LlamaIndex now integrates with Zilliz Cloud Pipelines, Learn about Vector Databases, Open Source Advent Winners, New contest, and Events
In this issue:?
LlamaIndex ?? Zilliz Cloud Pipelines
In our last issue, we introduced Zilliz Cloud Pipelines, a one-stop solution designed to simplify and streamline the transformation of unstructured data into optimized vector embeddings.
With a simple API call, you can…?
You can now use Zilliz Cloud Pipelines as a managed index in LlamaIndex! Here is the demo showing how: Managed Index with Zilliz Cloud Pipelines - LlamaIndex ?? 0.9.27?
?? And the Open Source Advent winners are…?
??1st place: Micha?l Romagné
??2nd place: Agung Sidharta So
??3rd place: Siddharth Sahu?
Thank you for participating in Open Source Advent last month! We introduced a new open-source project for 24 days leading up to Christmas. We hope you enjoyed contributing to new projects and learned something new.?
?? Win a $25 Amazon Gift Card
Whether you use open source Milvus or you’re a valued Zilliz Cloud customer, we’d love it if you shared your experience with others through a review on G2! As a token of our thanks, we are sending a $25 Amazon gift card to the first 50 published Zilliz reviews. Milvus users that get their review published will be entered to win one of five gift cards.
?? Vector Database 101?
Vector databases experienced a flood of interest in 2023. They play a critical role in the most popular LLM application: chatbots. Did you know that is only a small portion of what vector databases can be used for though? They can also be used for product recommendations, chemical analysis, reverse image search, and more.
Why? Because the primary use case of vector databases is to allow you to work with unstructured data.?
Learn about vector databases through these resources:?
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Upcoming Events?
Jan 25: Tutorial: Diving into Text Embedding Models (virtual)?
Frank Liu will be diving into the theory behind long-form text embeddings in a short presentation and then he will give a tutorial on utilizing the "sentence-transformers" library in an actual application.?
Register here.
Jan 30-31: Epic AI Dev Summit (virtual)?
Yujian Tang will be speaking at Epic AI Dev Summit, a 2-day online conference! This conference is great for AI developers, data scientists, engineers, CTOs and tech team leads to learn how to introduce the newest technologies to your work.
Get tickets here!
Feb 1: Delivering the Most Performant Vector Search with Zilliz Cloud Webinar (online)
Xiaofan(James) Luan , VP of Engineering at Zilliz, will explore the latest enhancements in Zilliz Cloud, the most performant managed vector database built atop open-source Milvus. Tailored for developers and technical professionals, this session will delve into the forefront of vector database innovation. This webinar is a must-attend for developers and AI professionals looking to deepen their understanding of vector database trends and advancements.
Reserve your spot today and be part of the future of vector database technology!
Feb 15: Build Better Multimodal RAG Pipelines with FiftyOne, LlamaIndex, and Milvus Webinar (online)
Jacob Marks will be sharing how to compare and evaluate multimodal retrieval techniques so that you can build a highly performant multimodal RAG pipeline with your data. The data-centric application we will be using is entirely free and open source, leveraging FiftyOne for data management and visualization, Milvus as a vector store, and LlamaIndex for LLM orchestration.?
Register here.
Feb 20: Unstructured Data Meetup San Francisco (in-person)
Our February Unstructured Data Meetup in San Francisco will be at GitHub again and will have talks from Open AI, Arize, and a contributor to ANN-Benchmarks! Come by to learn about LLM System Evaluations and Observability from Jason Lopatecki , the CEO of Arize, and more.?
This event is co-sponsored by Zilliz and Arize.
Save your spot by registering here!
?? Join our community on Discord!?
Be the first to know about live events, contests, and more by joining our growing community on Discord! Join us here
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