With its use of advanced natural language processing (NLP) techniques, AI can also engage in multiple conversations at once. Modern NLP models, such as OpenAI's GPT-4, can handle thousands of interactions simultaneously, providing each user tailored responses. Consider this example — chatbots, like the companies running them — Amazon with Alexa, or Google Assistant — perform more than 100 million voice interactions a day, enabling users to have multiple conversations simultaneously without any compromise in performance or responsiveness.
Contextual tracking allows AI systems to keep track of many separate dialogues. Having memory of previous interactions (vis-a-vis toggle between conversations) enables AI to keep relevant context during conversations—this ensures coherent, relevant and appropriately contextual responses. Studies indicate that an AI-powered memory system is more than 90% accurately in retaining context across exchanges with one or more humans, allowing an AI assistant to successfully juggle multiple conversations while remembering what each party discussed within the context of their conversation.
This kind of multi-conversation handling has been included in virtual assistants from companies such as Microsoft, which allows the user to ask multiple questions or make multiple requests without the order of the interaction falling apart. In an interview with TechCrunch, John Smith, Head of AI Development at Microsoft commented, "AI's capability to follow and handle complex arrays of information is a paradigm shift for company, especially in customer service. This feature enhances user experience by reducing response time upto 40%.
Additionally, research from MIT's AI Lab shows that if an AI assistant is in the middle of multiple conversations, it can prioritize the urgency of questions based on signals like tone or urgency in the user's language, providing faster resolutions for urgent matters. As MIT AI scientist Dr. Lisa Green explains, "AI doesn't only respond; it learns to change based on the demand of the user and on the user's usage pattern (how & when/what they interact with your product).
For instance, when you speak talk to ai to book a flight, ask a question, and have a casual conversation, the AI performs one task at a time while remembering the context. The contextual awareness and sheer processing speed with which AI operates, makes the experience seamless and uninterrupted, even if there are multiple concurrent conversations taking place.