NeuroxAI – GPU-Accelerated Neuromorphic Computing Platform (github.com)

NeuroxAI has launched a cutting-edge GPU-accelerated neuromorphic computing platform designed to emulate biologically realistic spiking neural networks. This platform supports the simulation of 1 to 10 million neurons and is optimized with CUDA for real-time performance, making it a significant advancement for AI and machine learning researchers focused on developing more brain-like computational architectures. Built using Rust, NeuroxAI incorporates biologically inspired neuron models and advanced learning algorithms such as triplet spike-timing-dependent plasticity (STDP) and metaplasticity, facilitating a deeper understanding of cognitive functions. The platform's capabilities extend to language processing and conversational AI, featuring a dual-stream architecture for context maintenance, paraphrase detection, and emotional state analysis. Key technical elements include the modeling of neural oscillations, the implementation of dopaminergic and serotonergic dynamics for neuromodulation, and efficient algorithms for training within a JSON-based system. This integration of neuroscience principles and modern computational techniques positions NeuroxAI as a transformative tool for advancing cognitive architectures and understanding complex neural interactions, paving the way for more adaptive AI systems.