Description
Modern Machine Learning (ML) represents everything as vectors, from documents, to videos, to user behavior. This representation makes it possible to accurately search, retrieve, rank, and classify different items by similarity and relevance. Running real-time applications that rely on large numbers of such high dimensional vectors requires a new kind of data infrastructure. In this talk we will discuss the need for such infrastructure, the algorithmic and engineering challenges in working with vector data at scale, and open problems we still have no adequate solutions for. Time permitting, I will introduce Pinecone as a solution to some of these challenges. Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc/ Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. https://databricks.com/databricks-named-leader…
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