The Future Of Coding

By Author: Johnson Philip
Total Articles: 90
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The number system is actually a system of codes to represent information that is not intrinsic to the code itself. So is the alphabet.

Since encryption also involves coding, some people confuse between codes and encryption. While there are elements common to both, the purpose of coding is to represent information efficiently, enabling arithmetical and logical manipulation, while the purpose of encryption is to hide information from unauthorized people. In that sense, code is information that is potentially available to all who who know the rules of coding and code-manipulation, while encryption is the process of restricting the meaning of the code to a select few. A good example of code would be DNA where the information is coded but not hidden. An example of encryption would be the way user-passwords are stored by most website databases.

Our concern in this article is with coding, and the use of technology for coding, and not with encryption. Since all encryption rides upon coding, knowing about the past and future of coding would automatically open up the way to understand the past and future of encryption, ...
... which can then be explained more efficiently in forthcoming write-ups devoted exclusively to encryption.

The arrival of computers made manipulation of codes easy, even when there are several levels of codes riding one on top of the other. So much so that what a man can do with paper and pencil in a thousand years can be done by a super computer in one second. However, contrary to what was expected in the last few decades, it has become clear that this raw increase in computational power and corresponding code-handling capacity has not resulted in a proportional capacity to mimic the human thought process.

If computers have to effectively take over all what men have envisaged them doing, then they need to mimic the human thought process. Raw computation power of a million supercomputers might be able to do that, we do not know, but then nobody in his right mind ever envisages a situation where a million supercomputers are connected together to guide a robot to sweep the house or go shopping. It has become increasingly clear that for the so-called Artificial Intelligence to arrive one needs more efficient ways of handling code and that is the bottleneck where things more or less the stand today.

Algorithms: The Demand For Future

Machines with better efficiency will be needed to handle code-manipulation in future. Better efficiency here means both the raw computing power as well as the ways in which code is handled to arrive at results.

Man handles code through addition, subtraction multiplication etc. But he also handles multiplication blazingly fast through tables, memorizing which at least up to the table of 30 was compulsory in Indian schools. In a previous generation stone masons also used to memorize tables of fractions, and were able to mentally compute area and volumes which for most of us requires books of references and calculators. Thus tables gave them unusual efficiency for mental computation in that bygone generation. What was done in these generation through tables is a good example of ''algorithms''.

An algorithm is a technique, method, or approach for solving a computational problem in an unusually efficient way. It is also a technique, method or approach for solving problems that demand complex logic. Mathematical tables are a good example. Logarithm that reduce very large multiplication and division to very simple addition and subtraction is another example. There are numerous other algorithms, some of which might look very complex to the reader, but which are easy for computers to handle. These algorithms give tremendous speed and accuracy to computers. However, even the best algorithm has not yet come to a point where it can mimic human thought even remotely. This is where the future of coding requires multiple breakthroughs.

A cursory look on any book on computational algorithm will show that they have already reached a very high level of complexity. So much so that further breakthroughs will require access to an array of networked supercomputers placed on one's table so as to invent and test more complex or more comprehensive algorithms. Such computers and such software are yet to arrive, but many do eagerly wait for them the way most people waited in the nineteen seventies for the arrival of table-top computers.

Raw Computing Power For Future

The raw computing power of the inconspicuous table-top computers of today is a million times more than that of ENIAC of yesterday which occupied a whole auditorium and which needs so much electric power that the small town would immediately see a voltage drop when it was turned on. Yet this computing power of today is only infantile processing power compared to the need of future computing.

What we need in power for the next breakthrough in code-handling is to have table top machines which are perhaps a billion billion times more powerful and faster than the fastest machines sitting on our tables today. This is simply impossible using the technology of today, but it can surely be done using the technologies visible on the horizon.

At present all operational computers worldwide use binary numbers for computation, a most inefficient way for coding decimal numbers because each decimal number is represented by many more digits in binary that in decimal. Also each act of computation requires many more steps than are needed in the decimal system. Thus machines that can handles numbers to the base ten need to arrive. If machines can be invented that can handle bases larger than decimal system such as the hexadecimal system, the computation would become all the more faster, and the raw power would make many degrees of jump.

DNA computing, which is still in a theoretical stage, and where the prototypes are still in infancy promises to offer a system where instead of depending upon the binary system, one can go directly to a decimal or hexadecimal system is the most promising system. Optical computing, which is still only a very remote idea might offer even more powerful ways of handling numbers in future. Since numbers are codes, and since many levels of code have to ride upon each other before code-handling is able to offer anything useful to the humans, these potential technologies do promise a bright future for code handling.

While industrialization did usher in the modern era, it brought only an order or two of sophistication over what it used to be before that. However, the real jump in the social use of machines came only with the arrival of machines that could handle code.

All the machines before this era handled one single job for which they were fabricated. They did not have the capacity for logic-based operations. The arrival of code handling machines, however, made them handle an unbelievable range of things using arithmatics and logic. These new machines could do ANYTHING that could be done with the help of arithmatics and logic, provided the task to be done could be expressed in terms of these two things. Since human thinking knows no limit, they did invent methods to code for everything from arithmetical calculations to ticket reservation, and from Desktop Publishing to voice recognition using computers. Instead of being dumb machines like bicycles, or stethoscope, computers became machines that were able to use a "decision process" and interact with users at the social level. Multiple levels of codes were needed to arrive at this stage, but it was done successfully.

The future of coding is unusually bright because we already know what to do. The bottleneck is only that raw computing power needed to implement what we know is not available yet. Once that bottleneck is crossed, multi-level coding will become so easy that what the computers would do might amaze even the most imaginative visionary. A corresponding breakthrough in algorithm would help man to touch the sky. Maybe you might not need me to write this article that day because a better one can be produced by my bot-assisted notebook computer in a fraction of the time I needed to compose it. Of course, I am joking. Machines will fortunately never replace humans. If they do, we deserve to quit our place in the Universe!
Dr. Johnson C. Philip, the President of TGSAT, is an internationally known physicist, theologican, and communicator