256lie

Maybe being a Harvard dropout with low EQ appeals more to VC. Elon makes up for it by working really work and having savior ego/massive hype that appeals to his fans and investors.

Reminds me of one of Ted Chiang's short stories where they can't recognize attractive faces.

https://www.goodreads.com/book/show/50550973-liking-what-you...

I wonder how long we can continue overfitting these benchmark datasets as a community of researchers? How much is ImageNet is labeled incorrectly/subotimally?

They meta analysis only found 8% with negative outcomes. What is the base rate for comparison for the current standard of care?

Maybe something like this https://en.m.wikipedia.org/wiki/17776

To be fair, the orientation is the only mandatory meeting you have to go to and the remote transition probably makes these logistics harder.

More like deferring to a later batch than kicked out entirely.

Maybe what you consider "good" recommendations don't make as much money. They extensively A/B test everything and what is in prod is what works.

Any type of preditive analysis in high dimensional data (medical imaging, surveillance, remote sensing, machine translation, speech recognition/synthesis, music information retrieval). Other important work being done on causality, AI ethics/safety, and explainability (XAI) but little industry impact yet.

Models to detect strokes in medical images to be deployed in a hospital.

The Clincal Center for Data Science at Massachusetts General Hospital (one of the top hospitals in the world) is hiring for a variety of positions. We have access to tons of medical data (imaging, NLP, time series), clinical domain expertise, and one of the largest GPU computing clusters. https://www.ccds.io/careers/