Researchers from UC Santa Barbara, ETH Zurich, and Miguel Hernández University demonstrated that artificial intelligence models can optimise electrical stimulation in visual cortical prostheses (bionic eyes), improving the accuracy, efficiency, and predictability of artificial visionVisual cortical prostheses or bionic eye skip the eyes and optic nerves entirely, delivering electrical stimulation directly to the visual cortex at the back of the brain. Key mechanical challenges of traditional prostheses include:Non-pixel behaviour: The brain does not process electrode signals as simple pixels; adjacent electrodes interact, and neural responses fluctuate over time. Perceptual disconnect: Standard electrical stimulation settings fail to reliably predict what a user actually perceives (phosphenes, or spots of light). Perceptual accuracy: Recorded neural responses served as a far stronger predictor of perceived phosphene features (shape, size, brightness, colour) than raw electrode settings alone. Adaptive systems for long-term usabilityBecause neural responses change daily, static stimulation settings cannot maintain reliable artificial vision.