Large-Scale Virtual Model of the Visual Cortex Enables Robust Solutions for AI Visual Tasks

The new large-scale model of the visual cortex has shown great success in solving visual tasks

Researchers from the Human Brain Project have trained a large scale model of the primary vision cortex of the mice to solve visual problems in a robust manner. This model is the foundation for a whole new generation of neural networks. These models are versatile and can be processed efficiently, which makes them a good candidate for neuromorphic computing.

Modeling the human brain has a huge impact on artificial intelligence. Since the brain is much more efficient at processing images than artificial networks, researchers can take inspiration from the neuroscience field to create neural network that work similarly to biological networks to save significant energy.

Brain-inspired neural network blueprints will likely have a significant impact on the future of technology by allowing for more energy-efficient processing. Researchers from Graz University of Technology’s Human Brain Project (HBP), Austria, have shown in a new study how a large-scale data-based model is able to accurately and versatilely reproduce the visual processing abilities of the brain. The results of the study were published in Science Advances.