Neuroinformatics, Neural Networks and Neurocomputers for Brain-inspired Computational Intelligence

The talk discusses briefly current challenges in artificial intelligence (AI), including: efficient learning of data (interactive, adaptive, life-long; transfer); interpretability and explainability; personalised predictive modelling and profiling; multiple modality of data (e.g. genetic, clinical, behaviour, cognitive, static, temporal, longitudinal); computational complexity; energy consumption; human-machine interaction.