If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Your message has been sent. There was an error emailing this page. Vacuuming is one of the most loathed household chores. While it doesn't come with the ick factor of cleaning the toilet or the tedium of dusting, pushing and dragging a noisy, cumbersome vacuum is its own kind of torture. No wonder most of us only break it out the bare-minimum-recommended once a week.
If an automated car had to choose between crashing into a barrier, killing its three female passengers, or running over one child in the street -- which call should it make? When three U.S.-based researchers started thinking about the future of self-driving cars, they wondered how these vehicles should make the tough ethical decisions that humans usually make instinctively. The idea prompted Jean-François Bonnefon, Azim Shariff, and Iyad Rahwan to design an online quiz called The Moral Machine. Would you run over a man or a woman? By 2069, autonomous vehicles could be the greatest disruptor to transport since the Model T Ford was launched in Detroit in 1908.
Manufacturing companies can feel product cycles tightening around them. In our fast-paced world, consumers are tossing out devices with rapid regularity, calling for the newest gadget, the hottest feature, the most instantaneous service. But how will manufacturing companies keep pace with this growing demand while continuing to produce increasingly complex goods? Smart Manufacturing, Industry 4.0, the Digital Enterprise, Factory of the Future or whatever you choose to call it, is revolutionizing the industry as we know it. Unlike the first industrial revolution of steam and iron (remember when hot water was a nifty tool?), this industrial revolution is splicing computing power and machine technologies to fuel a better, more efficient workplace that harnesses the abilities of modern informational, operational and communication technologies.
Machine learning (ML) and artificial intelligence (AI) continue to capture media attention and business investments. IDC estimates machine learning and AI spending to increase from $19.1 billion in 2018 to $52.2 billion by 2021. With billions of dollars invested in machine learning and AI, it's no surprise that tech giants Google, Microsoft and Amazon are investing billions in cloud infrastructure and development tools to accelerate the delivery of custom machine learning applications. Case in point, machine learning was the third-highest category for the number of patents granted between 2013 and 2017. So, what exactly is machine learning?
The reputation and bottom line of a company can be adversely affected if defective products are released. If a defect is not detected, and the flawed product is not removed early in the production process, the damage can run in the hundreds of dollars per unit. To mitigate this, many manufacturers install cameras to monitor their products as they move along the production line. But the data may not always be useful. For example, cameras alone often struggle with identifying defects at high volume of images moving at high speed.
The rapid adoption of Industry 4.0 technologies leaves manufacturers with a choice: accelerate with the market or be left behind. According to a 2019 Global Market Insights, Inc. report, the market for artificial intelligence in manufacturing will grow to $16 billion by 2025. Factors driving the adoption of Industry 4.0, the general name given to the deployment of cyber-physical systems, Internet-of-Things technologies and cognitive computing in the manufacturing environment, include: Achieving these goals is supported by two main principles: interconnection and information transparency. Interconnection refers to the ability of machines, devices, sensors and people to connect and communicate with each other. Information transparency provides operators with large amounts of useful information needed to make appropriate decisions.
As Industry 4.0 sweeps across the supply chain, it's clear it will have a significant impact on everyone involved. Still, the question is how so? As you'd expect from a name such as Industry 4.0, profound and revolutionary changes are coming to various industries, including manufacturing, development, and the modern supply chain. Industry 3.0 was the widespread adoption and rollout of automated technologies. Toward the end of this era, better and more efficient automation systems were introduced and now, players are using modern smart devices and data to improve and optimize the systems.
Thirty-two hours after an Ethiopian Airlines 737 Max crashed on takeoff from Addis Ababa, killing all 157 aboard, shares of the plane's manufacturer, Boeing, traced a similar trajectory, dropping 12 percent at the opening bell of the New York Stock Exchange and never fully recovering. While the cause of the Ethiopian incident hasn't yet been established, it makes sense that investors would lose confidence in Boeing: The crash came just five months after another involving a 737 Max in Indonesia, Lion Air flight 610, and the dual disasters have spooked airlines and the traveling public. Erring on the side of caution, China and Indonesia have grounded the 737 Max, and 22 individual carriers have done so as well, including Ethiopian and Cayman Airways. The 737 Max first flew just two years ago, and some 350 are now in service. For such a new type of aircraft to suffer two fatal crashes is extraordinarily unusual, and bad.
Mr. Douma said prosecutors' announcement Tuesday tracked with how typically people, and not car manufacturers, are held responsible for crimes they commit behind the wheel. But, as autonomous vehicles become more sophisticated, he said, such cases raise questions about that way of thinking. "Is this driver, or was this driver, behaving in any way different than what most drivers are going to be behaving like when the car is doing this much driving?" he said. "It's a very conventional way of thinking to say we can expect and we should expect people to sit and monitor technology that is otherwise doing all the decision-making." The Yavapai County Attorney's Office did its review at the request of the Maricopa County Attorney's Office, which had a potential conflict of interest in the case because of an earlier partnership with Uber in a safety campaign.
The Industry 4.0 market is poised to grow significantly in the coming years. The increasing adoption of the IoT in the digital transformation of manufacturing and related industries, the rise of industrial robotics and the proportionally higher spend in the Industrial Internet of Things are just some contributing factors. While we are still in the early days of Industry 4.0 and challenges remain on many fronts such as the integration of IT and OT, data capabilities, implementation challenges, guidelines and strategic capacities, skills, culture, standards and the maturity/readiness levels on the path from sheer optimization/automation to real transformation, Industry 4.0 is also driven by myriad challenges in the supply chain and customer expectations. In an ongoing quest to deliver the value of Industry 4.0, it is certainly also boosted by national and supra-national pushes in a changing geopolitical industrial ecosystem, further driven by some of the larger players and alliances in the industry. It's interesting to take a look at the key evolutions, drivers and areas of spending in the digital transformation of manufacturing, which Industry 4.0 ultimately is.