Ethics and public-private collaborations were two central elements discussed, as a way to make progress on the possibilities offered by artificial intelligence for industries such as healthcare, cybersecurity, industrial robotics, and smart cities, among others. This was the main theme of the second edition of the event known as AIHUB-Industry Connection (Conexión AIHUB-Industria in Spanish), a gathering organized by Spain’s Advanced Scientific Research Council (CSIC). Its aim is to bring together companies and CSIC researchers to discuss, promote, and solidify public-private collaborations on artificial intelligence research, design, and innovation (R&D+i).

With more than 80 attendees, AIHUB-Industry Connection 2023 provided a space for researchers and companies to develop and discuss opportunities and possibilities for collaborations between science and industry. A total of 20 presentations were given during the event, to showcase successful case studies involving collaboration between CSIC research centers and companies, such as the AgrarIA project.

Miguel Hormigo, GMV’s Manager for Industry, gave a presentation on some of the use cases now being investigated as part of that project. These included applications focused on the food and agricultural industry, with the aim of making it more technological, innovative, and sustainable, while increasing commitments to energy efficiency and carbon footprint reduction. He also explained some of the activities that GMV is now performing in collaboration with its partners, such as using satellite images to calculate agricultural capacities and applying quantum computing and image management to predict crop yields.

Also as part of the AgrarIA project, GMV and the CSIC are developing a pilot test case that will use quantum artificial intelligence and quantum machine learning (QML) to predict agricultural crop performance, by processing satellite images and applying a calculated predictive indicator. To carry out this proof of concept, a set of pre‑processed public satellite images will be used in combination with a QML-based indicator, with subsequent assessment and interpretation of the results. The prediction model will also be expanded by incorporating other data sets, such as climate information, multi-spectral imaging, risk data, etc.

AgrarIA now represents a collaboration among 24 entities, including large companies, SMEs, and research centers, all with the common interest of applying artificial intelligence to the agricultural value chain, as a way of strengthening the productivity of the Spanish food and agriculture industry. The project is funded by Spain’s Ministry of Economic Affairs and Digital Transformation, through the R&D Missions in Artificial Intelligence Program of the State Secretariat for Digitalization and Artificial Intelligence (SEDIA) (file no. MIA.2021.M01.0004), using funds from the country’s Recovery, Resilience, and Transformation Plan.