To get the most out of LLMs, you need three key elements working together:
- Context: Define the problem or task clearly. For example, if you’re using an LLM for customer support, train it on FAQs and common customer questions.
- Knowledge: LLMs thrive on high-quality data. The better the data they’re trained on, the more accurate and useful they’ll be. Companies can even add specific knowledge to fine-tune open-source models.
- Tools: Pick the right platform or tool for deploying and managing your LLM. If privacy is a concern, go with an open-source option you can host yourself. If you want ease, try a ready-made service like ChatGPT.
Takeaway Tooltip: Think of LLMs as cars—context is the driver, knowledge is the fuel, and tools are the dashboard!
Illustration Idea: A “three-gear” graphic showing “Context,” “Knowledge,” and “Tools” working together to power a productive AI system.