Part 1: What is a vector embedding? | master vector embeddings with weaviate

What is a Vector Embedding?

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 what is a vector embedding, 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!