Improving Chatbot Effectiveness using Large Language Models

Recent advancements in Natural Language Processing (NLP) have significantly improved the ability of chatbots to interact with humans in a natural and engaging way. As chatbots become more sophisticated, they are increasingly being integrated into various systems to provide personalized recommendations or assistance. However, there is currently no standard way to evaluate the effectiveness or clarity of a chatbot. Human evaluators are limited in their ability to test the chatbot's behaviour on specific topics of interest, leaving the field in need of more advanced evaluation methods.
The goal of this Challenge is to develop and test evaluation methods to benchmark chatbots, utilizing GPT-like advanced language models to imitate human evaluators. This project aims to improve chatbots' effectiveness and reliability as tools for businesses to engage with their customers.
The output will also include a two-hour workshop on Prompt Engineering, which covers both established and emerging techniques. The results of this Challenge have the potential to transform the way businesses interact with their customers and provide personalized experiences.

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Great work guys! ❤🎉🎉