"To support this transition, we needed to provide our business and editorial teams with the ability to design, build, and deploy new functionalities in hours or days, not in weeks or months.”
“The trouble is, I don't know which half.”
"We look forward to seeing how families interact with the Hundred Acre Wood experience and hope that they have a lot of fun engaging with our characters — just as they have for the last 90 years, but now in a thoroughly modern way… Google Maps APIs are great to …
"We wanted to use deep learning techniques to make our robots more intelligent and autonomous. But training these models requires an extreme amount of compute power for training and running simulations. That's where Google Cloud comes into play."
"For the majority of our portfolio, our current architecture still worked pretty well. But we wanted to push our customers to push even more data. We wanted to transfer even more power to our users."
“One of our key challenges is to reduce time to market, while making sure that the solutions we launch for our clients remain secure and reliable. That’s why we decided to move to the cloud, and as we wanted to use Kubernetes, Google Cloud was the natural choice.”
"Because we now have scalable architecture that can handle deeper functionality, we no longer have to support edge cases and focus on fixing things. Now, we can focus on deepening our functionality and innovating. We can do more, and we can do it on a bigger scale."
“Because we’ve been able to automate our deployments on Google Kubernetes Engine, the risk connected to the development life cycle and new feature deployment is much lower. That enables us to achieve a faster time to market without compromising on security or availability.”
“Understanding the genetics of the Brazilian population will not only help us understand our history but also greatly improve the quality of genetic tests, which will in turn directly help our patients.”
"You can move much faster building products on Google Cloud than on AWS."
“It’s a new market, but the potential is huge. So the main goal has been to identify a way to launch small and rapidly scale up, in a cost-effective manner.”
“We want to be on the cutting edge of healthcare provision today, and that means adopting AI and machine learning technologies to access insights from data and use it to make our services more patient-centric. With its AI-first approach, Google Cloud stands out from other cloud providers.”
"Discovering optimal uses for powerful Google Maps tools such as Place Details API, Places API and Geocoding API transformed our ability to grow our business and bring in a new generation of customers. Partnering with Searce opened new possibilities in Google Maps that we never before imagined."
"To increase the accuracy of the deep learning model, the training must be repeated and the parameters revised countless times. In the past, it took around 20 days of training for the model to process tens of thousands of pieces of data, but since we have migrated to Google Cloud, …
"We used Cloud Composer to orchestrate ETLs, whose ingestion is done through Dataflow. BigQuery was used as a data warehouse. Everything was automated using Cloud Datastore as setup."
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