Artificial Intelligence
Machine Learning Market | Demand, Size, Share, Trends, Opportunities, Challenges, Risks Factors Analysis & Competitive Situation | Douglas Insights
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)
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News Summary:
Cisco delivers seamless integration between ThousandEyes and Amazon CloudWatch Internet Monitor.ThousandEyes’ unmatched cloud and Internet visibility combined with AWS’s Internet health and performance insights will allow a complete view of an application’s entire service delivery path, across private environments, the public Internet and into AWS’s network.Customers benefit from new operational insights and recommendations enabling them to optimize deployments and assure exceptional digital experiences for any AWS-hosted application.LAS VEGAS, Nov. 28, 2023 /PRNewswire/ — AWS re:Invent — Today at AWS re:Invent 2023, Cisco (NASDAQ: CSCO) announced new integrations between Cisco ThousandEyes and Amazon CloudWatch Internet Monitor (CWIM), a new Internet monitoring service from Amazon Web Services (AWS). The first-of-its-kind integration empowers customers with unparalleled visibility into their cloud deployments, enabling them to deliver unmatched optimized digital experiences.
With this new integration, customers can leverage operational insights to ensure optimal placement of AWS instances and monitoring coverage based on user traffic profiles. This integration comes on the heels of ThousandEyes announcing AWS Network Path Enrichment, giving customers deeper visibility into AWS by enriching ThousandEyes Path Visualization with data from AWS data sources—helping customers work more collaboratively with providers to resolve issues that are impacting application performance.
Building upon the existing relationship between AWS and Cisco, the new integration demonstrates Cisco’s deep commitment to its end-to-end network assurance vision. Cisco securely and sustainably connects everyone to everything and assures the digital experience of every one of those connections. By working with AWS, Cisco is delivering on its promise to provide visibility into every domain that impacts digital experience—whether user, enterprise, Internet, or cloud—so it can ultimately provide artificial intelligence (AI)-driven insights, recommendations, and remediations to support the digital transformation of every customer, wherever they are on their journey.
“Since launching one year ago, Amazon CloudWatch Internet Monitor has delivered real-time insights into the traffic and performance of our customers’ AWS VPCs, CloudFront distributions, and Workspaces towards Internet destinations. In-depth Internet visibility is critical to our customers, so we’re excited to combine forces with ThousandEyes to provide a comprehensive view of Internet health.” — Robert Kennedy, VP of AWS Border Network Engineering, AWS
“Connectivity is key to Sutherland’s business model and to our customer interactions. Cloud visibility is a big part of that and with ThousandEyes’ end-to-end visibility all the way from our employees’ home environments to AWS, we’re able to quickly catch and resolve issues which allows us to deliver consistent high-quality application experiences to both our employees and customers.”—Ted Sanfilippo, VP Infrastructure, Head of Global Network Services and GTOC, Sutherland
“Customers today need to assure digital experiences over any network—the ones they own and the ones they don’t. As the leader in Internet visibility, Cisco is on a mission to deliver unmatched, end-to-end network assurance. Today’s integration with AWS demonstrates our shared commitment to empower our customers to more effectively monitor and manage their cloud environments.”— Mohit Lad, Senior Vice President and General Manager, Network Assurance, Cisco, and Co-Founder, ThousandEyes
For more information and live demos visit ThousandEyes at AWS re:Invent at booth #1621. Join our Lightning Talk on the exhibit floor: NET102-S, “Extending ThousandEyes visibility to the AWS network,” November 28 at 3:30 PM – 3:50 PM (PDT)
Availability
The Amazon CloudWatch Internet Monitor integration will be available in Cisco ThousandEyes in spring 2024. The ThousandEyes platform is available for purchase today in AWS Marketplace.Additional Resources
ThousandEyes Announcement BlogAWS Marketplace: CiscoCisco at AWS re:Invent 2023Additional Cisco news at AWS re:InventAbout CiscoCisco (NASDAQ: CSCO) is the worldwide technology leader that securely connects everything to make anything possible. Our purpose is to power an inclusive future for all by helping our customers reimagine their applications, power hybrid work, secure their enterprise, transform their infrastructure, and meet their sustainability goals. Discover more on The Newsroom and follow us on X at @Cisco. Cisco and the Cisco logo are trademarks or registered trademarks of Cisco and/or its affiliates in the U.S. and other countries. A listing of Cisco’s trademarks can be found at www.cisco.com/go/trademarks. Third-party trademarks mentioned are the property of their respective owners. The use of the word partner does not imply a partnership relationship between Cisco and any other company.
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Artificial Intelligence
Artificial Neural Network Market to Reach $1.4 Billion by 2032 at 19.9% CAGR: Allied Market Research
The growing demand for AI-based solutions and the rising need for intelligent business processes are expected to drive the global artificial neural network market growth.
NEW CASTLE, Del., Nov. 28, 2023 /PRNewswire/ — Allied Market Research published a report, titled, “Artificial Neural Network Market by Component (Solution and Service), Deployment Mode (On-premise and Cloud), Enterprise Size (Large Enterprises and Small & Medium-sized Enterprises), and Industry (Healthcare, BFSI, Retail and E-commerce, Manufacturing, Automotive, and Others): Global Opportunity Analysis and Industry Forecast, 2022–2032”. According to the report, the artificial neural network industry generated $227.8 million in 2022 and is anticipated to generate $1.4 billion by 2032, witnessing a CAGR of 19.9% from 2023 to 2032.
Prime determinants of growth
The notable factors positively affecting the artificial neural network market include the growing demand for AI-based solutions and the rising need for intelligent business processes. However, a lack of computational resources and a skilled workforce with expertise in artificial neural network (ANN) can hinder market growth. Furthermore, advancements in big data analytics and the availability of high-performance computing systems offer lucrative market opportunities for the market players.
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Report coverage & details:
Report Coverage
Details
Forecast Period
2023–2032
Base Year
2022
Market Size in 2022
$227.8 Million
Market Size in 2032
$1.4 Billion
CAGR
19.9 %
No. of Pages in Report
450
Segments covered
Component, Deployment Mode, Enterprise Size Industry, and Region.
Drivers
Growing demand for AI-based solutions
The rising need for intelligent business processes
Opportunities
Advancements in big data analytics.
The availability of high-performance computing systems.
Restraints
A lack of computational resources and a skilled workforce with expertise in artificial neural network (ANN)
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The solution segment to maintain its leadership status throughout the forecast period
Based on component, the solution segment held the highest market share in 2022, accounting for less than two-fifths of the artificial neural network market revenue, and is estimated to maintain its leadership status throughout the forecast period. This is attributed to the growing need for a high level of personalization which is one of the primary reasons enterprises are increasing their investment in the artificial neural network market. However, the services segment is projected to manifest the highest CAGR of 21.8% from 2023 to 2032. The services segment is expected to witness the highest growth, as these services help to reduce the time and costs associated with optimizing systems in the initial phase of deployment.
The on-premise segment to maintain its lead position during the forecast period
Based on deployment mode, the on-premise segment accounted for the largest share in 2022, contributing for more than one-fourth of the artificial neural network market revenue. An increase in the need for secure and reliable data within the organization is fueling the market growth for on-premises-based artificial neural network solutions. However, the cloud segment is expected to portray the largest CAGR of 21.2% from 2023 to 2032 and is projected to maintain its lead position during the forecast period. It provides several advantages such as reducing costs, supporting business, and effectively controlling the business environment in the organization.
The large enterprises segment to maintain its lead position during the forecast period
Based on enterprise size, the large enterprises segment accounted for the largest share in 2022, contributing for more than one-fourth of the artificial neural network market revenue, owing to the growing demand for artificial neural network solutions in large enterprises which is fueling the market growth in these enterprises. However, the small and medium-sized enterprises segment is expected to portray the largest CAGR of 22.2% from 2023 to 2032 and is projected to maintain its lead position during the forecast period. It provides various benefits to the small and medium-sized enterprises organization.
The healthcare segment to maintain its lead position during the forecast period
Based on industry vertical, the healthcare segment accounted for the largest share in 2022, contributing for less than two-fifths of the artificial neural network market revenue, owing to the development of digital technologies in IT sector. However, the manufacturing segment is projected to manifest the highest CAGR of 24.3% from 2023 to 2032. The surge in implementation of automation trends and the increase in utilization of digital technology in this sector are expected to provide lucrative opportunities for the market.
North America region dominated the global artificial neural network market in 2022
Based on region, the North America segment held the highest market share in terms of revenue in 2022, accounting for less than two-fifths of the artificial neural network market revenue. The increase in the usage of artificial neural network solutions in businesses to improve businesses and the customer experience is anticipated to propel the growth of the market in this region. However, the Asia-Pacific segment is projected to manifest the highest CAGR of 21.8% from 2023 to 2032. Countries such as China, India, and South Korea are at the forefront, embracing digital technologies to enhance their effectiveness and competitiveness, which is further expected to contribute to the growth of the market in this region.
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Competition Analysis:
Recent Product launches in the Artificial Neural Network Market
In April 2023, Google LLC launched a cloud-based automation toolkit for healthcare organizations and previewed Med-PaLM 2, a neural network capable of answering medical exam questions.In August 2021, IBM Corporation unveiled details of the upcoming new IBM Telum Processor designed to bring deep learning inference to enterprise workloads to help address fraud in real-time..Recent Partnerships in the Artificial Neural Network Market
In June 2023, Snowflake partnered with Microsoft to simplify joint customers’ artificial intelligence projects. A core focus of the collaboration is Microsoft’s Azure OpenAI Service. It provides cloud-based versions of OpenAI LP’s machine learning models, including GPT-4.In November 2021, Qualcomm Technologies partnered with Google Cloud, on Neural Architecture Search (NAS), enabling the companies to create and optimize AI models automatically rather than manually.Leading Market Players: –
Amazon Web Services Inc. Google Inc. Hewlett Packard Enterprise Development LP IBM Corporation Intel Corporation Microsoft Corporation NVIDIA Corporation Oracle Corporation Qualcomm Technologies Inc. Salesforce Inc.The report provides a detailed analysis of these key players in the artificial neural network market. These players have adopted different strategies such as new product launches, collaborations, expansion, joint ventures, agreements, and others to increase their market share and maintain dominant shares in different countries. The report is valuable in highlighting business performance, operating segments, product portfolio, and strategic moves of market players to showcase the competitive scenario.
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About Us:
Allied Market Research (AMR) is a full-service market research and business-consulting wing of Allied Analytics LLP based in Wilmington, Delaware. Allied Market Research provides global enterprises as well as medium and small businesses with unmatched quality of “Market Research Reports Insights” and “Business Intelligence Solutions.” AMR has a targeted view to provide business insights and consulting to assist its clients to make strategic business decisions and achieve sustainable growth in their respective market domain.
We are in professional corporate relations with various companies, and this helps us in digging out market data that helps us generate accurate research data tables and confirms utmost accuracy in our market forecasting. Allied Market Research CEO Pawan Kumar is instrumental in inspiring and encouraging everyone associated with the company to maintain high quality of data and help clients in every way possible to achieve success. Each and every data presented in the reports published by us is extracted through primary interviews with top officials from leading companies of domain concerned. Our secondary data procurement methodology includes deep online and offline research and discussion with knowledgeable professionals and analysts in the industry.
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Artificial Intelligence
New process definition capabilities in PIMS further enhance quality assurance and “right -first-time” initiatives for pharma manufacturers
WOKING, England, Nov. 28, 2023 /PRNewswire/ — IDBS unveils new process definition templates in its latest release, PIMS 5.1. Process definition templates enable pharma manufacturers to template process steps and quality specifications for faster process definition set-up and improved harmonization across the manufacturing teams to further enhance quality assurance (QA) and “right-first-time” initiatives.
Providing contextualized access to aggregated manufacturing data, PIMS offers a single source of data truth for efficient gathering, sharing and analysis of critical manufacturing process and quality data to support continued process verification (CPV), investigations and process optimization.
This release builds on recent PIMS’ process definition enhancements that added process definition versioning and approvals to help alleviate manual standard operating procedure (SOP) requirements and enhance QA for a more robust GxP environment.
PIMS’ customers report that these standardized process definition templates will reduce their manual process definition set-up and enable easy, harmonized site and product comparisons.
“Our customers recognize the value of being able to trace their process data over time, not only for tech transfer but also to help them learn from their historical data and optimize future process development,” says Pietro Forgione, General Manager at IDBS. “Having their critical process data in PIMS already gives them the assurance of data integrity and these new enhancements now make it even easier to complete QA and validation steps and move them closer to ‘right-first-time’ manufacturing.”
To learn more, register for the December 6 webinar here.
About IDBS
IDBS helps BioPharmaceutical organizations accelerate the discovery, development and manufacturing of the next generation of life-changing therapies that advance human health worldwide. From lab through manufacturing, IDBS leverages its 30+ years of experience working with a diverse list of customers – including 18 of the top 20 global BioPharma companies – and deep expertise in scientific informatics and process data management to tackle today’s most complex challenges.
Known for its signature IDBS E-WorkBook product, IDBS has extended solutions across the entire value chain for BioPharma Lifecycle Management (BPLM). Built on analytics-centric and cloud-native technology, IDBS Polar and Skyland PIMS platforms are powered by a digital data backbone to drive faster and smarter decisions in drug development and across the supply chain.
Learn more at idbs.com.
MEDIA ENQUIRIES e | [email protected]
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