Man versus machine has been a running theme in science fiction for decades. In fact, so intense has the rivalry been between computerised brains and human brains that scientists have dedicated their lives to perfecting artificial intelligence (AI).
Chess has always been the benchmark for any AI gaming computer and in 1996 Deep Blue did what many thought was impossible and beat the world’s best player, Garry Kasparov.
Creative Applications of Deep Learning with TensorFlow
New online course from Kadenze put together by PK Mital will teach you how to use Google’s machine learning platform Tensorflow for creative projects:
This course introduces you to deep learning: the state-of-the-art
approach to building artificial intelligence algorithms. We cover the
basic components of deep learning, what it means, how it works, and
develop code necessary to build various algorithms such as deep
convolutional networks, variational autoencoders, generative adversarial
networks, and recurrent neural networks. A major focus of this course
will be to not only understand how to build the necessary components of
these algorithms, but also how to apply them for exploring creative
applications. We’ll see how to train a computer to recognize objects in
an image and use this knowledge to drive new and interesting behaviors,
from understanding the similarities and differences in large datasets
and using them to self-organize, to understanding how to infinitely
generate entirely new content or match the aesthetics or contents of
another image. Deep learning offers enormous potential for creative
applications and in this course we interrogate what’s possible. Through
practical applications and guided homework assignments, you’ll be
expected to create datasets, develop and train neural networks, explore
your own media collections using existing state-of-the-art deep nets,
synthesize new content from generative algorithms, and understand deep
learning’s potential for creating entirely new aesthetics and new ways
of interacting with large amounts of data.
The online course is free ($10 a month for premium service) - you can find out more here
I trained an LSTM Recurrent Neural Network (a deep learning algorithm) on all the song lyrics from Hamilton. I then asked it to produce a new song based on what it learned. Here’s the song.
All the words and character assignments are from the AI. However, I added a bit of formatting to aid readability. Also, I tried to add strategic line breaks (//) to make it rhyme as best as possible (i.e. my interpretation on how it should be sung or rapped). I bolded my suggested rhymes and soft rhymes.
HAMILTON Tryin’ for a glass! Split, college. Oceans same. // Outmanned Grandpa’s go… ‘specially four. To the city will stay.
ELIZA Sir, this way
ANGELICA I challenge
LAFAYETTE: Let’s know, they have two States. There is a second? // And his way Empires duel to go. Just damn it // They know wonders upside I’m on, ya number // Maybe a side! So she’s a father, sir
BURR AND COMPANY Work! dadada its world // show it could tell all