Cognition comes from the Latin word “cognito,” which means “to think.” The definition can readily be expanded to also include learning and reasoning. When evaluating cognitive computing environments, the most important question is where should cognition, or machine intelligence, actually reside? In the bible, it says that god created man in his own image. Most likely it will be the same case when man creates intelligent machines. The very essence of human nature will lead to designs modeled after our own likeness. People will feel the most comfortable interacting with machines that look, talk, move, and think, just like we do. But what does this mean from a software architecture and design perspective, and what impact will it have on the long term success, and product viability, of existing cognitive computing products and environments?
Think of the human body for a moment. Where are our eyes, ears and mouth located? These core senses, as well as our ability to speak, are all positioned right alongside our brain. What this translates into, from a software engineering perspective, is that cognition needs to live right at the very edge of the computer network, at the point where cameras, microphones, speakers, and a host of other sensors, directly connect to laptops, desktops, and workstations.
Imagine for a moment the operation of a ‘self driving car’. What would happen if the intelligence of this vehicle were located somewhere up in the cloud? This would mean that when an eighteen wheeler jams on its brakes in front of the autonomous vehicle, a client application running under the hood would need to send a request containing real-time data to a server up in the cloud. Situated perhaps a thousand miles away. The vendor’s cognitive computing engine would have some machine vision algorithm running there, that would first determine that there is no safety bar in the rear of the tractor trailer, and then another would determine how long it would take before impact. The roundtrip request and response, without even factoring in the time it takes to perform these core computations, may take a half of a second. But in that time period, moving at 60 miles per hour, you would have traveled forty-four feet, which may mean the difference between life and death for you.
There are other business, medical, scientific, and military use cases that also confirm the basic design flaw in putting ‘cognition’ up in the cloud. Think for a moment of a battlefield scenario, where a technologically advanced enemy has the ability to electronically jam internet protocol communications between virtual assistants, or robo advisors. They would simply be rendered useless. The ability for an intelligent machine to operate independently in the midst of battle, is essential to victory. Then of course there is the proverbial ‘moon shot’ that every company dreams about. In the case of nTeligence corporation, we envision a ‘Mars shot’. Our long term goal is to accompany astronauts on a mission to the red planet. In this environment it will take a signal from Earth at least five minutes to reach Mars. If there were a ‘mission critical’ virtual assistant or robo advisor running on the surface of the planet, this enormous time lag could render it worthless, even if it were just to provide psychological counseling to the men and women there.
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