Federico II, quantum advantage achieved in artificial intelligence. This is what was demonstrated by the Federico II research team coordinated by Professor Giovanni Acampora of the Physics Department 'Ettore Pancini'.
Quantum computers will be able to “reason” faster than classical calculators. This is what was demonstrated by the research team from Federico II coordinated by Professor Giovanni Acampora, of the Department of Physics 'Ettore Pancini' of the University Federico II, who created a quantum algorithm capable of executing the so-called inferential engines, the main components of some artificial intelligence methodologies, using fewer computational resources than electronic calculators.
The study, conducted with PhD student Roberto Schiattarella and Dr. Autilia Vitiello, entitled “On the Implementation of Fuzzy Inference Engines on Quantum Computers”, was published in the prestigious journal IEEE Transactions on Fuzzy Systems.
In addition to the computational advantage, the algorithm offers a further advantage: it allows programming quantum computers using the linguistic approach typical of human reasoning, simplifying the interaction with these particularly complex tools to manage.
The result achieved by Acampora, Schiattarella and Vitiello could have important repercussions in the design of artificial intelligence methods of the future, which will have to have significant processing capacity and extreme programming simplicity to be able to manage the ever-increasing amount of data made available by the interconnection and interaction of different systems linked together by modern wired communication technologies such as fiber optics, and those for mobile devices such as 5G and 6G.
Inference engines are algorithms that simulate the ways in which the human mind draws logical conclusions through reasoning and are used in many artificial intelligence applications in various spheres of daily life such as medical diagnosis systems, industrial control systems, automotive, and automation and decision support systems in general. The inference engines on which the study conducted by Acampora, Schiattarella and Vitiello is based are those that use the so-called fuzzy linguistic rules. These rules implement a reasoning scheme capable of creating a link between the input and output variables of a system, using a linguistic approach, that is, using textual expressions typical of human thought. This is made possible by the use of fuzzy logic, a mathematical tool capable of modeling human reasoning and enabling calculations based on words and constructs of natural language. Although widely used in different types of systems, inference engines can suffer from a significant computational problem: the number of rules that model the behavior of a system can grow exponentially with the number of input variables of the system itself, making the inference engine inefficient in drawing logical conclusions. Consequently, there is a strong need to think of inferential computation methods that can evaluate the rules efficiently even as the number of input variables grows.
Quantum computers, computational tools that exploit principles of quantum mechanics such as superposition, entanglement and interference, may represent a possible solution to the aforementioned problem. In fact, these innovative computing tools enable massive parallelism in computation which, as demonstrated by Professor Acampora's group, offers the potential to achieve an exponential advantage in the execution of inference engines. This means that, even in the presence of large-scale systems, quantum inference engines can be executed efficiently, that is, with a shorter execution time than inference engines executed on classical electronic calculators.
The result achieved by Professor Acampora and his group comes after numerous international awards and prizes obtained for the results obtained in the research activities carried out in the area of quantum artificial intelligence. Among these awards, the 2019 Canada-Italy Innovation Award obtained by Professor Acampora and released by the Canadian Embassy in Italy, the 2021 Best Paper Award@Fuzz-IEEE obtained by Professor Acampora and Dr. Vitiello, the IEEE Computer Society Award on Emerging Technologies obtained by Professor Acampora and Dr. Vitiello, and the 2022 IEEE CIS Graduate Student Research Grant obtained by Roberto Schiattarella and which will allow him to test the quantum inference engine on the control systems of the particle accelerators at CERN in Geneva.
Article published on 5 October 2022 - 15:37
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