Tag: robotics

  • Low-Code and RPA With Appian CTO Michael Beckley

    Low-Code and RPA With Appian CTO Michael Beckley

    On the eve of the first virtual Appian World, we caught up with Appian founder and CTO Michael Beckley. Michael spoke to us about low-code and RPA as well as AI and robotics, all being leveraged to help organizations during the COVID-19 crisis.

    Obviously, given the current situation, developing applications quickly with a minimum of coding while harnessing automation and AI would be a big premium. This is a situation that seems perfect for Appian.

    In fact, the whole low-code and RPA model seems tailor-made for a COVID-like situation. Michael shares with us several instances of healthcare and governmental agencies using Appian and RPA to deliver massively scalable applications to measure and gather data around COVID-19.

    Low-code and RPA are not just COVID-19 trends, either. Michael and I discussed why the new normal will reward organizations that use RPA and low-code, as well as harnessing AI and robotics to build apps that can scale massively quickly with minimal coding.

    If Michael is correct, Appian is in an enviable position to deliver a robust, proven platform that will allow organizations to harness the power of low-code and RPA.

    My discussion with Michael is below. While Appian World virtual kicks off today, Michael actually delivers the keynote for the second day of Appian World on Wednesday. If you get a moment, don’t miss Michael’s talk. He has some great insight into how low-code and RPA can be a benefit during the COVID-19 crisis.

    While you’re at it, I highly recommend attending as much of Appian World that you can. I had the pleasure of attending one in Miami two years ago and was very much looking forward to this year’s event in Ft. Lauderdale, before it was converted to a virtual event. Appian’s hackathon is usually a great event to check out at Appian World as well.

  • 5G Security: Mitigating Threats in the Era of Hyperspeed and Hyperconnectivity

    5G Security: Mitigating Threats in the Era of Hyperspeed and Hyperconnectivity

    5G is one of the hottest industry buzzwords right now, and for good reason. Beyond its ability to deliver massive capacity, it is expected to be one of the fastest and most pervasive technologies of all time, fundamentally changing every sector of the economy.

    In recent years, we’ve lived through 3G and 4G. So what makes this next generation so revolutionary? Put simply, every emerging technology we are collectively excited about—IoT, VR/AR gaming, autonomous cars and smart cities—is enabled through 5G. This is because this next generation of the mobile network will increase the speed of service by extending high bandwidth and connectivity to the edge, a possibility that wasn’t quite there with 4G. 5G will connect everything around us via a network that is 100x faster than our current cellular connection and 10x faster than home broadband service.

    The technology is ready. From a commercial and business perspective, however, 5G implementation is still in its infancy. When it comes to capitalizing on the many use cases 5G offers, what is the holdup? With faster speeds, enormous data capacity, lower latency and more devices connecting and communicating than ever before, the security vulnerabilities are extreme. Given we are in the early stages of 5G deployments, service providers do not even know the full extent of the security concerns; they are just planning for the number of devices joining the network to grow exponentially. With the proliferation of connected personal devices, data privacy concerns have never been higher.

    To understand the potentially detrimental threats to personal safety and data privacy, we must first look at specific use cases enabled through this technology.

    The 5G Effect

    5G is more than just faster speeds—it is unlocking some of the most highly sought-after technologies of the decade. This is because low latency, or next-to-nothing lag time, allows a device asking something of the network to get a response almost instantaneously. For VR and AR gaming applications, this means a seamless user experience. And while sensory video games are good fun, these same principles can carry over to more serious applications in hospitals and other medical settings: By using a VR headset and special glove to control a robot arm, for example, a surgeon may have the ability to operate on a patient offsite.

    This extreme scenario offers two major risks: network lags and hacked equipment. An IoT-enabled hospital may have tens of thousands of “things” that could be compromised. Emergency room devices cannot afford to be starved for bandwidth if an admin printer is clogging the network. Any glitch in the network may lead to a slight delay in action, resulting in dangerous consequences. Additionally, with nefarious entries into the network through the high volume of vulnerable endpoints, the attack may have dire repercussions.

    A hospital is just one high-stakes environment. Now consider the IoT devices connected to a 5G network operating all around us—autonomous cars, energy grids, home security systems, etc.—the smallest glitch or endpoint vulnerability could lead to life-threatening situations.

    Many people do not realize 5G and IoT will have a major effect on seemingly innocuous devices such as refrigerators, thermometers and even light bulbs. While 5G will enable users to check on these types of appliances remotely through a simple app, convenience comes with consequence as these devices can also be usurped by malicious characters. It is important to recognize what 5G can enable, but also how it will all come together.

    Preparing for the Next-Gen

    Here are some tips on how enterprises can develop an effective 5G-ready security posture that encompasses the entire network:

    Invest in automation: 5G security poses its own Catch-22; because connections happen faster, attacks and breaches also happen faster and potentially with much more reach. To mitigate threats, 5G security will require actionable insights at scale. To achieve this, organizations need security systems that detect and automatically enforce security policy from endpoints to edge and every cloud in between.

    Scale up and out: To avoid a massive bottleneck, a proper 5G security posture will require upgrades to both physical and virtual infrastructures. Developing a secure architecture and solution that can keep up with the pace and scale of 5G without slowing it down is a large, but necessary, undertaking. The trick is to build in machine learning capabilities so the network can get smarter. Malware must traverse the network, so why not use all the data that the network already produces to fight it? A network that is constantly learning and updating is the only way to operate in the 5G landscape.

    Be proactive: History has shown us that whenever we expand our computing power and connectivity capabilities, we also expand the threat landscape. Not only that but as we continue to increase our dependency on communications networks and technologies to move tremendous amounts of data, there is greater potential for serious disaster should they be compromised. This is not the time to sit back and watch how things unfold, as major security risks are on the line.

    The use cases for 5G are plentiful. If we can conquer the threats, we can conquer anything the technology enables us to do—and the possibilities are endless.

    — Samantha Madrid

  • How IoT Security Risks Derailing Robotics

    How IoT Security Risks Derailing Robotics

    Driven by advances in technologies such as artificial intelligence and deep learning, the mobile robots market is projected to grow to $54.1 billion by 2023 from $18.7 billion last year, according to Markets and Markets. But for robotics to progress, security for the internet of things (IoT) needs to be addressed fast, before the reputation of the entire industry suffers a permanent setback.

    Every industry segment has a journey to maturity that involves ramping up how seriously it takes security. For robotics, that time has come. Failing to start robotics projects on the right software foundations will see confidence continue to drop, impeding the rate at which new solutions are created.

    The future of robotics rests firmly on the shoulders of the IoT. Robots act as one part of intelligent ecosystems—they depend on IoT to link various sensors and smart meters, and pass data to and from third parties.

    The self-driving car, for example, is a robot orchestrated by various smaller devices and smart sensors. In fact, robots are being created to tackle every conceivable problem. Take the Google-funded RangerBot, an underwater machine designed to track down a species of starfish responsible for coral reef destruction, or Small Robot Company, a startup tackling farming deficiencies with bots that autonomously feed, seed and weed arable crops.

    However, while IoT is an established concept and connected devices are now mainstream, its full potential has not been realized in part because of security concerns. Ninety percent of consumers lack confidence in connected devices, according to a recent survey. These concerns are more than valid, as nearly half of companies are unable to detect when a breach occurs, and only 15% of budgets are earmarked for IoT security.

    With IoT security a lingering weak spot, one major attack within robotics, could have a domino effect on the entire industry. Add to this the verticals that robots are beginning to infiltrate—health care and agriculture, for example—and the threat becomes immediate and very real.

    Rising levels of sophistication within robotics go hand in hand with more targeted and damaging attacks. For example, telesurgery uses robotics to help surgeons perform procedures remotely. A malware bug in this scenario could mean the downing of tools, threatening the patient’s life.

    Researchers at Brown University proved how easy it is to hack robots. The industry simply will not be sustainable without the backing of a secure, connected IoT network.

    Robot manufacturers, therefore, must build with a security-by-design mindset. This begins by selecting a robust operating system from the outset—secure now, but also ready for future market demands.

    Hackers are constantly evolving their activities and businesses must be flexible in their approach to security, shedding the old hardware-centric view of IoT security.

    Software no longer can end when a device is shipped. It must align to the lifespan of a robot and be able to update whenever there is a potential flaw. The world of mobile took many years to get to grips with this. Robotics and IoT developers should learn from their mistakes.

    One way developers can safely build and secure software is through snaps, containerized software packages on an open platform for building and publishing applications to an audience of millions.

    If a security vulnerability is discovered in the libraries used by an application, the app publisher is notified so the app can be rebuilt quickly with the supplied fix and pushed out. This allowsr developers to stay focused on innovation while ensuring the longevity of the robotics hardware.

    It remains unclear where the onus lies for IoT security, with nobody holding anyone else to account. Market constraints often prevent device makers from putting more budget than what is necessary into design security, when there is so much pressure to innovate ahead of competitors.

    These issues need to be solved. Robotics has too much potential to let security concerns stunt their growth.

    — Tom Canning

  • Full-Time Employment in the Age of Automation

    Full-Time Employment in the Age of Automation

    Back in 1930, the economist John Maynard Keynes wrote a short essay, “Economic Possibilities for our Grandchildren,” in which he predicted that in a hundred years the 15-hour work week will be commonplace. Keynes made this assertion based on two factors: first, the increase in capital due to extraordinary yields from the compound interest that was made possible by increased foreign (global) investment; second, the growth of technological achievement made necessary by the competitive forces of capitalism and made possible by the availability of excess capital.

    Keynes pointed out that these events are recent in terms of the entirety of human history, taking place over the last 500 years. Before that time, things were stagnant. Gold reserves remained static until the opening of the New World and technology, save for a few episodic breakthroughs, was pretty much unchanged. For example, the way cloth was made during the time of Joan of Arc, around 1400 AD, was not that different than the way it was made when the Roman emperor Hadrian had a wall built across northern England in 100 AD.

    But, the growing availability of money and technology changed everything. By 1920, the more affluent in the population wore factory-manufactured clothing bought in a store. Those of lesser means might still be making clothes at home, but the cloth from which the garment was made came from a factory.

    Mass-market capitalism powered by technological innovation increased human productivity on a scale unique in the human experience. Abundance on a global scale seemed a real possibility within a few generations. According to Keynes,

    “If capital increases, say, 2 percent per annum, the capital equipment of the world will have increased by a half in 20 years, and seven and a half times in a hundred years. Think of this in terms of material things—houses, transport, and the like.”

    Yet, today most people work 40 hours a week, if not more. Considering that Keynes was essentially a quant who lived and breathed data, how could he get it so wrong?

    My thinking is not so much that Keynes got it wrong, but that we’re having a hard time accepting that he might have gotten it right.

    Allow me to elaborate.

    The Facade of Productivity

    I have a theory: For the average contributor-employee in a medium- to large-size corporation (with 500 employees and more), of all the tasks he or she performs during a 40-hour week, only about half—20 hours’ worth—actually add value to the enterprise. The rest is organizational overhead. Thus, there is a good argument to be made that when you do the math, what we can call real full-time employment is closer to Keynes’s prediction of the 15-hour work week than not. The remaining time, which I call “organizational overhead,” is really just a facade of productivity.

    This theory occurred to me a while back, when I was sitting in a sprint planning meeting observing a project manager and tech-leads do task assignments. The first thing the project manager did was to determine how much time each member of the project team had available to work on the project’s tasks. The agreed-upon number was 20 hours a week.

    The 20-hours a week number struck me as strange. All members of the project team were completely dedicated to the project. They had no side work. The project was their one and only focus. What were they doing with the other 20 hours?

    I asked the project manager and he answered, “Well, they have to do things like answer emails, go to meetings and sometimes there’s some firefighting to be done.”

    Oh.

    The Amazing Ability to Absorb the Cost of Organizational Overhead

    I wish I could say that the project manager’s response was unique. But, in my experience, it’s not. I’ve been in more than one company in which meetings, email and firefighting occupy at least half of a full-time employee’s work week. And, I’ve got to tell you that, except in the rarest instance of mission-critical firefighting, most of these situations have marginal productive value.

    Granted, my theory is based on experiences that are anecdotal. The actual numbers might prove me wrong. Obviously, a thorough, quantitative study is needed. Still, whether it’s five, 10, 20 or even 35 hours a week, what’s amazing is not that employees spend a lot of time in activities that have questionable productive value, but rather, that businesses can actually operate profitably despite these ongoing time-sinks. Why? Because of automation. Machines and software are allowing people to do more work in less time—and it’s not only confined to IT.

    The Dirty Little Secret of Working on an Assembly Line

    Doubling up has always been the dirty little secret of automotive factory work. Ben Hamper revealed the details of technique in his 1986 book, “Rivethead: Tales from the Assembly Line.” Here’s how it works: Imagine that you and I work in a GM plant and do jobs at the same location on an assembly line—say, putting headlights and taillights in a car. Your job is to put in the headlights; my job is to put in the taillights. One day I notice that I can probably put the headlights and taillights in a car in the same amount of time it takes two of us to do the tasks separately. So, I propose a deal to you: I’ll do your job and my job for four hours a day in exchange for you doing the same for me. This way we can both work half time for full-time pay. We might have to pay the line foreman a small bribe to look the other way, but what the heck? The benefits are obvious, so we do it. Win-win, as the saying goes.

    How can we pull this off? Simple: as stated earlier, automation.

    Without the technology of the assembly line, we just couldn’t double up. The car needs to be brought to us for us to increase productivity to the point where one person can do the work of two. The automation of the assembly line effectively reduced our work week while maintaining our productivity, just as Keynes predicted.

    As you can see, the 15-hour work week is quite possible—and, in many cases, quite real. It’s just that the facade of productivity, which exists in larger companies, hides its existence. But, what about the smaller companies such as construction companies, law firms, small manufacturers, dental offices and software startups that employ fewer than 100 people? These types of companies cannot afford a lot of non-productive activity. How do these companies get to the 15-hour work week? Is it possible?

    My answer is yes, but the world that will need to exist to make the 15-hour work week possible will look dramatically different than the one we have today. What will that world look like? Allow me to illustrate using my neighborhood cafe, the C&M, as an example.

    The Real Implications of the 15-Hour Work Week

    My favorite neighborhood cafe is the C&M. It’s a hangout sort of place with good food, good coffee and Wi-Fi. The C&M is usually staffed by two employees during its business hours—7 a.m. to 5 p.m., seven days a week. Between them, they take orders as well as make the food and deliver it to the tables.

    Let’s do the math. Let’s figure that the actual working day at the C&M is 12 hours—10 hours of operation time and two hours of setup and cleanup. That comes out to 84 hours a week. Thus, excluding the owners’ time, the number of employee hours needed to run the C&M is 168. (two employees at 84 hours a week.) This comes out to around four people required to staff the business using the current 40-hour work week model, again excluding the owner’s time.

    Now, let’s say the business is quite profitable and the owner can afford to pay employees $20 an hour, plus health insurance. Adding in payroll tax and workman’s compensation (more than $5 an hour) plus the cost of health insurance ($400 a month, for illustration purposes), the weekly cost of each employee working 40 hours is $1,100, which translates into a total weekly labor cost for the C&M of $4,400.

    So far, so good.

    This time, let’s interpret the C&M labor situation in terms of the 15-hour work week. To cover the 168 hours per week that the C&M is operational, at a 15-hour work week per employee, the C&M needs to employee 11 people—actually, it’s 11.2 employees, but I rounded down. So, under Keynes prediction, if each employee is entitled to the established full-time compensation of $1,100 as calculated earlier, the weekly payroll for the C&M goes from $4,400 a week to $12,100—an almost three times increase, which is not an affordable number. Even though the number of employees has gone up, the odds are that the actual sales will remain the same. Instead of having to employ four people producing $14,000 a week in sales—$2,000 a day over seven days, again for illustration purposes—now the owner of the C&M will be employing 11 people to produce the same amount. Bankruptcy is imminent.

    Clearly, the C&M cannot tolerate 11 people working 15 hours a week for a full-time wage under current conditions. So much for the 15-hour work week. Well, not so fast. Let’s reimagine the scenario from a different angle: Suppose that the number of employees stays at four, but instead of working 40 hours a week, each employee works 15. What could we add to the mix to make this scenario possible? Give up? OK, I’ll tell you: robots.

    Imagine that instead of having two people on hand to set up the cafe, take orders, make the food, bring it over to tables, bus the table and then clean up at the end of the day, we had one person on hand to do what we’ll call human essential work. All the other work gets done by robots. Then, the typical interaction looks like this: Customers enter orders directly into an iPad, the robotic coffee maker gets the order and makes the double espresso, a robot in the kitchen makes the food, with the intermittent help of a human when necessary, and a robot delivers the food to the table. The one human on hand interacts with customers and picks up the slack work the robot can’t do. You can think of the scenario as the restaurant equivalent of a driverless Uber ride.

    Is such a world possible? Yes. In fact, it’s happening as you read this article. There’s already a chain of waiterless sushi restaurants in Japan. As the technology drops in price, more restaurants will make the transition.

    The 15-hour work week could indeed become a real possibility provided that two conditions exist: affordable robotic technology with a high degree of manual dexterity is available, and the employer is willing to pay the higher wages necessary to support the model.

    In the past, workers such as Ben Hamper used their ingenuity to take advantage of the reduction in labor that automation made possible. Sadly, such efforts were clandestine and deceitful. All that GM needed to do to realize a better return on labor was to speed up the assembly line. Yet, when you think about it, back then GM wasn’t doing that badly when Hamper was doubling up. 1984 was a record-setting year in sales, despite his shenanigans. Speeding up the line would undoubtedly increase GM’s bottom line. But, would it double Hamper’s take home? Probably not. (Author’s Note:  GM’s sales dropped 26 percent in 1986, but profits were still a healthy $1.06 billion.)

    So here are two questions to contemplate: As companies, large and small, adopt robotics to increase productivity, will they indeed share the benefits of the increased productivity with the average worker so he or she can enjoy a 15-hour work week? And then, should the 15-hour work week indeed become standard, what will the average person do with all this newfound leisure? As the saying goes, idle hands make fretful minds. According to Keynes:

    “Yet there is no country and no people, I think, who can look forward to the age of leisure and of abundance without a dread. For we have been trained too long to strive and not to enjoy. It is a fearful problem for the ordinary person, with no special talents, to occupy himself, especially if he no longer has roots in the soil or in custom or in the beloved conventions of a traditional society.”

    For those of you that think about such things, I will leave up to you to answer these questions. As for me, I can’t wait for the robots to take over so I can go back to my studies, full-time.

    — Bob Reselman

  • OECD Report Shows U.S. Leads in IoT, Lags in Robotics

    OECD Report Shows U.S. Leads in IoT, Lags in Robotics

    A newly published report by the Organisation for Economic Co-operation and Development (OECD) reveals the state of digital technology adoption, development and related research when it comes to digital transformation, manufacturing automation and providing skill sets for workers that will help carry them in the future.

    The “OECD Science, Technology and Industry Scoreboard 2017” found that when it comes to the internet of things (IoT), the United States leads other G20 countries. It also garners the largest share of the top 10 percent most-cited scientific publications in the world. But that’s where the very good news ends. According to the OECD, that share of the top scientific publications is dwindling as more and higher-quality research is increasingly coming from China. The United States is also below average when it comes to the adoption of robots in manufacturing.

    The top five economies when it comes to developing digital technologies? China, Chinese Taipei, Japan, Korea and the United States. According to the report, India and eastern Europe are becoming more substantially involved in innovation and science.

    Key findings in the 2017 Scoreboard include:

    • China, Chinese Taipei, Japan, Korea and the United States accounted for 70 percent to 100 percent of the 20 fastest growing new information and communications technologies (such as payment protocols or interactive TV) between 2012 and 2015, as measured by inventions patented in the five top intellectual property (IP) offices.
    • Korea and Japan are the leaders in robot intensity, which is measured as the number of robots used in a sector divided by the overall value created by that sector, giving a sense of the pace of automation relative to industry size. Robot intensity is rising in the Czech Republic, Hungary, Slovak Republic and Slovenia and in the BRICS—most notably in China, which is fast catching up to U.S. levels.
    • IoT, or machine-to-machine communication via internet-connected devices such as vehicles, sensors or home appliances, is growing fast. China had the most SIM cards in machines in 2017 at 228 million subscriptions, accounting for 44 percent of global M2M connections and three times the U.S. share. In terms of M2M cards per person, the United States is in the lead among G20 countries, but ranks sixth globally behind Sweden, New Zealand, Norway, the Netherlands and Finland.
    • The number of artificial intelligence technologies patented in the five top IP offices rose by 6 percent a year on average over 2010-2015, led by Japan. Japan, Korea and the United States. Together those countries accounted for over 62 percent of AI-related IP5 patent applications, down from 70 percent in 2000-2005, as filings rose from China and Chinese Taipei. EU countries contributed to 12 percent of the top AI inventions, down from 19 percent in the previous decade.
    • The United States has the biggest share of the world’s top 10 percent most-cited scientific publications, and China has overtaken the UK for second place after tripling its high-impact output in a decade. The U.S. share of top-cited research fell to 26 percent in 2016 from 38 percent in 2005, the UK slipped to 6 percent from 8 percent and China increased its share to 14 percent from 4 percent.

    — George V. Hulme