Science

A new study reveals that the method used to retrieve information within Azure AI Search dramatically affects the quality of AI-powered responses.

A new approach leverages data-driven learning and transformer networks to improve the accuracy of robot dynamic models, enhancing real-world performance.

Integrating artificial intelligence with computer-aided design is transforming how we plan and build essential water and power systems, particularly in challenging environments.

Researchers have developed a new framework allowing robotic arms to physically interact with smartphones, bypassing traditional software-based control methods.

This review offers a comprehensive, engineering-focused approach to designing, deploying, and maintaining robust agentic AI systems in real-world applications.

This review explores how deep neural networks are transforming the fields of reinforcement and imitation learning, enabling agents to learn complex behaviors from experience and demonstration.

New research reveals that providing explanations for artificial intelligence recommendations in medical diagnoses doesn’t always improve decision-making, and can actually decrease accuracy when the AI is wrong.

Researchers have developed an open-source tactile glove that allows robots to ‘feel’ objects, significantly improving their ability to perform delicate manipulation tasks.

New research reveals that simply increasing the number of AI agents doesn’t guarantee improved performance, and highlights the crucial role of task design and coordination.

New research demonstrates how robots can leverage audio cues to better understand and predict the physical world, leading to more robust manipulation skills.