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Cloud Covered: 2019 in Google Cloud

As we get ready to ring in 2020 here at Google Cloud, we’re taking a look back on stories that captured the imagination, provoked new ideas, and helped us be more efficient at work. Check out our top-read posts from 2019. 

Build the cloud that's right for your business
Just like you choose the right mix of apps you want on your phone, businesses that are using cloud computing choose the apps and services that will work for them. There are a lot of options available on Google Cloud, and some of the popular posts of the past year were about new technology that came out, as well as some new concepts to understand.

Lots of businesses learned how to organize their data better. 
Different types of data, like the price of a product or how many are sold, can be used to help a business understand their customers and make future planning decisions. Many of our blog posts this year explained different ways to process and manage that data.  

Technology keeps making work easier.
The technology we use at work has come a long way in a pretty short time—it wasn’t too long ago that a video conference would have seemed like science fiction. Collaboration and productivity tools keep getting better, and in 2019, popular posts explained new ways to be efficient, and new ways to use multiple apps together. 

Cloud inspiration is all around.
Cloud computing is constantly evolving to be even faster and work better for users. Lots of the highlights of 2019 were stories from customers about how they’re using Google Cloud to power their great work—and from one of our own Googlers on her record-breaking computing accomplishment.

Keep up on everything that’s new with Google Cloud on our blog.

Using AI to find where the wild things are

According to the World Wildlife Fund, vertebrate populations have shrunk an average of 60 percent since the 1970s. And a recent UN global assessment found that we’re at risk of losing one million species to extinction, many of which may become extinct within the next decade. 

To better protect wildlife, seven organizations, led by Conservation International, and Google have mapped more than 4.5 million animals in the wild using photos taken from motion-activated cameras known as camera traps. The photos are all part of Wildlife Insights, an AI-enabled, Google Cloud-based platform that streamlines conservation monitoring by speeding up camera trap photo analysis.

With photos and aggregated data available for the world to see, people can change the way protected areas are managed, empower local communities in conservation, and bring the best data closer to conservationists and decision makers.

Wildlife managers at Instituto Humboldt take advantage of a new AI-enabled tool for processing wildlife data.

Wildlife managers at Instituto Humboldt take advantage of a new AI-enabled tool for processing wildlife data

Ferreting out insights from mountains of data

Camera traps help researchers assess the health of wildlife species, especially those that are reclusive and rare. Worldwide, biologists and land managers place motion-triggered cameras in forests and wilderness areas to monitor species, snapping millions of photos a year. 


But what do you do when you have millions of wildlife selfies to sort through? On top of that, how do you quickly process photos where animals are difficult to find, like when an animal is in the dark or hiding behind a bush? And how do you quickly sort through up to 80 percent of photos that have no wildlife at all because the camera trap was triggered by the elements, like grass blowing in the wind?


Processing all these photos isn’t only time consuming and painstaking. For decades, one of the biggest challenges has been simply collecting them. Today, millions of camera trap photos languish on the hard drives and discs of individuals and organizations worldwide.


Illuminating the natural world with AI

With Wildlife Insights, conservation scientists with camera trap photos can now upload their images to Google Cloud and run Google’s species identification AI models over the images, collaborate with others, visualize wildlife on a map and develop insights on species population health.


It’s the largest and most diverse public camera-trap database in the world that allows people to explore millions of camera-trap images, and filter images by species, country and year.


Wildlife Insights

Seven leading conservation organizations and Google released Wildlife Insights to better protect wildlife.

On average, human experts can label 300 to 1,000 images per hour. With the help of Google AI Platform Predictions, Wildlife Insights can classify the same images up to 3,000 times faster, analyzing 3.6 million photos an hour. To make this possible, we trained an AI model to automatically classify species in an image using Google’s open source TensorFlow framework. 

Even though species identification can be a challenging task for AI, across the 614 species that Google’s AI models have been trained on, species like jaguars, white-lipped peccaries and African elephants have between an 80 to 98.6 percent probability of being correctly predicted. Most importantly, images detected to contain no animals with a very high confidence are removed automatically, freeing biologists to do science instead of looking at empty images of blowing grass. 

With this data, managers of protected areas or anti-poaching programs can gauge the health of specific species, and local governments can use data to inform policies and create conservation measures. 

Wildlife Insights Animal Classifier

The Wildlife Insights Animal Classifier tool helps researchers classify 614 species.

Acting before it’s too late

Thanks to the combination of advanced technology, data sharing, partnerships and science-based analytics, we have a chance to bend the curve of species decline.

While we’re just at the beginning of applying AI to better understand wildlife from sensors in the field, solutions like Wildlife Insights can help us protect our planet so that future generations can live in a world teeming with wildlife. 

Learn more about Wildlife Insights and watch the documentary film Eyes in the Forest: Saving Wildlife In Colombia Using Camera Traps and AI. The film tells the story of a camera trapper who uses Wildlife Insights to document and preserve the biological diversity in Caño Cristales, a reserve in Colombia’s remote upper Amazon region. 

Wildlife Insights is a collaboration between Conservation International, Smithsonian’s National Zoo and Conservation Biology Institute, North Carolina Museum of Natural Sciences, Map of Life, World Wide Fund for Nature, Wildlife Conservation Society, Zoological Society of London, Google Earth Outreach,  built by Vizzuality, and supported by the Gordon and Betty Moore Foundation and Lyda Hill Philanthropies. 

mPaani raises Series A from connections made at Google’s accelerator

Jen Harvey, Head of Marketing, Google Developers Launchpad

Google Developers Launchpad is an accelerator program that excels in helping startups solve the world’s biggest problems through the best of Google, with a focus on advanced technology. However our impact doesn’t stop there. A distinguishing aspect of our program is the network that we build with, and for, our founders. Over the past five years, Launchpad has created a global community of founders based on deep, genuine connections that we foster during the program, and that community supports one another in remarkable ways.

When Akanksha Hazari Ericson, Launchpad alumna and founder of m.Paani, took the stage at Google Developers Launchpad Future of Finance Summit in March, she didn’t know what would come of it. Fast forward, she just announced a Series A financing round, led by an institutional venture investor who was in the audience and two of her fellow founders in the Launchpad Accelerator program.

“We weren't even raising at the time,” said Akanksha. “They saw our Future of Finance presentation and engaged with me right after my talk. Soon after, they were on a flight to Mumbai to meet our team and customers. Their investment initiated this round.”

The peer investment came from Launchpad alumni, and angel investors, Kevin Aluwi, CEO and Co-Founder, and Ryu Suliawan, Head of Merchants at GO-JEK, a Southeast Asian on-demand, multi-service platform and digital payment technology group. Both Kevin and Ryu saw direct value in what m.Paani and have stated their excitement to be part of m.Paani’s journey. They also saw huge strategic potential for the company to empower local retailers beyond India.

“It is because of the strong community of founders that Launchpad creates that I was able to make these amazing friends and mentors. Those connections led to this investment,” Akanksha said. “These investors have strategic relevance and add immense value to our business.”

m.Paani’s product uses machine learning technology, powered by Google Cloud, to empower more than 60 million family-owned local businesses in India by providing them with an online store front. The vast majority of local retailers are not digitized in any way; m.Paani’s solution allows them to compete with an app & web store, ability to accept digital payments, create loyalty programs, and much more.

m.Paani, who attended the Launchpad Accelerator in 2019, is now part of a wider community of Launchpad founders and companies that spans almost 400 startups across the world.

mPaani group image

"It's exciting to watch startups grow, but it's even more exciting when investment comes through the resources and connections we helped foster as part of the program,” said David McLaughlin, Director of Google Developers Ecosystem team. “We put on strong focus on founder-to-founder interaction in our curriculum, mostly via our Leaders Lab and Growth Lab. We really want to create a wider community of founders who are willing to support each other. To see m.Paani take the next step on the funding ladder through that community showcases one of the many benefits for founders who join us for this accelerator".

Akanksha, and her team, are excited about how the funds will help scale the offering for local retailers. “The funding will allow us to grow quickly, invest in product and technology, and better serve our retailers. Our retail partners are the backbone of our local economy and culture, and deserve the ability to compete in the digital age. This, more than anything else, is what gets me and our whole team up and excited every morning.”

Want to learn more about Akanksha’s founder journey with m.Paani? Check out her story here.

Cloud Covered: What was new in November on Google Cloud

November was a cornucopia of Google Cloud news and tips, with new ways for companies to start using the cloud and improve the way they work. We’re thankful this season for all the ways cloud can make everyday work easier, and for all the cool technology that just keeps evolving.  

Take this easy path to cloud.

In November, we announced the acquisition of CloudSimple, a company that provides a secure, dedicated environment to run VMware workloads in the cloud. VMware is the company that invented virtualization, a way to use physical computer servers much more efficiently (find a full explanation here). This acquisition will make it easier for businesses running all kinds of applications on VMware, like their finance or HR software, to easily migrate those workloads to Google Cloud.

Try a do-it-yourself cloud kit.

OK, so it’s a bit more complicated than putting together something from IKEA. But our Bare Metal Solution became available at the Next UK conference. When businesses are starting to run applications based in the cloud, there can be some stragglers that are harder to move than others. That may be because of their underlying code, or the fact that they were built before cloud existed. This Bare Metal Solution brings all the tools and network connections that a business needs to start using native Google Cloud services.

We get by with a little help from our … work tools.

At the same conference, we announced new, AI-powered features to help you get through your work day more efficiently. First, fresh updates to Google Docs help you produce error-free work. And second, we announced expanded integrations between the Google Assistant and G Suite. These new features continue G Suite’s mission to help businesses become more productive and to streamline work. Check out details in this post.

Thanks for calling. How can cloud help you?

Our Contact Center AI platform became generally available last month, so companies can personalize their customer support. This is the kind of technology that powers the good experiences you have when you call customer support and are directed through options using your voice. Two features of Contact Center AI, Virtual Agent and Agent Assist (which is now generally available), both improve the customer experience while adding efficiency for the business. Virtual Agent helps provide 24/7 access to immediate, conversational self-service, while Agent Assist helps customer service agents through their work with continuous support in real time.

A networking control center helps IT take charge.

The newly introduced Network Intelligence Center can help those IT teams in charge of a company’s network (yes, that’s a very important job!) monitor across the cloud and in the company’s data centers. Networks involve a lot of moving pieces, and they all have to work together to make sure everything runs smoothly, from delivering emails immediately for employees to providing fast, uninterrupted experiences for customers. The Network Intelligence Center anticipates some of the common challenges that IT teams deal with and helps them do testing and see performance easily.

That’s a wrap for November! Till next time, stay tuned to the cloud blog.

Tools to help healthcare providers deliver better care

There has been a lot of interest around our collaboration with Ascension. As a physician, I understand. Health is incredibly personal, and your health information should be private to you and the people providing your care. 

That’s why I want to clarify what our teams are doing, why we’re doing it, and how it will help your healthcare providers—and you. 

Doctors and nurses love caring for patients, but aren’t always equipped with the tools they need to thrive in their mission. We have all seen headlines like "Why doctors hate their computers," with complaints about having to use "a disconnected patchwork" that makes finding critical health information like finding a needle in the haystack. The average U.S. health system has 18 electronic medical record systems, and our doctors and nurses feel like they are "data clerks" rather than healers. 


Google has spent two decades on similar problems for consumers, building products such as Search, Translate and Gmail, and we believe we can adapt our technology to help. That’s why we’re building an intelligent suite of tools to help doctors, nurses, and other providers take better care of patients, leveraging our expertise in organizing information. 


One of those tools aims to make health records more useful, more accessible and more searchable by pulling them into a single, easy-to-use interface for doctors. I mentioned this during my presentation last month at theHLTH Conference. Ascension is the first partner where we are working with the frontline staff to pilot this tool.

Google Health - Tools to help healthcare providers deliver better care

Google Health: Tools to help healthcare providers deliver better care

This effort is challenging. Health information is incredibly complex—there are misspellings, different ways of saying the same thing, handwritten scribbles, and faxes. Healthcare IT systems also don’t talk well to each other and this keeps doctors and nurses from taking the best possible care of you. 

Policymakers and regulators across the world (e.g., CMS, HHS, the NHS, and EC)have called this out as an important issue. We’ve committed to help, and it’s why we built this system on interoperable standards

To deliver such a tool to providers, the system must operate on patients' records. This is what people have been asking about in the context of our Ascension partnership, and why we want to clarify how we handle that data.

As we noted in an earlier post, our work adheres to strict regulations on handling patient data, and our Business Associate Agreement with Ascension ensures their patient data cannot be used for any other purpose than for providing our services—this means it’s never used for advertising. We’ve also published a white paper around how customer data is encrypted and isolated in the cloud. 

To ensure that our tools are safe for Ascension doctors and nurses treating real patients, members of our team might come into contact with identifiable patient data. Because of this, we have strict controls for the limited Google employees who handle such data:

  • We develop and test our system on synthetic (fake) data and openly available datasets.

  • To configure, test, tune and maintain the service in a clinical setting, a limited number of screened and qualified Google staff may be exposed to real data. These staff undergo HIPAA and medical ethics training, and are individually and explicitly approved by Ascension for a limited time.

  • We have technical controls to further enhance data privacy. Data is accessible in a strictly controlled environment with audit trails—these controls are designed to prevent the data from leaving this environment and access to patient data is monitored and auditable.

  • We will further prioritize the development of technology that reduces the number of engineers that need access to patient data (similar to our external redactiontechnology).

  • We also participate in external certifications, like ISO 27001, where independent third-party auditors come and check our processes, including information security controls for these tools.

I graduated from medical school in 1989. I've seen tremendous progress in healthcare over the ensuing decades, but this progress has also brought with it challenges of information overload that have taken doctors’ and nurses’ attentions away from the patients they are called to serve. I believe technology has a major role to play in reversing this trend, while also improving how care is delivered in ways that can save lives. 

Cloud Covered: What was new with Google Cloud in October

As fall arrived, we fell hard for news about machine learning, new trainings for those working on cloud technology, and some tips about secure passwords. Bundle up and read on for what was hot in cloud last month.

We celebrated National Cyber Security Awareness Month. 
Cyber attacks constantly evolve, and we build automatic protections into our products to keep people safe. That’s part of the puzzle, with another big piece being what you can do to keep your accounts protected. We introduced some best practices for password management, 2019 edition, to offer tips on developing good habits around passwords. Plus, we explored some best practices around two-factor authentication (2FA) when using Google Cloud. And finally, we made the new USB-C Titan Security Keys available for everyone in the U.S.

Students of cloud can explore new cloud 101 trainings.
New trainings came out in October, designed to tackle a few of the big questions that come up when businesses are first moving their applications and data into cloud services. One big decision is whether to use Google Compute Engine or Google Kubernetes Engine (GKE). Compute Engine is more similar to how businesses have been operating their technology systems, while GKE is a newer type of technology. The trainings can help explain the hows and whys of using and setting up each of the options.

We explored tech accessibility for Disability Awareness Month.
Accessibility isn’t just about physical spaces—it also matters that apps, online content and digital tools are inclusive of all users. So during Disability Awareness Month, we explored some of the Chromebook’s accessibility features, like the Select-to-speak text reader, the ChromeVox built-in screen reader, dictation tools and more. G Suite also comes with built-in accessibility features that make it easy to add closed captioning to your presentations, use voice typing tools and more.

We heard a story about jobs and tech changing together.
Changes at work can be hard, but can also result in great things. Lots of our engineering teams follow a model, developed here, called Site Reliability Engineering (SRE). It’s a methodology that helps teams build services that are reliable for users and that take the human element of technology into account—so IT teams on call can work harmoniously without getting burned out. This story describes how the Google team in charge of the network moved to this model. It involved changing the roles of team members so they can now do fewer repetitive tasks and more of the work to solve bigger problems.

Machine learning gets better at seeing moving images.
At Google Cloud, customers use our AI Building Blocksto get started easily with machine learning without requiring AI expertise. Recent updates to our vision products offer even more ways get insights from images and video. Customers use AutoML Vision to create models that are specific to their domain, so that they can get important information from images. AutoML Vision Edge, which runs ML models for devices like sensors, now detects objects in addition to classifying images. Plus, a new feature in AutoML Video means models can be trained to track objects in videos—useful for things like traffic management or sports analytics. In addition, a new feature in the Video Intelligence API can detect, track and recognize logos of popular businesses and organizations.  

APIs took center stage.
APIs are interfaces that enable different software programs to communicate with one another—think of how you can sign in to one app on your phone with the login credentials from another. As you might imagine, these APIs are pretty important in our interconnected world, and there are quite a lot of them out there. API management, then, is its own important area of using modern technology—it’s how organizations secure, analyze, and expose APIs in ways that make it easy for developers to build on them. Google Cloud’s API management platform, Apigee, was once again recognized a leader in the 2019 Gartner Magic Quadrant for Full Lifecycle API Management. This report is often used by our customers as a reliable evaluation tool. 

That’s a wrap for October. Keep up on cloud on our blog, and we’ll see you next month.

The Singapore students using Cloud for smarter recycling

Coming up with big ideas in technology used to take the kind of time and money that only large companies had.  Now open source tools—like TensorFlow, which provides access to Google’s machine learning technology—mean anyone with a smart concept has the opportunity to make it a reality. Just ask Arjun Taneja and Vayun Mathur, two friends and high school students from Singapore with a big ambition to improve recycling rates.  

Arjun and Vayun realized that separating waste is sometimes confusing and cumbersome—something that can derail people's good intentions to recycle. Using TensorFlow, they built a “Smart Bin” that can identify types of trash and sort them automatically. The Smart Bin uses a camera to take a picture of the object inserted in the tray, then analyzes the picture with a Convolutional Neural Network, a type of machine learning algorithm designed to recognize visual objects.  

To train the algorithm, Arjun and Vayun took around 500 pictures of trash like glass bottles, plastic bottles, metal cans and paper. It’s a process that would normally be laborious and expensive. But by using Google’s Colab platform for sharing resources and advice, the students could access a high powered graphics processor (GPU) in the cloud for free. They were also able to access Tensor Processing Units, Google’s machine learning processors which power services like Translate, Photos, Search, Assistant and Gmail. These tools helped their system analyze large amounts of data at once, so the students could correct the model if it didn't recognize an object. As a result, the model learned to classify the objects even more quickly. Once the Smart Bin was trained, all they had to do was place an object in the tray, and the system could predict whether it was metal, plastic, glass or paper—with the answer popping up on a screen. 

Building on their successful trials at home, Arjun and Vayun showcased the Smart Bin with a stall at last week’s Singapore Maker Faire, and they continue to work on other projects. It’s a great example of how tools available in the cloud are cutting out processes and costs that might have held back this kind of invention in the past.

Why virtualized servers are like apples, and how they work

With fall around the corner here in the U.S., our thoughts at Google Cloud are turning to … baking. Apple pies, applesauce, apple crisps—we’ve got it all covered. 

Because, for us, when we think of apples, what comes to mind is virtualization, which is the way computer servers are divided up to be more efficient. No, really. Bear with us while we explain why. Most of the computers running the applications you use, like email and web browsing, are not just one computer. They’re a set of computers, divided up into virtual computers, also called virtual machines. (There are millions upon millions of VMs in the world, so you have an idea of the scale.) 

When this concept first arrived, it changed computing entirely. Instead of one computer in one physical box (remember those desktop towers we all used to have at work?), that one physical box could now hold multiple computers that members of the IT team managed through software (called a hypervisor). So the one computer that held all of the HR department’s applications and files, for example, could now also hold the finance team’s applications and files too, without having to buy another computer. Here’s where the apples come in: If you think of a single, non-virtualized computer as a single apple, virtualization is that apple, but sliced up. 

But what about virtualization in the cloud?
In the years since virtualization was invented, it’s come a long way, especially as the cloud has come into the picture. Now, each of those virtual computers (known as virtual machines, or VMs) don’t need to be managed by that special software on-premises, but can actually be moved to the cloud and managed there. So there are different ways a company might choose to move their VMs—usually containing most or all of the applications and data that actually run their companies—into the cloud. They might just move those apple slices as is from their grocery store package (on-prem) to a plate (the cloud). 

But they might want to update those servers to work better in the cloud and be more efficient, so people get the information they need easily and quickly. In that case, they may modernize the servers—so those apple slices might now be mixed with some cinnamon and baked into a pie. You can still make out the actual slices, but they’re different from raw slices and have different pros and cons. Or, the IT teams moving the virtual servers might go even further with changing and modernizing them, so now they’re applesauce. You can’t make out the individual servers, or slices, anymore. But they maintain the same data and information they had before, but that data can be used and accessed more easily and by more computers and users than before. 

What we find at Google Cloud is that moving those sliced apples into the cloud as they are is a good place to start. They’re familiar, and look like they did before, so it’s a successful first step in the overall move to cloud. From an IT perspective, it’s easier to keep managing those apple slices because you’re already familiar with them. 

But, eventually, your business might yearn for something beyond apple slices. And that’s when you have to start cooking a little bit. A logical step might be to turn those virtual machines into containers instead, which is somewhat akin to baking an apple pie. There are clearly similarities you can see between the virtual machines and your new containers, but it’s still different—and tastier. And, from IT’s perspective, easier to manage, since there aren’t as many separate tools to keep track of. Plus, containers let you pack even more applications in because you can use fewer computing resources for each container vs. those virtual servers you started with.

We see lots of different journeys to cloud and those are just two examples. For us, though, we like to help customers plan how they’ll get all those servers to the cloud. So no matter what you want to do with your “apple slices,” we’ll figure out the best recipe for you based on your goals, requirements and constraints.

Learn more about cloud migration.

TerraTalk is changing how Japan’s students learn English

With increasing classroom sizes, more paperwork than ever and new mandates from the ministry of education, Japanese teachers face an uphill battle in their mission to teach their students. 

Yoshiyuki Kakihara wanted to use technology to figure out a solution, with an emphasis on English language education. He created TerraTalk, an AI-powered app that allows students to have audio conversations. TerraTalk’s artificial intelligence can hear and process what the students say and give feedback, removing this burden from teachers, and reinvigorating the classroom by creating an atmosphere filled with conversation and English learning games. TerraTalk was recently part of Google Developers Launchpad Accelerator, a program that provides mentorship and support to early-stage startups.

With nine acceleration programs and 341 startup alumni, we at Launchpadhave seen firsthand how  entrepreneurs around the world are using technology and startup innovation to solve the world’s biggest problems. In the third installment of our series, “Ideas to Reality,” we talked to Yoshiyuki about why he started TerraTalk, and where he hopes it will be in the next few years. 

TerraTalk app

A look at the TerraTalk English learning app.

When did you realize you wanted to make an impact on the education field? 

I grew up on the outskirts of Tokyo as a science-savvy kid and became super interested in foreign culture. I ended up leaving my high school to study in the United Kingdom. I did well academically back home, so it was quite a shock how my English fell short of being comprehensible at all abroad. It turns out that I wasn’t alone; in Japan, very few people reach conversational level at the end of secondary or university curriculum.

I feel that this is the result of an outdated methodology where too much emphasis is placed on explaining the grammar and little to no attention on putting the language into use. To make matters worse,  80 percent of teachers in Japan are putting 100 hours of overtime per month. They don’t have time to investigate, experiment with and transform the way they teach. When I learned this, I realized that I could help by creating a new technology to ease the burden on teachers, and make learning English more engaging for students.  

Who are your customers? How is your company positively affecting them?  

We do business directly with education institutions and local education councils. With our TerraTalk app, students can engage in role-playing style conversation lessons with their mobile devices. This enables teachers to ensure their students get enough speaking time, which is difficult to achieve with conventional classroom methodologies.

We are seeing students teach each other on how to tackle the exercises, sometimes creating their own competition out of it. In some ways, the technology we are bringing is humanizing classrooms, as it frees teachers from the standard lecture format.

How did you use Google products to make TerraTalk? 

BigQuery has helped us crunch massive user data to discover how people are using our app. Google Analytics is our go-to tool for marketing and search engine analysis. We use the TensorFlow family of machine learning tools and other numerous open source projects maintained by Google. We also use G Suite as a primary business tool, because of its reliability, security and ease of use.

Why did you choose to participate in Google Launchpad?

Google is a leading company in machine learning and cloud technology applications, which we heavily rely on. The prospect of receiving support in these areas was extremely appealing, especially when you are running a startup and saving time is everything.

What was the most memorable moment from Launchpad? 

We attended Launchpad Tokyo, which had seven startups in total. In a session called Founders Circle, founders from the startups got together and shared their biggest failures to date in a fireside-chat style. It was the moment where we became a true community, and many of us are still in touch after the program.

What advice do you have for future entrepreneurs? 

Don’t quit. Find a business or market where you have a natural advantage over other people. Whether your competition is other startups or established companies, it is the people you work with who make the difference.

Cloud Covered: What was new with Google Cloud in September

September will always be back-to-school season, even for those of us who have been in the working world for awhile. At Google Cloud, we sharpened our pencils and embraced the spirit of learning new things last month with stories from customers, technology improvements, and a how-to for cloud developers. 

Mayo Clinic uses cloud to improve health.
Mayo Clinic is building its data platform on Google Cloud, which means that it’s centralizing its data into our cloud to access it and analyze it as needed. They’re also using artificial intelligence (AI) to improve patient and community health, since it can find interesting and actionable information out of all that data much faster and more easily than humans could. Mayo Clinic also plans to create machine learning models that they can share with caregivers to help treat and solve serious and complex ideas.

The small but mighty Pixelbook can do software development.
In the spirit of learning new things, we published some tips on using a Pixelbook for software development, including how to set up a workflow on a Pixelbook that can meet many modern developer needs.

Good marketing needs cloud power, too.
We also heard from advertising holding company WPP last month. They shared their Google Cloud adoption story with details on how cloud helps them provide everything that’s needed to run a modern marketing campaign. That includes work with media, creative, public relations and marketing analytics to help their many Fortune 500 customers. To help all these users, they have to be able to use all the data they collect and make sure there’s not overlapping data stored in different places.

Graphics apps and remote desktops need special capabilities to run well.
We announced the general availability of virtual display devices for Compute Engine VMs. Each VM is essentially its own computer, and these new virtual display devices can be attached to any VM that’s hosted and run with Google Cloud. The devices give video graphics capabilities to VMs at a cheaper price than the more expensive GPUs that are available, and they can help when running applications that have graphics requirements such as remote desktops.

Redesigned Admin console gets faster, more searchable for Chrome Enterprise.
It’s entirely possible that you’re reading this on Chrome Browser, which is Google’s own web browser. What you may not know is that on the back end, there are people who make sure that your browser and other systems are running smoothly at work: IT admins. To help simplify work flows for Chrome Enterprise IT admins, we redesigned a key tool that admins use to maintain their device fleet, browsers, apps, security policies, and more—the Google Admin console for Chrome Enterprise. Read more about these new features in the Admin console for Chrome Enterprise

That’s a wrap for September. Stay up to date with Google Cloud on Twitter.