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OpenAI’s New Embedding Model: A Game-Changer
OpenAI has just unveiled text-embedding-ada-002, a state-of-the-art embedding model that brings together the capabilities of 5 earlier models for text search, text similarity, and code search.
So what?
This new model outperforms the previous most powerful model, Davinci, in most cases. Not only that, it’s also much more cost-effective with a 99.8% lower pricing. Plus, it’s easier to use, making it a more convenient option for users.
So, what exactly are embeddings and how do they work?
Embeddings are numerical representations of concepts that allow computers to understand the relationships between those concepts.
They’re often used in tasks such as recommendation, searching, clustering, anomaly detection, classification, and diversity measurement. Here’s the techie bit: embeddings are made of vectors of real or complex integers with floating-point arithmetic, and the distance between 2 vectors indicates the strength of their relationship. In general, closer distances indicate a stronger connection, while farther distances point towards a weaker one.
