I found this speech by Gregory Chaitin on the paradox of randomness particularly insightful regarding complexity theory. It examines how algorithmic information theory defines randomness and the inherent limitations of logical systems.
Image models can generate original physically impossible scenes, and evaluating those outputs surfaces what makes paradoxical images feel clever rather than merely strange.
I explore the convergence of complexity theory and quantum mechanics within the field of quantum information science, highlighting how these disciplines integrate to redefine our understanding of computational limits and fundamental physical systems.
I curated a collection of resources exploring complexity science and networked systems. The links cover the twelve principles of the networked world, the nature of complex adaptive systems, and speculative 'what if' scenarios in artificial intelligence.
I found that Microsoft's IT department successfully applied the Theory of Constraints to software development. This approach focuses on identifying and managing system bottlenecks to optimize overall project flow and engineering throughput.
I found an interesting NECSI article applying complex systems theory to basketball. It explores how the sport functions as a multi-scale system, looking beyond individual stats to understand collective patterns and emergent team behavior.