Building a Named Entity Recognition Model for the Legal Domain
We defined 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.
Named Entity Recognition in the Legal Domain
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.
Machine Learning through Database Glasses, NeurIPS 2021
This talk explores several techniques to improve the runtime performance of machine learning by taking advantage of the underlying structure of relational data. While most data scientists use relational data in their work, the data science tooling that works with relational data is quite lacking today. Let’s explore these new techniques and see how we can drastically improve machine learning through a database-oriented lens.
AI workloads inside databases, NeurIPS 2021
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.
Deep Learning with Relations, NeurIPS 2021
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.
Your Wit is my Command
Please join us for this fun and exciting talk by Tony Veale. As an associate professor in the School of Computer Science at University College Dublin (UCD), Ireland, he has worked in AI research for three decades, in academia and in industry, with a special emphasis on humor and linguistic creativity.