Most of today’s predictive Artificial Intelligence (AI) technologies are running on expensive cloud-based processors and they require tons of data. That means they consume a lot of energy and power to operate, making them less green and less environmentally friendly. They struggle to explain all their behaviour to users. Unless you have large and skilled teams of Data Scientists and Engineers, it is difficult to deploy them and integrate them to your business. That also means that time-to-market is long for those existing predictive AI technologies. They are also costly and expensive to maintain. They are usually biased towards larger classes while missing small classes and anomalies. That may lead to significant problems for example failing to diagnose a cancer at very early stages.