Sebastian Raschka, PhD
Kimi K3 Architecture Notes
A Few Notable Open-Weight Models This Week
Correction for Listing 6.5 in Build a Reasoning Model From Scratch
Controlling Reasoning Effort in LLMs
Inkling: A New Open-Weight 975B MoE with a Few Surprises
200,000 Subscribers
GPT 5.6 Has 72 Possible Configurations. What's A Good Default?
Build a Reasoning Model From Scratch Is Out
Using Local Coding Agents
Using Local Coding Agents
Local Open-Weight LLMs in Coding Harnesses
GLM-5.2 and IndexShare for Long-Context Sparse Attention
VibeThinker-3B and the Strength of Post-Training
North Mini Code and Agentic Coding Benchmarks
LLM Research Papers: The 2026 List (January to May)
Nemotron 3 Ultra and Latent MoE Scaling
MiniMax M2 and Production-Oriented Model Design
DeepSeek Sparse Attention From Scratch
Recent Developments in LLM Architectures: KV Sharing, mHC, and Compressed Attention
Recent Developments in LLM Architectures: KV Sharing, mHC, and Compressed Attention
Implementing LLM Architectures From Scratch
My Workflow for Understanding LLM Architectures
Components of A Coding Agent
Gemma 4 Architecture and Benchmark Notes
Claude Code's Real Secret Sauce Isn't the Model
LLM Architecture Gallery Diff Tool
A Visual Guide to Attention Variants in Modern LLMs
A Visual Guide to Attention Variants in Modern LLMs
New LLM Architecture Gallery
Nemotron 3 Super Throughput Notes
A Dream of Spring for Open-Weight LLMs: 10 Architectures from Jan-Feb 2026
State of AI 2026 with Sebastian Raschka, Nathan Lambert, and Lex Fridman
Categories of Inference-Time Scaling for Improved LLM Reasoning
The State Of LLMs 2025: Progress, Problems, and Predictions
The State Of LLMs 2025: Progress, Problems, and Predictions
LLM Research Papers: The 2025 List (July to December)
From Random Forests to RLVR: A Short History of ML/AI Hello Worlds
A Technical Tour of the DeepSeek Models from V3 to V3.2
Recommendations for Getting the Most Out of a Technical Book
Beyond Standard LLMs
DGX Spark and Mac Mini for Local PyTorch Development
Understanding the 4 Main Approaches to LLM Evaluation (From Scratch)
Understanding and Implementing Qwen3 From Scratch
From GPT-2 to gpt-oss: Analyzing the Architectural Advances
The Big LLM Architecture Comparison
LLM Research Papers: The 2025 List (January to June)
Understanding and Coding the KV Cache in LLMs from Scratch
Coding LLMs from the Ground Up: A Complete Course
The State of Reinforcement Learning for LLM Reasoning
First Look at Reasoning From Scratch: Chapter 1
Inference-Time Compute Scaling Methods to Improve Reasoning Models
Understanding Reasoning LLMs
Noteworthy LLM Research Papers of 2024
Implementing A Byte Pair Encoding (BPE) Tokenizer From Scratch
LLM Research Papers: The 2024 List
Understanding Multimodal LLMs
Building A GPT-Style LLM Classifier From Scratch
Building LLMs from the Ground Up: A 3-hour Coding Workshop
New LLM Pre-training and Post-training Paradigms
Instruction Pretraining LLMs
Developing an LLM: Building, Training, Finetuning
LLM Research Insights: Instruction Masking and New LoRA Finetuning Experiments?
How Good Are the Latest Open LLMs? And Is DPO Better Than PPO?
Using and Finetuning Pretrained Transformers
Tips for LLM Pretraining and Evaluating Reward Models
Research Papers in February 2024
Improving LoRA: Implementing Weight-Decomposed Low-Rank Adaptation (DoRA) from Scratch
Optimizing LLMs From a Dataset Perspective
The NeurIPS 2023 LLM Efficiency Challenge Starter Guide
Optimizing Memory Usage for Training LLMs and Vision Transformers in PyTorch
Finetuning Falcon LLMs More Efficiently With LoRA and Adapters
Accelerating Large Language Models with Mixed-Precision Techniques
Parameter-Efficient LLM Finetuning With Low-Rank Adaptation (LoRA)
Understanding Parameter-Efficient Finetuning of Large Language Models: From Prefix Tuning to LLaMA-Adapters
Finetuning Large Language Models On A Single GPU Using Gradient Accumulation
Keeping Up With AI Research And News
Some Techniques To Make Your PyTorch Models Train (Much) Faster
Understanding and Coding the Self-Attention Mechanism of Large Language Models From Scratch
Understanding and Coding Self-Attention, Multi-Head Attention, Causal Attention, and Cross-Attention in LLMs
Understanding Large Language Models -- A Transformative Reading List
What Are the Different Approaches for Detecting Content Generated by LLMs Such As ChatGPT? And How Do They Work and Differ?
Comparing Different Automatic Image Augmentation Methods in PyTorch
Curated Resources and Trustworthy Experts: The Key Ingredients for Finding Accurate Answers to Technical Questions in the Future
Training an XGBoost Classifier Using Cloud GPUs Without Worrying About Infrastructure
Open Source Highlights 2022 for Machine Learning & AI
Influential Machine Learning Papers Of 2022
Ahead Of AI, And What's Next?
A Short Chronology Of Deep Learning For Tabular Data
No, We Don't Have to Choose Batch Sizes As Powers Of 2
Sharing Deep Learning Research Models with Lightning Part 2: Leveraging the Cloud
Sharing Deep Learning Research Models with Lightning Part 1: Building A Super Resolution App
Taking Datasets, DataLoaders, and PyTorch’s New DataPipes for a Spin
Running PyTorch on the M1 GPU
Creating Confidence Intervals for Machine Learning Classifiers
Losses Learned
TorchMetrics
Machine Learning with PyTorch and Scikit-Learn
Introduction to Machine Learning
Introduction to Deep Learning
Datasets for Machine Learning and Deep Learning
Book Review: Deep Learning With PyTorch
How I Keep My Projects Organized
Scientific Computing in Python: Introduction to NumPy and Matplotlib
Interpretable Machine Learning
Chapter 1: Introduction to Machine Learning and Deep Learning
Book Review: Architects of Intelligence by Martin Ford
What's New in the 3rd Edition
My First Year at UW-Madison and a Gallery of Awesome Student Projects
Model evaluation, model selection, and algorithm selection in machine learning
Generating Gender-Neutral Face Images with Semi-Adversarial Neural Networks to Enhance Privacy
Model evaluation, model selection, and algorithm selection in machine learning
Model evaluation, model selection, and algorithm selection in machine learning
Model evaluation, model selection, and algorithm selection in machine learning
Writing 'Python Machine Learning'
Python, Machine Learning, and Language Wars
Single-Layer Neural Networks and Gradient Descent
Principal Component Analysis
Implementing a Weighted Majority Rule Ensemble Classifier
MusicMood
Turn Your Twitter Timeline into a Word Cloud
Naive Bayes and Text Classification
Kernel tricks and nonlinear dimensionality reduction via RBF kernel PCA
Predictive modeling, supervised machine learning, and pattern classification
Linear Discriminant Analysis
Dixon's Q test for outlier identification
About Feature Scaling and Normalization
Entry Point Data
Molecular docking, estimating free energies of binding, and AutoDock's semi-empirical force field
An introduction to parallel programming using Python's multiprocessing module
Kernel density estimation via the Parzen-Rosenblatt window method
Numeric matrix manipulation
The key differences between Python 2.7.x and Python 3.x with examples
5 simple steps for converting Markdown documents into HTML and adding Python syntax highlighting
Creating a table of contents with internal links in IPython Notebooks and Markdown documents
A Beginner's Guide to Python's Namespaces, Scope Resolution, and the LEGB Rule
Diving deep into Python
Implementing a Principal Component Analysis (PCA)
Installing Scientific Packages for Python3 on MacOS 10.9 Mavericks
A thorough guide to SQLite database operations in Python
Using OpenEye software for substructure alignments
Unit testing in Python
A short tutorial for decent heat maps in R
SQLite