A version of this article was published in TIME's newsletter Into the Metaverse. You can find past issues of the newsletter here. There are two versions of a BMW factory in the medieval town of Regensburg, Germany. One is a physical plant that cranks out hundreds of thousands of cars a year. The other is a virtual 3-D replica, accessed by screen or VR headset, in which every surface and every bit of machinery looks exactly the same as in real life.

In recent years, many manufacturers have turned to emerging technologies like Augmented Reality (AR) or Artificial Intelligence (AI) to solve challenges such as the imminent skills gap or the need to improve productivity and quality. What's mostly overlooked though are the opportunities these technologies provide to connect and augment manufacturing workers to create sustainable value throughout the organization. Leveraging AR and AI in a holistic manner allows manufacturing organizations to augment their frontline workforce with interactive and personalized instructions while also capturing human-centric activities that provide new insights into improving productivity, quality, and training. Building these solutions on a dependable cloud infrastructure like Microsoft Azure means building on a foundation that provides a rich set of built-in connectivity and security features, which enable reliable and secure bidirectional communication. In this webinar, you'll learn how you can leverage the synergies between Augmentir and Microsoft to successfully move your manufacturing business to the digital world and: Russ Fadel is a serial entrepreneur and the CEO and Co-Founder of Augmentir.

To thrive in today's global markets, manufacturers need to optimize everything under their command -- from supply chain, materials and order management to engineering design, manufacturing engineering, shop floor operations, order fulfillment, logistics and services. With these objectives in mind, manufacturers are reinventing their world with technologies that connect products, smart factories and supply chains in new ways. This transformation is fueled in part by massive amounts of data and the use of artificial intelligence across the manufacturing environment. As is the case in many industries, big data now goes hand-in-hand with AI for manufacturers. Modern manufacturers are producing enormous volumes of data, thanks to a steep drop in sensor costs that has allowed data collection at every stage of production, and now they need AI to make use of it all.

August 22, 2018 Written by: Dr. Jongwoon Hwang, Group Leader, KIST Europe and Marco Hüster, Business Lead AI Implementation, KIST Europe Artificial intelligence (AI) is no longer just a field for academic researchers; machine learning and deep learning are becoming mainstream technologies that any organization can harness. This could have dramatic implications for many industries, including manufacturing. The impact of AI on manufacturing is likely to usher in a whole new era of industrial development. The first three industrial revolutions were triggered by the introduction of mechanical, electrical and digital technologies, respectively. Now, AI will be the driver of a fourth revolution known as "Industry 4.0."

The role of machine learning (ML) and artificial intelligence (AI) in our professional world continues to grow due to the benefits that they offer. These technologies have the ability to digitize operations and streamline work processes in order to reduce costs and boost a company's ROI. This is especially true in the manufacturing world, where ML and AI are playing a role as the demand for customized products continues to increase. A new AI report from Infosys discovered that in the manufacturing industry, machine learning is higher by 79%, while the use of cognitive AI-led processes is up by 61%. Additionally, 66% of manufacturing companies want to automate tasks to increase productivity and 61% want to use it to minimize errors.

Call it Industrie 4.0 as the Germans, Smart Manufacturing as the Americans or Smart Factory as the Koreans, the manufacturing industry is witnessing a technological overhaul that is propelled by the power of data and analytics. Given that the manufacturing involves complex production activities, it is leveraging greater digitization, the adoption of connected systems, and implementation of sensors in various manufacturing processes to improve the production accuracy and quality of products. With the help of the huge volumes of data that these systems generate, the manufacturing sector is using machine learning techniques and big data analytics to develop predictive statistical models that can help them make smarter decisions, improve operational processes and increase profitability. But what essentially is Machine Learning and is it any different from big data analytics? By definition, Machine Learning is a method of data analysis that provides computers the ability to learn without explicit programming.