AI-Powered Autonomous Social Media CMO — 6-agent pipeline, 12 platforms, GPT Image 1.5, Brand Kit, local AI via Ollama. Free open-source alternative to SocialRails/Buffer/Hootsuite.

Agro-Vision – Multilingual AI Dashboard for Indian Farmers | Crop Health, Weather, Market Prices | AgriTech + AI | NDVI Satellite Integration

An innovative platform designed to enhance access to government schemes and subsidies.

Vedic Edge Computing Module for Indian Agriculture Department

Abir-Guard is a Post-Quantum Cryptography (PQC) powered security framework for AI agents, designed to protect memory, keys, and execution using hardware-backed encryption and zero-trust architecture.

Should you buy a DGX Spark or rent H100s? Run on Mac Mini or TAALAS cluster? Full cost & performance comparison of GPU hardware and cloud for Indian AI developers — with data sovereignty, IndiaAI Mission subsidies, and Dynamo 1.0 coverage.

Living tracker of the AI ecosystem — quantum computing research, AI summits, Silicon Valley updates, tool releases, and industry trends

Brahm-Ai source code, modules & updates

HTGM v2 Hindi LLM reaches 210+ hours and 54K+ steps. Session 23 shows stable validation despite high training fluctuations and real LLM training dynamics.

Real test results of HTGM v2 Hindi LLM after 150+ training hours. Base model output analysis, Hindi Q&A testing, and learning progress.

Building HTGM v2 — a Hindi LLM from scratch using GPT architecture. Real training logs, checkpoints, experiments, and progress shared publicly.

HTGM v2 crosses 150+ training hours while Mahesh Editor starts Smell AI, a new AI research project focused on smell and human emotional reactions.

Building HTGM v2 — a Hindi LLM from scratch using GPT architecture. Session 19 crosses 165+ hours training and 42K+ optimizer steps milestone.

Building HTGM v2 — a Hindi LLM from scratch using GPT architecture. Real training logs, checkpoints, experiments, and progress shared publicly.

Building HTGM v2 — a Hindi LLM from scratch using GPT architecture. Real training logs, checkpoints, experiments, and progress shared publicly.

HTGM v2 Hindi LLM reaches 180+ hours and 48K+ steps. Session 21 shows high learning rate instability and real LLM training dynamics.

HTGM v2 Hindi LLM trained for 220+ hours on 41GB dataset. Real model outputs, limitations, and insights from base pre-training before SFT.

Building HTGM v2 — a Hindi LLM from scratch using GPT architecture. Real training logs, experiments, and progress shared in public.

HTGM v2 Hindi LLM crosses 200+ hours and 51K+ steps. Session 22 shows recovery from instability with improved validation and stable training pipeline.

Building HTGM v2 — a Hindi LLM from scratch using GPT architecture. Session 18 crosses 155+ hours training and 40K+ optimizer steps milestone.