Global Open Source Software Market Projected to Reach USD XX.XX billion by 2025- Intel, Epson, IBM, Transcend, Oracle, Acquia, etc. – WaterCloud News

The study on Global Open Source Software Market , offers deep insights about the Open Source Software market covering all the crucial aspects of the market. Moreover, the report provides historical information with future forecast over the forecast period. Some of the important aspects analyzed in the report includes market share, production, key regions, revenue rate as well as key players. This Open Source Software report also provides the readers with detailed figures at which the Open Source Software market was valued in the historical year and its expected growth in upcoming years. Besides, analysis also forecasts the CAGR at which the Open Source Software is expected to mount and major factors driving markets growth. This Open Source Software market was accounted for USD xxx million in the historical year and is estimated to reach at USD xxx million by the end of the year 2025..

This study covers following key players:IntelEpsonIBMTranscendOracleAcquiaOpenTextAlfrescoAstaroRethinkDBCanonicalClearCenterCleversafeCompiereContinuent

Request a sample of this report @ https://www.orbismarketreports.com/sample-request/80775?utm_source=Pooja

To analyze the global Open Source Software market the analysis methods used are SWOT analysis and PESTEL analysis. To identify what makes the business stand out and to take the chance to gain advantage from these findings, SWOT analysis is used by marketers. Whereas PESTEL analysis is the study concerning Economic, Technological, legal political, social, environmental matters. For the analysis of market on the terms of research strategies, these techniques are helpful.It consists of the detailed study of current market trends along with the past statistics. The past years are considered as reference to get the predicted data for the forecasted period. Various important factors such as market trends, revenue growth patterns market shares and demand and supply are included in almost all the market research report for every industry. It is very important for the vendors to provide customers with new and improved product/ services in order to gain their loyalty. The up-to-date, complete product knowledge, end users, industry growth will drive the profitability and revenue. Open Source Software report studies the current state of the market to analyze the future opportunities and risks.

Access Complete Report @ https://www.orbismarketreports.com/global-open-source-software-market-growth-analysis-by-trends-and-forecast-2019-2025?utm_source=Pooja

Market segment by Type, the product can be split into SharewareBundled SoftwareBSD(Berkeley Source Distribution)

Market segment by Application, split into BMForumphpBBPHPWind

For the study of the Open Source Software market it is very important the past statistics. The report uses past data in the prediction of future data. The keyword market has its impact all over the globe. On global level Open Source Software industry is segmented on the basis of product type, applications, and regions. It also focusses on market dynamics, Open Source Software growth drivers, developing market segments and the market growth curve is offered based on past, present and future market data. The industry plans, news, and policies are presented at a global and regional level.

Some Major TOC Points:1 Report Overview2 Global Growth Trends3 Market Share by Key Players4 Breakdown Data by Type and ApplicationContinued

For Enquiry before buying report @ https://www.orbismarketreports.com/enquiry-before-buying/80775?utm_source=Pooja

About Us : With unfailing market gauging skills, has been excelling in curating tailored business intelligence data across industry verticals. Constantly thriving to expand our skill development, our strength lies in dedicated intellectuals with dynamic problem solving intent, ever willing to mold boundaries to scale heights in market interpretation.

Contact Us : Hector CostelloSenior Manager Client Engagements4144N Central Expressway,Suite 600, Dallas,Texas 75204, U.S.A.Phone No.: USA: +1 (972)-362-8199 | IND: +91 895 659 5155

Go here to see the original:
Global Open Source Software Market Projected to Reach USD XX.XX billion by 2025- Intel, Epson, IBM, Transcend, Oracle, Acquia, etc. - WaterCloud News

Command & Conquer Remastered will come with open source code for modding – SlashGear

One of the biggest hallmarks of PC gaming and something that consoles still have difficulty allowing is modding. Sometimes, modders have to bend over backward to apply some custom changes to a game, often coming at odds with the games developers or publishers, but there are many games that support modding right of the bat. EA Games, however, is going above and beyond what most major publishers do and will even release the open source code for Command & Conquer Tiberian Sun and Red Alert when their remastered versions launch next month.

This is very big news considering how major game studios are wary of open sourcing any part of their game (despite themselves using open source software for those games). Its a tricky legal situation that lawyers simply avoid by keeping code closed but EA Games wants to do right by fans of the 25-year-old C&C franchise, especially the still vibrant modding community that has grown up around it.

Open sourcing the code for the two major versions of Command & Conquer would allow modders to take a closer look at how the game was made and modify it to their hearts content. By choosing the GPL 3 license, however, EA Games is also doing more by making sure the code will be compatible with open source projects CnCNet and Open RA. And, of course, it could also help budding game developers see how one of the most popular RTS games was made.

Unfortunately, EAs announcement also comes with some sad but not unexpected news. LAN Play, which has also been a stable of the older C&C games and its mods, is temporarily out of the picture. Thats mostly because the requirement for testing LAN Play would mean gathering together and more or less violating social distancing measures. The good news is that the feature isnt completely off the tablet yet.

The Command & Conquer Remastered Collection celebrates the franchises 25th anniversary and is slated for a June 5th launch. Covering both the Tiberian Sun and its Red Alert sequel, the collection will rebuilt graphics, support for 4K resolutions, and all the fun FMVs the games became famous for. With open source code, EA Games is expecting both old fans and new modders to keep the brand alive with new ideas that they may have never even thought of or were not legally allowed to do.

Go here to read the rest:
Command & Conquer Remastered will come with open source code for modding - SlashGear

Electronic Health Records Software Market: Know More about the Years ahead – News Distinct

The Latest research study released by HTF MI Global Electronic Health Records Software Market with 100+ pages of analysis on business Strategy taken up by key and emerging industry players and delivers know how of the current market development, landscape, technologies, drivers, opportunities, market viewpoint and status. The research study provides estimates for Global Electronic Health Records Software market Forecasted till 2025*. Some of the Major Companies covered in this Research are Drchrono, ADP AdvancedMD, Greenway, HealthFusion, IPatientCare, Kareo, PracticeFusion, Siemens Healthcare, Epic Systems, GE Healthcare, Allscripts Healthcare Solutions, Cerner, EClinicalWorks, CPSI, Amazing Charts, Sage Software Healthcare, MEDITECH, EMDs, NextGen Healthcare, Athenahealth & MaineHealth etc.

Click here for free sample + related graphs of the report @:https://www.htfmarketreport.com/sample-report/2627654-global-electronic-health-records-software-market-2

Browse market information, tables and figures extent in-depth TOC on Electronic Health Records Software Market by Application (Hospital, Clinical & Other), by Product Type (, Open Source Software & Non-open Source Software), Business scope, Manufacturing and Outlook Estimate to 2025.

Early buyers will receive 10% customization on reports.

for more information or any query mail at [emailprotected]

At last, all parts of the Global Electronic Health Records Software Market are quantitatively also subjectively valued to think about the Global just as regional market equally. This market study presents basic data and true figures about the market giving a general assessable analysis of this market based on market trends, market drivers, constraints and its future prospects. The report supplies the worldwide monetary challenge with the help of Porters Five Forces Analysis and SWOT Analysis.

If you have any Enquiry please click here @:https://www.htfmarketreport.com/enquiry-before-buy/2627654-global-electronic-health-records-software-market-2

Customization of the Report: The report can be customized as per your needs for added data up to 3 businesses or countries or 40 analyst hours.On the basis of report- titled segments and sub-segment of the market are highlighted below:Global Electronic Health Records Software Market By Application/End-User (Value and Volume from 2019 to 2025) : Hospital, Clinical & Other

Market By Type (Value and Volume from 2019 to 2025) : , Open Source Software & Non-open Source Software

Global Electronic Health Records Software Market by Key Players:Drchrono, ADP AdvancedMD, Greenway, HealthFusion, IPatientCare, Kareo, PracticeFusion, Siemens Healthcare, Epic Systems, GE Healthcare, Allscripts Healthcare Solutions, Cerner, EClinicalWorks, CPSI, Amazing Charts, Sage Software Healthcare, MEDITECH, EMDs, NextGen Healthcare, Athenahealth & MaineHealthGeographically, this report is segmented into some key Regions, with manufacture, depletion, revenue (million USD), and market share and growth rate of Electronic Health Records Software in these regions, from 2012 to 2022 (forecast), covering China, USA, Europe, Japan, Korea, India, Southeast Asia & South America and its Share (%) and CAGR for the forecasted period 2019 to 2025.

Informational Takeaways from the Market Study:The report Electronic Health Records Software matches the completely examined and evaluated data of the noticeable companies and their situation in the market considering impact of Coronavirus. The measured tools including SWOT analysis, Porters five powers analysis, and assumption return debt were utilized while separating the improvement of the key players performing in the market.

Key Developments in the Market:This segment of the Electronic Health Records Software report fuses the major developments of the market that contains confirmations, composed endeavors, R&D, new thing dispatch, joint endeavours, and relationship of driving members working in the market.

To get this report buy full copy @:https://www.htfmarketreport.com/buy-now?format=1&report=2627654

Some of the important question for stakeholders and business professional for expanding their position in the Global Electronic Health Records Software Market :Q 1. Which Region offers the most rewarding open doors for the market Ahead of 2020?Q 2. What are the business threats and Impact of COVID scenario Over the market Growth and Estimation?Q 3. What are probably the most encouraging, high-development scenarios for Electronic Health Records Software movement showcase by applications, types and regions?Q 4.What segments grab most noteworthy attention in Electronic Health Records Software Market in 2019 and beyond?Q 5. Who are the significant players confronting and developing in Electronic Health Records Software Market?

For More Information Read Table of Content @:https://www.htfmarketreport.com/reports/2627654-global-electronic-health-records-software-market-2

Key poles of the TOC:Chapter 1 Global Electronic Health Records Software Market Business OverviewChapter 2 Major Breakdown by Type [, Open Source Software & Non-open Source Software]Chapter 3 Major Application Wise Breakdown (Revenue & Volume)Chapter 4 Manufacture Market BreakdownChapter 5 Sales & Estimates Market StudyChapter 6 Key Manufacturers Production and Sales Market Comparison Breakdown..Chapter 8 Manufacturers, Deals and Closings Market Evaluation & AggressivenessChapter 9 Key Companies Breakdown by Overall Market Size & Revenue by Type..Chapter 11 Business / Industry Chain (Value & Supply Chain Analysis)Chapter 12 Conclusions & Appendix

Thanks for reading this article; you can also get individual chapter wise section or region wise report version like North America, Europe or Asia.

About Author:HTF Market Report is a wholly owned brand of HTF market Intelligence Consulting Private Limited. HTF Market Report global research and market intelligence consulting organization is uniquely positioned to not only identify growth opportunities but to also empower and inspire you to create visionary growth strategies for futures, enabled by our extraordinary depth and breadth of thought leadership, research, tools, events and experience that assist you for making goals into a reality. Our understanding of the interplay between industry convergence, Mega Trends, technologies and market trends provides our clients with new business models and expansion opportunities. We are focused on identifying the Accurate Forecast in every industry we cover so our clients can reap the benefits of being early market entrants and can accomplish their Goals & Objectives.

Contact US :Craig Francis (PR & Marketing Manager)HTF Market Intelligence Consulting Private LimitedUnit No. 429, Parsonage Road Edison, NJNew Jersey USA 08837Phone: +1 (206) 317 1218[emailprotected]

Connect with us atLinkedIn|Facebook|Twitter

Originally posted here:
Electronic Health Records Software Market: Know More about the Years ahead - News Distinct

Future Trends of Global Business Analytics and Enterprise Software Market to Access Global Industry Players like SAP, IBM, Oracle – Cole of Duty

Business analytics software is a software that is designed to analyze business data to better understand an organizations strengths and weaknesses. Enterprise Software is a software used to satisfy the needs of an organization rather than individual users. Such organizations include businesses, schools, interest-based user groups, clubs, charities, and governments. Over the past five years there has been an increasing prevalence of low-cost open source alternatives. Open source has become a preferred platform for developing new technology. In the past, software product companies would open source software that was not making money, but now companies are open sourcing software to increase its presence and share in the market. The global Business Analytics and Enterprise Software Market is forecasted to reach USD +186 Billion by 2027 valued growing at a CAGR of +10% between 2020-2027.

Request a Sample Business Analytics and Enterprise Software Market Research Report at @ https://www.marketresearchinc.com/request-sample.php?id=26357

For augmenting readability, Market Research Inc has added a fresh market study, titled Business Analytics and Enterprise SoftwareMarket to its flared database. The report has been put together in a chapter-wise arrangement, by separating required illustrations transversely. This report is an expedient tool to get responses to some of the queries that hold significance for the growth of the Business Analytics and Enterprise Software market during the forecast period. The evidence in the report was congregated from qualified organizations & dependable sources and was further authenticated by industry specialists for increased integrity.

Market Segment by Regions, regional analysis covers

For competitor segment, the report includes global key players of Business Analytics and Enterprise Software are:

Business analytics refers to the skills, technologies, practices for continuous iterative exploration, and investigation of past business performance to gain insight and drive business planning. Business analytics software is being used by companies for query reporting and analysis tools, advanced and predictiveanalytics,location intelligence, content analytics, data warehousing platform, and enterprise performancemanagement.

The information for each competitor includes:

The objective of the Report:

Get Up To 40% Discount on this Premium Report

https://www.marketresearchinc.com/ask-for-discount.php?id=26357

Market segment by Type, the product can be split into

Market segment by Application, split into

What is covered in the report?

Why buy?

Ask Your Queries or Requirements:

https://www.marketresearchinc.com/enquiry-before-buying.php?id=26357

Table of Content:

Business Analytics and Enterprise Software Market Research Report 2019-2025

Chapter 1: Industry Overview

Chapter 2: Business Analytics and Enterprise Software Market International and Market Analysis

Chapter 3: Environment Analysis of Business Analytics and Enterprise Software

Chapter 4: Analysis of Revenue by Classifications

Chapter 5: Analysis of Business Analytics and Enterprise Software Market Revenue Market Status

Chapter 6: Analysis of Revenue by Regions and Applications

Chapter 7: Analysis of Business Analytics and Enterprise Software Market Key Manufacturers

Chapter 8: Sales Price and Gross Margin Analysis

Chapter 9: Continue To TOC

The Market Research Inc studies the Business Analytics and Enterprise Software market status and outlook of Global and major regions, from angles of players, countries, product types and end industries; this report analyzes the top players in global market, and splits the Business Analytics and Enterprise Software market by product type and applications/end industries.

Any special requirements about this report, please let us know and we can provide custom report.

About Us:

Market Research Inc is farsighted in its view and covers massive ground in global research. Local or global, we keep a close check on both markets. Trends and concurrent assessments sometimes overlap and influence the other. When we say market intelligence, we mean a deep and well-informed insight into your products, market, marketing, competitors, and customers. Market research companies are leading the way in nurturing global thought leadership. We help your product/service become the best they can with our informed approach.

Studying consumer behavior, changing preference patterns and events that impact different courses and flow of businesses and their corresponding markets, is our forte. Once we join hands with you, what you do, will be guided by our expertise, every step of the way.

Contact Us:

Market Research Inc.

Kevin

51 Yerba Buena Lane,

Ground Suite, Inner Sunset San Francisco,

CA 94103, USA.

+1(628) 225-1818

Write [emailprotected] [emailprotected]

See the original post:
Future Trends of Global Business Analytics and Enterprise Software Market to Access Global Industry Players like SAP, IBM, Oracle - Cole of Duty

EdgeX Foundry Hits Major Milestone with 5 Million+ Container Downloads and a New Release that Simplifies Deployment for AI, Data Analytics and Digital…

SAN FRANCISCO, May 21, 2020 /PRNewswire/ --EdgeX Foundry, a project under theLF Edge umbrella organization within theLinux Foundation that aims to establish an open, interoperable framework for IoT edge computing independent of connectivity protocol, hardware, operating system, applications or cloud, today announced a major milestone of hitting 5 million container downloads and the availability of its "Geneva" release. This release offers more robust security, optimized analytics, and secure connectivity for multiple devices.

"EdgeX Foundry is committed to developing an open IoT platform for edge-related applications and shows no signs of slowing down the momentum," said Arpit Joshipura, general manager, Networking, Edge and IoT, the Linux Foundation. "As one of the Stage 3 projects under LF Edge, EdgeX Foundry is a clear example of how member collaboration and diversity are the keys to creating an interoperable open source framework across IoT, Enterprise, Cloud and Telco Edge."

Launched in April 2017, and now part of the LF Edge umbrella, EdgeX Foundry is an open source, loosely-coupled microservices framework that provides the choice to plug and play from a growing ecosystem of available third-party offerings or to augment proprietary innovations. With a focus on the IoT Edge, EdgeX simplifies the process to design, develop and deploy solutions across industrial, enterprise, and consumer applications.

Currently, there are more than 170 unique contributors to the project and EdgeX Foundry averages one million container downloads a month, with a total of 5 million reached last month, and rising.

"The massive volume of devices coming online represents a huge opportunity for innovation and is making edge computing a necessity," said Keith Steele, EdgeX Foundry Chair of the Technical Steering Committee. "With at least 50% of data being stored, processed and analyzed at the edge we need an open, cloud-native edge ecosystem enabled by EdgeX to minimize reinvention and facilitate building and deploying distributed, interoperable applications from the edge to the cloud. In 3 short years, EdgeX has achieved incredible global momentum and is now being designed into IOT systems and product roadmaps."

The Geneva Release

As the sixth release in the EdgeX Foundry roadmap, Geneva offers simplified deployment, optimized analytics, secure connectivity for multiple devices and more robust security. Key features include:

EdgeX Foundry works closely with several of the other LF Edge projects such as Akraino Edge Stack and new project Open Horizon. During this release cycle, EdgeX was made to work under the Akraino Edge Lightweight IOT (ELIOT) Blueprint and tested under the Akraino Community Lab.

Launched last month, Open Horizonis a platform for managing the service software lifecycle of containerized workloads and related machine learning assets. Open Horizon is building an integration project that will demonstrate delivery and management of EdgeX Foundry as a containerized solution in stages, beginning with a single deployable unit and then progressing to a more modular set of services and alternate delivery targets.

Support from Contributing Members and Users of EdgeX Foundry:

"To further enhance use in production environments, EdgeX Foundry's Geneva release brings simplified deployments and improved security," said Tony Espy, Technical Architect at Canonical. "With EdgeX available as a snap, this aligns to the fundamentals of snaps' core principles which allow developers to benefit from confinement and transactional updates to ensure deployments are secure and with minimal need for manual intervention. As the EdgeX ecosystem continues to see strong traction, we look forward to continuing our contribution to building an open, interoperable framework for edge computing."

"EdgeX Foundry's middleware solution is an important component of an open, vendor-neutral pipeline connecting IoT devices and their data to analytics and data management at the on-premise edge," said Joe Pearson, Engineering Strategy & Innovation Leader, Edge Computing, IBM. "This latest release underscores the importance of working within LF Edge to encourage interoperability as we build a comprehensive open edge computing framework, beginning with Open Horizon."

"With the evolution of IoT and edge computing, there is a growing realization to deploy and run compute engines near the data source in a truly globally distributed manner. This architecture requires running intelligent AI-based functionality at the edge while processing a significant amount of data at high-throughput and low latency on small form-factor devices," said Yiftach Shoolman, CTO and co-founder at Redis Labs. "EdgeX Foundry with Redis as the primary data store provides an open-source data platform to meet these expectations by combining in-memory data processing with modern data-models, and can be extended with a serverless engine and AI-serving platform."

Additional resources:

For more information about LF Edge and its projects, visithttps://www.lfedge.org/

About the Linux FoundationFounded in 2000, the Linux Foundation is supported by more than 1,000 members and is the world's leading home for collaboration on open source software, open standards, open data, and open hardware. Linux Foundation's projects are critical to the world's infrastructure including Linux, Kubernetes, Node.js, and more. The Linux Foundation's methodology focuses on leveraging best practices and addressing the needs of contributors, users and solution providers to create sustainable models for open collaboration. For more information, please visit us atlinuxfoundation.org.

The Linux Foundation has registered trademarks and uses trademarks. For a list of trademarks of The Linux Foundation, please see our trademark usage page:https://www.linuxfoundation.org/trademark-usage. Linux is a registered trademark of Linus Torvalds.

Media Contact: Maemalynn MeanorThe Linux Foundation [emailprotected]

SOURCE EdgeX Foundry

http://www.linuxfoundation.org

Read more here:
EdgeX Foundry Hits Major Milestone with 5 Million+ Container Downloads and a New Release that Simplifies Deployment for AI, Data Analytics and Digital...

IDC Introduces an Interoperable Framework for Artificial Intelligence (AI) Infrastructure Stacks and Assesses the AI Infrastructure Stacks Currently…

FRAMINGHAM, Mass.--(BUSINESS WIRE)--Two new reports from International Data Corporation (IDC) offer a first look at infrastructure stacks for Artificial Intelligence (AI) applications. In the reports, IDC defines an interoperable framework for infrastructure stacks to deploy AI applications, referred to as the AI Plane (AIP). The reports also discuss vendor-specific implementations of AI infrastructure stacks that are currently available in the market.

As building AI capabilities becomes increasingly urgent, IDC sees that businesses are confused about the process of building their own AI infrastructure stack. IDC is seeing a growing number of AI server, storage, and processor vendors develop AI stacks that consist of abstraction layers, orchestration layers, AI development layers, and data science layers that are intended to seamlessly operate together. These stacks typically combine open source software, proprietary software, and nonmonetized commercial software (such as CUDA) layers that are intended to help customers' IT infrastructure teams, developers, and data scientists collaborate on a predesigned stack without having to build it themselves.

IDC believes that AI infrastructure stacks provide a clear advantage to customers and that their variety is, while confusing, not a disadvantage. IDC does not expect vendors to collaboratively develop a "standard" AI infrastructure stack this would defeat the advantage for customers of having multiple flavors to choose from. By offering an AIP framework, IDC hopes to provide a guide for IT vendors, encouraging them to improve the versatility of their stack, thereby increasing its ubiquitous adoption.

"Businesses are benefiting tremendously from the AI infrastructure software stacks that server, processor, and co-processor vendors are making available, several of which we are highlighting in these reports," said Peter Rutten, research director, Infrastructure Systems, Platforms and Technologies at IDC. "But buyers should be aware of complexity and a lack of interoperability with these stacks."

"Infrastructure requirements for AI workloads can be viewed as a function of scale, portability, and time," said Sriram Subramanian, research director, Infrastructure Systems, Platforms and Technologies at IDC. "With so many choices and options available, end users are often perplexed about the right infrastructure stack. AIP provides a simple framework to select the right infrastructure stack, with accommodations to considerations on cost, flexibility, and infrastructure utilization."

IDC recommends technology buyers to thoroughly investigate the entire AI stack that server vendors offer and to explore options beyond their regular hardware supplier. IT benefits to keep in mind when examining reference stacks include reduced costs, data and application availability, effective infrastructure consolidation and, where possible, a single interoperable application delivery platform. IDC also recommends technology vendors to focus on interoperability among AI infrastructure stacks.

The IDC report, The "AI Plane": An Interoperable Framework for Artificial Intelligence Infrastructure Stacks (IDC #US46283420), introduces AI Plane (AIP)an interoperable framework to select the right infrastructure stack to power AI workloads. The report also introduces two specific implementations of AIP: Open AI Plane and as-a-Service AI Plane. IDC recommends that enterprises leverage the AIP framework when selecting an appropriate infrastructure stack to power AI workloads.

The IDC report, AI Infrastructure Stack Review H1 2020: The Rapid and Varied Rise of the AI Stack (IDC #US46291620), assesses some of the AI infrastructure stacks that are currently available on the market, including the stacks offered by Intel, AMD, NVIDIA, Cisco, Huawei, and HPE.

About IDCInternational Data Corporation (IDC) is the premier global provider of market intelligence, advisory services, and events for the information technology, telecommunications, and consumer technology markets. With more than 1,100 analysts worldwide, IDC offers global, regional, and local expertise on technology and industry opportunities and trends in over 110 countries. IDC's analysis and insight helps IT professionals, business executives, and the investment community to make fact-based technology decisions and to achieve their key business objectives. Founded in 1964, IDC is a wholly-owned subsidiary of International Data Group (IDG), the world's leading tech media, data and marketing services company. To learn more about IDC, please visit http://www.idc.com. Follow IDC on Twitter at @IDC and LinkedIn. Subscribe to the IDC Blog for industry news and insights: http://bit.ly/IDCBlog_Subscribe.

Excerpt from:
IDC Introduces an Interoperable Framework for Artificial Intelligence (AI) Infrastructure Stacks and Assesses the AI Infrastructure Stacks Currently...

Small vendors that stand out in network automation – TechTarget

Incumbent vendors are typically behind in providing cutting-edge features in network management tools. So, enterprises looking for advanced analytics and network automation will more likely find them in small vendors' products.

More advanced tools are critical to enterprises switching to software-based network management in the data center from a traditional hardware-centric model. Driving the shift are initiatives to move workloads to the cloud and digitize more internal and external operations.

In a study released this month, almost half of the 350 IT professionals surveyed by Enterprise Management Associates said they wanted advanced analytics for anomaly detection and traffic optimization.

Small vendors are addressing the demand by incorporating machine learning in network monitoring tools that search for potential problems. Examples of those vendors include Kentik and Moogsoft.

Besides more comprehensive analytics, enterprises want software that automatically configures, provisions and tests network devices. Those network automation features are vital to improving efficiency and reducing human error and operating expenses.

Gartner recently named three small vendors at the forefront of network automation: BeyondEdge, Intentionet and NetYCE.

Moogsoft is using machine learning to reduce the number of events its network monitoring software flags to engineers. Moogsoft does that by identifying and then hiding multiple activities related to the same problem.

"It really helps streamline" network operations, said Terry Slattery, a network consultant at IT adviser NetCraftsmen.

Kentik, on the other hand, uses machine learning to correlate network traffic flow data generated by switches and routers that support the NetFlow protocol, Slattery said. The process can identify sources of malware or other potential security threats.

Moogsoft and Kentik use machine learning to improve specific features in their products. Vendors have yet to deploy it in broader network operations, which would likely require significant changes in network infrastructure.

Today, companies prefer to work on provisioning, monitoring and making hardware changes on a large scale. After that, they might start adding "smarts" to the network, said Jason Edelman, founder and CTO of consultancy Network to Code.

Gartner also named Network to Code as a small vendor that enterprises should consider. The consultancy's client base includes 30 of the Fortune 500. The company specializes in the use of open source software for managing networks with a variety of vendor devices.

Among Gartner's other small vendors, BeyondEdge was the only one focused on the campus network, where it competes with behemoths like Cisco and Hewlett Packard Enterprise's Aruba.

BeyondEdge has developed overlay software for Ethernet switching fabrics and passive optical networks. The software lets enterprises create configurations based on business and application policies and then applies them at devices' access points. BeyondEdge sells its vendor-agnostic technology through consumption-based pricing.

BeyondEdge is best suited for organizations that need to provision many ports for different classes of users, Gartner said. Those types of organizations are found in commercial real estate, hospitality, higher education and healthcare.

Intentionet and NetYCE provide tools for data center networks. The former has developed open source-based software that mathematically validates network configurations before deploying them. "This is a new capability in the market and can simultaneously enhance uptime and agility," Gartner said.

NetYCE stands out for developing a straightforward UI that simplifies network configuration change management, network automation and orchestration capabilities, Gartner said.

"It provides a simple way for networking personnel -- who may be novices in automation -- to get up to speed quickly," the analyst firm said.

NetYCE's technology supports hardware from the largest established vendors. The company claims to provide adapters to nonsupported gear within two weeks, Gartner said.

Here is the original post:
Small vendors that stand out in network automation - TechTarget

Google has found a way for machine learning algorithms to evolve themselves – Tech Wire Asia

Machine learning is a subset of artificial intelligence (AI) that gives computer systems the ability to automatically learn and improve from experience, rather than being explicitly programmed its now a hugely powerful tool that has been leveraged across a raft of completely different industries for several years already.

Machine learning is now used by banks to sift through hundreds of millions of transactions to detect fraud; its predictive analytics ability has been used in agriculture to comb through seasonal farming and weather data; machine learning will even help digital marketers to plan budget forecasts and research content trends. And those are just three examples of millions now used each days.

The basic premise of machine learning, in theory, is simple. An algorithm is fed a dataset, and is taught to respond in certain way the next time it encounters similar data.

But in practice, its very difficult, and thats why theres such demand for specialists like data scientists. Creating a machine learning algorithm requires numerous steps from gathering and preparing data, setting evaluation protocols and developing benchmark models, before there is anything near a workable machine learning algorithm ready for deployment.

Even then, they may not work well enough, and that means going back to the drawing board. Machine learning requires an extensive list of skills including computer science andprogramming, mathematics and statistics, data science, deep learning, and problem solving.

In short, machine learning is out of reach for many, and yet the rapid boom and endless applications emerging mean more and more businesses now want to get hands-on, whether thats to improve products and services for customers, or to make internal processes more efficient.

That surge of interest has led many to consider off-the-shelf machine learning solutions, and that was how automated machine learning came to be to make ML accessible to non-ML experts.

Automated machine learning, or AutoML, reduces or completely removes the need for skilled data scientists to build machine learning models. Instead, these systems allow users to provide training data as an input, and receive a machine learning model as an output.

AutoML software companies may take a few different approaches. One approach is to take the data and train every kind of model, picking the one that works best. Another is to build one or more models that combine the others, which sometimes give better results.

Despite its name, AutoML has so far relied a lot on human input to code instructions and programs that tell a computer what to do. Users then still have to code and tune algorithms to serve as building blocks for the machine to get started. There are pre-made algorithms that beginners can use, but its not quite automatic.

But now a team of Google computer scientists believe they have come up with a new AutoML method that can generate the best possible algorithm for a specific function, without human intervention.

The new method is dubbed AutoML-Zero, which works by continuously trying algorithms against different tasks, and improving upon them using a process of elimination, much like Darwinian evolution.

AutoML-Zero greatly reduces the human element which had heavily influenced ML programs before, with more complex programs requiring sophisticated code written by hand. Limiting human involvement also helps remove bias and potential errors, especially when multiple iterative developments are involved.

Esteban Real, a software engineer at Google Brain, Research and Machine Intelligence, and lead author of the research, explained to Popular Mechanics: Suppose your goal is to put together a house. If you had at your disposal pre-built bedrooms, kitchens, and bathrooms, your task would be manageable but you are also limited to the rooms you have in your inventory.

If instead you were to start out with bricks and mortar, then your job is harder, but you have more space for creativity.

Instead, Googles AutoML-Zero uses basic mathematics, much like other computer programming languages. AutoML-Zero appears to involv even less human intervention than Googles own ML programming language, Cloud AutoML.

In a basic sense, Google developers have created a system which is able to churn out 100 randomly-generated algorithms and then identify which one works best. After several generations, the algorithms become better and better until the machine finds one that performs well enough to evolve.

New ground can be made here as those surviving algorithms can be tested against standard AI problems for their ability to solve new ones.

The development team is working to eliminate any remaining human bias their method retains, as well as to solve a tricky scaling issue. If they are successful, Google might be able to introduce a full-scale version that provides machine learning capabilities to small-medium enterprises (SMEs) and non-ML developers.

And crucially, those machine learning applications will be free from human input.

Joe Devanesan | @thecrystalcrown

Joe's interest in tech began when, as a child, he first saw footage of the Apollo space missions. He still holds out hope to either see the first man on the moon, or Jetsons-style flying cars in his lifetime.

Read more from the original source:
Google has found a way for machine learning algorithms to evolve themselves - Tech Wire Asia

How machine learning can bridge the communication gap – ComputerWeekly.com

In October 2019, an Amazon employee in Melbourne, Australia bumped into another person while cycling on the road. As she was assuring that person that she would help, she realised that he was deaf and mute and had no clue on what she was saying.

The awkward situation could have been avoided if assistive technology was on hand to facilitate communication between the two parties. Following the incident, a team led by Santanu Dutt, head of technology for Southeast Asia at Amazon Web Services, got down to work.

Within ten days or so, Dutts team built a machine learning model that was trained on sign languages. Using images of a person gesturing in sign language that were captured from a camera, the model could recognise and translate gestures into text. The model also could convert spoken words into text for a deaf-mute person to see.

Dutt said the model can also be customised to translate speech into sign languages as the machine learning services and application programming interfaces (APIs) are available and open though he has not seen that demand yet. But once you write a small bit of code, training the machine learning model is easy, he said.

There is still more work to be done. As the training was performed with signs gestured against a white background, the efficacy of the model in its current form would be limited in actual use.

Our team had limited time to showcase this and we wanted to bump up something to showcase for experimental purposes, Dutt said, adding that organisations can use tools such as Amazon SageMaker to edit and train the model with more images and videos to recognise a larger variety of environments.

As the training process is intensive, Dutt said organisations with limited resources can use Amazon SageMaker Ground Truth to build training datasets for such machine learning models quickly. Besides automatic labelling, Ground Truth also provides access to human labellers through the Amazon Mechanical Turk crowdsourcing service.

This will also help to improve the models accuracy rate. The more data you have, the more accurate the model gets, Dutt said, adding that developers can set confidence levels and reject results that fall below a certain level of accuracy.

Dutt said AWSs public sector team has engaged non-profit organisations in Australia to conduct a proof-of-concept that makes use of the machine learning model, as well as those in other countries through credits that offset the cost of using AWS services to train and deploy the model.

Read the original post:
How machine learning can bridge the communication gap - ComputerWeekly.com

From streaming hive data to acoustics, SAS uses machine learning, analytics to boost bee populations – WRAL Tech Wire

CARY SAS wants to help save the worlds No.1 food crop pollinator the honey bee. And its doing so right in the Triangles backyard.

To coincide with World Bee Day, the Cary-base software analytics firm today confirmed it is working on three separate projectswhere technology is monitoring, tracking and improving pollinator populations around the globe.

They include observing real-time conditions of beehives using an acoustic streaming system; working with Appalachian State University on the World Bee Count to visualize world bee population data; and decoding bee communication to maximize their food access.

By applying advanced analytics and artificial intelligence to beehive health, we have a better shot as a society to secure this critically important part of our ecosystem and, ultimately, our food supply, said Oliver Schabenberger, COO and CTO of SAS, in a statement.

Researchers from the SAS IoT Division are developing a bioacoustic monitoring system to non-invasively track real-time conditions of beehives using digital signal processing tools and machine learning algorithms available in SASEvent Stream Processingand SAS Viya software.

By connecting sensors to SAS four Bee Downtown hives at its headquarters in Cary, NC, the team startedstreaming hive datadirectly to the cloud to continuously measure data points in and around the hive, including weight, temperature, humidity, flight activity and acoustics. In-stream machine learning models were used to listen to the hive sounds, which can indicate health, stress levels, swarming activities and the status of the queen bee.

To ensure only the hum of the hive was being used to determine bees health and happiness, researchers used robust principal component analysis (RPCA), a machine learning technique, to separate extraneous or irrelevant noises from the inventory of sounds collected by hive microphones.

The researchers found that with RPCA capabilities, they could detect worker bees piping at the same frequency range at which a virgin queen pipes after a swarm, likely to assess whether a queen was present. The researchers then designed an automated pipeline to detect either queen piping following a swarm or worker piping that occurs when the colony is queenless.

SAS said the acoustic analysis can alert beekeepers to queen disappearances immediately, which is vitally important to significantly reducing colony loss rates. Its estimated the annual loss rates of US beehives exceed 40 percent and between 25-40 percent of these losses are due to queen failure.

With this system, SAS said beekeepers will have a deeper understanding of their hives without having to conduct time-consuming and disruptive manual inspections.

As a beekeeper myself, I know the magnitude of bees impact on our ecosystem, and Im inspired to find innovative ways to raise healthier bees to benefit us all, said Anya McGuirk, Distinguished Research Statistician Developer in the IoT division at SAS.

The researchers said they plan to implement the acoustic streaming system very soon and are continuing to look for ways to broaden the usage of technology to help honey bees and ultimately humankind.

SAS is also launching a data visualization that maps out bees counted around the globe for theWorld Bee Count, an initiative co-founded by theCenter for Analytics Research and Education(CARE) at Appalachian State University.

The goal: to engage citizens across the world to take pictures of bees as a first step toward understanding the reasons for their alarming decline, SAS says.

The World Bee Count allows us to crowdsource bee data to both visualize our planets bee population and create one of the largest, most informative data sets about bees to date, said Joseph Cazier, Professor and Executive Director at Appalachian State Universitys CARE, in a statement.

In early May, the World Bee Count app was launched for users both beekeepers and the general public, aka citizen data scientists to add data points to the Global Pollinator Map. Within the app, beekeepers can enter the number of hives they have, and any user can submit pictures of pollinators from their camera roll or through the in-app camera. Through SAS Visual Analytics, SAS has created avisualization mapto display the images users submit via the app which, it says, could potentially provide insights about the conditions that lead to the healthiest bee populations.

In future stages of this project, SAS said, the robust data set created from the app could help groups like universities and research institutes better strategize ways to save these vital creatures.

Representing the Nordic region, a team from Amesto NextBridge won the 2020 SAS EMEA Hackathon, which challenged participants to improve sustainability using SAS Viya. Their winning project used machine learning to maximize bees access to food, which would in turn benefit mankinds food supply.

In partnership withBeefutures, the team developed a system capable of automatically detecting, decoding and mapping bee waggle dances using Beefutures observation hives and SAS Viya.

Observing all of these dances manually is virtually impossible, but by using video footage from inside the hives and training machine learning algorithms to decode the dance, we will be able to better understand where bees are finding food, said Kjetil Kalager, lead of the Amesto NextBridge and Beefutures team. We implemented this information, along with hive coordinates, sun angle, time of day and agriculture around the hives into an interactive map in SAS Viya and then beekeepers can easily decode this hive information and relocate to better suited environments if necessary.

SAS said this systematic real-time monitoring of waggle dances allows bees to act as sensors for their ecosystems. It may also uncover other information bees communicate through dance that could help us save and protect their population.

Read more here:
From streaming hive data to acoustics, SAS uses machine learning, analytics to boost bee populations - WRAL Tech Wire