Pushing the boundaries of what's convenient. We develop neural architectures that learn, adapt, and evolve.
Advanced object detection and segmentation model optimized for real-time edge computing. Capable of identifying complex patterns in chaotic environments.
Trainable K-Nearest Neighbor classifier working on top of MobileNet. Teach the system to recognize specific faces or objects directly in the browser.
Time-series forecasting engine designed for high-volatility datasets. Used in financial modeling and resource allocation prediction.
A genetic algorithm combined with neural networks. Agents learn to navigate infinite obstacles by evolving their brain structure over generations.
Interactive playground for core RL algorithms including Q-Learning (Grid World) and Multi-Armed Bandits. Watch agents learn from scratch in real-time.