17 DAILY CVPR Thursday Katerina Fragkiadaki Am I right if I say that the more problems you solve in computer vision, the more it opens new problems to solve? Well, right now, we’re in a very interesting stage where a lot of problems that can be supervised from images and text are making tremendous progress. For example, object detection, object labeling, and basic referential expression understanding. This is improving. Now, final perception that you need for robot action and decision making – yes, this requires more work. Is there anything you did not expect when you chose this field but you discovered on the way? Yeah, there are tons of things I haven’t expected. I didn’t expect neural networks would take over. I wouldn’t expect we’d be working on GPUs. After that, I definitely didn’t expect the tremendous language models generating such naturallooking and feeling language. Definitely, I didn’t expect the generative image models that generate these beautiful images. Are they four good things for you or bad surprises? This is the tremendous progress that the field makes that we can’t anticipate. I think this is good. It’s good! Is this a good moment to work in AI? Did you fall into the right generation? I think I fell into the right generation in the sense that I was in the field when the field was really not done, nothing was working, so then you are able to experience the whole revolution. If I was starting now, I think I would be more reluctant to join now. What would you do instead? I would go to open problems like green energy, renewable energy, chemistry, and maybe biology, and I’m sure machine learning has a lot of things to give to those fields. I think I would do that right now. It is not by chance that one of the outstanding papers here at ICLR is a biomedical paper about protein discovery. Yes, I think the machine learning applications in the sciences are very exciting. Might that be a direction that you will invest in the future? Yeah, it’s absolutely true that some models absolutely generalize. Generative models have made a tremendous impact not only for generating images, videos, or text but also molecules, and they facilitate search in the molecule space and the reward functions that
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