Artificial intelligence (AI) systems now generate authentic paintings, compose music pieces, and find out-of-box solutions to real-life problems in our world. Creativity, which was considered to be a moon shot for AI, does not seem to be too far any more. Is that true? Are we close to see creative AI? The answer is yes and no. We are moving closer to meaningful developments in Machine Learning, however there are several questions to be explored further to achieve the creative AI. What kind of creativity we want to represent? How do we translate creativity into what machines can understand? How do we design ML algorithms to be more creative?
Our goal is to design computational models that present the very possibility of the creative AI.
Students will be presenting their work on making AI more creative. Come by to learn more!
12:00 - 12:15 | Creative Adversarial Networks : CAN it do better?
12:15 - 12:30 | Design Physics
12:30 - 12:45 | Wav2Midi
12:45 - 01:00 | Creative Spatial Understanding
01:00 - 01:15 | An Open-ended evolutionary tool for boosting creativity during shape exploration sketching in industrial design
Come back on Thursday, 5 December: Gates Hillman 4101 - 12:00 - 1:20 pm
12:00 - 12:15 | Robot Painting
12:15 - 12:30 | Multi-agent RL and emergent creative behaviors
12:30 - 12:45 | Creative Image-Text Generation by Biasing its Topic
12:45 - 01:00 | doppleGANer