LLamaIndex, Generative Feedback Loops, and Multimodal Embedding Models…

🤗 Hello there!

Welcome to this week's Weaviate newsletter! We have a lot of exciting content to share with you, including deep dives into Weaviate, expert tips and tricks for working with vector data, and the latest advancements in AI and data tech. So sit back, relax, and enjoy reading!

Vector Data Tips, Tricks, and Tech

How-To

• ✍️ Multimodal Embedding Models

  By Zain Hasan

  • Discover ML models that can see, read, hear, and more!

• ✍️ LlamaIndex and Weaviate

  By Jerry Liu, Co-Founder/CEO LlamaIndex

  • Get an introductory overview of LlamaIndex and the LLM framework.

• 📚 10 Best Vector Database for Building LLMs

  By Mohit Pandey

  • Explore the importance of vector databases when building LLMs.

New AI & Data Tech

Podcasts

• 🎙 Aleksa Gordic - Weaviate Podcast #55

  In this episode, delve into Aleksa's incredible journey from Deep Learning YouTube to DeepMind and now creating Ortus! Gain insights into the latest updates on Ortus and Aleksa's perspective on the current state of AI development.

• 🎙 Weaviate Podcast Search meets Generative Feedback Loops

  Join us as we discuss with Aleksa Gordic his vision for the future of video content on YouTube. Discover how Weaviate and Generative Feedback Loops will transform digital content.

• 🎙 LlamaIndex and Weaviate - Episode 1: Data Loading

  This episode demonstrates how to connect your data to LlamaIndex and Weaviate. Walk through three examples of using LlamaIndex's data loaders to read files from a file system, webpage, and Notion, and pipe this data into Weaviate!

• 🎙 Andrei Bondarev on AI tools in Ruby! - Weaviate Podcast #54

  Explore the projects and gain insights into Andrei's experience in software consulting. Learn about using tools like Weaviate and LangChain with Ruby through the clients he has created!

Talks

• 🎤 A gentle introduction to Vector Databases – Zain Hasan, Conf42 Machine Learning 2023 

  Learn about machine learning models, vector embeddings, vector databases, and Weaviate.

• 🎥 Weaviate Air #9 

  Watch the Weaviate Air live stream on YouTube, where we discuss Multi-Tenant Support, the Multimodal Weaviate module, the winners of the Berlin Hackathon, and the HealthSearch Demo.

Elevate Your Knowledge with The Weaviate Academy

Unlock the potential of AI tools with Weaviate Academy and start with the first course, "From Zero to MVP," hosted by JP Hwang.

Gain all the core knowledge and essential skills for building with Weaviate. Learn how to build a Weaviate database, effectively perform queries, and find the right data.

By the end of these short units, you'll be able to build your own instance of Weaviate with your own data and have a suite of search tools available to retrieve data in your desired format.

Units:

1. Hello Weaviate

2. Queries

3. Schema and Imports

4. Queries (2)

Events

Upcoming events

• 🗓️ Weaviate Workshop – July 13, 2023, With Zain Hasan

  Join us in this introductory session to learn about text comprehension in AI language models, vector databases, and their role in scaling AI models. Gain hands-on experience with Python, perform vector searches, utilize Weaviate's generative search, and create a cloud-based vector database.

• 🗓️ Voxel51 (Virtual Event) – July 13, 2023

  Register now and join us for Zain's talk on "Computer Vision Applications at Scale with Vector Databases."

• 🗓️ Weaviate Air #10 – Livestream on YouTube, on Jul 19, 2023, 5 pm CET.

New to Team Weaviate

We have a full house! Let's give a warm welcome to the newest members of Team Weaviate!

• Ara Gonzalez - People & Culture, People Operations Manager

• Emma O'Keefe - Customer Success, Head of Customer Success

• Leonie Monigatti - DevGrowth, Developer Advocate

• Asdine El Hrychy - Applied Research Software Engineer

We're excited to have these talented individuals on board, and we can't wait to achieve great things together!

Thanks for Reading

If you have any questions, feel free to ask them in the Weaviate Forum. Stay tuned for more exciting updates in just two weeks.

Best,

Femke