Interactions between artificial intelligence and cybersecurity to protect future networks

Artificial Intelligence Safety and Cybersecurity: a Timeline of AI Failures

In this work, we present and analyze reported failures of artificially intelligent systems and extrapolate our analysis to future AIs. We suggest that both the frequency and the seriousness of future AI failures will steadily increase. AI Safety can be improved based on ideas developed by cybersecurity experts. For narrow AIs safety failures are at the same, moderate, level of criticality as in...

Artificial Neural Networks Analysis Used to Evaluate the Molecular Interactions between Selected Drugs and Human Cyclooxygenase2 Receptor

  Objective(s): A fast and reliable evaluation of the binding energy from a single conformation of a molecular complex is an important practical task. Artificial neural networks (ANNs) are strong tools for predicting nonlinear functions which are used in this paper to predict binding energy. We proposed a structure that obtains binding energy using physicochemical molecular descripti...

The Future of Artificial Intelligence

The first questions facing the development of artificial intelligence (AI), addressed by all three authors, are how likely it is that humanity will develop an artificial human-level intelligence at all, and when that might happen, with the implication that a human-level intelligence capable of utilizing abundantly available computational resources will quickly bootstrap itself into superintelli...

Neural Networks and Artificial Intelligence

SYNOPSIS Assessment of surgical risk in patients undergoing pulmonary resection is a fundamental goal for thoracic surgeons. Usually used risk scores do not predict the individual outcome. Data Mining (DM) and Artificial Neural Networks (ANN) are artificial intelligence mathematical models that have been used for estimation of several prognostic situations. When used to assess surgical risk the...

Artificial Intelligence: Future of Medicine and Healthcare