Recent advances in neural network design have spurred the development of energy-efficient architectures for speech recognition, a field that underpins a range of modern applications from smart ...

NAS methods can generally be classified based on tailored designs from the following aspects: search space, search strategy, and evaluation strategy. In particular, search space can be further ...

The most powerful artificial intelligence tools all have one thing in common. Whether they are writing poetry or predicting ...

MicroCloud Hologram Inc. has announced the creation of a noise-resistant Deep Quantum Neural Network (DQNN) architecture, which aims to advance quantum computing and enhance the efficiency of quantum ...

A new technical paper titled “Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration” was published by imec, TU Delft and University of ...

Neuro-symbolic AI is a unique form of artificial intelligence that combines the strengths of neural and symbolic AI architectures. This powerful AI model can model cognition, learning, and reason, ...

Integrating quantum computing into AI doesn’t require rebuilding neural networks from scratch. Instead, I’ve found the most effective approach is to introduce a small quantum block—essentially a ...

In their classic 1998 textbook on cognitive neuroscience, Michael Gazzaniga, Richard Ivry, and George Mangun made a sobering observation: there was no clear mapping between how we process language and ...