Apple Will Use Xnor.ai’s AI Chip Technology to Strengthen its Competitive Edge vis-à-vis Amazon, Microsoft, and Google

Summary Bullets:

• Apple will use the recently acquired Xnor.ai’s technology to enhance the AI and data processing capabilities of a range of products, including its cameras and HomeKit smart home system.

• To succeed against rivals such as Google, Apple will need to develop AI device capabilities that deliver additional functionality and value for its customers.

Apple’s recent US$200 million acquisition of Seattle-based Xnor.ai makes it the latest in a growing number of companies that are targeting the opportunities associated with AI and edge computing. Apple’s acquisition of Xnor.ai will potentially help it challenge the hyperscale cloud providers, Amazon Web Services, Microsoft Azure, and Google Cloud, all of which are focused on harnessing the benefits of AI and edge computing, and which compete against Apple in several product and service segments – including streaming media, virtual assistants, smart speakers, and tablets.

One goal of edge computing is to enable and support digital services and applications that require high levels of performance and low latency, including things like autonomous vehicles, HD video and immersive content. Edge computing technologies can be deployed in multiple locations, including secondary and tertiary data centers, factories and retail outlets, and telecom network operator base stations. In particular, there is a growing interest in the so-called “device edge” and the potential to leverage advanced data processing capabilities and sophisticated AI algorithms within portable devices such as smartphones, watches, and headphones, or within home, factory, or store equipment fitted with Internet-connected sensors. The advantages of processing data and applying AI within the device itself include higher levels of service performance, significantly lower latency, and the avoidance of network usage costs associated with transporting data to be processed within cloud data centers.

Combining edge computing with AI technologies such as machine learning (ML) unlocks opportunities to offer a wide range of new applications, including those that leverage image analytics, audio analytics, and motion or environmental sensor analytics. Leveraging Xnor.ai’s processor technology, Apple could enhance the existing AI capabilities of services such as its Siri virtual assistant, or introduce AI capabilities to additional products and services, ranging from cameras and watches to its HomeKit smart home system. Notable strengths of Xnor.ai’s processors include their lower energy consumption compared with Apple’s current AI device processers. They also include their use of solar power, which helps to alleviate the drain on device battery power that invariably comes with service consumption. Apple could therefore use Xnor.ai’s technology to build more processing and AI into its devices, without that having a negative impact on their battery life.

Apple needs to extend the use of AI across its products and service portfolio if it wants to remain competitive in a fast-changing and highly competitive market. Going forward Apple will face significant competition from Google, whose Edge TPU is a lightweight version of the ML technology Google uses within its cloud data centers. Edge TPU allows Google to bring ML capabilities to a range of end user devices, including smartphones, smart watches, digital cameras, and digital media players. As Apple focuses on building greater AI and edge computing functionality into its devices, it will also compete against products that leverage AI processors from companies like Intel, NVIDIA, Qualcomm, and Xilinx. In order to succeed, it is therefore imperative that Apple differentiates, not only with its device and service capabilities, but also with its use of AI to deliver additional functionality and value for its customers.

 

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