The University of Massachusetts Amherst
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Mrinmaya Sachan - Towards Literate Artificial Intelligence

Data Science Seminar
Tuesday, April 9, 2019 - 4:00pm
Computer Science Building, Room 150/151

Reception for attendees will be held in CS 150 at 3:30 p.m.



Over the past decade, the field of artificial intelligence (AI) has seen striking developments. Yet, today’s AI systems sorely lack the essence of human intelligence i.e. our ability to (a) understand language and grasp its meaning, (b) assimilate common-sense background knowledge of the world, and (c) draw inferences and perform reasoning. Before we even begin to build AI systems that possess the aforementioned human abilities, we must ask an even more fundamental question: How would we even evaluate an AI system on the aforementioned abilities? In this talk, I will argue that we can evaluate our AI systems in the same way as we evaluate our children - by giving them standardized tests. Standardized tests are regularly administered to students to evaluate the knowledge and the skills gained by them as they progress though the formal education system. Thus, it is a natural proposition to use these tests to measure the intelligence of our AI systems as well. Then, I will describe Parsing to Programs (P2P), a framework that combines ideas from semantic parsing and probabilistic programming for situated question answering. We used the P2P framework to build two systems that can solve pre-university level Euclidean geometry and Newtonian physics examinations. P2P achieves a performance at least as well as the average student on questions from textbooks, geometry questions from previous SAT exams, and mechanics questions from Advanced Placement (AP) exams. I will conclude by describing implications of this research and some ideas for future work.



Mrinmaya is a PhD candidate in the Machine Learning Department, School of Computer Science at Carnegie Mellon University. Mrinmaya focuses on building automated solver for standardized tests such as the SAT and the advanced placement tests. He is also interested in using these solvers as assistive technologies that can teach students. Mrinmaya spent his undergrad years at Indian Institute of Technology (IIT), Kanpur, where he graduated with a B.Tech in Computer Science and Engineering. He worked with the Information Management group at IBM Research India.