AIGA, the professional association for design, recognized Google as an exemplary company modeling design’s potential to delight users, inspire visionary products and services, fuel innovation, and improve our world. Google received the AIGA Award at the AIGA Awards Gala on April 20, 2018 in New York City.
We made a video to say thank you. It has a bunch of work by me, my friends at Creative Lab, and across Google.
Google’s mission is to “organize the world’s information and make it universally accessible and useful.” And we believe design plays a big part in making things accessible and useful for everyone. Find out more at https://g.co/design. And check out the description below the video for a list of projects featured.
Happy to have played a small part in this. The team work on developing the idea, naming, branding, language, and created some some high level UX/UI and design guidelines to help this important feature rollout consistently across our platforms and products.
In times of crisis, access to timely, actionable info is crucial so we are launching SOS alerts in Search & Maps https://t.co/NqsX9G0msz
Sideways Dictionary is a collection of fun, easy-to-understand analogies that help explain complicated technology terms. Use it to look up tech terms of all kinds, vote for the definitions you like best, and even add your own.
Creative Lab helped our friends at Google Jigsaw bring this project to life by writing, art directing, and producing two short animations. One to introduce the project, and a second to help people get in the right mindset to write and contribute analogies of their own.
There’s a bunch of amazing experiments on the site; but this one below is the one I spend the most time with during its early development phase.
Honestly; I never felt more out of my depth on a project than at the beginning of this one. Sat in the kickoffs with Alex, Kyle and Yotam who were deep in the weeds talking about t-SNE, dimensionality reduction, hi-dimensional space, convolutional neural networks, and supervised vs un-supervised learning. Was a full-on nose-bleed, crash course, in ML. But so worth it. Do not fear this stuff. It’s a different world to start; but after a few weeks it starts to take. So please enjoy….
Sounds are complex and vary widely. This experiment uses machine learning to organize thousands of everyday sounds. The computer wasn’t given any descriptions or tags – only the audio. Using a technique called t-SNE, the computer placed similar sounds closer together. You can use the map to explore neighborhoods of similar sounds and even make beats using the drum sequencer.
Here’s the explainer video:
For an extra sneak peak into the development process; here’s a video showing an earlier prototype. This one has around ~40k short samples from Freesound! For the final version we licensed ~17k.
This is one of the last projects I started working on in New York, so it’s great to see it out in the real world. Mad props to Alex, Catherine, Manny, Yotam, Eric, Jonas, Kyle, Gene and bunch of other very smart people.
One made beats and played them with Ableton Live and a MIDI keyboard. The other jammed live with a chromatic harmonica & pedal FX. It was like deep space Vangelis. Perfect for the setting. Perfect for the vibe.
Needed the break after putting a shift in at work (see last few posts) but feeling recharged and inspired. Don’t spend your money on stuff. Spend it on experiences and memories.