Public Cloud
How To Run A Large Scale ML Workflow On Dataflow ML For Autonomous Driving
Developing autonomous driving technology is a battle with data, both from a volume and data format point of view. Sources include point cloud 3D data obtained from LIDAR, video data obtained from multiple cameras, GPS position information, millimeter-wave radar, steering and various sensor information. Even in a busy city, less than 1% of the raw data …
Document AI For Government Makes It Easier To Process Documents And Deliver Better Constituent Services
Document AI for government makes it easier to process paper documents Every year, government agencies are responsible for distributing services and benefits that require processing billions of documents, images and forms. These documents are often expected to be manually transcribed into an electronic system error-free by a government employee to support time-sensitive tasks such as …
Using AI To Increase Asset Utilization And Production Uptime For Manufacturers
Today, manufacturers are advancing on their factory digitalization journey, betting on innovative technologies to strengthen competitiveness, deliver sustainable growth, and offer new services. Macroeconomic factors – such as high energy costs, increasing labor, and raw material shortages – drive the need for urgent operational optimizations and automation.Cloud capabilities have matured at an accelerated pace, giving …
Document AI: A Unified AI Agent For Your Document Processing Needs
As I type this blog in a Google Doc, I can’t help but think about how much we rely on digital documents to communicate, collaborate, and do business. Yet most of the data in documents remains un-analyzed. Even when documents are part of customer-facing workflows like processing a mortgage application or a contract, businesses frequently …
New AI Agents Can Drive Business Results Faster: Translation Hub, Document AI, And Contact Center AI
When it comes to the adoption of artificial intelligence (AI), we have reached a tipping point. Technologies that were once accessible to only a few are now broadly available. This has led to an explosion in AI investment. However, according to research firm McKinsey, for AI to make a sizable contribution to a company’s bottom line, they …
Streamline Your Models To Production With The Vertex AI Model Registry
Machine learning (ML) is iterative in nature — model improvement is a necessity to drive the best business outcomes. Yet, with the proliferation of model artifacts, it can be difficult to ensure that only the best models make it into production. Data science teams may get access to new training data, expand the scope of …
AWS And SK Telecom Collaborate To Co-Develop Computer Vision AI Services
Amazon Web Services (AWS), an Amazon.com company (NASDAQ: AMZN), and SK Telecom, the information and communications technology arm of SK Group, the second largest conglomerate in Korea, today announced at Mobile World Congress (MWC) Las Vegas that the two companies will co-develop a new set of computer vision services. This collaboration aims to make it easier and more cost effective for customers to …
Lufthansa Increases On-Time Flights By Wind Forecasting With Google Cloud ML
The magnitude and direction of wind significantly impacts airport operations, and Lufthansa Group Airlines are no exception. A particularly troublesome kind is called BISE: it is a cold, dry wind that blows from the northeast to southwest in Switzerland, through the Swiss Plateau. Its effects on flight schedules can be severe, such as forcing planes …
How Volkswagen And Google Cloud Are Using Machine Learning To Design More Energy-Efficient Cars
Volkswagen strives to design beautiful, performant, and energy efficient vehicles. This entails an iterative process where designers go through many design drafts, evaluating each, integrating the feedback, and refining. For example, a vehicle’s drag coefficient—its resistance to air—is one of the most important factors of energy efficiency. Thus, getting estimates of the drag coefficient for …
Building A Machine Learning Platform With Kubeflow And Ray On Google Kubernetes Engine
Increasingly more enterprises adopt Machine Learning (ML) capabilities to enhance their services, products, and operations. As their ML capabilities mature, they build centralized ML Platforms to serve many teams and users across their organization. Machine learning is inherently an experimental process requiring repeated iterations. An ML Platform standardizes the model development and deployment workflow to …