Software For Generating Quotes

Imagine a world in which generations of human beings come to believe that certain films were made by God or that specific software was coded by him. Imagine a future in which millions of our descendants murder each other over rival interpretations of Star Wars or Windows 98. Could anything -- anything -- be more ridiculous? And yet, this would be no more ridiculous than the world we are living in.

Religion knew the truth of metaphor and symbol for almost all of history until the past few hundred years, and especially until the wrongly named Enlightenment in the 17th and 18th centuries. Then we started confusing rational and provable with real. We actually regressed and went backward. In trying to defend its ground in the face of rationalism and scientism, religion tried to become "rational" itself and lost its alternative consciousness, which many of us call contemplation. It's as though we tried to deal with Mystery with the entirely wrong "software". We lost access to the higher levels of consciousness, the transrational, the transpersonal, the transcendent itself. Most tragic, we lost most inner experience of our own outer belief systems. That is the heart of religion's problem today, and it is indeed a deep and serious problem for upcoming generations. My generation took the symbols to literally, and now the following generation is just throwing them all out as useless. We are both losing. It might surprise you, but both religious fundamentalism and atheism are similar in that they are self-contained rational systems. Such a system works if you stay inside its chosen logic and territory.

Westrum’s description of a rule-oriented culture is perhaps best thought of as one where following the rules is considered more important than achieving the mission—and we have worked with teams in the US Federal Government we would have no issue describing as generative, as well as startups that are clearly pathological.

Businesses frequently prioritize new feature releases over fixing technical debt. They choose to work on revenue-generating work instead of revenue-protection work. This rarely works out as the business hopes, particularly as problems discovered during the final stages of uncompleted projects drag engineers away from the newer projects.

The man persisted. "No, no, no. It was so funny. What software did you use?" - apparently in the belief that the software had built-in humor generation.

No matter how good a jockey, he can’t turn a plow horse into a thoroughbred. It was the same with chips and software. Indeed, an operating system depended on a reliable chip.

Jeff Hammerbacher, a software coder and one of Facebook’s early hires, succinctly said, “The best minds of my generation are thinking about how to make people click ads. That sucks.

An entire generation of software engineers, capable of building the next generation of AI weaponry, has turned its back on the nation-state, disinterested in the messiness and moral complexity of geopolitics.

The digital keys in a user’s wallet are completely independent of the bitcoin protocol and can be generated and managed by the user’s wallet software without reference to the blockchain or access to the Internet.

If you collect hundreds of formal requirements and just start building software for all of them, you’ve generated a whole lot of work for skilled and dedicated project managers, but you haven’t made any real choices.

Both the Roadster and the Model S also take advantage of what’s known as regenerative braking, which extends the life of the brakes. During stop-and-go situations, the Tesla will brake by kicking the motor into reverse via software and slowing down the wheels instead of using brake pads and friction to clamp them down. The Tesla motor generates electricity during this process and funnels it back to the batteries, which is why electric cars get better mileage in city traffic.

I etch a pattern of geometric shapes onto a stone. To the uninitiated, the shapes look mysterious and complex, but I know that when arranged correctly they will give the stone a special power, enabling it to respond to incantations in a language no human being has ever spoken. ...Yet my work involves no witchcraft. The stone is a wafer of silicon, and the incantations are software. The patterns etched on the chip and the programs that instruct the computer may look complicated and mysterious, but they are generated according to a few basic principles that are easily explained.

Writing software is not a variable cost, but it's not really a fixed cost either. Writing software is an ongoing, revenue-generating operation of the company, and it is not the same as constructing a factory. The expensive craftsmen who build the factory leave and go to work on some other job after the building is erected.

A generation ago, fun wasn’t a deciding factor when we talked about career choices. Jobs aren’t supposed to be fun. They’re supposed to bring home the bacon. Fun is what you do on your off days. Fun happens in the evenings and weekends. But if your job isn’t fun, as we’ve come to realize, you don’t do a fantastic job at it.

Imagine a world in which generations of human beings come to believe that certain films were made by God or that specific software was coded by him. Imagine a future in which millions of our descendants murder each other over rival interpretations of Star Wars or Windows 98. Could anything—anything—be more ridiculous? And yet, this would be no more ridiculous than the world we are living in.

Most Web activities do not generate jobs and revenue at the rate of past technological breakthroughs. When Ford and General Motors were growing in the early part of the twentieth century, they created millions of jobs and helped build Detroit into a top-tier U.S. city. Today, Facebook creates a lot of voyeuristic pleasure, but the company doesn’t employ many people and hasn’t done much for Palo Alto; a lot of the “work” is performed more or less automatically by the software and the servers. You could say that the real work is done by its users, in their spare time and as a form of leisure. Web 2.0 is not filling government coffers or supporting many families, even though it’s been great for users, programmers, and some information technology specialists. Everyone on the Web has heard of Twitter, but as of Fall 2010, only about three hundred people work there.

The clarity offered by software as metaphor - and the empowerment allegedly offered to us who know software - should make us pause, because software also engenders a sense of profound ignorance. Software is extremely difficult to comprehend. Who really knows what lurks behind our smiling interfaces, behind the objects we click and manipulate? Who completely understands what one’s computer is actually doing at any given moment? Software as a metaphor for metaphor troubles the usual functioning of metaphor, that is, the clarification of an unknown concept through a known one. For, if software illuminates an unknown, it does so through an unknowable (software). This paradox - this drive to grasp what we do not know through what we do not entirely understand… does not undermine, but rather grounds software’s appeal. Its combination of what can be seen and not seen, can be known and no known - it’s separation of interface from algorithm, of software from hardware - makes it a powerful metaphor for everything we believe is invisible yet generates visible effects, from genetics to the invisible hand of the market, from ideology to culture. Every use entails an act of faith.

Security is a big and serious deal, but it’s also largely a solved problem. That’s why the average person is quite willing to do their banking online and why nobody is afraid of entering their credit card number on Amazon. At 37signals, we’ve devised a simple security checklist all employees must follow: 1. All computers must use hard drive encryption, like the built-in FileVault feature in Apple’s OS X operating system. This ensures that a lost laptop is merely an inconvenience and an insurance claim, not a company-wide emergency and a scramble to change passwords and worry about what documents might be leaked. 2. Disable automatic login, require a password when waking from sleep, and set the computer to automatically lock after ten inactive minutes. 3. Turn on encryption for all sites you visit, especially critical services like Gmail. These days all sites use something called HTTPS or SSL. Look for the little lock icon in front of the Internet address. (We forced all 37signals products onto SSL a few years back to help with this.) 4. Make sure all smartphones and tablets use lock codes and can be wiped remotely. On the iPhone, you can do this through the “Find iPhone” application. This rule is easily forgotten as we tend to think of these tools as something for the home, but inevitably you’ll check your work email or log into Basecamp using your tablet. A smartphone or tablet needs to be treated with as much respect as your laptop. 5. Use a unique, generated, long-form password for each site you visit, kept by password-managing software, such as 1Password.§ We’re sorry to say, “secretmonkey” is not going to fool anyone. And even if you manage to remember UM6vDjwidQE9C28Z, it’s no good if it’s used on every site and one of them is hacked. (It happens all the time!) 6. Turn on two-factor authentication when using Gmail, so you can’t log in without having access to your cell phone for a login code (this means that someone who gets hold of your login and password also needs to get hold of your phone to login). And keep in mind: if your email security fails, all other online services will fail too, since an intruder can use the “password reset” from any other site to have a new password sent to the email account they now have access to. Creating security protocols and algorithms is the computer equivalent of rocket science, but taking advantage of them isn’t. Take the time to learn the basics and they’ll cease being scary voodoo that you can’t trust. These days, security for your devices is just simple good sense, like putting on your seat belt.

As black-box technologies become more widespread, there have been no shortage of demands for increased transparency. In 2016 the European Union's General Data Protection Regulation included in its stipulations the "right to an explanation," declaring that citizens have a right to know the reason behind the automated decisions that involve them. While no similar measure exists in the United States, the tech industry has become more amenable to paying lip service to "transparency" and "explainability," if only to build consumer trust. Some companies claim they have developed methods that work in reverse to suss out data points that may have triggered the machine's decisions—though these explanations are at best intelligent guesses. (Sam Ritchie, a former software engineer at Stripe, prefers the term "narratives," since the explanations are not a step-by-step breakdown of the algorithm's decision-making process but a hypothesis about reasoning tactics it may have used.) In some cases the explanations come from an entirely different system trained to generate responses that are meant to account convincingly, in semantic terms, for decisions the original machine made, when in truth the two systems are entirely autonomous and unrelated. These misleading explanations end up merely contributing another layer of opacity. "The problem is now exacerbated," writes the critic Kathrin Passig, "because even the existence of a lack of explanation is concealed.

Entrepreneurship itself is an emergent system, where companies create the conditions for experimentation and learning to occur, often symbiotically with customers. In 1978, Eric von Hippel (my PhD advisor at MIT) pioneered the notion of user-driven innovation.10, 11 Back then, the conventional wisdom was that innovation only came from corporate, government, and university research-and-development labs. While some still believe this today, Eric's insight proved to be prescient in many areas, especially in the information age, as the widespread adoption of open-source software and Lean Startup methodologies have demonstrated.12 Twitter is a tangible example since three of the platform's most popular features—the @ reply, the # hashtag indexing, and retweet sharing—were all generated bottom-up by users.

Similarly, when you see a character jumping from a 100 story building and landing without hurting a bone, then believe that this is an example of special effects.   Special effects are provided by a few companies that use specialized software to add these effects. Many of these companies are located in India, in Bangalore and Mumbai. Movies like Avatar, Jurassic Park, and many others were sent to India for providing special effects.   Similarly, in Thor, when the main character rotates his hammer and generates a tornado, be rest assured that this is only an example of special effects. In reality, nothing like this happens.   And if you are able to do it, you are a superhuman, like Superman. You have got super-powers to do whatever you want and you can generate such a tornado by rotating your hand, even without a hammer.   So, my sincere advice to you is not to even attempt this. You will end up with a torn muscle, or a fractured hand, or maybe you may even suffer a heart malfunction and eventual death.   Let me not get into the science behind how this happens, but if you are educated enough, you will heed my advice and not attempt this anytime in your life.

One of those was Gary Bradski, an expert in machine vision at Intel Labs in Santa Clara. The company was the world’s largest chipmaker and had developed a manufacturing strategy called “copy exact,” a way of developing next-generation manufacturing techniques to make ever-smaller chips. Intel would develop a new technology at a prototype facility and then export that process to wherever it planned to produce the denser chips in volume. It was a system that required discipline, and Bradski was a bit of a “Wild Duck”—a term that IBM originally used to describe employees who refused to fly in formation—compared to typical engineers in Intel’s regimented semiconductor manufacturing culture. A refugee from the high-flying finance world of “quants” on the East Coast, Bradski arrived at Intel in 1996 and was forced to spend a year doing boring grunt work, like developing an image-processing software library for factory automation applications. After paying his dues, he was moved to the chipmaker’s research laboratory and started researching interesting projects. Bradski had grown up in Palo Alto before leaving to study physics and artificial intelligence at Berkeley and Boston University. He returned because he had been bitten by the Silicon Valley entrepreneurial bug.

There are hundreds of examples of highly functioning commons around the world today. Some have been around for centuries, others have risen in response to economic and environmental crises, and still others have been inspired by the distributive bias of digital networks. From the seed-sharing commons of India to the Potato Park of Peru, indigenous populations have been maintaining their lands and managing biodiversity through a highly articulated set of rules about sharing and preservation. From informal rationing of parking spaces in Boston to Richard Stallman’s General Public License (GPL) for software, new commons are serving to reinstate the value of land and labor, as well as the ability of people to manage them better than markets can. In the 1990s, Elinor Ostrom, the American political scientist most responsible for reviving serious thought about commoning, studied what specifically makes a commons successful. She concluded that a commons must have an evolving set of rules about access and usage and that it must have a way of punishing transgressions. It must also respect the particular character of the resource being managed and the people who have worked with that resource the longest. Managing a fixed supply of minerals is different from managing a replenishing supply of timber. Finally, size and place matter. It’s easier for a town to manage its water supply than for the planet to establish water-sharing rules.78 In short, a commons must be bound by people, place, and rules. Contrary to prevailing wisdom, it’s not an anything-goes race to the bottom. It is simply a recognition of boundaries and limits. It’s pooled, multifaceted investment in pursuit of sustainable production. It is also an affront to the limitless expansion sought by pure capital. If anything, the notion of a commons’ becoming “enclosed” by privatization is a misnomer: privatizing a commons breaks the boundaries that protected its land and labor from pure market forces. For instance, the open-source seed-sharing networks of India promote biodiversity and fertilizer-free practices among farmers who can’t afford Western pesticides.79 They have sustained themselves over many generations by developing and adhering to a complex set of rules about how seed species are preserved, as well as how to mix crops on soil to recycle its nutrients over centuries of growing. Today, they are in battle with corporations claiming patents on these heirloom seeds and indigenous plants. So it’s not the seed commons that have been enclosed by the market at all; rather, the many-generations-old boundaries have been penetrated and dissolved by disingenuously argued free-market principles.

Imagine an alternate universe in which people don’t have words for different forms of transportation—only the collective noun “vehicle.” They use that word to refer to cars, buses, bikes, spacecraft, and all other ways of getting from place A to place B. Conversations in this world are confusing. There are furious debates about whether or not vehicles are environmentally friendly, even though no one realizes that one side of the debate is talking about bikes and the other side is talking about trucks. There is a breakthrough in rocketry, but the media focuses on how vehicles have gotten faster—so people call their car dealer (oops, vehicle dealer) to ask when faster models will be available. Meanwhile, fraudsters have capitalized on the fact that consumers don’t know what to believe when it comes to vehicle technology, so scams are rampant in the vehicle sector. Now replace the word “vehicle” with “artificial intelligence,” and we have a pretty good description of the world we live in. Artificial intelligence, AI for short, is an umbrella term for a set of loosely related technologies. ChatGPT has little in common with, say, software that banks use to evaluate loan applicants. Both are referred to as AI, but in all the ways that matter—how they work, what they’re used for and by whom, and how they fail—they couldn’t be more different.

DEUTSCH: Yes, but you have to distinguish between hardware and software when you’re thinking about how this cognitive closure manifests itself. Like I said, it seems plausible that the hardware limitation is not relevant even for chimpanzees. I imagine that with nanosurgery, one could implant ideas into a chimpanzee’s brain that would make it able to create further knowledge just as humans can. I’m questioning the assumption that if everybody with an IQ of over a hundred died, then in the next generation nobody would have an IQ of over a hundred. I think they well might. It depends on culture. HARRIS: Of course. This wasn’t meant to be a plausible biological or cultural assumption. I’m just asking you to imagine a world in which we had seven billion human beings, none of whom could begin to understand what Alan Turing was up to. DEUTSCH: That nightmare scenario is different. It’s something that actually happened—for almost the whole of human existence. Humans had the ability to be creative and to do everything we’re doing. They just didn’t, because their culture was wrong. It wasn’t their fault. Cultural evolution has a nasty tendency to suppress the growth of what we would consider science or anything important that would improve their lives. So yes, that’s possible, and it’s possible that it could happen again. Nothing can prevent it except our working to prevent it.

In effect, we know from Darwin that there are only four characteristics necessary in order to get adaptive evolution, right? If you have reproduction, variation, differential success, and an environment of limited resources, you're going to get adaptive evolution. When we set up an economic system, or a political system...*it evolves*. Things evolve within it. And if we don't anticipate that what we write down in our documents about what we're trying to accomplish does not have the capacity to overwhelm whatever niche we have set up and that we will ultimately see the creatures that are supported by the environment that we created, then we will never get this right. Because we will always be fooled by our own intentions, and we will create structures that create predators of an arbitrary kind. So we need to start thinking evolutionarily, because that's the mechanism for shaping society into something of a desirable type rather than a monstrous type. [...] So let's say we're talking about a political structure...and we know we don't like corruption...and we're going to set a penalty for attempting to corrupt the system. OK, now what you've done is you've built a structure in which evolution is going to explore the questions, 'What kind of corruptions are invisible?' and 'What kinds of penalties are tolerable from the point of view of discovering how to alter policy in the direction of some private interest?' Once you've set that up, if you let it run, evolutionarily it will create a genius corruptor, right? It will generate something that is capable of altering the functioning of the system without being spotted, and with being only slightly penalized -- and then you'll have no hope of confronting it, because it's going to be better at shifting policy than you will be at shifting it back. So what you have to do is, you have to build a system in which there *is no selection* that allows for this process to explore mechanisms for corrupting the system, right? You may have to turn the penalties up much higher than you would think, so that any attempt to corrupt the system is ruinous to the thing that attempts it. So the thing never evolves to the next stage, because it keeps going extinct, right? That's a system that is resistant to the evolution of corruption, but you have to understand that it's an evolutionary puzzle in the first place in order to accomplish that goal. [...] We sort of have this idea that we inherited from the wisdom of the 50s that genes are these powerful things lurking inside of us that shift all of this stuff that we can't imagine they would have control over, and there's some truth in it. But the larger truth is that so much of what we are is built into the software layer, and the software layer is there because it is rapidly changeable. That's why evolution shifted things in that direction within humans. And we need to take advantage of that. We need to be responsible for altering things carefully in the software, intentionally, in order to solve problems and basically liberate people and make life better for as many people as possible, rather than basically throw up our hands because we are going to claim that these things live at the genetic layer and therefore what can we do?

intellectual imperialism. It has been, and still is, used to denigrate the orientation that many people still experience, that the world, and the other organisms with which we share this Earth, are alive, intelligent, and aware. It has been used to stifle the response of the heart to what has been presented to the senses. This has resulted in the creation of a conceptual monoculture that can’t see outside its limitations. Such imperialists have set out to conquer the superstitious natives inhabiting the dark continent, the place where the general populace lives. Midgley makes the point that arguments such as Day’s rest in a belief in human beings as “an isolated will, guided by an intelligence, arbitrarily connected to a rather unsatisfactory array of feelings, and lodged, by chance, in an equally unsatisfactory human body.”18 Or as Susan Sontag once described it: “consciousness harnessed to flesh,”19 as if there could be consciousness without the emergence of the self-organized system we call the body. This type of dissociation is a common side effect of the materialist and very reductionist view of the world most of us are trained in. But as Midgely notes, this system of thought is not reason, not science, but behavioral examples of, as she puts it, an unexamined, “exuberant power fantasy.” It is bad software, generated out of unexamined psychological frameworks. The evolutionary escalator metaphor and the assumptions of what constitutes intelligence (and value) that are embedded within it create, automatically, behavior that is very dangerous to every other life-form on this planet—in fact to the health of every ecosystem this planet possesses.

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How to choose a best website development company RNS IT Solutions is the best Software development company. When choosing a development company for your website, it is very important not only to look at the price, but also the quality of the work you hope to obtain and it is that a good Web of quality, realized of the hand of good engineers who have been working in the sector for years, can make you recover the investment in a short time and generate great benefits in the long term. Of course, to have a quality website the initial investment will probably be greater than you expect and maybe right now you think that the web you need does not require much quality, or a lot of work, but stop to think for a moment and consider the possibility that you are totally wrong, because that may depend on the future of your company as well as Web Development company India.The image that you want to transmit to the clients of the same one and the investment that you will have to do in the web once developed. With all this I do not mean that you have to ask for a loan from the bank to pay for the web. If the project you have in mind takes more work than you initially thought and the budget is out of your expectations, you can always limit and remove features that are dispensable. In this way you can publish the Web as soon as possible, so that once the initial investment is amortized, you can continue investing in adding those features that were left in the background. There are few Web Development Company In India hat right now could not survive, if they were not involved in the online world and it costs much less to make you a quality professional website, with a higher initial investment, to make you a website on which you have to invest, and then large amounts in development and consulting to correct deficiencies initially not contemplated. In the worst case, a bad development, may even force you to throw all the code of the web to the trash, to have to start from scratch. But what is quality of Web Development Services India? Let's see the characteristics that a website must have in order to be considered quality and professional: In any development project, meetings are always held to develop an initial analysis, gathering all the requirements and objectives of the web that the client wants. At this point you should have a proactive attitude, proposing functionalities that could be interesting or alternative ideas that we know can generate good results.

However, if you are having trouble figuring out what to do for the particular situation, there’s a good chance that the caller won’t know what to do either. Generating an exception in a situation like this just passes the problem to someone else and adds to the system’s complexity.

This was the power of Andrew Carnegie’s legacy. He had used his wealth to set up over 2,000 public libraries across North America. Three generations after his death, they were continuing to pay dividends. These new American citizens were fortunate that Carnegie had thought long-term. For the Taiwanese boys, Carnegie had created the hardware, and their mother the software. This bode well for their assimilation and success in America.

With the advent of cloning, this kind of thing is occurring not just at the level of messages but also in terms of individuals. Indeed, this is exactly what happens to the body when it is conceived of as nothing more than a message, nothing more than computer fodder. In such circumstances there is no obstacle in the way of a mass reproduction of the body exactly comparable to the mass reproduction of industrial objects and mass-media images described by Benjamin. Thus reproduction precedes production, and the genetic model of the body precedes all possible bodies. An exploding technology is what presides over this reversal - that technology which Benjamin was already able to describe, in its ultimate consequences, as a total medium; but Benjamin was writing in the industrial era: by then technology itself was a gigantic prosthesis governing the generation of identical objects and images which there was no longer any way of distinguishing from one another, but it was as yet impossible to foresee the technological sophistication of our own era, which has made it possible to generate identical beings, without any means of returning to an original. The prostheses of the industrial era were still external, exotechnical, whereas those we know now are ramified and internalized -esotechnical. Ours is the age of soft technologies, the age of genetic and mental software.

4. The potential levers to improve employees’ experience We have identified three levers to enable the transition from the current breakdown of employee activities to the ideal division of activities. They are: Automate: companies should identify and automate routine activities, such as generating a PowerPoint presentation for a weekly meeting or recording invoices in accounting software. Augment: organizations should seize the opportunity to increase the value of work activities delivered by employees. IA is used as a crucial component here, with, for example, the generation of insights through advanced analytics to help decision making. Abandon: some work activities do not fit with leading practices for efficient work, and represent an obstacle to the employee’s experience. These activities should be reduced or eliminated. For example, restricting the volume of meetings and email traffic is essential. We call these levers the “Triple-A artifact”. It has proven to be a handy framework to help organizations build their action plans to boost their employee experience.

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Figure 1.1: The three stages of life: biological evolution, cultural evolution and technological evolution. Life 1.0 is unable to redesign either its hardware or its software during its lifetime: both are determined by its DNA, and change only through evolution over many generations. In contrast, Life 2.0 can redesign much of its software: humans can learn complex new skills—for example, languages, sports and professions—and can fundamentally update their worldview and goals. Life 3.0, which doesn’t yet exist on Earth, can dramatically redesign not only its software, but its hardware as well, rather than having to wait for it to gradually evolve over generations.

Project management is the art of getting things done. Product management is deciding what to do in the first place—and also, as in the case of the benefit screeners, deciding what not to do. If you collect hundreds of formal requirements and just start building software for all of them, you’ve generated a whole lot of work for skilled and dedicated project managers, but you haven’t made any real choices.

Casper makes mattresses and distributes them directly to consumers via their website. I was always intrigued with how Casper could be considered a tech company, raising substantial money from Silicon Valley venture capitalists and fetching tech-like valuations in the process. Could there be an industry that feels less like technology than the pile of springs and fabric you sleep on?! But indeed Casper is a tech company. The technology isn’t about the product itself, but about how they acquire customers, how they distribute the product, and ultimately how they make the customers feel throughout the whole process of buying and using the product. Because of technology, they can do it at scale with minimal investment. They use digital engagement strategies to grow incredibly fast. Just five years since their founding, they’re doing nearly $500 million in revenue with fewer than one hundred employees. By contrast, Tempur Sealy, the largest mattress company in the world, employs seven thousand people to generate $2.7 billion in revenue.

LEARN THE SCIENCE OF THE SOUL, THE SOURCE CODE OF THE SOFTWARE BASED ON WHICH YOU ARE FUNCTIONING, OPERATING, GIVING COMMANDS, GENERATING COMMANDS.

IBM launched its Chess machine, renamed simply the Personal Computer, in August 1981, a scant four months after the Star. Judged against the technology PARC had brought forth, it was a homely and feeble creature. Rather than bitmapped graphics and variable typefaces, its screen displayed only ASCII characters, glowing a hideous monochromatic green against a black background. Instead of a mouse, the PC had four arrow keys on the keyboard that laboriously moved the cursor, character by character and line by line. No icons, no desktop metaphor, no multitasking windows, no e-mail, no Ethernet. Forswearing the Star’s intuitive point-and-click operability, IBM forced its customers to master an abstruse lexicon of typed commands and cryptic responses developed by Microsoft, its software partner. Where the Star was a masterpiece of integrated reliability, the PC had a perverse tendency to crash at random (a character flaw it bequeathed to many subsequent generations of Microsoft Windows-driven machines). But where the Star sold for $16,595-plus, the IBM PC sold for less than $5,000, all-inclusive. Where the Star’s operating system was closed, accessible for enhancement only to those to whom Xerox granted a coded key, the PC’s circuitry and microcode were wide open to anyone willing to hack a program for it—just like the Alto’s. And it sold in the millions.

2.0 can redesign much of its software: humans can learn complex new skills—for example, languages, sports and professions—and can fundamentally update their worldview and goals. Life 3.0, which doesn’t yet exist on Earth, can dramatically redesign not only its software, but its hardware as well, rather than having to wait for it to gradually evolve over generations.

Like a glitch in our biological software, repetition has no logical connection to truth. Yet it has somehow become a trap door to our beliefs. Sadly, governments, bullies, and leaders have used this trap for generations.

The more you produce, the more you have to read. Automated code generation only makes matters worse. As Martin Fowler writes about low code quality: “Even small changes require programmers to understand large areas of code, code that’s difficult to understand.” [32] Code that’s difficult to understand slows you down. On the other hand, every minute you invest in making the code easier to understand pays itself back tenfold.

In software development, engineers are often pressured to deliver features instead of fixing defects, addressing reliability issues, or working on internal improvement projects. As a result, so called “technical debt”§§ adds up, leading to more complex problems that are increasingly difficult to solve. Consequently, Marty Cagan, a product expert who has trained generations of product leaders on building software products that customers love, stresses the importance for product and engineering leaders to allocate at least 20% of engineering’s time to proactively fix issues before they snowball into catastrophic ones, such as having to “rewrite the entire codebase from scratch.

In 2012, a team of researchers at Google found that psychological safety was the top predictor of team effectiveness.8 Similarly, in the State of DevOps research, a high-trust culture, which includes psychological safety, predicted software delivery and organizational performance in technology value streams, as measured by the Westrum organizational typology model, which divided organizations into pathological, bureaucratic, and generative.

Financial management takes on a new meaning when you enter a partnership with a private equity group. There are software systems marketed to investment firms to consolidate their financials among the companies they own. For them, it has many benefits. It simplifies financial reporting and management of their investments. For the operating companies, it may provide huge value if their current reporting systems are inadequate. However, if your company has a well-implemented modern system, this can be a burden. Imagine having someone come in and require that you abandon your cuttingedge integrated system and, instead, put your reports in their format. I have a friend who was a CFO with a modern ERP system who was required to integrate their company’s reporting with an antiquated Excel-based report generator because their new equity partners required their charts to look a certain way. It cost them time and money that could have been applied to building their company’s value elsewhere.

The Importance of Bookkeeping Services for Businesses Effective bookkeeping is the foundation of any successful business. It involves the systematic recording, organizing, and managing of a company’s financial transactions. Whether you're a small business owner or running a large corporation, bookkeeping services help ensure that your financial records are accurate, up-to-date, and compliant with regulations. By outsourcing bookkeeping tasks to professionals, businesses can focus on growth and core operations without worrying about financial details. What Is Bookkeeping? Bookkeeping is the process of maintaining accurate records of all financial transactions, including sales, purchases, receipts, and payments. It involves organizing these records into categories like income, expenses, assets, and liabilities. The information generated through bookkeeping is essential for creating financial statements, tax filings, and understanding the overall financial health of the business. However, managing these tasks manually can be time-consuming and prone to errors, which is why many businesses opt for professional bookkeeping services. Benefits of Professional Bookkeeping Services One of the key benefits of hiring professional bookkeeping services is the accuracy they bring to financial management. Experienced bookkeepers are well-versed in the latest accounting software and financial regulations, ensuring that all records are kept accurately and consistently. Additionally, outsourcing this task allows business owners to save time and focus on other aspects of their business. As a result, they can make better financial decisions based on reliable data. Improved Financial Reporting Accurate bookkeeping leads to better financial reporting, which is critical for making informed business decisions. By keeping detailed and organized records, bookkeepers provide valuable insights into cash flow, profitability, and expenses. This allows businesses to plan their budgets more effectively, track financial performance, and identify areas for cost-saving or investment. Tax Compliance and Preparation Another important advantage of bookkeeping services is the ability to stay compliant with tax regulations. Bookkeepers ensure that all financial records are properly maintained and ready for tax season. With accurate and up-to-date records, businesses can avoid penalties and reduce the risk of audits, making tax preparation much smoother. In conclusion, professional bookkeeping services offer businesses the support they need to manage their financial records accurately and efficiently. By ensuring proper financial reporting and tax compliance, these services contribute to long-term financial stability and growth.

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Think about it. There are some phrases that just wouldn’t appear in the English language:* ‘I chose not to be angry.’ ‘He plans to fall in love at 4.30pm tomorrow.’ ‘She decided that she was no longer to feel uneasy in his presence.’ ‘From that moment on, she determined no longer to be afraid of heights.’* ‘He decided to like spiders and snakes.’ Things like this are not under our direct control, but are rather the product of instinctive and automatic emotions. There is a good evolutionary reason why we are imbued with these strong, involuntary feelings: feelings can be inherited, whereas reasons have to be taught, which means that evolution can select for emotions much more reliably than for reasons. To ensure your survival, it is much more reliable for evolution to give you an instinctive fear of snakes at birth than relying on each generation to teach its offspring to avoid them. Things like this aren’t in our software – they are in our hardware.

Continuous Glucose Monitoring I believe CGM is the most powerful technology for generating the data and awareness to rectify our Bad Energy crisis in the Western world. A CGM is a biosensor that can alert us to early dysfunction, coach us on how to eat and live in a way that promotes Good Energy in our unique bodies, and promote accountability. My belief in the potential of this technology to reduce global metabolic suffering is why I cofounded Levels, which enables access to CGMs and software to understand and interpret the data. A CGM is a small plastic disc worn on the arm that automatically tests your blood sugar roughly every ten minutes, twenty-four hours a day. And it sends that information to your smartphone.

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So can we arrive at a general principle as to why e-books have flopped in developed markets while audio and video streaming have triumphed? The technology commentator and best-selling author Edward Tenner argues that there are several reasons people are sometimes reluctant to abandon an old technology in favor of a new one. The first involves the potential vulnerabilities of the new thing. For instance, the fax machine is now a museum piece, but for a while people continued to prefer it over emailing scanned documents out of security concerns. Another potential reason involves aesthetics and nostalgia. Although dwarfed by music CDs and streaming, vinyl record sales continue to grow within the niche market of music aficionados. And despite improvements in automatic transmissions, certain car lovers prefer stick shifts. Perhaps the key to understanding format resilience is that technologies rise and fall as part of ecosystems, rarely on their own or by themselves. Those ecosystems need to evolve quickly, through open innovation, in order to appeal to new generations of users, transforming the landscape in the process. E-book platforms have remained fundamentally closed to external innovators, especially on the software side. As a result, the functionality of e-books remains limited. Moreover, research indicates that reading a physical book enables the reader to absorb information more efficiently than reading the same book on an e-reader or a tablet. “The implicit feel of where you are in a physical book turns out to be more important than we realized,” argues Abigail Sellen, a scientist and engineer at Microsoft Research Cambridge in England. “Only when you get an e-book do you start to miss it. I don’t think e-book manufacturers have thought enough about how you might visualize where you are in a book.

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with Facebook’s purchase of Instagram following the introduction of the front-facing camera. By 2012, many teen girls would have felt that “everyone” was getting a smartphone and an Instagram account, and everyone was comparing themselves with everyone else. Over the next few years the social media ecosystem became even more enticing with the introduction of ever more powerful “filters” and editing software within Instagram and via external apps such as Facetune. Whether she used filters or not, the reflection each girl saw in the mirror got less and less attractive relative to the girls she saw on her phone. While girls’ social lives moved onto social media platforms, boys burrowed deeper into the virtual world as they engaged in a variety of digital activities, particularly immersive online multiplayer video games, YouTube, Reddit, and hardcore pornography—all of which became available anytime, anywhere, for free, right on their smartphones. With so many new and exciting virtual activities, many adolescents (and adults) lost the ability to be fully present with the people around them, which changed social life for everyone, even for the small minority that did not use these platforms. That is why I refer to the period from 2010 to 2015 as the Great Rewiring of Childhood. Social patterns, role models, emotions, physical activity, and even sleep patterns were fundamentally recast, for adolescents, over the course of just five years. The daily life, consciousness, and social relationships of 13-year-olds with iPhones in 2013 (who were born in 2000) were profoundly different from those of 13-year-olds with flip phones in 2007 (who were born in 1994).

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An upcoming platform combining two of the X1 chips can process data collected from up to 12 high-definition cameras monitoring traffic, blind spots and other safety conditions in driver assistance systems, Huang said. Combined with next-generation software, the chips can help detect and read road signs, recognize pedestrians and detect braking vehicles, he said. Santa Clara, California-based Nvidia in recent years has been expanding beyond its core business of designing high-end graphics chips for personal computers. After struggling to compete against larger chipmakers like Qualcomm in smartphones and tablets, Nvidia is now increasing its focus on using its Tegra mobile chips in cars and is already supplying companies including Audi, BMW and Tesla.

In July, the mother of Sonic had left Sega, along with Jude Lange, to start their own software developer, Crystal Dynamics.

Effectiveness in terms of overall business value generated is more important than efficiency in terms of departmental cost.

We select our target customer segments, we design our value propositions to best serve these customer segments, we choose which type of relationships we will have with our customers and we choose which channels we will use to find, win, make, keep and grow our happy customers. We call this part of the business model the “Front Office.” Our front office activities will generate customers and revenue. In the “Back Office” of our business model we need to employ certain key resources that can execute certain key activities delivering our value propositions to our customers. The back office often builds relationships with key partners5 and the back office generates cost.

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PC makers put crapware on their computers—antivirus software, subscription offers, and so on—precisely because the revenue is lucrative. Apple forgoes such opportunities time and again, convinced that high-quality products will ultimately generate more profits. It’s a classic long-term approach.

IV. Real techies don’t worry about forced eugenics. I learned this from a real techie in the cafeteria of a software company. The project team is having lunch and discussing how long it would take to wipe out a disease inherited recessively on the X chromosome. First come calculations of inheritance probabilities. Given a population of a given size, one of the engineers arrives at a wipe-out date. Immediately another suggests that the date could be moved forward by various manipulations of the inheritance patterns. For example, he says, there could be an education campaign. The six team members then fall over one another with further suggestions. They start with rewards to discourage carriers from breeding. Immediately they move to fines for those who reproduce the disease. Then they go for what they call “more effective” measures: Jail for breeding. Induced abortion. Forced sterilization. Now they’re hot. The calculations are flying. Years and years fall from the final doom-date of the disease. Finally, they get to the ultimate solution. “It’s straightforward,” someone says. “Just kill every carrier.” Everyone responds to this last suggestion with great enthusiasm. One generation and—bang—the disease is gone. Quietly, I say, “You know, that’s what the Nazis did.” They all look at me in disgust. It’s the look boys give a girl who has interrupted a burping contest. One says, “This is something my wife would say.” When he says “wife,” there is no love, warmth, or goodness in it. In this engineer’s mouth, “wife” means wet diapers and dirty dishes. It means someone angry with you for losing track of time and missing dinner. Someone sentimental. In his mind (for the moment), “wife” signifies all programming-party-pooping, illogical things in the universe. Still, I persist. “It started as just an idea for the Nazis, too, you know.” The engineer makes a reply that sounds like a retch. “This is how I know you’re not a real techie,” he says.

While it was possible, then, for Apple to make up ground in software very quickly, doing so in the world of data was substantially more challenging even for a company of its resources. There are no shortcuts, as data simply cannot be generated overnight. There are only two means of producing it: collecting it over time, or acquiring an entity who has done so. Unlike software, then, which is a thin shield against would-be market entrants, organizations that amass a large body of data from which to extract value for themselves or their customers are well protected against even the largest market incumbents. Every software organization today should be aggregating data, because customers are demanding it. Consider, for example, online media services such as Netflix or Pandora. Their ability to improve their recommendations to customers for movies or music depends in turn on the data they’ve collected from other customers. This data, over time, becomes far more difficult to compete with than mere software. Which likely explains why Netflix is willing to open source the majority of its software portfolio but guards the API access to its user data closely.

In its place had arisen a Promised Land of Duane Reades and Chase ATMs on every corner, luxury doorman buildings, Pilates studios and spin classes, eighteen-dollar rosemary-infused cocktails and seven-dollar cups of single-origin coffee—all of which were there to cater to a new generation of twentysomethings, the data scientists and brand strategists and software engineers and social media managers and product leads and marketing associates and IT coordinators ready to disrupt the world with apps. And today, like every day, they would work until it was dark again, and then they would go to dinner parties or secret cocktail bars or rooftop events, and most of them would end the night watching Netflix on their laptops in bed" - Prologue, Save Your Generation, in Doree Shafrir's Startup

Having studied both the possible risks and the likely rewards, the Guardian’s managers decided both to “open in” the website, by bringing in more data and applications from the outside, and to “open out” the site, by enabling partners to create products using Guardian content and services on other digital platforms. To work toward the “open out” goal, the Guardian created a set of APIs that made its content easily available to external parties. These interfaces include three different levels of access. The lowest access tier, which the paper calls Keyless, allows anyone to use Guardian headlines, metadata, and information architecture (that is, the software and design elements that structure Guardian data and make it easier to access, analyze, and use) without requesting permission and without any requirement to share revenues that might be generated. The second access tier, Approved, allows registered developers to reprint entire Guardian articles, with certain time and usage restrictions. Advertising revenues are shared between the newspaper and the developers. The third and highest access tier, Bespoke, is a customized support package that provides unlimited use of Guardian content—for a fee.

Both magnetic and optical storage formats—videotape, digital discs, and drives—decay much faster than commercial film stock. Despite living in the cloud, there is no heaven for digital data. And in fifty years, even if our CDs, DVDs, flash drives, and YouTube accounts retain their contents, which is unlikely, there will be no devices or software with which to read them. Skip even one generation of technological change and the precious photos, videos, or letters on the floppy disks in the closet become inaccessible or illegible.

Launching a service booking platform like OpenTable, the restaurant reservation system, poses a classic chicken-or-egg problem. Without a large base of participating restaurants, why would patrons visit the OpenTable site? But without a large base of patrons, why would restaurants choose to participate? OpenTable solved the problem by first distributing booking management software that restaurants could use to manage their seating inventory. Once OpenTable had enough restaurants on board, they built out the consumer side, which allowed them to start booking tables and collecting a lead generation fee from the restaurants.

The Linux world behaves in many respects like a free market or an ecology, a collection of selfish agents attempting to maximize utility which in the process produces a self-correcting spontaneous order more elaborate and efficient than any amount of central planning could have achieved. Here, then, is the place to seek the “principle of understanding”. The “utility function” Linux hackers are maximizing is not classically economic, but is the intangible of their own ego satisfaction and reputation among other hackers. (One may call their motivation “altruistic”, but this ignores the fact that altruism is itself a form of ego satisfaction for the altruist). Voluntary cultures that work this way are not actually uncommon; one other in which I have long participated is science fiction fandom, which unlike hackerdom has long explicitly recognized “egoboo” (ego-boosting, or the enhancement of one’s reputation among other fans) as the basic drive behind volunteer activity. Linus, by successfully positioning himself as the gatekeeper of a project in which the development is mostly done by others, and nurturing interest in the project until it became self-sustaining, has shown an acute grasp of Kropotkin’s “principle of shared understanding”. This quasi-economic view of the Linux world enables us to see how that understanding is applied. We may view Linus’s method as a way to create an efficient market in “egoboo” — to connect the selfishness of individual hackers as firmly as possible to difficult ends that can only be achieved by sustained cooperation. With the fetchmail project I have shown (albeit on a smaller scale) that his methods can be duplicated with good results. Perhaps I have even done it a bit more consciously and systematically than he. Many people (especially those who politically distrust free markets) would expect a culture of self-directed egoists to be fragmented, territorial, wasteful, secretive, and hostile. But this expectation is clearly falsified by (to give just one example) the stunning variety, quality, and depth of Linux documentation. It is a hallowed given that programmers hate documenting; how is it, then, that Linux hackers generate so much documentation? Evidently Linux’s free market in egoboo works better to produce virtuous, other-directed behavior than the massively-funded documentation shops of commercial software producers. Both the fetchmail and Linux kernel projects show that by properly rewarding the egos of many other hackers, a strong developer/coordinator can use the Internet to capture the benefits of having lots of co-developers without having a project collapse into a chaotic mess. So to Brooks’s Law I counter-propose the following: Provided the development coordinator has a communications medium at least as good as the Internet, and knows how to lead without coercion, many heads are inevitably better than one.

Generative testing is an approach to testing software that was made popular by the QuickCheck library. Originally written in Haskell and since ported to several other programming languages (Ruby, Python, C, C++, Objective-C, Smalltalk, Java, JavaScript, Erlang, Scala, Clojure...), the QuickCheck library allows the developer to separate test logic from the generation of test cases. This means that, as developers, we can spend less time instructing the compiler how to test our code, and focus instead on what properties we expect our code to have.

Can’t we do better with Applicant Tracking System (ATS) software?

Today, the “mental workout” has gained great currency in the popular imagination. Brain gyms and memory boot camps are a growing fad, and brain training software was a $265 million industry in 2008, no doubt in part because of research that shows that older people who keep their minds active with crossword puzzles and chess can stave off Alzheimer’s and progressive dementia, but mostly because of the Baby Boomer generation’s intense insecurity about losing their marbles.

For example, Twist is “call-ahead” software that sees where you are and knows where you are heading, as well as knowing the driving conditions en route. It sends a text message to your next appointment while you keep your hands and your mind on the road. Glympse, as we mentioned, is similar and lets you share your location with others—who just might rat you out when you speed. GasBuddy.com lets you find the cheapest gas near your location. Nooly Micro Weather reports uber-localized weather, within .4 miles of where you are and just 15 minutes into the future, preparing you for the fog bank around the next curve on a mountain road. As we write this, it is available as a phone app and the developer is working with Ford and Toyota for the app to be included in cars as they ship. The integrated, automotive Nooly will signal the car to turn on fog lights or the defroster a moment before the weather changes. Waze is a mobile app that lets drivers share updates on road conditions in near realtime. With a community of nearly 50 million members as of May 2013, it is perhaps the most robust source of user-generated road data in the world. Google acquired Waze in the summer of 2013 for just under $1 billion.

Each group was required to propose its own “fitness function”—a linear equation that it could use to measure its own impact without ambiguity. For example, a two-pizza team in charge of sending advertising e-mails to customers might choose for its fitness function the rate at which these messages were opened multiplied by the average order size those e-mails generated. A group writing software code for the fulfillment centers might home in on decreasing the cost of shipping each type of product and reducing the time that elapsed between a customer’s making a purchase and the item leaving the FC in a truck. Bezos wanted to personally approve each equation and track the results over time. It would be his way of guiding a team’s evolution. Bezos was applying

Q: How many Java programmers does it take to change a lightbulb? A: One, to generate a “ChangeLightBulb” event to the socket. Q: How many C++ programmers does it take to change a lightbulb? A: You’re still thinking procedurally. A well-designed lightbulb object would inherit a change method from a generic lightbulb class. Q: How many Windows programmers does it take to change a lightbulb? A: Three. One to write WinGetLightBulbHandle, one to write WinQueryStatusLightBulb, and one to write WinGetLight-SwitchHandle. Q: How many database programmers does it take to change a lightbulb? A: Three. One to write the lightbulb removal program, one to write the lightbulb insertion program, and one to act as a lightbulb administrator to make sure nobody else tries to change the light-bulb at the same time. Q: How many software engineers does it take to change a lightbulb? A: None. That’s a hardware problem. Q: How many Microsoft engineers does it take to change a lightbulb? A: None. They will redefine darkness as an industry standard.

By the summer of 1988, Bill Gates was the leading representative of a new breed of tycoon: the software superrich. Just as oil created a kind of royalty in the last century, “wildcat” programmers had emerged among the wealthiest self-made men in America. Paul Allen, who had left Microsoft because of illness, was worth megamillions. So were the founders of other leading software companies. At the age of thirty-three, Gates was the youngest billionaire in the United States.

Despite his harsh criticisms Gates admired programmers and invariably put them in charge of projects, where they could both manage and program. While this double duty was stressful, Gates wanted to avoid a situation in which professional managers, with either no programming experience or out-of-date knowledge, held sway. It was destructive to rely on management pros to run software teams—or the company. They could not distinguish a promising program from a bust or evaluate schedules or product designs. At companies run by professionals, managers almost always came to mistrust their programmers, whom they could neither understand nor control. Gates

Nathan Myrhvold had been a protégé of the celebrated physicist Stephen Hawking before forming a software company in Berkeley, California, with some fellow Princeton University Ph.D’s. What drew Myrhvold, or any physicist, to programming? The outer reaches of science increasingly relied on computers; the days of a genius scribbling formulas on the back of an envelope had almost vanished. Physicists usually saw programming as a means to an end. Myrhvold found that his attachment to software superseded his fascination with physical science. His company gained wide notice when he and his friends wrote a faster, smaller clone of IBM’s TopView graphics program. IBM briefly considered making TopView the software interface—the piece seen by customers—for PCs. Trying to keep pace with IBM, Gates wanted a clone of TopView, so he bought Myrhvold’s company. Since

Having grown rapidly, many PC software companies were stretched to the limit simply building their programs. With customers clamoring for new products, testing inevitably had to take a backseat. In addition, though it was eroding, there remained a pejorative attitude toward testing: “Let the customer test the program.” That saved the builder money and time, but it frustrated buyers, who came to view the first release of a program as a gamble. Microsoft

In the formative years of digital computing, following World War II, both the operating system and applications were considered afterthoughts by designers. The “hardware” of electronics, as distinct from the “software” of programs, was so difficult that engineers could hardly see past it. The most important type of hardware was the circuitry or processors that actually carried out the instructions given the computer. A second set of devices made it possible to get data into and out of a computer. A third class stored information. A fourth class allowed one computer to send information to another, over special cable or telephone lines. The question of software generally arose only after the hardware pieces fell into place.

In the early 1960s, IBM attempted to revolutionize the field of software by making it possible to run the same program on any number of computers. IBM proposed a family of machines, covering most of the market and controlled by one operating system. The System/360 line, developed at a cost of five hundred million dollars, was a huge success.

It wasn’t until five years after the first 360 hardware was introduced in 1964 that all of its software ran well. By then, IBM had spent nearly as much writing the software as designing the hardware. This astonished the company’s managers and vividly highlighted “the greatest impediment to advances in computer technology,” the problem of managing large software projects. At

What is an operating system, really? What did Cutler’s team wish to create? Picture a wealthy English household in the early 1900s. Think of a computer—the hardware—as a big house, the family’s residence. The house consists of plumbing and lighting, bricks and mortar, windows and doors—all manner of physical things and processes. Next, imagine computer software as the people in the house. The household staff, living downstairs, provide a whole range of services at once. The butler stands by the door, the driver washes the car, the housekeeper presses the linen, the cook provides meals and bakes cakes, the gardener rakes the leaves from the lawn. And this activity, which seemingly happens of its own accord, is coordinated by the head of the household staff. Such is the life of the downstairs dwellers, who in a certain sense exist in the background. Then consider the people upstairs. They are the whole reason for the toil of the people downstairs. The husband desires a driver not simply for peace of mind but because he wishes to travel. The wife employs a cook, so her family can eat well. The children benefit from the work of the gardener, who clears the yard of debris, enabling them to play outdoors safely. The picture of the family upstairs and their faithful downstairs servants neatly illustrates the great divide in the world of software. The people upstairs are the applications: the word-processing, electronic ledger, database, publishing and numerous other programs that satisfy human needs and wants. The people downstairs collectively perform the functions of an operating system. Theirs is a realm of services, some automatic, some requiring a special request. These services lay the basis for the good stuff of life. Cutler

After he returned to London, we talked on the phone almost every day, and he got busy tinkering with the software. After I took a look at the finished version, I agreed to take the tracking system off his hands for $30,000. I sat down and wrote a simple agreement in which I outlined the general terms and conditions. I am not a lawyer, of course, but I thought I’d done a pretty good job of writing my first contract. And the way I did it was simplicity itself. I went online and did my homework. I looked at dozens of sample contracts, to try to get a handle on the way these things were written, and found everything I needed on the Web. (It’s even easier today; you can get a variety of contracts from various sites, at no charge.) The agreement stipulated that I would pay him in ninety days, once I had tested the program, but I already knew that it was working fine. The fact is, I needed those ninety days to generate enough income to pay him—though he didn’t need to know that. I also told him that if things worked out, I might want to hire him to run the software for me, on a month-to-month basis, when the company was up and running, and I mentioned the possibility of paying him $10,000 a month. I know that sounds like a huge number, and it was certainly a huge number to me, but I had been looking closely at my competition and at the staggering amounts of money that were being generated, and I knew that all I needed was one little deal to get my business off the ground.

When Franklin Graham recently called for a boycott of gay-friendly companies on his Facebook page, it quickly became apparent that to follow through on his own initiative, he’d need to delete his Facebook account (he didn’t), stop using any Microsoft software, and shut down all Apple devices. When he publicly moved the bank accounts of the Billy Graham Evangelistic Association to BB&T Bank in protest of a Wells Fargo ad featuring a lesbian couple and their daughter, it generated this Miami Herald headline: “Billy Graham Group Moving Money to BB&T, Sponsor of Miami Beach Gay Pride Fundraiser.”110

Even seasoned code writers could not dismiss the possibility of being trapped in something akin to an infinite loop, wherein fixes spawned their own bugs. It had happened to others. The history of software was littered with projects, large and small, that had been abandoned in disgust, destroying careers.

Regarding both size and performance, customer preferences were clear. They wanted software that gave speedy results on inexpensive hardware and got great mileage out of memory.

Poor performance was a common failing of most new programs. The annals of software amply showed this; nearly every landmark system, from IBM’s 360 to the various flavors of Unix to Microsoft’s Windows, was released in an immature state and evolved over time to win broader acceptance. Indeed, people expected the first commercial release of a new program to contain flaws of all sorts.

Jobs had tried to hire Rashid, then a computer science professor at Carnegie-Mellon University, but Rashid turned him down. He was reluctant to join the hurly-burly life of a corporation. His Mach research had been almost wholly funded by government grants; an agency of the Pentagon, his principal backer, saw Mach as crucial to unleashing the vast power of multiprocessor computers, inherently cheap machines that would someday replace pricey supercomputers as the backbone of the nation’s military and intelligence-gathering networks. Besides, Rashid was an academic purist. He seemed sincerely devoted to pursuing knowledge about software for its own sake. This was rare, even among academics, because software was such a remunerative field that the brightest researchers found themselves inexorably pulled into commerce: The money was too good. After

The Federal Trade Commission, a U.S. regulatory agency, was investigating Microsoft for possible violations of laws aimed at limiting abusive monopolies. This pained Gates, who felt he was simply a victim of his great success. “I don’t think the rich get much credit for anything,” he said. His own experience, he felt, bore this out. Just a few years earlier, he had been celebrated as the scrappy entrepreneur who courageously carved a thriving business from the technological wilderness ignored by entrenched powers. Now he was a maligned bully who wanted to own the entire software universe; a greedy man who thumbed his nose at both customers and competitors. Which

As software pundit Fred Brooks once observed, “How does a project get to be a year late?... One day at a time.” In

With software, you know what you have to do,” he said, “but it’s always a big surprise how long it will take.” Miller

Then as now the PC held a curious power over restless, analytical people. To start with, the computer carried a psychological appeal not unlike that of an automobile. Both machines were objects of intense attachment for many of their owners—feelings of attachment that went well beyond the utility of the machines. While illustrating the way in which people can form emotional bonds with tools, the symbolisms of the automobile and the PC differed in an important way. The realm of the automobile extended no further than that of fantasy and enjoyment. The PC, by contrast, was a medium for creation. The utility of a PC arose directly from its software. Writing software required little money and, surprisingly, scant experience.

The imminent arrival of NT had turned the computer industry on its ear. After outsiders took stock of the first beta, expectations for NT grew. While easy to nitpick over flaws, some heralded the program as a grand achievement likely to alter the destinies of scores of computer and software companies. Those rivals most at risk—IBM, Sun Microsystems and Novell, to name the three biggest—girded themselves against the onslaught. First Boston, a securities firm that advised investors on the industry’s outlook, captured the mood on February 15, 1993, calling NT the “most aggressive new piece of software ever.” Eight

Bugs were the backdrop of the code writer’s life. A comma in the wrong place. An “if” where there should be a “then.” An erroneous call from one piece of the program to another. Each could instantly cause a seizure, the collapse of a finely wrought abstraction into a puddle of ones and zeroes. Only human, software was born to fail. If not catastrophically, then aesthetically. Every software captain knew this.

In many ways what is happening now is what media, communications, and software moguls have been predicting for a generation: The fruits of Silicon Valley’s labor and those of New York and Hollywood are converging.