Information and Communications Technology new paradigm of probabilistic computing could inspire our thinking through a future World of uncertainty -Part 3-
Romanian Distribution Committee Magazine, 2021, vol. 11, issue 4, 14-26
The paper analyses some aspects regarding the evolution and implications of the Information and Communications Technology (ICT) probabilistic computing paradigm. When the data uncertainty level is high, as the consequences of COVID-19 19 pandemic, the ICT support is more than useful. For evaluating the potential of ICT to face this challenge, first we have considered the actual and emerging ICT advances that could provide real instruments and associated results to approach the diversity of problems with high uncertainty. ICT trends are among the complex evolutions of the associated technologies and concepts that continuously bring innovations aiming the performance, efficacy and efficiency improvements for the ICT services, products and applications that support Information Society (IS) on the way towards the Knowledge Based Society (KBS). Probabilistic computing (PC) is the actual new paradigm which is implemented by the ICT industry leaders, in order to support the most performant advances of ICT, where artificial intelligence (AI) is first pointed, but also linked with Bigdata or other ICT advances, like quantum computing (QC). The link between these advances is given by the ICT struggle to continue Moore Law, but PC is in the same time an emerging trend to improve AI toward human brain unreached features, like using fewer data (than machines) in order to generalize and decide. To reach such purposes, ICT innovations are made in both hardware and software areas, but also in new models and algorithms, more and more inspired from human brain, as the paper presents by analysing some relevant examples, including PC, QC and biological substrates for computation (cellular computing). The analysis revealed the role of “learning” in the innovation process, as the actual aim of AI/PC is to achieve the human brain ability to learn and re-create, including probabilistic programming, which is in the stage of providing the ability to self-develop and create new programs without human intervention. The analysis includes some elements which are linking the two emergent and unconventional computation concepts/technologies, i.e. probabilistic computing and quantum computing. Still, it is important to analyze such advanced instruments from all relevant implications, because we have to admit that in the more and more sophisticated world of soft/ICT, the logical covering of all scenarios is still necessary, but in the same time more difficult to achieve. All these challenges express the difficulty and complexity of innovation processes ICT/AI have to face toward further performance improvements, but also the high expectations from PC, just due to this context. The paper stressed the inherent care that should be considered for a sustainable progress of ICT/IS/KBS, including the necessary monitoring of all consequences (benefic or not) that could appear at planetary scale from the proliferation of using their services and products everywhere and everytime. Here climate changes, Earth resource fading or social contrasts, affecting Earth ecosystem and humankind life/evolution are crucial problems that should be considered. In this context, the learned lessons of ICT on the way of implementing the new paradigm of PC could bring benefic support also for people’s everyday life, when facing the uncertainities of World evolution/challenges. Our point of view and the paper focus is that the essence of those evolutions of the context factors is the fact that one of the main mechanisms that lead to complexity and difficulty to optimize the progress solutions is the increasing level of uncertainty that characterizes associated data of the analyzed processes to be optimized at planetary level, but at lower (individual) levels also. This way we agreed that some approaches of the models and technologies, used by ICT to implement the new paradigm of Probabilistic Computing (PC) could bring benefic support and learned lessons also for people’s everyday life, when everyone is facing the uncertainities and decision challenges in the general context of World evolution or of their own life context. The chances for maximizing the veracity of estimating the processes evolutions are given by trying to keep searching for the relevant data/information/knowledge, integrating the events results step by step and this way counting the average positive ones, i.e in a manner that is very close to Bayesian approach which forms the PC main premise. Starting from one of the remarkable PC basic models, >, our opinion is that this important approach is in fact one of the pillars humankind could learn from ICT (but not exclusively from it), when facing the World uncertainties, everyday and everywhere on Earth and beyond. It is clear that such apparent paradoxical approach must be discussed for every application area, where this ideea from PC/ICT should be applied with the appropriate solutions (if they are identifyed!), in order to find the approaches and algorithms that provide reliable constructions from probabilistic parts or at least lead to safer ensemble (by compensating the expected points of failure!), instead of simple using the probabilistic (not very safe) parts. This basic PC model could be benefic for understanding the suggested approach/method which then should be applied from case to case, either in simple problems of decision or in probabilistic programming applications, but always innovating something in the case model, i.e. using our imagination to estimate and compensate the probable risk of fealure and finally increasing the success probability. As a main conclusion, we just have to imagine how humankind could evoluate from the actual trends of using everyday ICT advances, including probabilistic computing/ programming, considering also the emergent changes in business models and jobs transformations AI/ICT have already started to produce, but eventually using the above ICT lessons to better face the World uncertainties.
Keywords: Probabilistic computing paradigm; Quantum computing; Probabilistic bits; Cellular computing; Bayesian programs; Probabilistic transistors; Probabilistic programming; Machine learning (search for similar items in EconPapers)
JEL-codes: L63 L86 M15 O31 O33 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:rdc:journl:v:11:y:2021:i:4:p:14-26
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