Compression is a universally useful problem. It is very connected to learning, specifically ML, since you have to understand your data and model it in order to compress it.
If you own a private cloud, placing VN24 compression endpoints would reduce the overall expected data sent. This is useful for learning problems where the data is massive to the point of being intractable without high cost infrastructure.
compression endpoint Offline:
- convolutional autoencoder (non-linear SVD)
- SVD
- VN24 #1
Online:
- clustering/ quantization
- VN24 #2
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