Understanding the Hidden Gaps in Brain-Inspired AI Recent advances in artificial intelligence have drawn heavily from the human brain’s architecture ...

Large scale datasets and information processing requirements, within complex environments, are continuously reaching unprecedented levels of sophistication, especially in the advent of artificial ...

Katie Schuman, assistant professor and algorithm expert in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, along with fellow professor Jim ...

Image courtesy by QUE.com Understanding the Hidden Gaps in Brain-Inspired AI Recent advances in artificial intelligence have ...

It’s estimated it can take an AI model over 6,000 joules of energy to generate a single text response. By comparison, your brain needs just 20 joules every second to keep you alive and cognitive. That ...

In the future, a new type of computer may be able to learn much like you do—by experience rather than endless repetition or instruction. Researchers at the University of Texas at Dallas, along with ...

Traditional artificial neural networks, exemplified by large-scale models such as ChatGPT, have been widely applied across various domains. However, these models commonly suffer from low computational ...

As artificial intelligence platforms like OpenAI's ChatGPT and Microsoft's Copilot go mainstream, power bills from their usage are exploding. In response, researchers are racing to build hardware that ...

This collection supports and amplifies research related to SDG 9 - Industry, innovation and infrastructure. The exploration of two-dimensional materials has garnered significant attention in recent ...

A new technical paper titled “An Ultra-Robust Memristor Based on Vertically Aligned Nanocomposite with Highly Defective Vertical Channels for Neuromorphic Computing” was published by researchers at ...