Sabre To Move Airline Availability To Amazon’s Cloud

CHERYL ROSEN | 113 views

"Sabre Corp. will begin delivering cloud-based flight availability later this year using solutions from the Amazon Web Services Cloud. For travel agents, the move will enable faster shopping and faster responses, Sabre said. Cloud computing refers to the practice of using a network of remote servers to store, manage, and process data, rather than a local server or a personal computer. Generally, a cloud has servers in several locations to meet the needs of users in different areas of the world."

Spotlight

iYogi

iYogi is an early leader in fulfilling the potential of the Internet of Things (IoT). iYogi is a global software and services company providing solutions for consumers in both, the home and business. Leveraging its proprietary Digital Service Cloud IoT platform, iYogi delivers support to 3+ million customers, making it the largest independent brand generating online service requests for tech support in the world. iYogi supports consumers and businesses in 11 countries including the United States, United Kingdom, UAE, Australia, Canada, Germany, France, Spain, Italy, India and Singapore.

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CLOUD SECURITY

What Is Cloud-Native and Why Does it Matter for CI

Article | July 8, 2022

Continuous intelligence (CI) relies on the real-time analysis of streaming data to produce actionable insights in milliseconds to seconds. Such capabilities have applications throughout a business. In today’s dynamic marketplace, new CI applications that use data from various sources at any given time might be needed on very short notice.The challenge is how to have the flexibility to rapidly develop and deploy new CI applications to meet fast-changing business requirements. A common approach employed today is to use a dynamic architecture that delivers access to data, processing power, and analytics capabilities on demand. In the future, solutions also will likely incorporate artificial intelligence applications to complement the benefits of traditional analytics. Increasingly, cloud-native is the architecture of choice to build and deploy AI-embedded CI applications. A cloud-native approach offers benefits to both the business and developers. Cloud-native applications or services are loosely coupled with explicitly described dependencies.

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CLOUD SECURITY

Why Microsoft Should Spinoff Its Cloud Business

Article | August 4, 2022

Microsoft currently features old-school solutions that are growing relatively slowly (Office and Windows) and new cloud solutions that are growing tremendously (Dynamics 365 and Azure). If the company stays in its current form, Microsoft stock will keep steadily advancing. But because the company’s total top and bottom lines are never going to increase much more than 30% or 35% per year, the shares are never going to deliver truly huge returns. But that would change if the company was to spin off its rapidly growing cloud businesses. In such a scenario, the current owners of Microsoft stock would receive shares in a cutting edge cloud services company (let’s call it Azure), and shares in a company focused on providing old, mostly PC-based software to businesses and consumers.

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CLOUD SECURITY

Intelligence Giant Upgrading its Cloud Technology

Article | July 18, 2022

With the huge amounts of data in all fields, a future in the cloud is imperative to help deal with this explosion of data, especially in the field of intelligence technology. This is the reason why the US Central Intelligence Agency is updating its cloud technology. The agency has recently released a draft request for proposal for its Commercial Cloud Enterprise contract.The C2E tens of billions contract will be a multi-award commercial cloud computing contract with a five-year base period and two five-year options for a period of performance of up to 15 years, according to nextgov.com.In a March 2019 presentation by the Directorate of Digital Innovation, a division of the CIA, the department outlined its vision for C2E. It would be broad and include infrastructure, platform and software cloud services supporting a broad range of users, with a variety of security clearances and a worldwide presence, as reported by techcrunch.com. The principal C2E Program objective is to acquire cloud computing services directly from commercial cloud service providers with established records for innovation and operational excellence in cloud service delivery for a large customer base,the department stated in the presentation.Apparently, the agency prefers to avoid all the attention that the Pentagon’s JEDI cloud procurement process got, and quietly go about its business.

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AWS tags US$235 million to expand its cloud infrastructure in Latin America

Article | February 10, 2020

Amazon Web Services (AWS) is raising its stake on cloud computing infrastructure in Latin America. Proof of this is that the IT company will use R$1 billion (around US$235 million) to expand its data center in Sao Paulo. These millions will be used for its Data Processing Center located in that part of Brazil. In addition, a portion of these US$235 million will also be used to increase the services it offers to both public and private parties.The move gives reason to suggest that AWS is upping the ante in the future of startups and tech in the region that rely on cloud services to develop their own products.It launched its cloud center in Brazil in 2011 but it’ll be getting some beefing up thanks to these funds. Moreover, AWS has two Edge networks in São Paulo and two in Rio de Janeiro. As well as one in each of the following cities: Bogotá (Colombia), Buenos Aires (Argentina), and Santiago (Chile).The objective of all of this is to be the region’s prime provider of cloud infrastructure and beat out its competition AKA, Google Cloud Platform and Microsoft’s Azure.

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Spotlight

iYogi

iYogi is an early leader in fulfilling the potential of the Internet of Things (IoT). iYogi is a global software and services company providing solutions for consumers in both, the home and business. Leveraging its proprietary Digital Service Cloud IoT platform, iYogi delivers support to 3+ million customers, making it the largest independent brand generating online service requests for tech support in the world. iYogi supports consumers and businesses in 11 countries including the United States, United Kingdom, UAE, Australia, Canada, Germany, France, Spain, Italy, India and Singapore.

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AWS MANAGEMENT

adidas Migrates SAP Environments to AWS

Amazon, adidas | November 22, 2021

Amazon Web Services (AWS), an Amazon.com, Inc. company, announced that adidas AG, one of the largest sports brands in the world, has selected AWS as its preferred cloud provider for SAP workloads. With this announcement, adidas will migrate its SAP environment to AWS and implement a modern SAP S/4HANA platform. Running these business-critical SAP workloads in the cloud will enable adidas to digitize core business processes across its value chain to provide better consumer experiences, become a more data-driven business, and support new business models such as direct-to-consumer. Modernizing its ERP system with SAP provides adidas with the technology foundation needed to connect its data across its entire global operations. This new cloud-based system will support the company’s physical sales channel by enabling SAP environments to be integrated with AWS capabilities, such as machine learning and analytics, to streamline supply chain, inventory, and merchandising operations for retail stores around the world. By creating a cloud-based consumer experience, adidas can offer personalized discounts, early access to new releases and collaborations, priority consumer service, and the ability to personalize experiences and offers. AWS’s extensive SAP experience allows adidas to closely integrate its SAP S/4HANA environment with AWS technologies to enable advanced analytics capabilities, data science, and enterprise reporting. By building a cloud-based data lake on AWS, adidas will gain visibility across its internal and consumer-facing operations to deliver new business and consumer insights. By applying machine learning capabilities, such as Amazon SageMaker, AWS’s service that helps developers and data scientists build, train, and deploy machine learning models quickly in the cloud and at the edge, adidas data scientists can predict seasonal demand for products to ensure the right product is available at a specific warehouse or retail store at the right time to increase customer satisfaction. In addition, Amazon SageMaker can also be applied to sales data to enable the sports company to provide personalized product and fit recommendations. This capability will help the adidas e-commerce site to match individual consumer’s style preferences and provide a more personal experience that deepens brand loyalty. Using high performance computing on AWS, adidas is able to run complex workloads simultaneously for design teams around the world to modernize 3D design capabilities at scale. This capability will speed up the design and creation process, reduce costs, and allow for greater collaboration with consumers and designers. AWS enables the sports brand to create digital twins, virtual representation of its product lines, that will speed up the design and creation process, reduce costs, and allow for greater collaboration with consumers and designers. Overall, incorporating these technologies into the design process will result in faster product creation and design for athletic apparel and shoes, enabling designers to quickly incorporate consumer feedback at the early stages of the creation process. In addition, AWS Sustainability programs will help adidas to reduce the environmental impact of their cloud usage. AWS sustainability solutions architects, experienced advisors on sustainable infrastructure and software design, will evaluate current and future cloud architectures, and determine which technology decisions will support adidas’ overall sustainability goals. “We want to drive innovation across our business, which includes everything from how we design our products to how we engage with the consumers who buy them. By committing to cloud infrastructure, we have the scalability and elasticity we need to handle the seasonality of our business during peak demand, and support the projected growth in our e-commerce business in the years to come. Deploying SAP environments on AWS isn’t just about transforming our technology—it’s about transforming business opportunities and using AWS’s wide range of cloud capabilities to create efficiencies and bring us closer to consumers.” Markus Rautert, Senior Vice President, Technology Enablement at adidas AG “We are seeing a fundamental change in how consumer goods companies run their technology infrastructures. adidas joins the thousands of customers that run SAP on AWS, leveraging AWS’s reliable and scalable global infrastructure and unmatched SAP experience to provide key insights, drive innovation, and support the creation of new products and services,” said Greg Pearson, Vice President of Worldwide Commercial Sales at Amazon Web Services, Inc. “We look forward to working with adidas on its SAP and digital transformation strategies that will help speed the introduction of new cloud-based customer experiences like its mobile app, tailored shopping, and personalized offers that deepen the consumer relationship.” Backed by its unmatched experience in running SAP workloads, AWS helps customers get the best performance and most value out of their mission-critical SAP platforms. Running SAP on AWS gives customers the control and confidence to securely run their business, leveraging the most reliable and scalable infrastructure, the broadest set of cloud capabilities, and the largest community of technology partners to help with SAP migration and modernization. About Amazon Web Services For over 15 years, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud offering. AWS has been continually expanding its services to support virtually any cloud workload, and it now has more than 200 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, virtual and augmented reality (VR and AR), media, and application development, deployment, and management from 81 Availability Zones within 25 geographic regions, with announced plans for 27 more Availability Zones and nine more AWS Regions in Australia, Canada, India, Indonesia, Israel, New Zealand, Spain, Switzerland, and the United Arab Emirates. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—trust AWS to power their infrastructure, become more agile, and lower costs. About Amazon Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. Amazon strives to be Earth’s Most Customer-Centric Company, Earth’s Best Employer, and Earth’s Safest Place to Work. Customer reviews, 1-Click shopping, personalized recommendations, Prime, Fulfillment by Amazon, AWS, Kindle Direct Publishing, Kindle, Career Choice, Fire tablets, Fire TV, Amazon Echo, Alexa, Just Walk Out technology, Amazon Studios, and The Climate Pledge are some of the things pioneered by Amazon. About adidas adidas is a global leader in the sporting goods industry. Headquartered in Herzogenaurach/Germany, the company employs more than 62,000 people across the globe and generated sales of € 19.8 billion in 2020.

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CLOUD APP MANAGEMENT

AWS Announces General Availability of Amazon EC2 DL1 Instances

Amazon | October 27, 2021

Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company announced general availability of Amazon Elastic Compute Cloud (Amazon EC2) DL1 instances, a new instance type designed for training machine learning models. DL1 instances are powered by Gaudi accelerators from Habana Labs (an Intel company) to provide up to 40% better price performance for training machine learning models than the latest GPU-powered Amazon EC2 instances. With DL1 instances, customers can train their machine learning models faster and more cost effectively for use cases like natural language processing, object detection and classification, fraud detection, recommendation and personalization engines, intelligent document processing, business forecasting, and more. DL1 instances are available on demand via a low-cost pay-as-you-go usage model with no upfront commitments. To get started with DL1 instances, Machine learning has become mainstream as customers have realized tangible business impact from deploying machine learning models at scale in the cloud. To use machine learning in their business applications, customers start by building and training a model to recognize patterns by learning from sample data, and then apply the model on new data to make predictions. For example, a machine learning model trained on large numbers of contact center transcripts can make predictions to provide real-time personalized assistance to customers through a conversational chatbot. To improve a model's prediction accuracy, data scientists and machine learning engineers are building increasingly larger and more complex models. To maintain prediction accuracy and high quality of the models, these engineers need to tune and retrain their models frequently. This requires a considerable amount of high-performance compute resources, resulting in increased infrastructure costs. These costs can be prohibitive for customers to retrain their models at the frequency they need to maintain high-accuracy predictions, while also posing an obstacle to customers that want to begin experimenting with machine learning. New DL1 instances use Gaudi accelerators built specifically to accelerate machine learning model training by delivering higher compute efficiency at a lower cost compared to general purpose GPUs. DL1 instances feature up to eight Gaudi accelerators, 256 GB of high-bandwidth memory, 768 GB of system memory, 2nd generation Amazon custom Intel Xeon Scalable (Cascade Lake) processors, 400 Gbps of networking throughput, and up to 4 TB of local NVMe storage. Together, these innovations translate to up to 40% better price performance than the latest GPU-powered Amazon EC2 instances for training common machine learning models. Customers can quickly and easily get started with DL1 instances using the included Habana SynapseAI SDK, which is integrated with leading machine learning frameworks (e.g. TensorFlow and PyTorch), helping customers to seamlessly migrate their existing machine learning models currently running on GPU-based or CPU-based instances onto DL1 instances, with minimal code changes. Developers and data scientists can also start with reference models optimized for Gaudi accelerators available in Habana’s GitHub repository, which includes popular models for diverse applications, including image classification, object detection, natural language processing, and recommendation systems. “The use of machine learning has skyrocketed. One of the challenges with training machine learning models, however, is that it is computationally intensive and can get expensive as customers refine and retrain their modelsAWS already has the broadest choice of powerful compute for any machine learning project or application. The addition of DL1 instances featuring Gaudi accelerators provides the most cost-effective alternative to GPU-based instances in the cloud to date. Their optimal combination of price and performance makes it possible for customers to reduce the cost to train, train more models, and innovate faster.” David Brown, Vice President, of Amazon EC2, at AWS Customers can launch DL1 instances using AWS Deep Learning AMIs or using Amazon Elastic Kubernetes Service (Amazon EKS) or Amazon Elastic Container Service (Amazon ECS) for containerized applications. For a more managed experience, customers can access DL1 instances through Amazon SageMaker, making it even easier and faster for developers and data scientists to build, train, and deploy machine learning models in the cloud and at the edge. DL1 instances benefit from the AWS Nitro System, a collection of building blocks that offload many of the traditional virtualization functions to dedicated hardware and software to deliver high performance, high availability, and high security while also reducing virtualization overhead. DL1 instances are available for purchase as On-Demand Instances, with Savings Plans, as Reserved Instances, or as Spot Instances. DL1 instances are currently available in the US East (N. Virginia) and US West (Oregon) AWS Regions. Seagate Technology has been a global leader offering data storage and management solutions for over 40 years. Seagate’s data science and machine learning engineers have built an advanced deep learning (DL) defect detection system and deployed it globally across the company’s manufacturing facilities. In a recent proof of concept project, Habana Gaudi exceeded the performance targets for training one of the DL semantic segmentation models currently used in Seagate’s production. “We expect the significant price performance advantage of Amazon EC2 DL1 instances, powered by Habana Gaudi accelerators, could make a compelling future addition to AWS compute clusters,” said Darrell Louder, Senior Engineering Director of Operations, Technology and Advanced Analytics, at Seagate. “As Habana Labs continues to evolve and enables broader coverage of operators, there is potential for expanding to additional enterprise use cases, and thereby harnessing additional cost savings.” Intel has created 3D Athlete Tracking technology that analyzes athlete-in-action video in real time to inform performance training processes and enhance audience experiences during competitions. “Training our models on Amazon EC2 DL1 instances, powered by Gaudi accelerators from Habana Labs, will enable us to accurately and reliably process thousands of videos and generate associated performance data, while lowering training cost,” said Rick Echevarria, Vice President, Sales and Marketing Group, Intel. “With DL1 instances, we can now train at the speed and cost required to productively serve athletes, teams, and broadcasters of all levels across a variety of sports.” Riskfuel provides real-time valuations and risk sensitivities to companies managing financial portfolios, helping them increase trading accuracy and performance. “Two factors drew us to Amazon EC2 DL1 instances based on Habana Gaudi AI accelerators,” said Ryan Ferguson, CEO of Riskfuel. “First, we want to make sure our banking and insurance clients can run Riskfuel models that take advantage of the newest hardware. We found migrating our models to DL1 instances to be simple and straightforward—really, it was just a matter of changing a few lines of code. Second, training costs are a big component of our spending, and the promise of up to 40% improvement in price performance offers potentially substantial benefit to our bottom line.” Leidos is recognized as a top 10 health IT provider delivering a broad range of customizable, scalable solutions to hospitals and health systems, biomedical organizations, and every U.S. federal agency focused on health. “One of the numerous technologies we are enabling to advance healthcare today is the use of machine learning and deep learning for disease diagnosis based on medical imaging data. Our massive data sets require timely and efficient training to aid researchers seeking to solve some of the most urgent medical mysteries,” said Chetan Paul, CTO Health and Human Services at Leidos. “Given Leidos’ and its customers’ need for quick, easy, and cost-effective training for deep learning models, we are excited to have begun this journey with Intel and AWS to use Amazon EC2 DL1 instances based on Habana Gaudi AI processors. Using DL1 instances, we expect an increase in model training speed and efficiency, with a subsequent reduction in risk and cost of research and development.” Fractal is a global leader in artificial intelligence and analytics, powering decisions in Fortune 500 companies. “AI and deep learning are at the core of our healthcare imaging business, enabling customers to make better medical decisions. In order to improve accuracy, medical datasets are becoming larger and more complex, requiring more training and retraining of models, and driving the need for improved computing price performance,” said Srikanth Velamakanni, Group CEO of Fractal. “The new Amazon EC2 DL1 instances promise significantly lower cost training than GPU-based EC2 instances, which can help us contain costs and make AI decision-making more accessible to a broader array of customers.” About Amazon Web Services For over 15 years, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud offering. AWS has been continually expanding its services to support virtually any cloud workload, and it now has more than 200 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, virtual and augmented reality (VR and AR), media, and application development, deployment, and management from 81 Availability Zones (AZs) within 25 geographic regions, with announced plans for 24 more Availability Zones and eight more AWS Regions in Australia, India, Indonesia, Israel, New Zealand, Spain, Switzerland, and the United Arab Emirates. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—trust AWS to power their infrastructure, become more agile, and lower costs. About Amazon Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. Amazon strives to be Earth’s Most Customer-Centric Company, Earth’s Best Employer, and Earth’s Safest Place to Work. Customer reviews, 1-Click shopping, personalized recommendations, Prime, Fulfillment by Amazon, AWS, Kindle Direct Publishing, Kindle, Career Choice, Fire tablets, Fire TV, Amazon Echo, Alexa, Just Walk Out technology, Amazon Studios, and The Climate Pledge are some of the things pioneered by Amazon.

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Cloud Storage Meets Blockchain: SiaCoin Takes on Amazon, Google & Microsoft

June 13, 2016

With nearly $8 million in market capitalization, the cryptocurrency attempting to take a slice out of the enterprise cloud storage industry largely dominated by huge firms like Amazon (Amazon S3), Google (Google Cloud Storage), Microsoft (Microsoft Azure) and Dropbox (Dropbox for Business), SiaCoin, has begun to break into the mainstream.

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AWS MANAGEMENT

adidas Migrates SAP Environments to AWS

Amazon, adidas | November 22, 2021

Amazon Web Services (AWS), an Amazon.com, Inc. company, announced that adidas AG, one of the largest sports brands in the world, has selected AWS as its preferred cloud provider for SAP workloads. With this announcement, adidas will migrate its SAP environment to AWS and implement a modern SAP S/4HANA platform. Running these business-critical SAP workloads in the cloud will enable adidas to digitize core business processes across its value chain to provide better consumer experiences, become a more data-driven business, and support new business models such as direct-to-consumer. Modernizing its ERP system with SAP provides adidas with the technology foundation needed to connect its data across its entire global operations. This new cloud-based system will support the company’s physical sales channel by enabling SAP environments to be integrated with AWS capabilities, such as machine learning and analytics, to streamline supply chain, inventory, and merchandising operations for retail stores around the world. By creating a cloud-based consumer experience, adidas can offer personalized discounts, early access to new releases and collaborations, priority consumer service, and the ability to personalize experiences and offers. AWS’s extensive SAP experience allows adidas to closely integrate its SAP S/4HANA environment with AWS technologies to enable advanced analytics capabilities, data science, and enterprise reporting. By building a cloud-based data lake on AWS, adidas will gain visibility across its internal and consumer-facing operations to deliver new business and consumer insights. By applying machine learning capabilities, such as Amazon SageMaker, AWS’s service that helps developers and data scientists build, train, and deploy machine learning models quickly in the cloud and at the edge, adidas data scientists can predict seasonal demand for products to ensure the right product is available at a specific warehouse or retail store at the right time to increase customer satisfaction. In addition, Amazon SageMaker can also be applied to sales data to enable the sports company to provide personalized product and fit recommendations. This capability will help the adidas e-commerce site to match individual consumer’s style preferences and provide a more personal experience that deepens brand loyalty. Using high performance computing on AWS, adidas is able to run complex workloads simultaneously for design teams around the world to modernize 3D design capabilities at scale. This capability will speed up the design and creation process, reduce costs, and allow for greater collaboration with consumers and designers. AWS enables the sports brand to create digital twins, virtual representation of its product lines, that will speed up the design and creation process, reduce costs, and allow for greater collaboration with consumers and designers. Overall, incorporating these technologies into the design process will result in faster product creation and design for athletic apparel and shoes, enabling designers to quickly incorporate consumer feedback at the early stages of the creation process. In addition, AWS Sustainability programs will help adidas to reduce the environmental impact of their cloud usage. AWS sustainability solutions architects, experienced advisors on sustainable infrastructure and software design, will evaluate current and future cloud architectures, and determine which technology decisions will support adidas’ overall sustainability goals. “We want to drive innovation across our business, which includes everything from how we design our products to how we engage with the consumers who buy them. By committing to cloud infrastructure, we have the scalability and elasticity we need to handle the seasonality of our business during peak demand, and support the projected growth in our e-commerce business in the years to come. Deploying SAP environments on AWS isn’t just about transforming our technology—it’s about transforming business opportunities and using AWS’s wide range of cloud capabilities to create efficiencies and bring us closer to consumers.” Markus Rautert, Senior Vice President, Technology Enablement at adidas AG “We are seeing a fundamental change in how consumer goods companies run their technology infrastructures. adidas joins the thousands of customers that run SAP on AWS, leveraging AWS’s reliable and scalable global infrastructure and unmatched SAP experience to provide key insights, drive innovation, and support the creation of new products and services,” said Greg Pearson, Vice President of Worldwide Commercial Sales at Amazon Web Services, Inc. “We look forward to working with adidas on its SAP and digital transformation strategies that will help speed the introduction of new cloud-based customer experiences like its mobile app, tailored shopping, and personalized offers that deepen the consumer relationship.” Backed by its unmatched experience in running SAP workloads, AWS helps customers get the best performance and most value out of their mission-critical SAP platforms. Running SAP on AWS gives customers the control and confidence to securely run their business, leveraging the most reliable and scalable infrastructure, the broadest set of cloud capabilities, and the largest community of technology partners to help with SAP migration and modernization. About Amazon Web Services For over 15 years, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud offering. AWS has been continually expanding its services to support virtually any cloud workload, and it now has more than 200 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, virtual and augmented reality (VR and AR), media, and application development, deployment, and management from 81 Availability Zones within 25 geographic regions, with announced plans for 27 more Availability Zones and nine more AWS Regions in Australia, Canada, India, Indonesia, Israel, New Zealand, Spain, Switzerland, and the United Arab Emirates. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—trust AWS to power their infrastructure, become more agile, and lower costs. About Amazon Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. Amazon strives to be Earth’s Most Customer-Centric Company, Earth’s Best Employer, and Earth’s Safest Place to Work. Customer reviews, 1-Click shopping, personalized recommendations, Prime, Fulfillment by Amazon, AWS, Kindle Direct Publishing, Kindle, Career Choice, Fire tablets, Fire TV, Amazon Echo, Alexa, Just Walk Out technology, Amazon Studios, and The Climate Pledge are some of the things pioneered by Amazon. About adidas adidas is a global leader in the sporting goods industry. Headquartered in Herzogenaurach/Germany, the company employs more than 62,000 people across the globe and generated sales of € 19.8 billion in 2020.

Read More

CLOUD APP MANAGEMENT

AWS Announces General Availability of Amazon EC2 DL1 Instances

Amazon | October 27, 2021

Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company announced general availability of Amazon Elastic Compute Cloud (Amazon EC2) DL1 instances, a new instance type designed for training machine learning models. DL1 instances are powered by Gaudi accelerators from Habana Labs (an Intel company) to provide up to 40% better price performance for training machine learning models than the latest GPU-powered Amazon EC2 instances. With DL1 instances, customers can train their machine learning models faster and more cost effectively for use cases like natural language processing, object detection and classification, fraud detection, recommendation and personalization engines, intelligent document processing, business forecasting, and more. DL1 instances are available on demand via a low-cost pay-as-you-go usage model with no upfront commitments. To get started with DL1 instances, Machine learning has become mainstream as customers have realized tangible business impact from deploying machine learning models at scale in the cloud. To use machine learning in their business applications, customers start by building and training a model to recognize patterns by learning from sample data, and then apply the model on new data to make predictions. For example, a machine learning model trained on large numbers of contact center transcripts can make predictions to provide real-time personalized assistance to customers through a conversational chatbot. To improve a model's prediction accuracy, data scientists and machine learning engineers are building increasingly larger and more complex models. To maintain prediction accuracy and high quality of the models, these engineers need to tune and retrain their models frequently. This requires a considerable amount of high-performance compute resources, resulting in increased infrastructure costs. These costs can be prohibitive for customers to retrain their models at the frequency they need to maintain high-accuracy predictions, while also posing an obstacle to customers that want to begin experimenting with machine learning. New DL1 instances use Gaudi accelerators built specifically to accelerate machine learning model training by delivering higher compute efficiency at a lower cost compared to general purpose GPUs. DL1 instances feature up to eight Gaudi accelerators, 256 GB of high-bandwidth memory, 768 GB of system memory, 2nd generation Amazon custom Intel Xeon Scalable (Cascade Lake) processors, 400 Gbps of networking throughput, and up to 4 TB of local NVMe storage. Together, these innovations translate to up to 40% better price performance than the latest GPU-powered Amazon EC2 instances for training common machine learning models. Customers can quickly and easily get started with DL1 instances using the included Habana SynapseAI SDK, which is integrated with leading machine learning frameworks (e.g. TensorFlow and PyTorch), helping customers to seamlessly migrate their existing machine learning models currently running on GPU-based or CPU-based instances onto DL1 instances, with minimal code changes. Developers and data scientists can also start with reference models optimized for Gaudi accelerators available in Habana’s GitHub repository, which includes popular models for diverse applications, including image classification, object detection, natural language processing, and recommendation systems. “The use of machine learning has skyrocketed. One of the challenges with training machine learning models, however, is that it is computationally intensive and can get expensive as customers refine and retrain their modelsAWS already has the broadest choice of powerful compute for any machine learning project or application. The addition of DL1 instances featuring Gaudi accelerators provides the most cost-effective alternative to GPU-based instances in the cloud to date. Their optimal combination of price and performance makes it possible for customers to reduce the cost to train, train more models, and innovate faster.” David Brown, Vice President, of Amazon EC2, at AWS Customers can launch DL1 instances using AWS Deep Learning AMIs or using Amazon Elastic Kubernetes Service (Amazon EKS) or Amazon Elastic Container Service (Amazon ECS) for containerized applications. For a more managed experience, customers can access DL1 instances through Amazon SageMaker, making it even easier and faster for developers and data scientists to build, train, and deploy machine learning models in the cloud and at the edge. DL1 instances benefit from the AWS Nitro System, a collection of building blocks that offload many of the traditional virtualization functions to dedicated hardware and software to deliver high performance, high availability, and high security while also reducing virtualization overhead. DL1 instances are available for purchase as On-Demand Instances, with Savings Plans, as Reserved Instances, or as Spot Instances. DL1 instances are currently available in the US East (N. Virginia) and US West (Oregon) AWS Regions. Seagate Technology has been a global leader offering data storage and management solutions for over 40 years. Seagate’s data science and machine learning engineers have built an advanced deep learning (DL) defect detection system and deployed it globally across the company’s manufacturing facilities. In a recent proof of concept project, Habana Gaudi exceeded the performance targets for training one of the DL semantic segmentation models currently used in Seagate’s production. “We expect the significant price performance advantage of Amazon EC2 DL1 instances, powered by Habana Gaudi accelerators, could make a compelling future addition to AWS compute clusters,” said Darrell Louder, Senior Engineering Director of Operations, Technology and Advanced Analytics, at Seagate. “As Habana Labs continues to evolve and enables broader coverage of operators, there is potential for expanding to additional enterprise use cases, and thereby harnessing additional cost savings.” Intel has created 3D Athlete Tracking technology that analyzes athlete-in-action video in real time to inform performance training processes and enhance audience experiences during competitions. “Training our models on Amazon EC2 DL1 instances, powered by Gaudi accelerators from Habana Labs, will enable us to accurately and reliably process thousands of videos and generate associated performance data, while lowering training cost,” said Rick Echevarria, Vice President, Sales and Marketing Group, Intel. “With DL1 instances, we can now train at the speed and cost required to productively serve athletes, teams, and broadcasters of all levels across a variety of sports.” Riskfuel provides real-time valuations and risk sensitivities to companies managing financial portfolios, helping them increase trading accuracy and performance. “Two factors drew us to Amazon EC2 DL1 instances based on Habana Gaudi AI accelerators,” said Ryan Ferguson, CEO of Riskfuel. “First, we want to make sure our banking and insurance clients can run Riskfuel models that take advantage of the newest hardware. We found migrating our models to DL1 instances to be simple and straightforward—really, it was just a matter of changing a few lines of code. Second, training costs are a big component of our spending, and the promise of up to 40% improvement in price performance offers potentially substantial benefit to our bottom line.” Leidos is recognized as a top 10 health IT provider delivering a broad range of customizable, scalable solutions to hospitals and health systems, biomedical organizations, and every U.S. federal agency focused on health. “One of the numerous technologies we are enabling to advance healthcare today is the use of machine learning and deep learning for disease diagnosis based on medical imaging data. Our massive data sets require timely and efficient training to aid researchers seeking to solve some of the most urgent medical mysteries,” said Chetan Paul, CTO Health and Human Services at Leidos. “Given Leidos’ and its customers’ need for quick, easy, and cost-effective training for deep learning models, we are excited to have begun this journey with Intel and AWS to use Amazon EC2 DL1 instances based on Habana Gaudi AI processors. Using DL1 instances, we expect an increase in model training speed and efficiency, with a subsequent reduction in risk and cost of research and development.” Fractal is a global leader in artificial intelligence and analytics, powering decisions in Fortune 500 companies. “AI and deep learning are at the core of our healthcare imaging business, enabling customers to make better medical decisions. In order to improve accuracy, medical datasets are becoming larger and more complex, requiring more training and retraining of models, and driving the need for improved computing price performance,” said Srikanth Velamakanni, Group CEO of Fractal. “The new Amazon EC2 DL1 instances promise significantly lower cost training than GPU-based EC2 instances, which can help us contain costs and make AI decision-making more accessible to a broader array of customers.” About Amazon Web Services For over 15 years, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud offering. AWS has been continually expanding its services to support virtually any cloud workload, and it now has more than 200 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, virtual and augmented reality (VR and AR), media, and application development, deployment, and management from 81 Availability Zones (AZs) within 25 geographic regions, with announced plans for 24 more Availability Zones and eight more AWS Regions in Australia, India, Indonesia, Israel, New Zealand, Spain, Switzerland, and the United Arab Emirates. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—trust AWS to power their infrastructure, become more agile, and lower costs. About Amazon Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. Amazon strives to be Earth’s Most Customer-Centric Company, Earth’s Best Employer, and Earth’s Safest Place to Work. Customer reviews, 1-Click shopping, personalized recommendations, Prime, Fulfillment by Amazon, AWS, Kindle Direct Publishing, Kindle, Career Choice, Fire tablets, Fire TV, Amazon Echo, Alexa, Just Walk Out technology, Amazon Studios, and The Climate Pledge are some of the things pioneered by Amazon.

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Cloud Storage Meets Blockchain: SiaCoin Takes on Amazon, Google & Microsoft

June 13, 2016

With nearly $8 million in market capitalization, the cryptocurrency attempting to take a slice out of the enterprise cloud storage industry largely dominated by huge firms like Amazon (Amazon S3), Google (Google Cloud Storage), Microsoft (Microsoft Azure) and Dropbox (Dropbox for Business), SiaCoin, has begun to break into the mainstream.

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