By Chris Churilo, thanks to Zilliz thenewstack.io/how-ai-is-tran…

LangChain Open at Microsoft 🚀Project Number 3 - DeepSearcher🔥 'The Open Source Deep Research Tool' by Zilliz #opensource #github #trending #AI #coding #search #softwaredevelopment #technology #innovation #programming #AItools #DeepSearcher

Still confused about 𝐅𝐮𝐥𝐥-𝐭𝐞𝐱𝐭 𝐬𝐞𝐚𝐫𝐜𝐡 𝐚𝐧𝐝 𝐒𝐞𝐦𝐚𝐧𝐭𝐢𝐜 𝐬𝐞𝐚𝐫𝐜𝐡? Let's see how OpenAI's GPT-4o explains it through comics. 🔹 Full-text search: The classic retrieval method that finds documents containing exact terms/phrases through direct keyword

Transform your workflows with Minish's product: 𝐌𝐨𝐝𝐞𝐥2𝐕𝐞𝐜, a lightweight, high-performance embedding technique that converts 𝐒𝐞𝐧𝐭𝐞𝐧𝐜𝐞 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫 𝐦𝐨𝐝𝐞𝐥𝐬 𝐜𝐨𝐦𝐩𝐚𝐜𝐭, 𝐬𝐭𝐚𝐭𝐢𝐜 𝐦𝐨𝐝𝐞𝐥𝐬. It reduces model size by up to 50x and speeds

We're thrilled that Milvus is a key component of the exciting Smart Health Agent demo being showcased at Google Cloud Next 2025! Visit the NVIDIA booth on April 10th (5 PM PT) or April 11th (11 AM PT) to see the demo

"How do I start with Milvus?" We hear you! 🔍 Proud to team up with The Linux Foundation on this tutorial! Check out Milvus's Bootcamp with notebooks for building image search, RAG, AI agents & more. Stefan Webb 🎥 Full video: trainingportal.linuxfoundation.org/learn/video/mi…

🚀 New Video: Deploying Milvus Distributed with Kubernetes – Step-by-Step 🛠️ Milvus is a highly scalable vector database with distributed architecture. It has 3 "T-shirt" sizes: Small (Milvus Lite, runs in python), Medium (Standalone, everything compacted in Docker image) and

Here's the final output!

Thanks, Francisco Javier Arceo, for the excellent presentation! Great observation on how the original RAG paper proposed a different method to what's commonly known as RAG these days, and the value of fine-tuning the document encoder and retriever. Feast makes it super simple to do

Day 2 of Milvus Week: Slashing costs with 𝐑𝐚𝐁𝐢𝐭𝐐 quantization 🐰 As engineers, we want it all—higher performance, lower cost, and competitive quality. What if you could compress a vector down to just 𝟏 𝐛𝐢𝐭 𝐩𝐞𝐫 𝐝𝐢𝐦𝐞𝐧𝐬𝐢𝐨𝐧 and still achieve over 𝟗𝟎%

🔍 Struggling to squeeze more accuracy from your #RAG pipeline? The bottleneck might lie in how you compress knowledge. Single vector retrieval flattens entire passages into a single embedding—like judging a book solely by its cover while losing every critical line inside. 💥

💰 𝐘𝐨𝐮𝐫 𝐯𝐞𝐜𝐭𝐨𝐫 𝐬𝐞𝐚𝐫𝐜𝐡 𝐛𝐢𝐥𝐥 𝐢𝐬 𝐩𝐫𝐨𝐛𝐚𝐛𝐥𝐲 𝐰𝐚𝐲 𝐡𝐢𝐠𝐡𝐞𝐫 𝐭𝐡𝐚𝐧 𝐢𝐭 𝐧𝐞𝐞𝐝𝐬 𝐭𝐨 𝐛𝐞. The problem: In multi-tenant apps, you're keeping inactive tenant data in expensive hot storage "just in case" they need it. Most of the time, they don't.

If you've ever wondered how vector search engines make similarity search fast, it comes down to smart indexing strategies. Milvus, created by Zilliz offers a variety of indexing methods for you to choose from: 𝐅𝐥𝐚𝐭 (𝐁𝐫𝐮𝐭𝐞-𝐟𝐨𝐫𝐜𝐞): Brute-force scan without index

🐦 Which Milvus are you today? Feeling positive? 😄 Spreading the love? 🫶 Or… just a little annoyed? 😤 At Milvus, we understand vectors — and vibes. Let Milvus lighten your mood and save a dry tech chat! These cute stickers were created by our amazing 𝐌𝐢𝐥𝐯𝐮𝐬