The horror, the horror…
— Mara Averick (@dataandme) February 24, 2020
😎 ∩ 👴🏼 "Grandpa Chad distribution" https://t.co/uETv4Pm8Bi @xkcdComic via @flowingdata pic.twitter.com/SZWmDHu6X9
The horror, the horror…
— Mara Averick (@dataandme) February 24, 2020
😎 ∩ 👴🏼 "Grandpa Chad distribution" https://t.co/uETv4Pm8Bi @xkcdComic via @flowingdata pic.twitter.com/SZWmDHu6X9
I prefer something more like this: https://t.co/TLUcVsGfN2 https://t.co/Sn9IFmAS7g
— hardmaru (@hardmaru) February 23, 2020
Reminds me of this comment: pic.twitter.com/z2AqWD4l33
— hardmaru (@hardmaru) February 23, 2020
3/ pursue deep learning. I started at 16 hours/week; then went to 8 hours/week in Nov 2018. That's well over $100K in salary lost right there! Then there's the "monster computer" to run all these experiments. That cost nearly $10K and the electric bill from it has exceeded $4K
— Jason Antic (@citnaj) February 22, 2020
A key design principle I follow in libraries (e.g. Keras) is "progressive disclosure of complexity". Make it easy to get started, yet make it possible to handle arbitrarily flexible use cases, only requiring incremental learning at each step.
— François Chollet (@fchollet) February 22, 2020
Like zooming in a complex landscape. pic.twitter.com/AzaySJeTMP
I'm unnerved by common claims of "with our super duper library X, doing Y is just 5 lines of code: ...". Ok you hid a lot of code under defs and reduced flexibility. I'd rather see it be 50 lines of code, with nice modular building blocks where various reconfigurations are clear.
— Andrej Karpathy (@karpathy) February 22, 2020
European Union swiftly pivots from 'let's ban facial recognition' to 'let's create a pan-European database of facial data'. https://t.co/vhQgk8L3zO
— Michael Veale (@mikarv) February 22, 2020
HyperNEAT is quite funky. https://t.co/nBhErbye03 https://t.co/aJF8Hn7nrh pic.twitter.com/k0ygWRL5lD
— hardmaru (@hardmaru) February 22, 2020
For me, the best model of a data science community isn't RStudio, it isn't the NeurIPS conference, or anything like that. It's R-Ladies. The R-Ladies community works as a bottom-up, decentralised community of practice that is built from empathy and support. We should be R-Ladies
— Danielle Navarro (@djnavarro) February 21, 2020
Suppose you have to choose between a black box AI surgeon that runs on TensorFlow 1.0 on an EC2 instance that hasn't been upgraded to Python 3 but has a 80% cure rate and a black box AI surgeon with an 80% cure rate that runs on Excel vlookups. Do you want to live on this planet?
— Vicki Boykis (@vboykis) February 21, 2020
The Problem with Metrics is a Fundamental Problem for AI-- paper by me and David Uminsky @DataInstituteSF accepted to EDSC 2020 https://t.co/bg0elsbBd9 cc: @craignewmark pic.twitter.com/UzFP24ySni
— Rachel Thomas (@math_rachel) February 21, 2020
This is huge.
— Jeremy Howard (@jeremyphoward) February 20, 2020
The creator of the YOLO algorithms, which (along with SSD) set much of the path of modern object detection, has stopped doing any computer vision research due to ethical concerns.
I've never seen anything quite like this before. https://t.co/jzu1p4my5V