This CoR brings together researchers at CSAIL working across a broad swath of application domains. Within these lie novel and challenging machine learning problems serving science, social science and computer science.
This community is interested in understanding and affecting the interaction between computing systems and society through engineering, computer science and public policy research, education, and public engagement.
All humans process vast quantities of unannotated speech and manage to learn phonetic inventories, word boundaries, etc., and can use these abilities to acquire new word. Why can't ASR technology have similar capabilities? Our goal in this research project is to build speech technology using unannotated speech corpora.
Our goal is to build a system that predicts where people are looking in images. Given an image and the location of a head, our approach follows the gaze of the person and identifies the object being looked at.
A new MIT study finds “health knowledge graphs,” which show relationships between symptoms and diseases and are intended to help with clinical diagnosis, can fall short for certain conditions and patient populations. The results also suggest ways to boost their performance.
Google AI’s Jeff Dean has a seemingly straightforward objective: he wants to use a collection of trainable mathematical units organized in layers to solve complicated tasks that will ultimately benefit many parts of society.