Brains, Minds and Mechanisms

There are multiple ways to approach Artificial Intelligence in relation to human or "natural" intelligence. At the center, the core aspect of behaviour characterizes the level of efficiency and adaptiveness to the environment, or how "intelligent" this behaviour looks like, regardless if it refers to human, animal or machine.

In this lecture, "intelligence" is investigated via two main pathways: Cellular Automata (CA), which often relate to the Theory of Computation, algorithmic complexity, computability, etc; and Signal Processing (SP), which can describe a very wide range of systems design, from simple digital filters and data transformation to non-linear automatic control and data-driven Machine Learning algorithms. Additionally, the notion of "memory" is investigated as a design specification and a tradeoff between "smart" behaviour / low adaptiveness versus "dumb" behaviour / quick adaptiveness.

Keywords: Machine Learning, Data Analytics, AI, Artificial Intelligence, lecture
Video: https://youtu.be/hY16_IFHbnw