Zilliz

Many vector database providers make exaggerated claims, but not all systems are built to handle the demands of modern AI workloads. Discover which features truly matter for scalability, reliability, and performance, and cut through the noise with actionable insights. Download The Definitive Guide to Choosing a Vector Database today. https://bit.ly/4g8AVx9

If you are in Singapore, check out this exciting event with Amazon Web Services (AWS) and Apache Doris. Zilliz's Solutions Architect Ivan Tang will speak about "Zilliz & Vector Databases: Driving Innovation in the Big Data & AI Ecosystem"! 🌟 Sign-up details below 👇

Vector search and advanced language models are reshaping the legal industry, creating new opportunities for engineers and AI specialists. ⚖️ Read the latest article on The New Stack now! https://lnkd.in/gxUdbHJw #LegalTech #AI #VectorSearch #LegalIndustry

🎬 AI is transforming video editing. Are you ready? The rise of short-form content, live streaming, and video-based marketing is driving demand for faster, smarter, and more efficient editing tools. AI-powered solutions like semantic search, automated editing assistance, and real-time collaboration are changing the game. 🔍 Forget manual tagging. AI can find clips based on descriptions like “sunset beach scene”—no need to scrub through hours of footage. 🎞️ Faster workflows. AI suggests edits, detects objects, and even generates subtitles in real time. 🤖 Smarter storytelling. AI-driven recommendations help editors find the perfect assets quickly. The future of video editing isn’t just automation—it’s creativity without limits. 🚀 https://lnkd.in/giCBGJQq #AI #VideoEditing #SemanticSearch #MachineLearning #Filmmaking

I am excited to announce the first SF Unstructured Data Meetup of 2025! Join us on Wednesday, February 26 at the Amazon Web Services (AWS) GenAI Loft, an exciting new location 👏 🗣️ 3 fun talks to kick off our series: ‣ Combining Lexical and Semantic Search with Milvus 2.5 by myself ‣ Bedrock Data Automation (Preview): Simplifying Unstructured Data Processing by Arnab Sinha and Jean Malha ‣ Talk 3 by Hasura.io Plus: Office hours with the Milvus team, networking opportunities, and food provided! Thank you @ AWS for the support! 🤝 #zilliz #milvus #aws #genai #meetup

𝐇𝐨𝐰 𝐅𝐀𝐕𝐀 𝐃𝐞𝐭𝐞𝐜𝐭𝐬 𝐚𝐧𝐝 𝐂𝐨𝐫𝐫𝐞𝐜𝐭𝐬 𝐇𝐚𝐥𝐥𝐮𝐜𝐢𝐧𝐚𝐭𝐢𝐨𝐧𝐬 🔍 Detecting and correcting hallucinations in AI outputs requires both identifying errors and verifying claims using reliable external evidence. 𝐅𝐀𝐕𝐀 (Fact Verification and Augmentation) employs a two-step process combining retrieval and editing to handle a wide range of hallucination types effectively. The model's training on a diverse dataset of synthetic errors plays a key role in its capabilities. 🤖 Learn more: https://lnkd.in/gvAehFWE #AI #Innovation #MachineLearning #TechNews #ArtificialIntelligence

Watch the video to learn the typical path of using lexical search 🔎

🔍 Want to build smarter search that understands both images AND text? Join Stefan Webb from Zilliz as he shows you how to create a multimodal search application using open source tools including Milvus, Hugging Face models, and PyTorch. Watch the full video now 📺 👉 https://go.aws/4aQuIEL In this step-by-step tutorial, you'll learn: • How to combine image and text search • Building a vector database for search • Using AI to improve search accuracy • Implementing reranking with Large Language Vision Models 🛠️ Best part? It's all using open source tools! #AWS #OpenSource

🔍 Join us LIVE this Thursday, Feb 6 to discover how to build advanced AI agents with multimodal capabilities! Learn to leverage FriendliAI's solutions and Milvus DB to create agents that understand both text and vision. Soomin Chun from FriendliAI will demonstrate the complete developer workflow - from fine-tuning models to production deployment, with a focus on implementing multimodal RAG for enhanced AI interactions. Save Your Spot: https://lnkd.in/g_JqNyV4 #Vectordatabase #Milvus #Agents #RAG

Hear from Arnab and Jean from AWS Bedrock on February 26. Details and reg below 👇