State of AI Report 2020

Daniel Bourke reviews the the State of AI 2020 report in the following video.

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.

Read the full State of AI Report 2020 here: https://www.stateof.ai

Index:

  • 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 China for other countries
  • 54:52 – US based companies and institutions dominate NeurIPS and ICML (ML conferences)
  • 56:13 – Three times more AI job postings then views for AI roles
  • 56:58 – TensorFlow and Keras have more job postings on LinkedIn than PyTorch
  • 57:18 – SECTION 3: Industry
  • 59:06 – INTERMISSION
  • 59:44 – AI predicting metabolic response to food
  • 1:00:45 – FDA acknowledge lack of policy for AI-driven systems
  • 1:01:54 – Less than 1% of AI-based medical imaging studies are high-quality
  • 1:02:48 – First reimbursement approval for deep learning based medical imagining
  • 1:05:16 – Self-driving mileage in California still well above autonomous driving mileage
  • 1:10:36 – Supervised ML improvements seem to follow an S-curve
  • 1:12:13 – A new kind of approach to self-driving cars
  • 1:17:17 – New AI-first chips (competition for NVIDIA)
  • 1:19:41 – The rise of MLOps
  • 1:21:52 – Computer vision for auto insurance claims
  • 1:23:45 – Using NLP to detect money laundering and terrorist schemes on the web
  • 1:25:17 – Robots in stock factories are picking millions of items per month
  • 1:26:23 – HuggingFace’s open-source NLP work is driving NLP’s explosion
  • 1:28:09 – SECTION 4: Politics
  • 1:29:59 – Creating a search engine for faces
  • 1:33:29 – GPT3 outputs bias predictions like GPT2
  • 1:33:49 – US military adopting deep reinforcement learning techniques
  • 1:35:52 – Fighter pilots vs AI pilots
  • 1:38:28 – Google’s People and AI guidebook talks about fairness, interpretability, privacy
  • 1:40:46 – China fronts big cash for chip manufacturing
  • 1:45:00 – A call to tackle climate change, food waste, generating new battery technologies and more with ML
  • 1:45:45 – SECTION 5: Predictions
  • 1:49:22 – A special guest appears

Frank

#DataScientist, #DataEngineer, Blogger, Vlogger, Podcaster at http://DataDriven.tv . Back @Microsoft to help customers leverage #AI Opinions mine. #武當派 fan. I blog to help you become a better data scientist/ML engineer Opinions are mine. All mine.