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Exploring mathematical accounting systems for collective intelligence, focusing on sense-making as a key component in understanding and articulating the phenomenon of intelligence.
Explore how institutions and innovation shape collective intelligence, examining scientific attention, discovery limitations, and strategies for fostering creativity in research and knowledge production.
Explore mathematical approaches to studying diverse intelligences across fields, discussing strategies for non-mathematicians to adopt these methods and potential funding opportunities for future research.
Explore learning and communication dynamics using anecdotal evidence, examining strategic behaviors, biases, and implications for opinion formation and collective intelligence.
Explores mesoscale structures in many-body systems, explaining the autonomy of continuum equations and their connection to lower-scale physics, with implications for deep neural networks.
Explore bioelectric embryos and synthetic organisms, delving into morphogenetic control, AI-driven tissue reconfiguration, and collective behaviors challenging traditional biological distinctions.
Survey of recent developments in collective intelligence for deep learning, exploring self-organization, emergent behavior, and cellular systems to address robustness and adaptability issues in neural networks.
Explore physical computation in insect swarms, focusing on firefly visual signals and bee pheromone communication. Discover how swarm intelligence emerges from individual interactions.
Explore multi-agent common sense through mathematical frameworks combining Bayesian learning and game theory. Discover insights into human collaboration, joint intentions, and cultural knowledge acquisition.
Explore the mathematics of connection through category theory, focusing on open systems, their interfaces, and composition. Learn how this approach applies to various fields and collective intelligence.
Explore learning via conjectural variations, including challenges, equilibrium concepts, experiments, and applications in collective intelligence mathematics.
Explore collective intelligence as computation, examining principles of information processing, dimension reduction, and emergent phenomena in biological and social systems.
Explore geometric measures of manifolds and their applications to symplectic embeddings. Discover area estimates for minimal submanifolds and quantitative symplectic camels in this advanced mathematics talk.
Explore large deviations for triangle densities in graphs, including Borell's inequality, Gaussian noise stability, and applications to quantum ground states approximation.
Explore new inequalities for 2-zonoid volumes, potential extensions to p-zonoids, and related determinant inequalities. Delve into Minkowski sums, projections, and support functions in this advanced mathematics lecture.
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