What Is Retrieval-Augmented Generation and How to Make AI Work for You, with Guil Hernandez

🎙 About the episode Meet Guil Hernandez 🇺🇸! He is a developer and educator with over 15 years of experience in tech. He's also a Scrimba teacher who is a part of the team bringing you the AI Engineer Path, and in this episode, he's helping us understand retrieval-augmented generation. In the previous episode, Tom Chant helped us understand the world of AI models. Today, Guil will further teach us how these models work under the hood. AI models don't understand the world like we do. When we interact with them, they turn our inputs into mathematical representations known as embeddings. By creating our own embeddings, we can teach AI to do what we want it to. Today, we're getting an introduction about making a model aware of your own data source so that that data can be considered for the AI output. For example, using the techniques you'll learn from Gil in this episode, you could connect a model to your customer support conversations so that the model knows what is necessary to answer unique questions about your (or your client's) business. This is the third episode of our series on AI engineering, introducing Scrimba's AI Engineer Path. This path is your gateway to unlocking the full potential of AI for your projects. 🔗 Connect with Guil🐦 Twitter🌐  Website👩‍🚀 Github 🧰 Resources MentionedThe AI Engineer PathLearn Embeddings and Vector DatabasesScrimba Podcast with Saron Yitbarek ⭐️ Leave a Review If you enjoyed this episode, please leave a 5-star review here and tell us who you want to see on the next podcast. You can also Tweet Alex from Scrimba at @bookercodes and tell them what lessons you learned from the episode so that he can thank you personally for tuning in 🙏 Or tell Jan he's butchered your name here.