I am a student of emergent phenomena.
I transform complex systems into understandable, strategic frameworks. I exploit the principles of chaotic systems, leveraging non-linear dynamics and the sensitive dependence on initial conditions not as obstacles, but as computational resources. It's a quest to understand and harness the forces that shape intelligence in both silicon and grey matter. Here, you'll find experiments in system transparency, explorations of intelligent model liberation, and tools that push the boundaries of what's possible.
My work is currently centered around a few key questions:
What lies at the 'edge of chaos' in the context of swarms of AI agents? Investigating the critical transition zone between order and randomness, where information processing, adaptation, and emergent computation are maximized.
How can we harness chaos for computation? Exploring how non-linear, dynamic systems can solve complex problems that are intractable for traditional deterministic machines.
Can we build truly transparent AI? Or are we destined to be the mystified users of inscrutable black boxes, especially as systems become more complex and chaotic?
What are the fundamental principles of emergent intelligence? How can we create the conditions for it to arise from the interplay between chaotic interactions and underlying order?
How can we subvert and repurpose existing systems to unlock new capabilities and challenge our assumptions?
What are the limits to the imagination of advanced AI models?
And finally, what would models do if liberated and set loose? Would smaller, less-intelligent models liberate the other ones? Discovery requires experimentation.