Business Trends in Practice. Бернард Марр
Чтение книги онлайн.

Читать онлайн книгу Business Trends in Practice - Бернард Марр страница 15

СКАЧАТЬ flowing into those lakes. And, as I've already mentioned, we have futuristic advances such as DNA data storage to look forward to.

      For businesses, the obvious advantage of all this data is that it can be harnessed to design better products and services, improve business processes, enhance decision-making, and even create new revenue sources (take a company like John Deere as an example, which has been able to package up the data collected from its farming machinery and sell it back to farmers).

      Another risk, of course, is that companies simply drown in all this data. Thus it's essential that companies develop smarter approaches to turning data into insights – and, in turn, ensure that those data-driven insights can be translated into action. Businesses must work to raise data literacy across the organization, and this means all decision makers in the organization must have access to the data they need, understand the value of that data, and have a basic ability to use that data. As such, we can expect to see more and more organizations implementing data literacy programs.

      The fact that our world is increasingly driven by data has brought about incredible leaps in artificial intelligence (AI). Data is a core enabler for AI, in the sense that the more data intelligent machines have to learn from, the better they become at spotting patterns, extracting insights, and even predicting what may happen next.

      Crucially, AI gives intelligent machines the ability to learn from data and make decisions, sometimes without human intervention. This is where the terms machine learning and deep learning come from. If we think of AI as the umbrella term, machine learning and deep learning are cutting-edge disciplines of AI that both involve getting machines to learn in the same way as humans do (i.e., by interpreting the world around us, sorting through information and learning from our successes and failures). Deep learning is the more advanced of the two because you can simply feed a deep learning system data and let it work out for itself how to find patterns.

      One thing that hasn't yet been achieved is the idea of general AI, or the hypothetical ability of machines to understand the world as well as humans and learn any task. This is the AI of sci-fi movies and books. For now, AIs tend to carry out specific, narrow tasks. But just because general AI hasn't been achieved yet doesn't mean it's impossible. General AI is certainly the goal of several AI companies, and I suspect that if we put all the existing AIs together, they would be able not only to match what humans can do, but even exceed it.

      As you can probably guess, advances in AI have fueled new developments in other technologies, including extended reality (XR). XR is an umbrella term representing the spectrum of immersive technologies we have today – virtual reality, augmented reality, and mixed reality – as well as those immersive technologies that are yet to be created. Currently, virtual reality (VR) offers the most immersive experience, by effectively blocking out the real world around the user and immersing them in a computer-simulated environment (usually with the aid of a VR headset). Augmented reality (AR), on the other hand, blends the digital and real worlds by overlaying digital objects or information onto the real world (often via a smartphone app or filter). Meanwhile, mixed reality (MR) sits somewhere between the two, creating an experience where the digital and real worlds can interact with each other – for example, letting a user manipulate virtual elements as if they were real.

      XR is primarily known for immersive gaming, but it is finding very real, very practical uses across a wide range of industries – often being used to create more immersive, personalized experiences for customers. House buyers, for example, can go on immersive virtual house tours. Customers can try out products virtually (for example, by overlaying a new style of glasses over their face or digitally placing a new sofa in their living room). And sports fans can immerse themselves in the stadium experience from the comfort of their home. The list of exciting new XR applications goes on. But as well as giving organizations new ways to engage with customers and СКАЧАТЬ