But there is still a long journey

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To be covered, as machines are still unable to reproduce very simple skills of the human mind or carry out activities that people perform very easily. However, some projects are already achieving interesting advances: product handling systems that can differentiate different skus to handle them appropriately, systems that help locate products in complex portfolios with minimal errors, systems that establish cause and consequence relationships to increase probability of indicating precise treatment to cure unusual diseases, systems that understand videos and interpret events, systems that can simulate common sense, systems that interpret emotions, systems that understand people's intentions. Knowing this, companies' senior leadership needs to ensure that there are people on their teams learning about the topic and experimenting with ways that make use of these new technologies to solve the business challenges that their organizations face. Chapter 2: data.

The amount of data generated in the world today is dizzying. And the future promises more. The internet of things is expected to generate 73 zb and each human being will leave a daily footprint of 3.4 eb per day in 2025. And the more data, the  Japan Email List greater the need for computing power, which in turn opens up new possibilities for generating and managing data in an upward spiral. This would mean that fewer and fewer organizations would be able to explore and take advantage of this dimension of technological progress. But something with the potential to eliminate this privilege is about to happen. Several studies, based on the ability of human beings to learn from a few experiences, are emerging in order to make it possible to use more restricted databases to help with organizational performance, in situations such as, for example, personalization in the presentation of offers in e-commerce websites.



The idea is to be able to do more with less data. And with that, democratize access to this powerful dimension of information technology. Chapter 3: expertise. Increasingly, development will come from the interaction between machines and humans. Machines amplify the mental and physical capabilities of human beings while humans train and create parameters for the machines to act. And in relation to the training of machines by people, one dimension has been increasingly highlighted: machine teaching, that is, the transfer of knowledge from experts at different levels in organizations to machine learning systems. At the limit, human beings teach even without knowing that they are teaching, as systems emerge capable of “observing” people and transforming their “tacit” knowledge of which they have little or no awareness into “explicit” knowledge codified and rationalized for later machine perform tasks that previously could only be performed by people with experience.