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AI Engineering
Agents, orchestration, tooling, and workflow-oriented posts.
LLM & RAG
LLM applications, retrieval pipelines, and adaptation methods.
Model & Training
Architecture, tokenization, training recipes, RL, and evaluation.
Systems & Platform
GPU kernels, inference performance, infrastructure, and deployment.
Research & Notes
Paper reading, tech notes, and core deep learning domains.