Flexible Duplex

Flexible duplex systems aim to create more natural and efficient real-time interactions between humans and AI, particularly within the context of large language models (LLMs). Current research focuses on improving the efficiency of duplex models through techniques like parallel decoding, mixture-of-experts architectures, and specialized hardware designs to handle the computational demands of real-time processing. These advancements are significant because they enable more human-like conversational AI, reducing latency and improving user experience in applications ranging from customer service to information retrieval. Furthermore, research is exploring the application of duplex principles beyond LLMs, including in areas like graph embedding and wireless communication.