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Killexams : HP Solutions techniques - BingNews https://killexams.com/pass4sure/exam-detail/HP2-B111 Search results Killexams : HP Solutions techniques - BingNews https://killexams.com/pass4sure/exam-detail/HP2-B111 https://killexams.com/exam_list/HP Killexams : Sale of U.S. Tractors Market to Reach 413k Units by 2028. Less than 50 HP Market Gaining Prominent – Arizton

Chicago, Aug. 08, 2022 (GLOBE NEWSWIRE) -- According to Arizton's latest research report, the U.S. tractors market is expected to grow at a CAGR of over 3.5% during 2022-2028. The agricultural tractor market in the US is currently in the growth stage, and manufacturers are looking for capacity augmentation in the country. Farm mechanization is still minimal in the Northeast and West of the country, and vendors can explore these regions with a portfolio of small tractors suitable for wet climates.

U.S. Tractors Market Report Scope

Report Attributes Details
MARKET SIZE (2028) 317 thousand Units
MARKET SIZE (2021) 413 thousand Units
CAGR (2022-2028) 3.82%  
BASE YEAR 2021  
FORECAST YEAR 2022-2028
MARKET SEGMENTS Horsepower, Drive Type, and Regions
LARGEST SEGMENT BY HORSEPOWER Less Than 50 HP
LARGEST SEGMENT BY ZONE Midwest Region
KEY VENDORS John Deere, TAFE, CNH Industrial, AGCO, and Kubota

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Development of Smart and Autonomous Tractors

The world is changing rapidly, increasing innovation, and the extensive use of robotics and AI are transforming every aspect of life. Within the next ten years, the current farming method will be completely transformed using autonomous tractors and agricultural robots that will perform time-consuming tasks in a much more efficient and effective manner. Autonomous tractors are driverless, and they operate with minimum or without any human intervention. The autonomous tractor technology is in its development stage and is expected to be an initiative to increase automation in agriculture and farming. Some leading autonomous tractor players globally are AGCO, CNH, Mahindra & Mahindra, John Deere, and Kubota.

Key Insights

  • 2-Wheel-Drive segment accounted 98.9% of the market share in the overall tractor market. The less than 50 HP segment, which accounts for the majority of market share, is expected to grow at a CAGR of 4.22 percent during the forecast period.
  • With more than 60% share, tractors are the largest segment of agricultural equipment in the US. In addition, the US is the largest exporter of tractors in the North America. The number of tractors manufactured in The US accounts for around two-third of the total number of tractors manufactured in North American countries.
  • U.S. government schemes and initiatives to facilitate credit to Improve agriculture-related operations are the major drivers contributing to the growth of the overall value chain in the US agricultural sector. The US being one of the major countries in the North America, the market scenario is expected to change and was likely to grow from 2020 due to an improvement of the country's economy because of (The American Rescue Plan Act, 2021) economic stimulus package of $1.9 trillion rolled out by the government.
  • Government strategies to enhance the welfare of farmers by converting agriculture into a viable activity are paving the way for new tractor purchases. The awareness of advanced agriculture equipment to Improve per hectare yield, reduce the overall cost of crop production, and increase the incomes of farmers is boosting the sales of new tractors in the U.S.
  • The U.S., a new frontier of innovation is emerging as agriculture meets digital technologies, opening various paths to a smart agricultural future. The smart agriculture will happen with the help of various technologies such as self-driving or autonomous tractors and GPS technology, among others. Self-driving or autonomous tractors can help farmers reduce working hours, however, there is a huge potential for data monitoring.
  • The US market witnessed an unexpected rise in tractor sales in 2021 and maintained it until now. Interestingly, the highest growth in the US tractor market was seen in the low HP power segments.
  • The key players in the US agriculture tractor market are John Deere, Massey Ferguson, and New Holland. In terms of units sold, John Deere and Massey Ferguson are the market leaders which accounted for more than 40% of overall the US agriculture tractors market in 2021.

Key Vendors

  • John Deere
  • TAFE
  • CNH Industrial
  • AGCO
  • Kubota

Other Prominent Vendors

  • Mahindra & Mahindra
  • Deutz-Fahr
  • Yanmar
  • ISEKI
  • ACE
  • SDF
  • Escorts

Horsepower

  • Less Than 50 HP
  • 50−100 HP
  • Above 100 HP

Drive Type

  • 2-Wheel-Drive
  • 4-Wheel-Drive

Regions
U.S.

  • Northeast
  • Midwest
  • South
  • West

Explore our  automotive mobility profile to know more about the industry.  

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About Arizton:   

Arizton Advisory and Intelligence is an innovation and quality-driven firm, which offers cutting-edge research solutions to clients across the world. We excel in providing comprehensive market intelligence reports and advisory and consulting services.  

We offer comprehensive market research reports on industries such as consumer goods & retail technology, automotive and mobility, smart tech, healthcare, and life sciences, industrial machinery, chemicals, and materials, IT and media, logistics and packaging. These reports contain detailed industry analysis, market size, share, growth drivers, and trend forecasts.  

Arizton comprises a team of exuberant and well-experienced analysts who have mastered in generating incisive reports. Our specialist analysts possess exemplary skills in market research. We train our team in advanced research practices, techniques, and ethics to outperform in fabricating impregnable research reports.  

Click Here to Contact Us  

Call: +1-312-235-2040  
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© 2022 Benzinga.com. Benzinga does not provide investment advice. All rights reserved.

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Killexams : QinetiQ expands U.S. footprint with Avantus Federal deal

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Killexams : IBM Research Rolls Out A Comprehensive AI And Platform-Based Edge Research Strategy Anchored By Enterprise Partnerships & Use Cases

I recently met with Dr. Nick Fuller, Vice President, Distributed Cloud, at IBM Research for a discussion about IBM’s long-range plans and strategy for artificial intelligence and machine learning at the edge.

Dr. Fuller is responsible for providing AI and platform–based innovation for enterprise digital transformation spanning edge computing and distributed cloud management. He is an IBM Master Inventor with over 75 patents and co-author of 75 technical publications. Dr. Fuller obtained his Bachelor of Science in Physics and Math from Morehouse College and his PhD in Applied Physics from Columbia University.

Edge In, not Cloud Out

In general, Dr. Fuller told me that IBM is focused on developing an "edge in" position versus a "cloud out" position with data, AI, and Kubernetes-based platform technologies to scale hub and spoke deployments of edge applications.

A hub plays the role of a central control plane used for orchestrating the deployment and management of edge applications in a number of connected spoke locations such as a factory floor or a retail branch, where data is generated or locally aggregated for processing.

“Cloud out” refers to the paradigm where cloud service providers are extending their cloud architecture out to edge locations. In contrast, “edge in” refers to a provider-agnostic architecture that is cloud-independent and treats the data-plane as a first-class citizen.

IBM's overall architectural principle is scalability, repeatability, and full stack solution management that allows everything to be managed using a single unified control plane.

IBM’s Red Hat platform and infrastructure strategy anchors the application stack with a unified, scalable, and managed OpenShift-based control plane equipped with a high-performance storage appliance and self-healing system capabilities (inclusive of semi-autonomous operations).

IBM’s strategy also includes several in-progress platform-level technologies for scalable data, AI/ML runtimes, accelerator libraries for Day-2 AI operations, and scalability for the enterprise.

It is an important to mention that IBM is designing its edge platforms with labor cost and technical workforce in mind. Data scientists with PhDs are in high demand, making them difficult to find and expensive to hire once you find them. IBM is designing its edge system capabilities and processes so that domain experts rather than PhDs can deploy new AI models and manage Day-2 operations.

Why edge is important

Advances in computing and storage have made it possible for AI to process mountains of accumulated data to provide solutions. By bringing AI closer to the source of data, edge computing is faster and more efficient than cloud. While Cloud data accounts for 60% of the world’s data today, vast amounts of new data is being created at the edge, including industrial applications, traffic cameras, and order management systems, all of which can be processed at the edge in a fast and timely manner.

Public cloud and edge computing differ in capacity, technology, and management. An advantage of edge is that data is processed and analyzed at / near its collection point at the edge. In the case of cloud, data must be transferred from a local device and into the cloud for analytics and then transferred back to the edge again. Moving data through the network consumes capacity and adds latency to the process. It’s easy to see why executing a transaction at the edge reduces latency and eliminates unnecessary load on the network.

Increased privacy is another benefit of processing data at the edge. Analyzing data where it originates limits the risk of a security breach. Most of the communications between the edge and the cloud is then confined to such things as reporting, data summaries, and AI models, without ever exposing the raw data.

IBM at the Edge

In our discussion, Dr. Fuller provided a few examples to illustrate how IBM plans to provide new and seamless edge solutions for existing enterprise problems.

Example #1 – McDonald’s drive-thru

Dr. Fuller’s first example centered around Quick Service Restaurant’s (QSR) problem of drive-thru order taking. Last year, IBM acquired an automated order-taking system from McDonald's. As part of the acquisition, IBM and McDonald's established a partnership to perfect voice ordering methods using AI. Drive-thru orders are a significant percentage of total QSR orders for McDonald's and other QSR chains.

McDonald's and other QSR restaurants would like every order to be processed as quickly and accurately as possible. For that reason, McDonald's conducted trials at ten Chicago restaurants using an edge-based AI ordering system with NLP (Natural Language Processing) to convert spoken orders into a digital format. It was found that AI had the potential to reduce ordering errors and processing time significantly. Since McDonald's sells almost 7 million hamburgers daily, shaving a minute or two off each order represents a significant opportunity to address labor shortages and increase customer satisfaction.

Example #2 – Boston Dynamics and Spot the agile mobile robot

According to an earlier IBM survey, many manufacturers have already implemented AI-driven robotics with autonomous decision-making capability. The study also indicated that over 80 percent of companies believe AI can help Improve future business operations. However, some companies expressed concern about the limited mobility of edge devices and sensors.

To develop a mobile edge solution, IBM teamed up with Boston Dynamics. The partnership created an agile mobile robot using IBM Research and IBM Sustainability Software AI technology. The device can analyze visual sensor readings in hazardous and challenging industrial environments such as manufacturing plants, warehouses, electrical grids, waste treatment plants and other hazardous environments. The value proposition that Boston Dynamics brought to the partnership was Spot the agile mobile robot, a walking, sensing, and actuation platform. Like all edge applications, the robot’s wireless mobility uses self-contained AI/ML that doesn’t require access to cloud data. It uses cameras to read analog devices, visually monitor fire extinguishers, and conduct a visual inspection of human workers to determine if required safety equipment is being worn.

IBM was able to show up to a 10X speedup by automating some manual tasks, such as converting the detection of a problem into an immediate work order in IBM Maximo to correct it. A fast automated response was not only more efficient, but it also improved the safety posture and risk management for these facilities. Similarly, some factories need to thermally monitor equipment to identify any unexpected hot spots that may show up over time, indicative of a potential failure.

IBM is working with National Grid, an energy company, to develop a mobile solution using Spot, the agile mobile robot, for image analysis of transformers and thermal connectors. As shown in the above graphic, Spot also monitored connectors on both flat surfaces and 3D surfaces. IBM was able to show that Spot could detect excessive heat build-up in small connectors, potentially avoiding unsafe conditions or costly outages. This AI/ML edge application can produce faster response times when an issue is detected, which is why IBM believes significant gains are possible by automating the entire process.

IBM market opportunities

Drive-thru orders and mobile robots are just a few examples of the millions of potential AI applications that exist at the edge and are driven by several billion connected devices.

Edge computing is an essential part of enterprise digital transformation. Enterprises seek ways to demonstrate the feasibility of solving business problems using AI/ML and analytics at the edge. However, once a proof of concept has been successfully demonstrated, it is a common problem for a company to struggle with scalability, data governance, and full-stack solution management.

Challenges with scaling

“Determining entry points for AI at the edge is not the difficult part,” Dr. Fuller said. “Scale is the real issue.”

Scaling edge models is complicated because there are so many edge locations with large amounts of diverse content and a high device density. Because large amounts of data are required for training, data gravity is a potential problem. Further, in many scenarios, vast amounts of data are generated quickly, leading to potential data storage and orchestration challenges. AI Models are also rarely "finished." Monitoring and retraining of models are necessary to keep up with changes the environment.

Through IBM Research, IBM is addressing the many challenges of building an all-encompassing edge architecture and horizontally scalable data and AI technologies. IBM has a wealth of edge capabilities and an architecture to create the appropriate platform for each application.

IBM AI entry points at the edge

IBM sees Edge Computing as a $200 billion market by 2025. Dr. Fuller and his organization have identified four key market entry points for developing and expanding IBM’s edge compute strategy. In order of size, IBM believes its priority edge markets to be intelligent factories (Industry 4.0), telcos, retail automation, and connected vehicles.

IBM and its Red Hat portfolio already have an established presence in each market segment, particularly in intelligent operations and telco. Red Hat is also active in the connected vehicles space.

Industry 4.0

There have been three prior industrial revolutions, beginning in the 1700s up to our current in-progress fourth revolution, Industry 4.0, that promotes a digital transformation.

Manufacturing is the fastest growing and the largest of IBM’s four entry markets. In this segment, AI at the edge can Improve quality control, production optimization, asset management, and supply chain logistics. IBM believes there are opportunities to achieve a 4x speed up in implementing edge-based AI solutions for manufacturing operations.

For its Industry 4.0 use case development, IBM, through product, development, research and consulting teams, is working with a major automotive OEM. The partnership has established the following joint objectives:

  • Increase automation and scalability across dozens of plants using 100s of AI / ML models. This client has already seen value in applying AI/ML models for manufacturing applications. IBM Research is helping with re-training models and implementing new ones in an edge environment to help scale even more efficiently. Edge offers faster inference and low latency, allowing AI to be deployed in a wider variety of manufacturing operations requiring instant solutions.
  • Dramatically reduce the time required to onboard new models. This will allow training and inference to be done faster and allow large models to be deployed much more quickly. The quicker an AI model can be deployed in production; the quicker the time-to-value and the return-on-investment (ROI).
  • Accelerate deployment of new inspections by reducing the labeling effort and iterations needed to produce a production-ready model via data summarization. Selecting small data sets for annotation means manually examining thousands of images, this is a time-consuming process that will result in - labeling of redundant data. Using ML-based automation for data summarization will accelerate the process and produce better model performance.
  • Enable Day-2 AI operations to help with data lifecycle automation and governance, model creation, reduce production errors, and provide detection of out-of-distribution data to help determine if a model’s inference is accurate. IBM believes this will allow models to be created faster without data scientists.

Maximo Application Suite

IBM’s Maximo Application Suite plays an important part in implementing large manufacturers' current and future IBM edge solutions. Maximo is an integrated public or private cloud platform that uses AI, IoT, and analytics to optimize performance, extend asset lifecycles and reduce operational downtime and costs. IBM is working with several large manufacturing clients currently using Maximo to develop edge use cases, and even uses it within its own Manufacturing.

IBM has research underway to develop a more efficient method of handling life cycle management of large models that require immense amounts of data. Day 2 AI operations tasks can sometimes be more complex than initial model training, deployment, and scaling. Retraining at the edge is difficult because resources are typically limited.

Once a model is trained and deployed, it is important to monitor it for drift caused by changes in data distributions or anything that might cause a model to deviate from original requirements. Inaccuracies can adversely affect model ROI.

Day-2 AI Operations (retraining and scaling)

Day-2 AI operations consist of continual updates to AI models and applications to keep up with changes in data distributions, changes in the environment, a drop in model performance, availability of new data, and/or new regulations.

IBM recognizes the advantages of performing Day-2 AI Operations, which includes scaling and retraining at the edge. It appears that IBM is the only company with an architecture equipped to effectively handle Day-2 AI operations. That is a significant competitive advantage for IBM.

A company using an architecture that requires data to be moved from the edge back into the cloud for Day-2 related work will be unable to support many factory AI/ML applications because of the sheer number of AI/ML models to support (100s to 1000s).

“There is a huge proliferation of data at the edge that exists in multiple spokes,” Dr. Fuller said. "However, all that data isn’t needed to retrain a model. It is possible to cluster data into groups and then use sampling techniques to retrain the model. There is much value in federated learning from our point of view.”

Federated learning is a promising training solution being researched by IBM and others. It preserves privacy by using a collaboration of edge devices to train models without sharing the data with other entities. It is a good framework to use when resources are limited.

Dealing with limited resources at the edge is a challenge. IBM’s edge architecture accommodates the need to ensure resource budgets for AI applications are met, especially when deploying multiple applications and multiple models across edge locations. For that reason, IBM developed a method to deploy data and AI applications to scale Day-2 AI operations utilizing hub and spokes.

The graphic above shows the current status quo methods of performing Day-2 operations using centralized applications and a centralized data plane compared to the more efficient managed hub and spoke method with distributed applications and a distributed data plane. The hub allows it all to be managed from a single pane of glass.

Data Fabric Extensions to Hub and Spokes

IBM uses hub and spoke as a model to extend its data fabric. The model should not be thought of in the context of a traditional hub and spoke. IBM’s hub provides centralized capabilities to manage clusters and create multiples hubs that can be aggregated to a higher level. This architecture has four important data management capabilities.

  1. First, models running in unattended environments must be monitored. From an operational standpoint, detecting when a model’s effectiveness has significantly degraded and if corrective action is needed is critical.
  2. Secondly, in a hub and spoke model, data is being generated and collected in many locations creating a need for data life cycle management. Working with large enterprise clients, IBM is building unique capabilities to manage the data plane across the hub and spoke estate - optimized to meet data lifecycle, regulatory & compliance as well as local resource requirements. Automation determines which input data should be selected and labeled for retraining purposes and used to further Improve the model. Identification is also made for atypical data that is judged worthy of human attention.
  3. The third issue relates to AI pipeline compression and adaptation. As mentioned earlier, edge resources are limited and highly heterogeneous. While a cloud-based model might have a few hundred million parameters or more, edge models can’t afford such resource extravagance because of resource limitations. To reduce the edge compute footprint, model compression can reduce the number of parameters. As an example, it could be reduced from several hundred million to a few million.
  4. Lastly, suppose a scenario exists where data is produced at multiple spokes but cannot leave those spokes for compliance reasons. In that case, IBM Federated Learning allows learning across heterogeneous data in multiple spokes. Users can discover, curate, categorize and share data assets, data sets, analytical models, and their relationships with other organization members.

In addition to AI deployments, the hub and spoke architecture and the previously mentioned capabilities can be employed more generally to tackle challenges faced by many enterprises in consistently managing an abundance of devices within and across their enterprise locations. Management of the software delivery lifecycle or addressing security vulnerabilities across a vast estate are a case in point.

Multicloud and Edge platform

In the context of its strategy, IBM sees edge and distributed cloud as an extension of its hybrid cloud platform built around Red Hat OpenShift. One of the newer and more useful options created by the Red Hat development team is the Single Node OpenShift (SNO), a compact version of OpenShift that fits on a single server. It is suitable for addressing locations that are still servers but come in a single node, not clustered, deployment type.

For smaller footprints such as industrial PCs or computer vision boards (for example NVidia Jetson Xavier), Red Hat is working on a project which builds an even smaller version of OpenShift, called MicroShift, that provides full application deployment and Kubernetes management capabilities. It is packaged so that it can be used for edge device type deployments.

Overall, IBM and Red Hat have developed a full complement of options to address a large spectrum of deployments across different edge locations and footprints, ranging from containers to management of full-blown Kubernetes applications from MicroShift to OpenShift and IBM Edge Application Manager.

Much is still in the research stage. IBM's objective is to achieve greater consistency in terms of how locations and application lifecycle is managed.

First, Red Hat plans to introduce hierarchical layers of management with Red Hat Advanced Cluster Management (RHACM), to scale by two to three orders of magnitude the number of edge locations managed by this product. Additionally, securing edge locations is a major focus. Red Hat is continuously expanding platform security features, for example by recently including Integrity Measurement Architecture in Red Hat Enterprise Linux, or by adding Integrity Shield to protect policies in Red Hat Advanced Cluster Management (RHACM).

Red Hat is partnering with IBM Research to advance technologies that will permit it to protect platform integrity and the integrity of client workloads through the entire software supply chains. In addition, IBM Research is working with Red Hat on analytic capabilities to identify and remediate vulnerabilities and other security risks in code and configurations.

Telco network intelligence and slice management with AL/ML

Communication service providers (CSPs) such as telcos are key enablers of 5G at the edge. 5G benefits for these providers include:

  • Reduced operating costs
  • Improved efficiency
  • Increased distribution and density
  • Lower latency

The end-to-end 5G network comprises the Radio Access Network (RAN), transport, and core domains. Network slicing in 5G is an architecture that enables multiple virtual and independent end-to-end logical networks with different characteristics such as low latency or high bandwidth, to be supported on the same physical network. This is implemented using cloud-native technology enablers such as software defined networking (SDN), virtualization, and multi-access edge computing. Slicing offers necessary flexibility by allowing the creation of specific applications, unique services, and defined user groups or networks.

An important aspect of enabling AI at the edge requires IBM to provide CSPs with the capability to deploy and manage applications across various enterprise locations, possibly spanning multiple end-to-end network slices, using a single pane of glass.

5G network slicing and slice management

Network slices are an essential part of IBM's edge infrastructure that must be automated, orchestrated and optimized according to 5G standards. IBM’s strategy is to leverage AI/ML to efficiently manage, scale, and optimize the slice quality of service, measured in terms of bandwidth, latency, or other metrics.

5G and AI/ML at the edge also represent a significant opportunity for CSPs to move beyond traditional cellular services and capture new sources of revenue with new services.

Communications service providers need management and control of 5G network slicing enabled with AI-powered automation.

Dr. Fuller sees a variety of opportunities in this area. "When it comes to applying AI and ML on the network, you can detect things like intrusion detection and malicious actors," he said. "You can also determine the best way to route traffic to an end user. Automating 5G functions that run on the network using IBM network automation software also serves as an entry point.”

In IBM’s current telecom trial, IBM Research is spearheading the development of a range of capabilities targeted for the IBM Cloud Pak for Network Automation product using AI and automation to orchestrate, operate and optimize multivendor network functions and services that include:

  • End-to-end 5G network slice management with planning & design, automation & orchestration, and operations & assurance
  • Network Data and AI Function (NWDAF) that collects data for slice monitoring from 5G Core network functions, performs network analytics, and provides insights to authorized data consumers.
  • Improved operational efficiency and reduced cost

Future leverage of these capabilities by existing IBM Clients that use the Cloud Pak for Network Automation (e.g., DISH) can offer further differentiation for CSPs.

5G radio access

Open radio access networks (O-RANs) are expected to significantly impact telco 5G wireless edge applications by allowing a greater variety of units to access the system. The O-RAN concept separates the DU (Distributed Units) and CU (Centralized Unit) from a Baseband Unit in 4G and connects them with open interfaces.

O-RAN system is more flexible. It uses AI to establish connections made via open interfaces that optimize the category of a device by analyzing information about its prior use. Like other edge models, the O-RAN architecture provides an opportunity for continuous monitoring, verification, analysis, and optimization of AI models.

The IBM-telco collaboration is expected to advance O-RAN interfaces and workflows. Areas currently under development are:

  • Multi-modal (RF level + network-level) analytics (AI/ML) for wireless communication with high-speed ingest of 5G data
  • Capability to learn patterns of metric and log data across CUs and DUs in RF analytics
  • Utilization of the antenna control plane to optimize throughput
  • Primitives for forecasting, anomaly detection and root cause analysis using ML
  • Opportunity of value-added functions for O-RAN

IBM Cloud and Infrastructure

The cornerstone for the delivery of IBM's edge solutions as a service is IBM Cloud Satellite. It presents a consistent cloud-ready, cloud-native operational view with OpenShift and IBM Cloud PaaS services at the edge. In addition, IBM integrated hardware and software Edge systems will provide RHACM - based management of the platform when clients or third parties have existing managed as a service models. It is essential to note that in either case this is done within a single control plane for hubs and spokes that helps optimize execution and management from any cloud to the edge in the hub and spoke model.

IBM's focus on “edge in” means it can provide the infrastructure through things like the example shown above for software defined storage for federated namespace data lake that surrounds other hyperscaler clouds. Additionally, IBM is exploring integrated full stack edge storage appliances based on hyperconverged infrastructure (HCI), such as the Spectrum Fusion HCI, for enterprise edge deployments.

As mentioned earlier, data gravity is one of the main driving factors of edge deployments. IBM has designed its infrastructure to meet those data gravity requirements, not just for the existing hub and spoke topology but also for a future spoke-to-spoke topology where peer-to-peer data sharing becomes imperative (as illustrated with the wealth of examples provided in this article).

Wrap up

Edge is a distributed computing model. One of its main advantages is that computing, and data storage and processing is close to where data is created. Without the need to move data to the cloud for processing, real-time application of analytics and AI capabilities provides immediate solutions and drives business value.

IBM’s goal is not to move the entirety of its cloud infrastructure to the edge. That has little value and would simply function as a hub to spoke model operating on actions and configurations dictated by the hub.

IBM’s architecture will provide the edge with autonomy to determine where data should reside and from where the control plane should be exercised.

Equally important, IBM foresees this architecture evolving into a decentralized model capable of edge-to-edge interactions. IBM has no firm designs for this as yet. However, the plan is to make the edge infrastructure and platform a first-class citizen instead of relying on the cloud to drive what happens at the edge.

Developing a complete and comprehensive AI/ML edge architecture - and in fact, an entire ecosystem - is a massive undertaking. IBM faces many known and unknown challenges that must be solved before it can achieve success.

However, IBM is one of the few companies with the necessary partners and the technical and financial resources to undertake and successfully implement a project of this magnitude and complexity.

It is reassuring that IBM has a plan and that its plan is sound.

Paul Smith-Goodson is Vice President and Principal Analyst for quantum computing, artificial intelligence and space at Moor Insights and Strategy. You can follow him on Twitter for more current information on quantum, AI, and space.

Note: Moor Insights & Strategy writers and editors may have contributed to this article.

Moor Insights & Strategy, like all research and tech industry analyst firms, provides or has provided paid services to technology companies. These services include research, analysis, advising, consulting, benchmarking, acquisition matchmaking, and speaking sponsorships. The company has had or currently has paid business relationships with 8×8, Accenture, A10 Networks, Advanced Micro Devices, Amazon, Amazon Web Services, Ambient Scientific, Anuta Networks, Applied Brain Research, Applied Micro, Apstra, Arm, Aruba Networks (now HPE), Atom Computing, AT&T, Aura, Automation Anywhere, AWS, A-10 Strategies, Bitfusion, Blaize, Box, Broadcom, C3.AI, Calix, Campfire, Cisco Systems, Clear Software, Cloudera, Clumio, Cognitive Systems, CompuCom, Cradlepoint, CyberArk, Dell, Dell EMC, Dell Technologies, Diablo Technologies, Dialogue Group, Digital Optics, Dreamium Labs, D-Wave, Echelon, Ericsson, Extreme Networks, Five9, Flex, Foundries.io, Foxconn, Frame (now VMware), Fujitsu, Gen Z Consortium, Glue Networks, GlobalFoundries, Revolve (now Google), Google Cloud, Graphcore, Groq, Hiregenics, Hotwire Global, HP Inc., Hewlett Packard Enterprise, Honeywell, Huawei Technologies, IBM, Infinidat, Infosys, Inseego, IonQ, IonVR, Inseego, Infosys, Infiot, Intel, Interdigital, Jabil Circuit, Keysight, Konica Minolta, Lattice Semiconductor, Lenovo, Linux Foundation, Lightbits Labs, LogicMonitor, Luminar, MapBox, Marvell Technology, Mavenir, Marseille Inc, Mayfair Equity, Meraki (Cisco), Merck KGaA, Mesophere, Micron Technology, Microsoft, MiTEL, Mojo Networks, MongoDB, MulteFire Alliance, National Instruments, Neat, NetApp, Nightwatch, NOKIA (Alcatel-Lucent), Nortek, Novumind, NVIDIA, Nutanix, Nuvia (now Qualcomm), onsemi, ONUG, OpenStack Foundation, Oracle, Palo Alto Networks, Panasas, Peraso, Pexip, Pixelworks, Plume Design, PlusAI, Poly (formerly Plantronics), Portworx, Pure Storage, Qualcomm, Quantinuum, Rackspace, Rambus, Rayvolt E-Bikes, Red Hat, Renesas, Residio, Samsung Electronics, Samsung Semi, SAP, SAS, Scale Computing, Schneider Electric, SiFive, Silver Peak (now Aruba-HPE), SkyWorks, SONY Optical Storage, Splunk, Springpath (now Cisco), Spirent, Splunk, Sprint (now T-Mobile), Stratus Technologies, Symantec, Synaptics, Syniverse, Synopsys, Tanium, Telesign,TE Connectivity, TensTorrent, Tobii Technology, Teradata,T-Mobile, Treasure Data, Twitter, Unity Technologies, UiPath, Verizon Communications, VAST Data, Ventana Micro Systems, Vidyo, VMware, Wave Computing, Wellsmith, Xilinx, Zayo, Zebra, Zededa, Zendesk, Zoho, Zoom, and Zscaler. Moor Insights & Strategy founder, CEO, and Chief Analyst Patrick Moorhead is an investor in dMY Technology Group Inc. VI, Dreamium Labs, Groq, Luminar Technologies, MemryX, and Movandi.

Mon, 08 Aug 2022 03:51:00 -0500 Paul Smith-Goodson en text/html https://www.forbes.com/sites/moorinsights/2022/08/08/ibm-research-rolls-out-a-comprehensive-ai-and-ml-edge-research-strategy-anchored-by-enterprise-partnerships-and-use-cases/
Killexams : Dynamic directing collective StyleWar join Sedona Productions
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STYLEWAR, known for their cheeky comedy and innovative visual style set the gold standard for technical feats of commercial filmmaking, always inserting their Swedish mischievous spirit into the mix. The directing collective have joined Sedona Productions for representation across Australia and New Zealand.

Founded by Oskar Holmedal and Martin Sjöström, they are drawn to technically challenging spots, and known for their razor-sharp use of hyper-real detail and explosive colour, creating their signature style. Utilising a variety of film and mixed media techniques, their films appear completely effortless, as they seamlessly combine live action, high end VFX and animation, showcasing their playfulness and brilliant sense of humour.

Their work is not only recognised globally in innovative and visually stunning spots for brands including Apple, Google, Coca-Cola, Lexus, HP, Nike, Nissan, Visa, Bacardi, Lexus, Toyota and Monday.com featured at The Superbowl. They also have a wonderful and celebrated collection of music videos.  First collaborating with Moby on the iconic “In This World” their most accurate clip “Keep Moving” for Bronson took the music and awards show circuit by storm.  Most notably winning the UKMVA Best Lockdown Video, Best Music Video and Best Animation at the 1.4 Awards and was a shortlist for Best Music Video of the Year at Shots Awards The Americas 2021 and also earned a spot on Creative Review’s coveted Best Music Video of the Year list.

Says Kim Wildenburg, managing director, Sedona Productions: “I first worked with StyleWar over 15 years ago in Los Angeles and I cannot sing their praise more highly. They are world class filmmakers with a desire to find bespoke solutions to any creative, whether it be elaborate set builds, VFX, puppetry or great performance. Their films are bold, entertaining and each one is unique. I’m delighted to offer their talent to the local market.”

For inquiries, please contact:

Kim Wildenburg on (02) 8379 1202 or via email kim@sedona.com.au.

Cinnamon Darvall at cinnamon@sedona.com.au

View StyleWar’s Reel

Wed, 03 Aug 2022 12:46:00 -0500 en-AU text/html https://campaignbrief.com/directing-collective-stylewar-join-sedona/
Killexams : Medic in heels commands respect on Ukraine's front lines

DONETSK REGION, Ukaine (AP) — All over the Donetsk region, close to the front lines of Russia’s war in Ukraine, Nataliia Voronkova turns up at Ukrainian field positions and hospitals wearing high heels. A colleague bought her running shoes, but Voronkova gave them away.

A helmet and a protective vest aren't part of her uniform, either, as she distributes first-aid kits and other equipment to Ukrainian soldiers and paramedics. She is a civilian, the founder of a medical non-profit, and looking like one is something no one can take from her, even in a combat zone.

“I am myself, and I will never deliver up my heels for anything,” Voronkova said of the red strappy sandals, beige pumps and other elegant footwear she typically pairs with full skirts and midi dresses as she makes her dangerous rounds to secret military bases and mobile medical units.

The former adviser to the Ukrainian Defense Ministry with graduate degrees in banking and finance is a familiar sight to officers and troops in eastern Ukraine. For eight years after Moscow seized Ukraine's Crimean Peninsula in 2014, Voronkova dedicated her life to providing tactical medical training and equipment for Ukrainian forces fighting pro-Russia separatists.

Russia's invasion of Ukraine in late February has created exponentially more need for her organization, Volunteers Hundred Dobrovolia, and new challenges.

Working on their own, Voronkova and her assistant, Yevhen Veselov, drive a van filled with donated supplies - everything from night vision goggles and battlefield basics like tourniquets and medical staplers to the advances equipment needed for brain surgery — swiftly through checkpoints, irrespective of curfews. Servicemen recognize Voronkova and with one look, let them through.

The smell of her sweet cherry cigarillos fills the air when she gets out of her van to smoke one with her manicured red nails. Although she manages 20 people and lives in Kyiv, Voronkova has been in eastern Ukraine since the Russians focused their attention there in April, and she insists on delivering first-aid kits to the front line herself.

“A woman is like the neck of the head. She moves everything,” she said.

Voronkova grew up loving medicine, but her family did not want her to pursue it. They were bankers and thought she should take the same career path. The separatist conflict that started in 2014 persuaded her to study combat medicine, and she eventually received certification as an instructor.

From 2015 until Russia invaded Ukraine, the Ukrainian Defense Ministry tasked her with finding solutions to problems encountered by army units in the Donbas. Now, she uses her own teaching techniques to help the units protect themselves and their comrades in battle.

“I still remind my mother that when I was in 10th grade, I had a box filled with (over-the-counter) pills, and all my friends at school knew I had medicine for everything," she said. "Unfortunately, I could not pursue my dream. But today I am implementing it by giving aid.”

Martial law has swelled the ranks of Ukraine's defenders, but many of the people who have joined the military during the war entering its sixth month do not have combat experience or the supplies they need.

“It feels like 2014. We need first-aid kits and uniforms for the territorial defense. I think it was created with hardly any time to allocate a budget for them. Therefore, they need support from volunteers,” Voronkova says.

As she brought boxes of scalpels, electrocoagulation devices, emergency catheters and other supplies to a hospital in the city of Kurakhove, the roar of outgoing rockets and incoming shelling did not make her flinch.

Tue, 26 Jul 2022 04:29:00 -0500 en-US text/html https://www.timesunion.com/news/article/Medic-in-heels-commands-respect-on-Ukraine-s-17329227.php?IPID=Times-Union-HP-nation-world-package
Killexams : Digital Asset Management Market: Technical Signs Point Higher Growth In Coming Years, Report - Allied Market Research

(MENAFN- EIN Presswire)

Digital Asset Management Market

Rise in need to meet the regulatory compliance and efficient data integration are estimated to fuel the market growth during the forecast period.

PORTLAND, PORTLAND, OR , UNITED STATES , July 29, 2022 /EINPresswire.com / -- Increased need for collaborative digital workflow especially for marketing applications has encouraged end-user industries to invest on enhanced digital asset management solutions and services. The global digital asset management market was valued at $1,928 million in 2016, and is projected to reach at $5,287 million by 2023, growing at a CAGR of 13.7% from 2017 to 2023.

The service segment is projected to grow at the CAGR of around 18% during the forecast period. Increase in demand for enhanced content management solutions and rise in competition among end-user organizations globally are anticipated to boost the segment growth during the forecast period.

Key market players such as - ADAM Software NV, Adobe Systems Incorporated, Cognizant Technology Solutions Corp, EMC Corporation, Hewlett-Packard (HP), IBM Corporation, Northplains Systems, Opentext Corporation, Oracle Corporation, and Widen Enterprises.

Download demo Report (Get Full Insights in PDF - 120 Pages) at:

The IT segment dominated the market in 2016, whereas the marketing segment is projected to witness the highest CAGR of 15% during the forecast period. This is attributed to growth in adoption of real-time digital asset management solutions among marketing departments of end-user industries to assist sales department with up-to-date content.

Region wise, North America dominated the market, in terms of expenditure on digital asset management solutions and services, owing to high penetration of digital technologies among end-user industries. Moreover, the market in Asia-Pacific is projected to grow at the highest CAGR of around 16%, owing to increase in awareness among end-user industries about benefits of adoption of digital asset management solutions.

If you have any questions please feel free to contact our analyst at:

Segmental analysis of the market is provided in both qualitative and quantitative aspects. This aids the clients in identifying the most lucrative segment to go on with investments, on the basis of a complete backend analysis concerning the segmental presentation, coupled with brief salutation of the operating organizations and their important developmental activities.

The market numbers are Checked by means of numerous data triangulation techniques. Additionally, reliable industry journals, accurate press releases from trade association, and government websites have also been revised for producing exclusive industry insights.

If you have any special requirements, please let us know at:

Lastly, this report provides market intelligence in the most comprehensive way. The report structure has been kept such that it offers maximum business value. It provides critical insights on the market dynamics and will enable strategic decision making for the existing market players as well as those willing to enter the market.

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Enterprise Asset Management Market

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AMR launched its user-based online library of reports and company profiles, Avenue. An e-access library is accessible from any device, anywhere, and at any time for entrepreneurs, stakeholders, and researchers and students at universities. With reports on more than 60,000 niche markets with data comprising of 600,000 pages along with company profiles on more than 12,000 firms, Avenue offers access to the entire repository of information through subscriptions. A hassle-free solution to clients' requirements is complemented with analyst support and customization requests.

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Thu, 28 Jul 2022 21:59:00 -0500 Date text/html https://menafn.com/1104612633/Digital-Asset-Management-Market-Technical-Signs-Point-Higher-Growth-In-Coming-Years-Report-Allied-Market-Research
Killexams : USD 8.81 bn Growth in Classroom Management Systems Market, Rising Adoption of Cloud-based Management Tools to Drive Growth - Technavio

NEW YORK, Aug. 2, 2022 /PRNewswire/ -- The classroom management systems market will be driven by factors such as the rising adoption of cloud-based management tools. Vendors are providing cloud-based classroom management systems owing to the increasing Internet penetration and the rising pace of digitization. Many schools and colleges can reduce the workload concerning administrative services with the help of cloud-based classroom management systems. These tools allow easy integration of other supporting software such as adaptive learning, LMS, and learning analytics. Moreover, cloud-based classroom management systems are cost-effective, with extended performance capabilities.

Technavio has announced its latest market research report titled Classroom Management Systems Market Growth, Size, Trends, Analysis Report by Type, Application, Region and Segment Forecast 2020-2024

The classroom management systems market size is expected to grow by USD 8.81 bn from 2019 to 2024. In addition, the growth momentum of the market will accelerate at a CAGR of 28.33% during the forecast period.

Get a comprehensive report summary describing the market size and forecast along with research methodology. The sample report is available in PDF format

Classroom Management Systems Market 2020-2024: Scope

The classroom management systems market report covers the following areas:

Classroom Management Systems Market 2020-2024: Challenge

Rising safety and privacy issues are challenging the growth of the market. Classroom management systems collect significant data, such as personal details, student behavior, and many other details, to create personalized courses. However, the data can be misused, leading to security and privacy concerns. Hence, vendors need to incorporate authorization techniques and a robust monitoring system to ensure the confidentiality of data.

Classroom Management Systems Market 2020-2024: Vendor Analysis

APLAF Inc., Blackboard Inc., ClassDojo Inc., Dell Technologies Inc., Faronics Corp., HP Inc., Impero Solutions Ltd., Lenovo Group Ltd., Netop Solutions AS, and NetSupport Ltd. are among some of the major market participants. The key offerings of some of these vendors are listed below:

  • APLAF Inc. - The company offers ProClass, which is an easy-to-use, scalable, and customizable software to effectively and efficiently manage schools, online registrations, and memberships.
  • Dell Technologies Inc. - Dell EMC K12 Education Solutions enable personalized learning, where students, teachers, and technology work together to enrich the learning process.
  • ClassDojo Inc. - The company offers a classroom management system, which helps in building a communication platform between teachers, students, and parents.
  • Faronics Corp. - The company offers Insight Classroom management, an effective classroom management software that helps teachers to create a better learning experience.
  • HP Inc. - The company offers HP Classroom manager 3.0, which helps teachers to share documents, messages, and websites easily with group chats to support project-based learning.

This report provides a full list of key vendors, their strategies, and the latest developments. Request a PDF demo Now

Classroom Management Systems Market 2020-2024: Segmentation

  • End User
  • Deployment
    • On-premise Deployment
    • Cloud-based Deployment
  • Geography
    • North America
    • Europe
    • APAC
    • South America
    • MEA

Classroom Management Systems Market 2020-2024: Key Highlights

  • CAGR of the market during the forecast period 2020-2024
  • Detailed information on factors that will assist classroom management systems market growth during the next five years
  • Estimation of the classroom management systems market size and its contribution to the parent market
  • Predictions on upcoming trends and changes in consumer behavior
  • The growth of the classroom management systems market
  • Analysis of the market's competitive landscape and detailed information on vendors
  • Comprehensive details of factors that will challenge the growth of classroom management systems market vendors

Related Reports

Edtech Market Growth, Size, Trends, Analysis Report by Type, Application, Region and Segment Forecast 2022-2026

Education Apps Market Growth, Size, Trends, Analysis Report by Type, Application, Region and Segment Forecast 2022-2026

Classroom Management Systems Market Scope

Report Coverage

Details

Page number

120

Base year

2019

Forecast period

2020-2024

Growth momentum & CAGR

Accelerate at a CAGR of 28.33%

Market growth 2020-2024

USD 8.81 billion

Market structure

Fragmented

YoY growth (%)

25.03

Regional analysis

North America, Europe, APAC, South America, and MEA

Performing market contribution

North America at 33%

Key consumer countries

US, UK, Germany, China, and India

Competitive landscape

Leading companies, competitive strategies, consumer engagement scope

Companies profiled

APLAF Inc., Blackboard Inc., ClassDojo Inc., Dell Technologies Inc., Faronics Corp., HP Inc., Impero Solutions Ltd., Lenovo Group Ltd., Netop Solutions AS, and NetSupport Ltd.

Market Dynamics

Parent market analysis, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, COVID 19 impact and future consumer dynamics, and market condition analysis for the forecast period.

Customization purview

If our report has not included the data that you are looking for, you can reach out to our analysts and get segments customized.


Table of Contents:

Executive Summary

Market Landscape

  • Market ecosystem
  • Value chain analysis

Market Sizing

  • Market definition
  • Market segment analysis
  • Market size 2020
  • Market outlook: Forecast for 2020 - 2025

Five Forces Analysis

  • Five Forces Summary
  • Bargaining power of buyers
  • Bargaining power of suppliers
  • Threat of new entrants
  • Threat of substitutes
  • Threat of rivalry
  • Market condition

Market Segmentation by End-user

  • Market segments
  • Comparison by End-user
  • Higher education - Market size and forecast 2020-2025
  • K12 - Market size and forecast 2020-2025
  • Market opportunity by End-user

Market Segmentation by Deployment

  • Market segments
  • Comparison by Deployment
  • On premise - Market size and forecast 2020-2025
  • Cloud based - Market size and forecast 2020-2025
  • Market opportunity by Deployment

Customer landscape

Geographic Landscape

  • Geographic segmentation
  • Geographic comparison
  • North America - Market size and forecast 2020-2025
  • Europe - Market size and forecast 2020-2025
  • APAC - Market size and forecast 2020-2025
  • South America - Market size and forecast 2020-2025
  • MEA - Market size and forecast 2020-2025
  • Key leading countries
  • Market opportunity by geography
  • Market drivers – Demand-led growth
  • Market challenges
  • Market trends

Vendor Landscape

  • Overview
  • Vendor landscape
  • Landscape disruption

Vendor Analysis

  • Vendors covered
  • Market positioning of vendors
  • APLAF Inc.
  • ClassDojo Inc.
  • Creatrix Campus
  • Dell Technologies Inc.
  • Faronics Corp.
  • HP Inc.
  • Impero Solutions Inc.
  • Lenovo Group Ltd.
  • NetSupport Ltd.
  • Providence Equity Partners LLC

Appendix

  • Scope of the report
  • Currency conversion rates for US$
  • Research methodology
  • List of abbreviations

About Us

Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging market trends and provide actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions. With over 500 specialized analysts, Technavio's report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio's comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

Contact

Technavio Research
Jesse Maida
Media & Marketing Executive
US: +1 844 364 1100
UK: +44 203 893 3200
Email: [email protected]
Website: www.technavio.com/

Technavio (PRNewsfoto/Technavio)

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Killexams : Understanding NIST’s post-quantum encryption standardization and next steps for CISOs

By Duncan Jones, Head of Cybersecurity at Quantinuum

In a accurate National Security Memo (NSM-10), the White House acknowledged the need for immediacy in addressing the threat of quantum computers to our current cryptographic systems and mandated agencies to comply with its initial plans to prepare. It’s the first directive that mandates specific actions for agencies as they begin a very long and complex migration to quantum-resistant cryptography. Many of the actions required of agencies depend on new cryptographic algorithms that have just been chosen by the National Institute of Standards and Technology, although final standardization will take 18 to 24 months.

What should CISOs be doing to prepare for the risks of quantum computers and to comply with NSM-10 requirements? They should start by gaining an understanding of the new algorithm standards, and from there, focus on inventorying the agency’s most important information and assets. 

NIST to the rescue

In as little as a decade, quantum computers will break many of the encryption schemes in use today, such as the popular RSA algorithm that we use for encrypting internet data and for digitally signing transactions. An attacker with a powerful quantum computer will be able to read data encrypted by an RSA public key or forge transactions signed by an RSA private key. Worse, a category of attack known as “hack now, decrypt later” may already be under way. Attackers who record data using quantum-vulnerable algorithms now can retrospectively decrypt it in the future using quantum computers. For any agency or contractor that shares data with a long sensitivity lifespan, this is a real concern.

Fortunately, the academic world has not been sitting idle. Since 2016, NIST has been working with the cryptographic community to identify and standardize new quantum-proof encryption algorithms. The NIST process will help ensure that these algorithms become standardized in Federal Information Processing Standards publications and are ready for consumption by federal authorities. As such, it’s important for CISOs to familiarize themselves with the new algorithms and their properties.

Each post-quantum algorithm has three different security levels defined—SL1, SL3 and SL5. These levels are very similar to key sizes in today’s algorithms. Much like 4096-bit RSA keys are stronger than 1024-bit RSA keys, SL5 is stronger than SL3 and SL1. However, that increased security comes at a cost. SL5 keys are typically larger to store and result in slower computations. It’s also notable that post-quantum algorithms cannot be used for both encryption and data signing. Instead, they are used for only one task or the other. This means we will be replacing a single algorithm, such as RSA, with two separate algorithms.

The table below shows some of the characteristics of the selected algorithms.

Algorithm Type Family Public Key Size Ciphertext/Signature Size
CRYSTALS-KYBER Key Establishment Lattice-based 1.6KB - 3.1KB 0.8KB - 1.5 KB
CRYSTALS-Dilithium Signature Lattice-based 2.5KB - 4.8KB 2.4KB - 4.6KB
Falcon Signature Lattice-based 1.2KB - 2.3KB 0.7KB - 1.3KB
SPHINCS+ Signature Hash-based 0.03KB-0.06KB 7.7KB - 49KB

For immediate action

According to NIST’s chief of the Computer Security Division, Matt Scholl, “…don't wait for the standard to be done. Start inventorying your most important information. Ask yourself what is that data that an adversary is going to want to break into first.”

According to NSM-10, leaders from the Office of Management and Budget, the Cybersecurity and Infrastructure Security Agency, NIST and the National Security Agency will be establishing requirements for inventorying all currently deployed cryptographic systems within six months of the May 4 memo. Within a year—and on an annual basis—“…heads of all federal civilian executive branch agencies shall deliver to the director of CISA and the national cyber director an inventory of their IT systems that remain vulnerable to CRQCs.”

Agency inventory requirements will include: 

  • A list of key information technology assets to prioritize
  • Interim benchmarks
  • A common—and preferably automated—assessment process for evaluating progress on quantum-resistant cryptographic migration in IT systems

Migrating an agency or department to a fully post-quantum position is a complex process that will take many years. Although these post-quantum algorithms will not be ready for widespread production use until the standardization process finishes in 2024, considerable work—now mandated under NSM-10 directive—must be done to prepare for these changes, starting with the inventorying process. 

Next steps for federal CISOs

Identify data assets and use of cryptography. Before you can prioritize migration, you need to understand exactly what data you have, and how vulnerable it is to attack. Data that is particularly sensitive and vulnerable to the “hack-now, decrypt-later” attacks should be prioritized above less sensitive data that isn’t transmitted freely. CISOs should start cataloging where quantum-vulnerable algorithms are currently being used. For a variety of reasons, not all systems will be affected equally. CISOs need a very clear picture of the vulnerabilities present in each of their systems.

Speak with vendors. Now is the perfect time to be asking your vendors about their plans for adopting post-quantum algorithms. A good vendor should have a clear roadmap already in place and be testing the candidate algorithms in preparation for 2024.

Test algorithms for home-grown software. Post-quantum algorithms have different properties than the algorithms we use today. The only way to know how they will affect your systems is to implement them and experiment. To assist with potential compatibility issues, NSM-10 encourages agency heads to begin conducting “…tests of commercial solutions that have implemented pre-standardized quantum-resistant cryptographic algorithms.” 

A good place to start is with the Open Quantum Safe project, which provides many different implementations of post-quantum algorithms designed for experimentation. 

Quantum is not all bad news. It is worth remembering that quantum computing also offers new techniques for strengthening existing systems. Quantum computers are already being used today to generate stronger cryptographic keys. In the future, once this migration to post-quantum algorithms is behind us, we’ll view quantum as a gift to cybersecurity, not a threat.

 Duncan Jones is the head of cybersecurity at Quantinuum.

Tue, 26 Jul 2022 06:00:00 -0500 en text/html https://gcn.com/cybersecurity/2022/07/understanding-nists-post-quantum-encryption-standardization-and-next-steps-cisos/374930/?oref=gcn-skybox-hp
Killexams : Devops Tool Market 2022 Witness Widespread Expansion, Rising Business Opportunities With Prominent Investment, Forecast To 2030

The MarketWatch News Department was not involved in the creation of this content.

Aug 02, 2022 (Alliance News via COMTEX) -- Key Companies Covered in the Devops Tool Research are Spirent Communications plc, Saltstack, IBM, VMware, Cisco, ServiceNow, Rally, Splunk, Nolio, Red Hat, Atlassian, Puppet Labs, Rackspace, Docker Inc., HP, Microsoft, CFEngine, AnsibleWorks, CA Technologies, DBmaestro, WMS and other key market players.

The Devops Toolmarket revenue was $$ Million USD in 2016, grew to $$ Million USD in 2022, and will reach $$ Million USD in 2030, with a CAGR of % during 2022-2030.

Market Overview

Global Devops Tool Market Development Strategy Pre and Post COVID-19, by Corporate Strategy Analysis, Landscape, Type, Application, and Leading 20 Countries covers and analyzes the potential of the global Devops Tool industry, providing statistical information about market dynamics, growth factors, major challenges, PEST analysis and market entry strategy Analysis, opportunities and forecasts. The biggest highlight of the report is to provide companies in the industry with a strategic analysis of the impact of COVID-19. At the same time, this report analyzed the market of leading 20 countries and introduce the market potential of these countries.

Request To Free demo of This Strategic Report:-https://reportocean.com/industry-verticals/sample-request?report_id=mai283655

Most important types of Devops Tool products covered in this report are:
API tools
Collaboration and Organizational Tools
Configuration Management Tools
Build Automation Tools
Application and Infrastructure Monitoring Tools

Most widely used downstream fields of Devops Tool market covered in this report are:
IT
Telecom
BFSI
Government and Public Sector
Others

Top countries data covered in this report:
United States
Canada
Germany
UK
France
Italy
Spain
Russia
China
Japan
South Korea
Australia
Thailand
Brazil
Argentina
Chile
South Africa
Egypt
UAE
Saudi Arabia

SPECIAL OFFER (Avail an Up-to 30% discount on this report) :-https://reportocean.com/industry-verticals/sample-request?report_id=mai283655

Chapter 1 is the basis of the entire report. In this chapter, we define the market concept and market scope of Devops Tool, including product classification, application areas, and the entire report covered area.

Chapter 2 is the core idea of the whole report. In this chapter, we provide a detailed introduction to our research methods and data sources.

Chapter 3 focuses on analyzing the current competitive situation in the Devops Tool market and provides basic information, market data, product introductions, etc. of leading companies in the industry. At the same time, Chapter 3 includes the highlighted analysis–Strategies for Company to Deal with the Impact of COVID-19.

Chapter 4 provides breakdown data of different types of products, as well as market forecasts.

Different application fields have different usage and development prospects of products. Therefore, Chapter 5 provides subdivision data of different application fields and market forecasts.

Chapter 6 includes detailed data of major regions of the world, including detailed data of major regions of the world. North America, Asia Pacific, Europe, South America, Middle East and Africa.

Chapters 7-26 focus on the regional market. We have selected the most representative 20 countries from 197 countries in the world and conducted a detailed analysis and overview of the market development of these countries.

Chapter 27 focuses on market qualitative analysis, providing market driving factor analysis, market development constraints, PEST analysis, industry trends under COVID-19, market entry strategy analysis, etc.

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Key Points:
Define, describe and forecast Devops Tool product market by type, application, end user and region.
Provide enterprise external environment analysis and PEST analysis.
Provide strategies for company to deal with the impact of COVID-19.
Provide market dynamic analysis, including market driving factors, market development constraints.
Provide market entry strategy analysis for new players or players who are ready to enter the market, including market segment definition, client analysis, distribution model, product messaging and positioning, and price strategy analysis.
Keep up with international market trends and provide analysis of the impact of the COVID-19 epidemic on major regions of the world.
Analyze the market opportunities of stakeholders and provide market leaders with details of the competitive landscape.

Table of Content:

  • Market Definition and Overview
  • Research Method and Logic
  • Market Competition Analysis
  • Product and Service Analysis
  • Strategies for Company to Deal with the Impact of COVID-19
  • Market Segment by Type, Historical Data and Market Forecasts
  • Market Segment by Application, Historical Data and Market Forecasts
  • Market by by Region, Historical Data and Market Forecasts
  • Market Dynamic Analysis and Development Suggestions

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List of Factors Covered in the Report are:
Major Strategic Developments:The report abides by quality and quantity. It covers the major strategic market developments, including R&D, M&A, agreements, new products launch, collaborations, partnerships, joint ventures, and geographical expansion, accompanied by a list of the prominent industry players thriving in the market on a national and international level.

Key Market Features:
Major subjects like revenue, capacity, price, rate, production rate, gross production, capacity utilization, consumption, cost, CAGR, import/export, supply/demand, market share, and gross margin are all assessed in the research and mentioned in the study. It also documents a thorough analysis of the most important market factors and their most accurate developments, combined with the pertinent market segments and sub-segments.

List of Highlights & Approach
The report is made using a variety of efficient analytical methodologies that offers readers an in-depth research and evaluation on the leading market players and comprehensive insight on what place they are holding within the industry. Analytical techniques, such as Porter's five forces analysis, feasibility studies, SWOT analyses, and ROI analyses, are put to use to examine the development of the major market players.

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Key Benefits for Industry Participants & Stakeholders

  • The Market Research allows the investors to understand the market size, dynamics, risks, and opportunities in the industry.
  • The market research report provides market sizing and forecast over major currencies - USD, EUR, JPY, GBP, and CHF.
  • This Market Research Report helps to forecast the revenues and analyze the market trends based on region, product type, and end-use.
  • The Market analysis of the market share of the can prove beneficial in terms of profit to the industry's participants and stakeholders.

Key Questions Answered in the Market Report

  • Which Manufacturing Technology is used for Market? What Developments Are Going on in That Technology?
  • Which Trends Are Causing These Developments? Who Are the Global Key Players in This Market?
  • What are Their Company Profile, Their Product Information, and Contact Information?
  • What Was Global Status of Market? What Was Capacity, Production Value, Cost and PROFIT of Market?
  • What Is Current Market Status of market Industry? What's Market Competition in This Industry, Both Company, and Country Wise?
  • What's Market Analysis of Market by Taking Applications and Types in Consideration?
  • What Are Projections of Global Market Industry Considering Capacity, Production and Production Value? What Will Be the Estimation of Cost and Profit?
  • What Will Be Market Share Report, Supply and Consumption? What about Import and Export?
  • What Is Market Chain Analysis by Upstream Raw Materials and Downstream Industry?

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COMTEX_411387186/2796/2022-08-02T03:08:32

The MarketWatch News Department was not involved in the creation of this content.

Mon, 01 Aug 2022 19:08:00 -0500 en-US text/html https://www.marketwatch.com/press-release/devops-tool-market-2022-witness-widespread-expansion-rising-business-opportunities-with-prominent-investment-forecast-to-2030-2022-08-02
Killexams : Digital Label Printing Market Share, Size, Global Industry Analysis, Key Growth Drivers Trends, Segments, Opportunity and Forecast 2030

The global digital label printing market will grow at a significant CAGR throughout 2020-2030. Factors such as cost-effectiveness, less labor requirement, and reduced waste production are enabling broader adoption of digital label printing.

Such benefits of digital label printing are making them commonplace in various sectors such as food & beverages, cosmetics, and pharmaceuticals. Further, FMI finds that the quantity of the packaging printed with digital printing will be threefold in contrast to its actual volume throughout the projected period.

The onset of digital printing solutions for manufacturing of packaging materials is creating a highly lucrative market for packaging companies, printing service providers, and commercial printers. Eventually, success at the point of sale (PoS) is a multimillion-dollar business for brand owners and producers.

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Digital Label Printing Market – Developments and Trends

Digitalization is paving way for innovative customer-centric business framework. Creativity is essential to gather customers’ attention at PoS. Digital label printing is offering market players a substantially broad field of value-capture opportunities.  Studies find that the digital printing packaging market is slated to reach around US$ 30 Bn in the coming years.

Personalization is leading the pack in packaging trend in 2020. Manufacturers are developing customized digital labels to cater to increasingly targeted group of purchasers. accurate data reveal that about 7 out of 10 marketers believe personalization has a significant impact on their consumers. For instance, Frito-Lay prints faces on its potato chip packages, and Coca-Cola prints consumers’ names on their soft drink containers.

Digital Label Printing Market – Region-wise Analysis

North America and Europe continue to remain the epicenter of development prospects in the global digital label printing market, mainly owing to rapid growth in the labeling sector.  Both the regions are home to pioneers of digital technologies. Moreover, the pace of broader economic structure in these regions acutely relies on their digital ecosystem.

Asia Pacific (APAC) is anticipated to account for high-value share in the global digital label printing market. accurate studies reveal that Asia will continue to maintain its supremacy in the labeling market, and is expected to capture around 45% of the worldwide revenue in the coming years.  As such, market players are rapidly shifting their manufacturing units to APAC to remain well-placed for better returns.

Digital Label Printing Market – Growth Restraints

Digital label printing requires additional expenses to install particular equipment for production. Moreover, companies that have been immune to the digital trend are required to invest in up-skilling their workforce to deal with the complexities associated with digital label printing processes. As such, small- and medium-scale enterprises are keeping away from going digital.

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COVID-19 Impact Analysis on Market Growth

With nation-wide lockdowns amid the COVID-19 pandemic, digital label printing manufacturers are witnessing huge demand for labels for hand sanitizers, face masks, as well as boxes for curbside delivery. Digital label printing is playing a crucial role, especially in the food & beverage industry.

The pandemic is compelling end users to rapidly move towards automation, and digital label printing is poised to get a boost in the bucket list of these end users. As there is acute labor shortage due to travel restrictions, digital label printing will complement the existing label printing technology well amid the tough times.

Digital Label Printing Market – Competitive Analysis

Market players are boosting their market presence by offering new products forming mergers & acquisitions (M&A).

  • Western Shield Label Company has acquired Label Print Technologies (LPT). The acquisition is offering a scope for complementary digital label and flexographic printing techniques and is help the company boost its presence in the Midwest and Ohio.
  • Argraf, a prominent manufacturer of high-end wine and food labels, is broadening its product portfolio by acquiring a Xeikon CX3 digital press, planned particularly for the manufacturing of labels.
  • Label Traxx has collaborated with HP PrintOS Print Beat Jobs API that is enabling users of HP Indigo digital press to link Label Traxx with HPs PrintOS in order to gather information received by the press such as production time, media, and ink usage obtained by the HP Indigo press.

Digital Label Printing Market – Segment Analysis

The global market is segmented as the following:

By System Type

  • Toner system
  • Inkjet System
  • Others

By End Use

  • Converting Companies
  • Consumers
  • Packaging Companies

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Tue, 26 Jul 2022 21:29:00 -0500 en-US text/html https://www.fmiblog.com/2022/07/27/digital-label-printing-market-share-size-global-industry-analysis-key-growth-drivers-trends-segments-opportunity-and-forecast-2030/
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