  This article presents a new design for autonomous artificial intelligence
(AI), based on the state-of-the-art algorithms, and describes a new autonomous
AI system called AutoAI. The methodology is used to assemble the design founded
on self-improved algorithms that use new and emerging sources of data (NEFD).
The objective of the article is to conceptualise the design of a novel AutoAI
algorithm. The conceptual approach is used to advance into building new and
improved algorithms. The article integrates and consolidates the findings from
existing literature and advances the AutoAI design into (1) using new and
emerging sources of data for teaching and training AI algorithms and (2)
enabling AI algorithms to use automated tools for training new and improved
algorithms. This approach is going beyond the state-of-the-art in AI algorithms
and suggests a design that enables autonomous algorithms to self-optimise and
self-adapt, and on a higher level, be capable to self-procreate.
