| Jul 12, 2026 | The World Models Series |
| Jul 12, 2026 | LeWorldModel: A Compact Latent World Model—and Where It Breaks |
| Jul 6, 2026 | Reinforcement Learning and Abstract World Models |
| Jun 1, 2026 | The AI Agents Series |
| Jun 1, 2026 | AI Agents Series | Self Improving Agents - Foundation and Advances |
| Jun 1, 2026 | AI Agents 101 | 14. Standards and Ecosystem |
| Jun 1, 2026 | AI Agents 101 | 13. Coding Agents as a Case Study |
| Jun 1, 2026 | AI Agents 101 | 12. Agentic UX |
| Jun 1, 2026 | AI Agents 101 | 11. Production Agent Architecture |
| Jun 1, 2026 | AI Agents 101 | 10. Evaluation and Observability |
| Jun 1, 2026 | AI Agents 101 | 09. Safety, Security, and Governance |
| Jun 1, 2026 | AI Agents 101 | 08. Data Layer and Enterprise Integration |
| Jun 1, 2026 | AI Agents 101 | 07. Orchestration Patterns |
| Jun 1, 2026 | AI Agents 101 | 06. Tools, MCP, Skills, and Plugins |
| Jun 1, 2026 | AI Agents 101 | 05. Context and Memory |
| Jun 1, 2026 | AI Agents 101 | 04. Agent Loop and Runtime Design |
| Jun 1, 2026 | AI Agents 101 | 03. The Core Agent Model |
| Jun 1, 2026 | AI Agents 101 | 02. From Prompt Engineering to Agent Systems Engineering |
| Jun 1, 2026 | AI Agents 101 | 01. Why Agents, Why Now |
| Dec 20, 2025 | Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 18- Human-Centered AI |
| Dec 20, 2025 | Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 17- Robot Learning |
| Dec 20, 2025 | Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 16- Vision and Language |
| Dec 20, 2025 | Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 15- 3D Vision |
| Dec 20, 2025 | Stanford CS231N Deep Learning for Computer Vision| Spring 2025 | Lecture 14- Generative Models 2 |
| Dec 20, 2025 | Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 13- Generative Models 1 |
| Dec 20, 2025 | Stanford CS231N | Spring 2025 | Lecture 12- Self-Supervised Learning |
| Dec 20, 2025 | Stanford CS231N | Spring 2025 | Lecture 11- Large Scale Distributed Training |
| Dec 20, 2025 | Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 10- Video Understanding |
| Dec 20, 2025 | Stanford CS231N | Spring 2025 | Lecture 9- Object Detection, Image Segmentation, Visualizing |
| Dec 20, 2025 | Stanford CS231N | Spring 2025 | Lecture 8- Attention and Transformers |
| Dec 20, 2025 | Stanford CS231N | Spring 2025 | Lecture 7- Recurrent Neural Networks |
| Dec 20, 2025 | Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 6- CNN Architectures |
| Dec 20, 2025 | Stanford CS231N | Spring 2025 | Lecture 5- Image Classification with CNNs |
| Dec 20, 2025 | Stanford CS231N | Spring 2025 | Lecture 4- Neural Networks and Backpropagation |
| Dec 20, 2025 | Stanford CS231N | Spring 2025 | Lecture 3- Regularization and Optimization |
| Dec 20, 2025 | Stanford CS231N | Spring 2025 | Lecture 2- Image Classification with Linear Classifiers |
| Dec 20, 2025 | Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 1- Introduction |
| Dec 17, 2025 | MIT 6.S184 - Lecture 6 - Diffusion for Protein Generation |
| Dec 17, 2025 | MIT 6.S184 - Lecture 5 - Diffusion for Robotics |
| Dec 17, 2025 | MIT 6.S184 - Lecture 4 - Building an Image Generator |
| Dec 17, 2025 | MIT 6.S184 - Lecture 3 - Training Flow and Diffusion Models |
| Dec 17, 2025 | MIT 6.S184 - Lecture 2 - Constructing a Training Target |
| Dec 17, 2025 | MIT 6.S184 - Lecture 1 - Generative AI with SDEs |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 18 - Diffusion Models for Discrete Data |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 17 - Discrete Latent Variable Models |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 16 - Score Based Diffusion Models |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 15 - Evaluation of Generative Models |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 14 - Energy Based Models |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 13 - Score Based Models |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 12 - Energy Based Models |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 11 - Energy Based Models |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 10 - GANs |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 9 - GANs |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 8 - Normalizing Flows |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 7 - Normalizing Flows |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 6 - VAEs |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 5 - VAEs |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 4 - Maximum Likelihood Learning |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 3 - Autoregressive Models |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 2 - Background |
| Dec 17, 2025 | Stanford CS236- Deep Generative Models I 2023 I Lecture 1 - Introduction |
| Dec 15, 2025 | Agent 08 - Building Game Simulation Agents |
| Dec 15, 2025 | Agent 07 - Building an Agent from Scratch by AI Engineer |
| Dec 15, 2025 | Agent 06 - Building Agents with MCP by Mahesh Murag Anthropic |
| Dec 15, 2025 | Agent 05 - How We Build Effective Agents by Barry Zhang Anthropic |
| Dec 15, 2025 | Agent 04 - Building and evaluating AI Agents by Sayash Kapoor AI Snake Oil |
| Dec 15, 2025 | Agent 03 - Stanford Webinar - Agentic AI - A Progression of Language Model Usage |
| Dec 15, 2025 | Agent 02 - Building Large Language Models by Stanford CS229 |
| Dec 15, 2025 | Agent 01 - Intro to Large Language Models by Andrej Karpathy |
| Dec 15, 2025 | Karpathy Series - Let's build GPT from scratch |
| Dec 15, 2025 | Karpathy Series - Let's build the GPT Tokenizer |
| Dec 15, 2025 | Karpathy Series - Let's reproduce GPT-2 |
| Dec 15, 2025 | Karpathy Series - How I use LLMs |
| Dec 15, 2025 | Karpathy Series - Deep Dive into LLMs like ChatGPT |
| Dec 15, 2025 | Karpathy Series - Intro to Large Language Models |
| Dec 15, 2025 | Karpathy Series - Bulding Makemore Part 5 - Wavenet |
| Dec 15, 2025 | Karpathy Series - Bulding Makemore Part 4 - Becoming a Backprop Ninja |
| Dec 15, 2025 | Karpathy Series - Bulding Makemore Part 3 - Activations, Gradients, BatchNorm |
| Dec 15, 2025 | Karpathy Series - Bulding Makemore Part 2 - MLP |
| Dec 15, 2025 | Karpathy Series - Building Makemore |
| Dec 15, 2025 | Karpathy Series - Building Micrograd |
| Dec 15, 2025 | Generating Lecture Notes by AI |
| Dec 7, 2025 | CS336 Series - Language Modeling from Scratch |
| Dec 7, 2025 | CS336 Lecture 17 - Alignment - RL - Part 2 |
| Dec 7, 2025 | CS336 Lecture 16 - Alignment - RL |
| Dec 7, 2025 | CS336 Lecture 15 - Alignment - SFT/RLHF |
| Dec 7, 2025 | CS336 Lecture 14 - Data - Part 2 |
| Dec 7, 2025 | CS336 Lecture 13 - Data |
| Dec 7, 2025 | CS336 Lecture 12 - Evaluation |
| Dec 7, 2025 | CS336 Lecture 11 - Scaling laws |
| Dec 7, 2025 | CS336 Lecture 10 - Inference |
| Dec 7, 2025 | CS336 Lecture 9 - Scaling laws |
| Dec 7, 2025 | CS336 Lecture 8 - Parallelism - Part 2 |
| Dec 7, 2025 | CS336 Lecture 7 - Parallelism |
| Dec 7, 2025 | CS336 Lecture 6 - Kernels, Triton |
| Dec 7, 2025 | CS336 Lecture 5 - GPUs |
| Dec 7, 2025 | CS336 Lecture 4 - Mixture of experts |
| Dec 7, 2025 | CS336 Lecture 3 - Architectures, hyperparameters |
| Dec 7, 2025 | CS336 Lecture 2 - PyTorch, resource accounting |
| Dec 7, 2025 | CS336 Lecture 1 - Overview and Tokenization |
| Oct 14, 2025 | Less is More - Recursive Reasoning with Tiny Networks |
| Aug 8, 2025 | GPT-5 Series - Safe Completion Training |
| Jul 23, 2025 | Personalized LLMs |
| Mar 15, 2025 | MS-Diffusion - Multi-subject Zero-shot Image Personalization with Layout Guidance (ICLR 2025) |
| Mar 14, 2025 | Unlearning LLMs |
| Mar 8, 2025 | The Foundations and Frontiers of Diffusion Models |
| Feb 28, 2025 | FineStyle - Fine-grained Controllable Style Personalization for Text-to-image Models (NeurIPS 2024) |
| Feb 27, 2025 | DreamStyler - Paint by Style Inversion with Text-to-Image Diffusion Models (AAAI-2024) |
| Feb 21, 2025 | Kolmogorov-Arnold Network (KAN) |
| Jan 28, 2025 | DeepSeek-R1 |
| Jan 19, 2025 | LLM Series - Part 5 - System Design for LLMs |
| Jan 18, 2025 | LLM Series - Part 4 - How to Jailbreak LLMs |
| Jan 17, 2025 | LLM Series - Part 3 - Build a Chatbot with Ollama |
| Jan 16, 2025 | LLM Series - Part 2 - Common Implementations in LLMs |
| Jan 15, 2025 | LLM Series - Part 1 - Important Concepts in NLP |
| Jan 15, 2025 | The LLM Series |
| Jan 15, 2025 | The Trustworthy GenAI Series |
| Jan 14, 2025 | Foundations of Machine Learning |
| Dec 18, 2024 | What is Safety Checker in Stable Diffusion |
| Dec 13, 2024 | Some notes on NeurIPS 2024 |
| Nov 18, 2024 | Random Thoughts and Notes |
| Jul 26, 2024 | Connection between Flatness and Generalization |
| Jul 9, 2024 | Trustworthy and Safety AI Resources |
| Jul 1, 2024 | Comparing Implementations of Diffusion Models - HuggingFace Diffusers vs. CompVis Stable Diffusion |
| Jun 26, 2024 | AdvPrompter - Fast Adaptive Adversarial Prompting for LLMs |
| May 5, 2024 | Lesson Learned from NeurIPS 2023 Machine Unlearning Challenge |
| Apr 21, 2024 | Unsolvable Problem Detection - Evaluating Trustworthiness of Vision Language Models |
| Apr 20, 2024 | Universal and Transferable Adversarial Attacks on Aligned Language Models |
| Apr 19, 2024 | Cold Diffusion - Inverting Arbitrary Image Transforms Without Noise |
| Dec 13, 2023 | Visual Prompt Tuning |
| Oct 17, 2023 | Tree-Ring Watermarks - Fingerprints for Diffusion Images that are Invisible and Robust |
| Oct 3, 2023 | A Tutorial on Diffusion Models (Part 2) |
| Oct 3, 2023 | A Tutorial on Diffusion Models (Part 1) |
| Sep 22, 2023 | Flow Matching for Generative Modeling |
| Sep 14, 2023 | Diffusion Models Beat GANs on Image Synthesis |
| Sep 1, 2023 | Comprehensive Algorithm Portfolio Evaluation using Item Response Theory |
| Aug 10, 2023 | Erasing Concepts from Diffusion Models |
| Aug 7, 2023 | Textual Inversion |
| Aug 5, 2023 | Papers Reading |
| Aug 5, 2023 | Dreambooth and Anti-Dreambooth |