AI- The artificial Intelligence as we call it, is not a technology which has seen an easy way through the science field. Since its birth in a workshop at Dartmouth College by a group of 5 young scientists, AI made the spectators drop their jaws. It was learning the strategies of checkers and solving most complex problems in lightening speeds. Who knew by just changing 0 and 1 and their positions, we could make almost all the tasks done by computer. The ups and downs of AI has been numerous and it was again a centre for exploration ever since google started using it in its packages from 2015.
So, what is the bottom line of AI in its basic sense actually?.. Computer science defines it as a device which perceives its environment and executes tasks that maximizes the successful results it is being employed for. Yeah, in its basic sense or more or less what it does, It is true indeed. Personally, I use the Artificial Neural Network (the other name of AI) to recognise an stochastical data, learn it and predict the future results, which goes hand in hand with the CS definition. The data I give the network is statistical, stochastic and cognitive. The AI has some learning algorithms like Trainbr, Trainlm etc to perceive the network and conceive the results.
Since the day I’ve started investigating and working on it to conceive a predictive artificial Intelligence throttled mathematical solution to my extremely noisy randomly distributed data, I have heard and read AI as an exterminator of the jobs currently done by humans and some may argue an fate where AI rules. Let us put it straight here. The term “Artificial Intelligence” is used when a machine perfectly mimics “Cognitive” functions that humans associate with other minds, such as “Learning” and “Problem Solving”. With the problem solving term I’ve used and what I’ve said till now, one might think there might be a very complex set of mathematical arc net running behind. This is often a misconception and I was a victim of it too. The beauty of AI is its simplicity in programming structure and ability to accurately reproduce the data with very simple tools.
The scope of AI is always a topic up for debate and disputed quite often. As machine becomes increasingly capable, tasks which required “Intelligence” earlier are often removed from the definition. As tesler’s theorem says “AI is whatever hasn’t been done yet”. Modern day AI is defined successful in understanding the human speech, playing a top notch strategic games like chess.
My knowledge and experience with the AI is primitive yet, I deem enough to make these statements. I think the disputes around the full scale AI might be the bitter fruits of certain gaps within the science of AI itself. From the literature of Kaplan and Haenlein, AI is classified into three types of systems: Analytical systems, Human Inspired System and Humanized System. Analytical AI is capable of performing cognitive tasks and limited to cognitive intelligence only. Most of our mechanical systems use this system primarily. These systems lack emotional intelligence whereas on the other hand human inspired and humanized systems respond to emotional intelligence and social intelligence. Although my expertise in those is very limited, but pretty much sure your terminator and I robot are a part of it. The creators of AI predicted that AI would be capable in 20 years to do everything what humans have done till now. But, they failed to predict the snaps of the strings underlying. The field of AI is subdivided which lack basic communication among them. This always leads to incomplete understanding over the science and it is necessary to establish a relation among them to know what it actually is capable of…
Right now, the principle problems associated with the AI are attributed to reasoning, knowledge representation, planning, learning, perception and ability to manipulate objects. But, does AI really capable of taking over the world is quite rhetoric and we don’t have enough data at hand to actually answer that question….
What do you think?
Please do comment.
Open for criticism too! As always ;)
Note: All the references are embedded as links.
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