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Humans Are More Intelligent Than Computers

Computers will be able to imitate more aspects of human brain in the next few decades but a computer capable to having all of abilities of human brain and equally efficient on resource utilization is still in realms of science fiction

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The rising power of computers and advances in Artificial Intelligence has reenergized the debate of intelligence of computers relative to humans. Broadly, there are two approaches to it.

First approach focusses on study of human brains and compares that with computers. Human brain has about 100 billion neurons which are often compared to gates in computers. Neurons interconnect through synapses and may have upto 10000 connections each giving a total of 100 to 1000 trillion connections. Neurons communicate through electrochemical signals which are one million times slower than speed of signals on fibre optic cables and neurons fire at about only 200 times a second. They collaborate to provide about 2.5 petabytes of memory. Brain consumes about 20 W of power.

Supercomputers have similar or better numbers except that they need power in MW and most importantly the transistors connect with very small number of neighbors and have 2D geometry. But computers cannot be compared with human brain on these numbers alone due as human brain is not a digital machine driven by a clock and it does not differentiate memory and processing areas. Besides, the functioning of brain is itself not properly understood. A simulation of human brain by

Fujitsu-built K took about 40 minutes to complete simulation of one second of neuronal network activity in real time in 2013.
Second and the more popular approach focusses on imitating the functionality of the brain. This approach also does away with the difficult question of defining intelligence. Computers are definitely ahead of humans in calculations or when it comes to executing simple step-by-step instructions. This power was at display in 1997 when IBM's Deep Blue, a computer defeated the then world chess champion, Garry Kasparov. The computer could evaluate millions of possible positions per second and think of the next 20 moves. And today super computers with speed in peta flops (10^15) can outwit any human in any calculative task.

One important quality of humans is that they can learn. Machine learning is the branch of Artificial Intelligence which focuses on creating machines or computers that can "learn". So, driverless vehicles, email filtering, spam detection and most importantly robotics is based on this idea. And success of Google's AlphaGo in defeating champion, Lee Sedol in game, Go is based on Machine Learning as number of possible positions in Go is so large that even fastest computers would be swamped. But computers need to be programmed or told on how to "learn" and computers thus programmed will work only for those situations.  Besides, success in these areas does not translate into superiority of computers e.g. while driverless vehicles will "learn", they still need detailed 3D maps to work efficiently unlike humans.

One important attribute of human brains is the ability to recognize patterns e.g. characters, faces, voice in noise. This is an area where computers do not match human abilities. Computers can recognize printed letters and numbers, and can recognize specific faces and automatically tag photos of those people as you take pictures. But humans can recognize complex patterns and adapt to them. Humans can also recognize faces which are covered with facial hair, have done make ups etc. A technique of Machine Learning called Deep Learning is used to train computers on pattern recognition. Here it creates layers of nodes with interconnection between layers similar to that of neurons in the brain.

Same applies for language abilities of human. As of now, computers can do simple translations between 2 languages, speech to text translation and vice versa. Again, deep learning is being used to improve capabilities of computers. IBM's Watson which won in Jeopardy! In 2011 had to use Natural language processing as the game needs questions to be created against answers. But computers are still behind as human languages are ambiguous and the linguistic structure can depend on many complex variables like slang, regional dialects

Computers need to bridge the gap on creativity front. Though there has been some progress here too. Computers are being used for writing news in Washington Posts, USA Today, Wired etc. Shimon, a robot from Georgia Institute of Technology can compose music and there are competitions to display paintings created by robots. However, human's abilities in arts e.g. writing stories and poems, making paintings, composing music etc are beyond the reach of current set of computers. Same applies to research. Adam, a robot designed by British scientists is capable formulating hypotheses, designing and running experiments, analyzing data, and deciding which experiments to run next. But current set of computers cannot formulate new scientific theories. Computer engineers at Cornell University designed a program that could give a computer basic set of tools it could use to observe and analyze the movements of a pendulum. Using this foundation, the software was able to extrapolate basic laws of physics from the pendulum's motions. But the computer could not create the tools of its own.

Additionally, the computers do not have feelings e.g. love, fear, anger etc. This fuels ambition and creativity and advances civilization. Superior feelings of humans allows them to make much stronger bonds with a much larger geographical spread and has contributed to their dominance over other species. This bonding allows humans to benefit from collective intelligence of mankind rather than an individual. Computers cannot reason or understand impact of a decision. Computers are yet to beat humans in a game called Startrek which requires lots of decision making.

Turing test devised in 1950 checks if a computer can mislead a human to think that it is human based on a conversation, a sort of imitation test. In 2014 a Russian-designed programme called Eugene Goostman could mislead 33% of the judges in one Turing test. Since then other tests e.g. Loebner etc have been devised with more difficult criteria including higher misleading rate.

Computers will be able to imitate more aspects of human brain in the next few decades but a computer capable to having all of abilities of human brain and equally efficient on resource utilization is still in realms of science fiction.

Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house. Unless otherwise noted, the author is writing in his/her personal capacity. They are not intended and should not be thought to represent official ideas, attitudes, or policies of any agency or institution.


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Sandeep K Chhabra

Sandeep K Chhabra is a software professional working as General Manager at Ericsson India Global Services Pvt Ltd (EGIL). He has more than 23 years of experience of working in IT industry. He is a B Tech in Computer Science and Engineering from IIT Delhi and has cleared CFA Level (III) exam. He is active on social media and mostly writes about current trends in Science and Technology.

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