

Sanjeev Namjoshi ~ Active Inference Insights 018 ~ Education, Expectation-Maximisation, Evolution
5 snips Jun 17, 2024
Join Sanjeev Namjoshi, a textbook-writing, Bayesian-educating enthusiast, in a discussion covering the teaching of active inference, its relation to evolution, and learning mechanisms. Explore topics like unsupervised learning, Bayesian inference, survival strategies in a dynamic world, expectation maximization, simplifying mathematics for active inference, using Python, R, and MATLAB for simulations, the influence of priors in Bayesian modeling, mathematical concepts in active inference, phenotypic priors in AI, and cutting-edge topics on intelligence and gratitude.
Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10
Intro
00:00 • 3min
Exploration of Active Inference and its Relations
03:28 • 26min
Active Inference and Survival Techniques in a Complex World
29:05 • 15min
Exploring Expectation Maximization Algorithm and Maximum Likelihood Estimation
43:41 • 8min
Simplifying Mathematics in Active Inference
51:45 • 11min
Discussion on Using Python, R, and MATLAB for Active Inference Simulations
01:02:41 • 4min
Exploring the Influence of Priors in Bayesian Modeling
01:06:18 • 9min
Mathematical Concepts and Active Inference
01:15:34 • 25min
Exploring Phenotypic Priors and Active Inference in AI
01:41:00 • 21min
Cutting-edge Topics in Intelligence and Gratitude Towards Contributions
02:02:20 • 4min