Vectors of Cognitive AI: Self-Organization
Panelists: Prof. Christoph von der Malsburg, Prof. György Buzsáki, Prof. Dave Ackley, Dr. Joscha Bach.
Biological and social agents are very different from our present approaches to technologically designed artificial agents. Technological systems are constructed “from outside in”: they extend a world with known, reliable functionality by forging a deterministic substrate into additional, required functions. This is true whether we are building a bicycle in a workshop or a learning algorithm in a software development environment. In contrast, biological systems (such as plants, or the mind of a human being) are growing “from inside out”: they organize an indeterministic substrate with unreliable properties into a structure that converges to serving the required function, and which will even self-heal and regrow when they are being damaged or disturbed. What can technological systems (and especially AI) learn from the self-organization of biology? What basic principles drive self-organization, and how do they lead to efficient, robust and adaptive implementations of intelligent information processing? How can we formally describe self-organizing systems in a computational context?In this panel, we discuss perspectives on self-organization in the context of AI, neuroscience and general computation.
Full program: https://cognitive-ai-panel.webflow.io/panels/self-organization
Chat log: https://drive.google.com/file/d/1GSOsqT41KTUVfa4R0jZF6QV0sR05f411/view?usp=sharing
Panelists: Prof. Christoph von der Malsburg, Prof. György Buzsáki, Prof. Dave Ackley, Dr. Joscha Bach.
Biological and social agents are very different from our present approaches to technologically designed artificial agents. Technological systems are constructed “from outside in”: they extend a world with known, reliable functionality by forging a deterministic substrate into additional, required functions. This is true whether we are building a bicycle in a workshop or a learning algorithm in a software development environment. In contrast, biological systems (such as plants, or the mind of a human being) are growing “from inside out”: they organize an indeterministic substrate with unreliable properties into a structure that converges to serving the required function, and which will even self-heal and regrow when they are being damaged or disturbed. What can technological systems (and especially AI) learn from the self-organization of biology? What basic principles drive self-organization, and how do they lead to efficient, robust and adaptive implementations of intelligent information processing? How can we formally describe self-organizing systems in a computational context?In this panel, we discuss perspectives on self-organization in the context of AI, neuroscience and general computation.
Full program: https://cognitive-ai-panel.webflow.io/panels/self-organization
Chat log: https://drive.google.com/file/d/1GSOsqT41KTUVfa4R0jZF6QV0sR05f411/view?usp=sharing
