Attention in transformers, visually explained | DL6

In a society that is confronting the new age of AI in which LLMs begin to display aspects of human intelligence, understanding the fundamental theory of deep learning and applying it to real systems is a compelling and urgent need. This panel will introduce some new simple foundational results in the theory of supervised learning….

This video on the Artificial Intelligence full course video cover all the topics you need to know to become a master in AI and ML. It covers all the basics of Machine Learning, the different types of Machine Learning, and the various applications of Machine Learning used in different industries. This video will also help…

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

To learn more, I highly recommend the book by Michael Nielsenhttp://neuralnetworksanddeeplearning….The book walks through the code behind the example in these videos, which you can find here:https://github.com/mnielsen/neural-ne… MNIST database:http://yann.lecun.com/exdb/mnist/ Also check out Chris Olah’s blog:http://colah.github.io/His post on Neural networks and topology is particular beautiful, but honestly all of the stuff there is great. And if…

https://www.youtube.com/watch?v=9-Jl0dxWQs8 AI Alignment forum post from the Deepmind researchers referenced at the video’s start:https://www.alignmentforum.org/posts/… Anthropic posts about superposition referenced near the end:https://transformer-circuits.pub/2022…https://transformer-circuits.pub/2023… Some added resources for those interested in learning more about mechanistic interpretability, offered by Neel Nanda Mechanistic interpretability paper reading listhttps://www.alignmentforum.org/posts/… Getting started in mechanistic interpretabilityhttps://www.neelnanda.io/mechanistic-… An interactive demo of sparse autoencoders (made…

Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer. This Python course teaches you how to use RAG to combine your own custom data with the power of Large Language Models (LLMs). 💻 Code: https://github.com/langchain-ai/rag-from-scratch ⭐️ Course Contents ⭐️⌨️ (0:00:00) Overview⌨️ (0:05:53) Indexing⌨️ (0:10:40) Retrieval⌨️ (0:15:52) Generation⌨️ (0:22:14)…