A quick overview of Machine Learning (ML)

Probably you heard about Artificial Intelligence. Some people say the Artificial Intelligence will be the fourth industrial revolution, a profoundly disruptive revolution that transforms services and professionals. Imagine trucks transporting being driven by machines, or machines analyzing various researches and given diagnosis to help a doctor in taking medical decisions, wow, really is disruptive.

But my purpose here is to write about a subfield of Artificial Intelligence (AI) that is Machine Learning (ML). ML gives computers the ability to learn without being explicitly programmed, when you “code” known behaviors. The focus is on developing algorithms that can automatically learn when exposed to data, identifying patterns and transforming data into knowledge. This really is the evolution of regular algorithms when computer programs became “smarter”. If you watched Matrix’s movie should remember the scene when the Trinity character must pilot a helicopter and her brain is exposed to an absurd amount of data (big data), to learn how to pilot that helicopter. That is it! Her brain receives data about helicopter’s behavior, mechanical skills, technical problems and how to solve them.

Besides the AI ​​is ready to transform our industry and technologies, such as electricity did in the middle of the 20th century, also have the potential to change art, music, products and services. Today we interact with various products and services (computer programs) that have Machine Learning on its core, as Siri (Apple), recommendation from Amazon, Google Translate, Google Photos, Google Now, Cortana (Microsoft), Prisma (photo APP) or Facebook to recognize your friends in pictures as well as ordering your timeline based on your relationship with the content (likes, comments, etc.), ie, when exposed to more fresh data ML will get better and better, creating new behaviors.

I’ll list here some projects that made use of Machine Learning to show you the potential that this field of Artificial Intelligence has.

“THE NEXT REMBRANDT”
The painting was created using data from Rembrandt’s total body of work using deep learning algorithms and facial recognition techniques. The portrait consists of over 148 million pixels, based on 168,263 painting fragments from Rembrandt’s oeuvre.

Link: 
http://www.wired.co.uk/article/new-rembrandt-painting-computer-3d-printed

Clickbait Headlines
A clickbait generator using a neural network, which is able to create sensationalist headlines that play on human readers’ curiosity.
Link: 
https://thestack.com/world/2015/10/15/machine-learning-generates-clickbait-headlines-that-will-shock-you/

Creating Music
It’s the first tangible product of Google’s Magenta program, which is designed to put Google’s machine learning systems to work creating art and music systems. 
Links: 
http://www.theverge.com/2016/6/1/11829678/google-magenta-melody-art-generative-artificial-intelligence
https://cdn2.vox-cdn.com/uploads/chorus_asset/file/6577761/Google_-_Magenta_music_sample.0.mp3

Transform a photo in a piece of art
Pick up an ordinary photo, upload to a Machine Learning APP as the result is a piece of art, thanks to a neural networks.

Links:
http://deepdreamgenerator.com/
http://prisma-ai.com/
https://www.engadget.com/2016/07/20/try-prismas-machine-learned-art-filters-on-android/

Logo Design
Imagine to type a word or your company name to Machine Learning algorithm starts to create a lot of logo for you.

Links: 
http://www.fastcodesign.com/3058852/what-happens-when-you-apply-machine-learning-to-logo-design
http://emblemmatic.org/markmaker/#/

Beer brewed by AI
Four beers have been created with the help pf artificial intelligence, with each recipe altered based on customer feedback received by an algorithm.

Link: http://www.wired.co.uk/article/beer-brewed-by-ai-intelligentx

These are some examples about ML, there are a thousand examples and researches. If you “Google” about it, you can found more.

Márcio Bueno
Director of Creative Technology / Digital Production