Artificial Intelligence

When intelligent algorithms are applied to research questions, a world of possibilities starts to emerge. Inspiring emotions and ideas in society, Artificial Intelligence (AI) applications hold a lot of promise in academic research too. Innovative technologies like foundational models, generative AI or neurosymbolic systems are developing quickly. AI is already automating labour-intensive tasks, even those beyond the reach of human capabilities alone. Convenience, scale and efficiency emerge as some of the key benefits. 

In the forthcoming boom in applications, we see the opportunity to apply AI to domain research – especially as smart cities and smart environments as well as computer models in many research domains such as climate or chemistry are being augmented or replaced with AI. 

Working with these technologies, the eScience Center focuses on making AI explainable and data ‘AI ready’. We want researchers to utilise algorithms that are data-efficient so that they need far fewer labelled data to train AI systems. 

We’re ready for an AI-enhanced future. Are you?

• Learn more about how the eScience Center worked with AI in our mcfly software to automatically find neural network configurations for deep learning on time series.
• An example of applying AI for fundamental chemistry research is the Protein Detective project.
• To learn more about our work on Explainable AI for scientists, read about our DIANNA project/software.