We have written much about large-scale deep learning implementations over the last couple of years, but one question that is being posed with increasing frequency is how these workloads (training in ...

Deep learning is rapidly ‘eating ... most programmers are not able to successfully modify machine-learning systems without substantial specialized training. Even highly trained data scientists ...

However, training deep learning models requires a great deal of computing power. Another drawback to deep learning is the difficulty of interpreting deep learning models. The defining ...

High-Level Workflow for Personalization with ONNX Runtime (source: Microsoft). "As opposed to traditional deep learning (DL) model training, On-Device Training requires efficient use of compute and ...

When it comes to training deep learning models, NVIDIA may be getting all the attention. However, Intel is not sitting quietly, just staring at the massive AI opportunity. It is moving fast in ...