Vector Similarity Search Hides in Plain View

Artificial intelligence (AI) has the potential to revolutionize various industries and tasks. One example is race timing, where AI can replace traditional chip timers with video cameras and machine learning algorithms. This technology, known as vector similarity search, involves converting unstructured data into feature vectors using neural networks, then calculating similarities between these vectors. Vector similarity search has applications in e-commerce, security, recommendation engines, chatbots, image or video search, and chemical similarity search. Open-source software like Milvus and publicly available datasets make AI more accessible to developers and businesses.