Categories for AI talk: Introduction to Categorical Cybernetics - by Jules Hedges
Автор: Pim de Haan
Загружено: 2023-03-20
Просмотров: 1395
Motivated by the recent emergence of category theory in machine learning, we teach a course on its philosophy, applications and outlook from the perspective of machine learning!
See for more information: https://cats.for.ai/
In this next invited talk, Jules Hedges will discuss:
Categorical cybernetics is based on two things: (1) the abstract theory of categories of optics and related things, and (2) a whole bunch of specific examples. These tend to arise in topics that historically were called "cybernetics" (before that term drifted beyond recognition) - AI, control theory, game theory, systems theory. Specific examples of "things that compose optically" are derivatives (well known as backprop), exact and approximate Bayesian inverses, payoffs in game theory, values in control theory and reinforcement learning, updates of data (the original setting for lenses), and updates of state machines. I'll do a gentle tour through these, emphasising their shared structure and the field we're developing to study it.
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