Apple buys Xnor.ai: an edge-based AI startup for reported $200 M

Xnor.ai started in 2017 from the Allen Institute for AI (AI2) which was a nonprofit entity, has been bought by Apple for about $200 million. A source close to the company verified a report this morning from GeekWire.

Apple has validated the reports with its regular statement for this sort of silent acquisition: “Apple buys smaller technology companies from time to time and we generally do not discuss our purpose or plans.” 

Xnor.ai’s Journey

Xnor.ai has begun its journey as a process for transforming machine learning algorithms highly efficient. So efficient, that the lowest tier of hardware could run those algorithms, things such as embedded electronics in security cameras that use only a shred of power. Yet by utilizing Xnor’s algorithms, they could execute tasks like object recognition, which in other aspects might need a stronger processor or connection to the cloud.

Ali Farhadi, the company’s CEO along with his founding team assembled the company at AI2 and spun it out just before the organization formally released its incubator program. It has raised $2.7M in early 2017 and $12M in 2018; both of the rounds were led by Seattle’s Madrona Venture Group, and have carefully widened its local operations and areas of business.

The source pointed out, that the $200M acquisition price is only an estimated amount. However, even if the actual number is smaller than half the estimated figure, it would be a big return for Madrona and other investors.

The company will likely move to Apple’s Seattle offices; GeekWire, visiting the Xnor.ai offices (in inclement weather, no less), reported that a move was underway. AI2 confirmed that Farhadi is no longer working there, but he will retain his faculty position at the University of Washington.

Apple focusing on Edge Computing

Apple acquiring the company makes complete sense when one observes the company’s efforts in directing its focus towards edge computing. With a chip devoted to running machine learning workflows in several kinds of situations, Apple clearly wishes for its devices to work without the help of the cloud for tasks such as facial recognition, augmented reality and natural language processing. The chip is dedicated to improving performance rather than privacy protocols.

Especially, its camera software makes thorough use of machine learning algorithms for capturing images as well as processing them; a compute-heavy work that could possibly be made much easier with the integration of economizing Xnor’s techniques. Code is the future of photography so that people can execute more of it; moreover, it consumes less time and power than orthodox methods.

It could also point to new attempts in the smart home. HomePod Apple has made potential steps towards the concept. However, Xnor’s technology is highly adaptable and as such rather difficult to predict as far as what it offers for such a big company as Apple.

Hello, I’m Anna Yeo. If you like my news coverage, please drop a good word in my inbox. I’m journalist by profession and have been part of many major reporting across the globe. I like to write crisp and factual news. I have completed my masters degree in journalism. Feel free to contact me at [email protected]

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