Filter Options
Date
Image
The MIT researchers developed an AI-powered simulator that generates unlimited, diverse, and realistic training data for robots. The team found that robots trained in this virtual environment called “LucidSim” can seamlessly transfer their skills to the real world, performing at expert levels without additional fine-tuning (Credit: Mike Grimmett/MIT CSAIL).
CSAIL article

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.