Neural language models, and an explanation of recurrent neural networks

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)…

Abstract: In this talk I’ll highlight several exciting trends in the field of AI and machine learning. Through a combination of improved algorithms and major efficiency improvements in ML-specialized hardware, we are now able to build much more capable, general purpose machine learning systems than ever before. As one example of this, I’ll give an…

Demystifying attention, the key mechanism inside transformers and LLMs.

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

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…

S07: Okay. Well, let’s get started. It’s a beautiful day out here in Washington State. The smoke has cleared a little bit so we can see the mountains again, and it’s very nice. I want to start right in with a demo, and what we’re going to do is we’re going to go through it…