no code implementations • 11 Oct 2023 • Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan Greenewald, Brian Belgodere, Mikhail Yurochkin, Jiri Navratil, Igor Melnyk, Jerret Ross
Using this framework, we formally develop a risk-aware approach for foundation model selection given guardrails quantified by specified metrics.
no code implementations • 21 Apr 2023 • Brian Belgodere, Pierre Dognin, Adam Ivankay, Igor Melnyk, Youssef Mroueh, Aleksandra Mojsilovic, Jiri Navratil, Apoorva Nitsure, Inkit Padhi, Mattia Rigotti, Jerret Ross, Yair Schiff, Radhika Vedpathak, Richard A. Young
We introduce a holistic auditing framework that comprehensively evaluates synthetic datasets and AI models.
no code implementations • 23 Feb 2023 • Prabhakar Kudva, Rajesh Bordawekar, Apoorva Nitsure
AI-Powered database (AI-DB) is a novel relational database system that uses a self-supervised neural network, database embedding, to enable semantic SQL queries on relational tables.
no code implementations • 19 May 2020 • Apoorva Nitsure, Rajesh Bordawekar, Jose Neves
This paper demonstrates the use of the AI-Powered Database (AI-DB) in identifying non-obvious patterns in crime data that could serve as an aid to predictive policing measures.