Researchers are exploring a new approach to artificial intelligence training where code-driven agents automatically generate and refine mathematical problems to push the boundaries of reasoning capabilities.
Researchers have developed a new framework that enables more robust and versatile control of humanoid robots performing complex, full-body tasks.
A new framework uses competing AI agents and Bayesian optimization to build more reliable and accurate scientific software from natural language prompts.
A new imitation learning framework allows robot swarms to master complex collective behaviors by learning from both human guidance and successful AI strategies.
A new review examines whether current artificial intelligence systems possess genuine uncertainty, or merely simulate it through probabilistic calculations.
A new wave of artificial intelligence and robotics is poised to redefine lunar science and ensure the safety of crewed missions, opening the door to sustainable operations beyond Earth.
A new pedagogical approach leverages generative AI as a ‘difficult partner’ to cultivate critical thinking and AI literacy in mathematics education.
New research explores how large language models can give robots the cognitive abilities to interpret instructions and perform complex tasks in the real world.
A new framework proposes how to design artificial intelligence systems that earn our trust through transparency, alignment, and robust knowledge foundations.
New research demonstrates that robots can significantly improve their task performance by retrieving and understanding visual instructions, opening the door to more adaptable and capable machines.