Research

RT @facebookai: We're releasing Flashlight: A modern, open source machine learning library written entirely in C++. It's customizable to the core to support your research's needs — and it's pretty fast too. https://t.co/DIJd35Gt4u https://t.co/oGlgxTibVG

RT @AccelerateSci: If you are a PhD or postdoc at Cambridge University, apply now for a funded training course that is equipping scientists with powerful tools to progress their research. The next Data for Science course starts mid-July. https://t.co/MXIRwFBHeH

[D] Bayesian Machine Learning for KITTI Depth Estimation https://t.co/YZNtHFKzSt

RT @bhutanisanyam1: An analysis of >100 ML Competitions by @ml_contests : Fav points: - 🍵 @kaggle is hosted the most competitions of any platform - 🚀 For DL competitions, 70% winning solution used @PyTorch - 🏆 >80% winners were the first-time winners https://t.co/wMBugJC1ie https://t.co/HBp5CXQlJx

RT @baxterkb: Look who are the keynote speakers at the @AIESConf (#AIethics & #Society) Conference) in May: @iajunwa, @timnitGebru, & @random_walker!! Topics "A Veil of Ignorance for Automated Decision-Making" & "Moving beyond the #Fairness Rhetoric in #AI." 🙌 https://t.co/AMma4255Ad

@yoavgo @rao2z In fact, there are 6 thematic pillars. 1. Safety-Critical AI 2. Fair, Transparent, and Accountable AI 3. AI, Labor, and the Economy 4. Collaborations Between People and AI Systems 5. Social and Societal Influences of AI 6. AI and Social Good https://t.co/O1F9p9wqqv

RT @BostonReview: .@DrDaronAcemoglu’s lead essay from our new book is now live and free for all to read! Preorder now to read responses from @danielsusskind @MollyKinder @abenanav @shakir_za @wsisaac @png_marie @erikbryn @katecrawford @robreich @red_abebe @maxkasy + more:https://t.co/3YtfwQVIqQ

@Isinlor @awjuliani This actually, coincidentally, the topic of a talk I’m giving at an ICLR WS (https://t.co/92cnMgdwkk) in a few weeks, and am writing right now. Do you guys mind if I screenshot your tweet thread for use on a slide?