Honestly I'm not an expert on autonomous driving so I'm not sure I have great insights there. I do know quite a bit about computer vision however so feel qualified to comment on that bit -- I suspect the decision by Tesla to only use CV, and not LIDAR, may turn out to be a mistake. I don't see any reason why we couldn't achieve full autonomy with our current tech including LIDAR, although I don't know if it can be achieved at a practical latency and power budget.

The new advances in DL I'm excited about are things I show in the class: the accessibility of modern NLP thanks to the Hugging Face ecosystem; the power of ConvNeXt for even better computer vision models; the way Gradio and HF Spaces makes it trivially easy to get a working prototype application using DL online.

I'm also excited about hosted models and applications like GPT-3, DALL-E, and Codex. All the illustrations on our course website are from DALL-E, for instance!