Читать книгу Machine Learning For Dummies - John Paul Mueller, John Mueller Paul, Luca Massaron - Страница 51

To survive, a technology must prove useful. In fact, it must prove more than useful; it must meet perceived needs in a manner that existing technologies don’t as well as build a base of adherents who provide a monetary reason to continue investing in the technology. For example, the Apple Lisa was an interesting and useful piece of technology that demonstrated the usefulness of the GUI to business users who had never seen one before. It solved the need to make computers friendly. However, it failed because it didn’t build a base of adherents. The computer simply failed to live up to the hype surrounding it (see https://www.inexhibit.com/case-studies/different-fate-apples-lisa-macintosh-design-matters/ for details). The next system that Apple built, the Macintosh, did live up to the hype a bit better — yet it built on the same technology that the Lisa used. The difference is that the Macintosh developed a considerable array of hard-core adherents.

Machine learning solves a considerable number of problems in a manner that other technologies would have a hard time copying. However, to become the must-have technology that everyone wants to invest in, machine learning must build that cadre of hard-core adherents. The bar chart at https://www.grandviewresearch.com/industry-analysis/machine-learning-market shows that machine learning is growing significantly, with services leading the way. The associated free downloadable report (you must fill in a request to get it) details just how much machine learning has grown in the past few years. The following sections discuss some of the ways in which machine learning is already affecting you personally and how this use will increase in the future — making machine learning a must-have technology.