As we look at the industry, of seeing big change coming with language model, AI, generative AI, and all that work coming, and we thought that it might be another opportunity to work with the Virginia Tech. With language models like Chat GPT, we rekindled our collaboration, and we are exploring this new research thrust and how language models can be used to enhance reader experience. I think it's been a great learning experience. They did a great job, and they came in and provided immediate help to the product launch. One of the challenges we faced was make sure that we prevent a prompt injection attack. How can we rethink of that problem from a very practical perspective, which is ultimately the goal of any research is to make it useful for a real world use case. That thinking, that thought process is something that I think I'm hoping I'm improving on. The learnings that we may find from, you know, all of the great work that the Virginia Tech students put into building "Climate Answers." Yes, maybe the next thing is for users, but we could similarly use that for a tool we're building for the newsroom. One of the nice things about this project is that it's a very practical problem based learning setup that we're providing for our students. Rather than just doing a research project here at the university, they now have the ability to be embedded within the Washington Post to work with their staff and colleagues to understand how AI and machine learning is being used right there in the company.