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Website 'In the Weights' shows whether AI models know who you are 网站'权重之中'显示AI模型是否认识你

Two former OpenAI employees have built something that should make every AI company and user deeply uncomfortable. Their new website, "In the Weights," isn't just a quirky tool; it's a brutal, quantitative mirror held up to our collective cultural memory. It ranks people by their "recall strength" within AI models—a score of up to 996 that measures how deeply a human being is seared into the statistical psyche of these systems. And the results are a damning indictment of what we, as a society, ha 两位前OpenAI员工创建了一个产品,该产品应让所有AI公司和用户深感不安。他们的新网站《在权重中》不仅是一款新奇工具;更是一面直指我们集体文化记忆的残酷量化之镜。该网站根据人物在AI模型中的"回忆强度"进行排名——这项最高分为996的评分,衡量着人类个体在这些系统统计心智中的烙印深度。其结果构成了对我们社会选择将何种存在镌刻于硅基载体之上的深刻控诉。

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Two former OpenAI employees have built something that should make every AI company and user deeply uncomfortable. Their new website, "In the Weights," isn't just a quirky tool; it's a brutal, quantitative mirror held up to our collective cultural memory. It ranks people by their "recall strength" within AI models—a score of up to 996 that measures how deeply a human being is seared into the statistical psyche of these systems. And the results are a damning indictment of what we, as a society, have chosen to immortalize in silicon.

The top of the list is predictable yet telling: Mozart, Shakespeare, Taylor Swift. This isn't a meritocracy of genius; it's a census of data abundance. It confirms that AI models are, first and foremost, cultural hoarders. They remember what we have obsessively documented, digitized, and replicated. Swift's dominance isn't a commentary on her musical supremacy over, say, Beethoven, but on the sheer, relentless volume of her contemporary digital footprint—lyrics, articles, social media, interviews, analyses of her lyrics. The "weights" aren't measuring importance, but data saturation.

This project strips away the last vestiges of the "neutral oracle" myth. There is no neutral training corpus. It’s a funhouse mirror reflecting our biases, our celebrity obsessions, and our historical amnesia. The scores will be wildly skewed towards English-language public figures, Western artists, and contemporary celebrities. A brilliant, historically significant poet from a non-digital, non-Western tradition might score a pathetic 15, while a viral TikTok dancer scores a 400. The AI doesn't know people; it contains shadows of people proportional to the noise they generated.

The real, unsettling value here isn't the leaderboard, but the search function. What happens when you type in your own name, or the name of a living relative, and get a score? A zero is an affirmation of private normalcy. A high score, however, could become a new, bizarre form of social capital or stigma—a "digital immortality quotient" you never asked for. We’re entering an era where your public profile isn't just what Google shows, but what an LLM probabilistically "thinks" of you based on the fragmented, often decontextualized data slurry it consumed.

This tool is a public service precisely because it's a little dangerous. It forces a conversation AI labs have avoided. They talk about alignment and safety in abstract terms, but here’s a concrete metric for the cultural alignment problem: are these models simply becoming high-tech mausoleums for the already-famous, further entrenching their dominance? Does having a high "weight" score grant a person a form of unassailable, probabilistic authority within AI-generated discourse?

I suspect this site will be labeled "niche" or a "gimmick" by the industry. That's a mistake. "In the Weights" is a vital piece of infrastructure for the new world we're building. It’s a crowdsourced audit of the unconscious biases etched into our most powerful systems. The founders have done something clever and important: they’ve taken the opaque, corporate concept of "training data influence" and given it a face, a name, and a score. It’s no longer just a technical challenge; it’s a profoundly human one, staring back at us with cold, numerical clarity. The most important question it asks isn't "Does the AI know who you are?" but "Why does it know what it knows?" The answers will be uncomfortable.

两位前OpenAI员工创建了一个产品,该产品应让所有AI公司和用户深感不安。他们的新网站《在权重中》不仅是一款新奇工具;更是一面直指我们集体文化记忆的残酷量化之镜。该网站根据人物在AI模型中的"回忆强度"进行排名——这项最高分为996的评分,衡量着人类个体在这些系统统计心智中的烙印深度。其结果构成了对我们社会选择将何种存在镌刻于硅基载体之上的深刻控诉。

两位前OpenAI员工构建的作品足以令所有AI企业与用户坐立难安。他们的新网站《在权重中》绝非简单的猎奇工具;它是一面以残酷量化方式映照集体文化记忆的镜子,依据人物在AI模型中的"回忆强度"进行排序——这一体系通过最高996的分值,衡量人类个体在系统统计心智中的烙印深度。其结果如同一纸判决书,揭露了我们整个社会选择在硅基载体中铭刻的文明样态。

榜单顶端的名单既在意料之中又意味深长:莫扎特、莎士比亚、泰勒·斯威夫特。这并非天才的精英俱乐部,而是数据丰度的普查报告。它证实了AI模型本质上是文化的囤积者——它们记忆着我们曾执迷记录、数字化复制的一切。斯威夫特的领先并非对其音乐造诣超越贝多芬的评判,而是对其在数字时代无处不在的痕迹的客观反映:歌词文本、媒体报道、社交动态、访谈录、作品解析。所谓"权重"计量的并非思想价值,而是数据饱和度。

这个项目剥去了"中性智者"神话的最后一层面纱。从来不存在中立的训练语料库,它如同游乐园的哈哈镜,映照着我们的偏见、名人迷恋与历史失忆症。评分必然严重倾斜于英语世界的公众人物、西方艺术家与当代明星。一位来自非数字化非西方传统的卓越历史诗人可能仅获可怜的15分,而某个抖音爆款舞蹈博主却能斩获400分。AI并不"认知"人类,它仅"容纳"与个体制造的声量成正比的虚影。

真正令人不安的并非排行榜本身,而是搜索功能。当你输入自己或在世亲友的姓名并看到那个分数时会发生什么?零分意味着私人生活的完整幸存...

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LLM 大模型 Evaluation 评测 Ethics 伦理