We're a team of engineers and researchers with diverse backgrounds collaborating to solve some of the toughest problems in AI research.
Aristo brings together machine reading and NLP, textual entailment and inference, reasoning with uncertainty, statistical techniques over large corpora, and diagram understanding to develop the first "knowledgeable machine" about science.
With over 100 million scientific research papers in print, and millions added each year, researchers are swamped. We are leveraging our capabilities in NLP, data mining, and computer vision to build a novel literature search experience that will help scientists discover and home in on research papers more efficiently than ever.
Project Plato is focused on extracting visual knowledge from images and videos to enrich knowledge bases that are conventionally derived from textual resources.
Euclid extends Question-Answering methods to multiple-choice math & geometry problems in standardized tests like the SAT. Geometry problems require us to combine text & diagram understanding in a novel manner.
The AllenNLP team is developing next generation, open domain language understanding models. We focus on both data amp; algorithms, and support the open source AllenNLP deep learning platform.