The concept of Artificial Intelligence (AI) is becoming increasingly pervasive in all technology-intensive sectors. The development of systems endowed with autonomous learning capabilities and with characteristics of “decision-making” autonomy in operating principles, inspired by human behavior patterns, is finding increasingly broad areas of application, not only in industrial and frontier contexts, but also in consumer applications involving large segments of the population. Thanks to the maturation of artificial intelligence techniques, there are more and more solutions developed by CRS4 that leverage these as an innovation tool for an increasingly wide range of application domains. Inspired by the new paradigm in AI where a shift from the traditional model-centric approach to a data-centric one is promoted, in this project the development of a technology platform is proposed where data engineering and management is the axis around which the development and continuous improvement of AI-based automation and decision support systems takes place.
The goals of the institutional project Artificial Intelligence (funded by the contribution under art. 9 L.R. 20/2015) aim to innovate through research and development on both the technological and application fronts. On the technological side, it aims to develop dedicated tools and interfaces so that any type of user (from domain experts to data scientists) can continuously contribute to the different phases of the production cycle: from data acquisition, collection, and annotation, to the transformation of these into predictive model capabilities and performance, as well as the archiving and/or sharing of datasets. From the application point of view, the project aims to propose more effective solutions to high-impact problems in areas such as medical diagnostics, applications aimed at people with sensory disabilities, precision agriculture, the study and interpretation of cultural heritage, tourism, and land enhancement, online platforms for education, autonomous systems and social interactions, digital twins, and the metaverse. Areas where the availability of quality datasets is particularly critical and where the proposed technology platform can have an immediate impact.
