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- make it possible - make it work - make it efficient - make it dependable and invisible - move on to the next layer and never think about it again
In AI, we're at stage 0 (groundwork). In deep learning, I'd say we're still at the "make it efficient" stage, so efforts to make it invisible & fully-automated may be premature in my opinion. We still need the monthly power consumption of a village to "solve" CIFAR10 from scratch
Can you provide a context? We would like to know what you mean by dependable and invisible...
it's not a read-only tweet ?
- automate it after it's proved reliable
I think you generally need an explanation before you can even make it possible.
I also want to read - clearly and explicitly document every line
To embed quality control it must be formal.. Well said sir.
@fchollet for prime minister. Love this policy.
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