Ai-Powered Search: Understanding Unstructured Data
Data is growing exponentially, and to find and utilize relevant data, it is necessary to search for it. However, most of the generated data is unstructured and doesn't follow conventional data models, making it difficult to store and manage. Vector Search is a method of information retrieval in which unstructured data is represented as vectors, and Machine Learning models allow a meaningful vector representation of the data.
In this talk, we will discuss the challenges associated with working with unstructured data and the importance of gaining insights from it. We will delve into Vector Search, covering concepts ranging from Machine Learning and Foundation Models to Image Similarity Search, Multimodal Search, and Semantic Search. By the end of this talk, you will not only recognize the importance and challenges of working with unstructured data but also learn how to effectively utilize various Machine Learning models and retrieval methods to take advantage of it.