Welcome to my space for exploring ideas across AI, aviation, geopolitics, philosophy, and culture. Each blog represents a different facet of my interests and work.
How Praval gained a common model runtime, MCP tools, multimodal input, voice, stronger Agent coordination, and exact-wheel validation while preserving its original design.
How Vajra 3D searches indexed point-cloud objects from text queries using a closed-source embedding model, Vajra HNSW, BM25 metadata search, RRF fusion, and a Three.js demo.
Why we must hold onto friction, understanding, and prioritize personal growth when working with AI, instead of ceding our cognitive processes to machines.
Vajra Search is the successor to Vajra-bm25, with a new backend implemented in Rust that covers the vector index core and which is published to PyPI as v0.2.1.
Technical notes on the Vajra search stack transition from BM25 benchmarks and Python vector search (v0.4.1/v0.5.0) to the Rust HNSW backend (`vajra_search`), with reproducible Wikipedia results.