New algorithm Quiet-STaR significantly improves accuracy and human-like communication of chatbotsAI breakthrough: Chatbots now able to consider multiple responses before answering. Credit: techxplore.com

A new partnership between AI experts at Stanford University and Notbad AI Inc. has yielded an innovative algorithm that allows chatbots to consider different responses before delivering a final answer. This breakthrough has been documented in a paper published on the arXiv preprint server, detailing the success of the new approach when implemented with an existing chatbot.

Until now, chatbots have typically relied on training data to formulate responses to user queries. However, this approach does not allow for contemplation of multiple potential answers before choosing the most appropriate one. The team's algorithm, named Quiet-STaR, addresses this limitation and promises to significantly enhance the accuracy and human-like communication of chatbots.

Rather than simply blurting out an answer, Quiet-STaR prompts chatbots to generate multiple responses to a query and then compares them to determine the most suitable one. The algorithm also has the ability to learn and improve its decision-making process over time.

To assess the effectiveness of their innovation, the researchers incorporated Quiet-STaR into the Mistral 7B chatbot and tested it on a standard reasoning test. The results showed a notable improvement, with the chatbot achieving a score of 47.2% compared to just 36.3% without the algorithm. It also performed well on a math test.

The team believes that their algorithm could be easily integrated into any existing chatbot, though this would need to be done by the developers. They suggest that this could greatly enhance the accuracy and overall performance of chatbots.

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