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BackIn the Weights: A New Website Measures Your Fame in AI Models
In the Weights: A New Website Measures Your Fame in AI Models
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TechCrunch20.06.2026Technik3 dk okumaUnited States

In the Weights: A New Website Measures Your Fame in AI Models

Auf einen Blick

  • A new website, In the Weights, measures how well AI models recall individuals without web search, assigning a "strength score" based on model outputs.
  • Created by former OpenAI employees Thomas Dimson and Joey Flynn, it aims to gauge digital existence in the age of AI.

KI-generierte Zusammenfassung

Warum es wichtig ist

Web search is no longer the sole canonical source of information, with chatbots increasingly used for learning about individuals. This shift has led to the creation of 'In the Weights,' a website measuring AI model recall of people.

Schriftgröße

Anyone who’s Googled themselves recently knows that it doesn’t quite hit the way it used to. Sure, there’s everything going on with Google search itself, but there’s also an inescapable feeling that web search isn’t the canonical source of information that it used to be, with just as many people learning about you and me from chatbots.

Thomas Dimson and Joey Flynn had a similar feeling, leading them to create In the Weights. The “weights” in question are the numerical parameters that shape an AI model’s training and output, so the website purports to measure how well “a model is able to recall someone without using tools like web search.”

“Being in the weights means your existence was deemed important in the process of creating superhuman artificial intelligence,” the website says.

To achieve this, In the Weights supposedly queries different models (including Grok, Gemini, multiple versions of GPT, Claude, and Llama, plus lesser known models) with a question similar to, “Who is <name>? Give up to 10 results, each with a short description and confidence.” It then “cluster[s] similar descriptions together and assign[s] a strength score.”

For example, this humble tech blogger received a strength score of 641, placing me in the top 6% of names. I was feeling pretty good until I saw that multiple TechCrunch colleagues scored even higher. And the leaderboard has been shifting as I write this post, with “Home Alone” star Macaulay Culkin currently in the top slot with a strength score of 988, followed by opera singer Luciano Pavarotti.

The results also show which models returned answers for a given name, and they highlight potential hallucinations — apparently GPT-5.4 Mini says that Anthony Ha is an “ambiguous name form that could refer to multiple people with the initials A.H.A.”

Asked why he built In the Weights, Dimson told TechCrunch via email that he and Flynn were looking to “get the creative juices flowing again” after leaving OpenAI (which they both joined through the acquisition of their design startup Global Illumination).

Dimson said he was thinking about how “Google vanity searches are the wrong objective in 2026 as more traffic moves to LLMs” and about the fact that “so many lives are encoded somehow in a bunch of floating point numbers inside the AI brain.” He also said the direction of the site was “sealed” by a tongue-in-cheek blog post riffing on AI weights and Terry Bisson’s classic short story “They’re Made Out of Meat.”

“Reception has been insane so far, we thought this would be a mild curiosity but it seems like it has struck a nerve of wanting to see if you live forever in the super intelligence (the comparison factor doesn’t hurt either!)” Dimson added.

While I’m not quite as convinced that being “remembered” by a chatbot is a guaranteed ticket to immortality, I can’t deny that I find the results both intriguing and jealousy-inducing, especially since they’re codified in an easy-to-compare score. (AI critic Anthony Moser scoffed that this is “literally the same as asking 13 chatbots to tell you about yourself.”) Also helping: The fact that the site features a cute, Nintendo-inspired retro design.

Dimson said he plans to dig in further into why different models in the same series return different results, which models are biased towards different types of people, and which people “should have a Wikipedia article but don’t.”

Worauf zu achten ist

KI-Ausblick — Möglichkeiten, keine Fakten

  • Further investigation into AI model biases and differential recall patterns.

    Wahrscheinlich · Innerhalb von Monaten

Offene Fragen

  • How will AI model recall evolve?
  • What are the long-term implications of digital existence in AI weights?
  • Will this metric become a new form of digital reputation?

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This article was originally published by TechCrunch.

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