A Dream of Spring for Open-Weight LLMs: 10 Architectures from Jan-Feb 2026
A Round Up And Comparison of 10 Open-Weight LLM Releases in Spring 2026
ai, deep-learning, llm, Machine Learning
llm
ai, deep-learning, llm, Machine Learning
State of AI 2026 with Sebastian Raschka, Nathan Lambert, and Lex Fridman
I recently sat down with Lex Fridman and Nathan Lambert for a comprehensive 4.5 h interview to discuss the current state of progress of AI, and what the…
ai, deep-learning, llm, Machine Learning
Categories of Inference-Time Scaling for Improved LLM Reasoning
Inference scaling has become one of the most effective ways to improve answer quality and accuracy in deployed LLMs. The idea is straightforward. If we are…
ai, deep-learning, llm, Machine Learning
The State Of LLMs 2025: Progress, Problems, and Predictions
A 2025 review of large language models, from DeepSeek R1 and RLVR to inference-time scaling, benchmarks, architectures, and predictions for 2026.
ai, deep-learning, llm, Machine Learning
LLM Research Papers: The 2025 List (July to December)
A curated list of LLM research papers from July–December 2025, organized by reasoning models, inference-time scaling, architectures, training efficiency…
ai, deep-learning, llm, Machine Learning
From Random Forests to RLVR: A Short History of ML/AI Hello Worlds
Two years ago, I posted a list of Hello World examples for machine learning and AI on social. Here, the Hello World means beginner-friendly examples to…
ai, deep-learning, llm, Machine Learning
From DeepSeek V3 to V3.2: Architecture, Sparse Attention, and RL Updates
Similar to DeepSeek V3, the team released their new flagship model over a major US holiday weekend. Given DeepSeek V3.2’s really good performance (on GPT-5…
ai, deep-learning, llm, Machine Learning
Recommendations for Getting the Most Out of a Technical Book
This short article compiles a few notes I previously shared when readers ask how to get the most out of my building large language model from scratch books…
ai, deep-learning, llm, Machine Learning
Beyond Standard LLMs
After I shared my Big LLM Architecture Comparison a few months ago, which focused on the main transformer-based LLMs, I received a lot of questions with…
ai, deep-learning, llm, Machine Learning
DGX Spark and Mac Mini for Local PyTorch Development
The DGX Spark for local LLM inferencing and fine-tuning was a pretty popular discussion topic recently. I got to play with one myself, primarily working…