Science

As artificial intelligence rapidly advances, a critical debate emerges about who-or what-will ultimately be in control.

New research shows that effectively coordinating multiple robots in a warehouse setting requires more than just individual intelligence, and a specific reinforcement learning approach is leading the way.

A new approach to AI education prioritizes accessibility and broad understanding over technical skill, empowering students from all disciplines.

A new framework combines tools from computational mechanics and diffusion modeling to provide a deeper understanding of how complex systems evolve.

Researchers are tackling the data bottleneck in robotics by creatively transforming existing human video footage into synthetic humanoid data for training more robust AI systems.

New research explores the potential of AI-powered vision-language-action models to automate the complex process of extracting valuable components from e-waste.

A new perspective argues that truly ethical multi-agent AI systems require understanding the underlying computational causes of harmful emergent behaviors, not just observing them.

Researchers have developed a novel data collection method that enables robots to generalize their manipulation skills to new environments more effectively.

New research reveals that smaller AI models, empowered by intelligent agent frameworks, can rival the performance of their larger counterparts in automating complex hardware design tasks.

New research explores how equipping AI agents with distinct personas dramatically improves their ability to generate diverse and impactful ideas when collaborating on complex problems.