Knowledge management using large language models in sugar industry

The sugar industry faces the dual challenge of an aging workforce and the pressing need to digitize operations for enhanced efficiency. The traditional knowledge, accrued over decades, risks being lost if not effectively transferred to the newer generations, while the industry's moderniza-tion beckons a digital overhaul. Harnessing Large Language Models (LLMs) like Llama3, Gemma2, and GPT-4o for Retrieval Augmented Generation (RAG) emerges as a viable solution to address these challenges. By encapsulating the veteran expertise in a digital framework and making it read-ily accessible through RAG, a seamless knowledge transfer is facilitated. Concurrently, the digitalization of operational processes is accelerated, fostering a culture of data-driven decision-making and innovation. The application of LLM for RAG not only ensures the preservation and accessibility of critical industry knowledge but also positions the sugar industry on a modernization trajectory, promising enhanced operational efficiencies, sustainability, and a competitive edge in the evolving market landscape.