Categories: AI/ML News

A brain-inspired AI technology boosts efficiency and reduces energy consumption

Researchers at FORTH have developed a new type of artificial neural network (ANN) that incorporates features of biological dendrites. This innovative design allows for accurate and robust image recognition while using significantly fewer parameters, paving the way for more compact and energy-efficient AI systems.

Integer addition algorithm could reduce energy needs of AI by 95%

A team of engineers at AI inference technology company BitEnergy AI reports a method to reduce the energy needs of AI applications by 95%. The group has published a paper describing their new technique on the arXiv preprint server.

October 13, 2024

In "AI/ML News"

Engineers develop thin film to make AI chips faster and more energy efficient

Addressing the staggering power and energy demands of artificial intelligence, engineers at the University of Houston have developed a revolutionary new thin-film material that promises to make AI devices significantly faster while dramatically cutting energy consumption.

December 3, 2025

In "AI/ML News"

Asynchronous AI cuts computing energy by orders of magnitude while learning continuously

As artificial intelligence systems grow larger and more powerful, their energy demands are rising dramatically. But recent research from the University of Massachusetts Amherst published in Nature Communications suggests that advanced AI capabilities may be achievable with dramatically lower energy consumption.

June 9, 2026

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