Practical AI and machine learning engineering. LLM inference, tokenization, RAG pipelines, model deployment, vector databases, and the infrastructure behind modern AI applications.
54 articles
A practical guide to vector databases -- how embeddings and ANN algorithms work, and an honest comparison of Pinecone, Weaviate, Qdrant, and pgvector.
A practical guide to building Retrieval-Augmented Generation pipelines -- from document chunking and embedding to hybrid retrieval and evaluation metrics.
Language models process tokens, not words. Learn how BPE tokenization works, what the context window really is, and how the KV cache speeds up generation — with real pricing comparisons across OpenAI, Anthropic, and Google.
Deploy a private ChatGPT alternative with Open WebUI and Ollama. Complete Docker Compose setup with model selection, RAG document upload, web search, multi-user config, and security hardening.
A practitioner comparison of LangGraph, CrewAI, and AutoGen -- benchmarks on research, code gen, and data analysis agents with code examples, token efficiency, and production guidance.
End-to-end guide to deploying ML models -- from ONNX export and FastAPI serving to Kubernetes GPU workloads, canary deployments, and Prometheus monitoring.
A practical guide to vector databases -- how embeddings and ANN algorithms work, and an honest comparison of Pinecone, Weaviate, Qdrant, and pgvector.
A practical guide to building Retrieval-Augmented Generation pipelines -- from document chunking and embedding to hybrid retrieval and evaluation metrics.
Language models process tokens, not words. Learn how BPE tokenization works, what the context window really is, and how the KV cache speeds up generation — with real pricing comparisons across OpenAI, Anthropic, and Google.
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