Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

A team at the University of California, San Diego has redesigned how RRAM operates in an effort to accelerate the execution ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

Neural network models that are able to make decisions or store memories have long captured scientists' imaginations. In these models, a hallmark of the computation being performed by the network is ...

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.

A new study led by researchers from the Yunnan Observatories of the Chinese Academy of Sciences has developed a neural network-based method for large-scale celestial object classification, according ...

Google's Genie generates infinite interactive worlds from text. The secret? AI models compress reality's rules into ...

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 ...

Multiverse Computing SL, a startup with technology that reduces the hardware footprint of artificial intelligence models, is reportedly raising new capital. Sources told Bloomberg today the Spanish ...