Solving Critical Real-World Business Challenges - NEC's Industrial Research Model in the AI Era

摘要

NEC is the leading ICT technology provider in the B-to-B market and is actively integrating cutting-edge technologies into its business solutions to drive innovation, enhance capabilities, and create new value for its customers in a broad spectrum of industrial segments. And the recent business focus of NEC is to support digital transformation of business processes of customer enterprises by leveraging technical capabilities in AI, Cyber Security and Communication. This keynote discusses the specific role of NEC's Research in such a business context by sharing a variety of generative and multimodal AI-related use cases that are aimed at solving critical customer challenges in the real-world. From the multimedia perspective, the topics will include world-leading facial recognition technology for security boost and enhanced customer experience, development of drive-recorder video analytics for insurance adjusters leveraging visual language model (VLM) and medical document generation AI service for genuinely supporting overworked clinical doctors. Meanwhile, distributed acoustic sensing technology using optical fiber cables is opening a new opportunity for infrastructure and incident monitoring solutions after integration with AI and ML algorithms. As the common denominator, our commitment of solving critical customer challenges requires (and justifies) nurturing both world-class excellence in performing academic research and accumulated experience and/or culture of application-oriented technology refinement as well as technology combination to ensure business-ready practicality. Also, being the industrial research organization, we are engaged at the forefront of customer co-creation and co-design that play an indispensable role in pinpointing customer's critical challenges. These expertise and practices are indeed the core ingredients of NEC's Research for creating new business opportunities from the technology innovation approach. Furthermore, we also envision that such an industrial lab model in the Generative AI era will become the driver of a new technology paradigm - industry segment-oriented customizable foundation models and business transforming Agentic AI framework.