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Killexams : HP Solutions study - BingNews Search results Killexams : HP Solutions study - BingNews 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,, 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
Killexams : HP launches HP Anyware for secure remote working

HP Anyware will be available somewhere in the coming months. The solution’s based on technology from Teradici, which HP acquired last year. HP Anyware should eventually replace HP’s existing zCentral Remote Boost solution.

Teradici is a cornerstone of the upcoming solution. The company provides virtual desktop environments using Cloud Access Software (CAS), allowing companies to remotely host PCs in their on-premises environment and the cloud.

Teradici uses its own PC-over-IP (PCoIP) protocol. The protocol streams the contents of a display. The data travelling over a network is unlike the data exchanged by traditional remote desktop tech, which promotes security.

HP Anyware is the next release of Teradici’s CAS solution. New functionality includes support for Arm-based M1 processors and Macs. In addition, HP and Teradici optimized the tool for Windows 11.

HP told The Register that HP Anyware will replace zCentral Remote Boost, HP’s existing solution for remote work. HP Anyware will have equivalent functionality by mid-2023, after which zCentral Remote is to be discontinued. Though the solution will receive security fixes for some time, users eventually have to migrate to Anyware.

Tip: HPC software company Teradici acquired by HP Inc.

Mon, 25 Jul 2022 22:15:00 -0500 en text/html
Killexams : Letters to the editor: Finding the right water policies; wind power and energy

Collaborate on water solutions

The solutions we have grappled with for decades relative to California’s water crisis have centered on conservation, regulation and innovation. However, strong advocacy by politically savvy groups for their favorite one of the three approaches has been accompanied by the group’s opposition to the other two.

Sadly, this has resulted in a dysfunctional stalemate on any real progress to a long-term solution.

Hopefully, the current level of crisis might produce an awareness that all three of these tools will be needed in thoughtful combination to meet the challenge of our drought.

And we need, in particular, to avoid the current tendency to over stipulate sacrifices in residential landscape use (conservation) while closing our eyes to the need to innovate and regulate as well.

A latest UC study (Pittinger and Hodel) found that residential landscape accounts for about 3.5% of our state’s water use. Undoubtedly, we can and must be better stewards of our water in gardens, backyards and recreational areas. But even great reductions in this 3.5% of water use will not put a dent in the larger issue and a less than thoughtful set of new water policies for residential landscape could fundamentally change the quality of life in our communities for years to come.

As we take responsible action to save water in residential landscape, let’s take equally reasonable actions to find innovative ways to reclaim water and to oversee and regulate the agricultural and development sectors which impact the greatest percent of water use in the state.

Robert Fraisse, Newbury Park

Understanding units of energy

Re: Terry Tamminen’s Aug. 3 guest column, “Amping up offshore wind power”:

Just read the column on wind energy. It’s totally without understanding the units of energy. The important value is not gigawatts, power, but gigawatt hours per year, energy. Twenty gigawatts is a meaningless number. It’s like saying you have a 500 Hp car in the garage but so what if you never take it out?

Look at the wind generators near Mojave. If you added up their kilowatt potential it would sound impressive but if they are not turning, like most of the time, they are worthless. Ultimately, we need nuclear power plants, which generate power 24/7, like Bill Gates’ Terra Power has designed and one is being built in Wyoming.

Paul Lux, Thousand Oaks

This article originally appeared on Ventura County Star: Letters: Finding the right water policies; wind power and energy

Sun, 07 Aug 2022 11:04:00 -0500 en-US text/html
Killexams : California aims to make its own insulin brand to lower price

SACRAMENTO, Calif. (AP) — A vial of insulin cost $25 in 1995, back when Chris Noble was 5 years old and just learning how to manage his Type 1 diabetes with the help of his parents and his doctors.

Nearly three decades later, Noble says that same vial of insulin costs more than $300 — a 12-fold increase for something he and millions like him can’t live without.

“It’s as essential as water,” Noble said.

Health care advocates have bemoaned for years that insulin, while inexpensive to produce, is held hostage by a U.S. health care system stubbornly resistant to reforms as companies monopolize and maximize profits.

Now, with several insulin patents nearing their expiration dates, California is looking to disrupt that market by making its own insulin and selling it for a much cheaper price. Last month, after a few years of study, state lawmakers approved $100 million for the project, with $50 million dedicated to developing three types of insulin and the rest set aside to invest in a manufacturing facility.

Gov. Gavin Newsom and state lawmakers still have many details to work out, including contracting with a private company to do most of the work. But the budget was a put-his-money-where-his-mouth-is moment for Newsom, who has been calling for the state to launch its own brand of generic drugs to lower the overall price of medication.

“Nothing epitomizes market failures more than the cost of insulin,” Newsom said in a video posted to his Twitter account. “California is now taking matters into our own hands.”

This wouldn't be the first time California has made its own medicine. In 1990, about half of all cases of infant botulism — a rare illness that affects the large intestine — were in California. The California Department of Public Health got a federal grant to develop and test a treatment. The treatment won federal approval in 2003, and California has been making it ever since.

But the market for infant botulism treatments is small, with about 110 cases reported each year, according to the U.S. Centers for Disease Control and Prevention. One course of California's botulism treatment costs more than $57,000, according to a legislative analysis.

Meanwhile, about 7 million people in the United States require insulin to manage their diabetes. The human body converts most of the food we eat into sugar. The pancreas then produces insulin, which converts that sugar into energy. People who have diabetes don't produce enough insulin. People with Type 1 diabetes must take insulin every day to survive.

Insulin was first discovered in 1920s by a team of Canadian scientists. They sold the patent to the University of Toronto for just $1, hoping the school would license the product to multiple companies to prevent a monopoly that would lead to high prices.

But over time, the insulin market was slowly cornered. Today, just three companies produce most of the world's insulin. In the United States, the line between an insulin manufacturer and a patient is not straight. It zigs and zags between insurance companies and pharmacy benefit managers — third parties that managed prescription drug benefits for health plans.

It's that system that has kept the cost of insulin much higher in the United States than other countries, as more companies benefit from the higher price tag, said Kasia Lipska, an associate professor at the Yale School of Medicine.

“It creates this really weird incentive,” Lipska said.

California will try to break that incentive. The reason more companies haven't entered the insulin market is because if they did, the established manufacturers would just undercut them, making it impossible to recoup their investment, said Anthony Wright, executive director of Health Access California, a consumer advocacy group.

Fri, 29 Jul 2022 03:46:00 -0500 en-US text/html
Killexams : SPB 2022 Q2 Artificial Intelligence & Biometric Privacy Quarterly Review Newsletter

Wednesday, August 3, 2022

Q2 did not disappoint in the AI and biometric privacy space, with a number of noteworthy litigation, legislative, and regulatory developments having taken place in these two rapidly developing areas of law. Read on to see what has transpired over the last quarter and what you should keep your eyes on as we head into the second half of 2022.

Biometric Privacy Cases to Keep on Your Radar

Cothron v. White Castle System, Inc., No. 128004 (Ill. Sup. Ct.): As many familiar with BIPA know, currently pending before the Illinois Supreme Court is Cothron v. White Castle System, Inc. (covered extensively by SPB team member Kristin Bryan in CPW articles hereherehere, and here), which is set to provide much-needed certainty regarding the issue of claim accrual in BIPA class action litigation. “Claim accrual” involves when a claim “accrues” or occurs—either only at the time of the first violation or, alternatively, each and every time a defendant violates Illinois’s biometric privacy statute. If the Cothron Court rules that BIPA violations constitute separate, independent claims, then the associated statutory damages of $1,000 to $5,000 per violation would compound with each successive failure to comply with Illinois’s biometric privacy law. Under this scenario, liability exposure would likely expand exponentially for BIPA claims. As such, companies should pay close attention to how the Illinois Supreme Court decides the Cothron appeal, as the ruling could result in yet another drastic shift in the biometric privacy landscape. In the interim, companies should consult with counsel and re-assess their compliance with BIPA to ensure they are satisfying the full range of requirements to mitigate potential class action litigation risks.

Mahmood v. Berbix Inc., No. 1:22-cv-2456 (N.D. Ill.): “Selfie” identity verification has become extremely popular due to the benefits offered by this verification method in significantly reducing fraud and facilitating a fast, accurate verification process. At the same time, companies that develop and supply this technology have also become an increasingly common target for BIPA class action suits. In Mahmood v. Berbix Inc., the plaintiff filed a putative class action against Berbix Inc. for alleged BIPA violations after being required to upload a photo of her driver’s license and a “selfie” to rent a car, the manufacturer of which used Berbix’s identity verification service. This case is worth keeping an eye on, as the litigation will likely provide valuable insights on the contours of the extraterritoriality defense applicable in certain BIPA disputes where the alleged violations of Illinois’s biometric privacy statute do not occur “primarily and substantially” within the borders of the Prairie State. 

Coss v. Snap Inc., No. 1:22-cv-02480 (N.D. Ill.): In early May, Snap Inc., the owner of popular social media platform Snapchat, was sued for alleged BIPA violations in connection with its “Face Lenses” feature, an augmented reality (“AR”) experience that uses innovative technology to modify and enhance users’ facial features to transform their appearance in photos and videos posted online. According to the complaint, Snap’s Lenses feature scans users’ faces and creates a detailed map or digital depiction of their facial features, during which time Snap collects their biometric data. This is another case worth watching, as the overlapping space between increasingly-popular image/video enhancement tools and efforts to ensure the privacy and security of biometric data is likely to lead to additional litigation moving forward. 

Hess v. 7-Eleven, Inc., No. 1:22-cv-02131 (N.D. Ill.): On April 25, four 7-Eleven customers filed a class action lawsuit against 7-Eleven, alleging that—unbeknownst to consumers—the company collects facial geometry data through cameras and video surveillance systems in violation of BIPA. According to the complaint, numerous 7-Eleven locations use systems provided by Clickit, an intelligent video solution provider, to collect biometric data. Hess is an example of the high volume of BIPA class actions targeting retailers of all types and the wide variety of allegations that are being asserted against them in connection with purported violations of Illinois’s biometric privacy statute. As such, all retail brands—even those that have put practices in place to comply with BIPA—should consult with experienced biometric counsel to re-assess the effectiveness of their biometric privacy compliance programs and mitigate growing BIPA risks to the greatest extent possible, as the retail industry will continue to remain one of the primary targets for BIPA suits for the foreseeable future.

Theriot v. Louis Vuitton N.A., Inc., No. 1:22-cv-02944 (S.D.N.Y.): In April, shoppers filed a class action against Louis Vuitton in a New York federal court for alleged BIPA violations in connection with company’s virtual try-on (“VTO”) tool made available to visitors of its website. The complaint alleges that the company’s technology scans users’ face geometry, producing complete facial scans and images of customers’ faces—all without giving notice or obtaining consent when visitors try on its designer eyewear using the tool. As VTO facial recognition class actions continue to be a hot trend in BIPA litigation (as discussed in more detail below), retailers and other companies that utilize this “try before you buy” technology should ensure they are strictly complying with the mandates of BIPA to mitigate the significant class action risks associated with these tools.

New and Emerging Biometric Privacy Trends

BIPA VTO Litigation Wave Not Over Yet: BIPA litigation in 2021 was marked by a wave of class action suits filed against retailers—including fashion, eyewear, and makeup brands—in connection with virtual try-on (“VTO”) tools offered to online shoppers. As the name suggests, VTO tools, also known as “virtual mirrors,” allow shoppers to “try on” products using their camera-equipped devices, such as home computers, tablets, or mobile phones. Importantly, VTO technology is powered by a combination of AI and AR, as opposed to traditional facial recognition technology used to identify or verify an individual’s identity. Despite this, many brands found themselves the targets of BIPA class litigation, with plaintiffs arguing that their VTO technology performed scans of face geometry, thus bringing the tools under the scope of BIPA. While the pace of filings has slowed somewhat in 2022, VTO technology continues to be a main target for class actions, including a number of suits filed against retailers that utilize these tools during Q2.

Increase in BIPA Suits Targeting Third-Party Vendors: Another notable trend seen during Q2 was a marked increase in the number of BIPA class actions targeting third-party vendors that offer biometric technology software and solutions, such as identity verification tools and employee timeclocks. Of note, these vendors do not maintain any direct relationship with the individuals who claim their biometric data was collected or used in violation of BIPA, but rather whose technology is merely utilized by their clients to facilitate the use of biometric data in commercial operations. Just two examples of this trend are the Berbix class action discussed above, as well as the Ronquillo case discussed below.

Contactless Fingerprinting Makes Strides Towards Adoption: While research around contactless fingerprinting technology is not new, latest advancements are drawing the attention and interest of law enforcement. The development of new, more advanced technologies used for identity verification purposes is on the rise, especially in the wake of COVID-19 and its associated health and safety concerns. Soon, phone cameras will be capable of scanning and capturing a person’s fingerprint—easily identifying all the lines and swirls on their fingertips—all without even having to touch a screen. While this technology may raise concerns amongst civil liberty and privacy groups, law enforcement is already looking into ways to harness its potential—and you can be sure the private sector will be soon to follow.

Significant Biometric Privacy Class Action Decisions & Related Developments

Zellmer v. Facebook, Inc., No. 3:18-cv-1880, 2022 U.S. Dist. LEXIS 60239 (N.D. Cal. Apr. 1, 2022): A California federal court issued a notable BIPA opinion in Zellmer v. Facebook, Inc. (covered by SPB team members Kristin Bryan and David Oberly in this CPW article), which could have significant implications moving forward for companies seeking to limit their scope of liability exposure in BIPA class action litigation. In Zellmer, the court granted summary judgment to Facebook on the Section 15(b) notice and consent claim asserted in the case, finding that non-users were precluded as a matter of law from maintaining an actionable claim under Section 15(b). The court reasoned that a Section 15(b) claim could not exist for non-users because it would be patently unreasonable to construe BIPA to require companies to provide notice to, and obtain consent from, non-users who were for all practical purposes total strangers to the company, and with whom the company maintained no relationship whatsoever. Rather, a Section 15(b) claim can be in play only where there is at least a minimum level of known contact between a person and the entity that might be collecting biometric information. While the opinion itself was short—comprising only eight pages—the Zellmer court’s reasoning may have a noteworthy impact on the scope of Section 15(b) claims moving forward. 

Sosa v. Onfido, Inc. No. 1:20-cv-04247, 2022 U.S. Dist. LEXIS 74672 (N.D. Ill. Apr. 25, 2022): In Sosa v. Onfido, Inc. , an Illinois federal court rejected the argument that BIPA exempts biometric data extracted from photographs, finding instead that faceprints derived through photographic means can constitute “biometric identifiers” regulated by Illinois’s biometric privacy statute. The Onfido opinion is significant, as it likely shuts the door on a defense that has, until now, been broadly utilized by a wide range of targets of BIPA class action suits. 

Ronquillo v. Doctor’s Assocs., LLC, 1:21-cv-04903, 2022 U.S. Dist. LEXIS 62730 (N.D. Ill. Apr. 4, 2022): As courts continue to expand the scope of BIPA class action liability exposure, they have been especially unforgiving to third-party technology vendors—despite the challenges that these non-consumer facing entities have with satisfying the requirements of Illinois’s biometrics law. Such was the case for HP Inc., which in early April saw its motion to dismiss a BIPA class action denied by an Illinois federal court—even though the company lacked any kind of direct relationship with the individual who filed suit. In Ronquillo, an employee at Subway restaurants brought suit against HP and Doctor’s Associates, LLC (“DAL”), alleging that the defendants captured and stored her fingerprints without her informed consent through a Subway point-of-sale system to clock in and out of work, and to unlock cash registers. DAL and HP took the position that they did not actively collect employees’ biometric data; rather, at most, they merely possessed such data. As such, according to DAL and HP, they fell outside the scope of the biometrics law. The court disagreed, finding that in making this argument, the defendants were “attempt[ing] to rewrite the complaint to avoid its genuine allegations, which allow for the reasonable inference that DAL and HP played more than a passive role in the process.” Id. at *8. While also noting that it was leaving the question of whether the plaintiff would actually be able to provide DAL’s and HP’s role in collecting her biometric data for another day and with a more developed record, the court concluded that, at least at the motion to dismiss stage, the complaint sufficiently alleged that Section 15(b) applied to DAL and HP. In addition, the court also expressly rejected the argument that Section 15(b) did not apply to third-party vendors of technology used by employers to obtain workers’ biometric data, finding that there was nothing in BIPA’s text that the law was intended to apply only to employers, but not to parties without any direct relationship to the plaintiff. Importantly, the Ronquillo decision deals a significant blow to one of the third-party vendors’ primary arguments against BIPA liability while at the same time demonstrating how courts continue to interpret the statutory text of BIPA in an extremely broad, plaintiff-friendly manner.

Johnson v. Mitek Sys., Inc., No. 0:22-cv-01830, 2022 U.S. Dist. LEXIS 80851 (N.D. Ill. May 4, 2022): While arbitration continues to remain a powerful defense in BIPA class actions, not all attempts at dismissing BIPA claims through the pursuit of motions to compel arbitration are successful. Such was the case in Johnson v. Mitek Sys., Inc., where ID verification firm Mitek Systems, Inc. recently lost its bid to force BIPA plaintiffs to resolve their claims out of court and through individual, binding arbitration. Mitek arose in connection with the company’s age and identity verification service, which was used by rental car service HyreCar and required the plaintiff to upload his driver’s license and photograph. According to the plaintiff, this verification process was completed with the assistance of facial recognition technology, which unlawfully collected her biometric data without providing notice or obtaining his consent. The court denied Mitek’s motion to compel arbitration, finding that the company was not a party to the arbitration agreement between the rental company and its customer and further that the third-party beneficiary exception to the general rule that non-signatories to an arbitration agreement cannot be bound by such contracts was inapplicable to force arbitration against the plaintiff. The Mitek decision should serve as a reminder for all companies that use biometric data in their operations to ensure they have a robust arbitration agreement of their own in place and to avoid relying solely on the agreements of their clients or vendors.

Rogers v. BNSF Ry. Co., No. 1:19-cv-03083, 2022 U.S. Dist. LEXIS 10934 (N.D. Ill. June 21, 2022): At the same time (and just the opposite of Ronquillo), courts continue to cast a wide liability net for allegedly improper biometric data collection and possession practices, ensnaring even those companies whose involvement with biometrics systems is tenuous at best. Such was the case for BNSF Railway Company, which hired external security contractors to operate its biometric-powered access control system at its Illinois rail facilities and later found itself the defendant in a BIPA class action. In June, an Illinois federal judge refused to certify an interlocutory appeal filed by BNSF following the court’s denial of its motion for summary judgment, which had rejected the railroad’s preemption argument and found that a jury must decide whether the railroad’s connection with its fingerprint access control technology operated by its third-party vendor was sufficient to trigger liability for improper biometric data collection and possession practices under BIPA Sections 15(a) and 15(b). The company had sought a Seventh Circuit review of the district court’s decision involving the issues concerning federal preemption and vicarious liability, but the district court refused to allow the appeal to proceed, basing its decision primarily on what it characterized as a “misreading of [the district court’s] ruling” and a failure to raise the arguments it looked to assert on appeal in its prior summary judgment briefing.

Barton v. Walmart Inc., No. 1:21-cv-04329 (N.D. Ill. May 31, 2022): In May, an Illinois federal court refused to dismiss a class action involving allegations that Walmart violated BIPA by requiring Illinois warehouse workers to use voice recognition software. In Barton, Walmart workers alleged that they were required to submit their voiceprints by reading into biometric-powered inventory computer systems known as “Pick Task-Voice Template Words.” Walmart, however, contended that its voice system did not identify specific employees by their voices but instead only recognized words spoken into the headsets. According to Walmart, the identification of specific worker identities came from workers’ employee numbers that were manually entered into the system—not based on their voice patterns. The Barton decision further underscores the lack of clarity regarding the precise definition of “biometric identifiers” under BIPA, which will remain one of the most hotly-contested issues in BIPA class litigation for the foreseeable future—and until courts provide more guidance on this key matter.

Rivera v. Google Inc., No. 2019-CH-00990 (Ill. Cir. Ct. Cook Cnty.): In late April, Google settled its longstanding Rivera BIPA dispute, agreeing to pay $100 million to resolve allegations that it improperly collected individuals’ facial biometric data through its cloud-based Google Photos feature in violation of Illinois’s biometric privacy statute. While notably less than 2020’s record-breaking $650 million BIPA settlement involving one of the world’s largest social media companies, the $100 million figure agreed to by Google to put an end to the Rivera litigation will only give plaintiff’s attorneys even more motivation to pursue BIPA class action litigation for the foreseeable future. And, although the size of the Rivera settlement is not by any means indicative of normal settlement figures in BIPA cases, the plaintiff’s lawyers will almost certainly use this settlement as a measuring stick to value other BIPA disputes—likely causing inflated settlement figures moving forward, at least in the immediate term. Importantly, this settlement should serve as a cautionary tale and reminder of the critical need for companies to maintain comprehensive, flexible biometric privacy programs to minimize potential liability exposure.

Artificial Intelligence & Biometric Privacy Legislative/Regulatory Developments

Majority of Biometric Privacy Bills Fail (With One Notable Exception): While the number of biometric privacy bills introduced by state and municipal legislatures in 2022 increased significantly as compared to the year prior, the vast majority of those proposals failed during the legislative process and did not make their way into law. With that said, one piece of proposed legislation remains currently pending that could bring wholesale changes to the biometric privacy legal landscape if enacted this year. That legislation, California’s HB 1189, provides for a private right of action almost identical to that of BIPA, which would likely bring with it a tsunami of class litigation to California on part with what has taken place in Illinois for several years now. Not only that, HB 1189 is one of several “hybrid” biometric privacy bills introduced in 2022 that blend traditional biometric privacy legal principles and other compliance requirements and limitations which, until now, were ordinarily confined exclusively to broader, comprehensive state consumer privacy statutes. Importantly, these hybrid requirements would significantly increase compliance burdens for all companies that collect and use biometric data while also ushering in a correspondingly-high increase in liability exposure risks. 

EEOC Issues Guidance on Use of Artificial Intelligence by Employers: On May 12, 2022, the U.S. Equal Employment Opportunity Commission (“EEOC”) issued important guidance regarding the use of algorithms and AI in the context of hiring and employment decisions. The guidance follows on the heels of the EEOC’s Initiative on Artificial Intelligence and Algorithmic Fairness, which was launched by the Commission in late 2021. The guidance itself provides a detailed discussion regarding how employers’ reliance on AI and algorithmic decision-making in the employment context may run afoul of the Americans with Disabilities Act (“ADA”). In addition, the guidance also provides several recommended “promising practices” for employers to consider to mitigate the risk of discriminating against individuals with disabilities when using algorithmic decision-making tools and similar AI technologies. All employers that are currently using AI for any purpose—or intend to do so in the future—should familiarize themselves with the guidance if they have not already done so.

CFPB Issues Guidance on Use of Artificial Intelligence by Creditors: Also in May, the federal Consumer Financial Protection Bureau (“CFPB”) issued guidance of its own, Circular 2022-03, “Adverse action notification requirements in connection with credit decisions based on complex algorithms,” focusing on the need for creditors to comply with the Equal Opportunity Credit Act’s (“ECOA”) requirement to provide a statement of specific reasons to applicants against whom adverse action is taken when making credit decisions based on complex algorithms. Importantly, the CFPB clarifies that compliance is required even when using algorithms—sometimes referred to as “black-box” models, that prevent creditors from accurately identifying the specific reasons for denying credit or taking other adverse actions. The guidance illustrates that the EEOC and its adverse action requirements will be enforced by the CFPB irrespective of the technology that is utilized by creditors and that creditors cannot excuse their noncompliance based on the mere fact that its technology used to evaluate applications is too complicated or opaque in its decision-making to understanding. The recently-issued guidance, along with a statement issued by CFPB Director Rohit Chopra in conjunction with the Circular, provides a key window into the aggressive tact that the CFPB will likely take in enforcing improper AI practices that may run afoul of the ECOA. All creditors (and other entities subject to the CFPB’s jurisdiction) that currently use AI—or intend to do so in the future—should familiarize themselves with the guidance if they have not already done so.

Federal Trade Commission Back at Full Strength: On May 11, 2022, privacy law expert and then-head of Georgetown University Law School’s Center on Privacy and Technology, Alvaro Bedoya, was confirmed as the latest FTC Commissioner. Bedoya replaces former FTC Commissioner Rohit Chopra, who now heads the Consumer Financial Protection Bureau (“CFPB”). Bedoya is an expert in facial recognition and is widely recognized for his role in co-authoring a 2016 study that is credited as the impetus for a number of latest state and local laws limiting the use of facial recognition by the public sector. During his late 2021 confirmation hearing testimony, Bedoya advocated for increased FTC scrutiny over facial biometrics and its privacy-related impacts, especially as it relates to minorities, noting its reputation for misuse and abuse. At the same time, he also noted his support for potential FTC privacy rulemaking. With the FTC now back at full strength and with a Democratic majority, companies should anticipate an aggressive privacy enforcement agenda by the Commission, including increased scrutiny of both facial recognition practices and potential bias and discrimination concerns relating to AI and algorithmic decision-making.

FTC Issues Report to Congress on Use of AI to Combat Online Harms: On June 16, 2022, the FTC issued a report to Congress, Combatting Online Harms Through Innovation, warning about the use of AI to combat online problems and urging lawmakers to exercise “great caution” about relying on AI as a policy solution. While the Report does not break any new ground in terms of how the FTC may pursue investigations or enforcement actions against private sector organizations that utilize AI in their day-to-day operations, the Report nonetheless provides several key takeaways for all entities that currently rely on this advanced form of technology or intend to do so in the future. To learn more about the Report and its major takeaways, read our latest CPW blog post here.

Automated Decision-Making and Profiling Conspicuously Absent From Initial Draft CPRA Regulations: The California Privacy Rights Act (“CPRA”) places significant power in the hands of the California Privacy Protection Agency (“CPPA”) to shape the future of privacy regulation in the United States, including with respect to how automated decision-making and profiling is regulated throughout the country. For this reason, the CPPA focused a significant amount of its preliminary rulemaking activities on these two interrelated issues. These efforts began last fall when automated decision-making and profiling were included as part of nine Topics on which the CPPA sought public comment. In May, the CPPA held stakeholder sessions over the course of three days, during which time three hours were devoted exclusively to allowing stakeholders to comment on issues relating to automated decision-making and profiling. Notably, however, the CPPA’s draft CPRA Regulations—issued at the end of May—do not address automated decision-making or profiling in any fashion whatsoever. With that said, companies should anticipate that these issues will be addressed in subsequent iterations of the Regulations.

Connecticut Enacts New Privacy Statute Encompassing Biometric Data: On May 10, 2222, Connecticut Governor Ned Lamont officially signed into law Public Act No. 22-15, “An Act Concerning Personal Data Privacy and Online Monitoring.” More commonly referred to as the “Connecticut Privacy Act,” the statute becomes the fifth law of its kind to be enacted in the U.S. and will go into effect on July 1, 2023. In addition to affording Connecticut consumers a range of new privacy rights, the law also governs the collection and use of “biometric data,” which is defined as any data generated by automatic measurements of an individual’s biological characteristics, such as a fingerprint, voiceprint, eye retinas, irises, or other unique biological patterns or characteristics that are used to identify a specific individual.

FTC Investigates In May, Oregon Senator Wyden urged the FTC to investigate the identity verification company for potential deceptive practices which may have misled consumers and government agencies. A company experiencing growth in the midst of the pandemic, uses a mixture of selfies, document scans, and other methods to verify identities online. is currently the subject of other government investigation. Senators are particularly concerned about the potential confusion between two different types of technology – one which involves a one-time comparison of two images to confirm an applicant’s identity and involves one-to-many recognition, where millions of innocent people have their photos included as a comparison in a digital “line up.” Wyden and others fear that the company made “multiple misleading statements” about “superior” facial recognition use, which may be potentially damaging to consumer understanding.

EU’s Artificial Intelligence Act Receives Support From Privacy Advocates: In April 2021, the European Commission released the initial draft version of its proposed Artificial Intelligence Act (“AIA”), which seeks to implement a first-of-its-kind comprehensive regulatory scheme for AI technologies. Like the EU’s General Data Protection Regulation (“GDPR”), the territorial scope of the AIA would be expansive, governing not just EU organizations that utilize AI but also companies located outside the EU that operate AI within the EU, as well as organizations whose operation of AI impacts EU residents. Recently, European Digital Rights (“EDRi”) and dozens of other privacy advocacy organizations penned an open letter not just supporting efforts to enact the AIA but to expand the legislation to include a ban on remote biometric identification (“RBI”) systems, such as facial recognition, in all public spaces. Companies that currently deploy AI in their operations—or may do so in the future—should keep tabs on future developments regarding the AI Act moving forward, which will have wide-reaching implications extending far beyond the EU if the legal framework becomes law.  

The Final Word

While Q2 provided us with a number of significant developments in the areas of AI and biometric privacy, companies are sure to see many additional litigation, legislative, and regulatory developments during the second half of 2022 as well.

© Copyright 2022 Squire Patton Boggs (US) LLPNational Law Review, Volume XII, Number 215

Wed, 03 Aug 2022 02:54:00 -0500 en text/html
Killexams : Effort tracking US school shootings loses federal funding weeks after Uvalde massacre

An effort to update one of the most comprehensive databases tracking school shootings nationwide is no longer receiving federal funding, according to the project’s top researcher, who says a private contractor recently decided not to renew his contract working on the database.  
The K-12 School Shooting Database has been widely cited by news organizations and featured in dozens of academic reports and studies, including numerous analyses of school safety by federal government agencies, including the Department of Justice, Department of Education and the Government Accountability Office. 
Since its inception four years ago, prompted by a high-profile school shooting in Parkland, Fla., the database had been supported by the federal Center for Homeland Defense and Security. 
But database co-founder David Riedman said a private company contracted by the federal center told him on June 30 that his contract with the company to work on the database, which expired that day, would not be renewed. 
Riedman said he believed political pressure played a role in that decision, which came weeks after the database received heightened press and public attention following a mass school shooting in Uvalde, Texas, in late May in which 19 children and two adults were killed – the second deadliest school shooting in U.S. history. 
Riedman said he's updated the database on his own over the past month on a separate website he’s funding himself, He said he’s committed to continuing the project but plans to do so independently.

"I'm disappointed to see after four years for the project to go that direction after one of the worst school shootings in latest U.S. history," said Riedman. 
Lea Culver, president and CEO of the private contractor, Creek Technologies Inc., declined to comment on why Riedman’s contract was not renewed, saying the company "does not comment directly on (employment) and consultant issues." 
Creek Technologies, an Ohio-based company that specializes in information technology, educational services and management consulting, "continues to deliver high-quality services" to the federal center "and is not breaching its contractual obligations," Culver said. 
The Center for Homeland Defense and Security this month revised its website to say future updates to the database will be done by Riedman on the new, independent website he created and provided a link to Riedman’s website. 
The center said it plans to convert the data previously collected into a historical report that will be part of an upcoming “School Shooting Safety Compendium to aid officials and researchers on the topic.” Along with the report, “the new Compendium website will include data, research links, recommended policies, procedures, and resources related to school safety and preventing violence in schools,” the center’s website said. 
Ed Early, a spokesman for the U.S. Navy’s Naval Postgraduate School based in Monterey, Calif., which operates the Center for Homeland Defense and Security, said in a statement: “Neither CHDS nor NPS was or is a party to financial or employment negotiations between Creek Technologies and its subcontractor. Within federal regulations and guidelines, the contractor can pursue different paths and options to meet the government’s requirements to include employment of sub-contractors or not.” 
“Regardless of any changes behind the scenes, what is important is that CHDS remains committed to supporting the K-12 School Shooting Database project and ensuring that this valuable resource continues to inform policymakers on possible solutions to these extraordinarily tragic events,” the statement added. “As part of this effort, CHDS has taken measures to maintain the historical database record on the CHDS website as a definitive, reliable resource for CHDS students, researchers and the public.” 
While some other federal and privately run databases track gun violence nationwide, the K-12 School Shooting Database stands out in several ways. 
"It's very, very valuable," said Justin Heinze, an educational psychology professor at the University of Michigan who has used the database. "What I like a lot about this database is the granularity." 
The definition for what types of incidents the database captures is broad. Riedman said the purpose is to not just account for high-profile mass shooting events, but also systemic gun violence incidents that can go overlooked and have been shown to disproportionately impact students of color and students from low-income families. According to the database, it "documents when a gun is brandished, is fired, or a bullet hits school property for any reason, regardless of the number of victims, time, or day of the week." 
There are more than 2,070 incidents recorded in the database, from a shooting Monday near a New York City high school that wounded a 16-year-old boy and a 12-year-old girl to the nation’s deadliest school shooting on record – the 2012 massacre at Sandy Hook Elementary School in which 20 children and 6 adults were killed. 
The data dates to 1970 – far longer than many other gun violence data sources – and it updates daily, whereas government data on mass shootings can lag by months or years. 

The database features uniquely rich details about each incident, such as describing where on school grounds the shooting occurred, what else was happening at the school at the time, and how the incident ended, which can be valuable for trying to understand trends and patterns around school gun violence, experts said. All the raw data, as well as details about the methodology researchers use to collect it, are available to anyone online. 
Heinze said if the project were to stop updating, it would be "a deficit to the research community." 
He said that's particularly the case because little research into gun violence was done from the mid-1990s, after the National Rifle Association successfully lobbied Congress to implement a de-facto ban on using federal funding for such research, until 2019, when Congress began allocating federal money to study gun violence – $25 million a year to the Centers for Disease Control and Prevention and the National Institutes of Health. 
"We are at a pivotal turning point where you are starting to see the federal government invest a lot of resources into gun violence prevention," said Heinze, who co-directs the National Center for School Safety and is an affiliate of the Institute for Firearm Injury Prevention. 
Kelly Drane, research director at the Giffords Law Center to Prevent Gun Violence, said there should be a greater investment of federal dollars to track school shootings and such work should not be viewed as controversial. 
“The federal government should be interested in tracking gun violence at schools and presenting that data to the public,” said Drane. “Every American should want to know how many times guns are being fired at schools regardless of what you think the solutions are.”  
At the time of the 2018 shooting in Parkland, Fla., which left 17 people dead and 17 injured, Riedman said he was enrolled in a Naval Postgraduate School program designed to incubate solutions for emerging homeland security issues.

“After Parkland, there were a number of warning signs, and those were missed because people didn't realize they were warning signs,” Riedman said.

He and another classmate initially envisioned creating a resource for teachers and school administrators to look out for, and act upon, potential warning signs.

To develop that, “We wanted to look at as many prior school shootings as we could to see how many they could stop,” Riedman said. "But we just couldn't find any good data."

Instead, he and the classmate began to build a database of their own, which became the K-12 School Shooting Database. The first iteration was published in September 2018.
Since December 2018, Riedman said he has been the lone researcher who has updated the database. 

Riedman said the project expanded and got a boost in resources during 2020 after the pandemic freed up money that would have otherwise been spent on travel. Updates included getting help to revamp the webpage hosting the data and building new ways to present the data using maps and graphics. 

Riedman said he hopes to keep improving the database through new partnerships with researchers and academic institutions. 
"This information has a ton of power to inform public policy and prevent another attack," Riedman said. 
He's focused on keeping the project "independent, nonpartisan and very transparent." 
While it wasn’t something he envisioned for the project a few weeks ago, he sees its newfound independence as a silver lining to his latest ordeal. 
“There are advantages to being involved with an official center and also disadvantages in terms of the amount of autonomy and how quickly you can make changes,” he said. Now, “there are a lot of opportunities to collaborate with people I otherwise wouldn’t have been able to collaborate with before.” 
“Ironically,” Riedman said, “this has highlighted the importance of this being an independent project.” 

Fri, 29 Jul 2022 07:49:00 -0500 en-US text/html Killexams : Retail Banking IT Spending Market to record USD 15.69 Bn growth -- Driven by the growing need for greater customer satisfaction

NEW YORK, Aug. 8, 2022 /PRNewswire/ -- The "Retail Banking IT Spending Market by Type and Geography - Forecast and Analysis 2022-2026" report by Technavio expects the market size to grow by USD 15.69 billion between 2021 and 2026, expanding at a CAGR of 5.15% during the forecast period. The report identifies North America as the key region. The rapid growth of the banking sector is creating significant opportunities for vendors operating in the region. The report provides a comprehensive analysis of latest developments, new product launches, major revenue-generating segments, and market behavior across geographies. Download trial PDF Report Here

Technavio has announced its latest market research report titled Retail Banking IT Spending Market by Type and Geography - Forecast and Analysis 2022-2026

The global retail banking IT spending market is fragmented, with the presence of a significant number of vendors. Key vendors hold significant shares in the market. Established vendors have strong financial abilities and technical expertise in offering innovative and quality products. They also invest a significant share of their capital in R&D and adopt organic growth strategies, such as product launches, to bring considerable differentiation in their solutions and gain high customer penetration. Small-scale vendors compete with established vendors by using low-price strategies and strengthening their local customer base. As more banks are embracing digital transformation in retail banking, this is expected to create further growth opportunities for the vendors during the forecast period.

Technavio identifies Accenture Plc, Atos SE, Capgemini SE, CGI Inc., Cisco Systems Inc., Cognizant Technology Solutions Corp., Dell Technologies Inc., Fidelity National Information Services Inc., Fujitsu Ltd., Genpact Ltd., HCL Technologies Ltd., Hitachi Ltd., HP Inc., Infosys Ltd., Intel Corp., International Business Machines Corp., Microsoft Corp., NetApp Inc., Oracle Corp., SAP SE, Wipro Ltd., and WNS Holdings Ltd. as some of the major market participants.

Although the growing need for greater customer satisfaction, increased efficiency in banking operations, and rise in autonomous banking will offer immense growth opportunities, issues related to data privacy and security, interoperability issues, and the lack of sufficient skilled labor will challenge the growth of the market participants. To make the most of the opportunities, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments. View trial Report Here

The retail banking IT spending Market is segmented as below:

The IT services segment held the largest share of the market in 2021. The segment includes application development and maintenance, system integration, IT consulting, software deployment and support, and hardware deployment and support. The adoption of advanced technologies such as big data analytics, AI, and cloud-based computing to reduce costs and increase operational efficiencies is driving the growth of the segment.

37% of the market growth will originate from North America during the forecast period. The increase in mobile banking transactions and the deployment of AI and machine learning (ML) technologies by BFSI firms are driving the growth of the regional market. Technavio presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources. Our retail banking IT spending market report covers the following areas:

Retail Banking IT Spending Market 2022-2026: Vendor Analysis

We provide a detailed analysis of around 25 vendors operating in the retail banking IT spending market. Backed with competitive intelligence and benchmarking, our research report on the retail banking IT spending market is designed to provide entry support, customer profile, and M&As as well as go-to-market strategy support.

Retail Banking IT Spending Market 2022-2026: Key Highlights

  • CAGR of the market during the forecast period 2022-2026

  • Detailed information on factors that will assist retail banking IT spending market growth during the next five years

  • Estimation of the retail banking IT spending market size and its contribution to the parent market

  • Predictions on upcoming trends and changes in consumer behavior

  • The growth of the retail banking IT spending market

  • Analysis of the market's competitive landscape and detailed information on vendors

  • Comprehensive details of factors that will challenge the growth of retail banking IT spending market vendors

Related Reports:

Retail Banking IT Spending Market Scope

Report Coverage


Page number


Base year


Forecast period


Growth momentum & CAGR

Accelerate at a CAGR of 5.15%

Market growth 2022-2026

USD 15.69 billion

Market structure


YoY growth (%)


Regional analysis

North America, Europe, APAC, Middle East and Africa, and South America

Performing market contribution

North America at 37%

Key consumer countries

US, Canada, China, Germany, and UK

Competitive landscape

Leading companies, competitive strategies, consumer engagement scope

Companies profiled

Accenture Plc, Atos SE, Capgemini SE, CGI Inc., Cisco Systems Inc., Cognizant Technology Solutions Corp., Dell Technologies Inc., Fidelity National Information Services Inc., Fujitsu Ltd., Genpact Ltd., HCL Technologies Ltd., Hitachi Ltd., HP Inc., Infosys Ltd., Intel Corp., International Business Machines Corp., Microsoft Corp., NetApp Inc., Oracle Corp., SAP SE, Wipro Ltd., and WNS Holdings 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, 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:

1 Executive Summary

2 Market Landscape

3 Market Sizing

4 Five Forces Analysis

5 Market Segmentation by Type

6 Customer Landscape

7 Geographic Landscape

8 Drivers, Challenges, and Trends

9 Vendor Landscape

10 Vendor Analysis

11 Appendix

About Us

Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging market trends and provides 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.


Technavio Research
Jesse Maida
Media & Marketing Executive
US: +1 844 364 1100
UK: +44 203 893 3200

Technavio (PRNewsfoto/Technavio)


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Mon, 08 Aug 2022 02:20:00 -0500 en-US text/html
Killexams : Gaming Monitor Market 2022-2026: Global Size, Share, Emerging Trends, Demand, Revenue and Forecast Study | 111 Report Pages

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

Jul 26, 2022 (The Expresswire) -- ""Gaming Monitor Market"" Insights 2022 AOC/Philips, ASUS, Acer, MSI, Samsung, Dell, LG, Lenovo, HP, HKC, BenQ ZOWIE, Viewsonic, Razer, Gigabyte, SANC, Regions and Forecast to 2026. The global Gaming Monitor market size is projected to reach multi million by 2026, in comparison to 2022, with unexpected CAGR during the forecast period, the Gaming Monitor Market Report Contains 111 pages Including Full TOC, Tables and Figures, and Chart with In-depth Analysis Pre and Post COVID-19 Market Outbreak Impact Analysis and Situation by Region.

Gaming Monitor Market - Covid-19 Impact and Recovery Analysis:

We have been tracking the direct impact of COVID-19 on this market, as well as the indirect impact from other industries. This report analyses the impact of the pandemic on the Gaming Monitor market from a Global and Regional perspective. The report outlines the market size, market characteristics, and market growth for Gaming Monitor industry, categorized by type, application, and consumer sector. In addition, it provides a comprehensive analysis of aspects involved in market development before and after the Covid-19 pandemic. Report also conducted a PESTEL analysis in the industry to study key influencers and barriers to entry.

Final Report will add the analysis of the impact of COVID-19 on this industry.


It also provides accurate information and cutting-edge analysis that is necessary to formulate an ideal business plan, and to define the right path for rapid growth for all involved industry players. With this information, stakeholders will be more capable of developing new strategies, which focus on market opportunities that will benefit them, making their business endeavours profitable in the process.

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Gaming Monitor Market - Competitive and Segmentation Analysis:

This Gaming Monitor Market report offers detailed analysis supported by reliable statistics on sale and revenue by players for the period 2017-2022. The report also includes company description, major business, Gaming Monitor product introduction, latest developments and Gaming Monitor sales by region, type, application and by sales channel.

The major players covered in the Gaming Monitor market report are:

● AOC/Philips ● ASUS ● Acer ● MSI ● Samsung ● Dell ● LG ● Lenovo ● HP ● HKC ● BenQ ZOWIE ● Viewsonic ● Razer ● Gigabyte ● SANC

Short Summery About Gaming Monitor Market:

The Global Gaming Monitor market is anticipated to rise at a considerable rate during the forecast period, between 2022 and 2026. In 2021, the market is growing at a steady rate and with the rising adoption of strategies by key players, the market is expected to rise over the projected horizon.

Gaming monitor is defined as displays with a frame rate of 100Hz or above, Gaming monitors are designed to make the output of your graphics card and CPU look as good as possible while gaming. They're responsible for displaying the final result of all of your computer's image rendering and processing, yet they can vary widely in their representation of color, motion, and image sharpness. When considering what to look for in a gaming monitor, it's worth taking the time to understand everything a gaming monitor can do, so you can translate gaming monitor specs and marketing into real-world performance.

Market Analysis and Insights: Global and United States Gaming Monitor Market

This report focuses on global and United States Gaming Monitor market, also covers the segmentation data of other regions in regional level and county level.

Due to the COVID-19 pandemic, the global Gaming Monitor market size is estimated to be worth USD 7578.4 million in 2022 and is forecast to a readjusted size of USD 17440 million by 2028 with a CAGR of 14.9% during the review period. Fully considering the economic change by this health crisis, by Refresh Rate, 144Hz accounting for % of the Gaming Monitor global market in 2021, is projected to value USD million by 2028, growing at a revised % CAGR in the post-COVID-19 period. While by Sales Channel, Online was the leading segment, accounting for over percent market share in 2021, and altered to an % CAGR throughout this forecast period.

The global key manufacturers of gaming monitor include AOC/Philips, ASUS, Acer , MSI and Samsung etc. The top 5 companies hold a share of nearly 50%. Asia-Pacific takes up the largest sales market, with a share of nearly 50%, followed by Europe and North America, with the share of about 30% and 20% respectively.

Global Gaming Monitor Scope and Market Size

Gaming Monitor market is segmented by region (country), players, by Type and by Application. Players, stakeholders, and other participants in the global Gaming Monitor market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on revenue and forecast by region (country), by Type and by Application for the period 2017-2028.

For United States market, this report focuses on the Gaming Monitor market size by players, by Refresh Rate and by Sales Channel, for the period 2017-2028. The key players include the global and local players, which play important roles in United States.

Segment by Refresh Rate






Segment by Sales Channel



By Region

North America

United States











South Korea



China Taiwan




Latin America




Middle East and Africa


Saudi Arabia


By Company
















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Report further studies the market development status and future Gaming Monitor Market trend across the world. Also, it splits Gaming Monitor market Segmentation by Type and by Applications to fully and deeply research and reveal market profile and prospects.

On the basis of product typethis report displays the production, revenue, price, market share and growth rate of each type, primarily split into:

● 144Hz ● 165Hz ● 240Hz ● 360Hz ● Others

On the basis of the end users/applicationsthis report focuses on the status and outlook for major applications/end users, consumption (sales), market share and growth rate for each application, including:

● Online ● Offline

Gaming Monitor Market - Regional Analysis:

Geographically, this report is segmented into several key regions, with sales, revenue, market share and growth Rate of Gaming Monitor in these regions, from 2015 to 2026, covering

● North America (United States, Canada and Mexico) ● Europe (Germany, UK, France, Italy, Russia and Turkey etc.) ● Asia-Pacific (China, Japan, Korea, India, Australia, Indonesia, Thailand, Philippines, Malaysia and Vietnam) ● South America (Brazil, Argentina, Columbia etc.) ● Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

Some of the key questions answered in this report:

● What is the global (North America, Europe, Asia-Pacific, South America, Middle East and Africa) sales value, production value, consumption value, import and export of Gaming Monitor? ● Who are the global key manufacturers of the Gaming Monitor Industry? How is their operating situation (capacity, production, sales, price, cost, gross, and revenue)? ● What are the Gaming Monitor market opportunities and threats faced by the vendors in the global Gaming Monitor Industry? ● Which application/end-user or product type may seek incremental growth prospects? What is the market share of each type and application? ● What focused approach and constraints are holding the Gaming Monitor market? ● What are the different sales, marketing, and distribution channels in the global industry? ● What are the upstream raw materials and manufacturing equipment of Gaming Monitor along with the manufacturing process of Gaming Monitor? ● What are the key market trends impacting the growth of the Gaming Monitor market? ● Economic impact on the Gaming Monitor industry and development trend of the Gaming Monitor industry. ● What are the market opportunities, market risk, and market overview of the Gaming Monitor market? ● What are the key drivers, restraints, opportunities, and challenges of the Gaming Monitor market, and how they are expected to impact the market? ● What is the Gaming Monitor market size at the regional and country-level?

Our research analysts will help you to get customized details for your report, which can be modified in terms of a specific region, application or any statistical details. In addition, we are always willing to comply with the study, which triangulated with your own data to make the market research more comprehensive in your perspective.

Inquire more and share questions if any before the purchase on this report at -

Detailed TOC of Global Gaming Monitor Market Research Report 2022

1 Gaming Monitor Market Overview

1.1 Product Overview and Scope of Gaming Monitor
1.2 Gaming Monitor Segment by Type
1.2.1 Global Gaming Monitor Market Size Growth Rate Analysis by Type 2022 VS 2026
1.3 Gaming Monitor Segment by Application
1.3.1 Global Gaming Monitor Consumption Comparison by Application: 2022 VS 2026
1.4 Global Market Growth Prospects
1.4.1 Global Gaming Monitor Revenue Estimates and Forecasts (2017-2026)
1.4.2 Global Gaming Monitor Production Capacity Estimates and Forecasts (2017-2026)
1.4.3 Global Gaming Monitor Production Estimates and Forecasts (2017-2026)
1.5 Global Market Size by Region
1.5.1 Global Gaming Monitor Market Size Estimates and Forecasts by Region: 2017 VS 2021 VS 2026
1.5.2 North America Gaming Monitor Estimates and Forecasts (2017-2026)
1.5.3 Europe Gaming Monitor Estimates and Forecasts (2017-2026)
1.5.4 China Gaming Monitor Estimates and Forecasts (2017-2026)
1.5.5 Japan Gaming Monitor Estimates and Forecasts (2017-2026)

2 Market Competition by Manufacturers
2.1 Global Gaming Monitor Production Capacity Market Share by Manufacturers (2017-2022)
2.2 Global Gaming Monitor Revenue Market Share by Manufacturers (2017-2022)
2.3 Gaming Monitor Market Share by Company Type (Tier 1, Tier 2 and Tier 3)
2.4 Global Gaming Monitor Average Price by Manufacturers (2017-2022)
2.5 Manufacturers Gaming Monitor Production Sites, Area Served, Product Types
2.6 Gaming Monitor Market Competitive Situation and Trends
2.6.1 Gaming Monitor Market Concentration Rate
2.6.2 Global 5 and 10 Largest Gaming Monitor Players Market Share by Revenue
2.6.3 Mergers and Acquisitions, Expansion

3 Production Capacity by Region
3.1 Global Production Capacity of Gaming Monitor Market Share by Region (2017-2022)
3.2 Global Gaming Monitor Revenue Market Share by Region (2017-2022)
3.3 Global Gaming Monitor Production Capacity, Revenue, Price and Gross Margin (2017-2022)
3.4 North America Gaming Monitor Production
3.4.1 North America Gaming Monitor Production Growth Rate (2017-2022)
3.4.2 North America Gaming Monitor Production Capacity, Revenue, Price and Gross Margin (2017-2022)
3.5 Europe Gaming Monitor Production
3.5.1 Europe Gaming Monitor Production Growth Rate (2017-2022)
3.5.2 Europe Gaming Monitor Production Capacity, Revenue, Price and Gross Margin (2017-2022)
3.6 China Gaming Monitor Production
3.6.1 China Gaming Monitor Production Growth Rate (2017-2022)
3.6.2 China Gaming Monitor Production Capacity, Revenue, Price and Gross Margin (2017-2022)
3.7 Japan Gaming Monitor Production
3.7.1 Japan Gaming Monitor Production Growth Rate (2017-2022)
3.7.2 Japan Gaming Monitor Production Capacity, Revenue, Price and Gross Margin (2017-2022)

4 Global Gaming Monitor Consumption by Region
4.1 Global Gaming Monitor Consumption by Region
4.1.1 Global Gaming Monitor Consumption by Region
4.1.2 Global Gaming Monitor Consumption Market Share by Region
4.2 North America
4.2.1 North America Gaming Monitor Consumption by Country
4.2.2 United States
4.2.3 Canada
4.3 Europe
4.3.1 Europe Gaming Monitor Consumption by Country
4.3.2 Germany
4.3.3 France
4.3.4 U.K.
4.3.5 Italy
4.3.6 Russia
4.4 Asia Pacific
4.4.1 Asia Pacific Gaming Monitor Consumption by Region
4.4.2 China
4.4.3 Japan
4.4.4 South Korea
4.4.5 China Taiwan
4.4.6 Southeast Asia
4.4.7 India
4.4.8 Australia
4.5 Latin America
4.5.1 Latin America Gaming Monitor Consumption by Country
4.5.2 Mexico
4.5.3 Brazil

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5 Segment by Type
5.1 Global Gaming Monitor Production Market Share by Type (2017-2022)
5.2 Global Gaming Monitor Revenue Market Share by Type (2017-2022)
5.3 Global Gaming Monitor Price by Type (2017-2022)
6 Segment by Application
6.1 Global Gaming Monitor Production Market Share by Application (2017-2022)
6.2 Global Gaming Monitor Revenue Market Share by Application (2017-2022)
6.3 Global Gaming Monitor Price by Application (2017-2022)

7 Key Companies Profiled
7.1 Company
7.1.1 Gaming Monitor Corporation Information
7.1.2 Gaming Monitor Product Portfolio
7.1. CGaming Monitor Production Capacity, Revenue, Price and Gross Margin (2017-2022)
7.1.4 Company’s Main Business and Markets Served
7.1.5 Company’s latest Developments/Updates

8 Gaming Monitor Manufacturing Cost Analysis
8.1 Gaming Monitor Key Raw Materials Analysis
8.1.1 Key Raw Materials
8.1.2 Key Suppliers of Raw Materials
8.2 Proportion of Manufacturing Cost Structure
8.3 Manufacturing Process Analysis of Gaming Monitor
8.4 Gaming Monitor Industrial Chain Analysis

9 Marketing Channel, Distributors and Customers
9.1 Marketing Channel
9.2 Gaming Monitor Distributors List
9.3 Gaming Monitor Customers

10 Market Dynamics
10.1 Gaming Monitor Industry Trends
10.2 Gaming Monitor Market Drivers
10.3 Gaming Monitor Market Challenges
10.4 Gaming Monitor Market Restraints

11 Production and Supply Forecast
11.1 Global Forecasted Production of Gaming Monitor by Region (2023-2026)
11.2 North America Gaming Monitor Production, Revenue Forecast (2023-2026)
11.3 Europe Gaming Monitor Production, Revenue Forecast (2023-2026)
11.4 China Gaming Monitor Production, Revenue Forecast (2023-2026)
11.5 Japan Gaming Monitor Production, Revenue Forecast (2023-2026)

12 Consumption and Demand Forecast
12.1 Global Forecasted Demand Analysis of Gaming Monitor
12.2 North America Forecasted Consumption of Gaming Monitor by Country
12.3 Europe Market Forecasted Consumption of Gaming Monitor by Country
12.4 Asia Pacific Market Forecasted Consumption of Gaming Monitor by Region
12.5 Latin America Forecasted Consumption of Gaming Monitor by Country

13 Forecast by Type and by Application (2023-2026)
13.1 Global Production, Revenue and Price Forecast by Type (2023-2026)
13.1.1 Global Forecasted Production of Gaming Monitor by Type (2023-2026)
13.1.2 Global Forecasted Revenue of Gaming Monitor by Type (2023-2026)
13.1.3 Global Forecasted Price of Gaming Monitor by Type (2023-2026)
13.2 Global Forecasted Consumption of Gaming Monitor by Application (2023-2026)
13.2.1 Global Forecasted Production of Gaming Monitor by Application (2023-2026)
13.2.2 Global Forecasted Revenue of Gaming Monitor by Application (2023-2026)
13.2.3 Global Forecasted Price of Gaming Monitor by Application (2023-2026)

14 Research Finding and Conclusion

15 Methodology and Data Source
15.1 Methodology/Research Approach
15.1.1 Research Programs/Design
15.1.2 Market Size Estimation
15.1.3 Market Breakdown and Data Triangulation
15.2 Data Source
15.2.1 Secondary Sources
15.2.2 Primary Sources
15.3 Author List
15.4 Disclaimer


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Mon, 25 Jul 2022 19:04:00 -0500 en-US text/html
Killexams : Oat Milk Market 2022 Study Reveals, Size, Share, Growth Factors, And Forecast By 2030

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

Aug 02, 2022 (Alliance News via COMTEX) -- New York (US) – Key Companies Covered in the Oat Milk Market Research are Califia Farms, LLC, Hain Celestial (Dream), Pacific Foods of Oregon, LLC. (Pacific Foods), Danone (Silk), HP HOOD LLC. (Plant Oat), Cereal Base Ceba AB (Oatly), Elmhurst Milked Direct LLC, RISE Brewing Co., Happy Planet Foods Inc., and Earths Own Food Company and other key market players.

Oat milk is a modern emergent in the plant-based beverage market, owing to its potential therapeutic benefits. Oats have gained widespread interest due to the presence of dietary fibers, phytochemicals, and high nutritive value. Oat-based products have gained traction in the latest years as a result of increased knowledge among consumers regarding the nutritional benefits of oats. In addition, rise in consumer awareness toward health has enabled to emphasize on intake of high fiber diet.

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Furthermore, plant-based beverages and other dairy alternatives have been gaining a considerable substantial consumer base. This has been driven primarily by consumers increased focus on fitness & sustainability and the availability of high-quality products. Shift toward plant-based foods & beverages has been fundamentally fueled by consumer concern regarding animal welfare, personal well-being, and the health risks associated with the consumption of meat.

In latest years, food traceability has gained momentum, wherein consumers care more about what they are eating and their source of food. In addition, consumers desire for more creativity and variety in their diets; hence, they are experimenting with new products and adding plant-based beverage combinations to their diet regime. The food industry players are responding to these consumer changes by developing a wide range of plant?based milk alternatives, including oat milk.

However, plant-based milk is not permitted to be labelled as milk in several countries and are taxed higher as compared to dairy milk. These factors can potentially hinder the growth of the oat milk market.

On the contrary, consumers in Asia-Pacific demand clear ingredients from sustainable sources and quality manufacturing processes. In addition, with growing urbanization, the demand for convenience products is on rise and hence packaged food & beverages is witnessing increased demand in the market. This can be regarded an opportunity by oat milk manufacturers for the expansion of their consumer and market base.
The global oat milk market is segmented into source, flavor, packaging form, distribution channel, and region. On the basis of source, the market is categorized into organic and conventional. By flavor, it is bifurcated into plain and flavored. Depending on packaging flavor, it is differentiated into carton and bottle. As per distribution channel, it is segregated into supermarket & hypermarket, grocery store, online retail, and others. Region wise, the market is studied across North America, Europe, Asia-Pacific, and LAMEA.

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– The report provides a quantitative analysis of the market trends, estimations, and dynamics of the market size from 2020 to 2027 to identify the prevailing opportunities.

– Porter's five forces analysis highlights the potency of buyers and suppliers to enable stakeholders to make profit-oriented business decisions and strengthen their supplier-buyer network.

– In-depth analysis and the market size and segmentation assist to determine the prevailing opportunities.

– The major countries in each region are mapped according to their revenue contribution to the market.

– The market player positioning segment facilitates benchmarking and provides a clear understanding of the present position of the market players in the oat milk industry.

– By Source
o Organic
o Conventional

– By Flavor
o Plain
o Flavored

– By Packaging Form
o Carton
o Bottle

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– By Distribution Channel
o Supermarket & Hypermarket
o Grocery Store
o Online Retail
o Others

– By Region
o North America
? U.S.
? Canada
? Mexico

o Europe
? Germany
? France
? UK
? Italy
? Sweden
? Russia
? Rest of Europe

o Asia-Pacific
? China
? India
? Japan
? Korea
? Australia
? Rest of Asia-Pacific

? Brazil
? Saudi Arabia
? South Africa
? Turkey
? Rest of LAMEA

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

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.

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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 latest 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.

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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Mon, 01 Aug 2022 19:28:00 -0500 en-US text/html
Killexams : The new HP Spectre x360 and ENVY 16 laptops are now available in Malaysia

HP Malaysia has presented its latest Spectre and ENVY laptops, which are designed with the flexibility to create and live seamlessly in today’s hybrid world.

HP Malaysia Spectre and ENVY laptops 1

The Spectre and ENVY laptops are equipped with HP Presence 4 and HP GlamCam alongside features like HP Auto Frame and HP Dynamic Voice Leveling which provide users with an interactive video and audio experience. This makes them an excellent choice for individuals who are attending conferences or online classes frequently.

HP Malaysia Spectre and ENVY laptops featured

On top of that, they also offer intelligent power management features such as In-bag detection that adjust the PC’s power to avoid overheating or battery drain when placed in a bag, as well as the Adaptive Battery Optimizer, which monitors battery temperature, battery-charging status, and usage time to preserve its battery’s health.

Check out the following lists for their specifications:

Spectre x360

Operating System
Dimensions & Weight
  • 298 x 220.45 x 16.99 mm
  • Starting from 1.37 kg
  • Intel Core i7-1255U
  • Intel Core i5-1235U
  • 13.5″ 3K2K (3000 x 2000) OLED, 100% DCI-P3, multitouch-enabled
  • 13.5″ WUXGA+ (1920 x 1280) IPS, 100% sRGB, multitouch-enabled
Storage & Memory
  • Up to 2TB PCIe Gen4 NVMe M.2 SSD
  • Up to 32GB LPDDR4x-4266 MHz RAM (onboard)
Wireless Connectivity
  • Intel Wi-Fi 6E AX211 and Bluetooth 5.2
I/O Ports
  • 2 x Thunderbolt 4 with USB4 Type-C
  • 1 x SuperSpeed USB Type-A
  • 1 x Combo Audio Jack
  • HP True Vision 5MP IR camera with camera shutter
  • Audio by Bang & Olufsen
  • Quad speakers
  • HP Audio Boost
  • 65 W USB Type-C power adapter
  • 4-cell, 66 Wh Li-ion polymer
  • Up to 15 hours Battery Life Video Playback


Operating System
Dimensions & Weight
  • 298 x 220.45 x 19.99 mm (RTX 3060 Model)
  • 357.4 x 251.8 x 18.95 mm
  • Intel Core i7-12700H
  • Intel Core i5-12500H
  • NVIDIA GeForce RTX 3060 6GB Laptop GPU
  • Intel Arc A370M Graphics
  •  16.0″ WQXGA (2560 x 1600) IPS, 120Hz, 100% sRGB
Storage & Memory
  • Up to 2TB PCIe Gen4 NVMe M.2 SSD
  • Up to 32GB DDR5-4800 MHz RAM (2 x 16GB)
Wireless Connectivity
  • Intel Wi-Fi 6E AX211 and Bluetooth 5.2 combo
  • MediaTek Wi-Fi 6 MT7921 and Bluetooth 5.2 combo
I/O Ports
  • 2 x Thunderbolt 4 with USB4 Type-C
  • 1 x SuperSpeed USB Type-A
  • 1 x Combo Audio Jack
  • 1 x AC smart pin
  • 1 x HDMI 2.1
  • HP True Vision 5MP IR camera with camera shutter
  • Audio by Bang & Olufsen
  • Quad speakers
  • HP Audio Boost
  • Up to 200 W Smart AC power adapter
  • 6-cell, 83 Wh Li-ion polymer
  • Up to 16 hours and 30 minutes Battery Life Video Playback

Pricing and Availability

The HP Spectre x360 and ENVY 16 are currently up for grabs on HP’s official website, as well as authorized sellers on Lazada and Shopee, with prices starting from RM7,199 and RM6,999 respectively with further customization options available, all catered to your needs.

There are also limited-time bundled promotions going on right now which provide shoppers with free M22f FHD Monitor, Bluetooth Headset 500, Dual Mode Mouse, etc when they purchase the laptops.

For more information, kindly refer to the following links.

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