What is OpenAI? I don't know anymore.
— Smerity (@Smerity) July 22, 2019
A non-profit that leveraged good will whilst silently giving out equity for years prepping a shift to for-profit that is now seeking to license closed tech through a third party by segmenting tech under a banner of pre/post "AGI" technology? https://t.co/X6JIIuvcAd
The NYT article is misleading here. We'll definitely spend the $1B within 5 years, and maybe much faster. It's also not Azure credits:https://t.co/YXmclmZDok
— Greg Brockman (@gdb) July 22, 2019
“Most of that $1 billion, @sama said, will be spent on the computing power OpenAI needs to achieve its ambitions. And under the terms of the new contract, Microsoft will eventually become the lab’s sole source of computing power.” https://t.co/aPgqfYJQ9m https://t.co/6Prf1tFNuM
— hardmaru (@hardmaru) July 22, 2019
Super exciting news: Microsoft is investing $1B into OpenAI, and we're partnering to build giant NN computers within Azure that will train giant NNs! https://t.co/PzJG5lPpkX
— Ilya Sutskever (@ilyasut) July 22, 2019
We've raised $1 billion from Microsoft and will be working together to build next-generation supercomputers, with the goal of building a platform within Azure which will scale to AGI: https://t.co/5tzkVusSRJ
— Greg Brockman (@gdb) July 22, 2019
New NLP News: NLP in Industry, Leaderboard madness, https://t.co/Uax3FSbOBV NLP, Transfer learning tools https://t.co/jgGfAaYukG via @revue
— Sebastian Ruder (@seb_ruder) July 22, 2019
If you like both data and public policy, this is a great read by @GarethIdeas https://t.co/iNZpLCzAV3
— Sharon Machlis (@sharon000) July 21, 2019
Are you an #rstats pipe %>% user? 💕Check out this history and context for the Unix pipe | . https://t.co/5AiW9hRj7f
— Julia Silge (@juliasilge) July 21, 2019
And companies complain why it's so hard to hire for machine learning roles. pic.twitter.com/xRjMflozVd
— Chip Huyen (@chipro) July 21, 2019
An unsupervised machine-learning technique has found a number of possible new materials. https://t.co/YkBMAqrlEo
— MIT Technology Review (@techreview) July 21, 2019
I asked interviewers and candidates for machine learning roles what are bad interview questions and these are some of their answers. What do you think are good/bad interview questions? pic.twitter.com/gorjYCuWWr
— Chip Huyen (@chipro) July 20, 2019
How the Transformers broke NLP leaderboards https://t.co/iNf5qBccQd
— /MachineLearning (@slashML) July 20, 2019
