https://tmzh.github.io/tags/natural-language-interface/Recent content in Natural-Language-Interface on Ephemeral Dance Of ElectronsHugoen-usSun, 27 Oct 2024 12:00:00 +0000https://tmzh.github.io/post/2024-10-27-building-natural-language-interfaces-with-llm-function-calling/Sun, 27 Oct 2024 12:00:00 +0000https://tmzh.github.io/post/2024-10-27-building-natural-language-interfaces-with-llm-function-calling/<p>Large Language Models (LLMs) are good at generating coherent text, but they have few inherent limitations:</p> <ol> <li><strong>Hallucinations</strong>: They learn and generate information in terms of likelihood and may produce information that is not grounded in facts</li> <li><strong>Knowledge Cutoff</strong>: LLMs are trained on a fixed dataset and do not have access to real-time information or the ability to perform complex tasks like web browsing or executing code.</li> <li><strong>Abstraction and Reasoning</strong>: LLMs may struggle with abstract reasoning and complex tasks that require logical steps or mathematical operations. Their output is not precise enough for tasks with fixed rule-sets without interfacing with external tools</li> </ol> <p>There are two ways to address these limitations:</p>