Transformers United: DL Models that have revolutionized NLP, CV, RL
22:43Transformers in Vision: Tackling problems in Computer Vision
1:08:36Decision Transformer: Reinforcement Learning via Sequence Modeling
1:20:42Mixture of Experts (MoE) paradigm and the Switch Transformer
1:05:44DeepMind's Perceiver and Perceiver IO: new data family architecture
58:58Self Attention and Non-parametric transformers (NPTs)
1:05:43Transformer Circuits, Induction Heads, In-Context Learning
59:34Neuroscience-Inspired Artificial Intelligence
1:22:14How I Learned to Stop Worrying and Love the Transformer
1:20:38Transformers in Vision: Tackling problems in Computer Vision
In this talk, Lucas discusses some of the ways transformers have been applied to problems in Computer Vision.
Lucas Beyer grew up in Belgium wanting to make video games and their AI, went on to study mechanical engineering at RWTH Aachen in Germany, did a PhD in robotic perception/computer vision there too, and is now researching representation learning at Google Brain in Zürich.
View the entire CS25 Transformers United playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rNiJRchCzutFw5ItR_Z27CM
Transformers United: DL Models that have revolutionized NLP, CV, RL
Next · Lecture 3Decision Transformer: Reinforcement Learning via Sequence Modeling