Advancing the Science of Brain-Inspired AI
Advancing AI with Neuromorphic Innovation
At Silicosapien, we are committed to advancing the field of AI through the intersection of cognitive computing and high-performance technologies. Our team of researchers and engineers continuously explores new methodologies, frameworks, and innovations to push the boundaries of what's possible.
Through our research, we are dedicated to ushering in a new era of AI that is smarter, safer, and fundamentally aligned with the dynamics of human cognition.
How Our Research Contributes
At Silicosapien, we believe that the intersection of cognitive neuroscience and artificial intelligence can reshape the development of AI across a wide variety of industries. Our research efforts contribute directly to developing more efficient algorithms, scalable systems, and impactful technologies that are making a difference in the real world.
Featured Research
1. A Computer Vision Implementation of a Neuromorphic Artificial Neural Network Architecture with a Learning Algorithm Based on Neural Selectivity
Authors: Youssef Mahmoud Massoud Shaiba Nassar
Affiliation: Ain Shams University, SilicoSapien Inc. Research Department
Abstract:
This first paper introduces the neuromorphic artificial neural network architecture that bridges the gap between traditional Convolutional Neural Networks (CNNs) and Cognitive Networks (CNs). By integrating biologically inspired learning mechanisms such as neural selectivity, the architecture enhances interpretability and efficiency in computer vision applications. The model achieves 98% accuracy on the MNIST dataset without relying on gradient descent and represent our first experimental test for a neuromorphic learning-based generalization, before introducing the Neuromorphic Symbolic Transformer.