Machine Learning Silicon Isn't One Size Fits All

These days, just about everyone in the technology industry is talking Artificial Intelligence (AI) and Machine Learning (ML). There's a huge amount of excitement and a rush to be the first to get it right. What you might have noticed in this dialogue is that almost everyone is talking big, powerful, Neural Network accelerators as an essential part of bringing ML to life on your device – and whilst it's true that they have a significant role to play, they're just one part of the story. Early ML was performed in the cloud with very large data sets, making significant processing power an absolute essential, but today – particularly in the mobile and smart device sectors – the focus is shifting to what can be achieved at the edge. There are a number of reasons for this shift, not least latency, reliability and responsiveness – factors that are of considerable importance to the consumer.