It is my passion to blend the research and technical side of A.I with the creative arts in order to produce high quality visualizations of deep learning optimization processes that can both inspire and help trigger new insights. As the project continues, new collaborations are arising with researchers at different institutions. In this way, we continue the mission of bringing a sense of beauty to A.I, combining rigurious research with very high resolution and quality visualizations that can bring new light and perspective onto some of the mysteries of deep learning training processes.
Studying the morphology and dynamics of the loss landscape is very expensive in different ways. It is a process that requires enormous amounts of computing power as well as time. In order to scale and take this project even further, I will need way more computing power and way more time. That’s why I welcome all suggestions and ideas regarding possibilities that may eventually allow me to dedicate more time and resources in order to take the loss landscape project way further as well as to share in parallel visualizations and related research with the community. Below you can visit some of the galleries that hold Ideami’s A.I artworks. Acquiring prints or unique editions of the artworks contributes to sustain the project.
- Loss landscape NFT collection, click link to visit
- Ideami A.I gallery, click link to visit
- Ideami @ Fine Art America, click link to visit
- Neuroscience NFT collection, click link to visit
The second phase of the Loss Landscape project is currently ongoing. The sky is the limit! Thank you for any suggestions. You can contact me at firstname.lastname@example.org. My central website is at ideami.com and ideami.com/ideami
This project exists because I was inspired by two important groups of people to which I am grateful: the phenomenal Fast.ai community, and the team formed by Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer and Tom Goldstein, authors of the paper that sparked my initial interest in the world of Loss Landscapes. To you both, thank you for inspiring the deep learning community with your teachings, research, spirit and ventures.