rkaplan
Joined 15 years ago
Karma
829
Submissions
84
Member since
Jan 25
Contact me: rjkaplan at cs dot stanford edu
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Comment · 6 years ago
This is the correct answer. A key reason Rebco is so much better than older alternatives is that it can be cooled to superconductivity using only liquid nitrogen (77K), as opposed to liquid helium, which is much harder to work with.
Comment · 6 years ago
Longtime DVC user here - this is going to be so helpful. We use DVC for all of our model and data versioning, but what's been missing is the ability to cleanly integrate that into our CI workflow. Looks like that's solved now! The cml.yaml syntax also looks quite nice, very easy to follow. Looking forward to trying this out.
Comment · 8 years ago
Great anecdote from Jeff Dean's twitter [1] about how they thought to try this experiment, given that doctors didn't know such a thing was possible:
"Funny story. We had a new team member joining, and @lhpeng suggested an orientation project for them of "Why don't you just try predicting age and gender from the images?" to get them familiar with our software setup, thinking age might be accurate within a couple of decades,and gender would be no better than chance. They went away and worked on this and came back with results that were much more accurate than expected, leading to more investigation about what else could be predicted."
Comment · 9 years ago
This is not "AI that builds AI". The actual research behind AutoML is called NASNet (https://arxiv.org/pdf/1707.07012.pdf), and all it is simply: we found two good neural network layers (called NASNet normal cells / reduction cells in the paper) that work well on many different image datasets. It's a very cool research result. But it's not something that will replace AI researchers.