SELF-LEARNING FROM AIR OF ARTIFICIAL INTELLIGENCE MODELS APPLICABLE FOR DRIVING

A method of self-learning from air of AI models applicable for driving, the method includes obtaining, by a computerized system, aerial image signatures of patches of aerial images that capture at least parts of an environment faced by a vehicle, wherein the computerized system is associated with a set of artificial intelligence models applicable for autonomous driving; identifying, from the aerial image signatures, a set of aerial image signatures in accordance with a specified driving scenario faced by the vehicle; and training, in a self-supervised learning process based, at least in part, on the identifying, a neural network implementing an artificial intelligent model to provide a decision making for the specified driving scenario, wherein the artificial intelligence model is at least one of: a new artificial intelligence model, or one of the set of artificial intelligence models associated with the computerized system.