，其中的一个问题是访问受限，而广告将帮助他们解决这一访问问题。

Now, is something I think about a lot, but the specific context for it was an article that came out as part of the broader set of assets around OpenAI's announcement that ads are coming to ChatGPT, with them basically saying that part of the issue is access and ads are going to help them with that access issue.

在这篇名为《AI赋能自我》的博客文章中，OpenAI将能力过剩定义为：当前AI系统所能实现的功能，与大多数个人、企业及国家实际大规模利用这些功能所产生的价值之间的差距。

Now, in that blog post called AI for Self Empowerment, OpenAI defines the capability overhang as the gap between what AI systems can do now and the value most people, businesses, and countries are actually capturing from them at scale.

换句话说，就是AI当前能力与社会当前使用水平之间的差距。

In other words, the delta between AI's current capabilities and society's current usage of them.

这个概念的关键在于，它讨论的不是某种未来状态。

And what's important about this concept is this is not about some future state.

也就是说，这并不是关于通用人工智能、超级智能或类似议题的争论。

This is not, in other words, a debate about AGI or superintelligence or anything like that.

相反，这是一个关于当前现状的讨论，探讨不同人群在利用这一技术方面落后了多少。

It is instead a discussion of the current state of play and how far behind different types of people and groups are in taking advantage of it.

所以今天我想谈谈AI能力缺口在六个不同群体中的表现：个人、社区、市政机构、教育者、企业和主权国家。

So what I want to do today is talk about the AI capabilities overhang across six different groups: individuals, communities, municipalities, educators, businesses, and sovereigns.

对于每个群体，我想简要讨论一下当前的能力缺口是什么样子，可能的解决方案有哪些，以及我们——这里的‘我们’可以指社会，也可以指本播客的听众——如何帮助应对这一能力缺口，改善人们利用当前技术可能性的方式。

For each of those groups, I want to talk a little bit about what the capabilities overhang looks like at the moment, what some of the answers to that overhang might be, and how we and this is the royal we, I could mean society, I could mean the listeners of this podcast but how we could support tackling that capabilities overhang and improving the way that people are taking advantage of what's possible right now.

那么我们先来谈谈个人。

So let's talk first about individuals.

当然，这是一个涵盖范围极广的类别，不同个体在这项能力缺口上的程度差异巨大。

Now this is admittedly a wildly all encompassing category with a huge range of different levels of this particular overhang.

虽然几乎没有人能声称自己完全没感受到这种缺口，但即使像我这样几乎把所有时间都花在这上面的人，也认为自己尚未充分利用许多可能的应用场景。

While there are very, very few people who could claim that they don't experience that overhang at all, In fact, even as someone who spends basically all of my time on this, I think that there are entire categories of what's possible that I don't take nearly full enough advantage of.

大多数人处于从几乎未利用到刚刚开始利用之间的某个阶段。

Most people fall somewhere on the spectrum from barely taking advantage to only just starting to take advantage.

事实上，我认为你之所以看到Claude Code如此受追捧，并逐渐进入《华尔街日报》等主流媒体视野，正是因为对那些开始使用它的人来说，它正通过极大提升效率，直接而显著地缩小了这一能力缺口。

In fact, I think part of the reason that you're seeing so much excitement around Claude Code and see it moving into the mainstream in The Wall Street Journal and things like that is that for people who are picking it up, it is radically and directly undercutting that capabilities overhang by massively accelerating what people can do.

但能力滞后的影响是巨大的。

But the implications of the capabilities overhang is dramatic.

需要多年才能掌握的技能，现在可以在几小时内得到增强或复制。

Skills that took years to develop can now be augmented or replicated in hours.

这种知识工作的商品化当然会带来替代风险，但同时也带来了巨大的机遇，因为它能极大地提升人们的效能。

Now this sort of commoditization of knowledge work creates displacement risk of course, but it also creates incredible opportunity in terms of the massive leverage that it can give people.

然而，就个人层面而言，能力滞后的一个影响是，个人的经济护城河正在比人们意识到的更快地消失。

One of the implications of the capabilities overhang, however, when it comes to that individual focus, is that personal economic moats are eroding faster than people realize.

换句话说，‘我应该学习这些AI技术’和‘我昨天就需要它’之间的差距正在迅速缩小。

In other words, the gap between I should learn this AI stuff and I needed it yesterday is closing.

那么，有哪些挑战呢？

So what are some of the challenges?

信息是其中之一，我所说的不仅仅是关于AI能做什么的信息——虽然这也是其中一部分——但我认为我们在讨论AI的方式上存在真正的问题。

Information is one, and by that I don't just mean information about what's possible with AI, although that's part of it, but also I think we have a real issue in the way that we discuss AI.

每一项调查都显示，尽管略显简化，但事实确实如此：东亚和低收入国家对AI极为热情，而西方和高收入国家的人们则相对不那么热衷。

Every survey that comes out shows that to be a little bit reductionist, but honestly not all that much, Eastern and lower income countries are extremely enthusiastic about AI, while people in Western and higher income countries are less so.

造成这种现象的原因多种多样，但这意味着，除了普遍的信息差距之外，还存在巨大的热情差距——那些不喜欢人工智能或希望它不存在的人正越来越落后，幻想着它会自行消失。

There are all sorts of reasons for this, but what it means is that in addition to just a general information gap, you also have a massive enthusiasm gap, which means that people who don't like AI or wish it didn't exist are getting farther and farther behind, kind of hoping that it just goes away.

随便登上任何一个社交媒体平台，你都能看到大量帖子，人们热切期待泡沫破裂，好让一切回归正常，尽管所有正在收听这个节目的人都清楚一个不可否认的事实：根本不存在什么回归正常这回事。

Go on any social media platform and you will be able to find myriad posts about people enthusiastically waiting for the end of the bubble so things can go back to normal despite the incontrovertible fact known by everyone who is listening to this particular show that there is no such thing as going back.

因此，不仅要提高人们对AI能力的认知，也要让人们意识到某些变化因AI而不可避免，这是克服这一能力落差的关键部分。

So improving information availability about what you can do with AI, but also about, to some extent, the inescapability of some changes because of it, is a key part of overcoming this overhang.

另一个部分当然是获取途径。

Another part is, of course, access.

目前，能支付更多费用的人拥有更好的AI访问权限。

People who can pay more right now have better access to AI.

然而，这种差距未必像表面看起来那么大。

However, the gap isn't necessarily as big as it seems.

尽管ChatGPT的数据显示，典型高级用户使用的计算资源是普通用户的七倍，但即使是这些工具的免费版本，也仍为任何人提供了惊人的可用能力。

Although ChatGPT data shows that the typical power user of their system uses seven times more compute than a typical user, there's still incredible capacity available to anyone, even in the free versions of these tools.

在我观察人们参与‘新年AI决心’（这是我新年一期节目推出的为期十周的自我教育计划）时，一件特别有趣的事是：许多处于高度优势群体的人，也开始发现免费版工具能为他们带来多少价值。

One of the things that's been super interesting to me watching people interact with the New Year's AI Resolution, which is the ten week self education program that came out of my New Year's episode, is that a lot of folks, despite being on the very high end of enfranchised users, are seeing how much they can get out of the free versions of these tools.

我实际上认为，这对普通用户来说非常有价值，甚至在很多方面比像我这样会为每个新工具都购买高级或顶级订阅的疯狂人士更具指导意义。

I actually think that that's incredibly valuable and more instructive in many ways to the average user than some insane person like me who's going to pay for the ultra or max subscription to every single tool that comes along.

我要说的是，即使如此，访问质量仍将继续成为一个问题，而且可能会变得更糟。

I will say that I think even with this, a quality of access is going to continue to be an issue and probably one that gets worse.

尽管我们可能不喜欢ChatGPT中的广告体验，但我相信它确实扩展了访问渠道，并以非广告模式无法实现的方式保持了访问的民主化。

As much as we might not like the experience of ads in something like ChatGPT, I do believe that it does extend access and keeps access democratized in a way that a non ad supported model just couldn't.

然而，平台的广告绝不是确保访问的唯一方式。

However, ads from the platforms are certainly not the only way to ensure access.

政府在这里可能发挥作用，坦率地说，这正是为什么一些关于阻止数据中心建设的想法如此荒谬的原因——因为它们很可能产生恰恰相反的效果，进一步将访问权限限制在仅能负担得起的人手中。

There might be a role for government here, and frankly it's one of the reasons that some of the ideas around things like stopping data center construction are so wrongheaded because they are likely to have the exact opposite impact where they actually further restrict access to only the people who can pay for it.

那么，我们该如何帮助个人克服能力滞后呢？

So how can we support individuals overcoming the capability overhang?

一是要开展关于AI的不同对话，并承认它即将到来。

One is a different conversation about AI and an acknowledgment that it's coming.

二是继续寻找方法来实现访问的民主化，无论是通过平台自身的广告或其他模式，还是通过公私合作或其他更大规模的倡议。

Two is continuing to look for ways to democratize access, whether that's from the platforms themselves through ads or other models, or through public private partnerships or some other larger type of initiative.

我认为最后一点是我们今年在这档节目中会大力尝试的：自我教育的机会。

And I think the last piece, and something that certainly we will be trying to do a lot of this year with this show, is self education opportunities.

有太多人对这份新年AI决心投入了如此深的参与，我百分百确信我们会推出其他类似的时间限定但最终由个人自主完成的项目。

So many people are engaging so deeply with this New Year's AI resolution that I am 100% sure that we will release other similar time bound, but ultimately self directed types of programs.

接下来，我们来谈谈社区。

Next up, let's talk about communities.

社区拥有许多AI无法复制的资源：信任网络、本地背景、线下聚会、共同身份和问责机制。

Communities hold many of the assets that AI can't replicate: trust networks, local context, physical gatherings, shared identity, accountability structures.

而能力过剩实际上提升了这些资源的价值，因为随着数字互动越来越依赖AI，在许多情况下人们更难信任它们，面对面的社区反而成为一种稀缺资源。

And the overhang actually increases the value of these assets, As digital interactions become AI mediated and in many cases for people harder to trust, in person community becomes a premium good.

事实上，当我们思考个体能力过剩时，地方机构掌握着可用于帮助成员应对AI转型的分发和信任基础设施，但当然，目前大多数机构还没有这样思考。

In fact, as we think about the individual overhang, local institutions are sitting on distribution and trust infrastructure that could be leveraged to help members navigate the AI transition, but of course most aren't thinking this way yet.

事实上，社区面临的挑战是，社区机构往往最缺乏硬性资源，因此参与社区领导的人不得不用时间换取一切。

Indeed, the challenge for communities is that community institutions tend to be the most strapped for hard resources, and so the people who are involved in leading communities have to trade time for everything.

简而言之，当没有资金时，你就需要人们自愿奉献时间来提供服务。

Basically, when there isn't money, you require people to volunteer time in service.

这意味着用于跟上所有这些机会的时间更少了。

That means less time for keeping up with all of these opportunities.

但如果我们能将社区机构定位为日益由人工智能中介的世界中的人类层面，这些机构在我们即将进入的新时代中重新获得重要性，将蕴含巨大的潜力。

But if we can position community institutions as the human layer in an increasingly AI mediated world, there is a ton of potential power in these institutions taking on renewed importance in this new age we're moving into.

为了支持这一点，我认为我们必须从支持他们的领导者开始。

To support that, think we have to start by supporting their leaders.

我们需要为这类机构提供专门的资源、领导支持和培训，它们所关注的并非仅仅是个人层面正在发生的事情，而是如何成为传播和协助群体转型的节点。

We need dedicated resources and leadership support and training for these particular types of institutions that are not necessarily just about the same things that are going on with individuals, but are really about how to become a node for disseminating and supporting transition among constituencies.

与社区密切相关的是市政机构的能力过剩问题。

Closely related to communities is the capabilities overhang for municipalities.

市政机构当然是许多社区机构的公共和政府层面的补充。

Municipalities are, of course, the public and governmental complement to many of those community institutions.

和社区一样，它们也资源匮乏。

Like communities, they're strapped for resources.

它们有着根深蒂固的做事方式，改变起来非常困难。

They have old patterns of doing things that can be very, very difficult to change.

这些团体是否可能成为AI带来的效率提升的最大受益者？

Are these groups potentially some of the biggest beneficiaries of the efficiency gains that come with AI?

一项研究发现，市政工作人员30%到50%的时间都花在了目前即可自动化或显著加速的任务上。

One study found that thirty-fifty percent of municipal staff time is spent on tasks that are already automatable or dramatically acceleratable right now.

只需花五秒钟想想一些例子：许可证和土地使用审批时间的缩短，从等待电话、语音菜单和人工转接，转变为即时受理、自动分派和主动跟进。

And it takes about five seconds to think about some of the examples: changing review time for permitting and land use moving from hold times, phone trees, and manual routing within constituent services to instant intake automated routing and proactive follow-up.

这对公共工程、社会服务、档案管理、法院、财政收入、公共卫生等领域都可能产生影响，不一而足。

There are potential implications for public works, for social services, for records, for courts, for revenue and finance, for public health, you name it.

AI在市政领域蕴含着巨大的机遇。

AI efficiencies are so full of opportunity among municipalities.

因此，我认为我们应该投入更多的时间、精力和资源来解决这一类能力滞后问题。

And for that reason, I think we should be spending way more time, energy, and resources on trying to fix this particular category of capabilities overhang.

这会是什么样子？

What does that look like?

当然，我不知道具体该怎么做，但我认为一些机会包括不同类型的公私合作伙伴关系。

Well, of course, I don't know, but I think that some opportunities include different types of public private partnerships.

我得说，目前Model Labs和许多AI初创公司整体上的品牌形象和声誉并不算好。

I gotta say, right now, the Model Labs and many AI startups in general don't necessarily have the best brand and reputation.

整个AI行业正面临一种更广泛的认知，尤其是在西方，人们普遍认为科技不再像过去那样以服务人为目的，而只是为了让科技的创造者获利。

The AI industry as a whole is suffering from a broader sense among many people, especially in the West, that tech no longer exists to serve people to the extent it ever did, but instead serves only to enrich the people who create that technology.

现在似乎是推动一些真正将AI利益带给更广泛人群的公私合作的好时机。

Seems like a pretty good time to try to engage in some public private partnerships that actually bring the benefits of AI to a wider audience.

坦白说，这在我看来也是一个机会，可以催生一类具有不同动机的新型企业。

Frankly, this also strikes me as an opportunity for perhaps a different class of business that has different incentives.

我认为，通过AI优化市政运作，存在非常明确的盈利商业机会。

I think there are very clear profit motivated business opportunities in AI ifying how municipalities work.

但我认为，我们应当寻找新一代的创业者，其中一些人可能有市政服务背景，他们正在设计更精简、资本效率更高的服务商，能够为市政部门提供合同和服务，给予过渡性支持，而不是剥削他们。

But I think that trying to find a new generation of entrepreneurs, maybe some of whom have backgrounds in that type of municipal service, who are designing leaner, more capital efficient providers, who are going to be able to offer municipalities contracts and services that provide that transitional support without gouging them.

在我看来，这正是新一代具有公共精神的创业者以最积极方式大展身手的绝佳时机。

It just strikes me that this could be a great moment for a new class of civic minded entrepreneur to really do some damage in the best possible way.

谈到教育工作者和教育领域，天哪，真不知从何说起？

When it comes to educators and education, goodness gracious, where to even begin?

这一点我们在这个节目里讨论过很多次，尽管最近一段时间没怎么提了，你可能想不到。

This is something we've talked about a lot on this show, although not for a little while, believe it or not.

但总的来说，教育界仍然纠结于学生现在能作弊的问题，而真正的问题是，在我们即将进入的未来，考试本身已经不再重要了。

But by and large, education is stuck being concerned that students can now cheat on the test when the real problem is that in the future that we're moving into, the test doesn't matter.

我们需要彻底重新评估我们所教授的一切。

We need nothing short of a radical reevaluation of everything that we teach.

为了简化起见——虽然在座的教育工作者可能会皱起眉头，我先道个歉——让我们先把所有内容分成三类：那些绝对仍然相关的技能，比如批判性思维、道德判断、创造性解决问题、人际互动和同理心，这些都非常重要，甚至比以往更重要。

To be wildly oversimplified and reductive in a way that the educators among you are going to be cringing your faces off, I apologize in advance, let's start by separating everything into three buckets: The skills that are definitely still relevant Critical thinking, ethical judgment, creative problem solving, human interaction and empathy Relevant, relevant, relevant, relevant, in fact, more so.

有趣的是，我们过去常常贬低地称之为‘软技能’的一组能力，而我们的教育体系长期以来对此重视不足。

Also interestingly enough, a set of skills which we've often pejoratively called soft skills that we haven't had nearly enough emphasis on in our education system for a very long time.

所以，我们有了第一类：绝对仍然相关的技能。

So we've got that one bucket of definitely still relevant.

然后是那些相关性正在发生根本变化的领域：写作与表达、研究与信息整合、编程，这些领域正被AI工具彻底改变。

Then we have the things that are definitely changing in relevance: subjects that are absolutely and undeniably being transformed by AI tools: writing and composition, research and information synthesis, programming.

我们不必把婴儿和洗澡水一起倒掉，就能意识到，从用算盘加法转向用计算器加法，根本无法形容这些技能在人类如何与之互动方面所发生的巨大变革。

We don't have to fully throw out the baby with the bathwater to recognize we're talking about a lot more than going from adding with an abacus to adding with a calculator when it comes to how dramatically this set of skills is changing in terms of how humans are going to interact with them.

当然，还有可能是最大的一类，我们姑且称之为‘天知道’。

And then of course there's perhaps the biggest category, which we will generously call Who the hell knows?

这一类中会有大量内容，我们完全无法预知人工智能将如何影响它们。

There is going to be so much in this category where we simply do not know how AI is going to impact it.

能够谦逊地认识到，我们所教授的一些内容可能会变得无关紧要，但我们尚不清楚，因此必须有所保留，我认为这是一种合理的做法。

And having the humility to understand that some stuff that we're going to teach could be irrelevant, but we just don't know and we have to hedge a little bit, is I think a reasonable way to proceed.

然后当然还有第四类：新出现的相关内容。

Then of course there is a fourth bucket new things that have become relevant.

其中一部分是人工智能特有的技能，但更多将围绕管理与组织，以及帮助人们利用这样一个事实：未来每个人都能获得当今任何公司都渴望拥有的人才。

Some of that's just AI specific skills, but a lot of that's going to be in and around management and organization and basically the things that help people take advantage of the fact that each of them will in the future have access to talent that every corporation in the world would kill for today.

从那里开始，我们将围绕这些内容的平衡重新设计课程。

And then from there, we redesign the curriculum around a balance of these things.

我们会开展大规模的实验。

We run big experiments.

我们要学会接受失败。

We get okay with failure.

这种颠覆与变革的领域，谈起来可能是最容易的，但在实践中却最难实现。

This area of disruption and change is going to be some of the easiest to talk about and the hardest to actually do in practice.

我认为我们能提供的最好支持，是为真正的变革创造空间，而不是渐进式的改变，而是真正的颠覆。

And the best way I think we can support is to create space for real change not incrementalism, but true actual disruption.

今天我们讨论的倒数第二个类别，是企业的能力过剩问题。

The second to last category we'll talk about today is the capabilities overhang for businesses.

正如个体之间存在巨大差异，企业的能力过剩情况也同样多样。

And once again, just as the individuals are incredibly diverse, so too is the capability overhang for companies.

正如我们在AI投资回报调查中所见，不同层级的企业都存在能力过剩的谱系。

As we saw with our AI ROI survey, there is a spectrum of capabilities overhang for companies at every different level.

尽管某些规模的企业可能在彼此之间拥有不同的优势，但我并不认为整体上，某一类、某种类型或规模的企业所面临的能力过剩问题会明显少于其他企业。

And while it may be the case that certain sizes of companies have different types of advantages over one another, I don't believe that en masse, there is one category or type or size of business that is experiencing dramatically less overhang than some other.

企业基本上都在经历从零AI到学习如何利用AI提升效率，或者从提升效率转向真正利用AI开拓新机遇的挑战。

Companies are pretty much all dealing with going from no AI to figuring out how to use AI for efficiency, or they are dealing with the challenge of moving from efficiency to actually leveraging AI for new opportunity.

在多年从事这项工作、接触了成千上万次高管访谈后，我可以肯定地说，无论企业规模大小，包括我自己的初创公司在内，只要足够重视并希望真正做好这件事，就无一例外地会以某种方式遭遇AI能力过剩的问题。

In years of doing this and seeing thousands and thousands of executive interviews, I will say confidently that I have never seen a single company of any size including my own startup and incentivized enough to get this right that doesn't experience the AI capabilities overhang in some way.

我们刚刚举办了一次超智能闭门会议，大家坐在一起，试图彻底梳理我们所做的每一件事，并思考如何进一步用人工智能改造它们。

We just had a superintelligent off-site where all of us sat down and basically tried to tear through everything we do and ask how we could AI ify it even more.

而我们尚未做的事情，数量巨大。

And the amount that we are not doing is immense.

企业能力过剩带来的大问题，往往涉及一些非常普遍的模式。

The big problems of the capabilities overhang with businesses involve really common patterns.

在超智能公司，我们最常听到的问题是：腾不出时间来重新设计。

The thing we hear about most at Superintelligent is creating time to redesign.

我们有一整套全新的技能需要人们去掌握，但人们在学习这些技能的同时，还得完成本职工作。

We have this whole new set of skills that people are expected to learn, but they are expected to learn them while also doing their normal jobs.

当前最典型、最典型的困境就是：我们没有时间去学习那些本可以为我们节省大量时间的东西。

Classic and quintessential conundrum of the moment is that we don't have time to learn the thing that could save us so much time.

还有一个挑战是我们习惯于等待未来，而不是主动去创造未来，这自然牵涉到新机遇的问题。

There's also the challenge of our normal disposition to wait for the future rather than to go invent it, which of course gets into the idea of new opportunities.

我们还不知道，当每个公司每一位员工都能利用软件实现并创造自己的关键绩效指标时，世界会是什么样子。

We don't know what it's going to look like when every single member of every single company can use software to deliver on their KPIs and invent new ones.

但我们即将开始找到答案。

But we're going to start to find out.

当然，我们可以帮助的是，尤其是当我们离AI效率时代越远，支持人们教育的资源就越发匮乏。

Certainly something that we could help with is that especially the farther away from the AI efficiency era we get, the worse and worse the resources to support people's education we find.

虽然现在仍有很多提示工程课程，但真正优质的资源——比如非程序员如何使用编程工具、如何构建和管理智能体、如何更系统地思考自动化——却少之又少。

There are still plenty of prompt engineering courses out there, but actual really strong resources on how to use coding tools for non coders, how to build and manage agents, how to think about automations more systematically these are much fewer and farther between.

希望市场激励能很快改变这一现状，因为这里存在着巨大的市场机遇；但无论我们能做些什么来提供更多教育资源或自我学习资源，都是有益的。

Now hopefully the market incentive for this changes that in short order, because goodness gracious is there a lot of market opportunity there, but anything we can do to provide more resources for education or self education, the better.

我们最后要讨论的一组人是‘主权者’。

The last group we'll talk about are the Sovereigns.

坦白说，这一群体可能是对自身能力滞后最清醒的一群人。

And honestly, this is the group that might be the most aware of their capabilities overhang of anyone.

在这种情况下，能力滞后是一个国家安全问题。

The overhang in this case is a national security issue.

可能性与实际部署之间的差距，代表着战略上的脆弱性。

The delta between what's possible and what's deployed represents strategic vulnerability.

这也代表了一个关于谁有权定义未来的挑战。

It also represents a challenge in terms of who gets to define the future.

不仅存在这种战略脆弱性，主权国家还面临着这样一个现实：每个人对世界的理解都由大型语言模型所中介，而这些模型依赖于特定的一组数据源，可能无法充分反映你们国家的复杂性与文化传承。

And not only is there this strategic vulnerability, but Sovereigns are also dealing with the fact of what it means to have everyone's understanding of the world mediated by LLMs that are reliant on a specific set of sources which may not take into account the full complexity and cultural legacy of your particular nation.

因此，对于主权国家而言，人工智能能力的滞后所带来的问题非常多。

So there is so much in the AI capabilities overhang for sovereigns.

当然，在中期内，人工智能能力的先发优势可能会造成一些极为持久的地缘政治不对称。

Certainly in the medium term, first mover advantages in AI capability could create some seriously durable geopolitical asymmetries.

正如我所说，我认为这一群体最清楚这一挑战，因此你看到许多国家将人工智能基础设施——包括算力、人才和数据——视为关键的国家资产。

Now like I said, this is the group that I think is most cognizant of this challenge, and it's why you see so many nations treating AI infrastructure in the form of compute, talent, and data as critical national assets.

这就是为什么你正目睹围绕这一领域发生大规模的地缘政治重组。

It's why you're seeing massive geopolitical realignment around this stuff.

未来几年，我们将非常期待看到这一趋势如何持续影响地缘政治对话。

And it's going to be fascinating to see how this continues to interact with the geopolitical conversation in the years to come.

好了，朋友们，这就是我们对人工智能能力滞后现象的快速概览——即当前人工智能所能实现的能力与社会在各种形态下实际利用这些能力之间的差距。

Anyways friends, that is our quick tour of the AI capabilities overhang, the gap between what AI can do right now and how society in all of its various manifestations is actually taking advantage of it.

我认为，在很多方面，我们都有动力去缩小我们所参与以及周围各类群体之间的能力差距。

I think we all, in many ways, have incentives to try to close the capabilities overhang among every type of group not only that we're participating in, but those around us.

希望将这个问题识别为一个挑战是一个良好的开端，这正是我在这里尝试做到的，也会在本节目中继续这样做。

Hopefully identifying it as a challenge is a good starting point and that's what I've tried to do here and will continue to do on this show.

不过目前，今天的AI每日简报就到这里。

For now though, that's going to do it for today's AI Daily Brief.

一如既往，感谢您的收听或观看，下次再见，保重。

Appreciate you listening or watching as always and until next time, peace