Together AI’s Post

Transcript

Retrieval, augmented generation, or simply RAG has rapidly become the most widespread approach to improving the performance and abilities of large language models for enterprise usage. My name Zen Hassan and I'm excited to be your instructor. As an AI engineer and educator, I've spent most of the last decade building AI powered applications and teaching developers how to build their own. Whether you want to build a personal assistant that knows about your calendar or dietary restrictions or. Help your company launch a customized chat bot that can confidently speak about your product. You'll need to give your LLM access to specialized information. RAG solves this problem by pairing a large language model with a database of trusted information that can be used to help answer domain specific questions and generate responses. Once you start looking for it, you'll see that RAG is powering many of the tools you use every day, from AI summaries at the top of web searches to the highly capable code agents built into modern Ides. Connecting LLNS with up to date and personalized data is enabling previously impossible experiences in a huge variety of industries. This course is designed for people who are already comfortable reading and writing code, but you don't need any previous experience with AI technology. Whether you want to lead the launch of a new rag based product at work or are generative AI enthusiasts looking to better understand the AI tools you use every day, you'll leave this course with the theoretical foundations and the hands on experience. We need to get the most out of retrieval augmented generation.