Category Archives: Data Mining
Newcrest’s Cadia gold mine responds to Environmental Protection Authority’s order to reduce dust – ABC News
The Environment Protection Authority says it wants to see proof that a New South Wales gold mine has reduced its dust pollution.
The NSW EPA says it has received a letter from Cadia Valley Operations' parent company, Newcrest Mining, outlining measures it has taken to lower dust emissions.
"They've laid out a series of operational changes they've made to their underground processes that, in their view, have substantially reduced the production of dust and created a situation where the mine should now be in compliance," EPA chief executive Tony Chappel said.
"They've also laid out a number of other steps underground in terms of better containing and managing any dust that is produced."
Mr Chappelsayshe is waiting for data from the mine, expected in the next few days, to verify its claims.
"We need to see the data validate the outcomes they've achieved," he said.
"We are expecting the first data set as part of the new monitoring regime that's been imposed later this week, and we'll be regularly monitoring to ensure that compliance.
"If they can achieve and maintain these results and do that consistently across the site, that is a quantum shift in the performance of the mine and that should bring it into compliance."
It comes after the EPA launched an investigation into Cadia Valley Operations (CVO) in May after it found an unacceptable volume of dust was being released from the mine'sair vent and nearby residents had heavy metals in their blood and rainwater tanks.
Mr Chappel said the mine has reported taking initial actions including changing their underground operations to be compliant.
"They have responded with significant changes but there is still more work to be done," Mr Chappel said.
The EPA says it has been told the mine has reduced dust production levels, installed additional dust spays and spray curtains; and reconfigured its dust extraction systems.
CVO has told the EPA it has also taken steps to increase sampling of dust emissions.
The EPA has appointed a panel of nine experts to advise on the next stage of its regulatory actions against the mine.
"Panel members will provide advice on sampling, testing and monitoring to understand the extent, impact and potential of pollutants making their way into the Cadia Valley community," Mr Chappel said.
The EPA's action was prompted by blood and water testing that was ordered by concerned local residents and returned elevated levels of lead, nickel and selenium.
Heavy metals were also found in people's rainwater tanks.
The EPA has continued to monitor and sample rainwater tanks at 50 properties near the mine.
The ABC has contacted CVO for a response.
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A robust data plan will heal our health sector – The Standard
By Brian Lishenga| Jun. 25, 2023
In the aftermath of recent reports exposing alleged fraud within some medical facilities involving officials at the National Hospital Insurance Fund, it is crucial to understand the root causes of these unfortunate events.
Two questions emerge: How can we prevent overconsumption in healthcare? How can data mining and analysis serve as early warning systems for detecting healthcare fraud and predicting costs?
Given the limited resources available and the rise of chronic illnesses, it is important to prioritise the rational utilisation of financial resources in the healthcare sector.
What Kenya requires at this juncture is an action plan for the control of healthcare. Such a plan should encompass modern control techniques, built upon a new legal framework that promotes close collaboration among health sector stakeholders.
The NHIF, together with relevant departments in the Ministry of Health and scientific associations responsible for publishing treatment guidelines and care standards, should engage in meaningful consultations to establish a unified strategy and identify synergies for effectively addressing overconsumption in healthcare.
These efforts should result in structural reforms supported by legal changes that govern the relationships and collaborations among these entities. To strengthen the NHIFs capacity to combat healthcare resource wastage, we propose establishment of a Directorate for Medical Evaluation and Control, led by a Medical Chief Inspector.
The Chief Inspector, assisted by a committee comprising healthcare providers and representatives appointed by regulatory bodies, including a medico-legal expert as the chairperson, would be responsible for conducting proceedings against healthcare providers suspected of violating the NHIF Act, particularly in cases involving overconsumption or over-prescription of care. The Chief Inspector would have the authority to initiate formal legal proceedings against such providers. To effectively assess, predict and control escalating costs of healthcare, Kenya must tap into its vast medical data repositories.
Therefore, it is essential to establish a legal framework for a Central Registry for Medical Data, supervised by the Office of the Data Protection Commissioner, a strategy that aligns with the current administrations focus on digital economy. This framework would facilitate seamless data sharing between healthcare insurance companies, the NHIF, and healthcare providers, supported by robust data.
At present, healthcare insurers, funds, and providers collect, process, store, and utilise administrative data primarily for billing and reimbursement purposes. However, with a solid legal foundation and well established infrastructure, this data can be harnessed for resource allocation and health services research. A harmonised system that allows private insurance providers and the NHIF to share relevant information would be highly beneficial. By utilising anonymised or pseudonymised data, we can develop a comprehensive patient profile incorporating indicators that highlight behavioural patterns contributing to overconsumption.
In envisioning the future, we can achieve a healthcare landscape where a healthcare provider who has been blacklisted by a private insurance company, is promptly flagged in the NHIF system, and conversely, any provider flagged by the NHIF is immediately visible to private insurers.
We can seize this opportunity and use it for transformative change. By embracing data-driven reforms, Kenya can establish a healthcare system characterised by efficiency, accountability, and improved patient outcomes. The time to act is now, and together, we can shape a brighter future for our nations health.
The writer is national chairman, Rural Private Hospitals Association of Kenya
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A robust data plan will heal our health sector - The Standard
Workshop on data mining and effective searching techniques held – Greater Kashmir
GK Photo
Ganderbal, June 13: Department of Convergent Journalism (DCJ), Central University of Kashmir (CUK) organised a lecture cum workshop on Data Mining and Effective Searching Techniques at Tulmulla campus here.
Prof. Umesh Arya, Professor and Dean, faculty of Media Studies, Guru Jambheshwar University of Science & Technology was the invited resource person.
In his address, Dean Academics Affairs, Prof. Shahid Rasool stressed on the significance of data mining skills for the media studies students and journalism professionals and said the abundant data available on the internet has made it difficult for the people to locate the accurate information. He said there is a significant change in the way people look out for information these days and people are shifting from books to online platforms. He said due to an overload of information on the internet, it becomes very important for people to know and understand the most appropriate commands and keywords that can be used to trace the exact information.
In his lecture, Prof. Umesh Arya talked about effective searching techniques and also demonstrated how" we can streamline our research involving data from the internet." He taught some basic tools for gathering and filtering information on the internet and how the data could be segregated using refined searching words and with the use of filters. Prof. Arya also talked about the data retrieval from journals using similar techniques. The session was followed by an interactive session wherein the students, scholars and the faculty members shared their thoughts.
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Workshop on data mining and effective searching techniques held - Greater Kashmir
Data Mining Tools Market In Depth Insight Analysis to 2023-2032 … – Reedley Exponent
The globaldata mining tools marketis forecast to reach USD 2,321.3 Million by 2030, according to a new report by Reports and Data. Data Mining is the process of analyzing data from various dimensions, domains, perspectives, and finding the previously used hidden patterns of heterogeneous set of data, to classify and group into the same clusters of data with respect to the identified relationships. Data mining tools help us get the valuable insights from huge amount of data, that is generated every second worldwide by applying data mining algorithms through machine leering, statistics, artificial intelligence, and visualizations in quick time. The global market is growing predominantly as the amount of data every second is being drastically elevated globally. SMEs are expected to contribute remarkably in the forecast period due to a massive adoption of the data mining tools for their relational, transactional and heterogeneous databases. Sales & marketing sub-segment in the business application has the highest usage of these tools and is also calculated to achieve the highest growth rate.
APAC is forecasted to achieve the fastest growth of about 14.1% in the period 2021 2030, due to an increase in adoption of the data mining tools in SMEs of all the industries in the countries like China, Singapore, and India. North America holds the highest market share of 37.6% in 2018 because of the prodigious rate of deployment of the data mining solutions in the conglomerates.
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Top 10 Companies Operating in the Global Data Mining Tools Market:
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The global market is further segmented into type and application:
Component Type Outlook (Revenue, USD Million; 2019-2030)
Service Type Outlook (Revenue, USD Million; 2019-2030)
Deployment Outlook (Revenue, USD Million; 2019-2030)
Business Application Outlook (Revenue, USD Million; 2019-2030)
Organization Size Outlook (Revenue, USD Million; 2019-2030)
End-use Outlook (Revenue, USD Million; 2019-2030)
Regional analysis provides insights into key trends and demands in each major country that can affect market growth in the region.
Key Takeaways of the Competitive Overview Section:
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Data Mining Tools Market In Depth Insight Analysis to 2023-2032 ... - Reedley Exponent
AidData lab receives $1.7M to advance agriculture and mining … – William & Mary
To effectively address globally important questions such as how to grow crops that will best serve regions affected by climate change or how to assess the environmental and economic impact of mining for transition minerals used in car batteries, policymakers need accurate data.
Thats what William & Marys AidData research lab is providing with support from The William and Flora Hewlett Foundation, which recently awarded the lab two grants totaling $1.7 million. This funding continues a more than decade-long partnership between the Hewlett Foundation and AidData, which operates under the Global Research Institute, a multidisciplinary hub comprising over 60 faculty and staff and more than 200 students.
The first grant, worth $1.2 million, will fund up to four collaborations with partner organizations in Africa that expand on the types of agricultural and economic projects AidData already has underway. These focus on geospatial impact evaluations, using satellite imagery and on-the-ground interviews to find ways to improve farming outcomes and reduce poverty in Africa. The collaborations will also focus on examining Africas gender-related policies in urban settings and enhancing agriculture policy researchers ability to use geospatial tools for evaluation and analysis.
A second grant for $500,000 will enable AidData to better understand Chinese development financing in mining for transition minerals that are essential for a renewable future. Minerals such as cobalt, lithium, nickel and magnesium the quest for which has sometimes been dubbed a new gold rush are necessary for batteries in electric vehicles and in incredibly high demand. China currently controls much of the market for the raw materials used in electric vehicle batteries from mining operations to processing plants.
Through this project, AidData will collect and analyze granular data on dozens of mining sites, focusing on how operations are affecting the local environment in their surrounding communities, mainly in sub-Saharan Africa and Latin America.
Like all things that we do at AidData, the main motivation is to bring new data and evidence to inform important public decision-making taking place around the world, said Ammar A. Malik, senior research scientist at AidData, who leads the Chinese Development Finance Program.
Malik is heading up the minerals project that will build upon AidDatas existing dataset of Chinese development projects worth $843 billion across 165 countries.
We will focus on the financing and implementation networks enabling projects including the banks and contractors involved in the delivery of mining projects, Malik said. Because China does not disclose details of their overseas development activities, there is very little data on these projects. We are trying to systematically and rigorously understand this issue in a consistent way.
Researchers will consider environmental, health and safety impacts from mining, such as deforestation and reduced air quality.
When a mining operation starts up, it further exposes where governance systems arent working, Malik said. If you dont have good labor rights or environmental protections, it makes underlying problems worse.
The AidData team will also look into the economic and social effects of mining, he said: Does it exacerbate inequities between the haves and the have-nots in those societies? Are men benefiting more than women?
Environmental protection, response to climate change and exploring the role of gender are common threads across the projects funded by both grants.
In Ghana, AidData is partnering with an agricultural research organization, the International Potato Center (known as CIP), to study how to promote and sustain the growth of sweet potatoes. These tubers supply nutrients that are necessary for child development and are lacking in some of the countrys other staple crops.
Encroachment of the Sahara Desert, termed desertification, is a major hindrance to crop growth in parts of the country.
Theyre having longer and longer dry seasons with less and less rain, said Ariel BenYishay, chief economist and director of research and evaluation at AidData as well as a William & Mary associate professor of economics.
Typically, a portion of the crop would be set aside for replanting the next year, but storing it through the lengthening dry season presents a challenge, he said: A lot of these potatoes are basically not viable as seeds for that long. CIP developed a solution to protect the potatoes for replanting by storing them in layers of sand.
Moving forward, AidData and CIP will study the spread of information about crops and nutrition through varied sources in the villages men, women, people of higher status and lower status to evaluate accuracy of the information, how it is spread and how listeners respond.
In Northern Ghana, the responsibility of growing things like sweet potatoes falls predominantly to women, and women are also making most of the decisions about which foods to feed their children, BenYishay said. But that doesnt mean women get all the say about what they grow and what they feed their kids. It will be interesting to see whether spreading the information through one genders networks versus anothers makes a difference.
AidDatas previous experience in Ghana has demonstrated the importance of collecting data about farming from both men and women, because surveys in which only the head of the household is asked questions tend to produce less accurate results. Conclusions from the earlier study funded by the Hewlett Foundation and Innovations for Poverty Action will be released in an upcoming working paper that will be submitted to an academic journal.
For that study, AidData partnered with the Ghana Center for Democratic Development (CDD-Ghana) to collect data from over 2,400 households and compare it with satellite imagery of farming plots.
In addition, AidData is working with CDD-Ghana to explore gender bias in artificial intelligence applications for estimating poverty. AidData and CDD-Ghana will host a workshop in Ghana for a mix of policymakers, aid donors, researchers and advocacy groups interested in addressing gender equity in decision making using survey data, poverty estimates and AI.
The workshop is being funded through the U.S. Agency for International Development (USAID) Equitable AI Challenge. The USAID initiative invests in programs that help identify and address gender biases within artificial intelligence systems, particularly those relevant to global development.
AidDatas work funded by the Hewlett Foundation helped catalyze a major Bill & Melinda Gates Foundation grant last fall to broaden the use of satellite imagery for studying agriculture and climate resiliency in developing countries. Each foundation is funding a portfolio of projects that are complementary in terms of their agricultural and gender focus, BenYishay said.
We hope that when we put all that together, we will have upwards of 10 projects that are letting us learn a lot about whats working, where there are points of synergy and ways to move forward more holistically, he said.
BenYishay emphasizes that half of the $1.2 million Hewlett Foundation grant will be shared with African partners who are collaborators on the projects.
Were trying to have these partners to participate in the research design from the outset, he said. The underlying research partnership is meant to flow in both directions. We meaningfully exchange ideas and they help to shape the longer-term direction here as well.
Editors note:Datais one of four cornerstone initiatives in W&Ms Vision 2026 strategic plan. Visit theVision 2026 websiteto learn more.
Tina Eshleman, University Marketing
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AidData lab receives $1.7M to advance agriculture and mining ... - William & Mary
Datamining Report: Cosmog and Team GO Rocket Special … – Pokmon GO Hub
Hello Trainers! Pokmon GO has had some texts pushed pertaining to Pokmon Sleep, the texts for the Cosmog special research for the Solstice Event, along with the texts for the Team Go Rocket Special Research.
So spoiler alert for the two special research lines!! Its a data mine report, so that kinda goes without saying but hey, never can be too careful right?
Please read through all of this with a grain of salt we often post data mining reports that take months to release, and we dont want our readers disappointed. Be smart, read this like speculation, and be happy once it goes live.
Disclaimer: You know the drill by now, everything in this article is data mined, and therefore subject to change or not even being released at all. All this information is publicly provided by the PokMiners and includes some of my commentaries.
Texts for the Solstice event, including a quest for catching Ghost or Dark-type Pokmon. Obviously for the Nighttime portion of the event.
Generic texts for the event, including the notice you must log in during the event to get the special research.
Oh look, Willow got himself in trouble again Also, I had no idea that the opposite of nocturnal was diurnal. Anyway, looks like we get to choose between day or night.
Texts for the Daytime and Nighttime branch choice.
If you choose the day branch, youll be after some Grass-type Pokmon.
If you choose the Nighttime branch youll be sent after some Ghost-type Pokmon.
Its Cosmog, so you know Rhi is making an appearance. Theyll stick around to help you with Willows tasks.
Apparently, you need to save Cosmog from blowing away. Get catching!
This round of the Team Go Rocket Special Research is called A Shadowy Disturbance.
Willow wants us to have a chat with some Team GO Rocket grunts because chit-chat is what theyre known for.
Thats right Willow, they were not interested in talking. Shocking, I know.
Ah yes, lets go talk to the leaders now. I dont think thats going to go how you want it to Willow.
At least hes not suggesting we have some sort of conversation with Giovanni.
Ey, Im down for a party!
Oh, youre still here. Heres a small collection of minor updates.
A notification for finding a raid group in Campfire, and Shadow raids appearing more often.
I am really interested to see how these work.
A couple of minor updates to some texts for Routes.
A few text updates for Pokmon Sleep, including a note that indicates if its unable to recognize the account associated with the device it will need to be reset.
Thats all for now Trainers, stay safe out there.
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Datamining Report: Cosmog and Team GO Rocket Special ... - Pokmon GO Hub
How Decision Intelligence and Artificial Intelligence Differ – Analytics Insight
In this article, learn about how decision intelligence and artificial intelligence differ
An advanced strategy for improving decision-making processes that incorporate human judgment, data analysis, and artificial intelligence algorithms is known as decision intelligence. It uses the power of technology to offer suggestions and insights that can be implemented to help people make good decisions in complicated business situations.
Decision intelligence entails obtaining pertinent data from various sources, including databases, text documents, and APIs, and combining it with other relevant data. Statistical methods, machine learning algorithms, and data mining techniques are used to find meaningful relationships and patterns in this data.
AI, which stands for artificial intelligence, refers to the research and creation of algorithms to imitate human cognitive abilities. Decision-making, language processing, and visual perception are just a few of the capabilities of these algorithms that were previously only available to humans. Machines can now analyze vast amounts of data, recognize patterns, and make predictions with increasing accuracy thanks to AIs remarkable advancements in recent years.
On the other hand, decision intelligence applies AI to commercial decision-making practically, taking AI one step further. It uses the capabilities of AI algorithms to offer suggestions for actions that specifically meet the requirements of businesses or solve complex business issues. The primary focuses of Decision intelligence are the achievement of commercial objectives and the promotion of efficient decision-making procedures within organizations operating in various industries.
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How Decision Intelligence and Artificial Intelligence Differ - Analytics Insight
The Law Is Coming for AIBut Maybe Not the Law You Think – The Information
While the approval of the AI Act in the European Parliament on Wednesday will no doubt go down in history as a day of reckoning for generative artificial intelligence, it was not the first. That honor belongs to March 31, when, citing a lack of compliance with various European data protection provisions, Italys data protection authority banned OpenAIs ChatGPT.
Products like ChatGPT and Googles Bard are members of the generative pre-trained transformer family of language models. These models rely on huge training data sets, to which they apply various artificial intelligence and machine-learning techniques, supervised and reinforced by human feedback, including user interactions with the model. Much of the training data is obtained by mining publicly available content, accessing data repositories and scanning large open data sets.
Just because these data sets are publicly available, however, does not mean the data itself is legally available to use.
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The Law Is Coming for AIBut Maybe Not the Law You Think - The Information
Wits University’s DigiMine aiming to serve as green data … – Creamer Media’s Mining Weekly
JOHANNESBURG (miningweekly.com) Most mining countries have already databased their green energy minerals and critical minerals and made them public so that investors and their global partners can evaluate national production capacities and capabilities.
Against that backdrop, the Wits Mining Institutes DigiMine Laboratory at University of the Witwatersrand (Wits) is setting out to build a comprehensive database to contribute to the understanding of the special abilities of critical green minerals and their applications inrenewable energy in particular.
Strong partnerships with mining industry players will be essential for DigiMine to achieve its goal of serving as a central hub for information exchange, research collaboration, technology development, innovation, and the driving of the growth of green energy into mining.
It is intent on integratingits system into South Africas upcoming national cadastral system, and in doing so, being able to provide feedback to the cadastral system.
It envisages that its comprehensive database system will be able to contribute to evidence-based policymaking and a supportive regulatory environment.
Once it has the database, it also expects to be able to provide the required framework for worker upskilling as per the needs of the industry.
By having this database, we can look into the required skills and define customised courses and training material so that we can also contribute to human capital development, DigiMine Laboratory head Ahsan Mahboob told Mining Weekly in a Zoom interview. (Also watch attached Creamer Media video.)
DigiMine set out initially to serve South African minings research and development needs in wireless communication, surveying, mapping and navigation, health and safety, and systems integration for smart mining, and then this year came up with the two new themes of cybersecurity and green energy minerals and technologies, the latter addressing South African minings energy the transition needs.
Weve observed with our global partners that there is a dire need to focus on the optimisation of the integration of renewable energy sources, such as solar and wind energy, into the mining operations," said Mahboob.
Most of the mining operations are moving towards renewables, for which storage is important, as well as to smart grid technology, which is required to transfer renewable energy to the mining operations. Then, most importantly, the energy management strategies need to ensure a reliable and efficient power supply, with DigiMine also planning to focus on power system modelling and planning.
Theres a need to apply sophisticated and advanced numerical models to see how the energy is going to be utilised in mining operations, and how we can leverage on the digital technologies, he said.
Green energy use can be modelled with the help of digital twinning technology, and based on that model, you can optimise, based on artificial intelligence algorithms. The focus will be to do research in terms of demand pattern analysis and then integration requirements, which will definitely help cost-effectiveness, added Mahboob.
Mining is also poised to benefit from the electrification of mining equipment, for which infrastructure to recharge battery electric vehicles is seen as critical. Wireless recharging stations being researched and developed obviate the need for vehicles to park while having their batteries recharged and allowfor battery electric vehicles to be recharged while continuing to operate, which is also something on which DigiMine wants to focus and analyse.
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Wits University's DigiMine aiming to serve as green data ... - Creamer Media's Mining Weekly
$4.4 Billion Composite AI Markets: Growing Intricacy of AI Applications for Better Performance and Accuracy to Drive Growth – Global Forecast to 2028…
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Global Composite AI Market
Global Composite AI Market
Dublin, June 13, 2023 (GLOBE NEWSWIRE) -- The "Composite AI Market - Global Forecast to 2028" report has been added to ResearchAndMarkets.com's offering.
The composite AI market is estimated to grow from USD 0.9 billion in 2023 to USD 4.4 billion by 2028, at a CAGR of 36.5%
With the proliferation of digital devices, sensors, and IoT devices, a wealth of data is generated across various industries. Composite AI leverages this data to gain insights, make predictions, and deliver personalized experiences. The growing availability of data fuels the development and adoption of Composite AI solutions.
The software segment is expected to hold the largest market size during the forecast period.
The global composite AI market is segmented based on offering hardware, software, and services. Based on software segment is divided into AI development platforms and tools, machine learning (ML) frameworks, AI Middleware, and other software (computer vision software, data management tools, monitoring software, and security and governance tools).
Composite AI software refers to the software systems and tools that enable the integration of multiple AI technologies, such as machine learning, natural language processing, computer vision, and robotics, to create more advanced AI applications. One of the key software tools used in composite AI is machine learning frameworks.
These frameworks provide tools and libraries for developing and training machine learning models, making creating and optimizing AI algorithms easier.
Data mining & machine learning segment to grow at a higher CAGR during the forecast period.
The global composite AI market is segmented based on technique into conditioned monitoring, pattern recognition, data processing, proactive mechanism, data mining & machine learning, and other methods (AutoML and Model Building, Model Stacking and Ensemble, and Transfer Learning).
Data mining and machine learning techniques to gain traction in coming years. These techniques extract valuable insights from large and complex datasets, which are then used to train AI models and drive intelligent decision-making.
Story continues
Among verticals, the BFSI segment holds the largest market size during the forecast period.
Composite AI solutions are being adopted across the BFSI sector for numerous applications such as fraud detection and prevention, risk assessment and management, customer service, credit scoring, and compliance and regulatory reporting.
The adoption of composite AI solutions in the BFSI sector offers numerous benefits, including improved operational efficiency, enhanced customer experience, risk reduction, and compliance with regulatory requirements.
Asia Pacific to grow at a higher CAGR during the forecast period.
The growth of composite AI solutions across the five major regions, namely North America, Europe, Asia Pacific, Middle East and Africa, and Latin America is driven by factors such as technological advancements, industry-specific demands, government initiatives, availability of talent, and the increasing recognition of AI's potential to transform businesses and societies.
Asia Pacific region is experiencing a rapid growth rate in adopting composite AI solutions. Countries like China, Japan, South Korea, and India are leading in AI R&D, with strong government support and investments. Key industry verticals such as manufacturing, eCommerce, healthcare, and BFSI aggressively implementing composite AI to gain a competitive edge, drive innovation, and cater to the growing demand for advanced AI-driven solutions.
Asia Pacific is home to some of the world's fastest-growing economies, and the region is experiencing rapid technological advancements. The increasing adoption of advanced technologies, such as AI, big data analytics, and cloud computing, has fueled the demand for composite AI solutions.
Competitive landscape
Market shares, growth strategies, and service offerings of leading players such as IBM (US), SAS Institute (US), Microsoft (US), Google (US), AWS (US), Salesforce (US), BlackSwan Technologies (Israel), Oracle (US), OpenText (Canada), SAP (Germany), HPE (US), Pega (US)
Key Attributes:
Report Attribute
Details
No. of Pages
281
Forecast Period
2023 - 2028
Estimated Market Value (USD) in 2023
$0.9 Billion
Forecasted Market Value (USD) by 2028
$4.4 Billion
Compound Annual Growth Rate
36.5%
Regions Covered
Global
Premium Insights
Growing Intricacy of AI Applications for Better Performance and Accuracy to Drive Market Growth
Market to Witness Minor Decline in Y-O-Y Growth in 2023
Customer Service Segment to Grow at Highest CAGR During Forecast Period
Software and Bfsi Segments to Hold Largest Shares in North America in 2023
North America to Hold Largest Share in 2023
Market Overview and Industry Trends
Market Dynamics
Drivers
Growing Intricacy of AI Applications for Better Performance and Accuracy
Increasing Demand for More Customized and Flexible Solutions to Improve Efficiency and Productivity
Advancements in Hardware Components and Infrastructure for Better Scalability
Rising Usage of Composite AI for Industry-Specific Applications
Restraints
Opportunities
Challenges
Case Study Analysis
Case Study 1: Creation of Holistic View of Clients and Activities of Tier-1 Bank Using Data Fabric Concept
Case Study 2: Intuit Used Amazon Sagemaker to Manage Machine Learning at Scale
Case Study 3: Sas Analytics Solutions Helped Usg Corporation to Improve Its Manufacturing Process
Case Study 4: Orlando Magic Used Mobile App Data and Machine Learning to Personalize Marketing Campaigns
Case Study 5: Amsterdam Umc Used Analytics and AI to Increase Speed and Accuracy of Tumor Evaluations
Case Study 6: in Special Olympics, Abu Dhabi Used Sas Analytics and AI Solutions to Keep Athletes Safe
Case Study 7: Hpe Helped New Work to Address Complex Data Privacy Requirements and Improve Operational Efficiency
Technology Analysis
Related Technologies
Supervised Learning
Unsupervised Learning
Natural Language Processing
Deep Learning
AI Governance (Ethical, Explainable, and Responsible AI)
Knowledge Graphs
Allied Technologies
Cloud Computing
Computer Vision
Federated Learning
Digital Twin
Ecosystem Analysis
Composite AI Framework/Library Providers
Composite AI Platform Providers
Composite AI Software Tool Providers
Composite AI Hardware Providers
Composite AI Service Providers
Regulatory Bodies
Business Models for the Development of Composite AI
Company Profiles
Key Players
IBM
Sas Institute
Microsoft
Aws
Salesforce
Blackswan Technologies
Oracle
OpenText
Recent Developments
Sap
Hpe
Pega
Other Key Players
Nvidia
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