Vector Search for Humans: Marqo with Jesse Clark
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Exploring Tensors and Vectors in Machine Learning and Search Technologies
The chapter delves into the terminology and evolution of language in machine learning, emphasizing the shift towards multi-dimensional data representations using tensors and vectors. It explores the adoption of tensor-based models, the concept of embeddings, and the potential for joint representations across different domains like text and vision models. The discussion also highlights the benefits of multimodal search, vector search applications in property risk assessment, and emerging use cases of vector search with generative AI models.
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