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.
Most of the stuff I work on is confidential so I don’t get to share it publicly—but my last project could hardly be more visible. I’m not going to write lots about it as there’s already plenty of coverage out there. All I wanted to say is that it’s the meatiest (and most rewarding) thing I’ve ever tackled. We kicked the project off in January 2015 with ten people in a room sketching ideas. By the end of August we had over 200+ engineers, designers, writers, product managers, and marketeers preparing to flip the switches on over 30+ product updates. As well as the product updates and a ton of guidelines and toolkits – we also made this Google, Evolved video, a Google Doodle for the occasion, and shared the thinking on the Official Google Blog.
Everything went live on September 1st 2015.
Bonus: we also broke down the process + thinking in much more detail over on the Google Design Blog post If you’re into how things get made you should definitely take time to read it. You’ll get a better understanding of how the process worked, why the system & framework were designed to hold together, and what we wanted to reflect in the brand by making Google more accessible and useful to our users—wherever they may encounter it.
Here’s a little teaser.
Early this year, designers from all across the company, including Creative Lab and the Material Design team, convened in New York for an intense, week-long design sprint. We drafted a brief that identified four challenges we wanted to address:
A scalable mark that could convey the feeling of the full logotype in constrained spaces.
The incorporation of dynamic, intelligent motion that responded to users at all stages of an interaction.
A systematic approach to branding in our products to provide consistency in people’s daily encounters with Google.
A refinement of what makes us Googley, combining the best of the brand our users know and love with thoughtful consideration for how their needs are changing.
It was a huge team effort. Hope you like the work!
Video Time Machine Handpicked popular culture from 1860 – 2011.
RobotFlaneur The idea is simple: pick a city, and every 30 seconds it will take you to a random place and show you the Google StreetView image. Each view is not important. What’s interesting is if you leave it running and occasionally glance at it. You might recognise some views in some cities, otherwise there’s a lot of mundanity: suburbs, motorways, traffic signs. These are the grain of the city and vary wildly. /via Dentsu Blog. http://robotflaneur.com/