These measurements are indispensable for tracking the results of your chatbot, identifying any stumbling blocks and continuously improving its performance. But which metrics should you choose?
Build document-based question-answering systems using LangChain, Pinecone, LLMs like GPT-4, and semantic search for precise, context-aware AI solutions.
There are currently few datasets appropriate for training and evaluating models for non-goal-oriented dialogue systems (chatbots); and equally problematic, there is currently no standard procedure for evaluating such models beyond the classic Turing test.
The aim of our competition is therefore to establish a concrete scenario for testing chatbots that aim to engage humans, and become a standard evaluation tool in order to make such systems directly comparable.
Brand new... good for you! "To endow computers with common sense is one of the major long-term goals of Artificial Intelligence research. One approach to this problem is to formalize commonsense reasoning using mathematical logic."