Engineering & Mining Journal

JUL 2018

Engineering and Mining Journal - Whether the market is copper, gold, nickel, iron ore, lead/zinc, PGM, diamonds or other commodities, E&MJ takes the lead in projecting trends, following development and reporting on the most efficient operating pr

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Page 47 of 75

HEALTH & SAFETY 46 E&MJ • JULY 2018 actually contacts the physical world.) Working in tandem with Nvidia cloud technology, Jetson initially will power cameras mounted on Komatsu's con- struction equipment and enable 360-de- gree views to readily identify people and machines nearby to prevent collisions and other accidents. Future applications include high-reso- lution rendering and virtual simulations of mining sites along with automated control of machinery. Personnel tracking systems using RFID tags are already a familiar and ex- panding approach for maintaining up- to-the-minute location information for workers and equipment. The next step, as envisioned by Microsoft, for example, could use cloud computing, AI and video not only to provide location information, but also to keep track of employee train- ing and certifications and control their ac- cess to equipment and workspaces on a scope much wider than current practice. In a recent demonstration, Andrea Carl, Microsoft's director of commercial com- munications, showed how a system using its Azure cloud computing and Cognitive Services solutions could contribute to im- provements in workplace safety. Why is Artificial Intelligence Important? AI automates repetitive learning and discovery through data. But AI is different from hardware-driven, robotic automation. Instead of automating manual tasks, AI performs frequent, high-volume, computerized tasks reliably and without fatigue. For this type of automation, human inquiry is still essential to set up the system and ask the right questions. AI adds intelligence to existing products. In most cases, AI will not be sold as an individual application. Rather, products you already use will be improved with AI capabilities. Automation, conversation- al platforms, bots and smart machines can be combined with large amounts of data to improve many technologies in the workplace. AI adapts through progressive learning algorithms to let the data do the programming. AI finds structure and regularities in data so that the algorithm acquires a skill: The algorithm becomes a clas- sifier or a predicator. And the models adapt when given new data. Back propagation is an AI technique that allows the model to ad- just, through training and added data, when the first answer is not quite right. AI analyzes more and deeper data using neural networks. You need lots of data to train deep-learning models because they learn directly from the data. The more data you can feed them, the more accurate they become. AI gets the most out of data. When algorithms are self-learning, the data itself can become intellectual property. The answers are in the data, you just have to apply AI to get them out. Since the role of the data is now more important than ever before, it can create a competitive advantage. If you have the best data in a competitive industry, even if everyone is applying similar techniques, the best data will win. Source: Artificial Intelligence: What it Is and How it Matters, www.

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