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Machine Learning Market | Demand, Size, Share, Trends, Opportunities, Challenges, Risks Factors Analysis & Competitive Situation | Douglas Insights

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Isle of Man, Nov. 02, 2022 (GLOBE NEWSWIRE) — The machine learning market‘s prospects, trends, driving forces, expectations, and restraints are now included in Douglas Insights, one of the first comparison engines in the world. Organisations, industry experts, market analysts, and researchers can use the comprehensive study offered by Douglas Insights to access a thorough analysis of data, market intelligence, and research reports. The study is highly beneficial for both data analysts and market researchers because it provides a selection of both public and private assessments on the criteria of publisher rating, table of contents, date of publication, and price. 

Machine learning is a form of analysis of data that incorporates statistical research methods to provide desired predictive outputs Without the need for human input. In order to achieve the intended outcome, it employs a series of algorithms to understand the connection between datasets. 

Decreasing both time and workload is the responsibility of machine learning. By automation, the algorithm completes the challenging task. Standard solutions are unable to process and assess the data as ML can. Data is the most important element in each and every model for machine learning. These elements are fueling market expansion.

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Robots are now better capable of contributing to applications like automated driving and drones because of developments in machine learning. The market has grown as a result of the expanding need for innovative automated devices in a variety of sectors.

Due to advancements in network connectivity systems, the demand for sensing devices, connected machinery, and equipment in the industry is anticipated to increase dramatically.

Due to the expanding implementation of technology improvements across a variety of industries, including healthcare, manufacturing, retail, and automotive, the worldwide machine learning market is anticipated to grow throughout the projected time frame. The market is forecasted to be driven by the growing prevalence of ML and AI technologies. Deep learning is the branch of artificial intelligence that is predicted to dominate the marketplace in the years to come, given its growing capacity for learning and implementing innovation. 

The COVID-19 outbreak had a favourable influence on the market as a result of the rising need for data analysis techniques across a variety of industries, including automotive, retail, and healthcare. Due to expanding activities in the medical business, it is also anticipated that there will be an increase in demand for such technologies in the healthcare industry. The software for data analysis was extensively utilised to track data and keep tabs on the COVID-19 virus’s prevalence in various nations. Due to these elements, the market has grown throughout the pandemic.

Due to the rising need for automated information analysis solutions, the market for machine learning is predicted to expand significantly throughout the projected time frame. Additionally, the healthcare industry has a strong demand for these solutions, which is expected to fuel the market and boost growth. Furthermore, it is anticipated that the rate at which the market generates revenue will expand as a result of technological advancement and rising investments in new technologies in emerging economies. These elements are most likely to guarantee the machine learning (ML) market during the anticipated time frame. However, technical constraints and a low level of precision can impede market expansion. 

By integrating machine learning within business operations, most companies face significant challenges due to a lack of competent personnel with analytical skills. The need for individuals who can analyse statistics is even higher. 

The selection of algorithms in machine learning remains a manual procedure. We need to execute and verify each one of the algorithms on the dataset. Only then can one decide which algorithm to utilise. 

The biggest problem appears when testing and training actual data. The size of the information may make it challenging to eliminate errors. Robotic process automation procedures that leverage artificial intelligence are susceptible to fraud and unintentional usage, which could stunt business expansion. 

During the projected period, North America will dominate the worldwide machine learning (ML) share of the market. The market is anticipated to grow as a result of the continent’s significant R&D industry. 

In the future years, Europe is anticipated to have rapid expansion due to the growing skilled labour force. Growth will be fuelled by rising demand for AI in the applications and commodities industries.

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Machine Learning Market Report Coverage

Report Attributes Details
Market Size in 2021  $XX Mn
Market Size Projection in 2028  $XX Mn
CAGR (2021-2028) XX %
Largest Market North America
Growth Drivers Rising need for automated information analysis solutions, Strong demand in healthcare industry, Technological advancement and rising investments in new technologies
Segmentation By Type (Supervised Learning, Unsupervised Learning, Semi-supervised Learning, Reinforcement Learning) by Solution (Software, Software Platform Components, Services, Integration and Deployment, Training and Consulting, Support and Maintenance) by Organization Size (Large Enterprises, Benefits for Large Enterprises, Small and Medium Enterprises (SMEs)) by Deployment Mode (On-premises, Cloud) by End Use (Banking, Financial Services and Insurance (BFSI), Machine-Learning Applications, Healthcare and Life Sciences, Machine-Learning Applications, Retail, Machine-Learning Applications, IT and Telecommunication, Machine-Learning Applications, Government and Defense, Machine-Learning Applications, Manufacturing, Machine-Learning Applications, Energy and Utilities, Machine-Learning Applications, Others)
Regional Analysis North America (US, Canada), Latin America (Brazil, Mexico, Argentina, Rest of Latin America), Europe (U.K, Germany, Italy, France, Spain, Russia and Rest of Europe), APAC (China, Japan, India, South Korea, Australia, ASEAN and Rest of Asia Pacific), ME (GCC Countries, Israel, and Rest of Middle East) & Africa (South Africa, North Africa and Central Africa)
Key Companies Covered ALPHABET INC. (GOOGLE INC.), ALTERYX, AMAZON.COM INC., ANACONDA, BAIDU INC., BIGML INC., FAIR ISAAC CORP. (FICO), HEWLETT PACKARD ENTERPRISE (HPE), H20.AI, IBM, INTEL CORP., KNIME, MATHWORKS, MICROSOFT, ORACLE CORP., RAPIDMINER, SAS INC., SAP SE, SALESFORCE.COM.

Segmentations

By Type of Machine Learning

  • Introduction
  • Supervised Learning
  • Unsupervised Learning
  • Semi-supervised Learning
  • Reinforcement Learning

By Solution

  • Introduction
  • Software
  • Software Platform Components
  • Services
  • Integration and Deployment
  • Training and Consulting
  • Support and Maintenance

By Organization Size

  • Introduction
  • Large Enterprises
  • Benefits for Large Enterprises
  • Small and Medium Enterprises (SMEs)

By Deployment Mode

  • Introduction
  • On-premises
  • Cloud

By End Use

  • Introduction
  • Banking, Financial Services and Insurance (BFSI)
  • Machine-Learning Applications
  • Healthcare and Life Sciences
  • Machine-Learning Applications
  • Retail
  • Machine-Learning Applications
  • IT and Telecommunication
  • Machine-Learning Applications
  • Government and Defense
  • Machine-Learning Applications
  • Manufacturing
  • Machine-Learning Applications
  • Energy and Utilities
  • Machine-Learning Applications
  • Others

Key questions answered in this report

  • COVID 19 impact analysis on global Machine Learning industry.
  • What are the current market trends and dynamics in the Machine Learning market and valuable opportunities for emerging players?
  • What is driving Machine Learning market?
  • What are the key challenges to market growth?
  • Which segment accounts for the fastest CAGR during the forecast period?
  • Which product type segment holds a larger mark et share and why?
  • Are low and middle-income economies investing in the Machine Learning market?
  • Key growth pockets on the basis of regions, types, applications, and end-users
  • What is the market trend and dynamics in emerging markets such as Asia Pacific, Latin America, and Middle East & Africa?

Unique data points of this report

  • Statistics on Machine Learning and spending worldwide
  • Recent trends across different regions in terms of adoption of Machine Learning across industries
  • Notable developments going on in the industry
  • Attractive investment proposition for segments as well as geography
  • Comparative scenario for all the segments for years 2018 (actual) and 2028 (forecast)

Compare the report and make your decision – https://douglasinsights.com/machine-learning-market

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About Douglas Insights-

Douglas Insights UK limited is the first company to provide comparison of market research reports by Table of content, price, ratings and number of pages. We understand the value of time. Productivity and efficiency are possible when you take prompt and assured decisions. With our advanced algorithm, filters, and comparison engine, you can compare your preferred reports simultaneously, based on publisher rating, published date, price, and list of tables. Our data portal enables you to find and review the reports from several publishers. You can evaluate numerous reports on the same screen and select the sample for your best match.

Similar Market Research Report Comparisons:

Life Sciences Machine Learning Market: Key machine learning in life sciences technologies and products are analyzed to determine present and future market status, and growth is forecast from 2022 to 2027. An in-depth discussion of strategic alliances, industry structures, competitive dynamics, patents and market driving forces is also provided. 

Machine Learning As A Service Market: The machine learning as a service market worldwide is estimated to grow with a CAGR of 35.4% throughout the forecast period from 2019 to 2027, starting from US$ 1,117.9 Mn in 2018. 

Education And Learning Analytics Market: Education and learning analytics is a measurement, collection, analysis and reporting about learners as well as their contexts in order to optimize learning, spot opportunities and trends, and be more innovative. 

Learning Management System (LMS) Market: Learning Management System is a web-based technology and software application designed to outline, execute, and evaluate learning procedures. Canvas, Google Classroom, and Moodle are a few LMS platforms today. The tool is generally used in retail, IT, education, and hospitality sectors. 


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Management ‘bought the AI hype’ and expect value but research shows lack of organizational readiness is primary hurdle: IFS

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IFS commissioned research shows value creation lags AI promise without the right planning and application
LONDON, April 23, 2024 /PRNewswire/ — New research from IFS, the global cloud enterprise software company, has found that executive and board leadership have ‘bought the AI hype’ but organizations are unable to deliver operationally on expectations. The new global study of 1,700 senior decision makers, Industrial AI: the new frontier for productivity, innovation and competition, found that the promise of AI is being held back by technology, processes and skills. Half of respondents remain optimistic that with the right AI strategy, value can be realized in the next two years, and a quarter believe in the next year.

Expectations failing to meet reality
84% of executives anticipate massive organizational benefits from AI, with the top three areas AI is expected to deliver value in being high-impact: product & service innovation, improved internal & external data availability, and cost reductions & margin gains. The hype has become so high that 82% of senior decision-makers acknowledge that there is significant pressure to adopt AI quickly. However, this same group of respondents state that they are concerned that a failure to plan, implement and communicate properly means AI projects will stall in pilot stage.
Many organizations have not prioritized elements of development, nor have the infrastructure required to reap the rewards or the skills to deliver on that promise. The study found that over a third (34%) of businesses had not moved to the cloud. While this is not essential to AI adoption, it is indicative of an unprepared enterprise unlikely to be able to scale AI across their business. According to IFS, a robust Industrial AI strategy requires a potent combination of cloud, data, processes, and skills. 80% of respondents agree that the lack of a strategic approach means they have insufficient skills in-house to successfully adopt AI. This sentiment is seen elsewhere in the research with 43% of respondents rating the quality of AI resources in their business, in terms of human skills, as passable and not where it needs to be.
Christian Pedersen, Chief Product Officer, IFS, commented: “AI is poised to become the most transformational enterprise tool ever seen, but our research reveals that there are still fundamental misunderstandings about how to harness its power within an industrial setting. It is telling that AI is expected to significantly reduce costs and raise margins, but a lack of robust strategy means most businesses are under-skilled and under-prepared to achieve these ambitions. We built IFS.ai specifically with these challenges in mind. AI value simply will not be found in a single AI capability but instead by delivering AI across all products and business processes. This supports customers’ decision cycles and provides the data and AI services required to realize value faster.”
Pedersen continued: “Achieving this at scale needs a clear-eyed strategic focus, including the high-impact use cases specific to their industry, having a cloud-based infrastructure in place which has industrial AI embedded, and investing early in developing the skills needed. Adopting this approach will turn the tide of disillusionment, and deliver the benefits that boards and the C suite are demanding.”
Outlook optimistic but planning needed
The unfortunate reality of the skills gap means that in terms of AI readiness, many businesses are falling behind. IFS found that nearly half of respondents (48%) were most likely to say that they are gathering proposals and were much less likely to have a clear strategy and perceivable results (27%). A fifth of respondents are in the research phase, with uncontrolled tests taking place and a further 5% are lacking a coordinated approach and do not have anything in motion yet. Despite initial challenges, there is still optimism with respondents most likely to feel AI could make a significant difference to their business in 1-2 years (47%), and a further quarter (24%) believe it could be within a year.
In particular, respondents are most optimistic about the impact of AI in smart production and/or service delivery on effectiveness & business and operational management (22%) in the future. One fifth see the biggest impact being on innovation with new products and services (20%), growth & business model decision-making (20%), empowering people and increasing talent retention (19%), and customer experience and customer service (19%).
Action needed on data readiness
To reap these benefits, enterprises need to leverage the most strategic asset they have – their data. The right data volume and quality is critical for the success of AI applications. Respondents recognize how important real-time data is to successful AI projects, with over 4 in 5 (86%) stating this. Yet despite this recognition, less than a quarter (23%) of respondents have completed their data foundation with it supporting both data-driven business decision making and real time response to changes, suggesting that more work needs to be done to get data AI ready. Moreover, under half (43%) of respondents have majority structured data, with some unstructured.
Pedersen commented: “The lack of maturity at the data foundation layer needs to be addressed as part of an overall AI strategy, otherwise AI simply will never be the magic bullet that can turbocharge the enterprise. Clearly enterprises need support on data management and migration. While AI is seen as a shiny new tool that will revolutionize business, like all technology, it is never that simple. The power of Industrial AI is that it can touch all facets of a business from product innovation and customer experience to productivity and ESG. Its potential is massive if executives and organizations can combine vision, strategy, technology and skills. Now is the time to step back, take stock, and build a true Industrial AI plan and turn the hype into reality.”
Methodology:
Censuswide surveyed 1,709 C-level/President/SVP/Directors who work in Manufacturing, Telecommunications, A&D, Services, Construction & Engineering or Energy & resources in organizations with $50m+ annual revenue (Aged 18+) across the UK, USA, Canada, Germany, France, UAE, Norway, Japan, Australia, Sweden, Denmark and Finland between 06.03.2024 – 27.03.2024.
IFS Press Contacts:MEA& APJ: Adam GillbeCorporate CommunicationsEmail: [email protected] Phone: +44 7775 114 856
USA: Mairi MorganCorporate CommunicationsEmail: [email protected] Phone: +44 7918 607 299
This information was brought to you by Cision http://news.cision.com
https://news.cision.com/ifs/r/management–bought-the-ai-hype–and-expect-value-but-research-shows-lack-of-organizational-readiness,c3965172
The following files are available for download:
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University medical centers in Germany choose Sectra’s radiology solution to streamline workflows and shorten lead times for patients

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LINKÖPING, Sweden, April 23, 2024 /PRNewswire/ — International medical imaging IT and cybersecurity company Sectra (STO: SECT B) has signed two contracts to provide the radiology module of its enterprise imaging solution with two university medical centers in Germany—Universitätsklinikum Tübingen and Universitätsmedizin Göttingen. By implementing Sectra’s radiology solution, the hospitals aim to improve and streamline radiology workflows with Sectra’s tools for enhanced reporting efficiency, in turn speeding up diagnostics.

“When choosing a vendor, we wanted one that could provide us with a stable and fast system. We also wanted one facilitating collaboration among our radiologists. That way we can streamline our radiology workflows and in turn shorten lead times for patients as well as reduce the ever increasing workload for radiologists,” says Dr. Babak Panahi, Managing Senior Physician and Head of CT and CT Intervention, Universitätsmedizin Göttingen.
Universitätsmedizin Göttingen and Universitätsklinikum Tübingen are two university medical centers located in the cities of Göttingen and Tübingen in Germany managing 300,000 and 600,000 radiology exams a year. The two separate contracts for Sectra’s radiology solution were both signed during the third quarter of Sectra’s 2023/2024 fiscal year.
“Radiologists are under a lot of pressure as they are challenged to handle more images and more complex cases with less resources. Having a solution designed to streamline radiology workflows, facilitating reading and reporting of images, is therefore paramount. I am happy and excited to support Universitätsmedizin Göttingen and Universitätsklinikum Tübingen on their journey towards efficient radiology diagnostics,” says Guido Bötticher, Managing Director, Sectra DACH.
The radiology module is part of Sectra’s enterprise imaging solution that provides a unified strategy for all imaging needs while lowering operational costs. The scalable and modular solution, with a VNA at its core, allows healthcare providers to grow from ology to ology and from enterprise to enterprise. Visit Sectra’s website to read more about Sectra and why it’s top-ranked in ‘Best in KLAS’.
About SectraSectra contributes to a healthier and safer society by assisting health systems throughout the world to enhance the efficiency of care, and authorities and defense forces in Europe to protect society’s most sensitive information. The company, founded in 1978, is headquartered in Linköping, Sweden, with direct sales in 19 countries, and distribution partners worldwide. Sales in the 2022/2023 fiscal year totaled SEK 2,351 million. The Sectra share is quoted on the Nasdaq Stockholm exchange. For more information, visit Sectra’s website.
For further information, please contact: Dr. Torbjörn Kronander, CEO and President Sectra  AB, 46 (0) 705 23 52 27Marie Ekström Trägårdh, Executive Vice President Sectra AB and President Sectra Imaging IT Solutions, 46 (0)708 23 56 10
This information was brought to you by Cision http://news.cision.com
https://news.cision.com/sectra/r/university-medical-centers-in-germany-choose-sectra-s-radiology-solution-to-streamline-workflows-and,c3965089
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New CPS Protection Platform: TXOne Networks Unveils SageOne at GISec Global

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TAIPEI, April 23, 2024 /PRNewswire/ — TXOne Networks, a frontrunner in the realm of cyber-physical systems (CPS) security, is set to unveil its groundbreaking CPS security platform, SageOne, at the highly anticipated GISec Global from April 23rd to 25th, 2024. Attendees can find TXOne Networks showcasing SageOne at stand B99 in hall 5. This innovative platform consolidates all CPS security products onto a single, central management platform, promising streamlined operations and optimized threat detection capabilities.

SageOne, aptly named “Wise Man Number One,” serves as a comprehensive management console providing a holistic view of the CPS attack surface within operational technology (OT) environments. By enabling centralized control of TXOne’s three core product lines – Stellar for endpoint protection, Element for security inspection, and Edge for network defense – SageOne facilitates integrated OT security throughout the lifecycle of protected assets, ensuring robust threat detection and response mechanisms.
Key features of SageOne include:
CPS Attack Surface Management: Prioritizing operational security by offering clear visibility into the overall security posture of OT environments, SageOne identifies security focal points, illuminating asset information and security controls.Integrated Lifecycle Protection: Through centralized management, SageOne simplifies cybersecurity governance and fosters collaborative defense. It serves as an abstraction layer, facilitating contextualization and consolidation of data across multiple products, offering tailored, task-oriented consoles for executives, security personnel, and plant leaders.CPS Threat Detection & Response: SageOne aggregates security insights from various solutions to scout for potential risks, enabling early caution and response to both known and unknown threats.SageOne’s foundation rests upon advanced components, including Threat Intelligence, Behavior-Based AI Analytics Engines, Compliance Framework, Data Visualizer, and Ecosystem Integrator, ensuring comprehensive protection and seamless integration of different tools and technologies.
With its focus on analyzing unexpected behavior and unknown threats, SageOne enables the identification of suspicious events through cross-telemetry analysis within the OT-native XDR engine. This amalgamation of advanced technologies and user-friendly interface ensures the protection of critical infrastructures.
For rapid threat response, SageOne issues early warnings of suspicious behavior and orchestrates cross-telemetry analysis for CPS Threat Detection & Response. Integrated Lifecycle Protection ensures the security of devices and systems throughout their service life, contributing to great cost efficiency.
TXOne Networks reaffirms its commitment to CPS security and continuous advancement in OT security through SageOne. Visit TXOne Networks at the GISec Global from April 23rd to 25th, 2024, at stand B99 in hall 5.
For further updates and information, follow TXOne Networks on the blog, Twitter, and LinkedIn.
About TXOne Networks:
TXOne Networks provides OT security products ensuring reliability and security in industrial control systems and operational technology environments through the OT Zero Trust methodology. Collaborating with leading industrial manufacturers and critical infrastructure operators, TXOne Networks offers practical and business-friendly approaches to OT defense. Its network and endpoint-based products secure OT networks and mission-critical devices in real-time with high security depth.
Website: www.txone.com 
Photo – https://mma.prnewswire.com/media/2389611/SageOne_header_3.jpg

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