A technical analysis of the DeepSeek model series, from V3 to the latest V3.2, covering architecture, performance, and release timeline.
Explores Andrej Karpathy's concept of Software 2.0, where AI writes programs through objectives and gradient descent, focusing on task verifiability.
A curated list of key LLM research papers from Jan-June 2025, organized by topic including reasoning models, RL methods, and efficient training.
Analyzes the use of reinforcement learning to enhance reasoning capabilities in large language models (LLMs) like GPT-4.5 and o3.
An introduction to reasoning in Large Language Models, covering concepts like chain-of-thought and methods to improve LLM reasoning abilities.
A technical guide on fine-tuning IBM's Granite3.1 AI model using Guided Reward Policy Optimization (GRPO) to enhance its reasoning capabilities.
A technical review of April 2024's major open LLM releases (Mixtral, Llama 3, Phi-3, OpenELM) and a comparison of DPO vs PPO for LLM alignment.
Analysis of recent AI research papers on continued pretraining for LLMs and reward modeling for RLHF, with insights into model updates and alignment.
An introductory chapter on machine learning and deep learning, covering core concepts, categories, and the shift from traditional programming.
