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Updated Jun 30, 2018
Bringing artificial intelligence technology to the masses is no easy task; doing so takes a ton of computing and processing power, which is why it’s difficult to equip personal devices like smartphones with AI capabilities.
Xnor.ai, a Seattle start-up spun off of the Allen Institute for AI, has established commercial proof that they can enable sophisticated AI on simple, low-cost devices at scale, working with partners to provide low-cost, low-power AI monitoring devices.
Along its journey, Xnor has partnered with GenUI to bring its vision to life. Here’s how.
App to enable AI on home monitoring device
One of Xnor’s earliest partners was Wyze, whose WyzeCam home security user base wanted fewer push notifications of motion detection, specifically only those related to person detection. In other words, only alert camera owners when a person enters their home, not something like a fly.
The first step to achieving that objective was to build Xnor’s AI technology into a mobile app that allowed for object detection of images, separating people from other objects. Xnor’s machine-learning engineers collaborated with GenUI’s iOS engineers to prototype an app on the iPhone, which was published to the AppStore and later integrated into WyzeCam’s mid-year 2019 release to over 1.2 million users. Person detection is now one of WyzeCam’s most appreciated features.
App to tell the Xnor AI story
Xnor then asked GenUI to help prepare them for the all-important Consumer Electronics Show (CES) just a couple of weeks away by building an app to effectively tell the Xnor story.
GenUI helped to unify random apps, fix bugs, improve collaborative storytelling, curate experiences and visibly demonstrate how Xnor is overcoming the difficult challenges in deploying edge-based AI computing (particularly as compared to cloud computing).
SDK for Developers to apply SI to edge technology Lastly, Xnor turned to GenUI to build a self-service software development portal (Software Development Kit), dubbed AI2GO, for developers interested in applying AI to edge technology.
The portal offers pre-tuned models based on speed and memory footprint across a number of hardware targets; a benchmarking tool that helps developers gauge the performance of their models; and a set of samples (counters, visualizers, etc.) available in Python, C and Swift.
“GenUI were an absolute joy to work with. From kick-off to hand-off they brought a level of creativity, attention to detail, and communication that allowed us to not only meet our deadlines but celebrate them as incredible successes. I can’t recommend GenUI and their talented team highly enough.” Sophie Lebrecht, SVP Strategy and Operations
As the second spinoff of the Allen Institute for Artificial Intelligence (early 2017), Xnor develops state-of-the-art, on-device AI solutions that enable businesses to make real-time decisions, deliver more efficient experiences to customers, and create revenue opportunities that never existed before. It’s mission is to make AI accessible by freeing it from the cloud, data centers and the limits of internet connectivity.
Xnor helps organizations add AI functionality to their products, powering a new generation of smart solutions for existing and new markets. Xnor’s patented edge AI technology has upended traditional AI, resulting in billions of devices and products being AI-optimized – from battery-operated cameras to complex manufacturing machinery like automobiles.
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