Part 1: Master Vector Embeddings with Weaviate

Introduction to Vector Embeddings

Vector embeddings are a cornerstone of modern artificial intelligence, transforming complex, abstract data into numerical representations that machines can process and understand. This Part 1 webinar of the community series with Weaviate provides a beginner-friendly introduction to vector embeddings, breaking down key concepts and showcasing practical applications.

Explore how embeddings have revolutionized AI, from the groundbreaking 2013 Word2Vec paper to modern embedding models used in real-world scenarios. Through demonstrations and discussions, gain a clear understanding of how to create, evaluate, and select embedding models for your applications.

What we will cover:

• Learn why the 2013 Word2Vec paper was a pivotal moment in AI and how it introduced the concept of embedding meaning with numbers.
• Gain a high-level overview of how modern embedding models work and their various use cases.
• Create vector embeddings in Weaviate using an embedding service, API (OpenAI), and open source models through Huggingface. 
• Learn the factors to consider when choosing an embedding model, including model size, open-source availability, industry relevance, and application type.
• Discover why selecting and implementing the right embedding model is both critical and complex, and explore the key considerations for success.

Want to join Part 2 of the series? Find it here!