SKT's new AI chip changes the company's AI semiconductor business vision

The SAPEON X220 is designed to process artificial intelligence tasks faster, using less power by efficiently processing large amounts of data in parallel. Its deep learning computation speed is 6.7 kilo-frames per second, as a comparison that is about 1.5 times faster than that of GPUs that are widely being used by AI-service companies. At the same time, the company says it uses 20% less power than GPU by consuming 60 watts of energy and is about half the price of a GPU. From next year, the company will apply SAPEON X220 to its AI service NUGU to improve the voice recognition capability. The new chip will also be utilised by SKT’s affiliate companies. For instance, ADT Caps will apply the chip to enhance the performance of its AI-based video monitoring service named T View. In addition, SAPEON X220 will be applied to the cloud server of the next-generation media platform of Cast.era, a joint venture of SKT and Sinclair Broadcast Group. SKT will also provide the AI chip to enable AI-based projects promoted under the Korean New Deal Initiative put forth by the Korean Government. The company aims to generate synergies by combining AI semiconductor chips and 5G edge cloud. With this the company aims to provide high-quality AI services with ultra-low latency regardless of customer device. The major change, or rather addition, to the company's vision is that it aims to go beyond just providing the AI chip to data centers by actively promoting the AI as a Service (AIaaS) business. It will offer a complete solution package as a service by combining its AI chip and AI software, including diverse AI algorithms for features like content recommendation, voice recognition, video recognition and media upscaling, along with Application Programming Interfaces (APIs). For instance, an over-the-top (OTT) service provider wanting to adopt an AI-based content curation service will be able to easily implement the service by simply using SKT’s solution that comes with all that is needed, from high-performance data center applied with AI chip to AI-based software like content recommendation algorithm and APIs.