At the Institute, while each School certainly has its own character and researchers’ work is highly specialized, there is nonetheless a sense of common purpose and shared environment. We inhabit the same space—the same woods—and not just in the literal sense. We share the experience of bewilderment, and the perpetual yearning for clarity.

"It's kind of like physics in its formative stages—Newton asking what makes the apple fall down," says Sanjeev Arora. "Thousands of years went by before science realized it was even a question worth asking. An analogous question in machine learning is 'What makes a bunch of pixels a picture of a pedestrian?' Machines are approaching human capabilities in such tasks, but we lack basic mathematical understanding of how and why they work."