- Published on
A technical deep-dive into building Browser RAG, a 100% local, client-side retrieval-augmented generation engine running inside the browser using PGlite WASM, pgvector, WebGPU, and client-side LLMs.
Rag
All Posts
rag (4)
- how-to (3)
- visualization (3)
- agents (3)
- webgpu (3)
- wasm (3)
- transformersjs (3)
- local-ai (3)
- ml (2)
- short_read (2)
- llm (2)
- onnx (2)
- python (2)
- retrieval (2)
- maths (1)
- news (1)
- sovereign-ai (1)
- data-center (1)
- compute (1)
- india (1)
- gpu (1)
- infrastructure (1)
- ai-policy (1)
- browser-ai (1)
- pglite (1)
- webllm (1)
- pgvector (1)
- mlx (1)
- sft (1)
- reasoning (1)
- qwen (1)
- deepseek (1)
- voice (1)
- markdown (1)
- pdf (1)
- typesetting (1)
- serverless (1)
- aws (1)
- azure (1)
- gcp (1)
- sandboxing (1)
- Published on
A 100% serverless, scale-to-zero RAG chatbot architectural comparison across AWS, Azure, and GCP, deep-diving into compute, streaming, ingestion pipelines, database choices, and cost traps.- Published on
Understanding the tradeoffs between sequential and parallel multi-hop retrieval flows in RAG systems through step-by-step visualizations.- Published on
Understanding the tradeoffs between bi-encoders, cross-encoders, and late interaction in dense retrieval systems and how they work.