Xnor.ai, spilled in 2017 from the Allen Institute for non -profit for AI (AI2), was acquired by Apple for around 200 million dollars. A source close to the company has corroborated A geekwire this morning report for this purpose.
Apple has confirmed relations with its standard declaration for this type of silent acquisition: “Apple buys smaller technological companies from time to time and we generally do not discuss our goal or our plans.” (I asked for clarifications in case.)
Xnor.ai started as A process to make automatic learning algorithms very effective – so effective that they could operate even on the lowest level of equipment, things like electronics integrated into security cameras which only use a minimum of power. However, using Xnor algorithms, they could accomplish tasks such as object recognition, which in other circumstances may require a powerful processor or connection with the cloud.
The equipment has the size of the size of the size of the size of XNOR redefine the edge
CEO Ali Farhadi and his founding team gathered the company to AI2 and returned it just before the organization officially launched its incubator program. He collected $ 2.7 million at the start of 2017 and 12 million dollars in 2018, the two rounds led by the Madrona Venture group in Seattle, and has continued to develop its local operations and its areas of activity.
The acquisition price of $ 200 million is only approximate, said the source, but even if the final number was less than half, it would be a comeback for Madrona and other investors.
The company will probably move to Apple offices in Seattle; Geekwire, visiting the Xnor.ai offices (in bad weather, no less), reported that a move was clearly in progress. AI2 has confirmed that Farhadi is no longer working on it, but he will keep his position as a professor at the University of Washington.
An Apple acquisition is perfectly logical when you think about how this company directed its efforts to the Edge accounts. With a chip dedicated to the execution of automatic learning workflows in a variety of situations, Apple clearly intends that its devices work independently of the cloud for tasks such as facial recognition, natural language treatment and augmented reality. It is as much for performance as confidentiality.
Its camera software particularly uses automatic learning algorithms for the capture and processing of images, a heavy calculation task that could potentially be much lighter with the inclusion of XNOR economy techniques. The future of photography is the codeAfter all – so you can execute, and the less time and power it takes to do it, the better.
This could also indicate new incursions in the smart house, with which with Homepod, Apple has made temporary steps. But Xnor’s technology is very adaptable and, as such, quite difficult to predict with regard to what it allows for a company as large as Apple.