Prompt Engineering Tutorial – Master ChatGPT and LLM Responses

Get ready for a showdown between LangChain and LangGraph, two powerful frameworks for building applications with large language models (LLMs.) Master Inventor Martin Keen compares the two, taking a look at their unique features, use cases, and how they can help you create innovative, context-aware solutions.

For more information about Stanford’s Artificial Intelligence programs visit: https://stanford.io/ai https://www.youtube.com/watch?v=Bl4Feh_Mjvo To follow along with the course, visit:https://cs229.stanford.edu/syllabus-s… Tengyu MaAssistant Professor of Computer Sciencehttps://ai.stanford.edu/~tengyuma/ Christopher RéAssociate Professor of Computer Sciencehttps://cs.stanford.edu/~chrismre/

An introduction to language modeling, followed by an explanation of the N-Gram language model! Sources (includes the entire series): https://docs.google.com/document/d/1e… Chapters0:00 Introduction1:39 What is NLP?2:45 What is a Language Model?4:38 N-Gram Language Model7:20 Inference9:18 Outro

LangChain became immensely popular when it was launched in 2022, but how can it impact your development and application of AI models, Large Language Models (LLM) in particular. In this video Martin Keen shares an overview of the features and uses of LangChain.

Demystifying attention, the key mechanism inside transformers and LLMs.

The attention mechanism is well known for its use in Transformers. But where does it come from? It’s origins lie in fixing a strange problems of RNNs. Chapters0:00 Introduction0:22 Machine Translation2:01 Attention Mechanism8:04 Outro