*Grumpy Chris:* One of my biggest research gripes is people boiling the world down into a couple summary statistic numbers and feeling like that somehow made things more rigorous.
— Chris Olah (@ch402) December 21, 2019
*Grumpy Chris:* One of my biggest research gripes is people boiling the world down into a couple summary statistic numbers and feeling like that somehow made things more rigorous.
— Chris Olah (@ch402) December 21, 2019
One of the hardest parts of product development is preventing “design by anecdote”. In many ways it’s even worse than design by committee. We all do it - this isn’t a criticism of other people - it’s just one of those things that can derail things quickly if not nudged back fast.
— Jason Fried (@jasonfried) December 18, 2019
One of the greatest and most common examples of self-delusion is the belief that one is "immune" to advertising (unlike the rest of those suckers)
— Tim Wu (@superwuster) December 14, 2019
“Leaders in artificial intelligence warn that progress is slowing, big challenges remain, and simply throwing more computers at a problem isn't sustainable.” #NeurIPSGreatDebate @tsimonite https://t.co/EFG56vSOUA
— hardmaru (@hardmaru) December 13, 2019
Here are some of my thoughts on the key trends in AI and machine learning in 2019 & what to expect in 2020 🔮 https://t.co/FLNqNPLCiv pic.twitter.com/UI291vSUwh
— Ines Montani 〰️ (@_inesmontani) December 9, 2019
There's plenty that I agree with in this article but the thing that I cannot abide is the concept that finding discrimination in privately held, IP-protected algorithms is easy is just plain wrong.https://t.co/ITMwIFJBzW
— Cathy O'Neil (@mathbabedotorg) December 8, 2019
I think 70% of our anxieties about modern technology can be traced back to Western governments transfering big chunks of R&D and expertise from public sector to private sector, which develops things in different ways with different priorities
— Jack Clark (@jackclarkSF) December 8, 2019
Intelligence is the capacity to do the right thing at the right time.
— Rachel Thomas @ #NeurIPS2019 (@math_rachel) December 4, 2019
Intelligence is a computation-- a transformation of information. Learning is a type of search. @j2bryson starting off by defining intelligence. #FantasticFutures2019 pic.twitter.com/RasX4EUEDS
AI needs better datasets (not just the most convenient or easy to collect data):
— Rachel Thomas @ #NeurIPS2019 (@math_rachel) December 4, 2019
- data that better reflects scope of human imagination
- better practices for data collection
- data collected by specialists
- takes into account ethics & consent@ctnzr #FantasticFutures2019 pic.twitter.com/JPohaa7c7a
From my *direct* experience, both in real life and online forums, a *lot* of criticism of @Kaggle by the soi-disant Data Science “thought leaders” boils down to one thing: self-handicapping behavior.https://t.co/Hcm5TBmh0h
— Bojan Tunguz (@tunguz) December 4, 2019
Finally got a chance today to read this detailed, thoughtful article on remote work by @buritica and @katie_womers and I cannot recommend it highly enough.
— Julia Silge (@juliasilge) November 29, 2019
I've worked remotely since basically grad school, and the thoughts shared here are 💯💯💯 https://t.co/lqdnXqq5lJ
Open-sourcing a community-focused library basically means you'll keep fighting with a bunch of well-intentioned people who want to morph your simple code in a cathedral of complex and smart abstractions.
— Thomas Wolf (@Thom_Wolf) November 29, 2019
Writing easy-to-read, simple-to-use code is an under-rated skill.