About the Project
Mapping automation's future and the people behind it
Our Vision
This project is being developed in QLab at Queen's University Belfast under the supervision of Dr. John Bustard.
The Universal Automation Wiki is focused on mapping the future of automation across diverse domains. Through this project we aim to track automation progress through a wide variety of topics, creating a comprehensive resource that monitors the advancement toward fully automated systems.
By systematically documenting what's currently possible and tracking emerging technologies, we provide a clear picture of automation's trajectory and help identify where future breakthroughs are likely to occur.
About the Developer
Jamie Matthews
I'm a student studying Software Engineering at Queen's University Belfast in the UK. I enjoy creating systems that make complex technologies more accessible and useful for everyday applications.
Currently, I'm primarily working on developing the Universal Automation Wiki and the underlying Iterative AI technology that powers it. My previous work includes the Simple Encryption Program, which explored making encryption more accessible for everyday users, without the need for an understanding of how the system works.
I'm interested in the potential of automation to transform our world and democratize access to advanced technologies. Through this project, I hope to create a platform that helps everyone understand and participate in the advancement of automation.
Iterative AI Approach
At the heart of our methodology is what we call "Iterative AI" - a bottom-up approach to data retrieval and analysis. This system is built on a library of specialized Python programs, with each designed to perform a very specific function in the automation mapping process.
The iterative approach allows us to:
- Break down complex tasks into manageable components
- Build upon existing automation capabilities
- Create detailed mappings of automation potential
- Generate predictions about future automation milestones
Community-Driven Development
Expert Collaboration
Our platform takes open source development to the next level by enabling experts from various fields to contribute their specialized knowledge and insights.
Direct User Input
Users can submit their opinions directly through the platform on how to improve both the software and the automation trees, creating a feedback loop that continuously refines our data.
Automation Timeline
The platform will eventually provide insights on when full automation is likely to be achievable for specific tasks, helping organizations plan their technology roadmaps.
Join Our Mission
Help us map the future of automation by contributing your expertise and insights. Whether you're an expert in a specific field or simply interested in automation's potential, your perspective is valuable to our project.