Securing Business Automation with Large Language Models: Privacy and Risks

Large Language Models (LLMs) can generate human-comprehensible content (text or figures) based on user queries. Building an accurate LLM (such as GPT-4, LLaMA, or BLOOM) requires vast resources in terms of data and computational cost. Often, constructing an LLM can be outsourced to a third party to overcome such cost and infrastructure burdens. Several companies now offer…

A business owner can leverage a third-party-built LLM by contextualizing it with local data generated from day-to-day business operations. Methods such as fine-tuning [1] and Retrieval Augmented Generation (RAG) [2] can be used for this purpose. In RAG, the…