Neural Search 101 | Algolia

The traditional keyword-based search is evolving with new technologies such as AI, machine learning, natural language processing (NLP), vector search, neural search, and deep learning. These advancements improve the quality of search results by understanding user activities and semantic relationships between words. Vector search uses mathematical representations to understand context, while neural search combines vectors' accuracy with quick performance and self-learning abilities. Deep learning is a subset of machine learning that focuses on how machines can learn using deep neural network computing models. Neural search leverages the power of deep neural networks to build every component of a search system. These advancements are expected to lead to more accurate search results in the future, combining full-text keyword and vector search technologies.