Guy Van den Broeck, Alexander Ratner, Benjamin Moseley, Konstantinos Karanasos, Parisa Kordjamshidi, Molham Aref, Arun Kumar
02 February 2022
less than a minute read
Watch the full panel discussion here
This incredible panel of experts gathered to discuss the current state of AI and machine learning workloads inside databases. The panel discussed new techniques, technologies, and recent papers that progress our understanding of what is possible. Q&A among the panel and from the audience concludes this deep and wide ranging conversation.
We defined named entity recognition (NER) in the legal domain and presented our approach towards generating ground truth data. In what follows, we go over the state-of-the-art in the NER domain and elaborate on the experiments we ran and the lessons we learned.Read More
Named entity recognition is a difficult challenge to solve, particularly in the legal domain. Extracting ground truth labels from long, hierarchical documents is often slow and prone to error. RelationalAI proposes a new, scalable algorithm based on the principles of data-centric AI, designed to meet this challenge and generate high-quality annotations with minimal supervision.Read More
Molham shares some history of relational databases, trends in modern cloud-native database systems, and the innovations pioneered at RelationalAI to bring deep learning with relations from idea to reality.Read More