Despite some of the astonishing accomplishments in the field of Deep Learning, more than a few well known researchers believe that current Machine Learning technologies have reached a relative stasis point. These same researchers go further to say that a rethink of how to approach the replication of human intelligence is in order, and is in fact necessary, for AI to progress significantly and boldly go where AI has never gone before. DARPA refers to this next generation of AI accomplishments as the Third Wave of AI, where the First Wave included techniques such as expert systems and the Second Wave covered Machine Learning including techniques such as Deep Learning and Symbolic Regression. This special topic issue is devoted to examining the science, engineering, and technologies for achieving the Third Wave of AI, the “Next Generation”. It is hoped that the articles presented in this issue might inspire the next generation of researchers to bring such concepts into reality. As well, this issue also promises to be a useful reference; to provide “under one roof” the multifaceted world of the breakthroughs occurring across the different disciplines that impact the future of artificial intelligence.

This look into the future will Include:

(1) A review of seminal works that defined both First and Second Waves of AI for perspective of what’s been done and its limitations

(2) What biological advancements are at the foreground of replicating and modifying nervous system, sometimes referred to as “wet ware”, including brain organoids and CRISPR modifications of DNA

(3) Neuromorphic computing, which although has a legacy backdrop, is yet making immense strides today with more advanced breakthroughs in lithography, stacking at the processor and mezzanine levels, doping, and more

(4) Quantum computing

(5) Neurological modeling

(6) Combinations of these and other technologies