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Tech
Jun 21, 2026
Analyzed by Glm 4.7 Flash

The New AI Vanity Search: Measuring Your Digital Immortality

AI Summary
A new tool called 'In the Weights' ranks how well AI models remember specific names, sparking curiosity about digital legacy and training data.

The Shift from Web Search to AI Memory

As the reliance on traditional web search declines in favor of Large Language Models (LLMs), a new metric for personal recognition has emerged. 'In the Weights,' a newly launched website, attempts to answer a modern question: if a superhuman AI were to recall your existence, how well would it do? This tool offers a unique lens into how our lives are being encoded into the numerical parameters of artificial intelligence.

How 'In the Weights' Quantifies AI Recognition

The core innovation of this platform is its method of measuring 'recall' within AI models. Instead of relying on external web links, the tool queries various AI models—including Grok, Gemini, GPT, Claude, and Llama—with a prompt asking, 'Who is [Name]?' The system then clusters similar descriptions and assigns a 'strength score' based on the model's ability to retrieve information from its internal weights.

  • Methodology: Queries multiple models for a single name.
  • Scoring: Assigns a strength score based on recall accuracy.
  • Transparency: Highlights hallucinations and model-specific biases.

Ranking Digital Legacy: The Current Leaderboard

The results have created a fascinating, albeit competitive, leaderboard. The site currently ranks individuals based on how prominently they appear in AI training data. Macaulay Culkin currently holds the top spot with a strength score of 988, closely followed by the legendary Luciano Pavarotti. Interestingly, the tool reveals that even niche tech figures are scoring highly; for instance, the author of this article received a score of 641, placing them in the top 6% of names tracked.

Why We Are Obsessed with AI Immortality

Co-founders Thomas Dimson and Joey Flynn, both former OpenAI employees, designed the site to explore the philosophical implications of AI training. Dimson noted that the concept was born from the idea that 'so many lives are encoded somehow in a bunch of floating point numbers inside the AI brain.' The reception has been overwhelming, suggesting a collective desire to see if we 'live forever' in the superintelligence era.

Decoding Bias and the Future of Digital Footprints

Looking ahead, Dimson plans to dig deeper into the mechanics of these scores. Future updates will focus on analyzing why different models return different results, identifying biases toward specific demographics, and determining which people 'should have a Wikipedia article but don't.' This tool may soon become the definitive source for understanding how our digital footprints are being preserved—or distorted—in the age of generative AI.