Artificial intelligence is a topic of mystery, wonder, and endless possibilities for many. Despite all the recent hype, AI remains elusive to the general public and is often shrouded in misconceptions.
In an attempt to make AI technology more accessible to the average person, developers worldwide are creating more and more experiments and opening them to the public. Through pictures, music, drawings and more, these demos show off the creative capacity of machine learning technology not typically covered in the media.
We at Lionbridge AI have put together a collection of our favorite AI experiments you can try online today. Enjoy!
1. Quick, Draw! – AI Pictionary
That’s right – you can now create terrible drawings and let Google guess what they are! Last year, Google released a free online game built using machine learning. It’s simple, really: draw an object, and Google will attempt to guess what it is. The model only gets better with the more drawings it guesses, and all the data is shared publicly to help advance machine learning research. Play the game for yourself here.
2. AttnGAN – Image generation machine
Researchers at Microsoft’s Deep Learning Technology Center recently taught an algorithm to turn text captions into images.
The goal of the model is to visualize text-based captions, and the results are as bizarre as you’d expect. When researchers trained the AI on a specific dataset (e.g. a dataset of cat images), it was able to produce convincing output. However, when trained on a large dataset of diverse images, it became a bit overwhelmed, as shown in the following screenshot:
You can play around with AttnGAN thanks to a demo created by Cristóbal Valenzuela, a technologist and research resident at New York University. It’s part of a larger project, Runway, that enables AI to be used creatively.
3. Talk to Books – Intelligent conversation
Google Research has developed multiple activities to teach AI the art of human conversation. In Talk to Books, you can type in any statement or a question, and the model will scan over 100,000 books to find a variety of responses based on your input.
Director of Engineering, Ray Kurzweil, said the model was trained on nearly a billion lines of dialogue in order to identify a suitable response.
4. Shelley AI – Human-AI collaborated horror stories
From the makers of the Nightmare Machine, Shelley is a deep-learning powered AI. Trained using creepy stories from Reddit’s r/nosleep subreddit, Shelley has been co-authoring horror stories with Twitter users for the past year.
Every hour, Shelley composes a series of tweets followed by the hashtag #yourturn. The model relies on Twitter users to continue the story by writing a line themselves, and then finishes it off with a twist of her own. And the results can be surprisingly bonechilling.
Find short stories written by Shelley and more information on her homepage.
5. AI Duet – Play piano with an AI
Play a duet with a piano that responds to you. Enter in some notes by clicking your mouse, using your computer keys, or even plugging into a MIDI keyboard, and the model will respond to your melody. This is just one example of how machine learning can spark creativity in new ways.
6. pix2pix – Image to image translation
Thanks to this interactive demo of pix2pix, you can now can turn simple line drawings into beautiful works of art. Sketch a simple line drawing and watch the pix2pix AI automatically transform your creation into cats, buildings or shoes.
How does it work? pix2pix uses a conditional generative adversarial network (cGAN) to learn a mapping from an input image to an output image. The model is training on pairs of images such as building facade labels to building facades, and then attempts to generate the corresponding output image from any input image you give it.
7. Even Stranger Things – Strange poster generator
A fun generator that uses AI image recognition to transform whatever image you upload into a Stranger Things poster.
Try the demo for free here.
8. Infinite Drum Machine – Create beats with everyday sounds
Built by the Google Creative Lab, the Infinite Drum Machine is a new way to create beats using everyday sounds.
Using a technique called t-SNE, the model was able to organize a large audio dataset into small groups of similar sounds without using descriptions or tags. By sliding markers around the sound map, you can explore different sounds and make beats using the drum sequencer.
9. FastPhotoStyle – Photo style transfer
Earlier this year, NVIDIA released a new AI algorithm called FastPhotoStyle that can transfer the style from any photo to a different image, producing impressive, photo-realistic results.
The model splits the task in two separate steps, stylization and smoothing. During stylization, the reference photo’s style is copied to the content photo. Next, a smoothing step helps make the output look extra convincing by encouraging “spacially consistent stylizations.” Here are some examples of what FastPhotoStyle can do:
10. Semantris – NLP word association
Created by Google, Semantris is a set of online word association games powered by machine-learned, natural language understanding (NLP) technology.
Each time you enter a clue, the model looks at the words in play and selects the one it thinks is most related. The model learned the connections between words after being fed billions of conversational text samples on the internet. Try it for yourself here, but be forewarned—it’s highly addictive.
As these experiments show us, there are a mind-boggling number of use cases for AI. In fact, no two projects are the same. That’s why machine-learning models need to be trained on custom data to reach their full potential. Here at Lionbridge AI, we specialize in creating and annotating datasets for a variety of NLP use cases. Whether you’re building a chatbot for business or just having fun with machine learning, contact us today to see how investing in data can take your project to the next level.
Feature image via PetaPixel