Getting bored with history lessons

Last post’s investigation into the post-Babbage history of computers took us up to around the end of the Second World War, before the computer age could really be said to have kicked off. However, with the coming of Alan Turing the biggest stumbling block for the intellectual development of computing as a science had been overcome, since it now clearly understood what it was and where it was going. From then on, therefore, the history of computing is basically one long series of hardware improvements and business successes, and the only thing of real scholarly interest was Moore’s law. This law is an unofficial, yet surprisingly accurate, model of the exponential growth in the capabilities of computer hardware, stating that every 18 months computing hardware gets either twice as powerful, half the size, or half the price for the same other specifications. This law was based on a 1965 paper by Gordon E Moore, who noted that the number of transistors on integrated circuits had been doubling every two years since their invention 7 years earlier. The modern day figure of an 18-monthly doubling in performance comes from an Intel executive’s estimate based on both the increasing number of transistors and their getting faster & more efficient… but I’m getting sidetracked. The point I meant to make was that there is no point me continuing with a potted history of the last 70 years of computing, so in this post I wish to get on with the business of exactly how (roughly fundamentally speaking) computers work.

A modern computer is, basically, a huge bundle of switches- literally billions of the things. Normal switches are obviously not up to the job, being both too large and requiring an electromechanical rather than purely electrical interface to function, so computer designers have had to come up with electrically-activated switches instead. In Colossus’ day they used vacuum tubes, but these were large and prone to breaking so, in the late 1940s, the transistor was invented. This is a marvellous semiconductor-based device, but to explain how it works I’m going to have to go on a bit of a tangent.

Semiconductors are materials that do not conduct electricity freely and every which way like a metal, but do not insulate like a wood or plastic either- sometimes they conduct, sometimes they don’t. In modern computing and electronics, silicon is the substance most readily used for this purpose. For use in a transistor, silicon (an element with four electrons in its outer atomic ‘shell’) must be ‘doped’ with other elements, meaning that they are ‘mixed’ into the chemical, crystalline structure of the silicon. Doping with a substance such as boron, with three electrons in its outer shell, creates an area with a ‘missing’ electron, known as a hole. Holes have, effectively, a positive charge compared a ‘normal’ area of silicon (since electrons are negatively charged), so this kind of doping produces what is known as p-type silicon. Similarly, doping with something like phosphorus, with five outer shell electrons, produces an excess of negatively-charged electrons and n-type silicon. Thus electrons, and therefore electricity (made up entirely of the net movement of electrons from one area to another) finds it easy to flow from n- to p-type silicon, but not very well going the other way- it conducts in one direction and insulates in the other, hence a semiconductor. However, it is vital to remember that the p-type silicon is not an insulator and does allow for free passage of electrons, unlike pure, undoped silicon. A transistor generally consists of three layers of silicon sandwiched together, in order NPN or PNP depending on the practicality of the situation, with each layer of the sandwich having a metal contact or ‘leg’ attached to it- the leg in the middle is called the base, and the ones at either side are called the emitter and collector.

Now, when the three layers of silicon are stuck next to one another, some of the free electrons in the n-type layer(s) jump to fill the holes in the adjacent p-type, creating areas of neutral, or zero, charge. These are called ‘depletion zones’ and are good insulators, meaning that there is a high electrical resistance across the transistor and that a current cannot flow between the emitter and collector despite usually having a voltage ‘drop’ between them that is trying to get a current flowing. However, when a voltage is applied across the collector and base a current can flow between these two different types of silicon without a problem, and as such it does. This pulls electrons across the border between layers, and decreases the size of the depletion zones, decreasing the amount of electrical resistance across the transistor and allowing an electrical current to flow between the collector and emitter. In short, one current can be used to ‘turn on’ another.

Transistor radios use this principle to amplify the signal they receive into a loud, clear sound, and if you crack one open you should be able to see some (well, if you know what you’re looking for). However, computer and manufacturing technology has got so advanced over the last 50 years that it is now possible to fit over ten million of these transistor switches onto a silicon chip the size of your thumbnail- and bear in mind that the entire Colossus machine, the machine that cracked the Lorenz cipher, contained only ten thousand or so vacuum tube switches all told. Modern technology is a wonderful thing, and the sheer achievement behind it is worth bearing in mind next time you get shocked over the price of a new computer (unless you’re buying an Apple- that’s just business elitism).

…and dammit, I’ve filled up a whole post again without getting onto what I really wanted to talk about. Ah well, there’s always next time…

(In which I promise to actually get on with talking about computers)

A Continued History

This post looks set to at least begin by following on directly from my last one- that dealt with the story of computers up to Charles Babbage’s difference and analytical engines, whilst this one will try to follow the history along from there until as close to today as I can manage, hopefully getting in a few of the basics of the workings of these strange and wonderful machines.

After Babbage’s death as a relatively unknown and unloved mathematician in 1871, the progress of the science of computing continued to tick over. A Dublin accountant named Percy Ludgate, independently of Babbage’s work, did develop his own programmable, mechanical computer at the turn of the century, but his design fell into a similar degree of obscurity and hardly added anything new to the field. Mechanical calculators had become viable commercial enterprises, getting steadily cheaper and cheaper, and as technological exercises were becoming ever more sophisticated with the invention of the analogue computer. These were, basically a less programmable version of the difference engine- mechanical devices whose various cogs and wheels were so connected up that they would perform one specific mathematical function to a set of data. James Thomson in 1876 built the first, which could solve differential equations by integration (a fairly simple but undoubtedly tedious mathematical task), and later developments were widely used to collect military data and for solving problems concerning numbers too large to solve by human numerical methods. For a long time, analogue computers were considered the future of modern computing, but since they solved and modelled problems using physical phenomena rather than data they were restricted in capability to their original setup.

A perhaps more significant development came in the late 1880s, when an American named Herman Hollerith invented a method of machine-readable data storage in the form of cards punched with holes. These had been around for a while to act rather like programs, such as the holed-paper reels of a pianola or the punched cards used to automate the workings of a loom, but this was the first example of such devices being used to store data (although Babbage had theorised such an idea for the memory systems of his analytical engine). They were cheap, simple, could be both produced and read easily by a machine, and were even simple to dispose of. Hollerith’s team later went on to process the data of the 1890 US census, and would eventually become most of IBM. The pattern of holes on these cards could be ‘read’ by a mechanical device with a set of levers that would go through a hole if there was one present, turning the appropriate cogs to tell the machine to count up one. This system carried on being used right up until the 1980s on IBM systems, and could be argued to be the first programming language.

However, to see the story of the modern computer truly progress we must fast forward to the 1930s. Three interesting people and acheivements came to the fore here: in 1937 George Stibitz, and American working in Bell Labs, built an electromechanical calculator that was the first to process data digitally using on/off binary electrical signals, making it the first digital. In 1936, a bored German engineering student called Konrad Zuse dreamt up a method for processing his tedious design calculations automatically rather than by hand- to this end he devised the Z1, a table-sized calculator that could be programmed to a degree via perforated film and also operated in binary. His parts couldn’t be engineered well enough for it to ever work properly, but he kept at it to eventually build 3 more models and devise the first programming language. However, perhaps the most significant figure of 1930s computing was a young, homosexual, English maths genius called Alan Turing.

Turing’s first contribution to the computing world came in 1936, when he published a revolutionary paper showing that certain computing problems cannot be solved by one general algorithm. A key feature of this paper was his description of a ‘universal computer’, a machine capable of executing programs based on reading and manipulating a set of symbols on a strip of tape. The symbol on the tape currently being read would determine whether the machine would move up or down the strip, how far, and what it would change the symbol to, and Turing proved that one of these machines could replicate the behaviour of any computer algorithm- and since computers are just devices running algorithms, they can replicate any modern computer too. Thus, if a Turing machine (as they are now known) could theoretically solve a problem, then so could a general algorithm, and vice versa if it couldn’t. Not only that, but since modern computers cannot multi-task on the. These machines not only lay the foundations for computability and computation theory, on which nearly all of modern computing is built, but were also revolutionary as they were the first theorised to use the same medium for both data storage and programs, as nearly all modern computers do. This concept is known as a von Neumann architecture, after the man who first pointed out and explained this idea in response to Turing’s work.

Turing machines contributed one further, vital concept to modern computing- that of Turing-completeness. A Turing-complete system was defined as a single Turing machine (known as a Universal Turing machine) capable of replicating the behaviour of any other theoretically possible Turing machine, and thus any possible algorithm or computable sequence. Charles Babbage’s analytical engine would have fallen into that class had it ever been built, in part because it was capable of the ‘if X then do Y’ logical reasoning that characterises a computer rather than a calculator. Ensuring the Turing-completeness of a system is a key part of designing a computer system or programming language to ensure its versatility and that it is capable of performing all the tasks that could be required of it.

Turing’s work had laid the foundations for nearly all the theoretical science of modern computing- now all the world needed was machines capable of performing the practical side of things. However, in 1942 there was a war on, and Turing was being employed by the government’s code breaking unit at Bletchley Park, Buckinghamshire. They had already cracked the German’s Enigma code, but that had been a comparatively simple task since they knew the structure and internal layout of the Enigma machine. However, they were then faced by a new and more daunting prospect: the Lorenz cipher, encoded by an even more complex machine for which they had no blueprints. Turing’s genius, however, apparently knew no bounds, and his team eventually worked out its logical functioning. From this a method for deciphering it was formulated, but it required an iterative process that took hours of mind-numbing calculation to get a result out. A faster method of processing these messages was needed, and to this end an engineer named Tommy Flowers designed and built Colossus.

Colossus was a landmark of the computing world- the first electronic, digital, and partially programmable computer ever to exist. It’s mathematical operation was not highly sophisticated- it used vacuum tubes containing light emission and sensitive detection systems, all of which were state-of-the-art electronics at the time, to read the pattern of holes on a paper tape containing the encoded messages, and then compared these to another pattern of holes generated internally from a simulation of the Lorenz machine in different configurations. If there were enough similarities (the machine could obviously not get a precise matching since it didn’t know the original message content) it flagged up that setup as a potential one for the message’s encryption, which could then be tested, saving many hundreds of man-hours. But despite its inherent simplicity, its legacy is simply one of proving a point to the world- that electronic, programmable computers were both possible and viable bits of hardware, and paved the way for modern-day computing to develop.

Bouncing horses

I have , over recent months, built up a rule concerning posts about YouTube videos, partly on the grounds that it’s bloody hard to make a full post out of them but also because there are most certainly a hell of a lot of good ones out there that I haven’t heard of, so any discussion of them is sure to be incomplete and biased, which I try to avoid wherever possible. Normally, this blog also rarely delves into what might be even vaguely dubbed ‘current affairs’, but since it regularly does discuss the weird and wonderful world of the internet and its occasional forays into the real world I thought that I might make an exception; today, I’m going to be talking about Gangnam Style.

Now officially the most liked video in the long and multi-faceted history of YouTube (taking over from the previous record holder and a personal favourite, LMFAO’s Party Rock Anthem), this music video by Korean rapper & pop star PSY was released over two and a half months ago, and for the majority of that time it lay in some obscure and foreign corner of the internet. Then, in that strange way that random videos, memes and general random bits and pieces are wont to do online, it suddenly shot to prominence thanks to the web collectively pissing itself over the sight of a chubby Korean bloke in sunglasses doing ‘the horse riding dance’. Quite how this was even discovered by some casual YouTube-surfer is something of a mystery to me given that said dance doesn’t even start for a good minute and a half or so, but the fact remains that it was, and that it is now absolutely bloody everywhere. Only the other day it became the first ever Korean single to reach no.1 in the UK charts, despite not having been translated from its original language, and has even prompted a dance off between rival Thai gangs prior to a gunfight. Seriously.

Not that it has met with universal appeal though. I’m honestly surprised that more critics didn’t get up in their artistic arms at the sheer ridiculousness of it, and the apparent lack of reason for it to enjoy the degree of success that it has (although quite a few probably got that out of their system after Call Me Maybe), but several did nonetheless. Some have called it ‘generic’ in music terms, others have found its general ridiculousness more tiresome and annoying than fun, and one Australian journalist commented that the song “makes you wonder if you have accidentally taken someone else’s medication”. That such criticism has been fairly limited can be partly attributed to the fact that the song itself is actually intended to be a parody anyway. Gangnam is a classy, fashionable district of the South Korean capital Seoul (PSY has likened it to Beverly Hills in California), and gangnam style is a Korean phrase referring to the kind of lavish & upmarket (if slightly pretentious) lifestyle of those who live there; or, more specifically, the kind of posers & hipsters who claim to affect ‘the Gangnam Style’. The song’s self-parody comes from the contrast between PSY’s lyrics, written from the first-person perspective of such a poser, and his deliberately ridiculous dress and dance style.

Such an act of deliberate self-parody has certainly helped to win plaudits from serious music critics, who have found themselves to be surprisingly good-humoured once told that the ridiculousness is deliberate and therefore actually funny- however, it’s almost certainly not the reason for the video’s over 300 million YouTube views, most of which surely go to people who’ve never heard of Gangnam, and certainly have no idea of the people PSY is mocking. In fact, there have been several different theories proposed as to why its popularity has soared quite so violently.

Most point to PSY’s very internet-friendly position on his video’s copyright. The Guardian claim that PSY has in fact waived his copyright to the video, but what is certain is that he has neglected to take any legal action on the dozens of parodies and alternate versions of his video, allowing others to spread the word in their own, unique ways and giving it enormous potential to spread, and spread far. These parodies have been many and varied in content, author and style, ranging from the North Korean government’s version aimed at satirising the South Korean president Park Guen-hye (breaking their own world record for most ridiculous entry into a political pissing contest, especially given that it mocks her supposed devotion to an autocratic system of government, and one moreover that ended over 30 years ago), to the apparently borderline racist “Jewish Style” (neither of which I have watched, so cannot comment on). One parody has even sparked a quite significant legal case, with 14 California lifeguards being fired for filming, dancing in, or even appearing in the background of, their parody video “Lifeguard Style” and investigation has since been launched by the City Council in response to the thousands of complaints and suggestions, one even by PSY himself, that the local government were taking themselves somewhat too seriously.

However, by far the most plausible reason for he mammoth success of the video is also the simplest; that people simply find it funny as hell. Yes, it helps a lot that such a joke was entirely intended (let’s be honest, he probably couldn’t have come up with quite such inspired lunacy by accident), and yes it helps how easily it has been able to spread, but to be honest the internet is almost always able to overcome such petty restrictions when it finds something it likes. Sometimes, giggling ridiculousness is just plain funny, and sometimes I can’t come up with a proper conclusion to these posts.

P.S. I forgot to mention it at the time, but last post was my 100th ever published on this little bloggy corner of the internet. Weird to think it’s been going for over 9 months already. And to anyone who’s ever stumbled across it, thank you; for making me feel a little less alone.

What we know and what we understand are two very different things…

If the whole Y2K debacle over a decade ago taught us anything, it was that the vast majority of the population did not understand the little plastic boxes known as computers that were rapidly filling up their homes. Nothing especially wrong or unusual about this- there’s a lot of things that only a few nerds understand properly, an awful lot of other stuff in our life to understand, and in any case the personal computer had only just started to become commonplace. However, over 12 and a half years later, the general understanding of a lot of us does not appear to have increased to any significant degree, and we still remain largely ignorant of these little feats of electronic witchcraft. Oh sure, we can work and operate them (most of us anyway), and we know roughly what they do, but as to exactly how they operate, precisely how they carry out their tasks? Sorry, not a clue.

This is largely understandable, particularly given the value of ‘understand’ that is applicable in computer-based situations. Computers are a rare example of a complex system that an expert is genuinely capable of understanding, in minute detail, every single aspect of the system’s working, both what it does, why it is there, and why it is (or, in some cases, shouldn’t be) constructed to that particular specification. To understand a computer in its entirety, therefore, is an equally complex job, and this is one very good reason why computer nerds tend to be a quite solitary bunch, with quite few links to the rest of us and, indeed, the outside world at large.

One person who does not understand computers very well is me, despite the fact that I have been using them, in one form or another, for as long as I can comfortably remember. Over this summer, however, I had quite a lot of free time on my hands, and part of that time was spent finally relenting to the badgering of a friend and having a go with Linux (Ubuntu if you really want to know) for the first time. Since I like to do my background research before getting stuck into any project, this necessitated quite some research into the hows and whys of its installation, along with which came quite a lot of info as to the hows and practicalities of my computer generally. I thought, then, that I might spend the next couple of posts or so detailing some of what I learned, building up a picture of a computer’s functioning from the ground up, and starting with a bit of a history lesson…

‘Computer’ was originally a job title, the job itself being akin to accountancy without the imagination. A computer was a number-cruncher, a supposedly infallible data processing machine employed to perform a range of jobs ranging from astronomical prediction to calculating interest. The job was a fairly good one, anyone clever enough to land it probably doing well by the standards of his age, but the output wasn’t. The human brain is not built for infallibility and, not infrequently, would make mistakes. Most of these undoubtedly went unnoticed or at least rarely caused significant harm, but the system was nonetheless inefficient. Abacuses, log tables and slide rules all aided arithmetic manipulation to a great degree in their respective fields, but true infallibility was unachievable whilst still reliant on the human mind.

Enter Blaise Pascal, 17th century mathematician and pioneer of probability theory (among other things), who invented the mechanical calculator aged just 19, in 1642. His original design wasn’t much more than a counting machine, a sequence of cogs and wheels so constructed as to able to count and convert between units, tens, hundreds and so on (ie a turn of 4 spaces on the ‘units’ cog whilst a seven was already counted would bring up eleven), as well as being able to work with currency denominations and distances as well. However, it could also subtract, multiply and divide (with some difficulty), and moreover proved an important point- that a mechanical machine could cut out the human error factor and reduce any inaccuracy to one of simply entering the wrong number.

Pascal’s machine was both expensive and complicated, meaning only twenty were ever made, but his was the only working mechanical calculator of the 17th century. Several, of a range of designs, were built during the 18th century as show pieces, but by the 19th the release of Thomas de Colmar’s Arithmometer, after 30 years of development, signified the birth of an industry. It wasn’t a large one, since the machines were still expensive and only of limited use, but de Colmar’s machine was the simplest and most reliable model yet. Around 3,000 mechanical calculators, of various designs and manufacturers, were sold by 1890, but by then the field had been given an unexpected shuffling.

Just two years after de Colmar had first patented his pre-development Arithmometer, an Englishmen by the name of Charles Babbage showed an interesting-looking pile of brass to a few friends and associates- a small assembly of cogs and wheels that he said was merely a precursor to the design of a far larger machine: his difference engine. The mathematical workings of his design were based on Newton polynomials, a fiddly bit of maths that I won’t even pretend to understand, but that could be used to closely approximate logarithmic and trigonometric functions. However, what made the difference engine special was that the original setup of the device, the positions of the various columns and so forth, determined what function the machine performed. This was more than just a simple device for adding up, this was beginning to look like a programmable computer.

Babbage’s machine was not the all-conquering revolutionary design the hype about it might have you believe. Babbage was commissioned to build one by the British government for military purposes, but since Babbage was often brash, once claiming that he could not fathom the idiocy of the mind that would think up a question an MP had just asked him, and prized academia above fiscal matters & practicality, the idea fell through. After investing £17,000 in his machine before realising that he had switched to working on a new and improved design known as the analytical engine, they pulled the plug and the machine never got made. Neither did the analytical engine, which is a crying shame; this was the first true computer design, with two separate inputs for both data and the required program, which could be a lot more complicated than just adding or subtracting, and an integrated memory system. It could even print results on one of three printers, in what could be considered the first human interfacing system (akin to a modern-day monitor), and had ‘control flow systems’ incorporated to ensure the performing of programs occurred in the correct order. We may never know, since it has never been built, whether Babbage’s analytical engine would have worked, but a later model of his difference engine was built for the London Science Museum in 1991, yielding accurate results to 31 decimal places.

…and I appear to have run on a bit further than intended. No matter- my next post will continue this journey down the history of the computer, and we’ll see if I can get onto any actual explanation of how the things work.