Generative AI for Consumer Electronics: Enhancing User Experience with Cognitive and Semantic Computing

Chamola, Vinay; Sai, Siva; Sai, Revant; Hussain, Amir; Sikdar, Biplab

Abstract

Generative Artificial Intelligence(GAI) models such as ChatGPT , DALL-E , and the recently introduced Gemini have attracted considerable interest in both business and academia because of their capacity to produce material in response to human inputs. Cognitive computing is a broader field of machine learning that encompasses GAI, which particularly emphasizes systems capable of creating content, such as images, text, or sound, while semantic computing acts as a fundamental element of GAI, furnishing the comprehension of context and significance essential for GAI systems to generate content akin to human-like standards. GAI is becoming a game-changing technology for consumer electronics industry with a variety of applications that improve user experiences and product development. GAI can revolutionise architectural visualisation by facilitating quick prototyping and the investigation of cutting-edge design ideas. By creating unique compositions and graphics for a variety of applications, it also empowers media production and music composition. Our research identifies several applications of GAI in the consumer electronics industry. We analyze how GAI is utilized in augmented reality (AR) applications, optimizing user interactions and immersive experiences. Moreover, we explore the integration of GAI in voice assistants and virtual avatars, enhancing images, natural language understanding and delivering more personalized interactions. We present a novel case study on a Generative Artificial Intelligence-based Framework for answering consumer electronics queries. We have developed and presented the system using various GAI-based tools and integrations. The paper also discusses the challenges in implementing GAI in consumer electronics, such as ethical considerations, data privacy, compatibility with existing systems, and the need for continuous updates and improvements.

• Journal Article Type: Article
• Online Publication Date: Apr 10, 2024
• Deposit Date: May 16, 2024
• Publicly Available Date: May 16, 2024
• Journal: IEEE Consumer Electronics Magazine
• Print ISSN: 2162-2248
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1109/mce.2024.3387049
• Keywords: Consumer electronics, Speech recognition, Hidden Markov models, Chatbots, Solid modeling, Testing , Optimization