In 2007, Professor Fei-Fei Li started assembling a massive dataset of 14 million pictures, labeled with the objects that appeared in those images. This dataset, dubbed ImageNet, spurred dramatic progress over the next decade in computer vision, the field of artificial intelligence that trains computers to understand images and videos. Such datasets can serve as “benchmark” challenges that researchers compete on, and incentivize advancements in fundamental and domain-specific fields.

We sent solicited ideas for a potential dataset that could drive a similarly transformative impact in education. Applicants submitted 300 word abstracts, as we selected a few to showcase.

Please use this time to listen to the recordings at the bottom of the schedule to learn more about the benchmark data set ideas.