LLM and DALLE Creates Illustrated Book (9.5)

This video explains how embeddings, represented as vectors of floating-point numbers, are used to measure the relatedness between different pieces of data, with smaller distances indicating higher relatedness. The video compares two OpenAI embedding models, "text-embedding-3-small" and "text-embedding-3-large," detailing their differences in performance, accuracy, computational resource requirements, and cost. It provides practical examples of using the smaller model, "text-embedding-3-small," which is recommended for efficient resource usage in this context. The video also demonstrates how to create embeddings, compare them using cosine similarity, and interpret the results through practical examples, such as comparing descriptions of a lawn mower and an airplane.
Code for This Video:
github.com/jef...
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#Embeddings #AI #OpenAI #MachineLearning #TextEmbedding #CosineSimilarity #NLP #DataScience #VectorAnalysis #TechTutorial