Milvus

Introducing Milvus 2.5 with built-in full-text search capabilities and more! 🔍 Here’s the TLDR on new updates: 🔎 Built-in full-text search with Sparse-BM25 💬 Advanced text matching using Tantivy's analyzers & Indexing 🏃 New Bitmap indexing for faster filtering + More! #Milvus #Launch #Vectordatabase #Search #HybridSearch #FullText #ML #AI Learn More: [Links in comments]

📊 Learn how we're teaching AI to better understand tabular data! Full video: https://lnkd.in/gfG5vrPG #ArtificialIntelligence #MachineLearning #DataScience #AI

So grateful to folks stopping by our booth at NVIDIA GTC. Enjoyed talking to everyone of you! Thanks to Amazon Web Services (AWS) GenAI competency team Victor Rojo for hosting us there. Go Milvus! 🐦

𝐌𝐢𝐥𝐯𝐮𝐬 𝐢𝐬 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞𝐝 𝐢𝐧𝐭𝐨 𝐋𝐥𝐚𝐦𝐚 𝐒𝐭𝐚𝐜𝐤! 𝐋𝐥𝐚𝐦𝐚 𝐒𝐭𝐚𝐜𝐤 (introduced by AI at Meta) is a service-oriented, API-first framework designed to standardize core building blocks for bringing generative AI applications to market, offering unified APIs for Inference, RAG, Agents, Tools, and more. 🤗 By integrating 𝐌𝐢𝐥𝐯𝐮𝐬 with Llama Stack, we enable efficient vector storage and retrieval for AI models, enhancing the performance of 𝐑𝐀𝐆 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬. This integration allows you to quickly set up, manage, and scale your AI solutions in any environment, empowering developers to achieve more with ease. 📚 https://lnkd.in/gERegqtW

🔴 LIVE NOW! If you can't attend our SF #UnstructuredData workshop with Milvus and OpenAI in person, it's streaming now on YouTube! https://lnkd.in/guaFSCpN #LIVE #YouTubeStream #Meetup #SanFrancisco

🐦 Follow Dave the Datum’s life to learn Milvus’s distributed architecture and more in this week’s newsletter! 🔧 Why manual sharding in vector databases is a costly mistake 👣 Day in the Life of a Milvus datum 💡 Integrate Anthropic MCP with Milvus 📅 Upcoming webinars you won’t want to miss! #AINewsletter #Vectordatabase #Milvus #MCP 

🧑🍳 𝐒𝐭𝐞𝐩 𝐢𝐧𝐭𝐨 𝐭𝐡𝐞 𝐦𝐚𝐠𝐢𝐜𝐚𝐥 𝐤𝐢𝐭𝐜𝐡𝐞𝐧 𝐨𝐟 𝐨𝐩𝐞𝐧-𝐬𝐨𝐮𝐫𝐜𝐞 𝐦𝐨𝐝𝐞𝐥𝐬! This cookbook shows how to whip up a RAG pipeline using the finest ingredients—Hugging Face 𝐦𝐨𝐝𝐞𝐥𝐬 and 𝐌𝐢𝐥𝐯𝐮𝐬 (no master chef skills required! 😉) ✅ Parse documents, generate vectors with open-source embedding models and store them in Milvus. ✅ Leverage popular open-source LLMs like Mixtral-8x7B on Hugging Face. ✅ Build an end-to-end RAG system that retrieves context and generates human-friendly answers. 👥 Tag an AI developer friend who might find this useful! 👉 https://lnkd.in/gkbwH2kE

🎉 💻 Happening Tonight! Exciting workshop with OpenAI and Milvus. If you can't in person, we'll be streaming it on YouTube! Bring your laptops and follow along. YouTube: https://lnkd.in/guaFSCpN In-person: https://lu.ma/ncr07fnd #LIVE #YouTubeStream #Meetup #SanFrancisco

We’re always talking about RAG, but how much does adopting a RAG-based solution cost? 💰 🤑 OpenAI’s text-embedding-3-large might yield better results but is expensive. 📈 Read about the components of RAG costs and calculate your own: https://lnkd.in/d8w7eJu9 #RAG #OpenAI #AI

Building a performant #vectordatabase like #milvus that scales to billions of vectors and handles web-scale traffic is no simple feat. It requires the careful, intelligent design of a distributed system. In our latest blog post, we delve into Milvus internals: ⚙️ Understand the design of Milvus Distributed at a high-level, including concepts like data nodes, index nodes, shards, partitions, and segments. ⚡️ Make more informed deployment decisions and debug corner-case performance issues. 🦸♂️ More generally, become a Milvus hero who is able to scale to billions of vectors with ease! 🔗 https://lnkd.in/gHkPbWTX