We're a team of engineers and researchers with diverse backgrounds collaborating to solve some of the toughest problems in AI research.
Common Sense integrates machine reading and reasoning, natural language understanding, computer vision, and crowdsourcing techniques to create a new extensive, foundational common sense knowledge source for future AI systems to build upon.
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.
PRIOR is a computer vision research team within the Allen Institute for Artificial Intelligence. PRIOR seeks to advance computer vision to create AI systems that see, explore, learn, and reason about the world.
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 & algorithms, and support the open source AllenNLP deep learning platform.
The incubator combines AI2's world class engineering and research organization with proven business leaders to bring innovative, AI powered ideas to life.