Navigating Azure Open AI: the Art of Effective Prompt Engineering

Welcome to my blog! I am excited to share insights and knowledge about prompt engineering, a fascinating field at the intersection of language and technology. Through my recently completed course, I have delved into the art of crafting precise and effective prompts to harness the power of AI models. Join me on this journey as we explore the nuances of prompt engineering and its impact on shaping intelligent outputs.

It is somewhat acceptable that people are losing jobs because of AI or automation, but there exists some rise of new roles such as prompt engineer, Annotator, etc. As a part of learning the new technologies, I found prompt engineering was sounding interesting and it is how I started learning this course.

What is Prompt Engineering?

Prompt engineering involves skilfully crafting input instructions to guide LLMs (large language models) in generating accurate and contextually fitting outputs. This practice requires a deep understanding of language nuances and model capabilities to ensure effective and relevant responses. Effective prompt engineering combines linguistic finesse with an awareness of AI model behaviour for optimal outcomes.

Open AI and Azure Open AI

Open AI is a group that makes smart computer programs which understand and write in human language. They made GPT, a special program that's good at talking and understanding what people say. Open AI wants to make sure these programs help everyone and are safe to use. 

Azure Open AI refers to the integration of Open AI's artificial intelligence technologies, particularly its language models like GPT, into Microsoft's cloud computing platform called Microsoft Azure. This collaboration allows developers and businesses to easily access and use Open AI's advanced AI capabilities within the Azure ecosystem. It enables users to build applications, tools, and services that can understand and generate human-like text, enhancing various tasks such as chatbots, content creation, language translation, and more, all within the Microsoft Azure environment.

Git Repo:

Here is the reference for learning the course of "Azure Open AI & Prompt Engineering Zero to Hero with ChatGPT”: https://github.com/Azure-Samples/openai

 

If you are a Rookie here is basic intro for the models that you can master through Azure Open AI:

Davinci: Most capable GPT-3 model. Can do any task the other models can do, often with higher quality. This feature enables the user to give less instructions and get maximum throughput from prompts.

Curie: Very capable, but faster and lower cost than Davinci. It can be used as a general chatbot that can answer your queries.

Ada: This is also like that of Curie but mainly used in classification purposes and parsing the texts.

Babbage: Capable of straightforward tasks, very fast, and lower cost. It accepts up to 2000+ tokens. Tokens are nothing but the chunk of characters or simply words.

Codex: Open AI Codex, a remarkable AI creation by Open
AI, possesses the unique ability to understand human language and translate it into code. This advanced model powers GitHub Copilot, an innovative programming tool integrated with select IDEs such as Visual Studio Code and Neovim, revolutionizing the coding process. Derived from the renowned GPT-3 model, Codex has been fine-tuned for programming tasks.

 

Location: Machilipatnam, Andhra Pradesh, India

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