Welcome to the registration form for the 12th Annual NEURAL Conference, which will take place in person on June 24-26, 2026, at the University of Alabama at Birmingham (UAB). Any questions regarding ...

The $368 million network of instruments collecting data in both the Atlantic and Pacific has been critical to climate and ocean research. By Eric Niiler The Trump administration is dismantling a $368 ...

A startup around-the-clock radio news network will make its debut with four experienced voices from CBS News Radio. Worldwide News Network is a 24-hour national radio news service that is slated to ...

The financial ecosystem of 2026 has definitively transitioned from a phase of speculative exploration to one of rigorous institutionalization. Stablecoins, once viewed through the lens of ...

Abstract: This article focuses on the application issue of deep neural networks for the control strategy in unmanned surface vehicles. A novel adaptive law is developed to update the weights of the ...

Abstract: The emergence of Deep Learning compilers provides automated optimization and compilation across Deep Learning frameworks and hardware platforms, which enhances the performance of AI service ...

Getting your Trinity Audio player ready... Frustrated with prior management of Medicaid and bracing for more near-term cuts, Colorado lawmakers plan to do a “deep dive” into the state’s massive ...

The long-range Disruptor drone was one of the systems ordered for Ukraine by the Phoenix Ghost program, which ended last year. Credit: Aevex A U.S. supplier of long-range attack drones to Ukraine won ...

It’s the farthest long-distance phone call in the known universe. When the astronauts of the Artemis II mission embark Wednesday on their scheduled journey beyond Earth’s orbit, in order to phone home ...

The Nothing Phone (4a) Pro is a budget phone with its sights firmly trained on flagships. It offers a huge 5000-nit AMOLED display, a seriously stylish 0.31-inch / 7.95mm thick aluminum unibody, and a ...

Physics-aware machine learning integrates domain-specific physical knowledge into machine learning models, leading to the development of physics-informed neural networks (PINNs). PINNs embed physical ...