Computer Programmer Quotes

Any fool can write code that a computer can understand. Good programmers write code that humans can understand.

That's the thing about people who think they hate computers. What they really hate is lousy programmers.

The computer programmer is a creator of universes for which he alone is the lawgiver. No playwright, no stage director, no emperor, however powerful, has ever exercised such absolute authority to arrange a stage or field of battle and to command such unswervingly dutiful actors or troops.

The best programs are written so that computing machines can perform them quickly and so that human beings can understand them clearly. A programmer is ideally an essayist who works with traditional aesthetic and literary forms as well as mathematical concepts, to communicate the way that an algorithm works and to convince a reader that the results will be correct.

A computer is a stupid machine with the ability to do incredibly smart things, while computer programmers are smart people with the ability to do incredibly stupid things.

Well, writing novels is incredibly simple: an author sits down…and writes. Granted, most writers I know are a bit strange. Some, downright weird. But then again, you’d have to be. To spend hundreds and hundreds of hours sitting in front of a computer screen staring at lines of information is pretty tedious. More like a computer programmer. And no matter how cool the Matrix made looking at code seem, computer programmers are even weirder than authors.

All great programmers learn the same way. They poke the box. They code something and see what the computer does. They change it and see what the computer does. They repeat the process again and again until they figure out how the box works.

The best computer programmers never write a new program when they can use an old one for a new job.

Most of us know that the media tell us our bodies are imperfect - too fat, to smelly, too wrinkled, or too soft. And, even though we may know it’s horseshit, these messages still seep into our brains and mess with our self-esteem. In a media-saturated country where most images of women and men have been photoshopped to perfection, it’s hard to find a living supermodel (much less a computer programmer), who doesn’t wish she had sexier earlobes or a tighter ass. So, buck up, even the prettiest bombshell has body insecurities. You can spend your life thinking your butt’s too big (or your cock’s too small) or feeling sexy as hell. Make the choice to appreciate your body as it is.

While we may continue to use the words smart and stupid, and while IQ tests may persist for certain purposes, the monopoly of those who believe in a single general intelligence has come to an end. Brain scientists and geneticists are documenting the incredible differentiation of human capacities, computer programmers are creating systems that are intelligent in different ways, and educators are freshly acknowledging that their students have distinctive strengths and weaknesses.

Monty Python is, for reasons best known to nobody, rather popular with computer programmers. There’s even a programming language called Python, based on their sketches.

With software there are only two possibilites: either the users control the programme or the programme controls the users. If the programme controls the users, and the developer controls the programme, then the programme is an instrument of unjust power.

Computer programmers are highly susceptible to the just world fallacy (that their economic good fortune is the product of virtue rather than circumstance) and the fallacy of transferable expertise (that being competent in one field means they’re competent in others).

DON’T GIVE UP! When the battle seems endless and you think you’ll never make it, remember that you are reprogramming a very carnal, fleshly, worldly mind to think as God thinks. Impossible? No! Difficult? Yes! But, just think, you have God on your team. I believe He is the best “computer programmer” around. (Your mind is like a computer that has had a lifetime of garbage programmed into it.) God is working on you; at least, He is if you have invited Him to have control of your thoughts. He is reprogramming your mind. Just keep cooperating with Him—and don’t give up!

The best computer programmers are much better than novices at remembering the overall structure of programs because they understand better what they’re intended to do and how.

You are not reading this book because a teacher assigned it to you, you are reading it because you have a desire to learn, and wanting to learn is the biggest advantage you can have.

You Can't Write Perfect Software. Did that hurt? It shouldn't. Accept it as an axiom of life. Embrace it. Celebrate it. Because perfect software doesn't exist. No one in the brief history of computing has ever written a piece of perfect software. It's unlikely that you'll be the first. And unless you accept this as a fact, you'll end up wasting time and energy chasing an impossible dream.

The corollary of constant change is ignorance. This is not often talked about: we computer experts barely know what we're doing. We're good at fussing and figuring out. We function well in a sea of unknowns. Our experience has only prepared us to deal with confusion. A programmer who denies this is probably lying, or else is densely unaware of himself.

When a computer creates art, who is the artist—the computer or the programmer? At MIT, a recent exhibit of highly accomplished algorithmic art had put an awkward spin on the Harvard humanities course: Is Art What Makes Us Human?

As a feminist I feel immediately guilty because everyone is trying to encourage girls into STEM subjects now, but to be honest I’m not dedicated enough to the Vagenda to force myself to become a computer programmer.

What one programmer can do in one month, two programmers can do in two months.

Babbage had most of this system sketched out by 1837, but the first true computer to use this programmable architecture didn’t appear for more than a hundred years.

How many computer programmers does it take to change a light bulb? Are you kidding? That's a hardware problem!

if you program a purpose into a computer program, does that constitute its will? Does it have free will, if a programmer programmed its purpose?

(To think like a computer programmer, it helps to be lazy.)

An Essay from Andy Weir: How Science Made Me a Writer I’m a nerd. Okay, a lot of people say that these days. But I really am. I was hired as a computer programmer for a national laboratory at age fifteen.

Computer science education cannot make anybody an expert programmer any more than studying brushes and pigment can make somebody an expert painter.

The Vedic viewpoint presents a type of linguistic realism in which reality is the 'text' which is being processed by the observer. Reality can also be modified by adding text to it similar to how a programmer programs a computer by inputting a computer program.

if you program a purpose into a computer program, does that constitute its will? Does it have free will, if a programmer programmed its purpose? Is that programming any different from the way we are programmed by our genes and brains? Is a programmed will a servile will? Is human will a servile will? And is not the servile will the home and source of all feelings of defilement, infection, transgression, and rage?

In other words, evolution is neither a free-for-all, nor the execution of a rigidly predetermined computer programme. It could be compared to a musical composition whose possibilities are limited by the rules of harmony and the structure of the diatonic scales-which, however, permit an inexhaustible number of original creations. Or it could be compared to the game of chess obeying fixed rules but with equally inexhaustible variations.

The real problem is that programmers have spent far too much time worrying about efficiency in the wrong places and at the wrong times; premature optimization is the root of all evil (or at least most of it) in programming.

Like Ada Lovelace, Turing was a programmer, looking inward to the step-by-step logic of his own mind. He imagined himself as a computer. He distilled mental procedures into their smallest constituent parts, the atoms of information processing.

For a long time it puzzled me how something so expensive, so leading edge, could be so useless, and then it occurred to me that a computer is a stupid machine with the ability to do incredibly smart things, while computer programmers are smart people with the ability to do incredibly stupid things. They are, in short, a perfect match.

Our brains are like computers; it's our responsibility to programme them well, daily, and remove the viruses.

After all, computer science was man-made. All the answers had to be there.

Simple explanation for kids: Seen as if a computer game: God is the programmer/creator of all the universe and all things, and Jesus would be his avatar/character in the game.

When a computer creates art, who is the artist—the computer or the programmer?

Each mobile phone today – indeed, each washing machine – has more computing power than NASA could deploy on the Apollo programme.

The computer programmer creates the only path available to the computer user; the effect of his decisions on others is masked by their abstraction.

Richard Stallman, a free-lance computer programmer, loudly proclaimed that information should be free.

The second reason that deep work is valuable is because the impacts of the digital network revolution cut both ways. If you can create something useful, its reachable audience (e.g., employers or customers) is essentially limitless—which greatly magnifies your reward. On the other hand, if what you’re producing is mediocre, then you’re in trouble, as it’s too easy for your audience to find a better alternative online. Whether you’re a computer programmer, writer, marketer, consultant, or entrepreneur, your situation has become similar to Jung trying to outwit Freud, or Jason Benn trying to hold his own in a hot start-up: To succeed you have to produce the absolute best stuff you’re capable of producing—a task that requires depth.

In context the computer programmers appeared idle. They sat quietly, stared into their screens and sipped cappuccinos. And yet they were by far the most important people on board Hyperion.

This is why so many of the best programmers are libertarians. In our world, you sink or swim, and there are no excuses. When those far removed from the creation of wealth — undergraduates, reporters, politicians — hear that the richest 5% of the people have half the total wealth, they tend to think injustice! An experienced programmer would be more likely to think is that all? The top 5% of programmers probably write 99% of the good software.

The computer programmer is a creator of universes for which he alone is responsible. Universes of virtually unlimited complexity can be created in the form of computer programs. — Joseph Weizenbaum, Computer Power and Human Reason

Neither Rafi nor I saw what was happening. No one did. That computers would take over our lives: Sure. But the way that they would turn us into different beings? The full flavor of our translated hearts and minds? Not even my most enlightened fellow programmers at CRIK foresaw that with any resolution. Sure, they predicted personal, portable Encyclopedia Britannicas and group real-time teleconferencing and personal assistants that could teach you how to write better. But Facebook and WhatsApp and TikTok and Bitcoin and QAnon and Alexa and Google Maps and smart tracking ads based on keywords stolen from your emails and checking your likes while at a urinal and shopping while naked and insanely stupid but addictive farming games that wrecked people’s careers and all the other neural parasites that now make it impossible for me to remember what thinking and feeling and being were really like, back then? Not even close.

Russians had a reputation for being the best programmers on Wall Street, and Serge thought he knew why: They had been forced to learn to program computers without the luxury of endless computer time. Many years later, when he had plenty of computer time, Serge still wrote out new programs on paper before typing them into the machine. “In Russia, time on the computer was measured in minutes,” he said. “When you write a program, you are given a tiny time slot to make it work.

Poke the box How do computer programmers learn their art? Is there a step-by-step process that guarantees you’ll get good? All great programmers learn the same way. They poke the box. They code something and see what the computer does. They change it and see what the computer does. They repeat the process again and again until they figure out how the box works. The box might be a computer or it might be a market or it might be a customer or it might be your boss. It’s a puzzle, one that can be solved in only one way—by poking.

It was an IBM machine, archaic now but gaudy then. The university owned it, in effect, and it lay inside a room that none but the machine’s professional caretakers could enter during the day. But Alsing found out that a student could just walk into that room at night and play with the computer. Alsing didn’t drink much and he never took any other drugs. “I was a midnight programmer,” he confessed.

So, when Cole was two and I was four, we moved to Goshen Falls. Lucky us! The whole town is three blocks long. We have a cute little farm with a cute little farmhouse. And even though Mom and Dad are computer programmers — not farmers — we have a backyard full of chickens.

A great programmer, on a roll, could create a million dollars worth of wealth in a couple weeks. A mediocre programmer over the same period will generate zero or even neg- ative wealth (e.g. by introducing bugs). This is why so many of the best programmers are libertarians.

What does AI have to do with me? Isn't it a distant future that has nothing to do with me, not a scientist, a technician, or a computer programmer? Well, Artificial intelligence is not a story of someone who has nothing to do with it, but the fact is, it is now everyone's story.

Intellectual curiosity was not one of the motives on the FBI’s list. Indeed, the whole concept seemed foreign to them. Those in authority tend to be annoyed by hackers’ general attitude of disobedience. But that disobedience is a byproduct of the qualities that make them good programmers.

Most organised abuser groups call each particular training a “programme”, as if you were a computer. Many specific trained behaviours have “on” and “off” triggers or switches. Some personality systems are set up with an inner world full of wires or strings that connect switches to their effects. These can facilitate a series of actions by a series of insiders. For example, one part watches the person function in the outside world, and presses a button if he or she sees the person disobeying instructions. The button is connected to an internal wire, which rings a bell in the ear of another part. This part then engages in his or her trained behaviour, opening a door to release the pain of a rape, or cutting the person's arm in a certain pattern, or pushing out a child part. So the watcher has no idea of who the other part is or what she or he does. These events can be quite complicated.

The word “hacker” has two very different meanings. The people I knew who called themselves hackers were software wizards who managed to creatively program themselves out of tight corners. They knew all the nooks and crannies of the operating system. Not dull software engineers who put in forty hours a week, but creative programmers who can’t leave the computer until the machine’s satisfied. A hacker identifies with the computer, knowing it like a friend.

Programmers are always surrounded by complexity; we cannot avoid it. Our applications are complex because we are ambitious to use our computers in ever more sophisticated ways. Programming is complex because of the large number of conflicting objectives for each of our programming projects. If our basic tool, the language in which we design and code our programs, is also complicated, the language itself becomes part of the problem rather than part of its solution.

Ultimately, man should not ask what the meaning of his life is, but rather must recognize that it is he who is asked. In a word, each man is questioned by life; and he can only answer to life by answering for his own life; to life he can only respond by being responsible.” Personal responsibility, or proactivity, is fundamental to the first creation. Returning to the computer metaphor, Habit 1 says, “You are the programmer.” Habit 2, then, says, “Write the program.

There’s a gravity and sense of importance inherent in deep work—whether you’re Ric Furrer smithing a sword or a computer programmer optimizing an algorithm. Gallagher’s theory, therefore, predicts that if you spend enough time in this state, your mind will understand your world as rich in meaning and importance.

When I deal with smart IT programmers, I have a strong impression that their job has much in common with the phenomenon of how the Lord arranged the Universe and created genetics (cells, DNA, molecules, etc.). Both genetics and computer programming create their magic by performing highly intelligent coding work.

Take a simple pocket pen, so cheap that they are given away as advertising. Back of it lie several sorts of chemists, metallurgists, synthetic polymer experts, mechanical engineers, extrusion presses, computer programmers, computers, computer technicians, toolmakers, electrical engineers, a planet-wide petroleum industry, five or more sorts of mines with mining engineers, geologists, miners, railroads, steamships, production engineers, management specialists, merchandizing psychologists—et cetera to a splitting headache. It is impossible even to list the myriad special skills that underlie even the most trivial trade item of our enormously complex and interdependent industrial web.

It is common knowledge in the programmer's circle that almost every smartphone in the world is infected with some form of trojan.

In our online world there is no way for a regular civilian to keep their phone uninfected. And that includes everybody except skilled and resourceful programmers.

Programmers tend to be divided into tribes by the languages they use. More even than by the kinds of programs they write.

Although computer science tends to be thought of as a traditionally male-dominated field, the world’s first programmer was a woman.

Computer science is no more about computers than astronomy is about telescopes.” —Edsger W. Dijkstra

No amount of excellence on the part of a computer can lead to the solution of a problem if the problem has been incorrectly defined by the programmer. In

What a waste of time it would be to insist that everyone develop each of the specialties we call upon to an equal level. We'd get bogged down in remedial training programs, trying to get the cornet players up to speed with the computer programmers, sacrificing the tends to be exceptional in so many individual situations in order to be average in all of them.

Tests are stories we tell the next generation of programmers on a project.

Programmers are like magicians who fool everyone into thinking they are perfect and never wrong, but it’s all an act. They make mistakes all the time.

perfect software doesn't exist. No one in the brief history of computing has ever written a piece of perfect software.

It has to become second nature, for a programmer, to notice when a concept is begging to be abstracted into a new word.

Those in authority tend to be annoyed by hackers’ general attitude of disobedience. But that disobedience is a byproduct of the qualities that make them good programmers.

Pascal (Object Pascal - Free Pascal) for real programmers, Delphi for Nerds... C/C++ for people who always wishes to do things like reinventing the wheel.

When programmers speak of "computer literacy," they are drawing red lines around ethnic groups, too, yet few have pointed this out.

However, for programmers, combining rich, flexible human thought with the rigid constraints of a digital computer exposes the power and the deepest flaws of both.

C gives the programmer what the programmer wants; few restrictions, few complaints... C++ maintains the original spirit of C, that the programmer not the language is in charge.

Douglas Adams amusingly satirized computer addiction of exactly the kind that hit me. The target of his satire was the programmer who had a particular problem X, which needed solving. He could have written a program in five minutes to solve X and then got on and used his solution. But instead of just doing that, he spent days and weeks writing a more general program that could be used by anybody at any time to solve all similar problems of the general class of X. The fascination lies in the generality and in the purveying of an aesthetically pleasing, user-friendly product for the benefit of a population of hypothetical and very probably non-existent users – not in actually finding the answer to the particular problem X.

I found an entry for the Beidr, of the Unon Plane, an aggressive and enterprising people with highly advanced material technologies, who have been in trouble more than once with the Interplanary Agency for interfering on other planes. The tourist guidebook gives them the symbols that mean “of special interest to engineers, computer programmers, and systems analysts.”)

To paraphrase an old joke among programmers, “Writing code accounts for 90 percent of programming. Debugging code accounts for the other 90 percent.” Your computer will do only what you tell it to do; it won’t read your mind and do what you intended it to do. Even professional programmers create bugs all the time, so don’t feel discouraged if your program has a problem.

If you have programmers, they probably save their code in Git, which is the closest I can think of to a useful blockchain-like technology: it saves individual code edits as transactions in Merkle trees with tamper-evident hashes, and developers routinely copy entire Git repositories around, identifying them by hash. It’s a distributed ledger, but for computer programs rather than money.

Hollywood and similar “popular culture” sources of disinformation have assigned largely negative images to programmers. For example, we have all seen the solitary, fat, ugly nerd with no social skills who is obsessed with video games and breaking into other people’s computers. He (almost always a male) is as likely to want to destroy the world as he is to want to save it. Obviously, milder versions of such caricatures exist in real life, but in our experience they are no more frequent among software developers than they are among lawyers, police officers, car salesmen, journalists, artists, or politicians.

Rust’s central feature is ownership. Although the feature is straightforward to explain, it has deep implications for the rest of the language. All programs have to manage the way they use a computer’s memory while running. Some languages have garbage collection that constantly looks for no longer used memory as the program runs; in other languages, the programmer must explicitly allocate and free the memory. Rust uses a third approach: memory is managed through a system of ownership with a set of rules that the compiler checks at compile time. None of the ownership features slow down your program while it’s running.

NASA was able to send a man to the moon. Engineers in Silicon Valley were able to devise a way to put a programmable computer on a chip called a microprocessor. And ARPA created a network that could connect distant computers.

Usability, fundamentally, is a matter of bringing a bit of human rights into the world of computer-human interaction. It's a way to let our ideals shine through in our software, no matter how mundane the software is. You may think that you're stuck in a boring, drab IT department making mind-numbing inventory software that only five lonely people will ever use. But you have daily opportunities to show respect for humanity even with the most mundane software.

Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child's? If this were then subjected to an appropriate course of education one would obtain the adult brain.

You’re either remarkable or invisible,” says Seth Godin in his 2002 bestseller, Purple Cow.1 As he elaborated in a Fast Company manifesto he published on the subject: “The world is full of boring stuff—brown cows—which is why so few people pay attention…. A purple cow… now that would stand out. Remarkable marketing is the art of building things worth noticing.”2 When Giles read Godin’s book, he had an epiphany: For his mission to build a sustainable career, it had to produce purple cows, the type of remarkable projects that compel people to spread the word. But this left him with a second question: In the world of computer programming, where does one launch remarkable projects? He found his second answer in a 2005 career guide with a quirky title: My Job Went to India: 52 Ways to Save Your Job.3 The book was written by Chad Fowler, a well-known Ruby programmer who also dabbles in career advice for software developers.

The fact is that life is not a race: success in life isn’t determined by how well you do compared to other people. It’s determined by whether you are able to achieve whatever hopes and dreams you set for yourself: to build a great company, to write a great book, to excel as a computer programmer, to be a great teacher or a great plumber. None of that requires besting others; the favorable circumstances they enjoy can’t hold you back. Exactly the reverse is true.

Only one thing can save us. We have to increase our mastery of the world. All this damage has come about through our conquest of the world, but we have to go on conquering it until our rule is absolute. Then, when we’re in complete control, everything will be fine. We’ll have fusion power. No pollution. We’ll turn the rain on and off. We’ll grow a bushel of wheat in a square centimeter. We’ll turn the oceans into farms. We’ll control the weather—no more hurricanes, no more tornadoes, no more droughts, no more untimely frosts. We’ll make the clouds release their water over the land instead of dumping it uselessly into the oceans. All the life processes of this planet will be where they belong—where the gods meant them to be—in our hands. And we’ll manipulate them the way a programmer manipulates a computer.

Astronomers saw me that way. “Cliff, he’s not much of an astronomer, but what a computer hacker!” (The computer folks, of course, had a different view: “Cliff’s not much of a programmer, but what an astronomer!” At best, graduate school had taught me to keep both sides fooled.)

Shortly before she died in 2011, Jean Jennings Bartik reflected proudly on the fact that all the programmers who created the first general-purpose computer were women: “Despite our coming of age in an era when women’s career opportunities were generally quite confined, we helped initiate the era of the computer.

Stop pushing people into web development as if it is the only true career path. Instead, push people into computer science, programming, coding, etc. There is so much competition because everyone is doing it, you just create a lot of demoralized and disgruntled people. There is more to programming than web development.

Before you start to look at the bug, make sure that you are working on code that built cleanly—without warnings. We routinely set compiler warning levels as high as possible. It doesn’t make sense to waste time trying to find a problem that the computer could find for you! We need to concentrate on the harder problems at hand.

Instead of feeling like you are the computer genius, descending from computer heaven to save your poor customer from purgatory, turn the tables around. If you’re, for example, working in the insurance industry, think of your customer as a subject matter expert in insurance from which you have to learn in order to get your job done.

The government spying on people doesn’t literally make programmers write worse code. It just leads eventually to a world in which bad ideas will win. And because this is so important to hackers, they’re especially sensitive to it. They can sense totalitarianism approaching from a distance, as animals can sense an approaching thunderstorm.

If a model did anything too obviously bizarre—flooded the Sahara or tripled interest rates—the programmers would revise the equations to bring the output back in line with expectation. In practice, econometric models proved dismally blind to what the future would bring, but many people who should have known better acted as though they believed in the results. Forecasts of economic growth or unemployment were put forward with an implied precision of two or three decimal places. Governments and financial institutions paid for such predictions and acted on them, perhaps out of necessity or for want of anything better. Presumably they knew that such variables as “consumer optimism” were not as nicely measurable as “humidity” and that the perfect differential equations had not yet been written for the movement of politics and fashion. But few realized how fragile was the very process of modeling flows on computers, even when the data was reasonably trustworthy and the laws were purely physical, as in weather forecasting.

My mother has always loved piano music and hungered to play. When she was in her early sixties, she retired from her job as a computer programmer so that she could devote herself more fully to the piano. As she had done with her dog obsession, she took her piano education to an extreme. She bought not one, not two, but three pianos. One was the beautiful Steinway B, a small grand piano she purchased with a modest inheritance left by a friend of her parents’. She photocopied all of her music in a larger size so she could see it better and mounted it on manila folders. She practiced for several hours every day. When she wasn’t practicing the piano she was talking about the piano. I love pianos, too, and wrote an entire book about the life of one piano, a Steinway owned by the renowned pianist Glenn Gould. And I shared my mother’s love for her piano. During phone conversations, I listened raptly as she told me about the instrument’s cross-country adventures. Before bringing the Steinway north, my mother had mentioned that she was considering selling it. I was surprised, but instead of reminding her that, last I knew, she was setting it aside for me, I said nothing, unable to utter the simple words, “But, Mom, don’t you remember your promise?” If I did, it would be a way of asking for something, and asking my mother for something was always dangerous because of the risk of disappointment.

By failing to make the obvious connection between an openly misogynistic culture and the mysterious lack of women, Levy contributed to the myth of innately talented hackers being implicitly male. And, today, it’s hard to think of a profession more in thrall to brilliance bias than computer science. ‘Where are the girls that love to program?’ asked a high-school teacher who took part in a summer programme for advanced-placement computer-science teachers at Carnegie Mellon; ‘I have any number of boys who really really love computers,’ he mused. ‘Several parents have told me their sons would be on the computer programming all night if they could. I have yet to run into a girl like that.’ This may be true, but as one of his fellow teachers pointed out, failing to exhibit this behaviour doesn’t mean that his female students don’t love computer science. Recalling her own student experience, she explained how she ‘fell in love’ with programming when she took her first course in college. But she didn’t stay up all night, or even spend a majority of her time programming. ‘Staying up all night doing something is a sign of single-mindedness and possibly immaturity as well as love for the subject. The girls may show their love for computers and computer science very differently. If you are looking for this type of obsessive behavior, then you are looking for a typically young, male behavior. While some girls will exhibit it, most won’t.

Pham Nuwen spent years learning to program/explore. Programming went back to the beginning of time. It was a little like the midden out back of his father’s castle. Where the creek had worn that away, ten meters down, there were the crumpled hulks of machines—flying machines, the peasants said—from the great days of Canberra’s original colonial era. But the castle midden was clean and fresh compared to what lay within the Reprise’s local net. There were programs here that had been written five thousand years ago, before Humankind ever left Earth. The wonder of it—the horror of it, Sura said—was that unlike the useless wrecks of Canberra’s past, these programs still worked! And via a million million circuitous threads of inheritance, many of the oldest programs still ran in the bowels of the Qeng Ho system. Take the Traders’ method of timekeeping. The frame corrections were incredibly complex—and down at the very bottom of it was a little program that ran a counter. Second by second, the Qeng Ho counted from the instant that a human had first set foot on Old Earth’s moon. But if you looked at it still more closely. . .the starting instant was actually some hundred million seconds later, the 0-second of one of Humankind’s first computer operating systems. So behind all the top-level interfaces was layer under layer of support. Some of that software had been designed for wildly different situations. Every so often, the inconsistencies caused fatal accidents. Despite the romance of spaceflight, the most common accidents were simply caused by ancient, misused programs finally getting their revenge. “We should rewrite it all,” said Pham. “It’s been done,” said Sura, not looking up. She was preparing to go off-Watch, and had spent the last four days trying to root a problem out of the coldsleep automation. “It’s been tried,” corrected Bret, just back from the freezers. “But even the top levels of fleet system code are enormous. You and a thousand of your friends would have to work for a century or so to reproduce it.” Trinli grinned evilly. “And guess what—even if you did, by the time you finished, you’d have your own set of inconsistencies. And you still wouldn’t be consistent with all the applications that might be needed now and then.” Sura gave up on her debugging for the moment. “The word for all this is ‘mature programming environment.’ Basically, when hardware performance has been pushed to its final limit, and programmers have had several centuries to code, you reach a point where there is far more signicant code than can be rationalized. The best you can do is understand the overall layering, and know how to search for the oddball tool that may come in handy—take the situation I have here.” She waved at the dependency chart she had been working on. “We are low on working fluid for the coffins. Like a million other things, there was none for sale on dear old Canberra. Well, the obvious thing is to move the coffins near the aft hull, and cool by direct radiation. We don’t have the proper equipment to support this—so lately, I’ve been doing my share of archeology. It seems that five hundred years ago, a similar thing happened after an in-system war at Torma. They hacked together a temperature maintenance package that is precisely what we need.” “Almost precisely.

Ava was blessed with amazing beauty but was academically challenged. Angelina tried to give her a quick introduction to computers but was horrified at Ava’s lack of knowledge and complete failure to understand. Ava called the CD drawer the cup holder and honestly thought it was her holding her coffee or drink when typing. She thought the monitor was the telly and the mouse was the roller. She kept exiting programmes instead of closing documents and kept deleting items and forgetting to save things. Things happened Angelina’s computers that never happened before: programs failed to respond and the computer kept crashing. She typed e-mails and then printed them and put them in an envelope to post them, Angelina was speechless. She even killed a machine by constant abuse for the week. It just died the screen went blank and a message came up of fundamental hard drive failure, the monitor went black and the keyboard and mouse went dead and could not be restored. It went to the computer scrap yard, RIP. Angelina ran her out of the IT dept in their firm terrified she’d cause any more mayhem. She was the absolute blonde bombshell when it came to computers

This is echoed by King-scott (1996, 295), who warns that unless technology-related issues are integrated into translator-training programmes, there is a real danger that the university teaching of translation may become so remote from practice that it will be marginalized and consequently be widely perceived as irrelevant to the translation task. Tha gap between technological advances and pedagogical practices must be closed.

We are about to study the idea of a computational process. Computational processes are abstract beings that inhabit computers. As they evolve, processes manipulate other abstract things called data. The evolution of a process is directed by a pattern of rules called a program. People create programs to direct processes. In effect, we conjure the spirits of the computer with our spells. A computational process is indeed much like a sorcerer's idea of a spirit. It cannot be seen or touched. It is not composed of matter at all. However, it is very real. It can perform intellectual work. It can answer questions. It can affect the world by disbursing money at a bank or by controlling a robot arm in a factory. The programs we use to conjure processes are like a sorcerer's spells. They are carefully composed from symbolic expressions in arcane and esoteric programming languages that prescribe the tasks we want our processes to perform. A computational process, in a correctly working computer, executes programs precisely and accurately. Thus, like the sorcerer's apprentice, novice programmers must learn to understand and to anticipate the consequences of their conjuring. Even small errors (usually called bugs or glitches) in programs can have complex and unanticipated consequences.

... bright young men of disheveled appearance, often with sunken glowing eyes, can be seen sitting at computer consoles, their arms tensed and waiting to fire their fingers, already poised to strike, at the buttons and keys on which their attention seems to be riveted as a gambler’s on the rolling dice. When not so transfixed, they often sit at tables strewn with computer printouts over which they pore like possessed students of a cabbalistic text. They work until they nearly drop, twenty, thirty hours at a time. Their food, if they arrange it, is brought to them: coffee, Cokes, sandwiches. If possible, they sleep on cots near the printouts. Their rumpled clothes, their unwashed and unshaven faces, and their uncombed hair all testify that they are oblivious to their bodies and to the world in which they move. These are computer bums, compulsive programmers ...

STOP STOPPING A growing body of research shows that often what looks like “multitasking” is actually “rapid task-switching,” especially when technology is involved. One study of computer programmers showed that as they attempted to work, they interrupted themselves or were interrupted about every 3 minutes, usually to check email. Other studies have shown that it’s now common for office workers to interrupt what they’re doing to check email 30 to 40 times an hour and that the more a worker self-interrupts, the more stress he or she experiences. Studies of college students show that while trying to study, they lose focus every 3 minutes on average, for example, to check Facebook or text a friend. The more often they interrupt themselves to “multitask,” the worse they do on tests. Multitasking with technology is no way to make the most of your time—those emails can wait!

Mike glanced at the two computer towers lying half-autopsied on her kitchen table. One had a bag of chips in it, the top held shut with a binder clip. A stack of motherboards rested on the chair in Mylar bags. “Maid’s been on vacation, I see,” said Mike. “Yeah. She ran off with the guy who writes your jokes.” “Ouch.” “There’s a postcard from them here somewhere. Want me to look for that instead?” “No, no. Just the logs will be fine.

To better understand the predicament of someone who is rational but emotionless, consider computers. Give a computer a program to run, and it will use flawless logic to execute it. But unless you give a computer a program to run, it will just sit there. Computers need a motivating force before they will do anything, and it is the job of the programmer to provide this motivating force. Damasio’s patient was like an unprogrammed computer. His

Universal computers are capable of performing all the computations permitted by the laws of physics. Once a universal computer is constructed, all you have to do is to load it with the right programme, and it can simulate any other system that is physically allowed. This includes the biosphere, with all its splendid richness of animals, plants, and microorganisms; and, in principle, it even includes your brain, together with thoughts and emotions.

Alan Turing appears to be becoming a symbol of the shift towards computing, not least because of his attitude of open-minded defiance of convention and conventional thinking. Not only did he conceptualise the modern computer – imagining a simple machine that could use different programmes – but he put his thinking into practice in the great code breaking struggle with the Nazis in World War II, and followed it up with pioneering early work in the mathematics of biology and chaos.

At present, computers are spectacular at number crunching and data processing. We can code programmes that feel as though computers are interacting with us, and that's fun, but in fact they aren't interacting in a way that we expect a human being to interact. But what will happen when a programme that has self-developed, that has its own version of what we call consciousness - realises, in the human sense of the verb 'to realise', exactly what/who is on the other side of the screen?

Meanwhile, the original programmers will have left, and their replacements -- believing they understand the code -- will make some truly spectacular errors, mistakes that will suddenly make everything completely stop working for a while. So that what had seemed to be a descending curve of bugs, a fall toward the ever-receding zero, will reveal itself as the shape of another equation altogether: a line of relentlessly rising, bug-counts climbing in an endless battle against infinity.

Tom Demarco, a principal of the Atlantic Systems Guild team of consultants ... and his colleague Timothy Lister devised a study called the Coding War Games. The purpose of the games was to identify the characteristics of the best and worst computer programmers; more than six hundred developers from ninety-two different companies participated. Each designed, coded, and tested a program, working in his normal office space during business hours. Each participant was also assigned a partner from the same company. The partners worked separately, however, without any communication, a feature of the games that turned out to be critical. When the results came in, they revealed an enormous performance gap. The best outperformed the worst by a 10:1 ratio. The top programmers were also about 2.5 times better than the median. When DeMarco and Lister tried to figure out what accounted for this astonishing range, the factors that you'd think would matter — such as years of experience, salary, even the time spent completing the work — had little correlation to outcome. Programmers with 10 years' experience did no better than those with two years. The half who performed above the median earned less than 10 percent more than the half below — even though they were almost twice as good. The programmers who turned in "zero-defect" work took slightly less, not more, time to complete the exercise than those who made mistakes. It was a mystery with one intriguing clue: programmers from the same companies performed at more or less the same level, even though they hadn't worked together. That's because top performers overwhelmingly worked for companies that gave their workers the most privacy, personal space, control over their physical environments, and freedom from interruption. Sixty-two percent of the best performers said that their workspace was acceptably private, compared to only 19 percent of the worst performers; 76 percent of the worst performers but only 38 percent of the top performers said that people often interrupted them needlessly.

forward to it, and Cooper, coatless and chilly in the desert evening, was thinking that the radio man was an asshole. He’d chased Vasquez for nine days now. Someone had warned the programmer just before Cooper got to the Boston walk-up, a brick rectangle where the only light had been a window onto an airshaft and the glowing red eyes of power indicators on computers and routers and surge protectors. The desk chair had been against the far wall as if someone had leaped out of it, and steam still rose from an abandoned bowl of ramen. Vasquez had run, and

It was thus that in the second half of 1969—amid the static of Woodstock, Chappaquiddick, Vietnam War protests, Charles Manson, the Chicago Eight trial, and Altamont—the culmination was reached for three historic enterprises, each in the making for almost a decade. NASA was able to send a man to the moon. Engineers in Silicon Valley were able to devise a way to put a programmable computer on a chip called a microprocessor. And ARPA created a network that could connect distant computers. Only the first of these (perhaps the least historically significant of them?) made headlines. THE

Programs should always have the form of paragraphs of comments that describe the intention of the program followed by paragraphs of code that implement that intention. All of the formatting should be designed to make readers as able as possible to read the code easily; the compiler doesn’t care. In particular, follow conventions of mathematics and your native language, not those you found in some random language manual. Write the comments first and then write the code, not the other way around. If you don’t know what you want to achieve and why, any code you write is, by definition, incorrect.

Think of the many articles one can find every year in the Wall Street Journal describing some entrepreneur or businessman as being a "pioneer" or a "maverick" or a "cowboy." Think of the many times these ambitious modern men are described as "staking their claim" or boldly pushing themselves "beyond the frontier" or even "riding into the sunset." We still use this nineteenth-century lexicon to describe our boldest citizens, but it's really a code now, because these guys aren't actually pioneers; they are talented computer programmers, biogenetic researchers, politicians, or media monguls making a big splash in a fast modern economy. But when Eustace Conway talks about staking a claim, the guy is literally staking a goddamn claim. Other frontier expressions that the rest of us use as metaphors, Eustace uses literally. He does sit tall in the saddle; he does keep his powder dry; he is carving out a homestead. When he talks about reining in horses or calling off the dogs or mending fences, you can be sure that there are real horses, real dogs or real fences in the picture. And when Eustace goes in for the kill, he's not talking about a hostile takeover of a rival company; he's talking about really killing something.

After the huge push for CES, it was time for Amiga to sort a few things out. First, the Amiga systems engineers began producing 100 Lorraine developer systems to hand out to companies like Activision, Electronic Arts, Infocom, and Microsoft. At the time, Commodore programmer Andy Finkel was helping Infocom in Cambridge to port its games to the C64. “That was where I first got a hint of the Amiga,” says Finkel. “There was this locked room where I couldn’t go, even though I could go anywhere else in the building. The Infocom tech people would sneak in and work on the computer. They told me there was a secret computer that they couldn’t talk about.

When Amabile analyzed the data, she came to a clear conclusion about one key factor: workers are happiest—and most motivated—when they feel that they accomplish something meaningful at work. These accomplishments do not need to be major breakthroughs: incremental but noticeable progress toward a goal was enough to make her subjects feel good. As one programmer described it, “I smashed that [computer] bug that’s been frustrating me for almost a calendar week. That may not be an event to you, but I live a very drab life, so I’m all hyped.”1 The lesson here is that managers can get the most out of their employees by helping them achieve meaningful progress every day.

Programming is not all the same. Normal written languages have different rhythms and idioms, right? Well, so do programming languages. The language called C is all harsh imperatives, almost raw computer-speak. The language called Lisp is like one long, looping sentence, full of subclauses, so long in fact that you usually forget what it was even about in the first place. The language called Erlang is just like it sounds: eccentric and Scandinavia. I cannot program in any of these languages because they're all too hard. But Ruby, my language of choice, was invented by a cheerful Japanese programmer, and it reads like friendly, accessible poetry. Billy Collins by way of Bill Gates.

Tiredness thus draws whole families into the vicious circle of poor nutrition and lack of exercise. The sluggishness that comes from poor diet feeds further exhaustion, which leads to more quick-fix junk food and telly-slumping … and so on, ad infinitum. And all this overlaps with another vicious circle. This is the one where exhausted parents attempt wanly to convince their children it’s bedtime. And the children - over-tired and brattish - play up more and more, until their parents give up the unequal struggle and let them watch ‘one more programme’ or play ‘one more computer game’. The next morning everyone wakes up tired again … and on it goes, the two vicious circles overlapping into a vicious Venn diagram, with a worn-out family trapped in the middle.

Code for Humanity (The Sonnet) There is no such thing as ethical hacking, If it were ethical they wouldn't be teaching it. Because like it or not ethics is bad for business, They teach hacking so they could use it for profit. With the right sequence of zeros and ones we could, Equalize all bank accounts of planet earth tomorrow. Forget about what glass house gargoyles do with tech, How will you the human use tech to eliminate sorrow? In a world full of greedy edisons, be a humble Tesla, Time remembers no oligarch kindly no matter the status. Only innovators who get engraved in people's heart, Are the ones who innovate with a humane purpose. Innovate to bridge the gap, not exploit and cater to disparities. In a world run by algorithms of greed write a code that helps 'n heals.

So which theory did Lagos believe in? The relativist or the universalist?" "He did not seem to think there was much of a difference. In the end, they are both somewhat mystical. Lagos believed that both schools of thought had essentially arrived at the same place by different lines of reasoning." "But it seems to me there is a key difference," Hiro says. "The universalists think that we are determined by the prepatterned structure of our brains -- the pathways in the cortex. The relativists don't believe that we have any limits." "Lagos modified the strict Chomskyan theory by supposing that learning a language is like blowing code into PROMs -- an analogy that I cannot interpret." "The analogy is clear. PROMs are Programmable Read-Only Memory chips," Hiro says. "When they come from the factory, they have no content. Once and only once, you can place information into those chips and then freeze it -- the information, the software, becomes frozen into the chip -- it transmutes into hardware. After you have blown the code into the PROMs, you can read it out, but you can't write to them anymore. So Lagos was trying to say that the newborn human brain has no structure -- as the relativists would have it -- and that as the child learns a language, the developing brain structures itself accordingly, the language gets 'blown into the hardware and becomes a permanent part of the brain's deep structure -- as the universalists would have it." "Yes. This was his interpretation." "Okay. So when he talked about Enki being a real person with magical powers, what he meant was that Enki somehow understood the connection between language and the brain, knew how to manipulate it. The same way that a hacker, knowing the secrets of a computer system, can write code to control it -- digital namshubs?" "Lagos said that Enki had the ability to ascend into the universe of language and see it before his eyes. Much as humans go into the Metaverse. That gave him power to create nam-shubs. And nam-shubs had the power to alter the functioning of the brain and of the body." "Why isn't anyone doing this kind of thing nowadays? Why aren't there any namshubs in English?" "Not all languages are the same, as Steiner points out. Some languages are better at metaphor than others. Hebrew, Aramaic, Greek, and Chinese lend themselves to word play and have achieved a lasting grip on reality: Palestine had Qiryat Sefer, the 'City of the Letter,' and Syria had Byblos, the 'Town of the Book.' By contrast other civilizations seem 'speechless' or at least, as may have been the case in Egypt, not entirely cognizant of the creative and transformational powers of language. Lagos believed that Sumerian was an extraordinarily powerful language -- at least it was in Sumer five thousand years ago." "A language that lent itself to Enki's neurolinguistic hacking." "Early linguists, as well as the Kabbalists, believed in a fictional language called the tongue of Eden, the language of Adam. It enabled all men to understand each other, to communicate without misunderstanding. It was the language of the Logos, the moment when God created the world by speaking a word. In the tongue of Eden, naming a thing was the same as creating it. To quote Steiner again, 'Our speech interposes itself between apprehension and truth like a dusty pane or warped mirror. The tongue of Eden was like a flawless glass; a light of total understanding streamed through it. Thus Babel was a second Fall.' And Isaac the Blind, an early Kabbalist, said that, to quote Gershom Scholem's translation, 'The speech of men is connected with divine speech and all language whether heavenly or human derives from one source: the Divine Name.' The practical Kabbalists, the sorcerers, bore the title Ba'al Shem, meaning 'master of the divine name.'" "The machine language of the world," Hiro says.

Why is programming fun? What delights may its practitioner expect as his reward? First is the sheer joy of making things. As the child delights in his first mud pie, so the adult enjoys building things, especially things of his own design. I think this delight must be an image of God’s delight in making things, a delight shown in the distinctness and newness of each leaf and each snowflake. Second is the pleasure of making things that are useful to other people. Deep within, we want others to use our work and to find it helpful. In this respect the programming system is not essentially different from the child’s first clay pencil holder “for Daddy’s office.” Third is the fascination of fashioning complex puzzle-like objects of interlocking moving parts and watching them work in subtle cycles, playing out the consequences of principles built in from the beginning. The programmed computer has all the fascination of the pinball machine or the jukebox mechanism, carried to the ultimate. Fourth is the joy of always learning, which springs from the nonrepeating nature of the task. In one way or another the problem is ever new, and its solver learns something; sometimes practical, sometimes theoretical, and sometimes both. Finally, there is the delight of working in such a tractable medium. The programmer, like the poet, works only slightly removed from pure thought-stuff. He builds his castles in the air, from air, creating by exertion of the imagination. Few media of creation are so flexible, so easy to polish and rework, so readily capable of realizing grand conceptual structures. (As we shall see later, this very tractability has its own problems.) Yet the program construct, unlike the poet’s words, is real in the sense that it moves and works, producing visible outputs separate from the construct itself. It prints results, draws pictures, produces sounds, moves arms. The magic of myth and legend has come true in our time. One types the correct incantation on a keyboard and a display screen comes to life, showing things that never were nor could be. Programming then is fun because it gratifies creative longings built deep within us and delights sensibilities we have in common with all men.

I WANT TO end this list by talking a little more about the founding of Pixar University and Elyse Klaidman’s mind-expanding drawing classes in particular. Those first classes were such a success—of the 120 people who worked at Pixar then, 100 enrolled—that we gradually began expanding P.U.’s curriculum. Sculpting, painting, acting, meditation, belly dancing, live-action filmmaking, computer programming, design and color theory, ballet—over the years, we have offered free classes in all of them. This meant spending not only the time to find the best outside teachers but also the real cost of freeing people up during their workday to take the classes. So what exactly was Pixar getting out of all of this? It wasn’t that the class material directly enhanced our employees’ job performance. Instead, there was something about an apprentice lighting technician sitting alongside an experienced animator, who in turn was sitting next to someone who worked in legal or accounting or security—that proved immensely valuable. In the classroom setting, people interacted in a way they didn’t in the workplace. They felt free to be goofy, relaxed, open, vulnerable. Hierarchy did not apply, and as a result, communication thrived. Simply by providing an excuse for us all to toil side by side, humbled by the challenge of sketching a self-portrait or writing computer code or taming a lump of clay, P.U. changed the culture for the better. It taught everyone at Pixar, no matter their title, to respect the work that their colleagues did. And it made us all beginners again. Creativity involves missteps and imperfections. I wanted our people to get comfortable with that idea—that both the organization and its members should be willing, at times, to operate on the edge. I can understand that the leaders of many companies might wonder whether or not such classes would truly be useful, worth the expense. And I’ll admit that these social interactions I describe were an unexpected benefit. But the purpose of P.U. was never to turn programmers into artists or artists into belly dancers. Instead, it was to send a signal about how important it is for every one of us to keep learning new things. That, too, is a key part of remaining flexible: keeping our brains nimble by pushing ourselves to try things we haven’t tried before. That’s what P.U. lets our people do, and I believe it makes us stronger.

a harbinger of a third wave of computing, one that blurred the line between augmented human intelligence and artificial intelligence. “The first generation of computers were machines that counted and tabulated,” Rometty says, harking back to IBM’s roots in Herman Hollerith’s punch-card tabulators used for the 1890 census. “The second generation involved programmable machines that used the von Neumann architecture. You had to tell them what to do.” Beginning with Ada Lovelace, people wrote algorithms that instructed these computers, step by step, how to perform tasks. “Because of the proliferation of data,” Rometty adds, “there is no choice but to have a third generation, which are systems that are not programmed, they learn.”27 But even as this occurs, the process could remain one of partnership and symbiosis with humans rather than one designed to relegate humans to the dustbin of history. Larry Norton, a breast cancer specialist at New York’s Memorial Sloan-Kettering Cancer Center, was part of the team that worked with Watson. “Computer science is going to evolve rapidly, and medicine will evolve with it,” he said. “This is coevolution. We’ll help each other.”28 This belief that machines and humans will get smarter together is a process that Doug Engelbart called “bootstrapping” and “coevolution.”29 It raises an interesting prospect: perhaps no matter how fast computers progress, artificial intelligence may never outstrip the intelligence of the human-machine partnership. Let us assume, for example, that a machine someday exhibits all of the mental capabilities of a human: giving the outward appearance of recognizing patterns, perceiving emotions, appreciating beauty, creating art, having desires, forming moral values, and pursuing goals. Such a machine might be able to pass a Turing Test. It might even pass what we could call the Ada Test, which is that it could appear to “originate” its own thoughts that go beyond what we humans program it to do. There would, however, be still another hurdle before we could say that artificial intelligence has triumphed over augmented intelligence. We can call it the Licklider Test. It would go beyond asking whether a machine could replicate all the components of human intelligence to ask whether the machine accomplishes these tasks better when whirring away completely on its own or when working in conjunction with humans. In other words, is it possible that humans and machines working in partnership will be indefinitely more powerful than an artificial intelligence machine working alone?

Chapter One Vivek Ranadivé “IT WAS REALLY RANDOM. I MEAN, MY FATHER HAD NEVER PLAYED BASKETBALL BEFORE.” 1. When Vivek Ranadivé decided to coach his daughter Anjali’s basketball team, he settled on two principles. The first was that he would never raise his voice. This was National Junior Basketball—the Little League of basketball. The team was made up mostly of twelve-year-olds, and twelve-year-olds, he knew from experience, did not respond well to shouting. He would conduct business on the basketball court, he decided, the same way he conducted business at his software firm. He would speak calmly and softly, and he would persuade the girls of the wisdom of his approach with appeals to reason and common sense. The second principle was more important. Ranadivé was puzzled by the way Americans play basketball. He is from Mumbai. He grew up with cricket and soccer. He would never forget the first time he saw a basketball game. He thought it was mindless. Team A would score and then immediately retreat to its own end of the court. Team B would pass the ball in from the sidelines and dribble it into Team A’s end, where Team A was patiently waiting. Then the process would reverse itself. A regulation basketball court is ninety-four feet long. Most of the time, a team would defend only about twenty-four feet of that, conceding the other seventy feet. Occasionally teams played a full-court press—that is, they contested their opponent’s attempt to advance the ball up the court. But they did it for only a few minutes at a time. It was as if there were a kind of conspiracy in the basketball world about the way the game ought to be played, Ranadivé thought, and that conspiracy had the effect of widening the gap between good teams and weak teams. Good teams, after all, had players who were tall and could dribble and shoot well; they could crisply execute their carefully prepared plays in their opponent’s end. Why, then, did weak teams play in a way that made it easy for good teams to do the very things that they were so good at? Ranadivé looked at his girls. Morgan and Julia were serious basketball players. But Nicky, Angela, Dani, Holly, Annika, and his own daughter, Anjali, had never played the game before. They weren’t all that tall. They couldn’t shoot. They weren’t particularly adept at dribbling. They were not the sort who played pickup games at the playground every evening. Ranadivé lives in Menlo Park, in the heart of California’s Silicon Valley. His team was made up of, as Ranadivé put it, “little blond girls.” These were the daughters of nerds and computer programmers. They worked on science projects and read long and complicated books and dreamed about growing up to be marine biologists. Ranadivé knew that if they played the conventional way—if they let their opponents dribble the ball up the court without opposition—they would almost certainly lose to the girls for whom basketball was a passion. Ranadivé had come to America as a seventeen-year-old with fifty dollars in his pocket. He was not one to accept losing easily. His second principle, then, was that his team would play a real full-court press—every game, all the time. The team ended up at the national championships. “It was really random,” Anjali Ranadivé said. “I mean, my father had never played basketball before.” 2. Suppose you were to total up all the wars over the past two hundred years that occurred between very large and very small countries. Let’s say that one side has to be at least ten times larger in population and armed might

Computers speak machine language," Hiro says. "It's written in ones and zeroes -- binary code. At the lowest level, all computers are programmed with strings of ones and zeroes. When you program in machine language, you are controlling the computer at its brainstem, the root of its existence. It's the tongue of Eden. But it's very difficult to work in machine language because you go crazy after a while, working at such a minute level. So a whole Babel of computer languages has been created for programmers: FORTRAN, BASIC, COBOL, LISP, Pascal, C, PROLOG, FORTH. You talk to the computer in one of these languages, and a piece of software called a compiler converts it into machine language. But you never can tell exactly what the compiler is doing. It doesn't always come out the way you want. Like a dusty pane or warped mirror. A really advanced hacker comes to understand the true inner workings of the machine -- he sees through the language he's working in and glimpses the secret functioning of the binary code -- becomes a Ba'al Shem of sorts." "Lagos believed that the legends about the tongue of Eden were exaggerated versions of true events," the Librarian says. "These legends reflected nostalgia for a time when people spoke Sumerian, a tongue that was superior to anything that came afterward." "Is Sumerian really that good?" "Not as far as modern-day linguists can tell," the Librarian says. "As I mentioned, it is largely impossible for us to grasp. Lagos suspected that words worked differently in those days. If one's native tongue influences the physical structure of the developing brain, then it is fair to say that the Sumerians -- who spoke a language radically different from anything in existence today -- had fundamentally different brains from yours. Lagos believed that for this reason, Sumerian was a language ideally suited to the creation and propagation of viruses. That a virus, once released into Sumer, would spread rapidly and virulently, until it had infected everyone." "Maybe Enki knew that also," Hiro says. "Maybe the nam-shub of Enki wasn't such a bad thing. Maybe Babel was the best thing that ever happened to us.

Man’s destiny was to conquer and rule the world, and this is what he’s done — almost. He hasn’t quite made it, and it looks as though this may be his undoing. The problem is that man’s conquest of the world has itself devastated the world. And in spite of all the mastery we’ve attained, we don’t have enough mastery to stop devastating the world — or to repair the devastation we’ve already wrought. We’ve poured our poisons into the world as though it were a bottomless pit — and we go on pouring our poisons into the world. We’ve gobbled up irreplaceable resources as though they could never run out — and we go on gobbling them up. It’s hard to imagine how the world could survive another century of this abuse, but nobody’s really doing anything about it. It’s a problem our children will have to solve, or their children. Only one thing can save us. We have to increase our mastery of the world. All this damage has come about through our conquest of the world, but we have to go on conquering it until our rule is absolute. Then, when we’re in complete control, everything will be fine. We’ll have fusion power. No pollution. We’ll turn the rain on and off. We’ll grow a bushel of wheat in a square centimeter. We’ll turn the oceans into farms. We’ll control the weather — no more hurricanes, no more tornadoes, no more droughts, no more untimely frosts. We’ll make the clouds release their water over the land instead of dumping it uselessly into the oceans. All the life processes of this planet will be where they belong—where the gods meant them to be—in our hands. And we’ll manipulate them the way a programmer manipulates a computer. And that’s where it stands right now. We have to carry the conquest forward. And carrying it forward is either going to destroy the world or turn it into a paradise — into the paradise it was meant to be under human rule. And if we manage to do this — if we finally manage to make ourselves the absolute rulers of the world — then nothing can stop us. Then we move into the Star Trek era. Man moves out into space to conquer and rule the entire universe. And that may be the ultimate destiny of man: to conquer and rule the entire universe. That’s how wonderful man is.

A somewhat provocative example of the interconnections between the gaming industry and finance. A technologist working for a large London hedge fund hinted this to me in interview. Trained in computer science and engineering, this interviewee first worked as a network programmer for large online multiplayer games. His greatest challenge was the fact that the Internet is not instantaneous: when a player sends a command to execute in action, it takes time for the signal to reach the computer server and interact with the commands of other players. For the game to be realistic, such delays have to be taken into account when rendering reality on the screen. The challenge for the network programmer is to make these asymmetries as invisible as possible so that the game seem 'equitable to everyone.' The problem is similar in finance, where the physical distance from the stock exchange's matching engines matters tremendously, requiring a similar solution to the problem of latency: simulating the most likely state of the order book on the firm's computers in order to estimate the most advantageous strategies or the firm's trading algorithms. Gaming and finance are linked not through an institutional imperative of culture or capital - or even a strategy, as such - but rather through the more mundane and lowly problems of how to fairly manage latency and connectivity.

These potential advantages of DNA computing over the traditional approach and the seminal experimental work of Adleman, demonstrating the practical in vitro implementation of a DNA algorithm for solving an instance of the Hamiltonian path problem, caused a strong increase of interest in DNA computing over the past years. Although the set of “bio-operations” that can be executed on DNA strands in a laboratory (including operators such as synthesizing, mixing, annealing, melting, amplifying, separating, extracting, cutting, and ligating DNA strands) seems fundamentally different from traditional programming languages, theoretical work on the computational power of various models of DNA computing demonstrates that certain subsets of these operators are computationally complete. In other words, everything that is Turing-computable can also be computed by these DNA models of computation. Furthermore, it has also been shown that universal systems exist, so that the programmable DNA computer is theoretically possible. The algorithms for DNA computing that have been presented in the literature use an approach that will not work for NP-complete problems of realistic size, because these algorithms are all based on extracting an existing solution from a sufficiently large initial population of solutions. Although a huge number (≈ 1012) of DNA molecules (i.e., potential solutions to a given problem) can be manipulated in parallel, this so-called filtering approach (i.e., generate and test) quickly becomes infeasible as problem sizes grow (e.g., a 500-node instance of the traveling salesman problem has > 101000 potential solutions).

Keep These Things in Mind While Enrolling For A Professional Online Course While online courses are gaining in popularity due to the conveniences they offer, you must consider a few things before enrolling in one. Not all programs are suitable for everyone. Not everyone is good at learning online. There are a lot of conditions that must be satisfied to make such learning successful. It is better that you consider everything carefully before starting your e-learning course. 1. How Will The Course Help You? There are many online professional programs available from various universities and educational platforms. You must see which one will be most useful for you. If you are working and you need to acquire a skill to get a promotion, then you must choose such a course. It is not just money that you are spending on these courses. You are also investing a lot of your time and effort to successfully complete your learning. 2. Do You Have The Motivation To Learn By Yourself? Getting motivated to study when you are in a classroom full of students is easy. A professor is teaching and also watching you. But in online certification courses, you have the freedom of studying whenever and wherever you want. Many of the e-learning platforms allow you to complete the program at your pace. This can make you lethargic and distracted. You must ask yourself whether you can remain motivated to complete the course. 3. How Familiar Are You With The Technology? You don’t need to be a computer genius to attend online professional programs. But you must be familiar with basic computer operations, playing videos on both desktops and mobile phones, and using a web browser. The other skill you will require in e-learning is the speed of typing on different devices. When there are live exchanges with the professors, you will need to type the queries very fast if you want to get your answers. 4. How Well Will You Participate In Online Classes? It is very easy to remain silent in virtual classes. There is no one staring at you and pushing you to ask questions or give answers. But if you don’t interact, you will not be making full use of online certification courses. Participation is very important in such classrooms. You must also take part in the group discussions that will bring out new ideas and opinions. E-learning is not for those who need physical presence. 5. Who Are The Others On The Programme? Knowing the other participants in online professional programs is very important, especially if you are already working and looking to acquire more skills. There must be people in the virtual classroom whose contributions will be useful for you. If the course has only freshers from college, then it may not give you any value addition. As a working person, you must look at networking opportunities that will help you with career opportunities. To Sum Up….. For working people, virtual classes are the best way to acquire more skills without taking a break from employment. These courses offer you the flexibility that you can never get in campus education. But you must make yourself suitable for e-learning to benefit from it.

Personal responsibility, or proactivity, is fundamental to the first creation. Returning to the computer metaphor, Habit 1 says, “You are the programmer.” Habit 2, then, says, “Write the program.” Until you accept the idea that you are responsible, that you are the programmer, you won’t really invest in writing the program.

In a perfect world, of course, no one person, much less a thirty-three-year-old computer programmer in soccer shoes, would have the power to manipulate a presidential election. And yet this is the world we live in. For too long, the gatekeepers who ran the most powerful information-spreading systems in human history were able to pretend that they weren’t gatekeepers at all. Information wants to be free; besides, people who take offense should blame the author, not the messenger; anyway, the ultimate responsibility lies with each consumer. Now, instead of imagining that we occupy a postgatekeeper utopia, it might make more sense—in the short term, at least—to demand better, more thoughtful gatekeepers.

Programmers don’t talk because they must not be interrupted.… To synchronize with other people (or their representation in telephones, buzzers and doorbells) can only mean interrupting the thought train. Interruptions mean certain bugs. You must not get off the train. —ELLEN ULLMAN

Machines produce only machines. The texts, images, films, speech and programmes which come out of the computer are machine products, and they bear the marks of such products: they are artificially padded-out, face-lifted by the machine; the films are stuffed with special effects, the texts full of longueurs and repetitions due to the machine's malicious will to function at all costs (that is its passion), and to the operator's fascination with this limitless possibility of functioning. Hence the wearisome character in films of all this violence and pornographied sexuality, which are merely special effects of violence and sex, no longer even fantasized by humans, but pure machinic violence. And this explains all these texts that resemble the work of 'intelligent' virtual agents, whose only act is the act of programming. This has nothing to do with automatic writing, which played on the magical telescoping of words and concepts, whereas all we have here is the automatism of programming, an automatic run-through of all the possibilities. It is this phantasm of the ideal performance of the text or image, the possibility of correcting endlessly, which produce in the 'creative artist' this vertige of interactivity with his own object, alongside the anxious vertige at not having reached the technological limits of his possibilities. In fact, it is the (virtual) machine which is speaking you, the machine which is thinking you.

When an airplane navigates through the sky it works its way along a route composed of beacons and waypoints – invisible signposts in the sky – which are defined by geographic coordinates. They constitute the pilot’s map of the world. Flight computers are programmed into these waypoints which are put into the systems before take-off. Assuming these coordinates have been programmed correctly, the plane will go from point A, passing through the designated waypoints, before arriving at point B without a hitch. However, if any of these waypoints are wrong, the aircraft will deviate from its flight programme and its destination which can prove fatal. Life for each of us contains thousands of waypoints; signposts that hopefully provide us with directions as to what to do, how to go about things and where to go next – our decision-making processes. But what happens when our own onboard computer, our brain, has initially been programmed with data that is corrupt and socially unacceptable. How are we able to make life decisions – correct decisions that is?

The advance of computerization and automation technologies has meant that many medium-skilled jobs—clerks, travel agents, bookkeepers, and factory workers—have been replaced with new technologies. New jobs have arisen in their place, but those jobs are often one of two types: either they are high-skilled jobs, such as engineers, programmers, managers, and designers, or they are lower-skilled jobs such as retail workers, cleaners, or customer service agents. Exacerbating the trends caused by computers and robots are globalization and regionalization. As medium-skilled technical work is outsourced to workers in developing nations, many of those jobs are disappearing at home. Lower-skilled jobs, which often require face-to-face contact or social knowledge in the form of cultural or language abilities, are likely to remain. Higher-skilled work is also more resistant to shipping overseas because of the benefits of coordination with management and the market. Think of Apple’s tagline on all of its iPhones: “Designed in California. Made in China.” Design and management stay; manufacturing goes.

What kinds of Work will You do in Freelancing? What kind of work will you do in Freelancing? And to understand the type of work in freelancing, You need to have a clear idea of what freelancing is. There is no specific type of freelancing, it can be of many types, such as - Freelance Photography, Freelance Journalism, Freelance Writer, Freelance Data Entry, Freelance Logo Designer, Freelance Graphics Designer etc. There's no end to the amount of work you can do with freelancing. The most interesting thing is that you are everything in this process. There is no one to twirl over your head, you are the boss here. Even here there is no obligation to work from 9-5. Today I discuss some freelancing tasks that are popular in the freelancing sector or are done by many freelancers. For example: Data Entry: It wouldn't be too much of a mistake to say that data entry is the easiest job. Rather, it can be said without a doubt that data entry is more difficult than any other job. Data entry work basically means typing. This work is usually provided as a PDF file and is described as a 'Word type work'. Any employee can take a data entry job as a part-time job for extra income at the end of his work. Graphics Design: One of the most popular jobs in the freelancing world is graphic design. The main reasons for the popularity of this work are its attractiveness and simplicity. Everything we see online is contributed by graphics. For example, Cover pages, Newspaper, Book cover pages, advertisements and Photographs, Editing or changing the background of a picture or photo, Creating banners for advertising, Creating visiting cards, Business cards or leaflets, Designed for webpages known as (PhD), T-shirt designing, Logo designing, Making cartoons and many more. Web Design and Development: 'Web design' or 'Site design' are used interchangeably. The most important job of freelancing is web design. From the simplest to the most difficult aspects of this work, almost all types of work are done by freelancers. There are many other themes like WordPress, Elementor, Joomla, and DV that can be used to create entire sites. Sometimes coding is required to create some sites. If the web designer has coding experience or skills then there is no problem, and if not then the site creation should be done by programmers. Programming: Programming means writing some signals, codes, or symbols into a specific system. And its job is to give different types of commands or orders to the computer. If you give some command to the computer in Bengali or English, the computer will not understand it. For that want binary code or number. Just as any book is written in English, Hindi, Japanese Bengali, etc. every program is written in some particular programming language like C++, Java, etc. The written form of the program is called source code. A person who writes source code is called a programmer, coder, or developer. While writing the program, the programmer has to follow the syntax or grammar of that particular programming language. Other work: Apart from the above jobs, there are various other types of jobs that are in high demand in the freelancing sector or market. The tasks are: Writing, Article or blog post writing SEO Marketing, Digital marketing, Photo, Audio, Video Editing, Admin jobs, Software development, Translation, Affiliate marketing, IT and Networking etc. Please Visit Our Blogging Website to read more Articles related to Freelancing and Outsourcing, Thank You.

Benn is a smart guy. He graduated from an elite college (the University of Virginia) with a degree in economics, and like many in his situation he had ambitions for his career. It didn’t take him long to realize that these ambitions would be thwarted so long as his main professional skills could be captured in an Excel macro. He decided, therefore, he needed to increase his value to the world. After a period of research, Benn reached a conclusion: He would, he declared to his family, quit his job as a human spreadsheet and become a computer programmer. As is often the case with such grand plans, however, there was a hitch: Jason Benn had no idea how to write code. As a computer scientist I can confirm an obvious point: Programming computers is hard. Most new developers dedicate a four-year college education to learning the ropes before their first job—and even then, competition for the best spots is fierce. Jason Benn didn’t have this time. After his Excel epiphany, he quit his job at the financial firm and moved home to prepare for his next step. His parents were happy he had a plan, but they weren’t happy about the idea that this return home might be long-term. Benn needed to learn a hard skill, and needed to do so fast.

What kinds of Work will You do in Freelancing? What kind of work will you do in Freelancing? And to understand the type of work in freelancing, You need to have a clear idea of what freelancing is. There is no specific type of freelancing, it can be of many types, such as - Freelance Photography, Freelance Journalism, Freelance Writer, Freelance Data Entry, Freelance Logo Designer, Freelance Graphics Designer etc. There's no end to the amount of work you can do with freelancing. The most interesting thing is that you are everything in this process. There is no one to twirl over your head, you are the boss here. Even here there is no obligation to work from 9-5. Today I discuss some freelancing tasks that are popular in the freelancing sector or are done by many freelancers. For example: Data Entry: It wouldn't be too much of a mistake to say that data entry is the easiest job. Rather, it can be said without a doubt that data entry is more difficult than any other job. Data entry work basically means typing. This work is usually provided as a PDF file and is described as a 'Word type work'. Any employee can take a data entry job as a part-time job for extra income at the end of his work. Graphics Design: One of the most popular jobs in the freelancing world is graphic design. The main reasons for the popularity of this work are its attractiveness and simplicity. Everything we see online is contributed by graphics. For example, Cover pages, Newspaper, Book cover pages, advertisements and Photographs, Editing or changing the background of a picture or photo, Creating banners for advertising, Creating visiting cards, Business cards or leaflets, Designed for webpages known as (PhD), T-shirt designing, Logo designing, Making cartoons and many more. Web Design and Development: 'Web design' or 'Site design' are used interchangeably. The most important job of freelancing is web design. From the simplest to the most difficult aspects of this work, almost all types of work are done by freelancers. There are many other themes like WordPress, Elementor, Joomla, and DV that can be used to create entire sites. Sometimes coding is required to create some sites. If the web designer has coding experience or skills then there is no problem, and if not then the site creation should be done by programmers. Programming: Programming means writing some signals, codes, or symbols into a specific system. And its job is to give different types of commands or orders to the computer. If you give some command to the computer in Bengali or English, the computer will not understand it. For that want binary code or number. Just as any book is written in English, Hindi, Japanese Bengali, etc. every program is written in some particular programming language like C++, Java, etc. The written form of the program is called source code. A person who writes source code is called a programmer, coder, or developer. While writing the program, the programmer has to follow the syntax or grammar of that particular programming language. Other work: Apart from the above jobs, there are various other types of jobs that are in high demand in the freelancing sector or market. The tasks are: Writing, Article or blog post writing SEO Marketing, Digital marketing, Photo, Audio, Video Editing, Admin jobs, Software development, Translation, Affiliate marketing, IT and Networking etc.

A 1964 study illustrated how status considerations could distort people's perceptions of the level of skill that was involved in various programming jobs. The study asked experienced computer personnel to distribute a list of programming tasks among a hierarchy of jobs–systems analyst, senior programmer, and programmer. The author found that "the higher the level of the job, the more job skills were included"–even if some of those tasks normally were performed by workers in the lower-status jobs. Higher-status workers were simply assumed to have a monopoly on skilled tasks, even by people who were familiar with the field and should have known better. We should not be surprised to find that employers, who often had no personal knowledge of programming, fell back on social categories when evaluating potential workers.

your world is the outcome of what you pay attention to, so consider for a moment the type of mental world constructed when you dedicate significant time to deep endeavors. There’s a gravity and sense of importance inherent in deep work—whether you’re Ric Furrer smithing a sword or a computer programmer optimizing an algorithm. Gallagher’s theory, therefore, predicts that if you spend enough time in this state, your mind will understand your world as rich in meaning and importance.

It will not halt until it is interrupted—an example of a common sort of program behavior called an infinite loop. Programmers often create infinite loops accidentally, and (as we shall see) it can be extremely difficult to predict when such loops will occur.

Subroutines allow sequences of instructions to be used over and over from many places within the program. In effect, the subroutine-calling convention allows the programmer to define new instructions by using sequences of other instructions. The program accesses a subroutine by using a Jump instruction to load the program counter with the address of the subroutine; but before doing so, the computer saves the previous contents of the program counter in a special memory location. At the end of the subroutine, another instruction reads this return address and jumps back to the location from which the subroutine was called.

However, the politics didn’t fall neatly along partisan lines: The traditionally Democratic trade union rank and file, for example, saw the growing presence of undocumented workers on construction sites as threatening their livelihoods, while Republican-leaning business groups interested in maintaining a steady supply of cheap labor (or, in the case of Silicon Valley, foreign-born computer programmers and engineers) often took pro-immigration positions.

The hurrieder I go / The behinder I get —NEEDLEPOINT SEEN IN BOONVILLE, CA Programmers don’t talk because they must not be interrupted.… To synchronize with other people (or their representation in telephones, buzzers and doorbells) can only mean interrupting the thought train. Interruptions mean certain bugs. You must not get off the train. —ELLEN ULLMAN

Quantum computing is not only faster than conventional computing, but its workload obeys a different scaling law—rendering Moore’s Law little more than a quaint memory. Formulated by Intel founder Gordon Moore, Moore’s Law observes that the number of transistors in a device’s integrated circuit doubles approximately every two years. Some early supercomputers ran on around 13,000 transistors; the Xbox One in your living room contains 5 billion. But Intel in recent years has reported that the pace of advancement has slowed, creating tremendous demand for alternative ways to provide faster and faster processing to fuel the growth of AI. The short-term results are innovative accelerators like graphics-processing unit (GPU) farms, tensor-processing unit (TPU) chips, and field-programmable gate arrays (FPGAs) in the cloud. But the dream is a quantum computer. Today we have an urgent need to solve problems that would tie up classical computers for centuries, but that could be solved by a quantum computer in a few minutes or hours. For example, the speed and accuracy with which quantum computing could break today’s highest levels of encryption is mind-boggling. It would take a classical computer 1 billion years to break today’s RSA-2048 encryption, but a quantum computer could crack it in about a hundred seconds, or less than two minutes. Fortunately, quantum computing will also revolutionize classical computing encryption, leading to ever more secure computing. To get there we need three scientific and engineering breakthroughs. The math breakthrough we’re working on is a topological qubit. The superconducting breakthrough we need is a fabrication process to yield thousands of topological qubits that are both highly reliable and stable. The computer science breakthrough we need is new computational methods for programming the quantum computer.

Writing computer software is one of the purest creative activities in the history of the human race. Programmers aren’t bound by practical limitations such as the laws of physics; we can create exciting virtual worlds with behaviors that could never exist in the real world.

That July, Xerox’s Display Word Processing Task Force endorsed the plan. For a few short, glorious weeks, official Xerox policy was to service the growing market for electronic word processing with the Alto III, a programmable personal computer that would bear the same relationship to the competition’s glorified typewriters as a Harley does to a tricycle. Ellenby’s group was on target to engineer an inexpensive computer-cum-word processor and printing system for shipment to customers by mid-1978. Had it done so, Xerox would have beaten the IBM PC to market by three years—with an infinitely more sophisticated machine. But it was not to happen. Bob Potter was not on board and never would be.

Software,” as the venture capitalist Marc Andreessen has proclaimed, “is eating the world.” It’s true. You use software nearly every instant you’re awake. There’s the obvious stuff, like your phone, your laptop, email and social networking and video games and Netflix, the way you order taxis and food. But there’s also less-obvious software lurking all around you. Nearly any paper book or pamphlet you touch was designed using software; code inside your car helps manage the braking system; “machine-learning” algorithms at your bank scrutinize your purchasing activity to help spy the moment when a criminal dupes your card and starts fraudulently buying things using your money. And this may sound weirdly obvious, but every single one of those pieces of software was written by a programmer—someone precisely like Ruchi Sanghvi or Mark Zuckerberg. Odds are high the person who originally thought of the product was a coder: Programmers spend their days trying to get computers to do new things, so they’re often very good at understanding the crazy what-ifs that computers make possible. (What if you had a computer take every word you typed and, quietly and constantly and automatically in the background, checked it against a dictionary of common English words? Hello, spell-check!) Sometimes it seems that the software we use just sort of sprang into existence, like grass growing on the lawn. But it didn’t. It was created by someone who wrote out—in code—a long, painstaking set of instructions telling the computer precisely what to do, step-by-step, to get a job done. There’s a sort of priestly class mystery cultivated around the word algorithm, but all they consist of are instructions: Do this, then do this, then do this. News Feed is now an extraordinarily complicated algorithm involving some trained machine learning; but it’s ultimately still just a list of rules. So the rule makers have power. Indeed, these days, the founders of high-tech companies—the ones who determine what products get created, what problems get solved, and what constitutes a “problem” in the first place—are increasingly technologists, the folks who cut their teeth writing endless lines of code and who cobbled together the prototype for their new firm themselves. Programmers are thus among the most quietly influential people on the planet.

Programmers do not ordinarily work in isolation. Although an individual programmer may find herself assigned the task of writing a program, even then she has other programmers to whom she may turn for help—and who, at the same time, may be turning to her.

A programmer who truly sees his program as an extension of his own ego is not going to be trying to find all the errors in that program. On the contrary, he is going to be trying to prove that the program is correct—even if this means the oversight of errors which are monstrous to another eye. All programmers are familiar with the symptoms of this dissonance resolution—-in others, of course.

The social science that provides us with the most useful overall model for computer programming is anthropology. With a little artistic license and stretching of the imagination, we could imagine computer programmers as having a culture—a shared set of beliefs and activities which shape their day-to-day activities.

the very first programmer, Lady Lovelace, seems to have had the idea of a programming language as a language as early as 1846. Although she was the niece of Lord Byron, it was not her knowledge of poetry but, rather, of mathematics which led her to think of a symbolic system as a language—for the idea of mathematics as a language seems to go back into the misty ages of the past. Thus, the idea of “programming language” was really born with the idea of programming itself.

People have lost sight of the original intention of COBOL’s designers. To quote one of them, Jean Sammet: The users for whom COBOL was designed were actually two subclasses of those people concerned with business data processing problems. One is the relatively inexperienced programmer for whom the naturalness of COBOL would be an asset, while the other type of user would be essentially anybody who had not written the program initially. In other words, the readability of COBOL programs would provide documentation to all who might wish to examine the programs, including the supervisory or management personnel. Little attempt was made to cater to professional programmers…

Overconfidence by the programmer could be attacked by a system that introduced random errors into the program under test. The location and nature of these errors would be recorded inside the system but concealed from the programmer. The rate at which he found and removed these known errors could be used to estimate the rate at which he is removing unknown errors. A similar technique is used routinely by surveillance systems in which an operator is expected to spend eight hours at a stretch looking at a radar screen for very rare events—such as the passing of an unidentified aircraft. Tests of performance showed that it was necessary to introduce some nonzero rate of occurrence of artificial events in order to keep the operator in a satisfactory state of arousal. Moreover, since these events were under control of the system, it was able to estimate the current and overall performance of each operator.

Specifications evolve together with programs and programmers. Writing a program is a process of learning—both for the programmer and the person who commissions the program.

When we do read code, we find that some of it gets written because of machine limitations, some because of language limitations, some because of programmer limitations, some because of historical accidents, and some because of specifications—both essential and inessential.

Programs, like any other human-made objects, are designed—or should be designed—with a definite lifespan and scope of application in mind. Like the “Deacon’s Masterpiece,” which was “built in such a logical way it ran a hundred years to the day,” a program should have neither over-designed or under-designed parts. Yet it is an occupational disease of programmers to spend more time on those program parts that present, for some reason, the most intellectual challenge rather than on those that require the most work.

each program has an appropriate level of care and sophistication dependent on the uses to which it will be put. Working above that level is, in a way, even less professional than working below it. If we are to know whether an individual programmer is doing a good job, we shall have to know whether or not he is working on the proper level for his problem.

Another essential personality factor in programming is at least a small dose of humility. Without humility, a programmer is foredoomed to the classic pattern of Greek drama: success leading to overconfidence (hubris) leading to blind self-destruction. Sophocles himself could not frame a better plot (to reveal the inadequacy of our powers) than that of the programmer learning a few simple techniques, feeling that he is an expert, and then being crushed by the irresistible power of the computer (the Deus ex Machina).

In 1968, Melvin Conway, a computer programmer and high school math and physics teacher, observed that systems tend to reflect the people and values who designed them. Conway was specifically looking at how organizations communicate internally, but later Harvard and MIT studies proved his idea more broadly. Harvard Business School analyzed different codebases, looking at software that was built for the same purpose but by different kinds of teams: those that were tightly controlled, and those that were more ad-hoc and open source.10 One of their key findings: design choices stem from how their teams are organized, and within those teams, bias and influence tends to go overlooked.

Mike Adams was by far the hardest for me to read. He was supportive in my first few weeks, but he was the least visible, occupied by prior projects. I also understood the least about the kinds of programming that were his strengths. Although I wasn't a programmer, I did have a computer science degree, something that, ironically, neither Adams, nor Peatling, nor Beau had. I didn't write code mostly because early in my career, I realized I did best at the level above code: leading teams, working with ideas, and shepherding projects to ship. Over my career, I've often been asked how I could manage programmers without doing programming myself. I believe I can manage anyone making anything provided two things are true: clarity and trust. If there is clarity between us on the goal and how we'll know when we're done, then we can speak the same language about what we need to do to get there. I knew enough about programming to call bullshit when needed and ask insightful questions. Making good things is about managing hundreds of trade-off decisions, and that's one of my best skills. Regarding clarity, most teams in the working world are starving for it. Layers of hierarchy create conflicting goals. Many teams have leaders who've never experienced clarity in their entire lives: they don't know what to look for, much less what to do when they find it. Thinking clearly, as trite as it sounds, was my strength.

According to Pythagoras everything is number, and God is a mathematician. This point of view has worked pretty well throughout the development of modern science. However now a neo-Pythagorian doctrine is emerging, according to which everything is 0/1 bits, and the world is built entirely out of digital information. In other words, now everything is software, God is a computer programmer, not a mathematician, and the world is a giant information-processing system, a giant computer.

Many years later, when he had plenty of computer time, Serge still wrote out new programs on paper before typing them into the machine. “In Russia, time on the computer was measured in minutes,” he said. “When you write a program, you are given a tiny time slot to make it work. Consequently we learned to write the code in ways that minimized the amount of debugging. And so you had to think about it a lot before you committed it to paper. . . . The ready availability of computer time creates this mode of working where you just have an idea and type it and maybe erase it ten times. Good Russian programmers, they tend to have had that one experience at some time in the past—the experience of limited access to computer time.

More than half the programmers at Goldman were Russians. Russians had a reputation for being the best programmers on Wall Street, and Serge thought he knew why: They had been forced to learn to program computers without the luxury of endless computer time. Many years later, when he had plenty of computer time, Serge still wrote out new programs on paper before typing them into the machine. “In Russia, time on the computer was measured in minutes,” he said. “When you write a program, you are given a tiny time slot to make it work. Consequently we learned to write the code in ways that minimized the amount of debugging. And so you had to think about it a lot before you committed it to paper. . . . The ready availability of computer time creates this mode of working where you just have an idea and type it and maybe erase it ten times. Good Russian programmers, they tend to have had that one experience at some time in the past—the experience of limited access to computer time.

Imagine another possibility – suppose you could back up your brain to a portable hard drive and then run it on your laptop. Would your laptop be able to think and feel just like a Sapiens? If so, would it be you or someone else? What if computer programmers could create an entirely new but digital mind, composed of computer code, complete with a sense of self, consciousness and memory? If you ran the program on your computer, would it be a person? If you deleted it could you be charged with murder?

When Konrad Zuse built the first working programmable computer, the Z2, in 1939, it could perform around 0.0000065 computations per second per 2023 dollar.

Soon after the West Coast Computer Faire, where we introduced the Apple II, a couple of other ready-to-use personal computers came out. One was the Radio Shack TRS-80, and the other was Commodore’s PET. These would become our direct competitors. But it was the Apple II that ended up kicking off the whole personal computer revolution. It had lots of firsts. Color was the big one. I designed the Apple II so it would work with the color TV you already owned. And it had game control paddles you could attach to it, and sound built in. That made it the first computer people wanted to design arcade-style games for, the first computer with sound and paddles ready to go. The Apple II even had a high-resolution mode where a game programmer could draw special little shapes really quickly. You could program every single pixel on the screen—whether it was on or off or what color it was—and that was something you could never do before with a low-cost computer. At first that mode didn’t mean a lot, but eventually it was a huge step toward the kinds of computer gaming you see today, where everything is high-res. Where the graphics can be truly realistic. The fact that it worked with your home TV made the total cost a lot lower than any competitors could do. It came with a real keyboard to type on—a normal keyboard—and that was a big deal. And the instant you turned it on, it was running BASIC in ROM.

We can’t control our environment everywhere we go, of course, but we have more control than we usually choose to exercise. Distractions literally make you stupid. Students whose classroom was situated near a noisy railroad line ended up academically a full year behind students with a quiet classroom. When the noise was dampened, the performance difference vanished. Offices aren’t much different. Research shows that the most productive computer programmers have one thing in common. It’s not experience, salary, or hours spent on a project. They had employers who gave them an environment free from distraction.

The most successful computer programmers aren't the ones who approach programming as a task they have to carry out in order to get their paychecks. They're the ones for whom programming is a joyful game.

How many computer programmers does it take to change a light bulb? Are you kidding? That's a hardware problem! " ♦◊♦◊♦◊♦

When the first professional computer programmers were all women during World War II, and only 12 percent of computer science degrees were awarded to women in 2011, it is clear that social factors play a significant role in who does and does not engage with computer technology. The gendering of computing technology is a recent social phenomenon, and we shouldn’t mistake the current disproportionate male presence in computer-related fields as reflecting an unchanging, innate, biological basis.6

Cory Doctorow hat dieses Werk unter der Creative-Commons-Lizenz(CC-BY-NC-SA) veröffentlicht die es jedermann erlaubt, das Werk frei zu verbreiten und zu bearbeiten ... (siehe wikipedia "little brother", dort auch Links zu den ebooks der Übersetzung) Unter Nutzung dieser Lizenz hat Christian Wöhrl eine deutsche Übersetzung des Romans angefertigt. Aus dieser ist ein Fanhörbuchprojekt entstanden. ... hier meine Zitate aus Readmill: Ich hatte also grade 10 Sekunden auf dreitausend Rechnern gemietet und jeden einzelnen angewiesen, eine SMS oder einen VoIP-Anruf an Charles' Handy abzusetzen; dessen Nummer hatte ich mal während einer dieser verhängnisvollen Bürositzungen bei Benson von einem Post-it abgelesen. Muss ich erwähnen, dass Charles' Telefon nicht in der Lage war, damit umzugehen? Zuerst ließen die SMS den Gerätespeicher überlaufen, sodass das Handy nicht mal mehr seine Routinen ausführen konnte, etwa das Klingeln zu koordinieren und die gefälschten Rufnummern der eingehenden Anrufe aufzuzeichnen. (Wusstet ihr, dass es völlig simpel ist, die Rückrufnummer einer Anruferkennung zu faken? Dafür gibts ungefähr 50 verschiedene Möglichkeiten - einfach mal "Anrufer-ID fälschen" googeln...) Charles starrte sein Telefon fassungslos an und hackte auf ihm herum, die wulstigen Augenbrauen regelrecht verknotet ob der Anstrengung, dieser Dämonen Herr zu werden, die das persönlichste seiner Geräte in Besitz genommen hatten. Sekunden später kackte Charles' Handy spektakulär ab. Zehntausende von zufälligen Anrufen und SMS liefen parallel bei ihm auf, sämtliche Warn- und Klingeltöne meldeten sich gleichzeitig und dann wieder und wieder. Den Angriff hatte ich mithilfe eines Botnetzes bewerkstelligt, was mir einerseits ein schlechtes Gewissen bereitete; aber andererseits war es ja im Dienst einer guten Sache. In Botnetzen fristen infizierte Rechner ihr untotes Dasein. Wenn du dir einen Wurm oder Virus fängst, sendet dein Rechner eine Botschaft an einen Chat-Kanal im IRC, dem Internet Relay Chat. Diese Botschaft zeigt dem Botmaster, also dem Typen, der den Wurm freigesetzt hat, dass da Computer sind, die auf seinen Befehl warten. Botnetze sind enorm mächtig, da sie aus Tausenden, manchmal Hunderttausenden von Rechnern bestehen, die über das ganze Internet verteilt sind, meist über Breitbandleitungen verbunden sind und auf schnelle Heim-PCs Das Buch passte grade so in die Mikrowelle, die sogar noch unappetitlicher aussah als beim letzten Mal, als ich sie brauchte. Ich wickelte das Buch penibel in Papiertücher, bevor ich es reinsteckte. "Mann, Lehrer sind Schweine", zischelte ich. Darryl, bleich und angespannt, erwiderte nichts. Dann packte ich das primäre Arbeitsgerät unserer Schule wieder aus und wählte den Klassenzimmer-Modus. Die SchulBooks waren die verräterischsten Geräte von allen - zeichneten jede Eingabe auf, kontrollierten den Netzwerkverkehr auf verdächtige Eingaben, zählten alle Klicks, zeichneten jeden flüchtigen Gedanken auf, den du übers Netz verbreitetest. Wir hatten sie in meinem ersten Jahr hier bekommen, und es hatte bloß ein paar Monate gedauert, bis der Reiz dieser Dinger verflogen war. Sobald die Leute merkten, dass diese "kostenlosen" Laptops in Wirklichkeit für die da oben arbeiteten (und im Übrigen mit massenhaft nerviger Werbung verseucht waren), fühlten die Kisten sich plötzlich sehr, sehr schwer an. Mein SchulBook zu cracken war simpel gewesen. Der Crack war binnen eines Monats nach Einführung der Maschine online zu finden, und es war eine billige Nummer - bloß ein DVD-Image runterladen, brennen, ins SchulBook stecken und die Kiste hochfahren, während man ein paar Tasten gleichzeitig gedrückt hielt. Die DVD erledigte den Rest und installierte etliche versteckte Programme auf dem Laptop, die von den täglichen Fernprüfungs-Routinen der Schulleitung nicht gefunden werden konnten.

Almost every PC owner has lost a weekend sorting through the debris of worms, viruses, spyware, and broken permissions. Since Windows was originally created in the pre-Internet days, programmers didn’t worry about closing holes in the operating system. Unfortunately, hackers and spammers could easily exploit these vulnerabilities. While security continues to improve with each new release, the Windows operating system is still based on a pre-Internet model, which is prone to viruses. Mac OS X was created only a few years ago with ultimate security and stability. There are no known Mac OS X viruses, and Windows Word Macros (a common home to threats)

Computer security was only as good as the programmer. The one who had fire walled this database has been good ---but not great. - Robert Puller

And Moore’s Law gave us bad software: Instead of writing efficient code, programmers just waited until the computers got faster. I’m reminded of Blaise Pascal’s comment three centuries ago. Apologizing for a verbose letters he wrote “I have only made this [letter] longer because I have not had the time to make it shorter.

At fifty years old and many years into her second career, she reinvented herself as a computer programmer.

Your identity should not be fully defined by what you do, by being a manager, a wife, a mother of children or a computer programmer

Let the computer do the repetitious, the mundane—it will do a better job of it than we would. We've got more important and more difficult things to do.

If you can create something useful, its reachable audience (e.g., employers or customers) is essentially limitless—which greatly magnifies your reward. On the other hand, if what you’re producing is mediocre, then you’re in trouble, as it’s too easy for your audience to find a better alternative online. Whether you’re a computer programmer, writer, marketer, consultant, or entrepreneur, your situation has become similar to Jung trying to outwit Freud, or Jason Benn trying to hold his own in a hot start-up: To succeed you have to produce the absolute best stuff you’re capable of producing—a task that requires depth.

They weren’t all Nixon supporters, either: self-described enemies were on hand, too. “Every generation needs somebody to hate, and he was ours,” said Richard Shilling, a computer programmer. “He politicized us, he incited us, he defined our cause. No one can ever take his place.

Today’s equivalent is probably ‘get an engineering degree’, but it will not necessarily be as lucrative. A third of Americans who graduated in STEM subjects (science, technology, engineering and maths) are in jobs that do not require any such qualification.52 They must still pay off their student debts. Up and down America there are programmers working as office temps and even fast-food servers. In the age of artificial intelligence, more and more will drift into obsolescence. On the evidence so far, this latest technological revolution is different in its dynamics from earlier ones. In contrast to earlier disruptions, which affected particular sectors of the economy, the effects of today’s revolution are general-purpose. From janitors to surgeons, virtually no jobs will be immune. Whether you are training to be an airline pilot, a retail assistant, a lawyer or a financial trader, labour-saving technology is whittling down your numbers – in some cases drastically so. In 2000, financial services employed 150,000 people in New York. By 2013 that had dropped to 100,000. Over the same period, Wall Street’s profits have soared. Up to 70 per cent of all equity trades are now executed by algorithms.53 Or take social media. In 2006, Google bought YouTube for $1.65 billion. It had sixty-five employees, so the price amounted to $25 million per employee. In 2012 Facebook bought Instagram, which had thirteen employees, for $1 billion. That came to $77 million per employee. In 2014, it bought WhatsApp, with fifty-five employees, for $19 billion, at a staggering $345 million per employee.54 Such riches are little comfort to the thousands of engineers who cannot find work. Facebook’s data servers are now managed by Cyborg, a software program. It requires one human technician for every twenty thousand computers.

Writing and repairing software generally takes far more time and is far more expensive than initially anticipated. “Every feature that is added and every bug that is fixed,” Edward Tenner points out, “adds the possibility of some new and unexpected interaction between parts of the program.”19 De Jager concurs: “If people have learned anything about large software projects, it is that many of them miss their deadlines, and those that are on time seldom work perfectly. … Indeed, on-time error-free installations of complex computer systems are rare.”20 Even small changes to code can require wholesale retesting of entire software systems. While at MIT in the 1980s, I helped develop some moderately complex software. I learned then that the biggest problems arise from bugs that creep into programs during early stages of design. They become deeply embedded in the software’s interdependent network of logic, and if left unfixed can have cascading repercussions throughout the software. But fixing them often requires tracing out consequences that have metastasized in every direction from the original error. As the amount of computer code in our world soars (doubling every two years in consumer products alone), we need practical ways to minimize the number of bugs. But software development is still at a preindustrial stage—it remains more craft than engineering. Programmers resemble artisans: they handcraft computer code out of basic programming languages using logic, intuition, and pattern-recognition skills honed over years of experience.

Today's Druids are artists, environmentalists, joiners, healers, teachers, fathers, students, unemployed, computer programmers, grandmothers; they come in all shapes, sizes, genders and colors and from all parts of the world. They

Today's Druids are artists, environmentalists, joiners, healers, teachers, fathers, students, unemployed, computer programmers, grandmothers; they come in all shapes, sizes, genders and colors and from all parts of the world.

Power tools for the mind. The most dramatic way to improve the productivity of management information systems (MIS) programmers is to go down to your local computer store and buy off the shelf what they would have built. This is not ridiculous; the availability of cheap, powerful shrink-wrapped software has met many needs that formerly would have occasioned custom packages. These power tools for the mind are more like electric drills, saws, and sanders than they are like big complex production tools.

A computer program is a message from a man to a machine. The rigidly marshaled syntax and the scrupulous definitions all exist to make intention clear to the dumb engine. But a written program has another face, that which tells its story to the human user. For even the most private of programs, some such communication is necessary; memory will fail the author-user, and he will require refreshing on the details of his handiwork. How much more vital is the documentation for a public program, whose user is remote from the author in both time and space! For the program product, the other face to the user is fully as important as the face to the machine. Most of us have quietly excoriated the remote and anonymous author of some skimpily documented program. And many of us have therefore tried to instill in new programmers an attitude about documentation that would inspire for a lifetime, overcoming sloth and schedule pressure. By and large we have failed. I think we have used wrong methods.

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In the previous two decades, as NUMMI’s success had become better known, executives in other industries had started adapting the Toyota Production System philosophy to other industries. In 2001, a group of computer programmers had gathered at a ski lodge in Utah to write a set of principles, called the “Manifesto for Agile Software Development,” that adapted Toyota’s methods and lean manufacturing to how software was created.

Her team had become NASA’s first computer programmers. The women still worked closely with the engineers, almost all of whom were men, but it was no longer enough for them just to be good at math. They needed to know how to build, fix, and run programs on the IBM computers, something the engineers rarely did.

The people most likely to grasp that wealth can be created are the ones who are good at making things, the craftsmen. Their hand-made objects become store-bought ones. But with the rise of industrialization there are fewer and fewer craftsmen. One of the biggest remaining groups is computer programmers.

Concurrent with the decline of manufacturing, the latter half of the twentieth century oversaw another shift. While earlier office technologies had supplemented workers and increased demand for them, the development of the microprocessor and computing technologies began to replace semiskilled service workers in many areas – for example, telephone operators and secretaries.20 The roboticisation of services is now gathering steam, with over 150,000 professional service robots sold in the past fifteen years.21 Under particular threat have been ‘routine’ jobs – jobs that can be codified into a series of steps. These are tasks that computers are perfectly suited to accomplish once a programmer has created the appropriate software, leading to a drastic reduction in the numbers of routine manual and cognitive jobs over the past four decades.22 The result has been a polarisation of the labour market, since many middle-wage, mid-skilled jobs are routine, and therefore subject to automation.23 Across both North America and Western Europe, the labour market is now characterised by a predominance of workers in low-skilled, low-wage manual and service jobs (for example, fast-food, retail, transport, hospitality and warehouse workers), along with a smaller number of workers in high-skilled, high-wage, non-routine cognitive jobs.24

The cultural divides within the advertising industry became wider when web pages became part of the marketing mix, beginning in 1995. Early web pages were like printed catalogs, and traditional advertising agencies knew how to design catalogs – they were just pictures and words in a different medium, right? The rub was that web pages seemed to clients and agencies more like the domain of software folk, like computer programmers, rather than the domain of traditional copywriters and art directors. An automotive company that wanted to put up web pages to help consumers choose car models and features was more likely to go to a group of programmers than to a traditional agency. The web production costs were exceptionally high, too – the hours spent by web designers and programmers far outstripped the creative hours spent on catalogs. Wasn’t the business of web design (and later, web advertising) a separate business? Traditional

speak to computers in a language that they understand and have them do anything that you want to do. This skill is one whose demand is increasing at an increasing rate the world over. Whether you want to learn code to pursue a career as a programmer, web developer or graphics designer or want to learn code to be able to develop your own web applications and other computerized systems, the one thing you need to do is to start somewhere. What better place to start

He’d been surprised to find that in at least one way he fit in: More than half the programmers at Goldman were Russians. Russians had a reputation for being the best programmers on Wall Street, and Serge thought he knew why: They had been forced to learn to program computers without the luxury of endless computer time. Many years later, when he had plenty of computer time, Serge still wrote out new programs on paper before typing them into the machine. “In Russia, time on the computer was measured in minutes,” he said. “When you write a program, you are given a tiny time slot to make it work. Consequently we learned to write the code in ways that minimized the amount of debugging. And so you had to think about it a lot before you committed it to paper. The ready availability of computer time creates this mode of working where you just have an idea and type it and maybe erase it ten times. Good Russian programmers, they tend to have had that one experience at some time in the past—the experience of limited access to computer time.

Any fool can write code that a computer can understand. Good programmers write code that humans can understand.

Hopper’s thrust was always to simplify and to demystify. She reserved some of her most cutting remarks for those who insisted that only an expert in writing machine code could run a machine; she had no time for programmers who saw themselves as high priests standing between computers and the public.46

Social capital is a capability that arises from the prevalence of trust in a society or in certain parts of it. It can be embodied in the smallest and most basic social group, the family, as well as the largest of all groups, the nation, and in all the other groups in between. Social capital differs from other forms of human capital insofar as it is usually created and transmitted through cultural mechanisms like religion, tradition, or historical habit. Economists typically argue that the formation of social groups can be explained as the result of voluntary contract between individuals who have made the rational calculation that cooperation is in their long-term self-interest. By this account, trust is not necessary for cooperation: enlightened self-interest, together with legal mechanisms like contracts, can compensate for an absence of trust and allow strangers jointly to create an organization that will work for a common purpose. Groups can be formed at any time based on self-interest, and group formation is not culture-dependent. But while contract and self-interest are important sources of association, the most effective organizations are based on communities of shared ethical values. These communities do not require extensive contract and legal regulation of their relations because prior moral consensus gives members of the group a basis for mutual trust. The social capital needed to create this kind of moral community cannot be acquired, as in the case of other forms of human capital, through a rational investment decision. That is, an individual can decide to “invest” in conventional human capital like a college education, or training to become a machinist or computer programmer, simply by going to the appropriate school. Acquisition of social capital, by contrast, requires habituation to the moral norms of a community and, in its context, the acquisition of virtues like loyalty, honesty, and dependability. The group, moreover, has to adopt common norms as a whole before trust can become generalized among its members. In other words, social capital cannot be acquired simply by individuals acting on their own. It is based on the prevalence of social, rather than individual virtues. The proclivity for sociability is much harder to acquire than other forms of human capital, but because it is based on ethical habit, it is also harder to modify or destroy. Another term that I will use widely throughout this book is spontaneous sociability, which constitutes a subset of social capital. In any modern society, organizations are being constantly created, destroyed, and modified. The most useful kind of social capital is often not the ability to work under the authority of a traditional community or group, but the capacity to form new associations and to cooperate within the terms of reference they establish. This type of group, spawned by industrial society’s complex division of labor and yet based on shared values rather than contract, falls under the general rubric of what Durkheim labeled “organic solidarity.”7 Spontaneous sociability, moreover, refers to that wide range of intermediate communities distinct from the family or those deliberately established by governments. Governments often have to step in to promote community when there is a deficit of spontaneous sociability. But state intervention poses distinct risks, since it can all too easily undermine the spontaneous communities established in civil society.

Computers: he always fixed on computers when his mind wandered into the future--instruments he revered and hated. The computer world was a place where snotty kids knew everything and nothing.... The computer was part of a future cloudy, unpredictable and menacing.

Although continual sound effects were common in VCS games, it is hard to produce anything that sounds like Western music on the machine. The frequencies that the TIA can generate miss most of the chromatic scale. When Garry Kitchen was working as a programmer for Activision, he went through and marked the notes that the Atari VCS could hit. He then asked a professional composer of jingles to put something together using only those notes.

Rayven T. Hill was born in 1954 in Markham, Ontario. He has had a variety of occupations and careers since then, spending the last fourteen years as a computer programmer and web site designer. His first

Vernor Vinge's novel, A Deepness in the Sky, describes a spacefaring trading civilization tens of thousands of years (hundreds of gigaseconds) in the future that apparently still uses the Unix epoch. The "programmer-archaeologist" responsible for finding and maintaining usable code in mature computer systems first believes that the epoch refers to the time when man first walked on the Moon, but then realizes that it is "the 0-second of one of Humankind’s first computer operating systems.