07
Aug
AI chatbots and virtual assistants have become increasingly popular in recent years thanks the breakthroughs of large language models (LLMs). Trained on a large volume of datasets, these models incorporate memory components in their architectural design, allowing them to understand and comprehend textual context. Most common use cases for chatbot assistants focus on a few key areas, including enhancing customer experiences, boosting employee productivity and creativity, or optimizing business processes. For instance, customer support, troubleshooting, and internal and external knowledge-based search. Despite these capabilities, a key challenge with chatbots is generating high-quality and accurate responses. One way of solving this…
