MEDIA AND BROADCASTING
CommScope | September 20, 2022
CommScope (NASDAQ: COMM), announced the launch of HomeVista™ solutions, a portfolio that leverages the technologies of AndroidTV and RDK-based streamer solutions for service providers to simplify and accelerate the introduction of new, innovative video services.With HomeVista solutions, service providers can deliver video services that offer streaming services and live TV with an individualized user experience, introduce streamer services to the market faster, and reduce development costs by avoiding fully customized solutions.
The HomeVista solution employs open-source software, including AndroidTV and RDK to deliver pre-integrated leading streaming applications that may include Netflix, Prime Video, Disney+, YouTube and more.1
The RDK-based HomeVista solution includes AppCloud from ActiveVideo, which provides operators the ability to deliver the latest, most up to date OTT content and applications. As opposed to traditional native app ports that can be resource intensive, time consuming and difficult to maintain, AppCloud runs standard Android OTT apps in the cloud and leverages state-of-the-art virtualization. This modern approach allows app providers to deliver app-based entertainment quickly and cost-effectively to operators at scale and makes it simple for service providers to deliver and maintain an evergreen OTT consumer experience.
“Our service provider customers are looking to us to offer next-generation solutions that combine top tier OTT applications with their streamed TV services to take their subscribers’ viewing experience to the next level, Our HomeVista portfolio enables our service provider customers to bring streaming video services to market faster than ever before.”
-Joe Chow, President, Home Networks, CommScope.
Within a defined scope, the HomeVista solution offers service providers the opportunity to customize the consumer experience through:
Installation of their own TV app that can be launched on boot and via a dedicated remote-control unit (RCU) button. It is also prominently displayed on the user interface (UI).
Customizable splash screen, RCU and streamer case
CommScope Home Networks Professional Services can provide additional customization on the HomeVista platform.
HomeVista solutions are also fully manageable, including USP (TR-369), and there is the option to use the HomeAssure® Software Update Service for life-cycle management.
The HomeVista suite of market-ready 4K UHD, Wi-Fi 6/Ethernet-connected streamers utilize high-performance hardware with a variety of form-factors including dongle and compact set-top. Voice-enabled services are supported via optional push-to-talk remote controls. These solutions have been designed with sustainability objectives in mind, including:
All trademarks identified by ™ or ® are trademarks or registered trademarks of CommScope, Inc. in the U.S. and may be registered in other countries. Android is a trademark of Google LLC. All other product names, trademarks and registered trademarks are property of their respective owners.
CommScope (NASDAQ: COMM) is pushing the boundaries of technology to create the world’s most advanced wired and wireless networks. Our global team of employees, innovators and technologists empower customers to anticipate what’s next and invent what’s possible. Discover more at www.commscope.com.
Azerion | November 25, 2022
Azerion has announced the acquisition of AdPlay, an Italian based digital advertising platform. Together, the companies will provide advertisers with access to even larger audiences in Italy through exciting new formats and content like digital out of home and first look at highly relevant sports content. At the same time, publishing partners will benefit from the additional revenues and advertising formats Azerion will bring to them.
“I am pleased to announce the acquisition of AdPlay and strengthen our advertising business in Italy. The AdPlay team is a perfect fit with our Azerion culture, and their local expertise and experience will add to our ability to help our Italian customers to get the results they need from their advertising budgets. I am also very excited to welcome AdPlay’s Italian partners to the Azerion platform and grow our business together with them as well as extending our connected TV and digital out of home reach in the local market.”
-Umut Akpinar, co-CEO of Azerion
Azerion will integrate AdPlay’s digital cross-media solutions and campaign performance management, adding to its robust current offering in these areas. AdPlay exclusively represents some of the most relevant Italian publishers and has been pioneering the digital out of home market in Italy. Through this acquisition, Azerion will strengthen its position in Italy and increase its relevance as a partner that delivers easy, impactful and affordable access to large and diverse audiences through highly engaging content.
Additionally, AdPlay recently launched Veedly, a dedicated solution focused on the distribution of on-demand multimedia content from the world of sports. Veedly is already cooperating with various sports leagues.
The aggregated consideration is a combination of cash and shares. In total, 580,470 treasury shares were transferred to the selling shareholder. The transaction is effective as of 11th November 2022. AdPlay generated approximately €12 million gross revenue in 2021. This announcement follows various previous acquisitions in 2022, as Azerion continues to execute on its growth strategy. So far this year, Azerion has acquired an estimated annualised revenue in the range of €100 million to €125 million for a total aggregated consideration (combination of cash and shares) in the range of €90 million to €100 million.
Azerion is a high-growth digital entertainment and media platform. As a content-driven, technology and data company, Azerion serves consumers, digital publishers, advertisers, and game creators globally. Azerion’s integrated platform provides technology solutions to automate the purchase and sale of digital advertising for media buyers and sellers, supported by in-market sales and campaign management teams. Through our technology, content creators, digital publishers and advertisers work with Azerion to reach the millions of people across the globe that play Azerion’s games and view its distributed entertainment content to increase engagement, loyalty, and drive e-commerce. Founded in 2014 by two Dutch entrepreneurs, Azerion has experienced rapid expansion driven by organic growth and strategic acquisitions. Azerion is headquartered in Amsterdam, the Netherlands and is a publicly traded company listed on Euronext Amsterdam. For more information visit: www.azerion.com.
AdPlay is a tech media company focused on the development of proprietary solutions for Publishers and Brand advertisers. AdPlay Media Holding is a strategic partner for the implementation of digital transformation and innovation plans, through its owned technologies and tailored consulting services.
TECHNOLOGIES, MEDIA AND BROADCASTING
AWS | October 11, 2022
Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), announced the general availability of Amazon Elastic Compute Cloud (Amazon EC2) Trn1 instances powered by AWS-designed Trainium chips. Trn1 instances are purpose built for high-performance training of machine learning models in the cloud while offering up to 50% cost-to-train savings over comparable GPU-based instances. Trn1 instances provide the fastest time to train popular machine learning models on AWS, enabling customers to reduce training times, rapidly iterate on models to improve accuracy, and increase productivity for workloads like natural language processing, speech and image recognition, semantic search, recommendation engines, fraud detection, and forecasting. There are no minimum commitments or upfront fees to use Trn1 instances, and customers pay only for the amount of compute used. To get started with Trn1 instances, visit aws.amazon.com/ec2/instance-types/trn1.ore customers are building, training, and deploying machine learning models to power applications that have the potential to reinvent their businesses and customer experiences.
These machine learning models are becoming increasingly complex and consume ever-growing amounts of training data to help improve accuracy. As a result, customers must scale their models across thousands of accelerators, which makes them more expensive to train. This directly impacts the ability of research and development teams to experiment and train different models, which limits how quickly customers are able to bring their innovations to market. AWS already provides the broadest and deepest choice of compute offerings featuring hardware accelerators for machine learning, including Inf1 instances with AWS-designed Inferentia chips, G5 instances, P4d instances, and DL1 instances. But even with the fastest accelerated instances available today, training more complex machine learning models can still be prohibitively expensive and time consuming.
New Trn1 instances powered by AWS Trainium chips offer the best price performance and the fastest machine learning model training on AWS, providing up to 50% lower cost to train deep learning models compared to the latest GPU-based P4d instances. AWS Neuron, the software development kit (SDK) for Trn1 instances, enables customers to get started with minimal code changes and is integrated into popular frameworks for machine learning like PyTorch and TensorFlow. Trn1 instances feature up to 16 AWS Trainium accelerators that are purpose built for deploying deep learning models. Trn1 instances are the first Amazon EC2 instance to offer up to 800 Gbps of networking bandwidth (lower latency and 2x faster than the latest EC2 GPU-based instances) using the second generation of AWS’s Elastic Fabric Adapter (EFA) network interface to improve scaling efficiency.
Trn1 instances also use NeuronLink, a high-speed, intra-instance interconnect, for faster training. Customers deploy Trn1 instances in Amazon EC2 UltraClusters consisting of tens of thousands of Trainium accelerators to rapidly train even the most complex deep learning models with trillions of parameters. With EC2 UltraClusters, customers will be able to scale the training of machine learning models with up to 30,000 Trainium accelerators interconnected with EFA petabit-scale networking, which gives customers on-demand access to supercomputing-class performance to cut training time from months to days. Each Trn1 instance supports up to 8 TB of local NVMe SSD storage for fast access to large datasets. AWS Trainium supports a wide range of data types (FP32, TF32, BF16, FP16, and configurable FP8) and stochastic rounding, a way of rounding probabilistically that enables high performance and higher accuracy as compared to legacy rounding modes often used in deep learning training. AWS Trainium also supports dynamic tensor shapes and custom operators to deliver a flexible infrastructure designed to evolve with customers' training needs.
“Over the years we have seen machine learning go from a niche technology used by the largest enterprises to a core part of many of our customers' businesses, and we expect machine learning training will rapidly make up a large portion of their compute needs, Building on the success of AWS Inferentia, our high-performance machine learning chip, AWS Trainium is our second-generation machine learning chip purpose built for high-performance training. Trn1 instances powered by AWS Trainium will help our customers reduce their training time from months to days, while being more cost efficient.”
-David Brown, vice president of Amazon EC2 at AWS
Trn1 instances are built on the AWS Nitro System, a collection of AWS-designed hardware and software innovations that streamline the delivery of isolated multi-tenancy, private networking, and fast local storage. The AWS Nitro System offloads the CPU virtualization, storage, and networking functions to dedicated hardware and software, delivering performance that is nearly indistinguishable from bare metal. Trn1 instances will be available via additional AWS services including Amazon SageMaker, Amazon Elastic Kubernetes Service (Amazon EKS), Amazon Elastic Container Service (Amazon ECS), and AWS Batch. Trn1 instances are available for purchase as On-Demand Instances, with Savings Plans, as Reserved Instances, or as Spot Instances. Trn1 instances are available today in US East (N. Virginia) and US West (Oregon), with availability in additional AWS Regions coming soon. For more information on Trn1 instances, visit aws.amazon.com/blogs/aws/amazon-ec2-trn1-instances-for-high-performance-model-training-are-now-available.
Amazon’s product search engine indexes billions of products, serves billions of customer queries daily, and is one of the most heavily used services in the world. “We are training large language models that are multi-modal, multilingual, multi-locale, pre-trained on multiple tasks, and span multiple entities (products, queries, brands, reviews, etc.) to improve the customer shopping experience,” said Trishul Chilimbi, senior principal scientist at Amazon Search. “Amazon EC2 Trn1 instances provide a more sustainable way to train large language models by delivering the best performance/watt compared to other accelerated machine learning solutions and offers us high performance at the lowest cost. We plan to explore the new configurable FP8 datatype and hardware accelerated stochastic rounding to further increase our training efficiency and development velocity.
PyTorch is an open source machine learning framework that accelerates the path from research prototyping to production deployment. At PyTorch, we want to accelerate taking machine learning from research prototyping to production ready for customers. We have collaborated extensively with AWS to provide native PyTorch support for new AWS Trainium-powered Trn1 instances. Developers building PyTorch models can start training on Trn1 instances with minimal code changes,” said Geeta Chauhan, Applied AI, engineering manager at PyTorch. “Additionally, we have worked with the OpenXLA community to enable PyTorch Distributed libraries for easy model migration from GPU-based instances to Trn1 instances. We are excited about the innovation that Trn1 instances bring to the PyTorch community, including more efficient data types, dynamic shapes, custom operators, hardware-optimized stochastic rounding, and eager debug mode. All these capabilities make Trn1 well suited for wide adoption by PyTorch developers, and we look forward to future joint contributions to PyTorch to further optimize training performance.
Helixon builds next-generation artificial intelligence (AI) solutions to protein-based therapeutics, developing AI tools that empower scientists to decipher protein function and interaction, interrogate large-scale genomic datasets for target identification, and design therapeutics such as antibodies and cell therapies.
“Today, we use training distribution libraries like Fully Sharded Data Parallel to parallelize model training over many GPU-based servers, but this still takes us weeks to train a single model, We are excited to utilize Amazon EC2 Trn1 instances featuring the highest networking bandwidth available on AWS to improve the performance of our distributed training jobs and reduce our model training times, while also reducing our training costs.”
-Jian Peng, CEO at Helixon.
Money Forward, Inc. serves businesses and individuals with an open and fair financial platform. “We launched a large-scale AI chatbot service on the Amazon EC2 Inf1 instances and reduced our inference latency by 97% over comparable GPU-based instances while also reducing costs. As we keep fine-tuning tailored natural language processing models periodically, reducing model training times and costs is also important,” said Takuya Nakade, CTO at Money Forward. “Based on our experience from successful migration of inference workload on Inf1 instances and our initial work on AWS Trainium-based EC2 Trn1 instances, we expect Trn1 instances will provide additional value in improving end-to-end machine learning performance and cost.
Magic is an integrated product and research company developing AI that feels like a colleague to make the world more productive. “Training large autoregressive transformer-based models is an essential component of our work. AWS Trainium-powered Trn1 instances are designed specifically for these workloads, offering near-infinite scalability, fast inter-node networking, and advanced support for 16-bit and 8-bit data types,” said Eric Steinberger, co-founder and CEO at Magic. “Trn1 instances will help us train large models faster, at a lower cost. We are particularly excited about the native support for BF16 stochastic rounding in Trainium, increasing performance while numerical accuracy indistinguishable from full precision.”
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 87 Availability Zones within 27 geographic regions, with announced plans for 21 more Availability Zones and seven more AWS Regions in Australia, Canada, India, Israel, New Zealand, Spain, and Switzerland. 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. To learn more about AWS, visit aws.amazon.com.
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. For more information, visit amazon.com/about and follow @AmazonNews.