The surge in Edge AI applications has propelled the need for architectures that balance performance, power efficiency, and flexibility. Architectural choices play a pivotal role in determining the success of AI processing at the edge, with trade-offs often necessary to meet the unique demands of diverse workloads. There are… Read More
The global market for earphones and headphones in 2020 is estimated to have been $34B and is expanding at a compound rate of over 20% per year. Of this almost 50% is said to be earphones which are shifting rapidly to True Wireless Stereo (TWS). We have seen the sales of TWS devices grow from 1M units is 2016 to 109M units in 2019, though … Read More
TinyML is kind of a whimsical term. It turns out to be a label for a very serious and large segment of AI and machine learning – the deployment of machine learning on actual end user devices (the extreme edge) at very low power. There’s even an industry group focused on the topic. I had the opportunity to preview a compelling webinar about… Read More
Machine Learning (ML) has become extremely important for many computing applications, especially ones that involve interacting with the physical world. Along with this trend has come the development of many specialized ML processors for cloud and mobile applications. These chips work fine in the cloud or even in cars or phones,… Read More
