New brain-inspired hardware, architectures and algorithms could lead to more efficient, more capable forms of AI.

However, modern learning algorithms for artificial neural networks, particularly ... More information: Zijian Wang et al, ...

July 2019 saw the announcement of the hybrid Tianjic chip, the first neuromorphic chip enabling scalable configurations of both artificial and spiking neural networks. Developed at Tsinghua ...

Researchers unveil a groundbreaking method to train spiking neural networks, offering a sustainable, brain-inspired path to energy-efficient AI solutions. AI applications like ChatGPT are based on ...

A new kind of memristor mimics how the brain learns by combining analog and digital behavior, offering a promising solution ...

A recent study led by Google AI researchers shows that modern LLMs are very similar to the human brain in the way they ...

Erlangen, Germany: The Fraunhofer Institute for Integrated Circuits IIS has developed an AI chip ... for spiking neural networks SENNA is inspired by the functioning of the brain, consists of ...

The shoe box-sized device, dubbed CL1, is a notable departure from a conventional computer, and uses human brain cells ... to train "biological AI," meaning neural networks that rely on actual ...

The project will develop a low-power Neuromorphic In-Memory Computing (IMC) ASIC prototype in nano-scale advanced CMOS technology based on spiking neural networks (SNNs) for both training and ...

Two trailblazing computer scientists have won the 2024 Turing Award for their work in reinforcement learning, a discipline in which machines learn through a reward-based trial-and-error approach that ...