Tag: machine learning

An intelligent machine is a type of device that integrates both machine-to-machine (M2M) technology and cognitive computing, artificial intelligence, or machine learning, for example. This allows you to solve problems, or even make decisions that result in concrete actions. That is the closest thing to the human reasoning capacity, with clear implications for business and society in general. In this category, we can include both robots and autonomous cars or cognitive computing systems, designed to perform tasks without human intervention; assets that are different in their form and functionality, but that can be considered disruptive elements because they represent a break with everything that has gone before. In the business world, they have the potential to increase the competitive advantage of companies, their margins, and profits, introducing more efficient production processes, even substituting means and human resources, or radically transforming the nature of work itself. Disruption, as opposed to evolution, although some continue to see previous references in other technological stages and look for its roots in the origins of mechanization or the first Industrial Revolution, the truth is that the irruption of the Internet, the cloud and IoT sensors, for example, can be considered elements that change many of the technological paradigms of the past, to propose something radically new. With business intelligence (BI) systems and advanced analytics, the way was opened for running algorithms to interpret and act on data, identifying patterns that could help predict future corporate events. This analytical ability, in turn, led to machine and deep learning, where computers themselves learned from additional data sets. More specifically, they use their new knowledge to adapt and adjust their performance. This is where a good part of the key to the irruption of intelligent machines is found, in those algorithms that are developed so that systems "self-learn and", improve with time and experience, even to the point of being able to form neural networks, voice recognition systems or natural language processing. One of the first visible examples of intelligent machines was Deep Blue, a chess-playing computer developed by IBM, which gained popularity when it defeated world chess champion, Garry Kasparov, in 1996. Watson, another IBM invention, also drew attention for his skill in the game, after winning the television show Jeopardy, in 2011, and today he applies himself to data analytics, especially in the field of health, where he helps to discover new drugs, improve the selection of treatments or in welfare programs. The future of the market Gartner predicts that intelligent machines will begin to be widely adopted in 2021 and will continue to be the most disruptive technology of the new decade about to begin. Researchers and technology leaders also agree that they will profoundly change the way work gets done and how value is created. And, in the labor market, analysts predict that, within twenty years, 4 out of 10 jobs will be affected by robotization and the automation of certain tasks However, there is no agreement on how they will affect our current lives, jobs, and relationships. Some agree with the theoretical physicist Stephen Hawking, who at the time assured that they embodied a great threat to humanity. While they don't express the same doom potential, others also worry about what they will entail, in terms of replacing certain jobs in industry, government, and society. In any case, it seems clear that intelligent machines are digital disruptors, with very positive potential effects for society and companies, and that their competitive advantages are increasingly obvious and decisive for the business world, in many sectors of activity, and for the advancement of modern science and medicine.