An executive’s guide to AI
Staying ahead in the accelerating artificial-intelligence race requires
executives to make nimble, informed decisions about where and how to
employ AI in their business. One way to prepare to act quickly: know the
AI essentials presented in this guide. https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/an-executives-guide-to-ai

Call for submissions! The 7th Women in Computer Vision Workshop (WiCV) at #CVPR2020 invites all vision researchers to submit papers and attend the workshop. There will be talks, posters, a panel discussion and dinner! More info: https://sites.google.com/view/wicvworkshop-cvpr2020/

Call for Papers for #NeurIPS2020 is out → https://mld.ai/neurips20call4papers

Learn more about what is new this year in this video → https://mld.ai/neurips20vid

Checkout this blog post by #NeurIPS2020 program chairs, Marc'Aurelio Ranzato, Nina Balcan, Hsuan-Tien Lin and Raia Hadsell → https://mld.ai/neurips20blog

TL;DR:
0) Watch this video summarizing the major changes → https://mld.ai/neurips20vid
1) This year’s abstract submission deadline is moved up to May 5th, 2020, while the paper submission deadline is May 12th, 2020. This shift allows us to handle the increased volume of submissions and accommodates the early rejection phase of the review process… which brings us to the next point.
2) Early rejection: Area Chairs will have two weeks to recommend papers for early rejection. We expect up to 20% of the papers to be selected for this category. Senior Area Chairs then have one week to approve the decision, at which point authors of rejected papers will be notified that their paper will not undergo any further review.
3) Authors are reviewers: We require that every (co-)author of every paper agrees to review papers if asked. This requirement is useful for increasing our reviewer pool size and to fairly distribute the reviewing load more evenly among community members who submit papers.
4) Broader impact: Authors are asked to include a section in their submissions discussing the broader impact of their work, including possible societal consequences — -both positive and negative.
5) Video spotlight: We request that all authors upload a video recording of the spotlight presentation of their work at camera-ready submission time, and we are also working on ways of enabling remote presentations as well as remote attendance.

Awesome Decision Tree Research Papers
https://github.com/benedekrozemberczki/awesome-decision-tree-papers

CS224N : Natural Language Processing with Deep Learning
https://www.youtube.com/playlist?list=PLU40WL8Ol94IJzQtileLTqGZuXtGlLMP_
#NaturalLanguageProcessing #DeepLearning #ArtificialIntelligence

Toward a General AI-Agent Architecture | Rich Sutton, DeepMind ALberta | NeurIPS 2019
https://www.youtube.com/watch?v=yTdDE5Lzo7w

Deep Learning. The full deck of (600+) slides
Gilles Louppe: https://github.com/glouppe/info8010-deep-learning/raw/v2-info8010-2019/pdf/lec-all.pdf
#ArtificialIntelligence #DeepLearning #MachineLearning

New machine learning method from Stanford, with Toyota researchers, could supercharge battery development for electric vehicles
https://news.stanford.edu/2020/02/19/machine-learning-speed-arrival-ultra-fast-charging-electric-car/

Causal Inference Book: "Causal Inference: What If"
https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/

PhD Studentship on Artificial Intelligence for Railway Operations and Management
https://phd.leeds.ac.uk/project/504-phd-studentship-on-artificial-inte

AI, Data, Culture: In Conversation with Ben Horowitz, GP, a16z
https://mattturck.com/horowitz/#more-1302

Turing-NLG: the largest language model with 17 billion parameters trained by DeepSpeed
LINKS
Turing-NLP: https://www.microsoft.com/en-us/research/blog/turing-nlg-a-17-billion-parameter-language-model-by-microsoft/
DeepSpeed: https://mspoweruser.com/meet-microsoft-deepspeed-a-new-deep-learning-library-that-can-train-massive-100-billion-parameter-models/
Github: https://github.com/microsoft/DeepSpeed