Introducing the Universal State Machine

Welcome to the first-ever public demonstration of the Universal State Machine (USM) — a revolutionary approach to artificial intelligence that redefines how machines learn from experience.

What is the USM?

The Universal State Machine is a groundbreaking new AI architecture, designed from the ground up for intelligence. Unlike traditional deep learning, USM dynamically adapts to new information, growing as it learns—just like the human brain. This approach offers efficiency, scalability, and interpretability far beyond conventional AI models.

Inside the Demo:

In this video, Rukmal, co-founder and CEO of Ren, walks through the core principles behind USM and showcases a live prototype in action. You’ll see how USM:

  • Learns dynamically from new experiences
  • Adapts its structure in real time
  • Operates efficiently on standard CPU hardware—without the need for expensive GPUs
  • Outperforms deep learning models in key aspects of scalability and efficiency

Why This Matters:

Deep learning has revolutionized AI, but it comes at immense computational cost. The Universal State Machine presents an entirely new paradigm—one that could redefine AI development in the years to come.

Want to Learn More?

📄 Read the USM whitepaper: https://opensource.getren.xyz/ittm/

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Background expertise

Maxwell Braun graduated with a BA in Political Economy from the Jackson School of International Studies at the University of Washington. He then began his career in Financial Services with UBS, acting as a technology liaison and helping drive AML efforts. While at UBS, he obtained his FINRA Series 7 and Series 66 licenses. Max then went on to become a Senior Financial Analyst at BNY Mellon in Seattle, where he refined KYC compliance protocols and become West Coast Associate of the Year in 2022. Max grew up in Piedmont, CA.

Background expertise

Rukmal Weerawarana graduated with a BBA in Finance and Business Economics from the Foster School of Business at the University of Washington.

In College, he contributed to various research projects, including targeted drug design for HIV patients, a CubeSat that is currently in orbit, and one of the world’s first functioning Hyperloop Systems.

As a Graduate Student at the Stevens Institute of Technology and a Research Fellow at Rensselaer Polytechnic Institute, he worked on ranking in knowledge graphs, and designing algorithms for processing sensorimotor data for BCI-driven robotic prosthetics.

After graduating with an MS in Financial Engineering from Stevens, Rukmal became a Software Engineer at ExtraHop Networks in Seattle. There, he worked with Big Data systems to develop cybersecurity algorithms and machine learning cloud infrastructure. He then contributed to kickstarting a (non-profit) technology-enabled school in Sri Lanka and was the Lead Data Scientist at Capitol AI in New York City in early 2023.

Rukmal is from Colombo, Sri Lanka.