Last October, we kicked off our annual Doodle 4 Google
art competition, asking students to create a doodle to tell the world “What makes me…me.” This time around, we added a little twist: for the first time in eight years of Doodle 4 Google, there were no restrictions on the medium or materials kids could use to create a doodle. Kids took us up on the challenge. A quarter of all finalists used some non-traditional media—from clay and wood to origami, photographs and sheets of music—in their submission.
Today, Googlers are hosting surprise assemblies at schools from Waterville, Maine to Waipahu, Hawaii to celebrate the winners of each state and thank the teachers and parents who have encouraged them along the way. And for the first time ever, we’re announcing winners for Washington, D.C., Guam and Puerto Rico. See all 53 State and Territory Winner
s on our website.
Now, our finalists need your votes for a shot at having their doodle make it onto the Google homepage. Starting today through Feb 22, head to the Doodle 4 Google site
to vote for your favorite artwork for each grade group. On March 21, we’ll announce the winner and four runners-up—and you’ll see the winning doodle on google.com.
Check out this year’s talented set of finalists and vote
for your favorite!
Growing up, my parents were daily reminders of the sacrifices made by earlier generations of Black Americans to give people like me the opportunities they were denied. To this day, their stories propel me to continue the fight for justice. I am far from alone—reflecting on a shared history inspires millions around the world to work toward equality. But without some record, those stories and the passion they ignite could get lost.
Artworks, artifacts and archives have the power not only to give a story life, but to encourage action and incite change. That’s why the Google Cultural Institute is excited to add records from institutions like the Smithsonian National Museum of African American History and Culture, the Studio Museum and Amistad Research Center and many more—bringing together important archives from Black history
for anyone to access not only during Black History Month, but throughout the year.
From the New Orleans Jazz Orchestra to the historical records of Frederick Douglass and Dr. Martin Luther King Jr., this collection includes 26 new institutions (50 overall) contributing 5,000+ items
and more than 80 curated exhibits
. It includes new Street View imagery and three Google Expeditions
, including an exploration of the resurgence of Jazz in New Orleans with Irvin Mayfield and Soledad O’Brien. You can see a 360 degree YouTube video made in conjunction with that Expedition here:
In The Baltimore Museum of Art
’s exhibition “Questioning the Canon
,” you can see Mickalene Thomas’s Le déjeuner sur l'herbe: Les Trois Femmes Noires
it side-by-side with the Manet original to see the ways Thomas has subverted the subject-matter of this canonical white European work.
You can trace along the paths of history by reading Frederick Douglass’ letter to his former master, and read the original manuscripts of Dr. King’s ”I Have a Dream” and “I’ve Been to the Mountaintop” speeches. Absorb Dr. King’s personal letter to wife Coretta Scott King at the beginning of his four-month prison term for non-violent protest, then cut to photographs documenting his momentous first handshake at the White House with President Lyndon B. Johnson.
Collecting these works into one place provides unprecedented access to a vital part of history that is too often forgotten. By comparing works of art and texts of speeches to find commonalities and distinctions, we can also build on the past to inspire ourselves and others. And while today is the first day of Black History Month, the work of remembering our history is necessary year round—which is why these records will be there on the Cultural Institute for generations to come.
The game of Go
originated in China more than 2,500 years ago. Confucius
wrote about the game, and it is considered one of the four essential arts
required of any true Chinese scholar. Played by more than 40 million people worldwide
, the rules of the game are simple: Players take turns to place black or white stones on a board, trying to capture the opponent's stones or surround empty space to make points of territory. The game is played primarily through intuition and feel, and because of its beauty, subtlety and intellectual depth it has captured the human imagination for centuries.
But as simple as the rules are, Go is a game of profound complexity. There are 1,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000 possible positions—that’s more than the number of atoms in the universe, and more than a googol times larger than chess.
This complexity is what makes Go hard for computers to play, and therefore an irresistible challenge to artificial intelligence (AI) researchers, who use games as a testing ground to invent smart, flexible algorithms that can tackle problems, sometimes in ways similar to humans. The first game mastered by a computer was noughts and crosses
(also known as tic-tac-toe) in 1952. Then fell checkers
in 1994. In 1997 Deep Blue famously beat Garry Kasparov at chess
. It’s not limited to board games either—IBM's Watson
[PDF] bested two champions at Jeopardy in 2011, and in 2014 our own algorithms learned to play dozens of Atari games
just from the raw pixel inputs
. But to date, Go has thwarted AI researchers; computers still only play Go as well as amateurs.
Traditional AI methods—which construct a search tree
over all possible positions—don’t have a chance in Go. So when we set out to crack Go, we took a different approach. We built a system, AlphaGo, that combines an advanced tree search
with deep neural networks
. These neural networks take a description of the Go board as an input and process it through 12 different network layers containing millions of neuron-like connections. One neural network, the “policy network,” selects the next move to play. The other neural network, the “value network,” predicts the winner of the game.
We trained the neural networks on 30 million moves from games played by human experts, until it could predict the human move 57 percent of the time (the previous record before AlphaGo was 44 percent
). But our goal is to beat the best human players, not just mimic them. To do this, AlphaGo learned to discover new strategies for itself, by playing thousands of games between its neural networks, and adjusting the connections using a trial-and-error process known as reinforcement learning
. Of course, all of this requires a huge amount of computing power, so we made extensive use of Google Cloud Platform
After all that training it was time to put AlphaGo to the test. First, we held a tournament between AlphaGo and the other top programs at the forefront of computer Go. AlphaGo won all but one of its 500 games against these programs. So the next step was to invite the reigning three-time European Go champion Fan Hui—an elite professional player who has devoted his life to Go since the age of 12—to our London office for a challenge match. In a closed-doors match last October, AlphaGo won by 5 games to 0. It was the first time a computer program has ever beaten a professional Go player. You can find out more in our paper, which was published in Nature
What’s next? In March, AlphaGo will face its ultimate challenge: a five-game challenge match in Seoul against the legendary Lee Sedol
—the top Go player in the world over the past decade.
We are thrilled to have mastered Go and thus achieved one of the grand challenges of AI
. However, the most significant aspect of all this for us is that AlphaGo isn’t just an “expert” system
built with hand-crafted rules; instead it uses general machine learning techniques to figure out for itself how to win at Go. While games are the perfect platform for developing and testing AI algorithms quickly and efficiently, ultimately we want to apply these techniques to important real-world problems. Because the methods we’ve used are general-purpose, our hope is that one day they could be extended to help us address some of society’s toughest and most pressing problems, from climate modelling to complex disease analysis. We’re excited to see what we can use this technology to tackle next!
A year and a half ago we introduced Google Cardboard, a simple cardboard viewer that anyone can use to experience mobile virtual reality (VR). With just Cardboard and the smartphone in your pocket, you can travel to faraway places
and visit imagined worlds
. Since then everyone from droid lovers
and Sunday edition subscribers
, to big kids
have been able to enjoy VR—often for the very first time. Here's a look at where we are, 19 months in:
1. 5 million Cardboard fans have joined the fold.
2. In just the past two months (October-December), you launched into 10 million more immersive app experiences:
3. Out of 1,000+ Cardboard apps
on Google Play, one of your favorites
got you screaming “aaaaaaahwsome,” while another
“gave you goosebumps.”
4. You teleported to places far and wide, right from the comfort of YouTube
5. Since we launched Cardboard Camera
in December, you’ve captured more than 750,000 VR photos, letting you relive your favorite moments anytime, from anywhere.
6. Students around the world have taken VR field trips to the White House
, the Republic of Congo
, and 150 other places around the globe with Expeditions
While you've been traveling the world and beyond with Cardboard, we've been on a journey, too. Keep your eyes peeled for more projects that bring creative, entertaining and educational experiences to mobile VR.