Key Takeaways Embeddings convert intricate, high-dimensional data into simplified, lower-dimensional vectors, allowing AI systems to efficiently process and analyze information. These vector representations maintain important relationships in the input data, enabling models to capture meaning, context, and similarity between entities. Both static and contextual embedding models have their strengths. Selecting the appropriate one depends on your objectives and your […]
