Chain of thought prompting is a method that enhances large language models by guiding them through step-by-step reasoning. This technique improves accuracy and transparency in problem-solving, making AI models more reliable. In this article, discover how chain of thought prompting works and why it’s a game-changer for complex tasks. Key Takeaways Understanding Chain of Thought […]
The most common way to communicate with the LLM when creating and testing prompts is through an API. A few parameters can be set to get different outcomes for your prompts. Finding the right settings for your use cases may require some trial and error, but tweaking these settings is crucial to enhancing the dependability […]
Prompt engineering is a relatively new field that creates and improves prompts so that large language models (LLMs) can be used and built with ease in a wide range of situations. Prompt engineering skills can help you learn more about what LLMs can and can’t do. They use prompt engineering to make LLMs safer and […]
Introduction to Prompts At the heart of interacting with an LLM is the concept of a prompt. A prompt is a question or instruction provided by the user, serving as a starting point for the model’s response. This natural language input could be as simple asking what actors have ever played Batman. It could also […]
