Real-world optimization problems often require an external “modeling engine” that computes fitnesses or data that are then input to an objective function. These programs often have much longer ...

Classiq 1.0 is designed for enterprise quantum R&D groups, algorithm developers, researchers and engineering teams that need to connect classical logic and constraints to quantum models and carry that ...

The history of AI training has been shaped by the limits of communication. For years, progress depended on placing machines ...

A new technique from Stanford, Nvidia, and Together AI lets models learn during inference rather than relying on static ...

The Department of Energy (DOE) has released specifications for 26 artificial intelligence (AI) challenges under its Genesis Mission that could reshape how ...

McGill and Queen's University researchers have built an improved version of a computer that uses light to solve extremely hard problems more quickly ...

Companies ranging from OpenAI, Meta, Microsoft, and Google to smaller firms and startups are looking for high-quality AI ...

Machine learning redesigns microscopic web sensors to be five times more flexible than nature-inspired versions, enabling detection of masses as small as trillionths of a gram.

Non-terrestrial networks have their own challenges that cellular networks didn't have. Will AI help solve them dynamically?

Better understanding of the design, implementation and operation of these cyber-physical systems can enable optimized process ...

The hunt is on for anything that can surmount AI’s perennial memory wall–even quick models are bogged down by the time and energy needed to carry data between processor and memory. Resistive RAM (RRAM ...