I was excited by the promise of Xnor.ai and its technique that drastically reduces the computing power necessary to perform complex operations like computer vision. Seems I wasn’t the only one: the company, just officially spun off from the Allen Institute for AI (AI2), has attracted $2.6 million in seed funding from its parent company and Madrona Venture Group.
The specifics of the product and process you can learn about in detail in my previous post, but the gist is this: machine learning models for things like object and speech recognition are notoriously computation-heavy, making them difficult to implement on smaller, less powerful devices. Xnor.ai’s researchers use a bit of mathematical trickery to reduce that computing load by an order of magnitude or two — something it’s easy to see the benefit of.
“Imagine what is possible if that style of computing could be done on the device in your hand, on your wrist, or in your car,” said Madrona’s managing director, Matt McIlwain, in a press release. I’m sure they’re all imagining very hard right now. “Machine Learning and AI have been a key investment theme for us for the past several years and bringing deep learning capabilities such as image and speech recognition to small devices is a huge challenge,” he added in a company blog post.
McIlwain will join AI2 CEO Oren Etzioni on the board of Xnor.ai; Ali Farhadi, who led the original project, will be the company’s CEO, and Mohammad Rastegari is CTO.
The new company aims to facilitate commercial applications of its technology (it isn’t quite plug and play yet), but the research that led up to it is, like other AI2 work, open source.