Explore the intricacies of machine learning in this comprehensive 2-hour 23-minute video featuring Stephen Wolfram reading and discussing his recent blog post. Delve into topics such as the mystery of machine learning, traditional neural nets, mesh neural nets, discrete rule arrays, multiway mutation graphs, and the optimization of learning processes. Gain insights into what can be learned through machine learning, examine various models and setups, and contemplate the fundamental nature of machine learning. Benefit from historical and personal notes shared by Wolfram, followed by an engaging Q&A session. Follow along with the provided blog post link for a deeper understanding of the concepts discussed.
What's Really Going On in Machine Learning? Some Minimal Models - Stephen Wolfram Reading
Overview
Syllabus
Start stream
SW starts talking
The Mystery of Machine Learning
Traditional Neural Nets
Simplifying the Topology: Mesh Neural Nets
Making Everything Discrete: A Biological Evolution Analog
Machine Learning in Discrete Rule Arrays
Multiway Mutation Graphs
Optimizing the Learning Process
What Can Be Learned?
Other Kinds of Models and Setups
So in the End, What's Really Going On in Machine Learning?
Historical & Personal Notes
Q&A
End stream
Taught by
Wolfram
