Building intelligent machines has been a long dream of humanity. While the journey has been difficult and slow, the progress in Machine Learning, Optimization Techniques and advancement in Deep Belief Networks offers promising ways to engineer cognitive systems. The science behind cognitive computing seeks to develop systems that emulate human brain functions such as perception, knowledge accumulation, goal planning, and logical inference. Cognitive systems will operate at a speed and an informational capacity that far exceeds human capability. They will serve to act as an advisor, partner, helpmate, and co-creator to the humans, collaborating on human terms.   Cognitive computing is a fundamentally new computing paradigm for tackling real world problems, exploiting enormous amounts of information using massively parallel machines that interact with humans and other cognitive systems. Cognitive systems will bring human-like reasoning to the problems of Big Data, and will also permit us to expand into the white space of domains that require human-like cognition but that either exceed human capacity or are impossible for a live human presence.   In this talk, I will review the past progress and discuss the future challenges. I will address the architectural challenges of building a general purpose system of systems that can learn, can reason, and can interact in a human natural way.
['David Nahamoo']
Cognitive computing journey