“People seem to have a preference for centralization in everything they think and do. People tend to look for the cause, the reason, the driving force, the deciding factor. When we observe patterns and structures in the world, we often assume centralized causes where none exist.”
— hardmaru (@hardmaru) February 6, 2019
Déjà Vu: "In a 1958 press conf. organized by the US Navy, Rosenblatt made statements about the perceptron that caused a heated controversy among the fledgling AI community. Based on Rosenblatt's statements, The New York Times reported the perceptron to be *the embryo of...(1/2)
— Zachary Lipton (@zacharylipton) February 5, 2019
Fantastic in-depth piece by @skynet_today on job loss due to AI. The main argument: AI will (most likely) *not be significantly more disruptive* than the impact of automation in the past.https://t.co/0fJRyknQqL pic.twitter.com/xfKer6h0ky
— Sebastian Ruder (@seb_ruder) February 5, 2019
Announcing Live Transcribe, a free Android service that makes conversations more accessible through real-time captioning, supporting over 70 languages and more than 80% of the world's population. Learn more at https://t.co/XMlT2AxYUe. https://t.co/50zMOjsfKZ
— Google AI (@GoogleAI) February 4, 2019
We tried to use Twitter to detect voter fraud & voter suppression. Here are a few things we learned during our quest:
— Emilio Ferrara (@jabawack) February 4, 2019
Perils and Challenges of Social Media and Election Manipulation Analysis: The 2018 US Midterms https://t.co/vTbKCMFkfA
w/ @ashokkdeb @LucaLuceri @adambbadawy pic.twitter.com/nhwb4odFuF
Surprised I haven't seen this flattery before: How open science helps researchers succeed https://t.co/zRN29H8vWI @GaelVaroquaux @agramfort @ogrisel Thanks @ctitusbrown @_inundata ;) pic.twitter.com/ox4y4Jy8Bw
— Andreas Mueller (@amuellerml) February 4, 2019
Great info for data science learners! https://t.co/qvxNZ176hs
— Data Science Renee (@BecomingDataSci) February 3, 2019
Great demonstration of what I recommend to beginners: collect your own data (or download a dataset) on a topic that matters to you, and do an analysis project on it that can be added to your portfolio! https://t.co/LU3um41ChE
— Data Science Renee (@BecomingDataSci) February 3, 2019
According to this researcher, there has been *no* reduction in the proportion of people making less than $7/day since 1981 (before that time we don't have data).
— Jeremy Howard (@jeremyphoward) February 3, 2019
That's shocking. https://t.co/EsXL1bNpN0
👏🏼 may I have your attention to this 👇🏼 https://t.co/kv7fcL0han
— Delip Rao (@deliprao) February 3, 2019
When traditional education folks study MOOCs they totally mess it up every time.
— Jeremy Howard (@jeremyphoward) February 3, 2019
e.g. Why on earth are people still using completion rate as a success metric? Our course, for instance, is explicitly designed to provide most of what you need in the first couple of lessons.
The end of the article is disappointing. The MOOCs weren't "domesticated" by existing higher ed; instead their learning model failed on its own. Would like to see a study that explained WHY they failed. The need is huge.
— Thomas G. Dietterich (@tdietterich) February 3, 2019
