Developing AI Models
Turning an AI model into an expert in your domain can be done in several layered steps depending on how much control you have over the model and what resources you have available. Here’s a breakdown from light customization to deep-level training (for developers and organizations): 1. Define Your Domain and Use Cases Clearly First, you need to narrow the scope of expertise: What specific knowledge area? What tasks do you want the AI to perform expertly? This clarity shapes the kind of data and examples you’ll feed it. 2. Teach the Model Through Interaction (Light Customization) For models like ChatGPT , you can: Feed it structured examples — and say, “Use this structure for all future responses.” Refine responses iteratively — correct its tone, accuracy, or style over time. Each correction acts like incremental fine-tuning through context learning. Use “memory” features (like mine) to persist your domain rules and preferences. This approach gradually makes the AI “...
.png)