Science

Researchers have developed a deep learning framework capable of accurately modeling diverse physical systems governed by different partial differential equations.

New research demonstrates a method for rapidly teaching robots diverse manipulation skills with minimal training data.

A new system harnesses the power of artificial intelligence to build and execute complex network measurement studies, lowering the barriers to in-depth internet analysis.

Researchers have developed an untethered, shape-morphing robot capable of seamlessly transitioning between land, underwater, and surface locomotion with improved energy efficiency.

A new unsupervised approach uses artificial intelligence to analyze stellar spectra and reveal the chemical composition of stars without relying on pre-labeled data.

Researchers have developed a reinforcement learning system that allows bipedal robots to execute controlled falls, prioritizing both safety and aesthetic pose achievement.

A new robotic system demonstrates the potential for automated assistance in overhead construction tasks, paving the way for safer and more efficient building practices.

Researchers have developed a novel framework that allows agents to independently generate challenges, learn from experience, and refine their capabilities without constant human oversight.

Researchers have developed a novel humanoid robot leg leveraging decoupled actuation to achieve more natural and rapid locomotion.

Researchers propose an Intelligent Foundation Model that learns by replicating the temporal dynamics of the brain, offering a potential leap beyond current AI limitations.