So good afternoon, everyone. Thank you for between now and the close. So it's the exciting part because it's my honor to give out the awards for the poster sessions earlier today. So we appreciate your time. And I believe I'm going to click and it should tell me. Okay, so there they are. The first one is the networking competition. And its first place is Eli Brignac. Are they here? Oh, I've got an award for you. Come on. Sorry, I didn't organize that very well, did I? Come this way, okay? So Eli, here is your award. Second place is Heilong Zhao. She had to go back to work. Well, then I will accept it on her behalf. And the third one is Uha Imandi. Congratulations to you all. Congratulations. So this is the poster award winners, and you will receive an e-mail from Lynette, correct? with your award, Ni-Otaki-Otou. You come on up, yeah, we'll take a picture with you all. And Logan Haley and Zach Davis. So congratulations on your award. We'll take a picture. I just want to say congratulations to all of you and the hard work you put in for today, and we appreciate as being offered to support this through the Delaware EPSCORE program. And if you don't know what that is, it's the established program to stimulate competitive research. We're here to build the research infrastructure and the ecosystem. So congratulations to all of the winners. So we don't have an award per se, but there's one more person that we have to extend some heartfelt thanks to who has sort of kept the glue completely, you know, infallible, I guess, despite all of the things that have thrown wrenches into the works. So Lynette Carney, would you stand up? And we have a little something to thank you. Come on up here. Yeah. So, you know, Lynette has been sort of the person with the, I guess, the most, the best focus in making sure that everything is set up, that everything goes off without a hitch. The one thing that she could not do was control the weather. but she was able to help coordinate all of the changes that needed to happen as a result of the weather and so thank you so much for all your hard work I need to jump down and get my phone so just a few closing remarks it is the end of the day I know that many of you probably felt like there's been a fire hose of information all day I hope that you've enjoyed this as much as I have I have a few comments Some things that sort of I've gleaned throughout the day. I learned a lot today. And I think that despite my sort of doomsday question earlier today about AI taking over everything and killing a thaw, I'm a lot more optimistic now, actually. So some things that I've learned. So one, being an academic, a researcher at university, and also being connected to many people who are programmers, who are research software engineers. And many folks are concerned that AI is sort of usurping their value, putting their jobs in danger. One of the things that I heard today is that we really don't need to sort of stay ahead of AI. In other words, we don't need to remain, we don't, we shouldn't have the expectation that any one person is going to be better than an AI system in any one, you know, skill or technique. So we don't have to stay on the cutting edge of everything, right? But we should try to keep up with what's most relevant and helpful in our own research, and that's what's going to make each human much better than an AI system, okay? Another thing to acknowledge is that everybody pretty much, well, maybe not everybody, but almost everybody is using AI, right? And perhaps they don't even know it, but they're using AI. And those that are using AI smartly are achieving incredible improvements in efficiency and productivity as a result of the way in which they're using AI. So if you haven't already embraced that idea, I challenge you to do so, right? Because it can help you reach a next level of productivity or efficiency or accomplishment that you wouldn't have gotten without that little extra boost. The third thing is, and this comes largely out of Eric's talk, I think what's really clear is that AI is likely to make many aspects of life better for humankind. You know, Eric's work in particular, the idea that when I get old, right, and if I'm going to have a robot that's going to do stuff for me, goodness, that's going to save my marriage long term, right? so you know the bottom line there is you can imagine that the the amazing things that have happened in the past 10 20 years and what's different now I mean think about it 20 years ago there was no iPhone right there was no smartphone what's going to happen now 20 years from now we're going to look back and say oh we didn't have any actual C3PO's in our house but maybe they become ubiquitous so I'm looking forward to seeing what happens and that leads me to my next point and this was I think made pretty clear and it's not something it's I think it's something that we've got a handle on and something that I think will continue to have a handle on and that is that humans need to make sure that AI has appropriate limits appropriate guardrails In other words, don't use AI to do anything that's particularly risky. So is it likely that we're going to have Skynet run our military? No. So no, you don't have to worry about all sorts in the air coming to kill you years from now. That's very unlikely to happen, I think, is the takeaway there. And then lastly, another thing that I want to point out, And this really is one of the things that I learned from our small table discussions is that UD and other universities like UD, you know, we're on the cutting edge of next generation advancements, right? And we shouldn't try necessarily to compete with industry. The idea that we're going to generate the next, you know, competitor to chat GPT here at UD, that's not our role, right? So don't think about that. But if we continue instead to do what we're really good at, which is to innovate, to come up with the next amazing thing, right, it's going to help lead to the next giant leaps that nobody anticipated, right? So one of the things that we're struggling with, what are we going to do with get the next Darwin? We need something that's even bigger. But wait, we don't, you know, Darwin has 6,672 cores, you know. But in order to train a large language model like ChatGPT, you need like 100,000 GPUs, so we're going to need, what, 15 Darwins? We're not going to get that. But what that does mean is that we have to figure out ways to accomplish really powerful advancements with a smaller system. Do it more efficiently, and can you imagine what's going to happen if all of a sudden the next big advancement, right, is not that, oh, we've now created a large language model that has umpteen billion parameters and cost, you know, $6.3 million to train. But no, we just created an AI that has, you know, the same number of parameters, but it was trained on a much smaller system because we invented a new and efficient, much more efficient way of training a large language model. that's what universities really are good at so with that note I want to thank you again for joining us both in February and also in April for the data science and Darwin symposium 2025 this is an annual thing right so you can you should expect to see a Darwin symposium again next February predictably on February 12th it will likely also be a data science symposium probably in the fall are we talking about, right? So we'll be able to do this sort of get -together twice a year. Also, for those of you that are students, I'd encourage you, if you're not already a member of the Data Science Student Association, to sign up. And there's a table in the back. I think there's still some forms you can sign up. And that's all I have for today. So thanks again. Oh, the last thing I should say, thanks again to our many sponsors, and I'm going to leave this slide up so they get their well-due recognition. Thank you again.