State of AI Report 2020 (review)

For the last three years, the State of AI Report has been published as a snapshot of what's happened in the field of artificial intelligence over the past 12 months. This is my review/walkthrough of the 2020 version. A big shout out to Nathan and Ian for their huuuuuuge efforts putting this together! See the full State of AI Report 2020 here: https://www.stateof.ai Connect: Web - https://www.mrdbourke.com Email updates - https://www.mrdbourke.com/newsletter Timestamps: 0:00 - Intro and hello 1:31 - AI report review start 2:12 - AI definitions 3:00 - SECTION 1: Research 3:37 - Transformers taking over NLP 5:50 - Universities starting AI-based degrees 6:35 - Only 15% of papers published share their code/data 8:20 - PyTorch outpacing TensorFlow in research papers 11:12 - Bigger models, datasets and compute budgets drive performance 15:40 - Increased performance costing more for incremental improvement 18:13 - Deep learning is getting more efficient 21:11 - AI for conversations is getting better 23:02 - Machine translation for code (Python to C++) 25:32 - Many algorithms starting to beat human baseline for NLP on GLUE test 27:04 - Using Transformers for computer vision 30:11 - AI performs incredibly well on mammography tasks across two regions (US and UK) 31:30 - Causal inference in ML 34:30 - ML for synthesizing new molecules 36:26 - AI starts to read DNA-encoded molecules 39:39 - AI generates tennis matches between any tennis players you want 40:46 - Transformers being used for object detection 41:46 - AI which learns from its dreams 44:26 - Really efficient on-device computer vision models 45:04 - Evolving machine learning algorithms from scratch (AutoML Zero) 46:20 - Federated learning is now booming 47:16 - Privacy-preserving ML 48:35 - Using Gaussian Processes for estimating model uncertainty 50:11 - SECTION 2: Talent 50:12 - Many top companies stealing AI professors 52:02 - Abu Dhabi opens the world's first AI university 54:03 - Many Chinese AI PhD's depart C