2/1 - Week 1 - Welcome Back, Rozin Mirrors
2/8 - Week 2 - Pixel Access, Brightness + Color Tracking, Text Rain
2/22 - Week 4 - Intro to Machine Learning with Teachable Machine
3/1 - Week 5 - Neural Networks, Machine Learning, StyleGAN2
3/8 - Week 6 - StyleGAN2 continued
3/15 - Week 7 - Seminar/open work time
3/22 - Week 8 - AI Art Lecture
4/5 - Week 10 - Final Project Proposals
4/12 - Week 11 - Dataset processing workshop
4/26 - Week 14 - Stable Diffusion
Intro to Computer Vision - Spring 2023
Disclaimer: many of these examples are interesting, but not all are relevant today. Some represent a point in the development of these technologies that have since been “solved,” while others are issues endemic to these technologies.
This isn’t much of a point at the end of this collection. Rather, it’s a survey of the various entry points into thinking these technologies. Ultimately, the point of this lecture is make out way back to art. The point of talking about such a broad range of approaches, techniques and contexts all at once is to expand our inquiry to transcend any narrow understanding of these technologies.
58:45-1:01:03, NVIDIA GTC Keynote 2023 with NVIDIA CEO Jensen Huang (Nvidia Omniverse, Amazon warehouse robots, synthetic data set and factory environment to train robots)
1:06:31-1:09:51, NVIDIA GTC Keynote 2023 with NVIDIA CEO Jensen Huang (BMW Electric Car plant fully constructed virtually before plant construction even begins. (sidenote: are the technicians in this Teams call real?? Their voices sound AI-generated…it’s all so stilted and uncanny)
https://www.theverge.com/23649329/nvidia-dgx-cloud-microsoft-google-oracle-chatgpt-web-browser
SMPLVerse (2022) - Will Wiebe (Fake it till you make it: face analysis in the wild using synthetic data alone)
Computer Vision in Triple Chaser - Forensic Architecture (https://www.youtube.com/watch?v=93rjwQMww9M)