technotes.

  In prompt engineering, Level 1 involves crafting simple and direct instructions or queries for the model. Users interact with the language model by providing specific prompts, and the model generates responses based on the input it receives. Level 2 refers to a more advanced or nuanced stage in the development of prompts for language models like GPT, Bard, etc. At this level, it implies a deeper understanding of how to fine-tune prompts for more complex tasks. This involves using techniques beyond basic prompt formulation, such as leveraging the model's capabilities to handle multi-step instructions, infer implicit context, or generate creative outputs.  Some important techniques :  Contextual Input and Explicit Instruction Multi-Turn Conversations and Context Management Task-Specific Optimization Creative Prompt Formulation Iterative Refinement and Evaluation Ethical Considerations and Bias Mitigation Handling Ambiguity and Edge Cases   Contextual Input an...

 What is prompt engineering ?   Prompt engineering refers to the practice of carefully crafting input prompts or instructions given to a generative AI model to guide its output in a desired direction. It involves choosing words, structuring sentences, and providing context in a way that influences the behavior of the model and helps achieve specific outcomes. Prompt engineering is crucial for effectively using generative AI systems, such as language models, to produce outputs that meet particular criteria or address specific tasks. Generative AI refers to a category of artificial intelligence systems that have the capability to generate new, original content, often in the form of images, text, or other types of data. These systems use machine learning techniques to understand patterns and structures in the data they are trained on and then generate new data that resembles that training data. The goal is to create content that is not directly copied but is in...