Mint Primer | Why multiple chatbots are better than one
Mint explains: Systems that rely on more than one chatbot or use multiple Large Language Models (LLMs) are called multi-agent systems (MAS). A chatbot on the website of a bank, auto, insurance, edtech or any other company has improved over the years, thanks to advances in AI and natural language processing. But it still falls short of answering questions that might require more ‘human-like’ capabilities or pulling data from different domains.
The solution lies in using multiple bots or more than one AI (artificial intelligence) model—each with a different, specialized capability, and complementing each other to deliver a better response. Companies and users are getting better at deploying and interacting with virtual agents. Open AI’s release of an upgraded GPT4 offers improved handling of text, vision and audio, boosts AI capabilities, and opens up new possibilities.
Just as teams of humans are better in tackling complex problems, more than one chatbot will improve customer interactions. So, a Hindi language chatbot could combine with a math teaching bot and deliver math lessons in Hindi. Each is a separate LLM (which helps chatbots understand human input and offer answers) and is better at executing specialist tasks.
If a chatbot gets stuck, the query is usually escalated to a human agent. Merging capabilities of multiple bots or making different bots work together is the way out. Microsoft, Meta, Exotel, Tokyo-based Sakana and others are trying multiple bots.
A single bot can break down the task and give an answer but it may lag in response time and lack accuracy. That’s the future. As machines get better with more computational power and ability to comprehend context and emotions, there will be many specialized bots.
. Read more on livemint.com
