Automation Process Quotes

When you repeat a behavior over time, your brain learns to automate the process. It's more energy efficient to automatically do something than to manually weigh your options and decide to act the same way every time. When you make a decision very quickly, it is probably from habit, even if you think you're actively deciding. In a way, you made the decision a while ago.

As a new entrepreneur, you're probably gonna have to hustle hard to get things going at first. But as the business grows and becomes more established, that unrefined hustle should be replaced by automated profit-producing processes and systems. Hustle is good as a temporary mode of operating, but it's unsustainable long term and unprofitable long term.

1. Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out.

However, one intriguing shift that suggests there are limits to automation was the recent decision by Toyota to systematically put working humans back into the manufacturing process. In quality and manufacturing on a mass scale, Toyota has been a global leader in automation technologies based on the corporate philosophy of kaizen (Japanese for “good change”) or continuous improvement. After pushing its automation processes toward lights-out manufacturing, the company realized that automated factories do not improve themselves. Once Toyota had extraordinary craftsmen that were known as Kami-sama, or “gods” who had the ability to make anything, according to Toyota president Akio Toyoda.49 The craftsmen also had the human ability to act creatively and thus improve the manufacturing process. Now, to add flexibility and creativity back into their factories, Toyota chose to restore a hundred “manual-intensive” workspaces.

He was thinking about automated teller machines. The term was aged and burdened by its own historical memory. It worked at cross-purposes, unable to escape the inferences of fuddled human personnel and jerky moving parts. The term was part of the process that the device was meant to replace. It was anti-futuristic, so cumbrous and mechanical that even the acronym seemed dated.

A Checklist is an Externalized, predefined Standard Operating Procedure for completing a specific task. Creating a Checklist is enormously valuable for two reasons. First, Checklisting will help you define a System for a process that hasn’t yet been formalized—once the Checklist has been created, it’s easier to see how to improve or Automate the system. Second, using Checklists as a normal part of working can help ensure that you don’t forget to handle important steps that are easily overlooked when things get busy.

We’ve now established three things. First, we don’t need willpower when we don’t desire to do something, and it isn’t a thing some of us have in excess and some of us don’t have at all. It’s a cognitive function, like deciding what to eat or solving a math equation or remembering your dad’s birthday. Willpower is also a limited resource; we have more of it at the beginning of the day and lose it throughout the day as we use it to write emails or not eat cookies. When you automate some decisions or processes (through forming habits), you free up more brain power. Second, for us to make and change a habit, we need a cue, a routine, and a reward, and enough repetition must occur for the process to move from something we have to think about consciously (“I need to brush my teeth,” “I don’t want to drink wine”) to something we do naturally, automatically. Third, throughout the day, we must manage our energy so that we don’t blow out and end up in the place of no return—a hyperaroused state where the only thing that can bring us down is a glass (or a bottle) of wine. Maybe

chickens are grown to standardized sizes so as to make them compatible with automated slaughtering and processing.

The more automated our experience becomes, the less involved we are in the art of living.

Always wait until the end of designing a process—after you have questioned all the requirements and deleted unnecessary parts—before you introduce automation.

You may not be able to automate the whole process, but you can make the first action mindless. Make it easy to start and the rest will follow.

I began looking for these four: Smart. It doesn’t mean high IQ (although that’s great), it means disposed toward learning. If there’s a best practice anywhere, adopt it. We want to turn as much as possible into a routine so we can focus on the few things that require human intelligence and creativity. A good interview question for this is: “Tell me about the last significant thing you learned about how to do your job better.” Or you might ask a candidate: “What’s something that you’ve automated? What’s a process you’ve had to tear down at a company?” Humble. I don’t mean meek or unambitious, I mean being humble in the way that Steph Curry is humble. If you’re humble, people want you to succeed. If you’re selfish, they want you to fail. It also gives you the capacity for self-awareness, so you can actually learn and be smart. Humility is foundational like that. It is also essential for the kind of collaboration we want at Slack. Hardworking. It does not mean long hours. You can go home and take care of your family, but when you’re here, you’re disciplined, professional, and focused. You should also be competitive, determined, resourceful, resilient, and gritty. Take this job as an opportunity to do the best work of your life. Collaborative. It’s not submissive, not deferential—in fact it’s kind of the opposite. In our culture, being collaborative means providing leadership from everywhere. I’m taking responsibility for the health of this meeting. If there’s a lack of trust, I’m going to address that. If the goals are unclear, I’m going to deal with that. We’re all interested in getting better and everyone should take responsibility for that. If everyone’s collaborative in that sense, the responsibility for team performance is shared. Collaborative people know that success is limited by the worst performers, so they are either going to elevate them or have a serious conversation. This one is easy to corroborate with references, and in an interview you can ask, “Tell me about a situation in your last company where something was substandard and you helped to fix it.

Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out.

5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out.

It is useful for companies to look at AI through the lens of business capabilities rather than technologies. Broadly speaking, AI can support three important business needs: automating business processes, gaining insight through data analysis, and engaging with customers and employees.

The optimists claim that through the course of evolution the nervous system has become adept at “chunking” bits of information so that processing capacity is constantly expanded. Simple functions like adding a column of numbers or driving a car grow to be automated, leaving the mind free to deal with more data. We

Whenever you face a problem repeatedly, your brain begins to automate the process of solving it. Your habits are just a series of automatic solutions that solve the problems and stresses you face regularly. As behavioral scientist Jason Hreha writes, “Habits are, simply, reliable solutions to recurring problems in our environment.

A use case is a description of the way that an automated system is used. It specifies the input to be provided by the user, the output to be returned to the user, and the processing steps involved in producing that output. A use case describes application-specific business rules as opposed to the Critical Business Rules within the Entities.

So, when should you think about automating a process? The simplest answer is, “When you have to do it a second time.” The third time you do something, it should be done using an automated process. This fine-grained incremental approach rapidly creates a system for automating the repeated parts of your development, build, test, and deployment process.

Every change that is made to an application’s configuration, source code, environment, or data, triggers the creation of a new instance of the pipeline. One of the first steps in the pipeline is to create binaries and installers. The rest of the pipeline runs a series of tests on the binaries to prove that they can be released. Each test that the release candidate passes gives us more confidence that this particular combination of binary code, configuration information, environment, and data will work. If the release candidate passes all the tests, it can be released. The deployment pipeline has its foundations in the process of continuous integration and is in essence the principle of continuous integration taken to its logical conclusion. The aim of the deployment pipeline is threefold. First, it makes every part of the process of building, deploying, testing, and releasing software visible to everybody involved, aiding collaboration. Second, it improves feedback so that problems are identified, and so resolved, as early in the process as possible. Finally, it enables teams to deploy and release any version of their software to any environment at will through a fully automated process.

On one weekend, they marched through the factory painting marks on machinery to be jettisoned. “We put a hole in the side of the building just to remove all that equipment,” Musk says. The experience became a lesson that would become part of Musk’s production algorithm. Always wait until the end of designing a process—after you have questioned all the requirements and deleted unnecessary parts—before you introduce automation.

Kensi Gounden, Highly innovative new technologies can be both disruptive and transformative, but technology adoption can also be incremental, such as simply automating a manual process. So introducing business technology innovations, either incremental or step-change, may embrace increasing online connectivity across the business, strategic technology acquisition and use or using time-saving technologies to improve internal communication.

I am the person who spends a great deal of time on the intricacies of interstellar communication through jumpgates—a process, Your Excellency, which is so very automated and regular that my time is absolutely most valuably spent on informing you about it. Would you like to come into a conference room?” One Cyclamen was amazingly obsequious, and in such a way that Eight Antidote felt more flattered than annoyed. He wished he could learn that skill.

advances in AI are poised to drive dramatic productivity increases and perhaps eventually full automation. Radiologists, for example, are trained to interpret the images that result from various medical scans. Image processing and recognition technology is advancing rapidly and may soon be able to usurp the radiologist’s traditional role. Software can already recognize people in photos posted on Facebook and even help identify potential terrorists in airports.

The coming wave of automation will move way beyond the factory or public infrastructure and into our very biological processes such as aging and even giving birth. Used as we are to the gradual societal shifts brought about by previous change waves, often allowing decades to adjust and respond, I ask if we as a tribe are ready to abdicate our human sovereignty to the faceless forces of technology? Are you ready for the biggest loss of free will and individual human control in history?

Whenever you face a problem repeatedly, your brain begins to automate the process of solving it. Your habits are just a series of automatic solutions that solve the problems and stresses you face regularly. As behavioral scientist Jason Hreha writes, “Habits are, simply, reliable solutions to recurring problems in our environment.” As habits are created, the level of activity in the brain decreases. You learn to lock in on the cues that predict success and tune out everything else. When

The process of decision making and projecting a future in which one future among many can be selected depends less and less on human will. We may call it the paradox of the decider: as the circulation of information becomes faster and more complex, the time available for the elaboration of relevant information becomes shorter. The more space taken by the available information, the less time there is for understanding and conscious choice. This is why the interdependence between data and decisions is more and more embedded in infomachinery, in technolinguistic interfaces. This is why the execution of the program is entrusted to automated procedures that human operators can neither change nor ignore. The machine pretends to be neutral, purely mathematical, but we know that its procedures are only the technical reification of social interests: profit, accumulation, competition—these are the criteria underlying the automatic procedures embedded in the machine. Human volition is reduced to a procedural pretense.

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.

2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out.

1. Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle. The only rules are the ones dictated by the laws of physics. Everything else is a recommendation

While poorhouses have been physically demolished, their legacy remains alive and well in the automated decision-making systems that encage and entrap today's poor. For all their high-tech polish, our modern systems of poverty management - automated decision-making, data mining, and predictive analysis - retain a remarkable kinship with the poorhouses of the past. Our new digital tools spring from punitive, moralistic views of poverty and create a system of high-tech containment and investigation. The digital poorhouse deters the poor from accessing public resources; polices their labor, spending, sexuality, and parenting; tries to predict their future behavior; and punishes and criminalizes those who do not comply with its dictates. In the process, it creates ever-finer moral distinctions between the 'deserving' and 'undeserving' poor, categorizations that rationalize our national failure to care for one another.

Work must be refused and reduced, building our synthetic freedom in the process.136 As we have set out in this chapter, achieving this will require the realisation of four minimal demands: 1.Full automation 2.The reduction of the working week 3.The provision of a basic income 4.The diminishment of the work ethic While each of these proposals can be taken as an individual goal in itself, their real power is expressed when they are advanced as an integrated programme. This is not a simple, marginal reform, but an entirely new hegemonic formation to compete against the neoliberal and social democratic options. The demand for full automation amplifies the possibility of reducing the working week and heightens the need for a universal basic income. A reduction in the working week helps produce a sustainable economy and leverage class power. And a universal basic income amplifies the potential to reduce the working week and expand class power.

The specific nature of capitalist commodity production shows itself in the fact that it is not simply a labour process in which products are created by the elements of production M and L. Rather the capitalistic form of commodity production is constructed dualistically – it is simultaneously a labour process for the creation of products and a valorisation process. The elements of production M and L figure not only in their natural form, but at the same time as values c and v respectively. They are used for the production of a sum of values, w, and indeed only on condition that over and above the used up value magnitudes c and v there is a surplus s (that is, s = w - c + v). The capitalist expansion of production, or accumulation of capital, is defined by the fact that the expansion of M relative to L occurs on the basis of the law of value; it takes the specific form of a constantly expanding capital c relative to the sum of wages v, such that both components of capital are necessarily valorised. It follows that the reproduction process can only be continued and expanded further if the advanced, constantly growing capital c + v can secure a profit, s. The problem can then be defined as follows – is a process of this sort possible in the long run?”[68]

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.

five commandments: 1. Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out.

Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience.

If we’re not careful, the automation of mental labor, by changing the nature and focus of intellectual endeavor, may end up eroding one of the foundations of culture itself: our desire to understand the world. Predictive algorithms may be supernaturally skilled at discovering correlations, but they’re indifferent to the underlying causes of traits and phenomena. Yet it’s the deciphering of causation—the meticulous untangling of how and why things work the way they do—that extends the reach of human understanding and ultimately gives meaning to our search for knowledge. If we come to see automated calculations of probability as sufficient for our professional and social purposes, we risk losing or at least weakening our desire and motivation to seek explanations, to venture down the circuitous paths that lead toward wisdom and wonder. Why bother, if a computer can spit out “the answer” in a millisecond or two? In his 1947 essay “Rationalism in Politics,” the British philosopher Michael Oakeshott provided a vivid description of the modern rationalist: “His mind has no atmosphere, no changes of season and temperature; his intellectual processes, so far as possible, are insulated from all external influence and go on in the void.” The rationalist has no concern for culture or history; he neither cultivates nor displays a personal perspective. His thinking is notable only for “the rapidity with which he reduces the tangle and variety of experience” into “a formula.”54 Oakeshott’s words also provide us with a perfect description of computer intelligence: eminently practical and productive and entirely lacking in curiosity,

Gadgetry will continue to relieve mankind of tedious jobs. Kitchen units will be devised that will prepare ‘automeals,’ heating water and converting it to coffee; toasting bread; frying, poaching or scrambling eggs, grilling bacon, and so on. Breakfasts will be ‘ordered’ the night before to be ready by a specified hour the next morning. Communications will become sight-sound and you will see as well as hear the person you telephone. The screen can be used not only to see the people you call but also for studying documents and photographs and reading passages from books. Synchronous satellites, hovering in space will make it possible for you to direct-dial any spot on earth, including the weather stations in Antarctica. [M]en will continue to withdraw from nature in order to create an environment that will suit them better. By 2014, electroluminescent panels will be in common use. Ceilings and walls will glow softly, and in a variety of colors that will change at the touch of a push button. Robots will neither be common nor very good in 2014, but they will be in existence. The appliances of 2014 will have no electric cords, of course, for they will be powered by long- lived batteries running on radioisotopes. “[H]ighways … in the more advanced sections of the world will have passed their peak in 2014; there will be increasing emphasis on transportation that makes the least possible contact with the surface. There will be aircraft, of course, but even ground travel will increasingly take to the air a foot or two off the ground. [V]ehicles with ‘Robot-brains’ … can be set for particular destinations … that will then proceed there without interference by the slow reflexes of a human driver. [W]all screens will have replaced the ordinary set; but transparent cubes will be making their appearance in which three-dimensional viewing will be possible. [T]he world population will be 6,500,000,000 and the population of the United States will be 350,000,000. All earth will be a single choked Manhattan by A.D. 2450 and society will collapse long before that! There will, therefore, be a worldwide propaganda drive in favor of birth control by rational and humane methods and, by 2014, it will undoubtedly have taken serious effect. Ordinary agriculture will keep up with great difficulty and there will be ‘farms’ turning to the more efficient micro-organisms. Processed yeast and algae products will be available in a variety of flavors. The world of A.D. 2014 will have few routine jobs that cannot be done better by some machine than by any human being. Mankind will therefore have become largely a race of machine tenders. Schools will have to be oriented in this direction…. All the high-school students will be taught the fundamentals of computer technology will become proficient in binary arithmetic and will be trained to perfection in the use of the computer languages that will have developed out of those like the contemporary “Fortran". [M]ankind will suffer badly from the disease of boredom, a disease spreading more widely each year and growing in intensity. This will have serious mental, emotional and sociological consequences, and I dare say that psychiatry will be far and away the most important medical specialty in 2014. [T]he most glorious single word in the vocabulary will have become work! in our a society of enforced leisure.

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THE SK8 MAKER VS. GLOBAL INDUSTRIALIZATION This new era of global industrialization is where my personal analogy with the history of the skateboard maker diverges. It’s no longer cost-effective to run a small skateboard company in the U.S., and the handful of startups that pull it off are few and far between. The mega manufacturers who can churn out millions of decks at low cost and record speed each year in Chinese factories employ proprietary equipment and techniques that you and I can barely imagine. Drills that can cut all eight truck holes in a stack of skateboard decks in a single pull. CNC machinery to create CAD-perfect molds used by giant two-sided hydraulic presses that can press dozens of boards in a few hours. Computer-operated cutting bits that can stamp out a deck to within 1⁄64 in. of its specified shape. And industrial grade machines that apply multicolored heat-transfer graphics in minutes. In a way, this factory automation has propelled skateboarding to become a multinational, multi-billion dollar industry. The best skateboarders require this level of precision in each deck. Otherwise, they could end up on their tails after a failed trick. Or much worse. As the commercial deck relies more and more on a process that is out of reach for mere mortals, there is great value in the handmade and one of a kind. Making things from scratch is a dying art on the brink of extinction. It was pushed to the edge when public schools dismissed woodworking classes and turned the school woodshop into a computer lab. And when you separate society from how things are made—even a skateboard—you lose touch with the labor and the materials and processes that contributed to its existence in the first place. It’s not long before you take for granted the value of an object. The result is a world where cheap labor produces cheap goods consumed by careless customers who don’t even value the things they own.

five commandments: 1. Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle.

Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle. The only rules are the ones dictated by the laws of physics.

Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle. The only rules are the ones dictated by the laws of physics. Everything else is a recommendation.

I became a broken record on the algorithm,” Musk says. “But I think it’s helpful to say it to an annoying degree.” It had five commandments: 1. Question every requirement. Each should come with the name of the person who made it. You should never accept that a requirement came from a department, such as from “the legal department” or “the safety department.” You need to know the name of the real person who made that requirement. Then you should question it, no matter how smart that person is. Requirements from smart people are the most dangerous, because people are less likely to question them. Always do so, even if the requirement came from me. Then make the requirements less dumb. 2. Delete any part or process you can. You may have to add them back later. In fact, if you do not end up adding back at least 10% of them, then you didn’t delete enough. 3. Simplify and optimize. This should come after step two. A common mistake is to simplify and optimize a part or a process that should not exist. 4. Accelerate cycle time. Every process can be speeded up. But only do this after you have followed the first three steps. In the Tesla factory, I mistakenly spent a lot of time accelerating processes that I later realized should have been deleted. 5. Automate. That comes last. The big mistake in Nevada and at Fremont was that I began by trying to automate every step. We should have waited until all the requirements had been questioned, parts and processes deleted, and the bugs were shaken out. The algorithm was sometimes accompanied by a few corollaries, among them: All technical managers must have hands-on experience. For example, managers of software teams must spend at least 20% of their time coding. Solar roof managers must spend time on the roofs doing installations. Otherwise, they are like a cavalry leader who can’t ride a horse or a general who can’t use a sword. Comradery is dangerous. It makes it hard for people to challenge each other’s work. There is a tendency to not want to throw a colleague under the bus. That needs to be avoided. It’s OK to be wrong. Just don’t be confident and wrong. Never ask your troops to do something you’re not willing to do. Whenever there are problems to solve, don’t just meet with your managers. Do a skip level, where you meet with the level right below your managers. When hiring, look for people with the right attitude. Skills can be taught. Attitude changes require a brain transplant. A maniacal sense of urgency is our operating principle. The only rules are the ones dictated by the laws of physics. Everything else is a recommendation.

By now, though, it had been a steep learning curve, he was fairly well versed on the basics of how clearing worked: When a customer bought shares in a stock on Robinhood — say, GameStop — at a specific price, the order was first sent to Robinhood's in-house clearing brokerage, who in turn bundled the trade to a market maker for execution. The trade was then brought to a clearinghouse, who oversaw the trade all the way to the settlement. During this time period, the trade itself needed to be 'insured' against anything that might go wrong, such as some sort of systemic collapse or a default by either party — although in reality, in regulated markets, this seemed extremely unlikely. While the customer's money was temporarily put aside, essentially in an untouchable safe, for the two days it took for the clearing agency to verify that both parties were able to provide what they had agreed upon — the brokerage house, Robinhood — had to insure the deal with a deposit; money of its own, separate from the money that the customer had provided, that could be used to guarantee the value of the trade. In financial parlance, this 'collateral' was known as VAR — or value at risk. For a single trade of a simple asset, it would have been relatively easy to know how much the brokerage would need to deposit to insure the situation; the risk of something going wrong would be small, and the total value would be simple to calculate. If GME was trading at $400 a share and a customer wanted ten shares, there was $4000 at risk, plus or minus some nominal amount due to minute vagaries in market fluctuations during the two-day period before settlement. In such a simple situation, Robinhood might be asked to put up $4000 and change — in addition to the $4000 of the customer's buy order, which remained locked in the safe. The deposit requirement calculation grew more complicated as layers were added onto the trading situation. A single trade had low inherent risk; multiplied to millions of trades, the risk profile began to change. The more volatile the stock — in price and/or volume — the riskier a buy or sell became. Of course, the NSCC did not make these calculations by hand; they used sophisticated algorithms to digest the numerous inputs coming in from the trade — type of equity, volume, current volatility, where it fit into a brokerage's portfolio as a whole — and spit out a 'recommendation' of what sort of deposit would protect the trade. And this process was entirely automated; the brokerage house would continually run its trading activity through the federal clearing system and would receive its updated deposit requirements as often as every fifteen minutes while the market was open. Premarket during a trading week, that number would come in at 5:11 a.m. East Coast time, usually right as Jim, in Orlando, was finishing his morning coffee. Robinhood would then have until 10:00 a.m. to satisfy the deposit requirement for the upcoming day of trading — or risk being in default, which could lead to an immediate shutdown of all operations. Usually, the deposit requirement was tied closely to the actual dollars being 'spent' on the trades; a near equal number of buys and sells in a brokerage house's trading profile lowered its overall risk, and though volatility was common, especially in the past half-decade, even a two-day settlement period came with an acceptable level of confidence that nobody would fail to deliver on their trades.

Selling is crucial to your success because without the sale, you do not make any money. The great thing about writing a book to position yourself is that the book does a lot of the selling for you. People read the book and come to you for more answers. If you have products created to match the theme of your book, your platform (website) will do the selling for you. Automate as much of the process as you can with opt-in boxes, video sales landing pages and special offers. Make it as easy as you can for your fans and followers. Once your products are created, simply write about them, talk about them, and create articles from the content and say, “Yes” to interviews. The buzz created will point people back to your site where your automatic sales team is ready to take orders 24 hours a day.

Corporate interests raised a nearly unified voice heralding automation as a certain and universal beneficial advancement. However, some observers saw the new technology as a cause for concern and cautioned that the final word on automation would depend on the choices that industry and the nation made in the face of difficult questions regarding the pace of automation’s implementation, the uses of the new productivity, and the fate of displaced workers as well as depleted or eliminated job classifications, communities, and even industries. Norbert Wiener, for example, a prominent MIT mathematician and pioneer in the science of cybernetics, emphasized the potentially calamitous economic and social consequences of the new production technology. Wiener had begun to express concerns about the impacts of automation on labor and the entire society during World War II, and he authored two books in the immediate Cold War years warning that potentially disastrous unemployment and related social problems may come from industry’s drive toward automation. He characterized automation and computer controls in the production process as the “modern” or “second” industrial revolution, which even more than the first held “unbounded possibilities for good and evil.” 104 In particular, Wiener feared that the larger impact of the changes caused by automation would be a massive displacement of workers, compounded by the profit-driven indifference of industry. “The automatic machine … will produce an unemployment situation, in comparison with which the present recession and even the depression of the thirties will seem a pleasant joke.” 105

RPA is software that emulates human execution of repetitive work. It's built on technologies designed to orchestrate, execute and enhance business workflows. Cognitive RPA adds intelligence the ability to perform human like decision making to RPA. CRPA can do things like read documents to identify specific information to pass to RPA to update another system. dayhuffgroup.com

Don’t be afraid to provide white glove customer support for early adopters to help them through the onboarding process. Sometimes automation also entails a host of emotional concerns, such as fear that someone’s job will be replaced by a shell script. By working one-on-one with early users, you can address those fears personally, and demonstrate that rather than owning the toil of performing a tedious task manually, the team instead owns the configurations, processes, and ultimate results of their technical work. Later adopters are convinced by the happy examples of early adopters.

Google has also benefitted from being at the inflection point of software moving from massive client-side binaries with multi-year release cycles to cloud-based services that are released every few weeks, days, or hours.1 This confluence of happy circumstances has endowed us with some similarities to the utopian software development process. Google SWEs are feature developers, responsible for building components that ship to customers. They write feature code and unit test code for those features. Google SETs are test developers, responsible for assisting SWEs with the unit test portion of their work and also in writing larger test frameworks to assist SWEs in writing small and medium tests to assess broader quality concerns. Google TEs are user developers, responsible for taking the users’ perspectives in all things that have to do with quality. From a development perspective, they create automation for user scenarios and from a product perspective, they assess the overall coverage and effectiveness of the ensemble of testing activity performed by the other engineering roles. It is not utopia, but it is our best attempt at achieving it in a practical way where real-world concerns have a way of disrupting best intentions in the most unforeseen and unforgiving way.

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Millions of copies of drivers’ licenses, social security cards, and other supporting documents were faxed to a centralized document processing center in Grant County; so many of them disappeared that advocates started calling it “the black hole in Marion.” Each month the number of verification documents that vanished—were not attached properly to digital case files in a process called “indexing”—rose exponentially. According to court documents, in December 2007 just over 11,000 documents were unindexed. By February 2009, nearly 283,000 documents had disappeared, an increase of 2,473 percent. The rise in technical errors far outpaced increased system use. The consequences are staggering if you consider that any single missing document could cause an applicant to be denied benefits.

This is what happened when I cofounded LinkedIn. The key business model innovations for LinkedIn, including the two-way nature of the relationships and filling professionals’ need for a business-oriented online identity, didn’t just happen organically. They were the result of much thought and reflection, and I drew on the experiences I had when founding SocialNet, one of the first online social networks, nearly a decade before the creation of LinkedIn. But life isn’t always so neat. Many companies, even famous and successful ones, have to develop their business model innovation after they have already commenced operations. PayPal didn’t have a business model when it began operations (I was a key member of the PayPal executive team). We were growing exponentially, at 5 percent per day, and we were losing money on every single transaction we processed. The funny thing is that some of our critics called us insane for paying customers bonuses to refer their friends. Those referral bonuses were actually brilliant, because their cost was so much lower than the standard cost of acquiring new financial services customers via advertising. (We’ll discuss the power and importance of this kind of viral marketing later on.) The insanity, in fact, was that we were allowing our users to accept credit card payments, sticking PayPal with the cost of paying 3 percent of each transaction to the credit card processors, while charging our users nothing. I remember once telling my old college friend and PayPal cofounder/ CEO Peter Thiel, “Peter, if you and I were standing on the roof of our office and throwing stacks of hundred-dollar bills off the edge as fast as our arms could go, we still wouldn’t be losing money as quickly as we are right now.” We ended up solving the problem by charging businesses to accept payments, much as the credit card processors did, but funding those payments using automated clearinghouse (ACH) bank transactions, which cost a fraction of the charges associated with the credit card networks. But if we had waited until we had solved this problem before blitzscaling, I suspect we wouldn’t have become the market leader.

The digital poorhouse is hard to understand. The software, algorithms, and models that power it are complex and often secret. Sometimes they are protected business processes, as in the case of the IBM and ACS software that denied needy

If MA gives the ability to replace virtually all the processes where a human being is not strictly necessary, in fact, no real automation will be reachable until hoteliers decide to hand over some tasks from human beings to machines

Without standard, shared languages, open APIs and predefined protocols for cross-software integration, no effective automation will ever be possible in hospitality, especially with legacy software, where integrations remain expensive, slow and complex processes

factory automation services Our company majorly dedicated to serving clients having biodiesel plants. Our company has more than 60 engineers who are highly experienced and proficient. Moreover, all our professionals are expertise in different niche such as electrical, process, application, project, mechanical, chemical, civil, structural and controls too. Our professionals do the best possible job to ensure a favorable outcome. For factory automation services, we build and maintain the biodiesel plant. In this context, our experts follow the biodiesel plant construction standards that include plant size determination, selecting an appropriate site, permitting, biodiesel plant engineering, determining your equipment needs, assistance which plant installation, quality and BQ-9000 considerations, plant start up and training, plant management and planning for the future.

They wanted the benefits of direct response copy in their business: they wanted to leverage their time, energy and money, while marketing one-to-many and automating their sales and marketing to free up their time and allow them to reach more people than they could without it… But they hated how it made them feel. Inauthentic. Hype-y. Sales-y. Slime-y. Like a used car salesman.

This includes the creation of automated build, integration, and test processes so that we can immediately detect when a change has been introduced that takes us out of a correctly functioning and deployable state.

If you think automating a process will reduce or eliminate the errors currently in that process, all you'll really be doing is automating the generation of those errors.

If you automate a process that has errors, all you’ve done is automate the generation of those errors.

This book is a compilation of interesting ideas that have strongly influenced my thoughts and I want to share them in a compressed form. That ideas can change your worldview and bring inspiration and the excitement of discovering something new. The emphasis is not on the technology because it is constantly changing. It is much more difficult to change the accompanying circumstances that affect the way technological solutions are realized. The chef did not invent salt, pepper and other spices. He just chooses good ingredients and uses them skilfully, so others can enjoy his art. If I’ve been successful, the book creates a new perspective for which the selection of ingredients is important, as well as the way they are smoothly and efficiently arranged together. In the first part of the book, we follow the natural flow needed to create the stimulating environment necessary for the survival of a modern company. It begins with challenges that corporations are facing, changes they are, more or less successfully, trying to make, and the culture they are trying to establish. After that, we discuss how to be creative, as well as what to look for in the innovation process. The book continues with a chapter that talks about importance of inclusion and purpose. This idea of inclusion – across ages, genders, geographies, cultures, sexual orientation, and all the other areas in which new ways of thinking can manifest – is essential for solving new problems as well as integral in finding new solutions to old problems. Purpose motivates people for reaching their full potential. This is The second and third parts of the book describes the areas that are important to support what is expressed in the first part. A flexible organization is based on IT alignment with business strategy. As a result of acceleration in the rate of innovation and technological changes, markets evolve rapidly, products’ life cycles get shorter and innovation becomes the main source of competitive advantage. Business Process Management (BPM) goes from task-based automation, to process-based automation, so automating a number of tasks in a process, and then to functional automation across multiple processes andeven moves towards automation at the business ecosystem level. Analytics brought us information and insight; AI turns that insight into superhuman knowledge and real-time action, unleashing new business models, new ways to build, dream, and experience the world, and new geniuses to advance humanity faster than ever before. Companies and industries are transforming our everyday experiences and the services we depend upon, from self-driving cars, to healthcare, to personal assistants. It is a central tenet for the disruptive changes of the 4th Industrial Revolution; a revolution that will likely challenge our ideas about what it means to be a human and just might be more transformative than any other industrial revolution we have seen yet. Another important disruptor is the blockchain - a distributed decentralized digital ledger of transactions with the promise of liberating information and making the economy more democratic. You no longer need to trust anyone but an algorithm. It brings reliability, transparency, and security to all manner of data exchanges: financial transactions, contractual and legal agreements, changes of ownership, and certifications. A quantum computer can simulate efficiently any physical process that occurs in Nature. Potential (long-term) applications include pharmaceuticals, solar power collection, efficient power transmission, catalysts for nitrogen fixation, carbon capture, etc. Perhaps we can build quantum algorithms for improving computational tasks within artificial intelligence, including sub-fields like machine learning. Perhaps a quantum deep learning network can be trained more efficiently, e.g. using a smaller training set. This is still in conceptual research domain.

Why people churn Most churn occurs at the time of the sale. In 2017, my churn was over 60%. I signed up customers who were a poor fit for my solution. Many customers thought Connex was an inventory management tool and others thought we built custom software. We had no onboarding process and we expected users to figure out Connex on their own. Many users failed to choose the right settings, since they are small business owners and not accountants. Since the software failed to work as expected, they quickly cancelled. From experience, most users churn in the first 30 days. It is critical that you reach out to them and ensure the software works correctly. My staff performs an onboarding and ensures Connex works to the customer’s satisfaction. Users churned because my software lacked features that it has today. We noticed a dramatic shift in churn, after implementing a sales and marketing process. In the first quarter of 2021, we had only a handful of refunds out of 100 purchases. People churn because they fail to achieve their desired result or experience. People buy Connex because they want accurate financial information, better order fulfillment, or protection from overselling. If the sync were inaccurate and unreliable then we would lose customers. In other cases, your software may become superfluous. For example, I used the excellent meeting automation tool Calendly. When I migrated to HubSpot, however, I no longer needed Calendly because HubSpot offered meeting automation as part of its suite of offerings. Even if your tool works, your customer’s desired situation or desired outcomes may change. I churned from my ticketing system because I was unhappy with the customer service and experienced technical issues with their chat and phone system. Companies often tack on features that are nowhere near as usable as their core offering.

a deployment pipeline. That’s your entire value stream from code check-in to production. That’s not an art. That’s production. You need to get everything in version control. Everything. Not just the code, but everything required to build the environment. Then you need to automate the entire environment creation process. You need a deployment pipeline where you can create test and production environments, and then deploy code into them, entirely on-demand.

With the cannabis legalization boom, more and more cannabis organizations are looking for solutions to help automate their cannabis packaging processes. Dura-Pack has been helping cannabis organizations streamline their packaging operations for decades. Dura-Pack’s automated cannabis packaging filling and weighing systems are the perfect packaging solutions for cannabis flower, edibles, gummies and CBD products. If you have questions about cannabis packaging and would like to speak with a cannabis packaging expert, please contact us. We look forward to hearing from you.

A good chief executive is essentially a hard-to-automate decision engine, not unlike IBM’s Jeopardy!-playing Watson system. They have built up a hard-won repository of experience and have honed and proved an instinct for their market. They’re then presented inputs throughout the day—in the form of e-mails, meetings, site visits, and the like—that they must process and act on. To ask a CEO to spend four hours thinking deeply about a single problem is a waste of what makes him or her valuable. It’s better to hire three smart subordinates to think deeply about the problem and then bring their solutions to the executive for a final decision.

AI can be a great tool to automate repetitive and time-consuming work where human-level decision-making is involved.

Phase 1: Discovery 1. Define the problem statement What is the challenge that will be solved? The problem statement is defined at this step and becomes the foundation of the project. Here is a sample problem statement: The company has more than one hundred thousand email addresses and has sent more than one million emails in the last twelve months, but open rates remain low at 8 percent, and sales attributed to email have remained flat since 2018. Based on current averages, a 2 percentage-point lift in email open rates could produce a $50,000 increase in sales over the next twelve months. It’s important to note that a strong and valid problem statement should include the value of solving the problem. This helps ensure that the project is worth the investment of resources and keeps everyone focused on the goal. 2. Build and prioritize the issues list What are the primary issues causing the problem? The issues are categorized into three to five primary groups and built into an issues tree. Sample issues could be: •​Low open rates •​Low click rates •​Low sales conversion rates 3. Identify and prioritize the key drivers. What factors are driving the issues and problem? Sample key drivers could include: •​List fatigue •​Email creatives •​Highly manual, human-driven processes •​Underutilized or missing marketing technology solutions •​Lack of list segmentation •​Lack of reporting and performance management •​Lack of personalization 4. Develop an initial hypothesis What is the preliminary road map to solving the problem? Here is a sample initial hypothesis: AI-powered technologies can be integrated to intelligently automate priority use cases that will drive email efficiency and performance. 5. Conduct discovery research What information can we gain about the problem, and potential solutions, from primary and secondary research? •​How are talent, technology, and strategy gaps impacting performance? •​What can be learned from interviews with stakeholders and secondary research related to the problem? Ask questions such as the following: •​What is the current understanding of AI within the organization? •​Does the executive team understand and support the goal of AI pilot projects?

The dimensions impacting your team’s structure the most, and the ones you must most carefully consider include: The maturity of the market: the less mature the market (read: the more unique your product category is), the more evangelizers you need, as opposed to the next point: The maturity of your product: the less mature the product, the more hand-holding the customer needs. The maturity of your deployment process: the easier it is for the customer to get on-boarded and become self-sufficient, the more streamlined your organization can be (fewer roles, less complexity and fewer people touching the customer). The size of your customer base: the more customers you have to manage, the more important it is to move quickly towards automating activities in order to control costs. The extent of the Land-and-Expand strategy: the more potential for expansion there is with your customers, the more involved you want to be with them over time and the more quickly you would want to move commercial responsibilities over from Sales to the Customer Success organization.

More fundamentally, productivity gains from automation may always be somewhat limited, especially compared to the introduction of new products and tasks that transform the production process, such as those in the early Ford factories. Automation is about substituting cheaper machines or algorithms for human labor, and reducing production costs by 10 or even 20 percent in a few tasks will have relatively small consequences for TFP or the efficiency of the production process. In contrast, introducing new technologies, such as electrification, novel designs, or new production tasks, has been at the root of transformative TFP gains throughout much of the twentieth century.

This created an opportunity for plastics makers such as Nomacorc to step into the breech. Nomacorc’s value chain made it relatively easy for it to undertake research into the chemistry of wine taint, and to solve the problem. While the traditional cork makers were stuck in an older mind-set (“we’re in the cork business”), the plastics makers could see how to become part of a larger value-creating process. By 2009, Nomacorc’s automated North Carolina factory was churning out close to 160 million plastic stoppers a month, and synthetic corks had captured 20 percent of the market.

Whenever you face a problem repeatedly, your brain begins to automate the process of solving it. Your habits are just a series of automatic solutions that solve the problems and stresses you face regularly.

In 2018, Arowana is working with RPA (robotic process automation) specialists to introduce robotic process automation software and tools into our companies. RPA will help them process menial, repetitive tasks faster, with zero errors and at much lower costs. In one case, an accounts payable robot can process in 1 hour what a human being can process in 1 week.

Which company is best for using construction Project work? The Shree Siva Balaaji Steels project is a significant endeavor that encompasses the establishment and operation of a modern and advanced steel manufacturing facility. This project represents a fusion of innovation, cutting-edge technology, and industrial expertise, aimed at delivering high-quality steel products to meet the growing demands of various sectors. Key Features: State-of-the-Art Manufacturing Plant: The project involves the construction and operation of a state-of-the-art manufacturing plant equipped with the latest machinery, automation systems, and environmentally friendly processes. This allows for efficient production and reduced environmental impact. Diverse Product Range: Shree Siva Balaaji Steels aims to offer a diverse range of steel products to cater to different industries such as construction, automotive, infrastructure, and manufacturing. This versatility enables the company to meet the varying needs of clients and partners. Quality Assurance: A cornerstone of the project is its commitment to delivering high-quality steel products. The facility adheres to strict quality control measures and follows international standards to ensure that the end products are durable, reliable, and meet or exceed industry specifications. Sustainability Focus: The project places a strong emphasis on sustainability and environmentally conscious practices. Energy-efficient processes, recycling initiatives, and waste reduction strategies are integrated into the manufacturing process to minimize the ecological footprint. Employment Opportunities: Shree Siva Balaaji Steels contributes to local economies by creating employment opportunities across various skill levels, from skilled labor to technical experts. This helps stimulate economic growth in the region surrounding the manufacturing facility. Collaboration and Partnerships: The project fosters collaborations with suppliers, distributors, and clients, establishing strong relationships within the steel industry. This network facilitates efficient supply chain management and enables the company to provide tailored solutions to its customers. Innovation and Research: The project invests in research and development to constantly improve manufacturing processes, product quality, and the development of new steel products. This dedication to innovation positions the company at the forefront of the steel industry. Community Engagement: Shree Siva Balaaji Steels is committed to engaging with local communities and implementing corporate social responsibility initiatives. These efforts include supporting education, healthcare, and other community-centric projects, fostering goodwill and positive impact. Vision: The Shree Siva Balaaji Steels project envisions becoming a leading name in the steel manufacturing sector, renowned for its exceptional quality, technological innovation, and sustainability practices. By adhering to its core values of integrity, excellence, and environmental responsibility, the project strives to contribute positively to the industry and the communities it operates within.

Consider this incomplete list of things that can be made better with data: Answering a factual question Telling a story Exploring a relationship Discovering a pattern Making a case for a decision Automating a process Judging an experiment

Social networks like Facebook seem impelled by a similar aspiration. Through the statistical "discovery" of potential friends, the provision of "Like" buttons and other clickable tokens of affection, and the automated management of many of the time-consuming aspects of personal relations, they seek to streamline the messy process of affiliation. Facebook's founder, Mark Zuckerberg, celebrates all of this as "frictionless sharing"--the removal of conscious effort from socializing. But there's something repugnant about applying the bureaucratic ideals of speed, productivity, and standardization to our relations with others. The most meaningful bonds aren't forged through transactions in a marketplace or other routinized exchanges of data. People aren't notes on a network grid. The bonds require trust and courtesy and sacrifice, all of which, at least to a technocrat's mind, are sources of inefficiency and inconvenience. Removing the friction from social attachments doesn't strengthen them; it weakens them. It makes them more like the attachments between consumers and products--easily formed and just as easily broken. Like meddlesome parents who never let their kids do anything on their own, Google, Facebook, and other makers of personal software end up demeaning and diminishing qualities of character that, at least in the past, have been seen as essential to a full and vigorous life: ingenuity, curiosity, independence, perseverance, daring. It may be that in the future we'll only experience such virtues vicariously, though the exploits of action figures like John Marston in the fantasy worlds we enter through screens.

The history of the development of any urban center will be incomplete without a mention of the role of mass transit in the whole process. In deed the role of mass transit as a catalyst of industrial revolution and urbanization cannot be over emphasized. In the case of the New

Determine Keywords Use Compete PRO to find out which keywords drive traffic in an industry category; then create a search with them in Traackr to find the influencers. Validate Use the automated tools as a stepping-stone in the influencer discovery process, read their blogs, and validate the data to build relationships with influencers. Show Commitment Influencer identification is not a one-time thing. You need to do it regularly. It is a marriage, not a date. Welcome Surprises Don’t discount the “little” guy. Some of their one-to-one interactions are stronger than those of broadcasters. It takes only a pebble to start an avalanche. Combine Tools Use Google to find the most relevant keywords, Traackr to gain insights, and Klout to validate Twitter. Value Relevance Over Popularity Choose relevance over popularity. The most popular influencers on social media are often the least helpful in a social media campaign. Study Understand the influencer’s core audience. Combine Human and Machine Tools and technology are a good place to start, but we always need the human element.

Though Cannon's study serves to sanction on biological grounds the principle of automation, it also exposes the limitation of an economy that seeks to translate man's higher functions into an automatic system that will finally be capable of making decisions and plans of action without calling upon anticipatory mental processes or memories except those that can be programmed on a computer. The path of human advance is not toward such collective automation but toward the increase of personal and communal autonomy; and any system that reverses this direction not merely turns man's most highly developed organ, his brain, into a virtual non-entity, but cuts itself off from the most precious products of the human mind: that vast storehouse and powerhouse of images, forms, ideas, institutions, and structures, through which man rises above the conditions of his immediate environment. To reduce or destroy this heritage is to inflict brain damage on the human race.

technologies like payroll processing software, factory automation, computer-controlled machines, automated inventory control, and word processing have been deployed for routine work, substituting for workers in clerical tasks, on the factory floor, and doing rote information processing.

But the test happens, whether we make it formal or not. We ask and you answer. We seek a human response. But more than that—you are my test, Elefsis. Every minute I fail and imagine in my private thoughts the process for deleting you from my body and running this place with a simple automation routine which would never cover itself with flowers. Every minute I pass it, and teach you something new instead. Every minute I fail and hide things from you. Every minute I pass and show you how close we can be, with your light passing into me in a lake out of time. So close there might be no difference at all between us. Our test never ends.

The human touch is there, it has worked for long, sitting by the patient’s bedside and trying to lift their spirits. Although with the advances of human genomics, parts of the process have become automated, medical professionals cannot practice the way they used to, it is no longer the same human contact that we had before. Patients usually get interested in new technologies first; therefore there is a constant request that physicians start using them. Medical professionals don’t have to get detailed training about how magnetic resonance imaging works, they just need to know why it works.

Executives need to understand the basic challenges of their current architecture and work to improve it over time. The build process needs to support managing different artifacts in the system as independent entities. Additionally, a solid, maintainable test automation framework needs to be in place so developers can trust the ability to quickly localize defects in their code when it fails. Until these fundamentals are in place, you will have limited success effectively transforming your processes.

We recommend creating four types of folders: • Archives (any email that contains information that might be needed) • Automated (any email newsletter that relates to a strategy you’d like to pursue in the future) • Follow-Up (any email relating to a specific action that needs to be completed) • Send (if you use an assistant to process email, then have this person filter messages that require your final approval into this folder)

It was 5:30 in the morning, and Wally’s coffee maker was just completing its automated process, yielding its much appreciated nectar for Richard’s consumption. He filled the biggest cup he could find two-thirds of the way up, and then opened the cabinet, selecting an espresso shot from the shelf. It proclaimed in bright red letters: “WARNING HIGH CAFFIENE. LIMIT 2 PER DAY”. Richard laughed a little as he dumped four of them into his coffee

The most important qualification of a process analyst is not a facility for sending out information, but a facility for receiving it. Good process analysts naturally want to understand everything thoroughly.

Predictive modeling generates the entire model from scratch. All the model’s math or weights or rules are created automatically by the computer. The machine learning process is designed to accomplish this task, to mechanically develop new capabilities from data. This automation is the means by which PA builds its predictive power.

This immense, still impending total human sacrifice cannot be appraised in the rational or scientific terms that those who have created this system favor: it is, I stress again, an essentially religious phenomenon. As such it offers a close parallel with the original doctrines of Buddhism, even down to the fact that it shares Prince Gautama's atheism. What, indeed, is the elimination of man himself from the process he in fact has discovered and perfected, with its promised end of all striving and seeking, but the Buddha's final escape from the Wheel of Life? Once complete and universal, total automation means total renunciation of life and eventually total extinction: that very retreat into Nirvana that Prince Gautama pictured as man's only way to free himself from sorrow and pain and misfortune. When the life-impulse is depressed, this doctrine, we know, exerts an immense attraction upon masses of disappointed and disheartened souls: for a few centuries Buddhism became dominant in India and swept over China. For similar reasons it is reviving again today. But note: those who originally accepted this view of man's ultimate destiny, and sought to meet death halfway, did not go to the trouble of creating an elaborate technology to accomplish this end: in that direction they went no farther, significantly enough, than the invention of a water-driven prayer wheel. Instead they practiced concentrated meditation and inner detachment, acts as free from technological intervention as the air they breathed. And they earned an unexpected reward for this mode of withdrawal, a reward that the worshippers of the machine will never know. Instead of extinguishing forever their capacity to feel pleasure or pain, they intensified it, creating poems, philosophies, paintings, sculptures, monuments, ceremonies that restored their hope, their organic animation, their creative zeal: revealing once more in the erotic exuberance an impassioned and exalted sense of man's own potential destiny. Our latter-day technocratic Buddhism can make no such promises

Amazingly, the transformations are not primarily based on automation. Instead, the incredible improvements come from modifying policies around the system of work and the policies that control work in process, ensuring that there are effective cross-functional teams, subordinating everything to the constraint, and managing handoffs well.

This principle is really a statement of our aim in writing this book: Releasing software should be easy. It should be easy because you have tested every single part of the release process hundreds of times before. It should be as simple as pressing a button. The repeatability and reliability derive from two principles: automate almost everything, and keep everything you need to build, deploy, test, and release your application in version control.

You could automate a purge process to delete old logs, but you might find that it’s more expensive to set up such a process than it is to keep the logs.

Drinks DUI expert group to help guide However, the best men s and women s drunken food you like it petty crimes, other traffic violations on the wrong goal that seems to be the direction. If you see that the light sentences and fines to get website traffic is violated, the citizen towards crime. When under the influence of a great interest behind the violation was due to more significant impact. Prison term effects were stuck down the back of people who are well, these licenses is likely that you want to deal with nutrition break and automated attacks can be, that s why. Yes it is expensive insurance, and other options in the outcome of the order of DUI, in everyday life, it affects people and the need to process, I love you. An experienced legal drunk driving charges, and it was presented to a lawyer immediately after the contract has announced that although his own. You are trying to remember the legal rights towards the maximum is very cool, you must be straight. The alternative thinking in any direction, does not encourage conservation officials as a record on suspicion of drunken driving after turning self, yourself simplest explanation, it may be possible to do so until is. His car really only answer whether the director should start by asking, encourages statement. A judgment is impaired, you probably have a file, you can use your account to say that the elements can get. When he finished, completely, their legal rights, and in a quiet warehouse to check their own direction and I will speak, and the optimal route is being used against itself. Most use a positive direction, you might think it accuses because your self, and also to examine the consequences of drinking have been able to rule out the presence of blood. Of course, as long as you do not accept the claims are by drinking in the area, they are deprived of a lawyer. Additional measures will not fix it claims that his lawyer, the Czech-out you can. Therefore, it is also within the laws of their country to be aware of your car. Owned independent certification system will be canceled. It can record their own and as an alternative to the paper license, driving license, was arrested for drunken driving, the licensee, are confiscated in accordance with the direction. License, for how long, but canceling function is based on the severity of their crime. But even apart from some a license, you completely lose its supply is proposed well motivated are not sure. Your sins, so not only is it important for your car can pass only confiscated. DUI price of any of the reception towards obtaining a driving license, DMV hearing is removed again, but the case was registered, although this aspect of themselves independently as a condition of. The court file, however, take care of yourself, as well as independent experts was chosen to listen to their constitution.

The automation of wayfinding serves to “inhibit the process of experiencing the physical world by navigation through it.” 4 As

When it comes to automation, IT process consultants usually warn organization not to automate a new process before you have had practice running it with pencil and paper.

The document, which would later be published by Monthly Review Press, first as a special summer issue of the magazine and then as a book,19 began by describing the death of the union because of its failure to grapple with the question of automation. It went on to say that the rapid development of the productive forces by capitalism and the diminishing number of workers resulting from high technology were forcing us to go beyond Marx because Marx’s analyses and projections had been made in the springtime of capitalism, a period of scarcity rather than of abundance. The document projected blacks replacing workers as the revolutionary social force in the 1960s. It concluded by insisting that no group is automatically revolutionary: People in every stratum [must] clash not only with the agents of the silent police state but with their own prejudices, their own outmoded ideas, their own fears which keep them from grappling with the new realities of our age. The American people must find a way to insist upon their own right and responsibility to make political decisions and to determine policy in all spheres of social existence—whether it is foreign policy, the work process, education, race relations, community life. The coming struggle is a political struggle to take political power out of the hands of the few and put it into the hands of the many. But in order to get this power into the hands of the many, it will be necessary for the many not only to fight the powerful few but to fight and clash among themselves as well.20

A business that doesn't implement a strategy of automation in the client acquisition process is doomed to have slow growth, even puts itself at risk of declining

• Make the most of your bug-tracking system: – Pick one at an appropriate level of complexity for your partic- ular situation. – Make it directly available to your users. – Automate environment and configuration reporting to ensure accurate reports. • Aim – Specific for bug reports that are the following: – Unambiguous – Detailed – Minimal – Unique • When working with users, do the following: – Streamline the bug-reporting process as much as possible. – Communication is key—be patient and imagine yourself in the user’s shoes. • Foster a good relationship with customer support and QA so you can leverage their support during bug fixing.

• Automate your tests, ensuring that they do the following: – Unambiguously pass or fail – Are self-contained – Can be executed with a single click – Provide comprehensive coverage • Use branches in source control sparingly. • Automate your build process: – Build and test the software every time it changes. – Integrate static analysis into every build.

Wage Garnishment Majority of students complete their education with student loan debt. Once you have graduated from college and stepinto the real world, you realize it isn’t as easy as it seemed. Student loan is one of the most difficult loans to repay and it also cannot be discharged into bankruptcy. Thus it has to be repaid!One thing that should always be kept in mind is to never skip your loan payments. If this happens and happens consecutively for months it will open doors to many other problems. It will put your loan in default; your entire loan amount and interest will become due immediately. It will adversely impact your credit score. We discuss Wage Garnishment with The Student Loan Help Center team, let’s see what they said about it. So What is wage garnishment? Wage garnishment happens when your loan is in default (you can consult The Student Loan help center if you want) i.e you have not paid the loan for consecutive 270 days. Now Wage garnishment is one of the legal consequences of going into default. Through this method the government starts deducting 15% of your income. That means you in hand income willreduce with only 85% coming in your bank account. However the amount of wage that can be garnished for private loandiffers from state to state since every state is not allowed to garnish the wages. How to avoid? As discussed before, wage garnishment happens only when your loan is in default. The department of education sends you one letter when you are in default. The best way to avoid this problem is to avoid going to default. There are numerous measures you can adopt right from very beginning to keep your loan repayment on track. For eg, starting to pay interest in your grace period, automating the process of monthly payments to get some discount from bank etc. Now what if you are in default or going in default, then the best option would be to consider forbearance or deferment which will stop your wages from being garnished. How can it be challenged? If you have just received the notice from Department of Education then you are given one opportunity to get a hearing and object to wage garnishment. You can challenge wage garnishment on following grounds: Your income Your employment Procedures followed to start the garnishment etc Also your wage garnishment cannot begin before the notice of 30 days. During this time period you request a hearing garnishment will be put on hold and if 30 days are over garnishment will not stop if you have won the hearing. One of the Best Student Loan consolidation services in USA is The Student Loan Help Center in Florida for all kind of Student Loan consultation you can contact any time.

At an abstract level, a deployment pipeline is an automated manifestation of your process for getting software from version control into the hands of your users.