Bright Data MCP server: https://t.co/usgVhAtiMN(don't forget to star it ⭐ ) ...

Big update for ChatGPT/Claude Desktop users!MCP servers in Claude/Cursor don't offer any UI experience yet, like interactive widgets. It's just text/JSON, like below:{"product": "iPhone 16 Pro","price": "$999","rating": "4.5 stars"}Displaying this as a visual element isn't impossible, but most MCP servers make you write the same boilerplate twice, once for the React component and again to register it as an MCP tool.So you end up with duplicate schemas, manual prop mapping, and a bunch of registration code.A ...

RT Avi Chawla (@_avichawla)4 strategies for Multi-GPU training, explained visually: https://t.co/o5Z2Ni9qHk ...

4 strategies for Multi-GPU training, explained visually: https://t.co/o5Z2Ni9qHk ...

RT Avi Chawla (@_avichawla)The ultimate Full-stack AI Engineering roadmap to go from 0 to 100.This is the exact mapped-out path on what it actually takes to go from Beginner → Full-Stack AI Engineer.> Start with Coding Fundamentals.> Learn Python, Bash, Git, and testing.> Every strong AI engineer starts with fundamentals.> Learn how to interact with models by understanding LLM APIs.> This will teach you structured outputs, caching, system prompts, etc.> APIs are great, but raw LLMs still need the latest inf ...

The ultimate Full-stack AI Engineering roadmap to go from 0 to 100.This is the exact mapped-out path on what it actually takes to go from Beginner → Full-Stack AI Engineer.> Start with Coding Fundamentals.> Learn Python, Bash, Git, and testing.> Every strong AI engineer starts with fundamentals.> Learn how to interact with models by understanding LLM APIs.> This will teach you structured outputs, caching, system prompts, etc.> APIs are great, but raw LLMs still need the latest info to be effective.> Learn h ...

RT Avi Chawla (@_avichawla)Your embedding stack forces a 100% re-index just to change models.And most teams treat that as unavoidable.Imagine you built a RAG pipeline with a large embedding model for high retrieval quality, and it ships to production.Six months later, your application traffic and your embedding model costs are soaring while your pipeline struggles to scale. You want to switch to a model that prioritizes cost and latency in order to meet this new demand.But your existing embeddings live in o ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs. https://t.co/lNSHKvmczqAvi Chawla (@_avichawla):Your embedding stack forces a 100% re-index just to change models.And most teams treat that as unavoidable.Imagine you built a RAG pipeline with a large embedding model for high retrieval quality, and it ships to production.Six months later, your application traffic and https://t.co/EtZ05xrK81 ...

Download Voyage-4-nano from HF: https://t.co/mXjgxriy6d ...

Your embedding stack forces a 100% re-index just to change models.And most teams treat that as unavoidable.Imagine you built a RAG pipeline with a large embedding model for high retrieval quality, and it ships to production.Six months later, your application traffic and your embedding model costs are soaring while your pipeline struggles to scale. You want to switch to a model that prioritizes cost and latency in order to meet this new demand.But your existing embeddings live in one vector space, while the ...