Artificially Intelligent Messaging
Summary
AIME (Artificially Intelligent Messaging Engine) is an AI system that profiles a target in real time, draws from a core content library, and generates unique, conversational message fragments. It delivers them across any medium or platform and keeps iterating — testing understanding and refining — until 100% knowledge acquisition is confirmed.
I began developing the concept while at AT&T in 2017 and submitted the patent outline to AT&T Intellectual Property in July of 2018. Upon acceptance from IP a law firm was assigned to the project with whom I worked to create the patent application. Two years later the patent was accepted by the USPTO.
The Origin Story
The idea for AIME started with a very human problem: how to create high-quality audio descriptions so blind people could fully enjoy video content. While at AT&T, I was building a business case to position the company as a leader in accessibility for people with disabilities.
The deeper I went, the clearer the real challenge became — there are a million different ways to describe visual content on screen, especially artistic or entertainment material that’s inherently subjective. Any single “average” description would always fall short for someone.
One day while out on a jog, the full concept downloaded in a flash. I realized information behaves like energy in E=mc² — it can be freely converted between any medium (video, text, audio, billboards, AR, etc.) without loss. The core insight: “It’s not what you say, it’s how you say it.”
There is an archetype (the pure idea or core message) on a higher plane. We can prototype it in infinite ways, and one prototype will always resonate better with a specific person than another. Instead of forcing one average prototype to serve everyone, why not create a unique prototype optimized exactly for each individual?
That spark became the Artificially Intelligent Message Engine (AIME) — a computer program and content delivery system that tautologically iterates prototype messages, constantly testing understanding and refining the delivery until the archetype is fully understood and “knowledge acquisition” occurs.