IFE AI

Hybrid Artificial Intelligence (AI) and Distributed Ledger Technology (DLT) are among today’s most actively debated developments in information technology with the potential for tremendous impact on individuals, organizations, and societies over the next decades.

The AI technologies that are used in DLT include Machine Learning (ML) and Deep Learning (DL) models. ML is further subdivided into Supervised and Unsupervised Learning, Reinforcement Learning, and Transfer Learning. Within Supervised Learning, the most commonly used algorithms are K-Nearest-Neighbor (KNN), Linear Discriminant Analysis (LDA), Multilayer Perceptrons (MLP), and Support Vector Machine (SVM). Transfer Learning relies on transfers between either task, subjects, or sessions respectively. DL’s algorithms are Convolutional Neural Networks (CNN), Recurrent Neural Network (RNN), in particular, Long Short Term Memory (LSTM), Gated Recurrent Units (GRU), and Generative Adversarial Networks (GAN) and their hybrids: CNN/LSTM, RNN/LSTM, LSTM/GRU.