Dr. Sasha Rubel:

We see AI and cybersecurity as one of the major conversations happening in policy spaces. We see many promising uses of AI to identify and stop cyberattacks. One of the most common use cases of generative AI is to combat cyberattacks, but also to combat fraud in the financial services. These are two early adopters of generative AI that we witnessed across industry verticals. I am happy to share a couple of use cases, particularly, for example, NASDAQ, which is using our services to identify and mitigate the risk of market manipulation. We see that as a promising use case.

On the protection of data and AI, privacy-enhancing technology is another area that we have invested much in, as an example. One of the biggest concerns that we hear from customers is about what is happening to their data, where it is stored, whether it is secure, and if it is being used to train and improve these different models. This is at the top of many customers' minds, in addition to responsibility. We worked, for example, with the University of Padua, to develop a privacy-enhancing technology that allows it to use generative AI for personalised learning. We see this as the future of the next iterations of generative AI and foundation models. It embeds privacy by design in the ways in which these models are developed and deployed.

The last question was about democratising AI. This is in our DNA from the beginning of the establishment of Amazon Web Services. We are convinced that, through this approach of customer choice, confidentiality and control over costs, more and more small and medium enterprises will have access to this technology. On the idea of being tied in, I am happy to revert to the Deputy with more information, particularly in light of the European Data Act, about how we ensure interoperability of our services to make sure that customers preserve that choice.