The abundance of automation and tooling made it relatively manageable to scale designs in complexity and performance as demand grew.

However, the power being consumed by AI and machine learning applications cannot feasibly grow as is on existing processing architectures.

Where do we go from here?

New Mind explores.

Here’s an interesting tutorial on prepping image data for CNNs.

It is challenging to know how to best prepare image data when training a convolutional neural network. This involves both scaling the pixel values and use of augmentation techniques during both the training and evaluation of the model. Instead of testing a wide range of options, a useful shortcut […]