APPLICATIONS OF ARTIFICIAL INTELLIGENCE: PLATFORMS AND MODELLING TOOLS

The book begins by looking at the development of AI applications with platforms and modelling tools. Among the AI platforms, Microsoft Azure, Microsoft Cortana, Amazon AWS, Amazon Alexa, Bixby, Google Assistant and IBM Watson are described. In terms of modelling tools, Azure Machine Learning, Knime, SPSS Modeler, Rapid Miner and Orange are described. Other important programming tools are automatic code generation tools for creating software with intelligent behaviour such as Genexus, Mendix and Lobe, which are also described here.

In terms of modelling with neural networks, Python, Tensor Flow and R as a programming tool and IBM SPSS Modeler software as a visual tool for working with neural networks in Artificial Intelligence are taken into account. Fully solved working examples of automatic Analytics procedures and predefined neural network modules are presented using IBM SPSS Modeler. These procedures belong to Visual Analytics, as the tool is completely visual and does not require programming code.

This is followed by a discussion of technological convergence and its advantages and disadvantages. The connection between voice, sound and image technologies is studied and the most important electronic convergence systems are presented, including Blockchain, Internet of Things (IoT) and Cloud Computing. Security in technological convergence is also analysed. Finally, industrial and business automation models are studied. Corporate strategies, business models, asset and resource management and automation models are considered.