This talk explores the transformative role of machine learning (ML) and artificial intelligence (AI) in advancing modern science and technology, as confirmed by the Nobel Prize in Physics 2024.
During my presentation, I will give a brief introduction to AI and ML, highlighting how these technologies may benefit innovative, interdisciplinary, and application-oriented research, with focus on gas sensor technologies. I will provide numbers to show the economic profits around the massive market adoption of such technologies, although it is extremely fragmented due to lack of standardization, unsatisfactory data reliability, and the need to find innovative solutions to improve sensor performance and overcome existing limitations. To facilitate understanding and support my arguments, I will suggest practical examples and case studies on the promising use of ML-enhanced gas sensor technologies in different real-world applications, such as early cancer diagnostics, forensics, food quality, and cultural heritage preservation. I will share the challenges encountered, the solutions proposed, and the results achieved. I will conclude with reflections on future perspectives and next steps.