Brief Intro
Welcome to my personal page. I work at the intersection of systems design, artificial intelligence, and time-based theoretical frameworks. My focus is on understanding how people, processes, and technologies evolve over time — and how those patterns can be shaped, improved, or understood more clearly.
This site offers a simple overview of where my current work lives, along with links to the organizations and research spaces I maintain.
What I Do
I build frameworks — technical, behavioral, and conceptual — that explore:
- How intelligent systems learn through behavior and feedback
- How long-term memory and process understanding shape AI
- How temporal structures influence physical and conceptual systems
Much of this work spans both applied AI and research. I keep the two worlds intentionally separate:
- Temvorn handles applied AI and behavioral learning systems
- Temporal Sciences Foundation supports theoretical work
This page is simply the personal hub tying it together.
Current Focus Areas
Temvorn (Applied AI)
I lead the development of frameworks that help AI systems understand process, behavior, and change over time. The goal is to move AI beyond static outputs toward adaptive, transparent learning systems.
- Visit Temvorn
Temporal Sciences Foundation
I founded the Temporal Sciences Foundation to support work exploring time as a structural principle of the universe. All work is shared openly as speculative non-peer-reviewed documents to encourage examination, refinement, and critique.
- Visit Temporal Sciences Foundation
- Visit Temporal Sciences Wiki
Documents & Open Access
All Temporal Sciences work is openly available through Zenodo in “document” form and are not represented as “publications” in recognition of the rigor required for formal peer review.
Generative AI “Start Here” Website
- Visit ColinLynch.ai
A simple starting point for people who haven’t yet begun working with generative AI.
A Few Guiding Principles
- Clarity over complexity
- Process over outcomes
- Behavior precedes learning
- Respect for peer review
- Humility in uncertain domains
These principles guide both my applied AI work and my speculative research.