Make Real-time AI a Reality with Weaviate + Confluent
Hello Weaviate friends, 🤗
Welcome to the latest edition of the Weaviate Newsletter, with valuable updates, tutorials, demos, and noteworthy highlights.
One significant announcement we're excited to share is the integration of Weaviate with Confluent Cloud. This integration opens up new possibilities and opportunities for your business.
Let's dive right into the latest updates.
Weaviate + Confluent
Weaviate's integration with Confluent Cloud gives users simple access to data streams from across their entire business to build a real-time, contextual, and trustworthy knowledge base fueling their AI applications.
With easy access to data streams from across their entire business, Weaviate users can now:
Create a real-time knowledge base: Build a shared source of real-time truth for all your operational and analytical data, no matter where it lives for sophisticated model building and fine-tuning. Think business competitive analysis dashboards that are updated with latest market news updates.
Bring real-time context at query time: Convert raw data into meaningful chunks with real-time enrichment and continually update your embedding databases for your GenAI use cases. Think real-time filtering based on region, demographics, personas in online shopping, etc.
Build governed, secured, and trusted AI: Establish data lineage, quality and traceability, providing all your teams with a clear understanding of data origin, movement, transformations and usage.
Experiment, scale and innovate faster: Reduce innovation friction as new AI apps and models become available. Decouple data from your data science tools and production AI apps to test and build faster.
Learn how to build an application using Weaviate and Confluent:
Vector Data Tips, Tricks, and Tech
The details behind how you can compress vectors using PQ with little loss of recall.
Erika covers four query engines implemented in LlamaIndex. Explaining each concept, then jumping into a demo notebook of each query engine.
Learn how to leverage the power of AI through Semantic Search to query a dataset of books, producing recommendations based on user inputs.
Newest AI & Data Technology Developments
We appreciate those who tuned in to this episode featuring a special guest, Richards Liskovkis, the 🏆 2nd place winner in the SuperAGI Autonomous Agents Hackathon—furthermore, updates about Python client updates, Hacktoberfest, Community events, and more.
New Unit: Weaviate Academy
In This Unit:
Learn how Weaviate organizes and stores data.
Explore the role of indexes in Weaviate for efficient searches.
Define data schemas and properties with appropriate data types.
Discover how to populate Weaviate with data, including best practices like batch imports.
You'll be equipped to structure and populate your Weaviate instance effectively by the end.
Weaviate Company Trip 2023
We’re preparing for our second company trip, this time to the beautiful country of Croatia. ☀️
With our team now boasting 50 members scattered across the globe, from Europe to the U.S., South America, and Australia, this trip is a momentous occasion that will bring us all together under the Croatian sun.
In our commitment to a remote-first work structure, we recognize the irreplaceable value of in-person connections. This workation is about fun, forging stronger bonds, intensifying collaboration, and brainstorming ideas.
Your support means the world to us as we continue to evolve and grow as a company. 🌍🇭🇷
Curious about our first Company Trip? Read the blog here.
Welcoming New Faces
Meet Jenna Zarum, our new Chief of Staff.
Thank for Reading
Do you have questions about Weaviate, vector databases, documentation, or other topics? Feel free to explore the Weaviate Forum, where you can engage in community conversations. Looking forward to your participation over the next two weeks!