Choosing the right blueprint can accelerate learning in visual AI systems. Artificial intelligence systems built with biologically inspired structures can produce activity patterns similar to those seen in the human brain even before they undergo any training, according to new research from Johns H

A radically miniaturized brain implant called BISC is redefining what’s possible in human–computer interaction, offering a paper-thin, wireless, high-bandwidth link directly to the brain.

With over 65,000 electrodes and unprecedented data throughput, it enables advanced AI decoding of thoughts, intentions, and sensory experiences while remaining minimally invasive.

The human brain processes spoken language in a step-by-step sequence that closely matches how large language models transform text.

A new framework that causes artificial neural networks to mimic how real neural networks operate in the brain has been developed by a RIKEN neuroscientist and his collaborator. In addition to shedding light on how the brain works, this development could help inspire new AI systems that learn in a brain-like way. The research is published in Nature Communications.

Humans and animals have remarkable capacities to learn and perform complex tasks due to the brain’s amazing ability to take in sensory information and produce complex outputs.

Toshitake Asabuki of the RIKEN Center for Brain Science is fascinated by the brain and wants to discover how it works. “My team investigates how the brain learns efficiently and robustly,” he says. “We aim to identify learning rules that could, in principle, be implemented by real neural circuits in the brain.”