Login with your Social Account

Machine Learning and Artificial Intelligence

The Future of Computing and Artificial Intelligence

The advent of computers propelled society and spurred into action a lot of businesses and industries that would otherwise have been impossible. Computers and computer technology changed the way humans worked and functioned. The very first computer was a behemoth. Today, everything that you need is available on the computer through the internet and even the most complex computations can be carried out by these modern wonders. But, what does the future have in store for these computers? Are there any more frontiers that these brilliant systems need to face and overcome, and as a result, become even more powerful computationally? Let’s find out.

Computers are already ubiquitous, but, they possess the ability to enhance their presence even more. Computers are on desks and countertops, in bags and pockets, but, soon, they might be a part of everything imaginable. Yes, everything conceivable, even the tiniest of devices and commodities, might soon have computers embedded within them. There is an increasing demand for products that can carry out the computations that they need on their own and this has led to the need for devices that have computers embedded in them.

Some people perceive the final goal of computers to be that of ensuring that computers are inextricable from society and human life. Computers would be so involved in every process that the very thought of its non-existence would make life impossible! The aim is to ensure that computers are entangled with human life in such a way that computers would be indistinguishable from human life.

The notion going around that the future of computing is limited to Artificial Intelligence is incorrect. Artificial Intelligence is still burgeoning and is expected to be an essential part of day-to-day life, but, the future of computing is not limited to just Artificial Intelligence, there is much more to computing.

Artificial Intelligence


Image Source: Mike MacKenzie (Flickr)

The first challenge involved with Artificial Intelligence is the definition of intelligence. Intelligence has long been considered to be subjective and each person’s interpretation and definition of intelligence is generally different. Is a machine intelligent if it is able to communicate? Is it intelligent if it is able to learn? Or, is it intelligent if it can merely solve problems? One way to measure intelligence is through processing power. Machines can potentially gain computing powers that are greater than the processing power of all human beings put together. This situation is termed as the Singularity. The term was coined by John von Neumann and refers to the point when human affairs would cease, and computers would completely take over.

Potential threats

The low-end repetitive tasks have already been replaced by computing systems that automate it. The need for automation has made it imperative that we develop the computing potentials of computers. But, this growth has already caused a lot of concerns. There are several concerns over whether machines would someday surpass human intelligence. Currently, human intelligence, based on processing power, is considered to be 100,000 times more than that of the most powerful processing computer. But, it is estimated that computers can reach the processing power of humans within the next decade, at the rate of growth they are showing. By 2050, it is estimated that they would have processing power that is more than the sum total of all human brains combined. That is a scary thought indeed.

So, computers can take away our jobs and surpass our intelligence, what does that suggest? Is the world doomed? Not quite. Although one cannot quite rule out world domination by super intelligent computers and artificial intelligence, it is unlikely to happen due to the complexity brake. Scientists argue that computers and systems cannot grow to gain such super intelligence because as the processing power grows, the complexity increases and the complexity would reach a level that would restrain the growth of intelligence. Even if computers somehow broke free from the shackles of the complexity break, it is hypothesized that there would be enough ‘obedient’ intelligent systems that would keep the ‘misbehaving’ ones in check.

Let’s now get back to defining artificial intelligence. Since intelligence cannot be quantifiable, a generalist definition of artificial intelligence would be “machines and computers that carry out computations and tasks that would otherwise be carried out by humans”. This definition clearly does not capture the whole picture, but, is a reasonable attempt at defining A.I.

Evolution of Artificial Intelligence

The evolution of artificial intelligence can be viewed with regards to the forms of problems that it intended on solving. The early works in artificial intelligence focused on formal tasks, such as game playing and theorem proving. Checkers playing programs and chess playing algorithms were the earliest works in the field. Theorem provers such as the ‘The Logic Theorist’ aimed at solving theorems.


Image Source: Pixabay

A.I. then began to be implemented in solving common sense reasoning problems. A.I. was used to simulate the human ability to make presumptions about everyday activities. Reasoning about physical objects and their relationships, and about actions and their consequences were the problems that came under this field.

When A.I. began to grow, it started being built for perception problems. These problems were especially difficult because they involve analog data such as speech and vision.

A.I. is now being used for natural language understanding and natural language processing. Humans possess the ability to communicate through expressions and languages. Perceiving the languages and various constructs of the languages and being able to process them, are all problems that A.I. was created to solve. These fields are still not fully developed, but, systems that carry out natural language processing with a high degree of accuracy are already in place.

A.I. is now being used in tasks where human experts are needed. These tasks, such as engineering design, scientific discovery, medical diagnosis and financial planning are being carried out using artificial intelligence with a great degree of accuracy and precision. Expert systems are computer systems that use inferences and knowledge bases to mimic the decision making ability of human experts.

Domains of Artificial Intelligence

Artificial intelligence consists of countless domains. It would be highly improbable to list all of them. Here are some of the interesting domains of Artificial Intelligence:


Heuristic techniques involve finding approximate solutions to problems instead of accurate ones. Heuristic techniques are generally used when the time for computing the solutions is restricted or when it is computationally too expensive to look for the global optimal solution.

Statistical reasoning

This form of reasoning involves using probabilities and probabilistic theorems to determine most likely occurrences. Logical rules based on probabilities are created to determine what event is more likely to occur, given certain conditions.

Natural language understanding and processing

Natural language understanding involves the interpretation of natural language spoken by humans. Natural language processing, on the other hand, involves both interpretation and generation of natural language spoken by humans.

Expert systems

Expert systems are involved in carrying out tasks that would otherwise require human experts. These systems use inferences, which, are generally if-then rules, and the knowledge of previous problems and inferences derived from these previous problems, to provide solutions to the problem at hand.

Fuzzy logic systems

Fuzzy logic systems remove the notion of crisp boundaries and use fuzzy sets instead of crisp sets. In fuzzy logic, everything is viewed in terms of degree of membership. The hotness of a day is generally not quantifiable, but, fuzzy logic aims to quantify such occurrences using the concept of membership degrees. A temperature of 45°C, which, most people would perceive to be hot, could, therefore, belong to a set called ‘Cold’ to a certain degree (a small membership value) and to a set called ‘Hot’ to a certain degree (large membership value).

Genetic algorithms

Genetic algorithms aim to mimic the biological behavior of human beings and animals to solve problems. Artificial Neural Networks have been widely used in the computation. These networks consist of nodes that are intricately interconnected just like the human neural networks. Outputs at each layer of a network is propagated to the next layer. This system is used to solve a lot of complex problems. Ant colony optimization is one of the areas of genetic algorithms, where actual ant colonies are mimicked to solve problems such as finding the shortest paths.

Evaluation of artificial intelligence: Turing test

Turing test


Turing Test Illustration. Image Source: Wikipedia

Alan Turing hypothesized that a computer can achieve intelligence equivalent to that of a human being, or at least, intelligence that is indistinguishable from human intelligence if it could successfully lead a human being to believe that the machine was human. The Turing test is renowned for being the basis for classifying machine as either intelligent or not intelligent.

The Turing test involves a human evaluator who is responsible for determining which of the two entities he is talking to is actually human. The evaluator is allowed to ask a series of questions to carry out this classification. These questions are asked to both the human being and the machine. If the human evaluator fails to determine which one is human, and which one is a machine, based on the responses, then, the machine is said to have successfully fooled the evaluator and is deemed to be intelligent.

The Turing test is said to have set the benchmark for evaluating systems that may be intelligent.

The CEO of SoftBank, which, is a Japanese conglomerate, Masayoshi Son, once said, “I believe this artificial intelligence is going to be our partner. If we misuse it, it will be a risk. If we use it right, it will be our partner”. It is absolutely imperative that we tread carefully in matters pertaining to artificial intelligence. It is important to ensure that humans do not lose control over artificial intelligence. The result of losing control can be catastrophic. There is a need to impose regulations that prevent detrimental outcomes due to the development of artificial intelligence. The field of artificial intelligence has immense capabilities and should be allowed to grow, under regulated circumstances. Artificial intelligence need not have sinister outcomes. It is the responsibility of humanity to monitor A.I. and let it grow.

Read More:

  1. A Technical Overview of AI & ML (NLP, Computer Vision, Reinforcement Learning) in 2018 & Trends for 2019
  2. Bill Gates: These breakthrough technologies are going to profoundly change the world
Alan Turing Aged 16

Breaking the Enigma: Alan Turing and the Turing Machine

Very rarely do you find individuals that change the course of history purely through sheer brilliance. But, when you do find such individuals it is imperative to celebrate them. These individuals tend to produce magnificence through brilliance so effortlessly and with such fluency that it is hard not to remain awestruck. Alan Turing was one such individual. Alan Turing is the man who formulated many of the theoretical concepts that have enabled modern computation. He is widely regarded as the father of computer science, and, rightfully so.

About Alan Turing

Alan Turing was an English mathematician and cryptanalyst whose work in breaking the Enigma code and work in the development of computer science gained him a lot of recognition. He is also credited as being the father of Artificial Intelligence, which, is an exciting and promising field. He studied at King’s College, Cambridge and was widely considered to possess brilliance that was far beyond his age.


Turing Machine

Turing machine is a hypothetical simplistic machine that was created by Alan Turing as a solution to the decision problem. The simplicity of the Turing machine made it a phenomenon. The field of computer science was still in its initial stages and was a burgeoning field and the role of the Turing machine in its growth cannot be overstated. The contribution of the Turing machine was immense in the development and acceptance of computer science.

A Turing machine consists of an infinitely long memory tape that contains input characters or symbols. Upon reading a character on the memory tape, the state of the machine could change. There were operations such as read, write or modify that could be carried out on the tape. There also existed a set of rules that defined what would happen for a particular state and input symbol. These rules specified the effect of the character read from the tape on the current state. Each memory tape had a head. The head was responsible for carrying out either the operation of read, or, that of write. This head could also be moved either to the left or to the right.

This seems simple, right? This is where the beauty of the system lies. Without being overly complicated, the Turing machine had the potential of solving any problem. Alan Turing stated that this machine could solve any computational problem, given enough time and memory. This simplistic machine could solve everything!


An Enigma decryption machine called a “bombe.” This machine, made by National Cash Register of Dayton, Ohio, eliminated all possible encryptions from intercepted messages until it arrived at the correct solution. (U.S. Air Force photo)

Therefore, the Turing machine provided the basis for computational studies. In terms of solving computational problems, there is no computer more powerful than the Turing machine. Any computer that is considered to be as powerful as the Turing machine is considered to be Turing complete. Every modern computing system is considered to be Turing complete.

To answer the decision problem, Turing proposed a puzzle that is renowned as the halting problem. This problem aims to figure out whether there exists an algorithm that can determine if the machine will keep running, or, halt, given the input tape and description of the Turing machine.

This halting problem can be used to determine whether computer programs would halt or continue perpetually. Alan Turing was successful in proving that the halting problem was in fact unsolvable. Consider a Turing machine that takes the description of a program and certain inputs for its memory tape. Also, consider the output for this machine to be either Yes if the program halts or No if the program fails to cease. Now consider another Turing machine that is built on top of this machine. Now, if the output of the first Turing machine is Yes, which means that the program halts, then, we make the second machine run in an infinite loop. If the output of the first Turing machine is No, which means the program does not halt, then, we make the second machine output No and halt.

If you have followed carefully, you will notice that the second Turing machine does the exact opposite of the first one. Consider the combination of these machines as a single unified machine. Let’s call this machine, Alan. Now if we pass the description of the unified machine, Alan, as input to the same machine, Alan, then we are asking the system to evaluate itself. If the first Turing machine in Alan outputs Yes, the second machine goes into an infinite loop and it does not halt. If the first machine outputs No, the second machine halts.

So, the first machine cannot determine the solution to this problem. It results in a paradox. Since Turing proved that all computational problems can be solved on the Turing machine, the fact that this problem cannot be solved on it means that the problem does not have a solution. He, therefore, proved through contradiction that the halting problem is not solvable. By showing that the halting problem was not solvable, he proved that the decision problem had no solutions.

You may ask, what is the decision problem? Decision problem was put forth by David Hilbert. The problem asks for an algorithm that takes a sentence of first-order logic as input and produces either a Yes or a No according to whether the statement is universally valid or not.

Alonzo Church also proved that the decision problem had no solutions through his lambda calculus. This led to the formation of the Church-Turing thesis, which, says that lambda calculus and Turing machines are capable enough to solve all computational problems that have solutions.

Breaking the Enigma

Turing played a pivotal part in the Second World War in deciphering German codes that were created through the Enigma machine. This machine scrambled any text and transmitted the scrambled text. This scrambling was carried out by the Germans to ensure that nobody intercepts and understands their messages. The scrambling was not random, it was determined by the rotors of the Enigma machine, which meant that it could be descrambled on another Enigma machine. Thus, the Germans would transmit messages encrypted by one Enigma machine and receive messages decrypted by the receiving Enigma machine. The challenge for Turing was to crack the Enigma and understand the rotor configurations.

Alan Turing came up with the Bombe, which, was an enhancement of the Polish code breaking system that aimed to crack Enigma codes. Bombe predicted rotor settings of the Enigma machine more effectively than any other system. The Germans would periodically update the Enigma machine and add rotors to ensure that codes were not being encrypted by anyone else. Turing and his colleagues worked tirelessly to break this code and were appreciated for potentially reducing the duration of the war by several years.

Turing Test

Perhaps, the most promising contribution of Alan Turing was his contribution to Artificial Intelligence. Turing hypothesized that a computer can achieve intelligence equivalent to that of a human being, or at least, intelligence that is indistinguishable from human intelligence if it could successfully lead a human being to believe that the machine was human. The Turing test is renowned for being the basis for classifying machine as either intelligent or not intelligent.

The Turing test involves a human evaluator who is responsible for determining which of the two entities he is talking to is actually human. The evaluator is allowed to ask a series of questions to carry out this classification. These questions are asked to both the human being and the machine. If the human evaluator fails to determine which one is human, and which one is a machine, based on the responses, then, the machine is said to have successfully fooled the evaluator and is deemed to be intelligent.

Controversy regarding Alan Turing

Sadly, the greatness of this brilliant individual was marred with controversy. Alan Turing was homosexual in a time when homosexuality in the United Kingdom was illegal. When he was convicted of these charges, he was given the option of either imprisonment or chemical castration. He chose chemical castration so that he could continue his academic work. As a result, he spent much of his post-war life unable to conform to the changes that resulted in him due to chemical castration. He, unfortunately, took his own life at a very young age of 41.

Artificial Intelligence

The gift of Artificial Intelligence was provided to us by Alan Turing. Artificial Intelligence has shown immense potential and could soon be incorporated into everyday systems. Although one could say that Artificial Intelligence is still only a burgeoning field, the accomplishments of Artificial Intelligence are already so significant that it would be foolish to not consider it to be a powerful aspect of society in the not so distant future.

The genius, Alan Turing once said, “We can only see a short distance ahead, but we can see plenty there that needs to be done”. Alan Turing had tremendous dedication towards his work. He was even willing to undergo chemical castration to be able to continue with his academic work. That was the dedication that the man possessed.

There probably are not enough adjectives to describe the brilliance that Alan Turing possessed. Then again, it probably would be an injustice to the great man to express appreciation towards his intelligence through mere words. The potential the man possessed could not be, nay, should not be described through mere words constrained by the vocabulary. It is tragic how his story unfolded, but, his contributions to the field of computer science and artificial intelligence will forever live on. He was truly a rare gem.