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.
Check out how large language models (LLMs) and generative AI intersect to push the boundaries of possibility. Unlock real-world use cases and learn how the power of a prompt can enhance LLM performance. You’ll also explore Google tools to help you learn to develop your own gen AI apps. https://www.youtube.com/watch?v=RBzXsQHjptQ https://www.youtube.com/watch?v=RBzXsQHjptQ
Ready to launch your vector search game? 🚀 Ditch your traditional keywords and discover the power of vector search! This video will help you discover ways users can make search smarter, and generate creative text along the way. Get hands-on with vector search on Vertex AI! Jump directly to the topics you want to learn:00:00…
This video on the Artificial Intelligence tutorial will make you learn in detail about the different concepts involved in AI. You will understand the basics of AI and get an idea about Machine Learning and Deep Learning with hands-on demo in this Artificial Intelligence full course. You will look at how to become an AI…
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 CS50, Harvard University’s introduction to the intellectual enterprises of computer science and the art of programming. TABLE OF CONTENTS 00:00:00 – Welcome00:01:01 – Introduction00:03:13 – Image Generation00:08:23 – ChatGPT00:11:06 – Prompt Engineering00:12:40 – CS50.ai00:19:03 – Generative AI00:22:08 – Decision Trees00:26:33 – Minimax00:34:27 – Machine Learning00:42:56 – Deep Learning00:48:53 – Large Language Models00:53:36 –…
If you’re interested in the herculean task of interpreting what these large networks might actually be doing, the Transformer Circuits posts by Anthropic are great. In particular, it was only after reading one of these that I started thinking of the combination of the value and output matrices as being a combined low-rank map from…
