Hardware Components Quotes

Even though the software component of a technology is often not so easy to observe, we should not forget that technology almost always represents a mixture of hardware and software aspects. According to our definition, technology is a means of uncertainty reduction that is made possible by information about the cause-effect relationships on which the technology is based.

To be a software developer was to run the rest stops off the exits and to make sure that all the fast-food and gas station franchises accorded with each other and with user expectations; to be a hardware specialist was to lay the infrastructure, to grade and pave the roads themselves; while to be a network specialist was to be responsible for traffic control, manipulating signs and lights to safely route the time-crunched hordes to their proper destinations. To get into systems, however, was to be an urban planner, to take all of the components available and ensure their interaction to maximum effect. It was, pure and simple, like getting paid to play God, or at least a tinpot dictator.

In early 2016, Amazon was given a license by the Federal Maritime Commission to implement ocean freight services as an Ocean Transportation Intermediary. So, Amazon can now ship others’ goods. This new service, dubbed Fulfillment by Amazon (FBA), won’t do much directly for individual consumers. But it will allow Amazon’s Chinese partners to more easily and cost-effectively get their products across the Pacific in containers. Want to bet how long it will take Amazon to dominate the oceanic transport business? 67 The market to ship stuff (mostly) across the Pacific is a $ 350 billion business, but a low-margin one. Shippers charge $ 1,300 to ship a forty-foot container holding up to 10,000 units of product (13 cents per unit, or just under $ 10 to deliver a flatscreen TV). It’s a down-and-dirty business, unless you’re Amazon. The biggest component of that cost comes from labor: unloading and loading the ships and the paperwork. Amazon can deploy hardware (robotics) and software to reduce these costs. Combined with the company’s fledgling aircraft fleet, this could prove another huge business for Amazon. 68 Between drones, 757/ 767s, tractor trailers, trans-Pacific shipping, and retired military generals (no joke) who oversaw the world’s most complex logistics operations (try supplying submarines and aircraft carriers that don’t surface or dock more than once every six months), Amazon is building the most robust logistics infrastructure in history. If you’re like me, this can only leave you in awe: I can’t even make sure I have Gatorade in the fridge when I need it.

Jobs’s reluctance to make the Mac compatible with the architecture of the Lisa was motivated by more than rivalry or revenge. There was a philosophical component, one that was related to his penchant for control. He believed that for a computer to be truly great, its hardware and its software had to be tightly linked. When a computer was open to running software that also worked on other computers, it would end up sacrificing some functionality. The best products, he believed, were “whole widgets” that were designed end-to-end, with the software closely tailored to the hardware and vice versa. This is what would distinguish the Macintosh, which had an operating system that worked only on its own hardware, from the environment that Microsoft was creating, in which its operating system could be used on hardware made by many different companies.

A great deal of effort has been devoted to explaining Babel. Not the Babel event -- which most people consider to be a myth -- but the fact that languages tend to diverge. A number of linguistic theories have been developed in an effort to tie all languages together." "Theories Lagos tried to apply to his virus hypothesis." "Yes. There are two schools: relativists and universalists. As George Steiner summarizes it, relativists tend to believe that language is not the vehicle of thought but its determining medium. It is the framework of cognition. Our perceptions of everything are organized by the flux of sensations passing over that framework. Hence, the study of the evolution of language is the study of the evolution of the human mind itself." "Okay, I can see the significance of that. What about the universalists?" "In contrast with the relativists, who believe that languages need not have anything in common with each other, the universalists believe that if you can analyze languages enough, you can find that all of them have certain traits in common. So they analyze languages, looking for such traits." "Have they found any?" "No. There seems to be an exception to every rule." "Which blows universalism out of the water." "Not necessarily. They explain this problem by saying that the shared traits are too deeply buried to be analyzable." "Which is a cop out." "Their point is that at some level, language has to happen inside the human brain. Since all human brains are more or less the same --" "The hardware's the same. Not the software." "You are using some kind of metaphor that I cannot understand." "Well, a French-speaker's brain starts out the same as an English-speaker's brain. As they grow up, they get programmed with different software -- they learn different languages." "Yes. Therefore, according to the universalists, French and English -- or any other languages -- must share certain traits that have their roots in the 'deep structures' of the human brain. According to Chomskyan theory, the deep structures are innate components of the brain that enable it to carry out certain formal kinds of operations on strings of symbols. Or, as Steiner paraphrases Emmon Bach: These deep structures eventually lead to the actual patterning of the cortex with its immensely ramified yet, at the same time, 'programmed' network of electrochemical and neurophysiological channels." "But these deep structures are so deep we can't even see them?" "The universalists place the active nodes of linguistic life -- the deep structures -- so deep as to defy observation and description. Or to use Steiner's analogy: Try to draw up the creature from the depths of the sea, and it will disintegrate or change form grotesquely.

The collapse, for example, of IBM’s legendary 80-year-old hardware business in the 1990s sounds like a classic P-type story. New technology (personal computers) displaces old (mainframes) and wipes out incumbent (IBM). But it wasn’t. IBM, unlike all its mainframe competitors, mastered the new technology. Within three years of launching its first PC, in 1981, IBM achieved $5 billion in sales and the #1 position, with everyone else either far behind or out of the business entirely (Apple, Tandy, Commodore, DEC, Honeywell, Sperry, etc.). For decades, IBM dominated computers like Pan Am dominated international travel. Its $13 billion in sales in 1981 was more than its next seven competitors combined (the computer industry was referred to as “IBM and the Seven Dwarfs”). IBM jumped on the new PC like Trippe jumped on the new jet engines. IBM owned the computer world, so it outsourced two of the PC components, software and microprocessors, to two tiny companies: Microsoft and Intel. Microsoft had all of 32 employees. Intel desperately needed a cash infusion to survive. IBM soon discovered, however, that individual buyers care more about exchanging files with friends than the brand of their box. And to exchange files easily, what matters is the software and the microprocessor inside that box, not the logo of the company that assembled the box. IBM missed an S-type shift—a change in what customers care about. PC clones using Intel chips and Microsoft software drained IBM’s market share. In 1993, IBM lost $8.1 billion, its largest-ever loss. That year it let go over 100,000 employees, the largest layoff in corporate history. Ten years later, IBM sold what was left of its PC business to Lenovo. Today, the combined market value of Microsoft and Intel, the two tiny vendors IBM hired, is close to $1.5 trillion, more than ten times the value of IBM. IBM correctly anticipated a P-type loonshot and won the battle. But it missed a critical S-type loonshot, a software standard, and lost the war.

Similarly, the computers used to run the software on the ground for the mission were borrowed from a previous mission. These machines were so out of date that Bowman had to shop on eBay to find replacement parts to get the machines working. As systems have gone obsolete, JPL no longer uses the software, but Bowman told me that the people on her team continue to use software built by JPL in the 1990s, because they are familiar with it. She said, “Instead of upgrading to the next thing we decided that it was working just fine for us and we would stay on the platform.” They have developed so much over such a long period of time with the old software that they don’t want to switch to a newer system. They must adapt to using these outdated systems for the latest scientific work. Working within these constraints may seem limiting. However, building tools with specific constraints—from outdated technologies and low bitrate radio antennas—can enlighten us. For example, as scientists started to explore what they could learn from the wait times while communicating with deep space probes, they discovered that the time lag was extraordinarily useful information. Wait times, they realized, constitute an essential component for locating a probe in space, calculating its trajectory, and accurately locating a target like Pluto in space. There is no GPS for spacecraft (they aren’t on the globe, after all), so scientists had to find a way to locate the spacecraft in the vast expanse. Before 1960, the location of planets and objects in deep space was established through astronomical observation, placing an object like Pluto against a background of stars to determine its position.15 In 1961, an experiment at the Goldstone Deep Space Communications Complex in California used radar to more accurately define an “astronomical unit” and help measure distances in space much more accurately.16 NASA used this new data as part of creating the trajectories for missions in the following years. Using the data from radio signals across a wide range of missions over the decades, the Deep Space Network maintained an ongoing database that helped further refine the definition of an astronomical unit—a kind of longitudinal study of space distances that now allows missions like New Horizons to create accurate flight trajectories. The Deep Space Network continued to find inventive ways of using the time lag of radio waves to locate objects in space, ultimately finding that certain ways of waiting for a downlink signal from the spacecraft were less accurate than others. It turned to using the antennas from multiple locations, such as Goldstone in California and the antennas in Canberra, Australia, or Madrid, Spain, to time how long the signal took to hit these different locations on Earth. The time it takes to receive these signals from the spacecraft works as a way to locate the probes as they are journeying to their destination. Latency—or the different time lag of receiving radio signals on different locations of Earth—is the key way that deep space objects are located as they journey through space. This discovery was made possible during the wait times for communicating with these craft alongside the decades of data gathered from each space mission. Without the constraint of waiting, the notion of using time as a locating feature wouldn’t have been possible.

The Android sensor framework lets you access many types of sensors. Some of these sensors are hardware-based and some are software-based. Hardware-based sensors are physical components built into a handset or tablet device. They derive their data by directly measuring specific environmental properties, such as acceleration, geomagnetic field strength, or angular change. Software-based sensors are not physical devices, although they mimic hardware-based sensors. Software-based sensors derive their data from one or more of the hardware-based sensors and are sometimes called virtual sensors or synthetic sensors. The linear acceleration sensor and the gravity sensor are examples of software-based

software-based. Hardware-based sensors are physical components built into a handset or tablet device. They derive their data by directly measuring specific environmental properties, such as acceleration, geomagnetic field strength, or angular change. Software-based sensors are not physical devices, although they mimic hardware-based sensors. Software-based sensors derive their data

In Celebration, AT&T donated the hardware and installation components to create the Celebration Community Network, an intranet that provides town residents with email, chat rooms, a bulletin-board service, and access to the Internet, all free of charge.

each service can be deployed on hardware that’s best suited to its resource requirements. This is quite different than when using a monolithic architecture, where components with wildly different resource requirements—for example, CPU-intensive vs. memory-intensive—must be deployed together.

To complicate matters, the human machine, with its hardware and software components, doesn’t always function as anticipated. Our DNA, our genetic code, essentially acts like an instruction manual, working in the background to influence our behaviour alongside our occasionally faulty logic systems, making us vulnerable to emotional influence. Annoyingly, there is no user manual to explain this.

Virtualization in computing often refers to the abstraction of some physical component into a logical object. By virtualizing an object, you can obtain some greater measure of utility from the resource the object provides. For example, Virtual LANs (local area networks), or VLANs, provide greater network performance and improved manageability by being separated from the physical hardware.

Gracie, ill-behaved cretins can thrash your user interface, frag your hardware, unplug your peripherals, uninstall your components—but dreams are proprietary technology.” “Huh?” “No one can take your dreams away.

That being said, if performance and isolation are the upside, then efficiency and flexibility are its main downsides. Bare metal servers cannot be subdivided beyond their hardwired components. This either tends to leave a lot of underutilized hardware out there, or results in developers piggybacking multiple applications onto each physical server

Hardware had to be researched, purchased, secured, integrated, tracked, and disposed of. Software had to be licensed, configured, patched, updated, and eventually replaced. Networks had to be built, secured, upgraded, and inevitably rebuilt. And every component interacted with every other component in curious and unexpected ways, with unexpected occasionally culminating in catastrophic.   The

If the Mac was so great, why did it lose? Cost, again. Microsoft concentrated on the software business and unleashed a swarm of cheap component suppliers on Apple hardware. It did not help, either, that suits took over during a critical period. (And it hasn't lost yet. If Apple were to grow the iPod into a cell phone with a web browser, Microsoft would be in big trouble.)

FUNCTIONAL SAFETY AS PER IEC 61511 SIF SIS SIL TRAINING FUNCTIONAL SAFETY COURSE OBJECTIVES: The main objective of this training program is to give engineers involved in safety instrumented systems the opportunity to learn about functional safety, current applicable safety standards (IEC 61511) and their requirements. The Participants will be able to learn to follow: • Understand the basic requirements of the functional safety standards (IEC 61511) • The meaning of SIS, SIF, SIL and other functional safety terminology • Differentiate between safety functions and control functions • The role of Hazard and Risk analysis in setting SIL targets• • Create basic designs of safety instrumented systems considering architectural constraints • Different type of failures and best practices for minimizing them • Understand the effect of redundancy, diagnostics, proof test intervals, hardware fault tolerance on the SIL • The responsibility of operation and maintenance to ensure a SIF meets its SIL • How to proof test a SIF The Benefits for the Participants: At the conclusion of the training, the participants will be able to: Participate effectively in SIL determination with Risk graph, Risk matrix, and LOPA methodology Determine whether the design of a Safety Instrumented Function meets the required SIL. Select a SIF architecture that both meets the required SIL and minimizes spurious trips. Select SIF components to meet the target SIL for that SIF Target Audience: Instrument and Control Design and maintenance engineers Process Engineers Process Plant Operation Engineers Functional safety Management Engineers For Registration Email Us On techsupport@marcepinc.com or call us on 022-30210100

Systems are complex. A computer system is not just hardware, not just software, not even just people plus hardware plus software. The procedures, formal and informal, that have evolved with the system are part of the system; so is the current load on various components, and so is the attitude and experience of the users. Even among the commonly accepted “parts” of a system, clear lines of separation do not exist. Hardware merges with operating system, operating system merges with programming language, programming language merges with debugging tools, debugging tools merge with documentation, and documentation merges with training, and all of them mingle with the social climate in which the system is used.

Apple has a consistent and exquisite concept of using the God curve in everything. The God curve is the curvature of the rounded corners that you can see in many places. For example, in the iPhone, you can see the God curve in the metal frame, the physical buttons, the rear bump, the camera, the receiver, the display, the Lighting connector, and even some internal components. In the software, you can see the God curve in the app icon, the dock, the search bar, the settings bar, the control center, the notification bar in notification center, the widget, and the notch (or dynamic island). The God curve is also present in other products, such as the Macbook and its software. And even in Apple's buildings and facilities, such as the Apple Park visitor center and its trash cans and seats. The God curve is a legacy of Mr. Jobs, who made sure that everything Apple does has a high level of consistency and elegance across hardware, software, product, and enterprise.

Apple has a consistent and exquisite concept of using the God curve in everything. The God curve is the curvature of the rounded corners that you can see in many places. For example, in the iPhone, you can see the God curve in the metal frame, the physical buttons, the rear bump, the camera, the receiver, the display, the Lighting connector, and even some internal components. In the software, you can see the God curve in the app icon, the dock, the search bar, the settings bar, the control center, the notification bar in notification center, the widget, and the notch (or dynamic island). The God curve is also present in other products, such as the Macbook and its software. And even in Apple's buildings and facilities, such as the Apple Park visitor center and its trash cans and seats. The God curve is a legacy of Mr. Jobs, who made sure that everything Apple does has a high level of consistency and elegance across hardware, software, product, and enterprise.

This is particularly true for hardware, where creating revisions of circuits and mechanical components can take weeks or months. Sweating the details up front of what we’re trying to accomplish can easily avoid an extra round of revisions, shaving months and serious dollars from the project.

The logistics and assembly of the parts, as directed by Eken, were a testament to the way Starrett Bros. & Eken got things done. The components that made up the building came from factories, foundries, and quarries from far and wide—the limestone from Indiana, steel girders from Pittsburgh, cement and mortar from upper New York State, marble from Italy, France, and England, wood from northern and Pacific Coast forests, hardware from New England. Hundreds of other things from equally distant points of manufacture or origin were delivered to the building site and assembled into one great structure, each fitting into its proper place as detailed in the architect’s plans.