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) …
The UK, which spends more than £2bn on video surveillance each year, is to mark National Surveillance Camera Day on 20 June as part of the National Surveillance Camera Strategy. The aim of the national event is to raise awareness about surveillance cameras and to encourage debate about the use of surveillance cameras in modern society by highlighting how they are used in practice, why they are used and who is using them. The initiative by the Surveillance Camera Commissioner (SCC) and the Centre for Research into Information, Surveillance and Privacy (Crisp) is also aimed at starting a nationwide conversation about how camera technology is evolving, especially around automatic face recognition and artificial intelligence (AI). The organisers hope that the resultant public debate will help inform policy-makers and service providers regarding societally acceptable surveillance practices and legitimacy for surveillance camera systems that are delivered in line with society's needs. As part of the initiative, the SCC is encouraging surveillance camera control centres to throw their "doors open" so that the public can see how they operate.
One of the major hurdles companies face in transforming to a Digital Supply Chain is their inability to get data from customers and suppliers--or even from other departments in their own company. What is new is the idea of "trading data" to overcome that hurdle and use as a catalyst for Digital Supply Chain transformation. Companies are aggressively turning to artificial intelligence and machine learning (AI/ML) to gain a competitive advantage. But for that strategy to succeed, companies must develop algorithms that rely on AI/ML technology to run their business. And what is the life force behind algorithms?
To assist manufacturers in performing an automated visual inspection, Kitov.ai has developed a smart visual inspection technology for a broad range of production lines. Israel-based Kitov.ai has built an end-to-end, fully automated 3D inspection system powered by artificial intelligence and deep learning that enables manufacturers to produce quality products at a low cost rapidly. In an interview with CIO Applications, Hanan Gino, CEO of Kitov.ai, Give us an overview of Kitov.ai Kitov.ai was founded in late 2014 by CTO and Founder Dr. Yossi Rubner, as a spin-off of RTC Vision, a company that has been developing advanced computer vision algorithms for leading companies for over a decade.
Encoder Products Company (EPC) is a leading designer and world-wide manufacturer of motion sensing devices. EPC began operations in 1969, producing a line of custom encoders (the original Cube series) from a small, home-based shop. Today, EPC is the largest privately-held encoder manufacturer in North America, producing the most complete line of incremental and absolute rotary encoders in the industry. Meeting the diverse needs of a wide range of global customers, EPC's core philosophy is that each and every customer deserves quality products, superior customer service, and expert support. Adherence to these principals has enabled EPC to achieve its goal of maintaining long-lasting customer relationships.
In pop culture, the combination of business interests and artificial intelligence is something to be feared. It brings to mind Skynet, the malevolent neural network from the Terminator movies that goes to great lengths to destroy its human makers. The reality is different, though. We take advantage of it every time we check out new products recommended by Amazon.com, We have fun with it when we browse Netflix, which uses AI to predict what viewers might like to watch next.
Artificial Intelligence is benefiting to various industries including healthcare, education and manufacturing. But what is Artificial intelligence (AI)? In Layman language, a simulator of human intelligence, which makes the decision after analyzing various data utilizing a collection of different intelligent technologies including machine and deep learning, analytics and computer vision. The fourth industrial revolution is employing AI to enhance its overall efficiency. The technology is not only helping to reduce manufacturing cost as well as it is improving productivity and quality. Manufacturing is a capital-intensive process, and once a plant is a set-up, replacing, removing or renovating is exorbitantly expensive. New machines improve performance; reduce redundancies, while improving overall quality metrics. AI is proving an alternative route to achieve all this and at extremely competitive price points. Instead of now replacing machines, manufacturers are adding AI/ML tools to pre-inspect raw materials identify defects, perform quality evaluations, and a lot more.
Artificial Intelligence has an immense influence on various industrial or manufacturing sectors, together with aviation, manufacturing, technology, and others. Because of the features of Artificial Intelligence like machine learning and deep learning will generate higher productivity. Artificial intelligence becomes a long way in the past few years, connecting the gap between technical conversations and what are now practical possibilities, and nowhere are the possibilities more exciting than in the automotive industry. Between the designs of the cars, we currently drive and the process of manufacturing them, there is a lot of opportunities for Artificial Intelligence to develop, create efficiencies and make the process of auto-making and driving safer overall. But one manufacturer which is already seeing exciting changes from Artificial Intelligence in the automotive industry.
The Food and Drug Administration announced Tuesday that it is developing a framework for regulating artificial intelligence products used in medicine that continually adapt based on new data. The agency's outgoing commissioner, Scott Gottlieb, released a white paper that sets forth the broad outlines of the FDA's proposed approach to establishing greater oversight over this rapidly evolving segment of AI products. It is the most forceful step the FDA has taken to assert the need to regulate a category of artificial intelligence systems whose performance constantly changes based on exposure to new patients and data in clinical settings. These machine-learning systems present a particularly thorny problem for the FDA, because the agency is essentially trying to hit a moving target in regulating them. The white paper describes criteria the agency proposes to use to determine when medical products that rely on artificial intelligence will require FDA review before being commercialized.
In this May 22, 2019, photo, a customer waits for a coffee in front of a robot named b;eat after placing an order at a cafe in Seoul, South Korea. SEOUL, South Korea – Are robot baristas the future of South Korea's vibrant coffee culture? The company now has 45 robot-equipped outlets in shopping malls, company cafeterias, schools and an airport. Coffee is just one of many industries that could be transformed by automated services in this tech-forward nation, a notion both exciting and worrisome as jobs become scarcer. South Korean industries, including restaurants, convenience stores, supermarkets, banks and manufacturers, are relying increasingly on robots and other automation.
WHEN manufacturers think of artificial intelligence (AI), they think of its ability to produce insights from data. Most manufacturers are keen on using AI to analyze demand and factor in lags in the supply chain to optimize operations, but forget the heavy equipment they're using. According to a new whitepaper, McKinsey argues that companies with heavy assets can reap great dividends if their operators start using AI to review their workflows and make necessary alterations. "AI can deliver improvements without capital-intensive equipment upgrades and thus produce attractive returns quickly," it says. The consulting giant finds that despite the advances in technology, operators of heavy machinery still rely on judgment and intuition to manually monitor signals and adjust settings, troubleshoot and run tests, and perform other tasks that strain the limits of their human capacity.