Big foundational models like GPT-4, Gemini, Claude, and Llama -- aka large language models or "LLMs" -- are awesome, but they are not experts in your business. They are also available to all of your competitors, so creating competitive advantage requires you to train your subject matter experts to get the most out of the AI and to augment your LLMs to be as relevant to your business as possible. One of the most effective ways to augment an LLM is with the addition of external signals, which are various types of real-world data and information that can be used to influence and improve the performance and relevance of LLMs. Let's take a high-level look at how external signals can transform LLMs, making them more relevant, responsive, and ultimately, more useful.
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