Artificial Intelligence Brings the Era of Thinking Machines

by August 10, 2018 0 comments

Thinking Machines

After hearing about promises of intelligent machines for more than 50 years, Artificial Intelligence (AI) has finally become the most in-demand item on the list of leading technology firms and startups all around the world. The reason being the ever increasing size of data that is beyond the processing capabilities of the humans. Arvind Krishna, Senior Vice President of Hybrid Cloud and Director of IBM Research says, “What was deemed impossible a few years ago is not only becoming possible, it’s very quickly becoming necessary and expected.”

We already live a life enhanced by AI in some way or the other. Machine capabilities are growing and are expected to reach levels where they might be more fully integrated into daily life. They’ll soon be able to perform all sorts of mundane jobs that probably humans don’t want to do and the jobs that are beyond the scope of humans. All this so that humans are better able to focus on activities that they are intrinsically programmed to perform well in, like providing empathetic solutions, strategy formulation, creativity, etc.

The confluence of big data, advanced graphics processing units (GPU’S) and deep learning has caused the rapid acceleration towards an AI future. The main attraction of AI is technologies performing certain tasks autonomously without any human intervention or supervision. Yet there are instances where the machine fails to surpass human logic. Dr. Mateja Jamnik of Cambridge’s Department of Computer Science & Technology, mentions the case of creating a formula to find the area of a parallelogram. On one hand, while humans will simply reassemble the figure to create a rectangle and simplify the problem, computers may get caught up in using complex integration formulae to solve such a simple problem.

World’s leading industry thought leaders have predicted many achievements for AI technology, the most important one being its adoption within diagnostic groups in leading healthcare systems. Biometric capabilities, on the other hand, will see our face becoming the new credit card, the new barcode and the new driver’s license. And this will be the year when deep learning will start to get extensively deployed in engineering simulation and design.

The single most important variable in the development of AI technology is deep learning. IBM’s John Smith, Manager of Multimedia and Vision, says “We’re seeing deep learning have a huge new impact, whether it’s in speech or vision or some problem in natural language processing. This is going to continue for some time.”

Areas of well-defined problems have been tackled by AI systems quite efficiently. The real challenge is to make computers think like a human with respect to their ability to reason and think flexibly. Tasks like handling changing situations or applying basic common sense are something which are implicit in the human brain, but intelligent systems have not yet developed this kind of common sense capability.

The indivisible social structure places humans at the top of the intelligence pinnacle and therefore the ultimate goal of AI is typically assumed to be humans. A lot of human skills are for sure a part of the AI plan but it will be a real achievement to build an AI system that might perhaps fill gaps that humans cannot reach, like building AI systems thinking in non-human ways or not thinking at all.

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