Rochetshipz
Rochetshipz on Hacker News
Particularly, claiming Russian collusion the last time did not turn out to be true, but the Media jumped on this narrative. Let's not do it again.
Well Cloudflare has an office there, where their CTO is.
I just read a book about it from the co-creator of Siri, Luc Julia.
He spends a good part of the book complaining about french research, which does not care about products impact and thus is very theoretical, but also about the heavy hand of the government in dictating where innovation happens.
He also talks about Sophia-Antipolis. It started with a boom, and a lot of tax credits to incentivize corporations. But after the subvention dried up, many companies left. It seems to me that most of the companies left do not have innovation in their DNA.
A lot of ML classes at CMU (and probably other prestigious campuses) are sponsored by AWS or GCP through cloud credit donation, including the popular Cloud Computing class. Is that any different ?
The whole interview (multiple hours) is fascinating, like a good episode of "On the Metal". Heavy recommend for people interested in CS history and Innovation.
This is an uninformed opinion yeah. Facebook is recruiting HEAVILY and appears to have the published state-of-the-art research in the field. They also recently acquired a hot startup in the field, Scape based in London, and kickstarted Facebook Reality Labs in London which is hiring. They are also hiring in Seattle.
If someone wants to look how Microsoft is also doing from a engineering PoV, watch this cool video from Marc Pollefys from ETH Zurich/Microsoft. It was made for a technical-minded scene and shows the behind-the-scene, some potential issues (privacy) and where it is going next https://vimeo.com/380218937
This paper is a bit "old" by the way. An excellent paper was released a week ago :
https://arxiv.org/abs/2003.01587Findings are mostly the same. For day/day images, with a properly tuned pipeline, SIFT is really good.
Mhhhhh, I'm a researcher in the field and I'd say it's a mostly inaccurate statement. The root-SIFT detectors and descriptors are still really good. If you try to match images in different conditions (day/night), then CNN based approaches are OK.
Which one were you thinking about?