ChatGPT For Enterprise

The video discusses a common misconception about large language models (LLMs) like GPT, observed during master classes and boardroom sessions. Many people treat LLMs like simple tools such as calculators or apps, expecting perfect results from minimal input. However, the effective use of LLMs requires a different approach. These models perform better with more detailed engagement and information, understanding the user's context and the problem they are trying to solve. The video highlights that users often provide basic commands and expect flawless outputs, leading to disappointment when the results are not as expected. In contrast, those who provide detailed prompts and context receive more accurate responses. The key to success with LLMs is continuous engagement, where users iteratively refine their requests based on the model's responses. This process of adjustment and feedback leads to outcomes that closely match the user's initial intentions. The video emphasizes that this interactive and iterative approach is a significant departure from how people typically interact with technology, and understanding this difference is crucial for harnessing the full potential of LLMs.