Software engineer · Atlanta, Georgia

Building software and exploring intelligent systems.

Berlin Brown is a software engineer with more than 15 years of experience developing distributed and enterprise systems. His technical writing covers artificial intelligence, large language models, JVM technologies, cellular automata, computer graphics, and lessons from open-source experimentation.

Original computer-generated landscape artwork

Background

Engineering experience grounded in curiosity

Berlin’s interest in programming began at age ten in Austin, Texas, with a TRS-80 and BASIC. That early curiosity led to a degree in electrical engineering and computer science and a career building large-scale systems across financial services, insurance, public-sector engineering, and public-health data collection.

His work focuses on backend and distributed systems, alongside continued research into how AI, machine learning, simulation, graphics, and emerging models of intelligence can inform practical software.

Open-source work

Selected software projects

These projects are working laboratories: places to take systems apart, rebuild them, and share what the process reveals about software design, intelligence, emergence, and computation.

Vanus Play Framework

An experimental web server and application framework centered on durable web standards—HTTP, HTML, CSS, forms, and links—with a deliberately small frontend footprint.

Openbotlist / Umbra Social

An open-source discussion and link-sharing platform built with a traditional server-side architecture using Java, Spring MVC, JSP, JRuby, Hibernate, and MySQL.

Light Reports

A lightweight Clojure and Java toolkit for generating PDF, image, and SVG reports from structured documents and templates.

Umbra Cellular Automata Game

A Java framework for experimenting with cellular automata, simulations, visual systems, and game-development concepts.

Octane Mech OpenGL Game

A long-running 3D graphics project exploring modern C++, OpenGL rendering, camera systems, particles, game entities, and real-time networking.

Cellular Automata Examples

Code and demonstrations that make elementary cellular automata—including Rule 30—easier to study, modify, and apply.

Research notes

Cellular automata and emergent systems

Cellular automata show how simple local rules can produce complex behavior. Stephen Wolfram’s work, including A New Kind of Science, helped bring these systems to a wider audience and demonstrated their relevance across biology, physics, computation, and other fields.

In an elementary cellular automaton such as Rule 30, each cell’s next state is determined by its current neighborhood. There are eight possible three-cell inputs, each mapped to a binary output. Repeating that small rule across a grid can generate intricate, seemingly unpredictable patterns.

Researchers have applied cellular automata to cryptography, data compression, artificial intelligence, geographic modeling, urban planning, music generation, terrain generation, and financial-market simulations. Their value lies in a powerful idea: apparent complexity can emerge from a compact, reproducible set of rules.

Computer-generated Mandelbrot fractal visualization

Patterns, intelligence, and machine learning

Current research interests connect emergent computation with AI, local large language models, Numenta’s Hierarchical Temporal Memory, and the Thousand Brains theory of intelligence.

Explore the unofficial HTM.java project

Robotic sensor experiment identifying a cup

Embodied intelligence

Experiments inspired by Numenta’s Monty project investigate how intelligent systems can learn through movement, sensory input, and object-centered representations.

Learn about the Thousand Brains theory

Explore further

Writing, profiles, and resources