Themesis Academy

Week 2: "T3 Week 2 Video Transcripts - Days 8 - 14" (DWNLD - for Claude)

Week 2: "T3 Week 2 - Consolidated PDFS" (DWNLD for Claude)

Week 2: "T3 Week 2 Exercises" (DWNLD for Claude)

Day 8: Microstates (VID)

Day 8: Statistical Mechanics is a Metaphor, Not a Model (YouTube Link)

Day 8: Statistical Mechanics (PDF)

Day 8: Microstates (PDF)

Day 8: Microstates Reading Assignment - SMNNAI (book) Chapter 10:"Introduction to Statistical Mechanics: Microstates and the Partition Function"

Day 8: Exercise - Microstates (EXERCISE)

Day 9: Stat Mech Overview ( Connection to Generative AI) (VID)

Day 9: Entropy from a Statistical Mechanics Perspective (Vid)

Day 9: Entropy from a Statistical Mechanics Perspective (PDF)

Day 9: Entropy - Explained in Terms of Probabilities and Surprise (YouTube Link)

Day 9: Entropy - Jason Brownlee's Explanation

Day 9: Entropy (Two YouTube Links)

Day 9: Exercise - Entropy (Stat Mech Perspective) (EXERCISE)

Day 10: The Partition Function - Introduction (Video)

Day 10: The Partition Function - Full Tutorial (Video)

Day 10: The Partition Function (PDF)

Day 10: Exercise - Partition Function (EXERCISE)

Day 11: The Ising Model - Simple Experiments (Video)

Day 11: The Ising Equation (YouTube #Short Link - "The Ising Equation Lets You Understand All Energy-Based Neural Networks")

Day 11: Free Energy and the Ising Equation (PDF)

Day 11: Free Energy and the Ising Equation Reading Assignment - SMNNAI (book) Chapter 11: "Free Energy"

Day 11: Excel Spreadsheet (Download Link)

Day 11: Exercise - Free Energy (EXERCISE)

Day 12: Equilibrium (PDF)

Day 12: Exercise - Equilibrium (EXERCISE)

Week 2: Day 13 - Integration (EXERCISE)

Day 14: Meditating on an Equation (Video)

Day 14: Sunday Meditation on Paperwork and Entropy (Exercise)

Day 15: The REVERSE Kullback-Leibler Divergence and Generative AI (Video)

Day 15: The K-L Divergence: Resources (Blogpost Links)

Day 15: The Reverse KL Divergence (PDF, Substantive Read)

Day 16: Bayesian Probability and Stat Mech: Confluence of Two Worlds (Video)

Day 16: Generative AI and Bayesian Probabilities (YouTube Link)

Day 16: The Most Important Blogpost You Can Read on Probabilities

Day 16: Bayesian Probabilities: Resources (Precis PDF and Wiki Links)

Day 17: Generative AI Moves in Three Directions (Video)

Day 17: Energy-Based NN Historical Intro (YouTube #short - "How to Identify the First Energy-Based Neural Network")

Day 17: "The Boltzmann Machine" (YouTube #short Link)

Day 17: Supplemental Resource (YouTube Link: "A New Neural Network Class: Creating the Framework" on Energy-Based Neural Networks)

Day 17: Reading Assignment (Re-Read): "The Hopfield Neural Network and the (Restricted) Boltzmann Machine" - Chapter 9 (from SMNNAI)

Day 17.5: Kingma and Welling on Variational Autoencoders (PDF Link)

Day 17.5: Auto-Encoders - Yet Another form of Generative AI

Day 18: Derivation of Variational Bayes Equations (A 70-Page Tutorial Paper - PDF)

Day 18: Variational Inference - My Personal Blooper Reel (Blogpost Link)

Day 19: Active Inference (YouTube Link: Friston's Use of "Psi")

Day 19: Active Inference and Renormalising Generative Models: Why They Are Important

Day 20: Generative AI and AGI (Artificial General Intelligence) (YouTube Link)

Day Final: Book "Statistical Mechanics, Neural Networks, and AI": Precis and Selected Chapters (LINKS)

Day 4: Enthalpy Exercise (Reflection and Play) (Supplemental)