What are 'Embeddings' and why they are crucial for AI solutions
Embeddings are mathematical representations of objects as vectors in a multidimensional space that capture semantic relationships and similarities. They enable AI systems to understand the meaning and context of data and form the foundation for modern AI applications such as semantic search, recommendation systems, chatbots, and multimodal AI solutions. Through efficient vectorization, embeddings enable scalable, context-aware AI systems that go beyond simple pattern recognition.