This column is by Oliver Cameron, VP – Engineering & Product, Udacity
Many have written about how deep learning is taking over the world and why that is important; I cannot echo them enough. Playing with deep learning is the closest I’ve ever felt to being a magician, and it’s become clear to me that every (great) piece of software will be powered by deep learning within the next ~3 years. However, deep learning isn’t mainstream yet, so I thought I’d share work by some very talented contributors, in the hopes to bring it just that little bit closer.
Here’re ten reasons why I think deep learning is living up to the hype…
1. Stuck with a low-resolution photo? Deep learning can predict what the higher-resolution photo might look like, and add missing details
Tried this out, wow! Down-sampled a photo of my cute kid to 250x167px, ran it through the neural net and 15 seconds later… pic.twitter.com/EIqiHBZ84D
— Oliver Cameron (@olivercameron) October 29, 2016
3. Deep learning can compose classical music that you’d believe to be created by a human
4. Deep learning can replicate the style of your favourite painter with the image of your choice
9. Want to sketch a beautiful landscape but can’t draw? Don’t worry, deep learning can take it from here!
10.Best of all (at least to me), you can train a deep neural network to steer a car, just like a human
Some kinks (not road ready ), but this student submission to predict steering angles using deep learning is coming along nicely. pic.twitter.com/lMzZAIOTCm
— Oliver Cameron (@olivercameron) October 17, 2016
1️⃣ You’ll build this in the first weeks of our self-driving curriculum! 160×320 images fed into a DNN keep the car on the road pic.twitter.com/xgT0YytbDW — Oliver Cameron (@olivercameron) September 22, 2016
…it even turns out Grand Theft Auto is a great simulation environment for training a self-driving car
Why am I so sure that deep learning is revolutionary? If you look closely at the above tasks that the machine is performing, you’ll see a common thread: creativity. A machine, albeit trained with human data, is able to demonstrate almost artistic traits.
We’ve spent decades building and refining machines to be computationally powerful. In the next decade I hope we discover what the human race will be empowered to do when our software thinks creatively.
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