CONTEXT ENTRY POINTS

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CONTEXT ENTRY POINTS

See the picture. Build for the context.

Created by John Dawson and Michael Goldstein. Powered by Share of Model^TM.

Google Gemini OpenAI

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Scene Description

Context

Brand Presence

Detection Details

This is an experimental tool designed to illustrate the concept of Context Entry Points — exploring how AI image generation models respond to contextual cues and how brands surface across different consumer scenarios. By prompting these models with structured combinations of context, audience, and setting — without specifying any brand names — we elicit the innate associations and perceptions embedded within the large language models that power image generation. The brands that appear are not placed deliberately; they reflect what the model has learned to associate with a given scene.

This builds on the principle behind Share of Model^TM (shareofmodel.ai) — that every brand occupies a distinct position within the knowledge and reasoning of large language models. Share of Model^TM measures how and when your brand appears in AI-generated responses across platforms like ChatGPT, Gemini, and Perplexity. Context Entry Points extends that lens to visual AI, revealing the specific consumer moments and scenarios where your brand is — or isn't — part of the model's default picture.

All images are AI-generated and all brand identifications are performed by large language models. We make no representations as to the accuracy of these outputs, the completeness of brand representation, or the manner in which any brand, person, or scenario is depicted.