Rather than create another video featuring Archer half-heartedly apologizing for his absence at San Deigo Comic Con, the show’s production team thought it would be fun to change things up, and have Archer interact in real-time with fans.
When the Guggenheim Bilbao museum opened 20 years ago it was described by many as a starship from outer space. Its swirling roof is made of paper-thin titanium tiles—33,000 of them—covering the building like fish scales. At the time, it was such a novelty that the museum had to commission a chemical laboratory to produce a custom liquid to clean the titanium!
The museum was an unusual experiment not just because of its gleaming shell. Over two decades ago, following the collapse of the traditional industries Bilbao was built on, the city was scarred with industrial wastelands, abandoned factories, and a community afflicted by unemployment and social tensions. Bilbao surprised the world (and raised a few eyebrows) with a unique idea to kickstart the city’s regeneration, and they set out to build—not new factories or new roads—but instead a new center for modern art.
Since then, the museum has attracted 19 million visitors and became the epicenter of the urban renewal that rippled through Bilbao. Today it stands as an icon of the city and its successful self-transformation. To celebrate the Guggenheim’s 20th anniversary, Google Arts & Culture partnered with the museum to bring their stories to you and show it from a new angle.
But how do you find a new angle on one of the world’s most photographed buildings? Google invited Johan Tonnoir—known for running and jumping across Paris’s busy rooftops with only a pair of sturdy shoes—to the Guggenheim.
Johan explored the building in his own way … through a breathtaking stunt-run across the building and its iconic slippery roof. He climbed to the highest peak and jumped, flipped and leapt from one wing of the roof to the other at 50 meters high. And all along, urban photographer Trashhand from Chicago followed him with his lens.
Check out the museum’s masterpieces on Google Arts & Culture (but please don’t try to do it Johan’s way…). You can see all this online at g.co/guggenheimbilbao or in the Google Arts & Culture app on iOS and Android.
Advancing our students’ understanding of the principles and practices of computing is critical to developing a competitive workforce for the 21st century.
In every field, businesses of all sizes are looking to hire people who understand computing, so we need more students to leave school confident in skills like coding, computational thinking, machine learning and cybersecurity.
The U.K. has already led the way in preparing for this future by making computer science education a part of the school curriculum in 2014. But we know there is more to do to ensure young people in every community have access to world-class computer science education.
A recent report from the Royal Society found that despite the good progress in recent years, only 11 percent of Key Stage 4 pupils take GCSE computer science. The majority of teachers are teaching an unfamiliar school subject without adequate support. These teachers are eager to offer computer science to their students but they need access to subject area training to build their confidence.
The U.K. government’s announcement that they’re investing £100 million for an additional 8,000 computer science teachers supported by a new National Centre for Computing is an encouraging step forward. It builds on the progress that’s been made since computing was added to the curriculum in 2014 by helping to ensure teachers have the specialist training and support they need to educate the next generation of British computer scientists.
We want to continue to play our part too.
Today we’re announcing £1 million in grants to support training for secondary school computing teachers in the U.K.
The Google.org grant will allow the Raspberry Pi Foundation, the British Computer Society and the National STEM Learning Centre to deliver free computer science and pedagogy training for thousands of key stage 3 and key stage 4 teachers in England over three years, with a specific focus on disadvantaged areas.
Through this effort, they will make make online courses and professional development resources available to teachers anywhere, anytime, for free, and deliver free in-person workshops for teachers across the country.
Googlers care deeply about helping to develop our future computer scientists, and many of them will give their time and skills to this program. A team of Google engineers and learning and development specialists will volunteer with Raspberry Pi to ensure that all teachers are able to access the online resources and courses.
This grant is part of Google’s long-standing commitment to computer science education. Through Google.org, we’ve given nearly $40 million to organizations around the globe ensuring that traditionally underrepresented students have access to opportunities to explore computer science.
In the U.K., we also support teacher recruitment and professional development by teaming up with organizations like Teach First and University of Wolverhampton, and we focus on inspiring more children, especially girls and those from disadvantaged areas, to take up computing through Code Club UK after-school clubs.
CS education and computational thinking skills are key to the future, and we’re committed to supporting Raspberry Pi—and other organizations like them—to ensure teachers and young people have the skills they’ll need to succeed.
Editor’s note: Google has just completed its first-ever Google for Education Study Tour, bringing nearly 100 educators from 12 countries around Europe to Lund, Sweden, to share ideas on innovating within their systems and creating an environment that embraces innovation.. One of the highlights of the two-day event was a visit to Oxievång School in Malmö, where principal Jenny Nyberg has led their adoption of technology in the classroom. Below, Jenny explains how to support teachers during a period of technology adoption.
When we’re introducing new technology for our classrooms, I tell my teachers to imagine the ultimate goal as an island we all have to swim toward. Some of us are very fast swimmers, and we’ll figure out how to get to the island quickly, and even get around any sharks. Some of us are slow swimmers, and may be hesitant to jump in, but the strong swimmers will show us the way (and how to get around the sharks). Eventually, we all have to jump into the water.
Bringing tech-based personalized learning into the classrooms at Oxievång School was our “island” and we’ve all completed the journey, which was particularly important given that our school, like the city of Malmö itself, is a mix of different people with varying needs. We have immigrant students as well as native Swedes; 40 percent of our students speak Swedish as their second language. But all students can become strong learners when teachers discover what motivates and excites them. When we adopted G Suite for education, our “fast-swimmer” teachers showed their colleagues how they could now customize learning for each and every student.
As school leaders, my vice principals and I served as role models for using G Suite— not just for teaching, but for making our jobs easier too. We showed teachers how to use Google Sites to store information we needed every day, like staff policies and forms. We walked teachers through the Google Docs tools that allow them to comment on student work immediately rather than waiting to receive homework from students, and giving feedback much later. When teachers saw this in action, they understood how adopting G Suite was going to make a big difference for their teaching effectiveness and their productivity.
If you want teachers to become enthusiastic about using new technology, they need to be confident in their use of the new technology. For this, you have to give them support. So we hired a digital learning educator who works exclusively with teachers to help them build up their technology skills. Every teacher receives a personalized development plan with a list of resources for training.
Our students have become more engaged in their coursework as teachers have become better at using Google technology to personalize learning. If students are curious about a subject, they can use their Chromebooks and G Suite tools to further explore the topic on their own. They also interact with teachers more often, even using Hangouts to meet with teachers outside of the classroom. As teachers become more confident, their enthusiasm spreads to the students.
Once we give teachers basic training, we keep supporting them so that the transformation spreads throughout the school. When they need extra help with using G Suite, teachers know where to find it: they can schedule a meeting with the digital learning educator. We have team leaders across grades and subjects who help teachers’ follow their development plans. Once a month, we all meet at school sessions called “skrytbyt,” which roughly translates as “boost exchange.” In these sessions teachers trade stories about lessons that went well and ask for advice about how to improve lessons they find challenging. Sharing knowledge is a great way to build confidence.
As leaders in education, we have to be honest with teachers and acknowledge that change isn’t easy, but assure them that we’re here for them. Teachers worry that students know more about technology than they do—students are the digital natives, while teachers are the digital immigrants. We constantly remind teachers that they can find inspiration in each other and in their students’ knowledge, so that we all make it to the island together.
Nine months ago, 37 newsrooms worked together to combat misinformation in the run-up to the French Presidential election. Organized by First Draft, and supported by the Google News Lab, CrossCheck launched a virtual newsroom, where fact-checkers collaborated to verify disputed online content and share fact-checked information back to the public.
The initiative was a part of the News Lab’s broader effort to help journalists curb the spread of misinformation during important cultural and political moments. With a recent study finding that nearly 25% of all news stories about the French Presidential election shared on social media were fake, it was important for French newsrooms to work closely together to combat misinformation in a timely fashion.
Yesterday at our office in Paris, alongside many of the newsrooms who took part in the initiative, we released a report on the project produced by academics from the University of Toulouse and Grenoble Alpes University. The report explored the impact the project had on the newsrooms and journalists involved, and the general public.
A few themes emerged from the report:
- Accuracy in reporting rises above competition. While news organizations operate in a highly competitive landscape, there was broad agreement that “debunking work should not be competitive” and should be “considered a public service.” That spirit was echoed by the willingness of 100 journalists to work together and share information for ten weeks leading up to Election Day. Many of the journalists talked about the sense of pride they felt doing this work together. As one journalist put it, “debunking fake news is not a scoop.”
- The initiative helped spread best practices around verification for journalists. Journalists interviewed for the report discussed the value of the news skills the picked up around fact-checking, image verification, and video authentication—and the lasting impact that would have on their work. One journalist noted, “I strengthened my reflexes, I progressed in my profession, in fact-checking, and gained efficiency and speed working with user generated content.”
- Efforts to ensure accuracy in reporting are important for news consumers. The project resonated with many news consumers who saw the effort as independent, impartial and credible (reinforced by the number of news organizations that participated). By the end of the election, the CrossCheck blog hit nearly 600,000 page views, had roughly 5K followers on Twitter and 180K followers on Facebook (where its videos amassed 1.2 million views). As one news reader noted, “many people around me were convinced that a particular piece of misinformation was true before I demonstrated the opposite to them. This changed how they voted.”
You can learn more about the News Lab’s efforts to work with the news industry to increase trust and fight misinformation here.
With the season for giving right around the corner, we’re excited to kick off the Fi it Forward referral challenge. The challenge is rolling out today starting on desktop.
Like our last referral challenge, participants will earn prizes for the referrals they make throughout the challenge. In the Fi it Forward challenge, you can win up to two hardware gifts when you refer friends to Project Fi: a Google Chromecast and the new Android One moto x4.
But we’re most excited about our opportunity to pay it forward with our third gift. At the end of the challenge, Project Fi will donate $50,000 to the Information Technology Disaster Resource Center (ITDRC). We’re thrilled to see organizations like the ITDRC harness the power of communications technology to make a meaningful difference in crisis response and recovery, and we’re grateful to come together as a community to support their initiatives. Project Fi users don’t have to take any action to participate in the community gift—you’re already supporting the ITDRC’s disaster relief efforts just by being a part of Project Fi.
Ready to get started?. Remember to enter the challenge and get your referrals in by December 17. We can’t wait to Fi it Forward with all of you this holiday season.
Shadows don’t always have to be scary—they can be downright magical. This week, #teampixel is sharing everything from a solitary lemon’s shadow to palm trees silhouetted against a vivid sky in Venice, CA. Come chase shadows with us and see what you find.
If you’d like to be featured on @google and The Keyword, tag your Pixel photos with #teampixel and you might see yourself next.
Thanksgiving is just a few days away and, as always, your Google Assistant is ready to help. So while the turkey cooks and the family gathers, here are some questions to ask your Assistant.
- Show up to dinner on time: “Ok Google, how’s traffic?”
- Prepare accordingly: “Ok Google, set a turkey timer for 4 hours.”
- And don’t forget dessert: “Ok Google, add apple pie and pumpkin pie to my shopping list”
- Play a game while you wait for turkey: “Ok Google, play Thanksgiving Mad Libs”
- Hear a funny tale: “Ok Google, tell me a turkey story”
- Learn something new: “Ok Google, give me a fun fact about Thanksgiving”
- When Thanksgiving’s over, get ready for the next occasion: “Ok Google, play holiday music”
Happy Thanksgiving 🦃
Earlier this year, 3D modeler Jarlan Perez joined the Blocks team for a two-week sprint. The goal of his time with the team was to create a fully immersive virtual reality game in just two weeks using Blocks and Unreal Engine, two tools that have significantly influenced his process as a modeler and game enthusiast.
The result was “Blocks Isle,” the first level of a game that takes you on a journey to find your long lost friend in a sci-fi land of wonder. To win, you must solve a puzzle using hidden clues and interactions throughout the experience.
You start out on a strange desert island. After uncovering some clues and pulling a handy lever, a rocky pathway opens for exploration. Up ahead, hidden radios and books reveal clues to solve the puzzle.
We caught up with Jarlan to hear more about his process and advice for other developers building immersive experiences using Blocks and Unreal Engine 4.
Brittany: Tell us about using Blocks and Unreal to develop a game in such a short amount of time.
Jarlan: Tag teaming both pieces of software worked very well! Blocks allowed me to visualize and be in the space during the modeling and conceptual phase. Unreal is like giving an artist magical powers: I’m able to fully build a proof of concept and implement functionality without having to be a professional programmer.
I found myself spending part of the day in Blocks experimenting with concepts and the rest in Unreal creating basic functionality for those ideas. This method allowed for rapid prototyping and was later beneficial when populating the space with art assets.
What tips and tricks did you uncover that made it easy to build your game?
Being able to build large parts of the environment while standing smack dab in the middle of it is wonderful.
A big thing that I found myself doing is blowing the scene up to actual size, standing in it, and using a combination of the move grip and me moving my arms back and forth to simulate walking within the space. It helped me further understand how I wanted the player to navigate the space and where certain things needed to be placed. Again all within Blocks and no code.
Another general tip, the snap trigger is your friend! I’ve used it for most of my modeling in Blocks to snap and place assets.
How did you experiment with different ideas and concepts?
I had a few different concepts when I started the project. Blocks allowed me to quickly build a mock up of each for testing.
Blocks is an amazing tool for spatial prototyping. Before bringing a scene into Unreal, I’d blow it up to scale and move around in the space to see if it makes sense for what I’m trying to achieve. This saved me so much time.
Without Blocks, how might this process have been different?
After all is said and done, I still had to take the geometry from Blocks and bring it into a 3D program for unwrapping and lightmap baking.
That said, even though I am proficient in traditional 3D modeling, I think the project would have taken longer to put together without Blocks. Blocks helped me take out some steps in the process. Traditionally I’d model out the scene and export pieces as I went, bringing them into the engine, placing them, and moving around to get a sense of how the space feels. All that got combined inside Blocks. Oh, and not to mention color exploration. If I wanted to try out colors I’d also have to create materials and place them on each asset during the in-engine test which takes more time. I can easily preview all of that in Blocks.
What advice would you give to other game developers about using these tools?
Keep exploring and always stay hungry. Be on the lookout for new tools that can improve your process and don’t be afraid of trying something new. If it doesn’t work out, it’s ok. We learn so much more from the challenges we take on than from the ones we don’t face by walking the easy path.
There are some amazing low poly games and artists out there. I think many artists would benefit from making models in VR using Blocks. If I was able to finish this project in two weeks, I can only imagine what a small team could do. Give it a try, and post your creations or questions using #MadeWithBlocks.
If you’d like to experience Blocks Isle on the HTC Vive, you can download the game.
Turkey, “Titanic” and the pope’s new ride were on our minds this week. Here are a few of the week’s top search trends, with data from the Google News Lab.
Almost time for turkey
As people in the U.S. prepare to gather around the table for Thanksgiving next week, our Thanksgiving insights page has all the trends. Pumpkin pie dominates searches in the U.S., but pecan pie is more popular in the southeast and apple pie is the state favorite in New Hampshire and Massachusetts. A smoked turkey is popular in most states, though some contend it should be roasted, fried or grilled. And Friendsgiving continues to rise in popularity, with searches like “friendsgiving ideas,” “friendsgiving invitations” and “friendsgiving games.”
We’ll never let go
Two decades ago, “Titanic” left an iceberg-sized hole in our hearts, and now it’s coming back to theaters in honor of its 20-year anniversary. In the years since its debut, search interest in “Titanic” reached its highest point globally in April 2012 when Titanic in 3D was released. All this talk of sinking ships made us think about other famous boats—the top searched shipwrecks this week include the Batavia, the Edmund Fitzgerald and the USS Indianapolis.
The “popemobile” got an upgrade this week. Lamborghini gifted the pope a special edition luxury car, which he decided to auction off for charity. Though the pope is known for his affinity for Fiats, interest in “Pope Lamborghini” zoomed 190 percent higher than “Pope Fiat.” People also searched to find out, “Why did the Lamborghini company give the pope a car?” and “How much does the Lamborghini that they gave the pope cost?”
That’s a foul
Searches for “UCLA basketball players” shot 330 percent higher this week when three players returned home after being arrested for shoplifting while on tour with the team in China. The search queries dribbled in: “How long are the UCLA players suspended for?” “Why did China let the UCLA players go?” and “What were the UCLA players stealing?”
All about the music
With hits like “Despacito” and “Mi Gente” taking over the globe this year, the Latin Grammys last night were a hot ticket. People searched “How to watch the Latin Grammy awards online,” “What time are the Latin Grammy awards on?” and “How does music qualify for a Latin Grammy award?” Of the nominees for Record of the Year, “Despacito,” “Guerra,” and “Felices Los 4” were the most searched.
Suhani Vora is a bioengineer, aspiring (and self-taught) machine learning expert, SNES Super Mario World ninja, and Google AI Resident. This means that she’s part of a 12-month research training program designed to jumpstart a career in machine learning. Residents, who are paired with Google AI mentors to work on research projects according to their interests, apply machine learning to their expertise in various backgrounds—from computer science to epidemiology.
I caught up with Suhani to hear more about her work as an AI Resident, her typical day, and how AI can help transform the field of genomics.
Phing: How did you get into machine learning research?
Suhani: During graduate school, I worked on engineering CRISPR/Cas9 systems, which enable a wide range of research on genomes. And though I was working with the most efficient tools available for genome editing, I knew we could make progress even faster.
One important factor was our limited ability to predict what novel biological designs would work. Each design cycle, we were only using very small amounts of previously collected data and relied on individual interpretation of that data to make design decisions in the lab.
By failing to incorporate more powerful computational methods to make use of big data and aid in the design process, it was affecting our ability to make progress quickly. Knowing that machine learning methods would greatly accelerate the speed of scientific discovery, I decided to work on finding ways to apply machine learning to my own field of genetic engineering.
I reached out to researchers in the field, asking how best to get started. A Googler I knew suggested I take the machine learning course by Andrew Ng on Coursera (could not recommend it more highly), so I did that. I’ve never had more fun learning! I had also started auditing an ML course at MIT, and reading papers on deep learning applications to problems in genomics. Ultimately, I took the plunge and and ended up joining the Residency program after finishing grad school.
Tell us about your role at Google, and what you’re working on right now.
I’m a cross-disciplinary deep learning researcher—I research, code, and experiment with deep learning models to explore their applicability to problems in genomics.
In the same way that we use machine learning models to predict the objects are present in an image (think: searching for your dogs in Google Photos), I research ways we can build neural networks to automatically predict the properties of a DNA sequence. This has all kinds of applications, like predicting whether a DNA mutation will cause cancer, or is benign.
What’s a typical day like for you?
On any given day, I’m writing code to process new genomics data, or creating a neural network in TensorFlow to model the data. Right now, a lot of my time is spent troubleshooting such models.
I also spend time chatting with fellow Residents, or a member of the TensorFlow team, to get their expertise on the experiments or code I’m writing. This could include a meeting with my two mentors, Mark DePristo and Quoc Le, top researchers in the field of machine learning who regularly provide invaluable guidance for developing the neural network models I’m interested in.
What do you like most about the AI Residency program? About working at Google?
I like the freedom to pursue topics of our interest, combined with the strong support network we have to get things done. Google is a really positive work environment, and I feel set up to succeed. In a different environment I wouldn’t have the chance to work with a world-class researcher in computational genomics like Mark, AND Quoc, one of the world’s leading machine learning researchers, at time same time and place. It’s pretty mind-blowing.
What kind of background do you need to work in machine learning?
We have such a wide array of backgrounds among our AI Residents! The only real common thread I see is a very strong desire to work on machine learning, or to apply machine learning to a particular problem of choice. I think having a strong background in linear algebra, statistics, computer science, and perhaps modeling makes things easier—but these skills are also now accessible to almost anyone with an interest, through MOOCs!
What kinds of problems do you think that AI can help solve for the world?
Ultimately, it really just depends how creative we are in figuring out what AI can do for us. Current deep learning methods have become state of the art for image recognition tasks, such as automatically detecting pets or scenes in images, and natural language processing, like translating from Chinese to English. I’m excited to see the next wave of applications in areas such as speech recognition, robotic handling, and medicine.
Interested in the AI Residency? Check out submission details and apply for the 2018 program on our Careers site.