Generative Artificial Intelligence (GenAI) based on Large Language Models (LLMs) is moving swiftly from hype to tangible reality in maximising business value. By creating efficiencies and stimulating revenue growth, GenAI has assertively secured a place on executive agendas.
However, integrating LLM’s into business processes is never easy and fraught with challenges. Model safety & ethical concerns top this list, and a noteworthy challenge is that of model accuracy. Model inaccuracies surface through hallucinations, and these accuracy gaps can lead to a rapid loss of business trust and adoption while also potentially causing unforeseeable outcomes. Be it the non-existent historical legal decisions brief generated by GenAI in the Avianca airlines Lawsuit case (here) or the false claims of serving prison term made by GenAI in the Australian mayor case (here), it is quite evident that hallucinations can cause major erosion to business value.
So how do you build trust in GenAI and improve the accuracy of LLMs? The answer to this accuracy challenge lies in using Reliable Data and Leveraging Smart Technologies like Knowledge Graphs.