Independent coverage of frontier models, Indian compute initiatives, practical implementation guides, and open benchmarks.
From Cursor AI and Claude Code to local Ollama setups and vLLM inference runners: the essential productivity stack for engineering teams.
Meta's latest open-weights model achieves 405B-class benchmark performance on a single 8x H100 node or quantized 4-bit dual RTX 4090s.
Ola's AI arm launches bare-metal GPU clusters and managed inference endpoints with native rupee billing and localized customer support.
Why naive RAG fails in production: implementing semantic document chunking, Cohere/BGE re-ranking cross-encoders, and hybrid dense-sparse vector search.
Collaborating with the Indian Institute of Science (IISc), Google DeepMind releases 14,000 hours of open-source conversational audio across 80 Indian districts.
Clear, jargon-free explanation of how neural networks predict next tokens, how transformers process text, and why fine-tuning creates intelligent AI systems.
A practical tutorial on running quantized 1.5B, 7B, 14B, and 32B DeepSeek-R1 reasoning models completely offline on Mac, Windows, and Linux.
Mukesh Ambani and Jensen Huang outline plans for gigawatt-scale AI infrastructure powered by green solar energy to serve Indian sovereign computing needs.
Headed by IIT Bombay and funded by DST, BharatGen is training foundation models dedicated to Indian culture, languages, and citizen public services.