Ontario-based DarwinAI, founded by a team from the Ontario-based university, provides a platform for developers to generate slimmed-down models from neural networks. This offers a quicker way for developers to spin out multiple networks with smaller data footprints.
The company’s lean models are aimed at businesses developing AI-based edge computing networks to process mountains of sensor data from embedded systems and mobile devices.
Industries of all stripes — autonomous vehicles, manufacturing, aerospace, retail, healthcare and consumer electronics — are developing next-generation businesses with AI computing at the edge of their GPU-powered networks.
It’s estimated that by 2025 some 150 billion machine sensors and IoT devices will stream continuous data for processing.
Yet many find that talent and computing resources run high to build these various models.
DarwinAI’s position is that companies can reduce development time and costs — like DarwinAI did for themselves — by using its platform to spin out compact models from full-sized ones [Read more].