How to add Domain-Specific Knowledge to an LLM Based on Your Data

<h1>Introduction</h1> <p>In recent months, Large Language Models (LLMs) have profoundly changed the way we work and interact with technology, and have proven to be helpful tools in various domains, serving as writing assistants, code generators, and even creative collaborators. Their ability to understand context, generate human-like text, and perform a wide range of language-related tasks has propelled them to the forefront of artificial intelligence research.</p> <p>While LLMs excel at generating generic text, they often struggle when confronted with highly specialized domains that demand precise knowledge and nuanced understanding. When used for domain-specific tasks, these models can exhibit limitations or, in some cases, even produce erroneous or hallucinatory responses. This highlights the need for incorporating domain knowledge into LLMs, enabling them to better navigate complex, industry-specific jargon, exhibit a more nuanced understanding of context, and limit the risk of producing false information.</p> <p><a href="https://medium.com/towards-data-science/how-to-add-domain-specific-knowledge-to-an-llm-based-on-your-data-884a5f6a13ca"><strong>Read More</strong></a></p>