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A random idea: in this article, they talked about a Feature Store shared across teams. Feature extraction also seems a major bottleneck in their modeling. It se
by strin 9y ago
A random idea: in this article, they talked about a Feature Store shared across teams. Feature extraction also seems a major bottleneck in their modeling. It seems a very natural and valuable thing to have a platform to share "generic features".
Yann LeCun said once a deep neural network predicts many targets, say 1000 classes in ImageNet, it is possible for the model to learn quite generic features. So it makes sense to pre-train on a large amount of data and a reasonable number of targets, and then share the learned feature extractors with others.
Could this be a business? Or a community? Thoughts?
- Eridrus 9y agoPretrained models for generic things exist publicly, e.g. models trained on ImageNet, or pretrained word vectors. Not a whole lot of general use in having a feature extractor tuned to Uber's data.