AI — Models & Research

Stanford CS329A Self-Improving AI Agents | Part 9 | Future Research Areas

Stanford CS329A Self-Improving AI Agents | Part 7 | Self-Improvement and Deep Research Agents

Stanford CS329A Self-Improving AI Agents | Part 6 | Train Time Scaling/Scaling RL

Stanford CS329A Self-Improving AI Agents | Part 5 | Planning and Multi-Step Reasoning

Stanford CS329A Self-Improving AI Agents | Part 4 | Learning from Feedback with Tools/Code

Stanford CS329A Self-Improving AI Agents | Part 3 | Robust Verification

Stanford CS329A Self-Improving AI Agents | Part 2 | Test-Time Compute Scaling

Stanford CS329A Self-Improving AI Agents | Part 1 | Course Overview

New BEST AI video generator is here! Seedance 2.5 vs Minimax H3

Efficient Reinforcement Learning for Diffusion Models

Distributional Diffusion Models

ASTRA, la nouvelle IA d’OpenAI : beaucoup trop puissante (la fin de l’ère GPT) !

ASTRA, OpenAI's new AI: way too powerful (the end of the GPT era)!

Understanding AI Agent Hallucination in AI Systems

Architectures for an AI agent for route planning and Next-Latent Prediction

You Have to Try the New ChatGPT Voice!

MLT | Week-7 | Solve with us-Decision Tree and K-NN

A Chinese Open Model Just Hit the Frontier

Stanford CS229 Machine Learning | Spring 2026 | Lecture 9: K-Means and GMM (non-EM)

Stanford CS229 Machine Learning | Spring 2026 | Lecture 20: GMM (EM), PCA

Stanford CS229 Machine Learning | Spring 2026 | Lecture 18: GMM (EM), PCA

Stanford CS229 Machine Learning | Spring 2026 | Lecture 16: Basic Concept in RL, Policy Gradient

Stanford CS229 Machine Learning | Spring 2026 | Lecture 14: Transformers, In-Context Learning

Stanford CS229 Machine Learning | Spring 2026 | Lecture 13: LLMs, Next-Word Prediction Loss

Stanford CS229 Machine Learning | Spring 2026 | Lecture 12: Representation Learning

Stanford CS229 Machine Learning | Spring 2026 | Lecture 11: Diffusion Models

Stanford CS229 Machine Learning | Spring 2026 | Lecture 10: GMM (EM), PCA

Neural Network-Based Estimation of Time-Dependent Parameters || July 31, 2026

MLP Live session

Stanford CS229 Machine Learning | Spring 2026 | Lecture 8: Neural Networks 2 (Backprop)

Stanford CS229 Machine Learning | Spring 2026 | Lecture 7: Neural Networks 1 (Architecture)

Stanford CS229 Machine Learning | Spring 2026 | Lecture 6: Dataset Split, ML Advice

Stanford CS229 Machine Learning | Spring 2026 | Lecture 5: Gaussian Discriminant Analysis

Lec 18: First steps in performance

Lec 17: Data loaded & Feeding the model efficiently

Lec 16: The Training Loop

How to Check AI generated text, image and videos?

Stanford CS229 Machine Learning | Spring 2026 | Lecture 4: Exponential Family, GLMs Classification

Stanford CS229 Machine Learning | Spring 2026 | Lecture 3: Weighted Least Squares

Stanford CS229 Machine Learning | Spring 2026 | Lecture 2: Supervised Learning Setup

Stanford CS229 Machine Learning | Spring 2026 | Lecture 1: Introduction