For roboticists, one challenge towers above all others: generalization – the ability to create machines that can adapt to any environment or condition. Since the 1970s, the field has evolved from writing sophisticated programs to using deep learning, teaching robots to learn directly from human behavior. But a critical bottleneck remains: data quality. To improve, robots need to encounter scenarios that push the boundaries of their capabilities, operating at the edge of their mastery.
This publication explores how these new technologies will transform the way we build database management software, creating new systems that can ingest, store, process, and query all data.
When Nikola Tesla predicted we’d have handheld phones that could display videos, photographs, and more, his musings seemed like a distant dream. Nearly 100 years later, smartphones are like an extra appendage for many of us.
Earlier this month, electrical engineering and computer science researchers from around the world came together at MIT for the twelfth annual Rising Stars Workshop. The event welcomed graduate students and postdocs of historically underrepresented genders who are interested in pursuing academic careers in the field.
