Cognee GitHub repo: https://t.co/Ken9bmXWY9(don't forget to star 🌟) ...

RAG was never the end goal.Memory in AI agents is where everything is heading. Let me break down this evolution in the simplest way possible.RAG (2020-2023):- Retrieve info once, generate response- No decision-making, just fetch and answer- Problem: Often retrieves irrelevant contextAgentic RAG:- Agent decides if retrieval is needed- Agent picks which source to query- Agent validates if results are useful- Problem: Still read-only, can't learn from interactionsAI Memory:- Read AND write to external knowledg ...

RT Avi Chawla (@_avichawla)I boosted my AI Agent's performance by 184%...using a 100% open-source technique.Now you can automatically find the best prompts for any agentic workflow you're building.So you don't need to manual prompt engineering at all!The snippet below explains this using Comet's Opik.The idea is simple:1. Start with an initial prompt & eval dataset2. Let the optimizer iteratively improve the prompt3. Get the optimal prompt automatically!And this takes just a few lines of code.Why use Opik?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/V55Af2OZpsAvi Chawla (@_avichawla):I boosted my AI Agent's performance by 184%...using a 100% open-source technique.Now you can automatically find the best prompts for any agentic workflow you're building.So you don't need to manual prompt engineering at all!The snippet below explains this using Comet's https://t.co/KT3rCWEOO8 ...

GitHub repo: https://t.co/tZfGoaL8BL(don't forget to star it ⭐ ) ...

I boosted my AI Agent's performance by 184%...using a 100% open-source technique.Now you can automatically find the best prompts for any agentic workflow you're building.So you don't need to manual prompt engineering at all!The snippet below explains this using Comet's Opik.The idea is simple:1. Start with an initial prompt & eval dataset2. Let the optimizer iteratively improve the prompt3. Get the optimal prompt automatically!And this takes just a few lines of code.Why use Opik?Opik is a 100% open-source L ...

RT Avi Chawla (@_avichawla)Vector Index vs Vector Database, clearly explained!Devs typically use these terms interchangeably.But understanding this distinction is necessary since it leads to problems down the line.Here's how to think about it:A vector index is basically a search algorithm.You give it vectors, it organizes them into something searchable (like HNSW), and it finds similar items fast. FAISS is another example.But here's the thing.That's all it does. It doesn't handle storage, it doesn't filter ...

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/lgCr54DUEVAvi Chawla (@_avichawla):Vector Index vs Vector Database, clearly explained!Devs typically use these terms interchangeably.But understanding this distinction is necessary since it leads to problems down the line.Here's how to think about it:A vector index is basically a search algorithm.You https://t.co/wI5HOVlUyt ...

Milvus GitHub repo:(don't forget to star 🌟)https://t.co/QWS0u9aHCK ...

Vector Index vs Vector Database, clearly explained!Devs typically use these terms interchangeably.But understanding this distinction is necessary since it leads to problems down the line.Here's how to think about it:A vector index is basically a search algorithm.You give it vectors, it organizes them into something searchable (like HNSW), and it finds similar items fast. FAISS is another example.But here's the thing.That's all it does. It doesn't handle storage, it doesn't filter by metadata, and it doesn't ...