Current study materials

[1412.6980] Adam: A Method for Stochastic Optimization

Learning with not Enough Data Part 1: Semi-Supervised Learning | Lil'Log

RAG vs. Fine-tuning and more | Google Cloud Blog

A real explanation of discrete Fourier transform

MLOps system design is boring. - by Alexandru Vesa

Faster Python calculations with Numba: 2 lines of code, 13× speed-up

Things that go wrong with disk IO | notes.eatonphil.com

Dependency Injection for Artificial Intelligence (DI4AI)

On Task-specific and General-purpose Distillation Techniques to Enhance Reasoning Capabilities of LLMs

[2503.05336v3] Toward an Evaluation Science for Generative AI Systems

Introduction | RLHF Book by Nathan Lambert

Is GOPRIVATE actually needed? : r/golang


Demystifying Chains, Trees, and Graphs of Thoughts

Sequential decision making - Kevin Murphy, DeepMind

Strategic Foundation Models - Large_Language_Models__Foundation_Models_and_Game_Theory___Research_Manifesto (16).pdf

Streaming DiLoCo with overlapping communication: Towards a Distributed Free Lunch

International AI safety report - International_AI_Safety_Report_2025_accessible_f.pdf

DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

7B Model and 8K Examples: Emerging Reasoning with Reinforcement Learning is Both Effective and Efficient

A Little Bit of Reinforcement Learning from Human Feedback

DeepSeek R1's recipe to replicate o1 and the future of reasoning LMs

A Mathematical Framework for Transformer Circuits

A Recipe for Training Neural Networks

Scaling and networking a modular photonic quantum computer | Nature

Large Language Diffusion Models

KindXiaoming/grow-crystals: Getting crystal-like representations with harmonic loss

Harmonic Loss Trains Interpretable AI Models