Navigating Generative AI: Practical Use Cases and Beyond for Traditional Data Scientists (1)
A Comprehensive Guide to OpenAI, Azure, LangChain, and RAG Techniques
1. Introduction
I am writing this post because I believe Generative AI will ultimately compete with human output, playing roles such as that of data scientists.
The introduction of OpenAI’s ChatGPT in 2022 serves as a typical example, showcasing strong capabilities in Artificial General Intelligence (AGI). The growth of generative AI tools, including OpenAI, LLaMA, and Mistral, marks a significant evolution in the field, despite its early stage and many challenges. This progress reminds us of a future where businesses across various sectors leverage Generative AI for comprehensive tasks, such as custom content creation, data analysis, and predictive modeling, prompting a worrying question: what new roles and challenges await data scientists?
Before 2023, I was a traditional senior data scientist. However, the occurrence of ChatGPT by OpenAI in November 2022 provided me the chance to transition into a generative AI-focused data scientist. Since March of the same year, I have been deeply engaged in learning about Generative AI and understanding the use of APIs from OpenAI, Azure OpenAI, and Mistral LLM, along with LangChain and RAG techniques…
