Avi Chawla (@_avichawla)

Every generate() call to an LLM runs two distinct computational phases on the same GPU:...

- Google Maps uses graph ML to predict ETA - Netflix uses graph ML in recommendation - Spotify uses graph ML in recommendation - Pinterest uses graph ML in recommendation Here are 6 must-know ways for graph feature engineering (with code):...

Fine-tuning LLM Agents without Fine-tuning LLMs! Imagine improving your AI agent's performance from experience without ever touching the model weights. It's just like how humans remember past episodes and learn from them. That's precisely what Memento does. The core concept: Instead of updating...

KV caching in LLMs, clearly explained (with visuals):...

The growth of LLM context length with time: - GPT-3.5-turbo → 4k tokens - OpenAI GPT4 → 8k tokens - Claude 2 → 100k tokens - Llama 3 → 128k tokens - Gemini → 1M tokens Let's understand how they extend the context length of LLMs:...

A new embedding model cuts vector DB costs by ~200x. It also outperforms OpenAI and Cohere models. Here's a complete breakdown (with visuals):...

An MCP server that makes anyone a database engineer (open-source)! @MongoDB just released an MCP Server that lets AI tools like Claude, Cursor, and GitHub Copilot talk directly to a MongoDB deployment. That means anyone (technical or non-technical) can now say: - “Show me the most active users” -...

A simple technique makes RAG ~32x memory efficient! - Perplexity uses it in its search index - Azure uses it in its search pipeline - HubSpot uses it in its AI assistant Let's understand how to use it in RAG systems (with code):...

Andrew Ng's team once made a big mistake in a research paper. And it happened due to randomly splitting the data. Here's what happened:...