The last five years have witnessed a dramatic resurgence of excitement in the goal of creating intelligent machines.
Technology companies are now investing billions of dollars in this field, new research laboratories are springing up around the globe, and competition for talent has become intense. In this Discourse Chris Bishop describes some of the recent technology breakthroughs which underpin this enthusiasm, and explores some of the many exciting opportunities which artificial intelligence offers.
Chris Bishop is the Laboratory Director at Microsoft Research Cambridge and is a professor of computer science at the University of Edinburgh. He has extensive expertise in artificial intelligence and machine learning.
I traveled to Amsterdam for a week to speak at The Next Web Conference on AI Safety. While roaming the streets of the city, I decided to take some shots and formulate a video on the same topic for you guys. In the battle of good vs evil, it’s up to our community to ensure good wins. I’ll resume the coding videos next week when I get back to San Francisco.
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We’re going to build a variational autoencoder capable of generating novel images after being trained on a collection of images. We’ll be using handwritten digit images as training data. Then we’ll both generate new digits and plot out the learned embeddings. And I introduce Bayesian theory for the first time in this series 🙂
Please subscribe! And like. And comment. That’s what keeps me going.
-The embedding visualization at the end would be more spread out if i trained it for more epochs (50 is recommended) but i just used 5.
-The code in the video doesn’t fully implement the reparameterization trick (to save space) but check the GitHub repo for details on that.
We’re going to learn how the visualizer that comes with Tensorflow works in this live stream. We’ll go through a bunch of different features and test out its functionality both programmatically and visually.