In The Weights Service Measures Thomas Dimson and Joey Flynn’s Presence in AI Weights
Image: Zamin.uz

In The Weights Service Measures Thomas Dimson and Joey Flynn’s Presence in AI Weights

20 June, 2026.Technology and Science.4 sources

The story in 15 seconds

  • Vanity search reveals users' online presence and AI training data footprint.
  • Founded by Thomas Dimson and Joey Flynn.
  • Shows extent of presence in AI training data and model memory.

The divide · 1 of 3

What the service measures: AI “weights” vs broader “AI footprint” framing.

One stresses model-weights recall; another stresses training-data “footprint” transparency.

Who skipped what

How each outlet frames it

Every outlet we compared, the headline it ran, and a link to the original article.

Source Diversity
4 sources
Local Western
1
Western Mainstream
1
Western Alternative
1
Other
1

Local Western

mezha.net
mezha.net

In the Weights lets you control your online reputation with AI

20 June, 2026

Read the original →

Western Mainstream

TechCrunch
TechCrunch

In the Weights is your new AI-centric vanity search

20 June, 2026

Read the original →

Western Alternative

The Tech Buzz
The Tech Buzz

In the Weights Lets You Check Your AI Training Data Footprint

20 June, 2026

Read the original →

Other

Zamin.uz
Zamin.uz

In the Weights: A New Service to Check Your Presence in AI Memory

20 June, 2026

Read the original →

Full story

A new AI vanity search

A new service called In the Weights, created by Thomas Dimson and Joey Flynn, is designed to measure how deeply a person is embedded in the internal parameters of Large Language Models, or their "weights."

An AI-driven vanity search uncovers how you appear online and offers tools to suppress unwanted results while promoting the profile you prefer

mezha.netmezha.net

TechCrunch says the platform queries dozens of popular models—including Grok, Gemini, multiple versions of GPT, Claude, and Llama—with the question "Who is this person?"

Image from mezha.net
mezha.netmezha.net

The site then analyzes the received answers, groups similar descriptions, and provides a final "strength score," with TechCrunch describing Macaulay Culkin and Luciano Pavarotti as occupying the highest ranks.

In a statement on the project’s premise, the In the Weights website says, "Being in the weights means your existence was deemed important in the process of creating superhuman artificial intelligence," tying the service to the idea that AI “memory” could confer a kind of digital permanence.

Scores, models, and skepticism

TechCrunch reports that its own testing produced a strength score of 641, placing the blogger in the top 6% of names, while Macaulay Culkin was described as currently in the top slot with a strength score of 988.

The same TechCrunch account says the leaderboard is shifting as it is written, with Luciano Pavarotti described as "neck-and-neck" with Culkin.

Image from TechCrunch
TechCrunchTechCrunch

In the TechCrunch piece, Dimson told the outlet via email that he and Flynn were looking to "get the creative juices flowing again" after leaving OpenAI.

AI critic Anthony Moser is quoted in TechCrunch saying the concept is "literally the same as asking 13 chatbots to tell you about yourself," and the article also notes that the results can highlight potential hallucinations.

From curiosity to control

Beyond scoring, the platform is also described as offering tools to manage a user’s online reputation with AI, including removing outdated information or reducing its visibility while elevating relevant content.

A new vanity search tool called In the Weights is giving people an unprecedented look at their digital footprint in AI training data

The Tech BuzzThe Tech Buzz

mezha.net says the service scans sources "from profiles to posts and mentions" and uses artificial intelligence to form a consolidated profile that users can monitor through a dashboard.

The Tech Buzz frames In the Weights as "essentially Google for AI weights," positioning it as a consumer-facing window into how extensively people appear in the datasets powering large language models.

TechCrunch adds that Dimson plans to dig in further into why different models in the same series return different results, which models are biased toward different types of people, and which people "should have a Wikipedia article but don’t."

The deep audit

How victims, perpetrators and terms are handled across outlets.

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