Artificial Intelligence
Semiconductor Manufacturing Equipment Market Worth $171.6 Billion by 2030 – Exclusive Report by Meticulous Research®
Redding, California, Jan. 24, 2023 (GLOBE NEWSWIRE) — According to a new market research report titled, ‘Semiconductor Manufacturing Equipment Market by Front-end Equipment (Silicon Wafer Manufacturing, Wafer Fabrication), Back-end Equipment (Testing, Assembling & Packaging), Dimension, Component, End User, and Geography – Global Forecast to 2030’ the global semiconductor manufacturing equipment market is expected to reach $171.6 billion by 2030, at a CAGR of 6.0% during the forecast period 2023–2030.
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A multitude of applications, including artificial intelligence (AI), computer vision, internet of things (IoT), autonomous and electric vehicles, high-performance computing (HPC), satellite communications, 5G technology and smart cities, depend on advancements in semiconductor technologies. Semiconductors, such as microprocessors and memory devices, are used in various manufactured products, including computers, telecommunications equipment, and consumer electronics goods. Semiconductor manufacturing equipment is used in the most complex and advanced manufacturing processes and encompasses all equipment used to produce semiconductor devices.
The growth of this market is mainly driven by the rapid technological advances coupled with consumers’ increasing acceptance of connected devices, rising demand for semiconductors and the resultant proliferation of fabrication facilities, and increasing utilization of semiconductors in EV manufacturing. In addition, government initiatives aimed at boosting the semiconductors industry and the growing use of connected devices in home automation are expected to offer significant opportunities for the growth of this market. However, supply chain disruptions caused by the COVID-19 pandemic may restrain the market to a certain extent.
Impact of COVID-19 on the Semiconductor Manufacturing Equipment Market
During the COVID-19 pandemic, the lockdown restrictions impacted manufacturing operations, with production facilities either completely shutting down or running at reduced capacities to ensure social distancing and employee safety. Semiconductor manufacturing industries came to a standstill due to raw material & workforce shortages, supply chain disruptions, and restrictions on international trade. Most industries, such as consumer electronics and automotive, were affected by the negative impact of COVID-19; however, other industries, such as cloud-computing data centers, communication & connectivity technology, and healthcare, witnessed gradual but consistent growth. This helped the semiconductor manufacturing equipment market to regain its growth. In addition, favorable government policies & initiatives, including reduction and ease in interest rates, exceptions in tax, and the number of financial packages, are also aimed at promoting the growth of this market.
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Although COVID-19 has affected most semiconductor manufacturing equipment businesses across the globe, these businesses are eyeing to make a strong comeback by attracting consumers in the post-COVID-19 business environment. For instance, in October 2021, Advantest Corporation (Japan) entered into an agreement to acquire R&D Altanova, Inc. (U.S.) to expand its test and measurement solutions across the continuously evolving semiconductor value chain. In July 2021, Tokyo Seimitsu Co., Ltd. (Japan) launched the new SURFCOM NEX (DX2/SD2) contour measuring instrument. These machines have features such as high efficiency, high precision, high accuracy, and high reliability. Such initiatives, along with the rise in the production volume and demand for consumer electronic devices and hybrid electric vehicles, contribute to the market growth post the COVID-19 pandemic.
After Beijing launched unprecedented drills around Taiwan, the U.S. and China military conflict may affect the consumer market and important industrial manufacturing bases and slow down global manufacturing and production. The trade war led to market turbulence for semiconductor chipmakers. The U.S. is opposing foreign-made chips manufactured with American technology from being sold to China. The economic fallout, the heightened concern about vulnerabilities and dependencies, and the rising concern over geopolitical conflicts resulting from the disruptive shortage have also fueled the tech war between the U.S. and China. This has led to inflated pricing and constraints on raw materials, affecting semiconductor manufacturing and distribution to a certain extent.
Further, ongoing conflicts between Russia and Ukraine have escalated into hybrid warfare and digital skirmishes with the potential to cripple industrial infrastructure. The situation has been evolving unpredictably, and organizations and industries have been alert, anticipating, and planning for various scenarios. This has also affected the growth of the semiconductor manufacturing equipment market to a certain extent.
The semiconductor manufacturing equipment market is segmented by type (front-end equipment [silicon wafer manufacturing equipment, wafer fabrication equipment, other front-end equipment], back-end equipment [testing equipment, assembling & packaging equipment, other back-end equipment]), dimension (2D, 2.5D, 3D), component (memory, logic, analog, micro processing units [MPUs], optical devices, discrete devices, microcontroller units [MCUs], sensors, digital signal processors [DSPs]), end user (integrated device manufacturers [IDMs], foundry, outsourced semiconductor assembly & test [OSAT]), and geography. The study also evaluates industry competitors and analyses the market at the regional and country levels.
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Based on type, the global semiconductor manufacturing equipment market is broadly segmented into front-end equipment and back-end equipment. Front-end equipment is further segmented into silicon wafer manufacturing equipment, wafer fabrication equipment, and other front-end equipment. Back-end Equipment is further segmented into testing equipment, assembling & packaging equipment, and other back-end equipment. In 2023, the front-end equipment segment is estimated to account for the larger share of the global semiconductor manufacturing equipment market. This segment is also expected to register the highest CAGR during the forecast period. The large market share of this segment is attributed to the growing consumer electronics market and the increasing number of foundries, rising demand for electric and hybrid vehicles, and the need to streamline production, improve yield and reliability, and minimize design and manufacturing errors.
Based on dimension, the global semiconductor manufacturing equipment market is segmented into 2D, 2.5D, and 3D. In 2023, the 3D segment is estimated to account for the largest share of the global semiconductor manufacturing equipment market. This segment is also expected to register the highest CAGR during the forecast period. The large market share of this segment is mainly attributed to the increasing need to automate required design steps, the growing demand for improved functionalities and miniaturization of portable hand-held devices, the need for rapid prototyping, and the rising need to deliver better products in a shorter amount of time.
Based on component, the global semiconductor manufacturing equipment market is segmented into memory, logic, analog, microprocessing units (MPUs), optical devices, discrete devices, microcontroller units (MCUs), sensors, and digital signal processors (DSPs). In 2023, the memory segment is estimated to account for the largest share of the global semiconductor manufacturing equipment market. This segment is also expected to register the highest CAGR during the forecast period. The large market share of this segment is attributed to the increasing use of memory devices in the automotive sector for infotainment & navigation systems and advanced safety devices, decreasing prices of memory devices; and increasing consumption of memory in electronics devices, rising investment in various research & development activities for the development of existing and forthcoming memory devices to increase efficiency.
Based on end user, the global semiconductor manufacturing equipment market is segmented into integrated device manufacturers (IDMs), foundries, and outsourced semiconductor assembly & test (OSAT). In 2023, the integrated device manufacturers segment is estimated to account for the largest share of the global semiconductor manufacturing equipment market. This segment is also expected to register the highest CAGR during the forecast period. The large market share of this segment is attributed to the significant presence of IDMs in the market, the increasing consumption of consumer electronics devices, and the growing need to provide design and foundry services to other semiconductor companies.
Based on geography, the global semiconductor manufacturing equipment market is segmented into North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa. In 2023, Asia-Pacific is estimated to account for the largest share of the global semiconductor manufacturing equipment market, followed by Europe and North America. The region is also expected to witness rapid growth during the forecast period. The large market share of Asia-Pacific is mainly attributed to the rising demand for semiconductor manufacturing equipment, rapid growth in automotive and industrial electronics, the proliferation of IoT devices, the presence of major players in Taiwan and China, increasing need for high-quality processing equipment for semiconductive materials, and increasing government initiatives to support semiconductor industries.
The report also includes an extensive assessment of the key growth strategies adopted by the leading market participants between 2020 and 2022. The key players operating in the semiconductor manufacturing equipment market are Tokyo Electron Limited (Japan), Lam Research Corporation (U.S.), SCREEN Holdings Co., Ltd. (Japan), Teradyne, Inc. (U.S.), Advantest Corporation (Japan), Hitachi High-Tech Corporation (Japan), Applied Materials, Inc. (U.S.), KLA Corporation (U.S.), Plasma-Therm (U.S.), ASML (Netherlands), Taiwan Semiconductor Manufacturing Company Limited (Taiwan), Ferrotec Holdings Corporation (Japan), Canon Machinery Inc. (Japan), Veeco Instruments Inc. (U.S.), Onto Innovation Inc. (U.S.), Nordson Corporation (U.S.), and Tokyo Seimitsu Co., Ltd. (Japan).
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Scope of the report:
Semiconductor Manufacturing Equipment Market by Type
- Front-end Equipment
- Silicon Wafer Manufacturing Equipment
- Wafer Fabrication Equipment
- Other Front-end Equipment
- Back-end Equipment
- Testing Equipment
- Assembling & Packaging Equipment
- Other Back-end Equipment
Semiconductor Manufacturing Equipment Market, by Dimension
- 2D
- 2.5D
- 3D
Semiconductor Manufacturing Equipment Market, by Component
- Memory
- Logic
- Analog
- Microprocessing Units (MPUs)
- Optical Devices
- Discrete Devices
- Microcontroller Units (MCUs)
- Sensors
- Digital Signal Processors (DSPs)
Semiconductor Manufacturing Equipment Market, by End User
- Integrated device manufacturers (IDMs)
- Foundries
- Outsourced Semiconductor Assembly and Test (OSAT)
Semiconductor Manufacturing Equipment Market, by Geography
- North America
- U.S.
- Canada
- Europe
- U.K.
- Germany
- France
- Italy
- Spain
- Netherlands
- Denmark
- Sweden
- Rest of Europe
- Asia-Pacific
- China
- India
- Japan
- Taiwan
- South Korea
- Singapore
- Malaysia
- Rest of Asia-Pacific
- Latin America
- Middle East & Africa
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About Meticulous Research®
Meticulous Research® was founded in 2010 and incorporated as Meticulous Market Research Pvt. Ltd. in 2013 as a private limited company under the Companies Act, 1956. Since its incorporation, the company has become the leading provider of premium market intelligence in North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa.
The name of our company defines our services, strengths, and values. Since the inception, we have only thrived to research, analyze, and present the critical market data with great attention to details. With the meticulous primary and secondary research techniques, we have built strong capabilities in data collection, interpretation, and analysis of data including qualitative and quantitative research with the finest team of analysts. We design our meticulously analyzed intelligent and value-driven syndicate market research reports, custom studies, quick turnaround research, and consulting solutions to address business challenges of sustainable growth.
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Artificial Intelligence
Fingerprint Sensor Market worth $5.9 billion by 2029 – Exclusive Report by MarketsandMarkets™
CHICAGO, May 27, 2024 /PRNewswire/ — The Fingerprint Sensor Market is projected to grow from USD 4.2 billion in 2024 and is estimated to reach USD 5.9 billion by 2029; it is expected to grow at a Compound Annual Growth Rate (CAGR) of 7.0% from 2024 to 2029 according to a new report by MarketsandMarkets™. The rise in number of identity threats is one of the key factors leading to emergence of fingerprint technologies. Identity theft refers to the illegal acquisition of an individual’s personal or financial details to perpetrate fraud, including unauthorized transactions. It occurs through various methods and inflicts harm on victims’ credit, finances, and reputation.
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Browse in-depth TOC on “Fingerprint Sensor Market” 100 – Tables60 – Figures200 – Pages
Fingerprint Sensor Market Report Scope:
Report Coverage
Details
Market Revenue in 2024
$ 4.2 billion in 2024
Estimated Value by 2029
$ 5.9 billion
Growth Rate
Poised to grow at a CAGR of 7.0%
Market Size Available for
2020–2029
Forecast Period
2024–2029
Forecast Units
Value (USD Million/Billion)
Report Coverage
Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
Segments Covered
By technology, sensor technology, type, end-use application and Region
Geographies Covered
North America, Europe, Asia Pacific, and Rest of World
Key Market Challenge
Sensor performance limitations
Key Market Opportunities
Increased adoption of IoT-based biometric technology
Key Market Drivers
Rise in number of identity threats leading to emergence of fingerprint technologies
Area & Touch sensors in the sensor type segment is expected to witness higher CAGR during the forecast period.
Area & touch sensors segment is expected to witness a higher CAGR during the forecast period in the fingerprint sensor market. These sensors activate upon physical contact with an object or individual and are more sensitive compared to traditional buttons or manual controls. They provide users with a seamless and responsive experience, making them ideal for modern electronic devices where sleek design and user convenience are paramount.
The 2D segment in the fingerprint sensor market is expected to capture higher share during the forecast period.
2D sensor technology captures a person’s fingerprint pattern, including ridges and valleys, in two dimensions using a single plane of lasers to measure the X and Y dimensions. This technology is primarily utilized for detection and ranging tasks. Due to its affordability, 2D sensor technology remains popular among OEMs, especially in mobile devices requiring compact sensors to meet the preferences of end users. Key players such as Synaptics Incorporated (US), Fingerprints (Sweden), and Shenzhen Goodix Technology Co., Ltd. (China) offer 2D sensors for various consumer electronics and applications.
Ultrasonic is expected to witness the highest CAGR in the fingerprint sensor market during the forecast period.
Ultrasonic fingerprint sensors utilize sound waves to penetrate the outer layers of the skin, enabling the capture of three-dimensional (3D) details and distinct fingerprint characteristics like ridges and sweat pores. Unlike current capacitive touch-based fingerprint technologies, ultrasonic sensors can read both the epidermal and dermal layers of the skin, allowing for the capture of fine details. Consequently, these sensors can accurately read wet fingers or those with ruptured or damaged skin. The continuous advancements in sensing technology are expected anticipated to propel the growth of the ultrasonic fingerprint sensor market. In January 2022, vivo (China) announced the 1000 9 Pro smartphone with Qualcomm’s 3D Sonic Max ultrasonic fingerprint sensor. The new smartphone is based on Snapdragon 8 Gen 1 processor. The Qualcomm 3D Sonic Max in the IQ00 9 Pro enables a super-fast one-tap fingerprint registration process.
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North America is expected to hold the second largest share of the fingerprint sensor industry during the forecast period.
North America is driven by the increasing adoption of biometric authentication across various sectors, particularly consumer electronics, government, and commercial domains. The US Department of Homeland Security (DHS) has been actively promoting the use of biometric technologies, including fingerprint sensors, for enhancing border security and immigration processes. The DHS’s Biometric Entry-Exit Program has facilitated the deployment of fingerprint scanners at various ports of entry, contributing to the market’s growth in the region. According to November 2023 statistics by US Department of Homeland Security (DHS), 1,018,349 persons obtained lawful permanent resident status in year 2022 compared to 740,002 persons in 2021, which is 37.6% y-o-y increase.
Key Players
Major vendors in the fingerprint sensor companies include Shenzhen Goodix Technology Co., Ltd. (China), Fingerprints (Sweden), Synaptics Incorporated (US), Apple Inc. (US) NEXT Biometrics (Norway), Novatek Microelectronics Corp. (Taiwan), Qualcomm Technologies, Inc. (US) among others.
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Browse Adjacent Market: Semiconductor and Electronics Market Research Reports &Consulting
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Artificial Intelligence
Cloud Analytics Market worth $118.5 billion by 2029- Exclusive Report by MarketsandMarkets™
CHICAGO, May 27, 2024 /PRNewswire/ — The market for cloud analytics has a promising future because of the acceptance of real-time analytics, the expansion of big data and IoT, and the integration of AI and machine learning. Its adoption across multiple industries will be further accelerated by improved security, edge computing integration, and user-friendly platforms that prioritise data-driven decision-making and customised customer experiences.
The Cloud Analytics Market is estimated to grow from USD 35.7 billion in 2024 to USD 118.5 billion in 2029, at a CAGR of 27.1% during the forecast period, according to a new report by MarketsandMarkets™. Cloud analytics revolutionizes data storage and analysis by harnessing the power of the cloud. By storing and analyzing data in the cloud, businesses can extract actionable insights crucial for both SMEs and large enterprises. This approach facilitates identifying patterns, predicting future outcomes, and gaining valuable insights. Cloud analytics offers an opportunity to consolidate data and convert it into actionable intelligence while reducing procurement and maintenance costs. It involves utilizing both cloud-stored data and the rapid computing power of the cloud for faster analytics. However, with cloud infrastructure, organizations gain access to scalable, secure, and efficient data storage and processing solutions, enabling them to meet the demands of big data and drive innovation.
Browse in-depth TOC on “Cloud Analytics Market”
333 – Tables 66 – Figures342 – Pages
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Scope of the Report
Report Metrics
Details
Market size available for years
2019–2029
Base year considered
2023
Forecast period
2024–2029
Forecast units
USD Billion
Segments Covered
Offering, Data Type, Data Processing, Vertical, and Region
Geographies covered
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
Companies covered
IBM (US), SAS Institute (US), Oracle (US), Google (US), Microsoft (US), Teradata (US), Salesforce (US), AWS (US), NetApp (US), Qilk (US), Sisense (US), SAP (Germany), Atos (France), Altair (US), Microstrategy (US), Tibco Software (US), Hexaware Technologies (India), Zoho (India), Rackspace Technology (US), Splunk (US), Cloudera (US), Domo (US), Hewlett Packard Enterprise (US), Incorta (US), Tellius (US), Rapyder (US), Hitachi Vantara (US), Board International (Switzerland), Ridge (Israel), Jaspersoft (US), Yellowfin (Australia), Deonodo (US), GoodData (US), Thoughtspot (US), and Infogain (US)
By offering the services segment to account for higher CAGR during the forecast period
Services segment in the Cloud Analytics Market have experienced remarkable growth in the Cloud Analytics Market, fueled by the increasing adoption of data-driven decision-making across industries. These services offer businesses the capability to analyze vast amounts of data stored in the cloud swiftly and efficiently, enabling them to extract valuable insights for strategic planning, optimization, and innovation. With the scalability and flexibility of cloud infrastructure, analytics services can accommodate diverse data types and analytical workloads, empowering organizations to derive actionable intelligence from their data in real time. As businesses continue to prioritize agility and competitiveness, the demand for cloud analytics services is expected to soar, driving further innovation and expansion in the Cloud Analytics Market landscape.
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By Type, advanced analytics solution is expected to hold the largest market size for the year 2024
The surge in advanced analytics adoption within the Cloud Analytics Market is reshaping the landscape of data-driven decision-making. Organizations across diverse sectors are increasingly turning to advanced analytics solutions hosted on cloud platforms to extract deeper insights from their data. This trend stems from the growing realization that traditional analytics methods are no longer sufficient to cope with the complexities of modern data ecosystems. Advanced analytics, powered by machine learning algorithms, predictive modeling, and AI, offer unparalleled capabilities to uncover hidden patterns, forecast trends, and optimize business processes. By leveraging the scalability, flexibility, and cost-effectiveness of cloud infrastructure, businesses can access powerful analytics tools without the burden of hefty upfront investments in hardware and software. As a result, the Cloud Analytics Market is witnessing rapid expansion, fueled by the transformative potential of advanced analytics in driving innovation, enhancing operational efficiency, and gaining a competitive edge in today’s data-driven economy.
By Vertical, Healthcare & Life Sciences is projected to grow at the highest CAGR during the forecast period
The healthcare and life sciences sector is experiencing a transformative shift with the emergence of cloud analytics. This technology integrates vast amounts of data from various sources, including electronic health records, wearable devices, and genomic information, to derive meaningful insights and drive informed decision-making. Cloud analytics offers scalability, flexibility, and cost-effectiveness, enabling organizations to efficiently manage and analyze massive datasets that were previously challenging to handle. By leveraging advanced analytics techniques such as machine learning and predictive modeling, healthcare providers and life sciences companies can enhance patient care, optimize clinical workflows, and accelerate drug discovery processes. Moreover, cloud-based analytics facilitates collaboration among researchers, clinicians, and stakeholders, fostering innovation and driving advancements in personalized medicine and population health management. As the industry continues to embrace digital transformation, cloud analytics stands as a cornerstone for unlocking the full potential of data-driven healthcare and life sciences initiatives.
Asia Pacific is expected to grow at the highest CAGR during the forecast period
The Asia Pacific region is experiencing a significant surge in the adoption of cloud analytics, reshaping how businesses make data-driven decisions. Companies spanning various industries are embracing cloud-based analytics platforms to optimize operations, foster innovation, and gain actionable insights. Additionally, the ubiquitous nature of mobile devices and internet connectivity has heightened the demand for real-time analytics accessible from anywhere. Governments and enterprises recognize the strategic value of harnessing analytics to maintain competitiveness in the global marketplace. Consequently, investments in cloud analytics technologies and talent development are escalating, positioning the Asia Pacific region as a pivotal player in the global cloud analytics landscape.
Top Key Companies in Cloud Analytics Market:
The significant cloud analytics software and service providers include IBM (US), SAS Institute (US), Oracle (US), Google (US), Microsoft (US), Teradata (US), Salesforce (US), AWS (US), NetApp(US), Qilk(US), Sisense (US), SAP (Germany), Atos (France), Altair (US), Microstrategy (US), Tibco Software (US), Hexaware Technologies (India), Zoho (India), Rackspace Technology (US), Splunk (US), Cloudera (US), Domo (US), Hewlett Packard Enterprise (US), Incorta (US), Tellius (US), Rapyder (US), Hitachi Vantara (US), Board International (Switzerland), Ridge (Israel), Jaspersoft (US), Yellowfin (Australia), Deonodo(US), GoodData(US), Thoughtspot (US), and Infogain (US). These companies have used organic and inorganic growth strategies such as product launches, acquisitions, and partnerships to strengthen their position in the Cloud Analytics Market.
Recent Developments:
In January 2024, Salesforce unveiled fresh Commerce Cloud tools leveraging generative AI and data-driven insights, enhancing every customer interaction for heightened loyalty and revenue growth.In February 2024, IBM and Wipro strengthened their collaboration to offer clients expanded AI services and support. This collaboration aims to utilize AI technologies to tackle various business challenges and foster innovation across industries.In June 2023, Salesforce and Google formed a partnership. The partnership between Salesforce and Google focuses on integrating Google’s AI capabilities into Salesforce’s products, enhancing their analytics offerings.In May 2023, Microsoft launched Microsoft Fabric Data Analytics which is a cutting-edge platform tailored for the AI era, facilitating seamless integration of analytics and AI capabilities into data processing workflows. It streamlines data ingestion, preparation, and analysis, enabling organizations to derive actionable insights efficiently.In August 2022, Teradata introduced VantageCloud Lake, a cloud-native service designed to simplify data lakes for businesses, enabling seamless management and analytics of vast data sets.Inquire Before Buying@ https://www.marketsandmarkets.com/Enquiry_Before_BuyingNew.asp?id=959
Cloud Analytics Market Advantages:
Platforms for cloud analytics offer scalable resources, making it simple for companies to modify their requirements for storage and processing power in response to demand. Because of its adaptability, businesses may manage different data volumes without having to make costly infrastructure investments.Businesses can lower their capital hardware and software costs by utilising cloud analytics. Pay-as-you-go cloud service pricing allows businesses to optimise their total IT expenditure by only paying for the resources they really utilise.Compared to on-premises systems, cloud analytics solutions may be implemented and deployed far more quickly. This speedy deployment shortens the time to insight, allowing companies to begin data analysis and value extraction right away.Platforms for cloud-based analytics enable remote access to analytics tools and data from any location with an internet connection. Team members can collaborate on data projects regardless of location thanks to this accessibility, which fosters teamwork.Advanced analytics features like machine learning, artificial intelligence, and predictive analytics are frequently included in cloud analytics solutions. Organisations can gain deeper insights and make better decisions with the aid of these technologies.Businesses can analyse data as it is generated with the use of cloud analytics solutions, which provide real-time data processing and analytics. Applications that need instant insights, like fraud detection, operational monitoring, and customer engagement, depend on this real-time capacity.Platforms for cloud analytics can easily interface with a range of data sources, such as databases, data lakes, outside apps, and Internet of Things gadgets. A unified perspective of corporate operations and thorough data analysis are guaranteed by this integration capabilities.Report Objectives
To define, describe, and predict the Cloud Analytics Market by offering, data type, data processing, vertical, and regionTo describe and forecast the Cloud Analytics Market, in terms of value, by region—North America, Europe, Asia Pacific, Middle East & Africa, and Latin AmericaTo provide detailed information regarding major factors influencing the market growth (drivers, restraints, opportunities, and challenges)To strategically analyze micro markets with respect to individual growth trends, prospects, and contributions to the overall Cloud Analytics MarketTo profile key players and comprehensively analyze their market positions in terms of ranking and core competencies, along with detailing the competitive landscape for market leadersTo analyze competitive developments such as joint ventures, mergers and acquisitions, product developments, and ongoing research and development (R&D) in the Cloud Analytics MarketTo provide the illustrative segmentation, analysis, and projection of the main regional marketsBrowse Adjacent Markets: Analytics Market Research Reports & Consulting
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Get access to the latest updates on Cloud Analytics Companies and Cloud Analytics Industry
About MarketsandMarkets™
MarketsandMarkets™ has been recognized as one of America’s best management consulting firms by Forbes, as per their recent report.
MarketsandMarkets™ is a blue ocean alternative in growth consulting and program management, leveraging a man-machine offering to drive supernormal growth for progressive organizations in the B2B space. We have the widest lens on emerging technologies, making us proficient in co-creating supernormal growth for clients.
Earlier this year, we made a formal transformation into one of America’s best management consulting firms as per a survey conducted by Forbes.
The B2B economy is witnessing the emergence of $25 trillion of new revenue streams that are substituting existing revenue streams in this decade alone. We work with clients on growth programs, helping them monetize this $25 trillion opportunity through our service lines – TAM Expansion, Go-to-Market (GTM) Strategy to Execution, Market Share Gain, Account Enablement, and Thought Leadership Marketing.
Built on the ‘GIVE Growth’ principle, we work with several Forbes Global 2000 B2B companies – helping them stay relevant in a disruptive ecosystem. Our insights and strategies are molded by our industry experts, cutting-edge AI-powered Market Intelligence Cloud, and years of research. The KnowledgeStore™ (our Market Intelligence Cloud) integrates our research, facilitates an analysis of interconnections through a set of applications, helping clients look at the entire ecosystem and understand the revenue shifts happening in their industry.
To find out more, visit www.MarketsandMarkets™.com or follow us on Twitter, LinkedIn and Facebook.
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Artificial Intelligence
PolyU research finds improving AI large language models helps better align with human brain activity
HONG KONG, May 27, 2024 /PRNewswire/ — With generative artificial intelligence (GenAI) transforming the social interaction landscape in recent years, large language models (LLMs), which use deep-learning algorithms to train GenAI platforms to process language, have been put in the spotlight. A recent study by The Hong Kong Polytechnic University (PolyU) found that LLMs perform more like the human brain when being trained in more similar ways as humans process language, which has brought important insights to brain studies and the development of AI models.
Current large language models (LLMs) mostly rely on a single type of pretraining – contextual word prediction. This simple learning strategy has achieved surprising success when combined with massive training data and model parameters, as shown by popular LLMs such as ChatGPT. Recent studies also suggest that word prediction in LLMs can serve as a plausible model for how humans process language. However, humans do not simply predict the next word but also integrate high-level information in natural language comprehension.
A research team led by Prof. Li Ping, Dean of the Faculty of Humanities and Sin Wai Kin Foundation Professor in Humanities and Technology at PolyU, has investigated the next sentence prediction (NSP) task, which simulates one central process of discourse-level comprehension in the human brain to evaluate if a pair of sentences is coherent, into model pretraining and examined the correlation between the model’s data and brain activation. The study has been recently published in the academic journal Sciences Advances.
The research team trained two models, one with NSP enhancement and the other without, both also learned word prediction. Functional magnetic resonance imaging (fMRI) data were collected from people reading connected sentences or disconnected sentences. The research team examined how closely the patterns from each model matched up with the brain patterns from the fMRI brain data.
It was clear that training with NSP provided benefits. The model with NSP matched human brain activity in multiple areas much better than the model trained only on word prediction. Its mechanism also nicely maps onto established neural models of human discourse comprehension. The results gave new insights into how our brains process full discourse such as conversations. For example, parts of the right side of the brain, not just the left, helped understand longer discourse. The model trained with NSP could also better predict how fast someone read – showing that simulating discourse comprehension through NSP helped AI understand humans better.
Recent LLMs, including ChatGPT, have relied on vastly increasing the training data and model size to achieve better performance. Prof. Li Ping said, “There are limitations in just relying on such scaling. Advances should also be aimed at making the models more efficient, relying on less rather than more data. Our findings suggest that diverse learning tasks such as NSP can improve LLMs to be more human-like and potentially closer to human intelligence.”
He added, “More importantly, the findings show how neurocognitive researchers can leverage LLMs to study higher-level language mechanisms of our brain. They also promote interaction and collaboration between researchers in the fields of AI and neurocognition, which will lead to future studies on AI-informed brain studies as well as brain-inspired AI.”
Media ContactMs Annie WongSenior Manager, Public AffairsTel: +852 3400 3853Email: [email protected]
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