Active Foreground Neural Network (AFNN) is a revolutionary neural network which aims at bridging the computation, learning, and application’s implementation gap across conventional neural networks and cognitive learning processes with dual-band training and application layers. The aim is to perform asynchronous and parallel training of cross-interface Artificial Intelligence models with simultaneous implementation of the same. Therefore, the user may or may not need to implement the learning model.
- Active Foreground Neural Network (AFNN)
- Artificial neural network (ANN)
- Tensor processing unit (TPU)
- OpenCL (Open Computation Library)
- Compute Unified Device Architecture (CUDA)
- Graphical processing unit (GPU)