Science

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.

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.

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

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.

New research explores how to move large language models past simply completing patterns and towards genuine logical reasoning abilities.

This review explores the rapidly evolving intersection of generative artificial intelligence and self-adaptive systems, examining the potential to create more robust and responsive technologies.

Researchers have developed a new simulation framework to accurately model and optimize the movement of snake robots across challenging and deformable surfaces.

The question isn’t whether machines can perform qualitative analysis, but how a collaborative human-AI system can best approximate rigorous research and where the inherent limitations lie.

New research demonstrates a method for improving robot manipulation by merging learned visuomotor policies with pre-defined movement primitives, enabling more robust and adaptable performance.