Visualizing transformers and attention | Talk for TNG Big Tech Day ’24

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…

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

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….

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

Demystifying attention, the key mechanism inside transformers and LLMs.

Aug 28, 2024Jürgen Schmidhuber, the father of generative AI shares his groundbreaking work in deep learning and artificial intelligence. In this exclusive interview, he discusses the history of AI, some of his contributions to the field, and his vision for the future of intelligent machines. Schmidhuber offers unique insights into the exponential growth of technology…