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12.05.19 Deep learning networks can require significant bandwidth and storage for intermediate computations, in addition to substantial computing resources. Network quantization to lower numerical precision can reduce the burden of intermediate results, but with a reduction in model accuracy that could in the past only be recovered by using the original training data set for additional training or fine tuning.
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
