How does a university based researcher keep feeling relevant in this fast changing and compute driven field?
— hardmaru (@hardmaru) August 25, 2020
Some good discussion here ➝ https://t.co/hlGNFrHete pic.twitter.com/q5vABdR9dS
How does a university based researcher keep feeling relevant in this fast changing and compute driven field?
— hardmaru (@hardmaru) August 25, 2020
Some good discussion here ➝ https://t.co/hlGNFrHete pic.twitter.com/q5vABdR9dS
"We should do X because that is the way we did it at Google" is almost always a bad idea, unless you work at a FAANG.
— Chris Albon (@chrisalbon) August 20, 2020
What you're missing when you're just starting out as a software engineer isn't technical ability, it's perspective.
— François Chollet (@fchollet) August 18, 2020
Perspective on the lifecycle of codebases, on the business context (and sometimes social context) of how software is used, on the evolution of your industry, etc.
Today’s pro leadership tip:
— Angela Bassa (@AngeBassa) August 18, 2020
You don’t have to work with assholes. You can choose to surround yourself with kind people 🥰
4/ Since then, time and time again, it has paid off for me, big time, to simply remember to look where others aren't looking, and to prioritize actual observation over trying uncritically assume that smarter people have already covered the territory and are right.
— Jason Antic (@citnaj) August 18, 2020
2/ e.g. Why weren't pretrained Unets or transfer learning employed in GANs in late 2018 for GANs? Probably simply because nobody else was doing it- lack of social validation. It certainly wasn't hard to come up with a proof of concept, especially for a fresh MOOC grad like me.
— Jason Antic (@citnaj) August 18, 2020
People who are determined that they must have their own opinion on every topic and therefore don't trust experts are invariably the easiest to manipulate
— Tim Wu (@superwuster) August 17, 2020
Science is how we learn about the world. Art is how we learn about ourselves.
— François Chollet (@fchollet) August 16, 2020
I say this in talks all the time, don’t be afraid to ask users vs making a model. Usually this happens because the ML team has been pushed down in the org or act in an embedded service model such that they have no real control over UX. Front end changes for ML become impossible.
— peteskomoroch (@peteskomoroch) August 16, 2020
I suspect that a lot of “brilliant insights” are natural next steps from someone who has deep intimacy with a research topic. And that actually seems more profound.
— Chris Olah (@ch402) August 16, 2020
Research intimacy is also different from research taste. But it does feed into it, and I suspect it’s one of the key ingredients in beating the “research taste market.”
— Chris Olah (@ch402) August 16, 2020
Research intimacy is different from theoretical knowledge. It involves internalizing information that hasn’t become part of the “scientific cannon” yet. Observations we don’t (yet) see as important, or haven’t (yet) digested. The ideas are raw.
— Chris Olah (@ch402) August 16, 2020