The Information and Communications Technology is Driving Artificial Intelligence to Leverage Refined Knowledge for the World Sustainable Development - Part 2 -

The paper approaches the analysis of artificial intelligence (AI) development, in the context of Information and Communications Technologies (ICT) exponential evolution as main driving factor of the progress of the Information society (IS) toward Knowledge Based Society (KBS). The actual context of the exponential pace of ICT development, which is still mainly generated by Moore s Law, is analysed by considering scientific, technical, economic and social implications, which led to the reasonable conclusion that any result are inherently partial and time sensitive, due to complexity and fast pace of these evolutions. The base of the advances of technology, which support this pace and Moore s Law, is presented by some relevant actual examples. The 10nm technology is the highest peak this race reached, but the fight for the next 7nm target was dramatically uncertain until Extreme Ultraviolet (EUV) lithography became a practical reality last year, reason for which it is shortly detailed, along with main trends of implementations by GlobalFoundries, Taiwan Semiconductor Manufacturing Co. (TSMC) and Intel, i.e. the World leaders. The revolutionary technology of the carbon-nanotube field-effect transistors, which has the amazing target to improve both the energy efficiency and speed of computers by a factor of 1,000 and the challenge of continuing Moore's Law), is also presented. In the second section, the paper is focusing on some strategies and methods to approach the target, context, models or algorithms for developing AI, where the complex relationship between AI and HI is essential, as the huge diversity of ICT networks, equipments and software/applications could not be created and used without the AI-HI symbiosis, i.e. working in a mutual dependence. One important conclusion is that the efficiency of AI-HI applications is strongly depending on the human expertise/education and responsibility, first by properly designing AI and then using AI to extract information/knowledge from data all over the World, aiming the humankind stable progress in every activity field and Earth ecosystem. Because AI most prolific ways to leverage refined knowledge include machine and deep learning, in order to optimize the development and use of AI for providing sustainable progress everywhere, a more detailed picture of approaching its main techniques and processes is necessary. This way, the main features and differences of machine and deep learning are presented, including both supervised machine learning and unsupervised machine learning approaches. Along with these, the emergent cognitive AI is intended to extend human cognition, as the main process of refining knowledge, essential for IS toward KBS. As a main consequence, unlock more economic value and leveraging innovations are among the most important goals of ICT development for IS/KBS and became naturally priority fields for the potential of AI to analyse simple industrial or more complicated economical data flows in order to extract information and leverage refining knowledge. The paper also analyzes one of the challenges for ICT/AI amazing targets/development, beyond the feasibility, as the sustainability, i.e. conluding that we have to carefully watch ICT/AI trends in order to foresee and evaluate the negative consequences before it is not too late, because the chances to foresee all the consequences of the exponential ICT/AI development complex and complicate processes are lowering as their speed is increasing, as it is the actual case of digital age of IS/KBS. An important conclusion of the paper is that, although we have deeply entered the AI development mechanisms, this is a never ending road with complex and interdependent obstacles, considering the iceberg of ICT and the elusive Morgan le Fay (Morgana mirage) evolution of the performance/applications targets, which are recalling sometimes the old issue of science fiction versus reality. This conclusion is also confirmed by a typical example: the fact that we see every day that, in spite of the crucial advances, in the last decades, of the ICT/AI power impact on weather forecast services applications, the recent aggressive evolutions of the weather, clearly induced by the climate changes, are more and more violent and more difficult to forecast. The final conclusion is that, in order to fully optimize the intelligent ICT development, including AI, we have to further analyse how wisdom could influence our power and why this development has to teach us to deeply think.