digital twin

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pages: 523 words: 61,179

Human + Machine: Reimagining Work in the Age of AI by Paul R. Daugherty, H. James Wilson

3D printing, AI winter, algorithmic trading, Amazon Mechanical Turk, augmented reality, autonomous vehicles, blockchain, business process, call centre, carbon footprint, cloud computing, computer vision, correlation does not imply causation, crowdsourcing, digital twin, disintermediation, Douglas Hofstadter,, Erik Brynjolfsson, friendly AI, future of work, industrial robot, Internet of things, inventory management, iterative process, Jeff Bezos, job automation, job satisfaction, knowledge worker, Lyft, natural language processing, personalized medicine, precision agriculture, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, Rodney Brooks, Second Machine Age, self-driving car, sensor fusion, sentiment analysis, Shoshana Zuboff, Silicon Valley, software as a service, speech recognition, telepresence, telepresence robot, text mining, the scientific method, uber lyft

Engineers, thanks to AI, now have more data than ever to understand the operations of their systems.7 Reimagined operations. The field data collected also enables GE to build digital twins of its deployed products, like its jet engines. Engineers can then test virtual flights in which the plane experiences cold, heat, dust, rain, and even a flock of birds.8 The company is also monitoring ten thousand wind turbines, and their digital twins are helping the turbines to adapt in real time. One valuable insight from an analysis of that data is that, depending on the direction of the wind, it might be best to have the leading turbine run slower than engineers might expect.

One valuable insight from an analysis of that data is that, depending on the direction of the wind, it might be best to have the leading turbine run slower than engineers might expect. When the front turbine absorbs less energy, the ones behind it can operate at close to their optimal levels, increasing energy generation overall. This application shows that digital twin technology can be applied beyond a single product to holistically optimize an entire wind farm’s activity. According to GE, digital twins could increase wind-farm output by 20 percent and provide $100 million of value over the lifetime of a 100-megawatt wind farm.9 All three of these uses of Predix are freeing up human workers to do less routine work and more engaging work.

In the case of the GE maintenance worker, you would need the ability to ask the machine smart questions across multiple levels of abstraction. We call this skill intelligent interrogation. As a maintenance worker using the GE’s digital twin, you would start your interrogation with the troubled rotor but quickly scale up, asking questions about operations, process, and financial concerns. You aren’t just a rotor expert; with the help of the digital twin, you’ve become an expert of a much more complex system; your knowledge of “how things work” has become ever more important. We describe each of the eight fusion skills to guide managers and workers in designing and developing a workforce capable of thriving in the missing middle (see figure 8-1).

pages: 244 words: 66,977

Subscribed: Why the Subscription Model Will Be Your Company's Future - and What to Do About It by Tien Tzuo, Gabe Weisert

3D printing, Airbnb, airport security, Amazon Web Services, augmented reality, autonomous vehicles, blockchain, Build a better mousetrap, business cycle, business intelligence, business process, call centre, cloud computing, cognitive dissonance, connected car, death of newspapers, digital twin, double entry bookkeeping, Elon Musk, factory automation, fiat currency, Internet of things, inventory management, iterative process, Jeff Bezos, Kevin Kelly, Lean Startup, Lyft, manufacturing employment, minimum viable product, natural language processing, Network effects, Nicholas Carr, nuclear winter,, profit maximization, race to the bottom, ride hailing / ride sharing, Sand Hill Road, shareholder value, Silicon Valley, skunkworks, smart meter, social graph, software as a service, spice trade, Steve Ballmer, Steve Jobs, subscription business, Tim Cook: Apple, transport as a service, Uber and Lyft, uber lyft, Y2K, Zipcar

He pointed out that digital twins don’t just represent how their physical assets were designed or how they were built—they display how those assets are operating in real time. A jet engine that’s being operated in the US Southwest, for example, has a different digital twin from one that primarily flies across the North Sea. Over time, those engines behave and degrade in different ways, and they transmit usage data accordingly. Very soon, engineers on the ground will use augmented reality headsets to see all this information overlaid on the jet engines when they inspect them. The digital twins will point out wear and trouble spots and offer opinions on how to resolve issues based on asset history.

Today . . . most of our factories look the same as they did 50 years ago. That’s all about to change. DIGITAL TWINS You may have grown up thinking of General Electric as a kitchen appliance company. Today they build wind turbines, jet engines, oil rigs. They also have a thriving data services business—maybe you’ve seen some of their commercials aimed at recruiting more developers. They have over $3 trillion in assets that they manage on a regular basis, and today almost all of them have twins—more specifically, digital twins. We recently hosted Gytis Barzdukas, vice president at General Electric Digital, at our Subscribed conference in San Francisco.

So sensor retrofitting and networking, or the “implementation phase” of IoT, are set to become a huge growth industry in the years ahead. And what happens when you have a vast network of digital twins that represent every asset across your entire product line? Well, the first beneficiary was GE itself. What if you had one engine acting up, or one compressor behaving strangely, among thousands? Imagine that if instead of trying to catch problems with expensive and laborious mass maintenance procedures, you had a network of digital twins sending you relevant signals from individual assets. Well, you could fix the biggest problems much faster. GE quickly realized more than $200 million a year in savings, simply by improving their efficiency.

Industry 4.0: The Industrial Internet of Things by Alasdair Gilchrist

3D printing, additive manufacturing, Amazon Web Services, augmented reality, autonomous vehicles, barriers to entry, business intelligence, business process, chief data officer, cloud computing, connected car, cyber-physical system, deindustrialization, DevOps, digital twin, fault tolerance, global value chain, Google Glasses, hiring and firing, industrial robot, inflight wifi, Infrastructure as a Service, Internet of things, inventory management, job automation, low cost airline, low skilled workers, microservices, millennium bug, pattern recognition, peer-to-peer, platform as a service, pre–internet, race to the bottom, RFID, Skype, smart cities, smart grid, smart meter, smart transportation, software as a service, stealth mode startup, supply-chain management, trade route, undersea cable, web application, WebRTC, Y2K

Again, in this scenario Rolls Royce uses thousands of sensors to monitor the engines every second of their working life, building up huge amounts of predictive data, so that it knows when a component’s service is degrading. By collecting and storing all those vast quantities of data, Rolls Royce can create a “digital twin” of the physical engine. Both the digital and its physical twin are virtual clones so engineers don’t have to open the engine to service components that are subsequently found to be fine, they know that already without touching or taking the engine out of service. This concept of the “digital twin” is very important in manufacturing and in the Industrial Internet as it allows Big Data analytics to determine recommendations that can be tested on a virtual twin machine and then processed before being put into production.

Creators of these robots are designing them to be self-sufficient, autonomous, and interactive, so that they are no longer simply tools used by humans, but they are already integral work units that function alongside humans. Simulation Previously, if manufacturers wanted to test if a process was working efficiently and effectively, trial and error was required. Industry 4.0 uses virtualization to create digital twins that are used for simulation modeling and testing and they will play more major roles in the optimization of production, as well as product quality. Horizontal and Vertical System Integration Having fully integrated OT and IT systems is something that Industry 4.0 aims for. The goal is to create a scenario where engineering, production, marketing, and after-sales are closely linked.

See Industrial internet of things (IIoT) Industrial operations technology (IOT), 1–2, 183 Industrial internet architecture framework (IIAF), 67 Industrial internet consortium (IIC), 66 Industrial internet of things (IIoT) B2C, 2 Big Data, 3, 5 building’s energy efficiency, 20 business gains, 3 catalysts and precursors adequately skilled and trained staff, 6 innovation, commitment to, 6 security, 7 cloud-computing model, 6 commercial market, 1 consumer market, 1 digital and human workforce, 11 digital twin, 11 green house gas emissions, 19 heath care, 14 Industry 4.0, 2 innovation, 7 installing sensors and actuators, 20 intelligent devices, 8 IOT, 1–2 IOT, disadvantages, 20 247 248 Index Industrial internet of things (IIoT) (cont.) IOT6 Smart Office, 21 IT sectors, 5 key opportunities and benefits, 8 logistics adopting sensor technologies, 24 advanced telemetric sensors, 26 augmented reality glasses, 25 automating stock control task, 24 barcode technology, 23 Big Data, 26–27 document scanning and verification, 26 forklift, 24–25 Google Glass, 25 multiple sensors, 26 pick-by-paper, 25 RFID, 23–24 SmartLIFT technology, 24–25 temperature and humidity sensors, 24 track and trace, 26 M2M, 3 manufacturers, 10 Oil and Gas industry automated remote control topology, 18 automation, 18 Big Data analytics, 19 cloud computing, 17 data analytics, 16 data collection and analysis, 18 data distribution system, 17 DDS bus, 18 down-hole sensors, 16 drilling and exploration, 16 industry regulations, 16 intelligent real-time reservoir management, 19 interconnectivity, 17 MQPP and XMPP, 17 remote node's status, 17 6LoWLAN and CoAP, 17 technological advances, 16 wireless technologies and protocols, 17 outcome economy, 10 power of 1%, 4 retailer innovations, 29 IT costs, 27 POS, 27–28 real-time reporting and visibility, 28 stock control, 28 sensor technology, 4 smartphone, 20 WSN, 21 WWAN, 5 Industrial Internet system communication protocols Ethernet protocol, 100 industrial Ethernet, 98 TCP/UDP containers, 100 concept of, IIoT, 88 diverse technology, 116 gateways, 115 heterogeneous networks, 116 industrial gateway, 118 industrial protocols current loop, 97 field bus technology, 98 RS232 serial communications, 96 proximity and access network address types, 114 IIoT context, 115 IPv4, 109 IPv6, 112 IPv6 Subnets, 114 NAT, 111 proximity network, 89 wireless communication technology, 102 bluetooth low energy, 103 IEEE 802.15.4, 102 NFC, 107 RFID, 106 RPL, 108 6LoWPAN, 107 Thread, 107 Wi-Fi backscatter, 105 ZigBee, 103 ZigBee IP, 104 Z-Wave, 105 WSN edge node, 90 functional layers, 93 IP layers vs.

pages: 424 words: 114,905

Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again by Eric Topol

23andMe, Affordable Care Act / Obamacare, AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, artificial general intelligence, augmented reality, autonomous vehicles, bioinformatics, blockchain, cloud computing, cognitive bias, Colonization of Mars, computer age, computer vision, conceptual framework, creative destruction, crowdsourcing, Daniel Kahneman / Amos Tversky, dark matter, David Brooks, digital twin, Elon Musk,, epigenetics, Erik Brynjolfsson, fault tolerance, George Santayana, Google Glasses, ImageNet competition, Jeff Bezos, job automation, job satisfaction, Joi Ito, Mark Zuckerberg, medical residency, meta analysis, meta-analysis, microbiome, natural language processing, new economy, Nicholas Carr, nudge unit, pattern recognition, performance metric, personalized medicine, phenotype, placebo effect, randomized controlled trial, recommendation engine, Rubik’s Cube, Sam Altman, self-driving car, Silicon Valley, speech recognition, Stephen Hawking, text mining, the scientific method, Tim Cook: Apple, War on Poverty, Watson beat the top human players on Jeopardy!, working-age population

With their cloud-based platform, cluster computing, natural-language processing, and AI capabilities, there was the infrastructure to build “the world’s largest library of molecular and clinical data and an operating system to make that data accessible and useful.”46 Tempus Labs, now collaborating with more than forty of the National Cancer Institute centers in the United States, performs a range of studies, including the list above from sequencing to culturing. Beyond the extensive assessment of the patient, Tempus provides “digital twin” information with their report generated two to three weeks after samples are received. This consists of treatment and outcomes information from the de-identified patients most similar with respect to demographics and biologic information. That, too, employs an AI advanced analytic method of nearest neighbor analysis.

It would compensate for the fact that most biomedical research performed to date has been done with subjects of European ancestry, which means that physicians often cannot extrapolate their findings to individuals of other ancestries. If all members of the species had comprehensive data in such a resource, with their treatments and outcomes, this would enable AI nearest neighbor analysis to find “digital twins.” These are individuals who most resemble, by all demographic, biologic, physiologic, and anatomic criteria, the person at risk or with a new important diagnosis. Knowledge of outcomes from twins would enable better prevention or treatment of the individual and the next generation. The likelihood of assembling such a resource for the world’s population is very low, especially impaired by concerns over privacy, data security, and cross-cultural sharing considerations.

It’s a think-big scenario to imagine what awaits us in the longer term for all medical conditions without geographic boundaries. But even if the odds are low now, I hope recognition of the possibilities will help make those odds better. As soon as patient outcomes are shown to be unequivocally improved by having digital twins inform best treatment, it is likely there will be substantial commitments across health systems to develop and prioritize such infrastructure. With this review of the opportunities at the level of healthcare systems, it’s time to turn upstream—to the discovery side of drugs and the science that leads to better treatments and mechanistic insights about health and disease.

pages: 179 words: 43,441

The Fourth Industrial Revolution by Klaus Schwab

3D printing, additive manufacturing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, augmented reality, autonomous vehicles, barriers to entry, Baxter: Rethink Robotics, bitcoin, blockchain, Buckminster Fuller, call centre, clean water, collaborative consumption, commoditize, conceptual framework, continuous integration, crowdsourcing, digital twin, disintermediation, disruptive innovation, distributed ledger, Edward Snowden, Elon Musk, epigenetics, Erik Brynjolfsson, future of work, global value chain, Google Glasses, income inequality, Internet Archive, Internet of things, invention of the steam engine, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, life extension, Lyft, mass immigration, megacity, meta analysis, meta-analysis, more computing power than Apollo, mutually assured destruction, Narrative Science, Network effects, Nicholas Carr, personalized medicine, precariat, precision agriculture, Productivity paradox, race to the bottom, randomized controlled trial, reshoring, RFID, rising living standards, Sam Altman, Second Machine Age, secular stagnation, self-driving car, sharing economy, Silicon Valley, smart cities, smart contracts, software as a service, Stephen Hawking, Steve Jobs, Steven Levy, Stuxnet, supercomputer in your pocket, TaskRabbit, The Future of Employment, The Spirit Level, total factor productivity, transaction costs, Uber and Lyft, uber lyft, Watson beat the top human players on Jeopardy!, WikiLeaks, winner-take-all economy, women in the workforce, working-age population, Y Combinator, Zipcar

Positive impacts – Increased efficiency in using resources – Rise in productivity – Improved quality of life – Effect on the environment – Lower cost of delivering services – More transparency around the use and state of resources – Safety (e.g. planes, food) – Efficiency (logistics) – More demand for storage and bandwidth – Shift in labour markets and skills – Creation of new businesses – Even hard, real-time applications feasible in standard communication networks – Design of products to be “digitally connectable” – Addition of digital services on top of products – Digital twin provides precise data for monitoring, controlling and predicting – Digital twin becomes active participant in business, information and social processes – Things will be enabled to perceive their environment comprehensively, and react and act autonomously – Generation of additional knowledge, and value based on connected “smart” things Negative impacts – Privacy – Job losses for unskilled labour – Hacking, security threat (e.g. utility grid) – More complexity and loss of control Unknown, or cuts both ways – Shift in business model: asset rental/usage, not ownership (appliances as a service) – Business model impacted by the value of the data – Every company potentially a software company – New businesses: selling data – Change in frameworks to think about privacy – Massively distributed infrastructure for information technologies – Automation of knowledge work (e.g. analyses, assessments, diagnoses) – Consequences of a potential “digital Pearl Harbor” (i.e. digital hackers or terrorists paralysing infrastructure, leading to no food, fuel and power for weeks) – Higher utilization rates (e.g. cars, machines, tools, equipment, infrastructure) The shift in action The Ford GT has 10 million lines of computer code in it.

Demystifying Smart Cities by Anders Lisdorf

3D printing, artificial general intelligence, autonomous vehicles, bitcoin, business intelligence, business process, chief data officer, clean water, cloud computing, computer vision, continuous integration, crowdsourcing, data is the new oil, digital twin, distributed ledger, don't be evil, Elon Musk,, facts on the ground, Google Glasses, income inequality, Infrastructure as a Service, Internet of things, Masdar, microservices, Minecraft, platform as a service, ransomware, RFID, ride hailing / ride sharing, risk tolerance, self-driving car, smart cities, smart meter, software as a service, speech recognition, Stephen Hawking, Steve Jobs, Steve Wozniak, Stuxnet, Thomas Bayes, Turing test, urban sprawl, zero-sum game

Methods for communicating with devices When a device has been connected to a central platform or solution, we usually operate with a central representation of that device. This is called a digital twin or a digital shadow depending on vendor. The idea is that the centralized system keeps track of the device’s current state and its target state. This is the way that devices are typically managed. Consider a signal that can take the values of red, yellow, and green. The digital shadow may report that it is currently green. A central solution may wish it to be red and set the digital twin target state to red. This is then sent to the device which updates the signal to red. The central solution has to exchange data with the device in order for this to happen.

pages: 374 words: 94,508

Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage by Douglas B. Laney

3D printing, Affordable Care Act / Obamacare, banking crisis, blockchain, business climate, business intelligence, business process, call centre, chief data officer, Claude Shannon: information theory, commoditize, conceptual framework, crowdsourcing, dark matter, data acquisition, digital twin, discounted cash flows, disintermediation, diversification,, endowment effect, Erik Brynjolfsson, full employment, informal economy, intangible asset, Internet of things, linked data, Lyft, Nash equilibrium, Network effects, new economy, obamacare, performance metric, profit motive, recommendation engine, RFID, semantic web, smart meter, Snapchat, software as a service, source of truth, supply-chain management, text mining, uber lyft, Y2K, yield curve

The rise of the machines, algorithmic sprawl, and the promise of artificial intelligence (AI) depend upon accurate, complete, timely, granular, and unique information sources. The internet of things (IoT) will become the single fastest growing source and most voracious consumer of information. Digital twins that precisely represent models of physical things and their state rely on a variety of metadata, along with condition and event information. 3D printing is entirely contingent upon information-based representations of objects, and their ability to be monetized and managed effectively. The institutionalization of ethics in the face of commercialized and politicized misinformation will require the generation and management of new information sources to emerge with built-in trust indicators.

pages: 788 words: 223,004

Merchants of Truth: The Business of News and the Fight for Facts by Jill Abramson

23andMe, 4chan, Affordable Care Act / Obamacare, Alexander Shulgin, Apple's 1984 Super Bowl advert, barriers to entry, Bernie Madoff, Bernie Sanders, Charles Lindbergh, Chelsea Manning, citizen journalism, cloud computing, commoditize, corporate governance, creative destruction, crowdsourcing, death of newspapers, digital twin, diversified portfolio, Donald Trump, East Village, Edward Snowden, Ferguson, Missouri, Filter Bubble, future of journalism, glass ceiling, Google Glasses, haute couture, hive mind, income inequality, information asymmetry, invisible hand, Jeff Bezos, Joseph Schumpeter, Khyber Pass, late capitalism, Marc Andreessen, Mark Zuckerberg, move fast and break things, move fast and break things, Nate Silver, new economy, obamacare, Occupy movement, performance metric, Peter Thiel, phenotype, pre–internet, race to the bottom, recommendation engine, Robert Mercer, Ronald Reagan, Saturday Night Live, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, skunkworks, Snapchat, social intelligence, social web, Steve Jobs, Steven Levy, technoutopianism, telemarketer, the scientific method, The Wisdom of Crowds, Tim Cook: Apple, too big to fail, WikiLeaks

While the print journalists worked at the paper’s headquarters near the White House, which was made famous in the movie All the President’s Men, “the web people” worked a good distance away, across the Potomac River, in Virginia. The print team didn’t trust the people working on the web to have the same values that Bradlee and Downie had inculcated in the newsroom on 15th Street. Graham thought the culture of the main newsroom would suffocate its digital twin. He also liked that Virginia was a nonunion state. Its storied history and strong local ties did little to save the Post from the inexorable decade of decline that began in 2002. The internet had changed people’s reading habits, and circulation of the printed paper fell by nearly half. Ad revenue plummeted too, as local department stores and businesses of all kinds closed.

It was the digital cousin of the old theory of salesmanship, “The customer is always right.” Even in 2011 the digital operations at most of the major news outlets amounted to a website that was only marginally sleeker than it had been more than a decade prior. News websites were still designed to be digital twins of newspapers. For Smith, this presented an enormous business opportunity. “I feel in general the 800–1,200 word form of the news article is broken,” he said in a Nieman Lab interview. The basis for that conclusion: “You don’t see people sharing those kinds of stories.” BuzzFeed’s stated goal was “reinventing the wire story for the social web.”

pages: 501 words: 114,888

The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives by Peter H. Diamandis, Steven Kotler

Ada Lovelace, additive manufacturing, Airbnb, Albert Einstein, Amazon Mechanical Turk, augmented reality, autonomous vehicles, barriers to entry, bitcoin, blockchain, blood diamonds, Burning Man, call centre, cashless society, Charles Lindbergh, Clayton Christensen, clean water, cloud computing, Colonization of Mars, computer vision, creative destruction, crowdsourcing, cryptocurrency, Dean Kamen, delayed gratification, dematerialisation, digital twin, disruptive innovation, Edward Glaeser, Edward Lloyd's coffeehouse, Elon Musk,, epigenetics, Erik Brynjolfsson, Ethereum, ethereum blockchain, experimental economics, food miles, game design, Geoffrey West, Santa Fe Institute, gig economy, Google X / Alphabet X, gravity well, hive mind, housing crisis, Hyperloop, indoor plumbing, industrial robot, informal economy, Intergovernmental Panel on Climate Change (IPCC), Internet of things, invention of the telegraph, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, Joseph Schumpeter, Kevin Kelly, Kickstarter, late fees, Law of Accelerating Returns, life extension, lifelogging, loss aversion, Lyft, M-Pesa, Mary Lou Jepsen, mass immigration, megacity, meta analysis, meta-analysis, microbiome, mobile money, multiplanetary species, Narrative Science, natural language processing, Network effects, new economy, New Urbanism, Oculus Rift, out of africa, packet switching, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, Peter Thiel, QR code, RAND corporation, Ray Kurzweil, RFID, Richard Feynman, Richard Florida, ride hailing / ride sharing, risk tolerance, Satoshi Nakamoto, Second Machine Age, self-driving car, Silicon Valley, Skype, smart cities, smart contracts, smart grid, Snapchat, sovereign wealth fund, special economic zone, stealth mode startup, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, supercomputer in your pocket, supply-chain management, technoutopianism, Tesla Model S, Tim Cook: Apple, transaction costs, Uber and Lyft, uber lyft, unbanked and underbanked, underbanked, urban planning, Watson beat the top human players on Jeopardy!, We wanted flying cars, instead we got 140 characters, X Prize

Your comments become commands: “I’d love some black pumps to match my new dress” makes racks of perfectly fitting shoes appear. Yet none of these shoes seem exactly right. “How would this dress look with those satin Jimmy Choos sitting in your closet?” asks your friend. No problem. Every piece of physical clothing you own in the real world has a digital twin available in the virtual. You ask, and instantly, you’re wearing them. When you’re done selecting your outfit, the AI pays the bill. While your new clothes are being 3-D printed at a warehouse—before speeding your way via drone delivery—a digital version has been added to your personal inventory for use at future virtual events.