Prompt Engineering Tutorial – Master ChatGPT and LLM Responses

Chapters0:00 Introduction1:54 Neural N-Gram Models6:03 Recurrent Neural Networks11:47 LSTM Cells12:22 Outro

What is generative AI? Not sure where to begin? Check out this short course! We’ll take you through the basics of generative AI including common applications, model types, and the fundamentals of how you can use it. Discover the power behind this technology and see how it’s changing the way we solve problems, and tell…

This is the last of a series of 3 videos where we demystify Transformer models and explain them with visuals and friendly examples. 00:00 Introduction01:50 What is a transformer?04:35 Generating one word at a time08:59 Sentiment Analysis13:05 Neural Networks18:18 Tokenization19:12 Embeddings25:06 Positional encoding27:54 Attention32:29 Softmax35:48 Architecture of a Transformer39:00 Fine-tuning42:20 Conclusion

Attention mechanisms are crucial to the huge boom LLMs have recently had.In this video you’ll see a friendly pictorial explanation of how attention mechanisms work in Large Language Models.This is the first of a series of three videos on Transformer models. https://www.youtube.com/watch?v=OxCpWwDCDFQ

Oct 9, 2024As LLMs are being integrated into more and more applications, security standards for these integrations have lagged behind. Most security research either focuses 1) on social harms, biases exhibited by LLMs, and other content moderation tasks, or 2) zooms in on the LLM itself and ignores the applications that are built around them….

This is the second of a series of 3 videos where we demystify Transformer models and explain them with visuals and friendly examples. 00:00 Introduction01:18 Recap: Embeddings and Context04:46 Similarity11:09 Attention20:46 The Keys and Queries Matrices25:02 The Values Matrix28:41 Self and Multi-head attention33:54: Conclusion