Plectics Laboratories

Our Vision

In alignment with Murray Gell-Mann's vision for the term Plectics, and Norbert Wiener’s original vision for Cybernetics, Plectics Laboratories endeavors to advance a transdisciplinary understanding of complex systems. This approach, emphasizes the interconnectedness of fields and the application of shared mathematical tools across disciplines. We believe that fostering collaboration across these domains is critical to addressing the pressing challenges posed by contemporary complex systems, such as AI interpretability and social dynamics 

Our research stands at the intersection of statistical physics, deep learning, and high-dimensional statistics. We are particularly interested in how computation emerges in complex systems through the collective dynamics of simple processing units. We investigate this principle across multiple domains—from the latent geometry of neural representations to the large-scale patterns of social dynamics. By modeling these underlying dynamics, our goal is to build more interpretable and robust frameworks for understanding how local interactions give rise to the complex, emergent structures that shape our world. Through our open-source knowledge base and public events, we work to enable researchers to bridge theoretical insights with practical applications and build a community dedicated to solving these problems.

Our Approach

We believe, complexity science struggled due to technological limitations: detailed measurements and computationally intensive simulations were simply beyond reach. By the late 20th century, complexity-focused companies and researchers were forced to pause their efforts as computing resources failed to match theoretical ambitions. Today, consumer-grade hardware routinely surpasses the performance of earlier supercomputers, and vast streams of data have become abundant. Leveraging this computational revolution, Plectics Labs aims to reconcile two divergent scientific traditions: the predictive power of data-driven machine learning and the explanatory rigor of mechanistic modeling. Our goal is to transcend traditional minimalistic approaches, illuminating instead the generative processes, historical, adaptive, and evolutionary, that shape the intricate structures and behaviors of the complex world around us.

Our Values

Plectics Laboratories remains committed to cultivating an open-source knowledge base, enabling researchers to bridge theoretical insights with practical applications across diverse domains. By facilitating interdisciplinary collaboration, we strive to unlock deeper understanding and innovative solutions in complexity science.

• Interdisciplinarity: We believe that the most significant breakthroughs occur at the intersections of different fields. We actively foster collaboration and dialogue between researchers from diverse backgrounds to create a whole greater than the sum of its parts.

• Rigorous Inquiry: We are committed to the highest standards of intellectual honesty and analytical depth. Our work is driven by curiosity and a relentless pursuit of the truth, grounded in mathematical and logical reasoning.

• Historicism: To build the future, one must understand the past. We emphasize the importance of historical thinking to provide deeper context for modern problems and to learn from the evolution of scientific ideas.

• Open source knowledge: We are dedicated to making our research, lectures, and resources publicly available to a global audience. We believe that sharing knowledge is essential for accelerating scientific progress and contributing to a wider public conversation.