Join Stephen Batifol on April 10th for a talk about using LLM Agent to chat with the Berlin Parliament 🗣️. He will talk about: ➡️ How to build an LLM Agent that works with Open-Data from the Berlin Parliament using Milvus and interact with them. ➡️ The power of specialized embeddings by comparing different ones. See you at Thoughtworks in Berlin on April 10th! 💫 https://bit.ly/3vBwHNb
Zilliz
Software Development
Redwood City, CA 7,722 followers
vector database trailblazer and creator of Milvus, the world's most widely-adopted open source vector database.
About us
Zilliz is a leading vector database company for enterprise-grade AI. Founded by the engineers behind Milvus, the world's most widely-adopted open-source vector database, the company builds next-generation database technologies to help organizations create AI applications at ease. On a mission to democratize AI, Zilliz is committed to simplifying data management for AI applications and making vector databases accessible to every organization.
- Website
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https://zilliz.com
External link for Zilliz
- Industry
- Software Development
- Company size
- 51-200 employees
- Headquarters
- Redwood City, CA
- Type
- Privately Held
- Founded
- 2017
- Specialties
- database, artificialintelligence, unstructureddata, machinlearning, similaritysearch, vectordatabase, and distributedsystem
Locations
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Primary
Redwood City, CA 94065, US
Employees at Zilliz
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Christy Bergman
AI Developer Advocate @ Zilliz | OSS MIlvus Vector Database, Unstructured Data
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Emily Kurze
Director of Marketing | Zilliz (creators of Milvus, world's most popular open-source vector database)
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Frank Liu
Director of Operations, Head of AI & ML @ Zilliz
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谢宇
Principal Engineer
Updates
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Join Christy Bergman for a #RAG mashup! She will speak about and demo RAG best practices using Milvus, Zilliz, embedding models and LLMs with or without OpenAI, and #RAGeval using Ragas at the SFBayACM Meetup on April 24th at Hackerdojo. https://bit.ly/3xoJbbx
RAG using Milvus, HuggingFace, LangChain, Ragas, with or without OpenAI, Wed, Apr 24, 2024, 6:45 PM | Meetup
meetup.com
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Explore insights from Charles, CEO of Zilliz, as he delves into the current landscape and future trajectory of vector database systems in his blog series. 🔮 #VectorDatabases #AI #DataScience https://bit.ly/3xvTOZU
The Evolution and Future of Vector Databases: Insights from Charles, CEO of Zilliz - Zilliz blog
zilliz.com
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You've heard of vector search, but do you know what's going on under the hood? There are three main similarity metrics to compare vectors: Euclidean distance, Inner product, and Cosine similarity. Each of these measures something different. Euclidean distance measures distance in space. Cosine similarity measures the angle difference. Inner product measures both. Learn more here: https://bit.ly/3xiE4cG.
Similarity Metrics for Vector Search - Zilliz blog
zilliz.com
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Zilliz reposted this
Welcome to the first edition of Milvus Newsletter! This issue summarizes the notes from Milvus’s latest release: Milvus 2.4. Read the documentation, check out our code examples, and watch a quick video on groupby search with a Snoopy example 🐶💪
Learn how Milvus 2.4 Enhances Search Capabilities and More!
The Milvus Project on LinkedIn
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Dig into multimodal embeddings with Zilliz's Yujian Tang and Voxel51's Jacob Marks this Wednesday at 9AM PT/12PM ET. Details below 👇
ML @ Voxel51 | Formerly Google X, Wolfram Research | Stanford Theoretical Physics Ph.D. | Open Source
2️⃣0️⃣2️⃣4️⃣ 🟰🟰 👀📚🔈 2024 is the year of MULTIMODAL If you want to learn how to leverage multimodal embeddings to dive deeper into your data, you NEED to come to the free webinar Yujian Tang and I are running this Wednesday at 9AM PT / 12PM ET. We'll be using OpenAI's CLIP model, Zilliz's The Milvus Project, and Voxel51's FiftyOne! #ml #ai #computervision #multimodal #datacentricai #vectorsearch #vectordb https://lu.ma/nnnwcmbw
Exploring and Understanding Multimodal Embeddings · Luma
lu.ma
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Thank you to everyone who attended Zilliz’s first South Bay Unstructured Data meetup in Sunnyvale last week! 💯 Thank you Yi Wang, Jay R., and Tengyu Ma for speaking at this event. In case you missed it, here are the key highlights: ▶️ Yi introduced Milvus and gave insight into the latest features in Milvus 2.4. ▶️ Jay walked us through RAG on NVIDIA RTX using TensorRT-LLM, Milvus, and LlamaIndex. ▶️ Tengyu introduced Voyage AI embedding models for code retrieval tasks. 🔽 Slides and upcoming meetups are in the comments below! #UnstructuredData #GenerativeLLMs #SiliconValleyMeetup
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🗣️ Make your voice heard by participating in Airbyte State of Data & AI 2024 survey! Airbyte will donate $5 to one of two charities at the end. Click the link to take the vendor-agnostic survey about the everyday tools you use: https://bit.ly/3P3ToA7 #AI #DataScience
State of Data & AI 2024 Survey
docs.google.com
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While LLMs are trained on large amounts of data, they're not trained on YOUR data ... and that's where RAG comes in. Laurie Voss shares how you can revolutionize your data processing with RAG in this on-demand webinar: https://bit.ly/3IxEQoz #RAG #Zilliz #VectorDatabase
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Information Retrieval (IR) systems are designed to traverse extensive, dense datasets using relevant input queries. Some popular basic IR metrics include: • Precision@k • Recall@k • F1-Score@k Popular ranking metrics include: • MAP (Mean Average Precision) • NDCG (Normalized Discounted Cumulative Gain) Take a deeper dive into IR metrics and learn how to apply them to evaluate your systems: https://bit.ly/43oBFsV #Zilliz #VectorDatabase
Information Retrieval Metrics - Zilliz Vector database blog
zilliz.com