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KLA, a Fortune 500 company with 12,000+ global employees, is a leading supplier of process control and process enabling solutions for the global semiconductor and electronics industry. At KLA India, engineers, data scientists and problem-solvers design solutions that improve the performance of KLA's process control products and facilitate customer success. KLA's new state-of-the-art, high-tech research and development center serves as a cultural and collaboration hub for the engineering teams.

"KLA is at the forefront of using AI technology in our process control systems to identify and isolate critical issues in chip manufacturing," stated Ahmad Khan, president, semiconductor process control at KLA. "To expand the reach of AI in our products and develop the next generation of AI innovations, we created our new AI-ACL research facility. Our researchers and engineers at AI-ACL join the AI experts at our AI Modeling and Center of Excellence in Michigan to form a global team committed to advancing the boundaries of AI, software, image processing and physics modeling."

Officiating over the opening of both facilities, Prof. Bhaskar Ramamurthy, Director of IIT Madras said, "KLA and IIT Madras have been collaborating for over 15 years. We look forward to an expanded collaboration with KLA in AI, advanced parallel computing, and quantum computing research for applications in the semiconductor inspection and metrology domain. The IIT Madras Research Park ecosystem is a perfect enabler for such an industry with academic collaboration that is bringing together our resident experts, top student researchers and industry's best minds. I also congratulate KLA on the grand opening of its new office in RMZ Millenia-II today."

Beyond expanding business in India, KLA prioritizes making a positive impact on the local community. In May, KLA created a $550,000 India pandemic relief fundto aid healthcare facilities in procuring critically-needed equipment in the fight against Covid-19. The donation also supports a long-term investment to expand ICU capacity in regional hospitals and better address the needs of under-privileged communities.

Those interested in careers with KLA India may find more information at http://www.kla.com/careers/locations/India.

About KLA:

KLA develops industry-leading equipment and services that enable innovation throughout the electronics industry. We provide advanced process control and process-enabling solutions for manufacturing wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. In close collaboration with leading customers across the globe, our expert teams of physicists, engineers, data scientists and problem-solvers design solutions that move the world forward. Additional information may be found atwww.kla.com.

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KLA Corporation Opens New Artificial Intelligence-Advanced Computing Lab at Indian Institute of Technology Madras Research Park - PR Newswire India

How should an essay be marked? You might think a teacher should simply read it and make a judgment based on the impression it makes: logically coherent, offers evidence to back up its case, reads well, is original feels like an A. But that, obviously, is risky. Its subjective. What stirs one assessor might not appeal to another.

So maybe there needs to be an agreed rubric. The essay must cover certain key points, achieve certain goals. But the danger then is that essays become box-ticking exercises, that a student could doggedly go through the checklist and achieve top marks despite making little sense: or a brilliant essay might omit one point and so be marked down.

As Daisy Christodoulou, director of education at No More Marking, points out, the debate between the spirit and the letter of the law is ancient, and has relevance to modern football. In Marks gospel, Christ and the disciples are criticised by the pharisees for breaching the prohibition on working on the sabbath by picking some heads of grain. To which Christ replies that the sabbath was made for man, not man for the sabbath. Christ implies that the specific laws are less important than the spirit that underlies them; for the pharisees the laws are what make religion: to rely on the spirit is to tolerate rule-breaking and self-indulgence.

In football, the two ends of the spectrum tend to be referred to as consistency and common sense. We fans, journalists, players, managers feel instinctively that an inconsequential and non-deliberate nudge on a player moving away from goal is too trivial to be punished with a penalty, a three-quarters chance of a goal, and so call for common sense, and yet we want that common sense somehow to be universal in application, for referees also to feel the situation as we do.

VAR has not changed that, but it has made the issue more fraught. Once inconsistencies could be written off as inevitable consequences of the pace of the game; we accepted, up to a point, that referees chasing along behind the play could not be expected to see everything and so accepted some latitude. But VAR extends the illusion of perfectibility. If we can see everything from a multitude of angles and slow it down, should we not be able to agree on a decision? Very clearly, we cannot.

Take handball, in some ways the simplest of laws. There is no issue of a level of acceptable force, or which player initiated contact, or whether something may conceivably have endangered an opponent there is a ball, there is a hand and there is a question of intent. And yet since the introduction of VAR, football has tied itself in knots trying to decide what a handball is.

As an example, take the handball for which Ivan Perisic was penalised in the 2018 World Cup final as a throw-in glanced off Paul Pogba, who was a foot in front of him, and on to his arm, which was very slightly extended from his body as he landed having jumped for a header. Not merely did Perisic have no time to react, he was unsighted. By the letter of the law, perhaps it was a handball, but it felt wrong, a game turned by the random bounce of a ball on to an opponent who had no way of avoiding it and that in part explains the constant revisions to and extension of the law over the past few years.

The handball law used to comprise only 20 words, with three advisory bullet-points to help referees decide what might constitute deliberate. The law as it stands is 252 words long, none of it advisory, and also includes a diagram to explain the point at which the shoulder becomes the arm.

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But adding text doesnt necessarily clarify the issue; rather it risks adding more scope for interpretation. In marking, Christodoulou favours a process called comparative judgment, by which teachers are given a series of match-ups between a randomly selected pair of the essays under consideration. They judge which of each pair is better, without using a mark scheme. Each essay is judged several times in different match-ups by different assessors, and all the judgments are then combined to provide a mark and a rank order.

Quite apart from the practical benefits the process is apparently much quicker than traditional marking it simultaneously allows for the subjectivity of knowing what a good essay is, while at the same time making judgment less reliant on the individual view of a single teacher.

No More Marking has used this approach to assess half a million pieces of student writing over the past few years. Christodoulou sees the mental challenge of applying a mark scheme to an essay as similar to applying a rule book to a handball incident and believes comparative judgment could improve decisions in football, too.

Take a panel of stakeholders referees, managers, players, journalists, fans show them a series of pairs of handball incidents and ask them to judge which one is more deserving of a free-kick. A consensus would build: some incidents would obviously be handballs and some would obviously not, while others would be less clear-cut.

That would at the very least refine the discussion, using practical examples rather than convoluted verbal descriptions, and could then be used to amend the law and the way it is explained, not only to referees but to players and the public.

But what could revolutionise refereeing is what comes next. The technology is not yet sufficiently advanced but, before too long, with sufficient data, it is at least theoretically possible that footage of a handball decision could be examined not by a VAR official but by artificial intelligence, which could then access the previous incident most similar to the one under discussion and see whether a majority of the panel had decided that should be deemed an offence. There would then be consistency within the common-sense instincts of the panel, the letter of the law effectively being conditioned by the spirit of the law. We are not there yet, but the possibility is tantalising.

Read more from the original source:

Using artificial intelligence to rule on handball is a tantalising possibility - The Guardian

Abstract: Global Artificial Intelligence (AI) Market to Reach US$291. 5 Billion by the Year 2026 . Artificial Intelligence (AI) is emerging as one of the promising technologies, against the backdrop of fast paced digitalization and rapidly evolving technology landscape globally.

New York, Oct. 27, 2021 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Artificial Intelligence (AI) Industry" - https://www.reportlinker.com/p05478480/?utm_source=GNW AI technology is associated with making machines and related processes intelligent through the use of advanced computer programming solutions. The AI technology market is poised to grow at a robust pace driven by its increasing adoption in an expanding range of applications in varied industries. The growing need to analyze and interpret burgeoning volumes of data and the escalating demand for advanced AI solutions to improve customer services are expected to fuel growth in the AI market. With significant improvements being seen in data storage capacity, computing power and parallel processing capabilities, the adoption of AI technology in various end-use sectors is on the rise. The rising adoption of cloud-based services and applications, rapid growth of big data, and the increasing need for intelligent virtual assistants are also contributing to the rapid growth of AI market. The advent of face, image, and voice recognition technologies is further favoring growth in the global market.

Amid the COVID-19 crisis, the global market for Artificial Intelligence (AI) estimated at US$47.1 Billion in the year 2020, is projected to reach a revised size of US$291.5 Billion by 2026, growing at a CAGR of 34.3% over the analysis period. Services, one of the segments analyzed in the report, is projected to grow at a 34.1% CAGR to reach US$154.8 Billion by the end of the analysis period. After a thorough analysis of the business implications of the pandemic and its induced economic crisis, growth in the Software segment is readjusted to a revised 31.7% CAGR for the next 7-year period. This segment currently accounts for a 37.9% share of the global Artificial Intelligence (AI) market. The increasing penetration of chatbots or virtual assistants for providing customer assistance in various end-use industries including e-commerce and banking is expected to further enhance demand for AI-based software and systems.

The U.S. Market is Estimated at $28.9 Billion in 2021, While China is Forecast to Reach $53.6 Billion by 2026

The Artificial Intelligence (AI) market in the U.S. is estimated at US$28.9 Billion in the year 2021. The country currently accounts for a 41.4% share in the global market. China, the world`s second largest economy, is forecast to reach an estimated market size of US$53.6 Billion in the year 2026 trailing a CAGR of 40.9% through the analysis period. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 28.8% and 30.2% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 32.5% CAGR while Rest of European market (as defined in the study) will reach US$70.9 Billion by the end of the analysis period. The dominant share of the US is mainly attributed to the widespread adoption of AI technology in several end-use industries including media, e-commerce and manufacturing. Increased funding for developing and advancing AI technology and applications, and a robust technical adoption base are also favoring growth. Europe, is the second largest regional AI market. Europe is expected to witness a significant increase in the deployments of cloud-based AI solutions, driven by the growing consumer demand for on-demand and faster access to data and relatively easy document control. Europe`s AI market is likely to benefit from the European Commission`s plans to invest 20 billion for AI research during the period 2018-2020 in order to fuel R&D initiatives for businesses and government. Growth in Asia-Pacific including China is propelled by the increasing adoption of natural language processing (NLP) and deep learning technologies in sectors such as marketing, finance, law, and agriculture. The market also benefits from the rapid pace of improvements being seen in computing power, data storage capacity and processing capabilities, which facilitate adoption of AI technology in sectors such as healthcare and automotive.

Hardware Segment to Reach $71.2 Billion by 2026

The constant decline in hardware costs is fueling growth in the hardware segment. By type of hardware, processor captures the largest share of the AI chipsets market, due mainly to the rising demand for high computing processors for running AI algorithms in servers and for the development of edge devices. In the global Hardware segment, USA, Canada, Japan, China and Europe will drive the 38.2% CAGR estimated for this segment. These regional markets accounting for a combined market size of US$7.8 Billion in the year 2020 will reach a projected size of US$74.8 Billion by the close of the analysis period. China will remain among the fastest growing in this cluster of regional markets. Led by countries such as Australia, India, and South Korea, the market in Asia-Pacific is forecast to reach US$9.8 Billion by the year 2026. Select Competitors (Total 300 Featured)

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Accenture

AIBrain, Inc.

Amazon Web Services

Baidu, Inc.

BIGO Technology

ByteDance Ltd

Cisco Systems, Inc.

CloudMinds

Dell Technologies

eGain Corporation

Esri

Facebook, Inc.

General Electric Company

Google, Inc.

Habana Labs Ltd

Inspur

Intel Corporation

International Business Machines Corporation (IBM)

IPsoft Inc

Micron Technology, Inc.

Microsoft Corporation

Mobileye, an Intel Company

NetEase Fuxi Lab

NetEase, Inc

Next IT Corporation

NICE inContact

Nuance Communications, Inc.

NVIDIA Corporation

Omron Robotics and Safety Technologies, Inc

Oracle Corporation

Rockwell Automation, Inc.

Salesforce.com, inc.

Samsung Electronics Co., Ltd.

SAP SE

SAS Institute Inc.

Siemens AG

Smartron India Private Limited

The Hewlett-Packard Company

Trifo

Xilinx, Inc.

Read the full report: https://www.reportlinker.com/p05478480/?utm_source=GNW

I. METHODOLOGY

II. EXECUTIVE SUMMARY

1. MARKET OVERVIEW Impact of Covid-19 and a Looming Global Recession 2020: A Year of Disruption & Transformation As the Race between the Virus & Vaccines Intensifies, Where is the World Economy Headed in 2021? EXHIBIT 1: World Economic Growth Projections (Real GDP, Annual % Change) for 2020 through 2022 Artificial Intelligence Gains Interest during COVID-19 Pandemic Artificial Intelligence Makes Significant Contribution in War against COVID-19 Machine Learning Benefits Healthcare Organizations AI-Powered Sentiment Analysis Scales & Shapes Vaccination Programs in US Industrial and Commercial Applications Take a Hit as COVID-19 Evolves Into an Economic Crisis EXHIBIT 2: Global PMI Index Points for the Years 2018, 2019 & 2020 EXHIBIT 3: Business Confidence Index (BCI) Points for 3Q 2019, 4Q 2019, 1Q 2020, & 2Q 2020 COVID-19-Led Budgetary Reticence Dampens Spending, but AI Enjoys Resilient Interest in Banking Sector Retailers Rely on AI during COVID-19 to Stay Afloat & Embrace New Normal Emphasis on Technology Adoption Elicits AI Implementation in Manufacturing Industry AI & Machine Learning to Redefine Manufacturing Operations Artificial Intelligence (AI): A Prelude Technologies Enabling AI Outlook Advances in Real World AI Applications Bolster Growth Inherent Advantages of AI Technology to Accelerate Adoption in Varied Applications Banking Sector Shows Unwavering Interest in AI AI Reshapes the Future of Manufacturing Industry AI-based Services Segment Captures Major Share of Global AI Market Developed Markets Dominate, Asia-Pacific to Spearhead Future Growth Deep Learning and Digital Assistant Technologies Present Significant Growth Potential Major Challenges Faced in AI Implementation Competition AI Marketplace Characterized by Intense Competition EXHIBIT 4: Global Artificial Intelligence Market by Leading Vendors for 2020 Growing Focus on AI by Leading Tech Companies with Huge Financial Resources Investments in AI Startups on Rise EXHIBIT 5: Global AI Startup Funding (in US$ Million) for the Years 2014 through Q12020 EXHIBIT 6: Number of AI Startups with $1 Billion Valuations for the Years 2014-2020 EXHIBIT 7: AI Cumulative Funding (in US$ Billion) by Category (As of 2020) AI Applications and Major Startups Select Companies Raising AI Investments in 2020 EXHIBIT 8: Total Number of Investments in AI by Investor Type: April 2021 World Brands Recent Market Activity

2. FOCUS ON SELECT PLAYERS

3. MARKET TRENDS & DRIVERS AI Breakthroughs with Significant Potential to Radically Transform Future Machine Learning and AI-Assisted Platforms to Personalize Customer Experiences in Marketing Applications EXHIBIT 9: Ranking of Business Outcomes Realized through AI Application in Marketing Ecommerce Attracts Strong Growth Detailed Insight into how e-commerce makes use of AI 3x Faster Acceleration in E-Commerce Induced by the Pandemic Brings Out Automated Fulfilment of E-Commerce Orders as a Major Growth Driver EXHIBIT 10: Global B2C e-Commerce Market Reset & Trajectory - Growth Outlook (In %) For Years 2019 through 2025 EXHIBIT 11: Retail M-Commerce Sales as % of Retail E-commerce Sales Worldwide for the Years 2016, 2018, 2020 & 2022 AI Hosting at Edge to Drive Growth EXHIBIT 12: Global Edge Computing Market in US$ Billion: 2020, 2024, and 2026 AI-enabled Analysis and Forecasts Aid Organizations Make Profitable Decisions AI-Powered Biometric Security Solutions Gain Momentum EXHIBIT 13: Global Biometrics Market in US$ Billion: 2016, 2020, and 2025 New and Improved Concepts in ML and AI take Stage IIoT & AI Convergence Brings in Improved Efficiencies EXHIBIT 14: Global Breakdown of Investments in Manufacturing IoT (in US$ Billion) for the Years 2016, 2018, 2020 and 2025 Increasing Adoption of AI Technology to Boost AI Chipsets Market Combination of Robotics and AI Set to Cause Significant Disruption in Various Industries AI in Customer-Centric Operations Gain Momentum AI Innovations Widen Prospects Blockchain & Artificial Intelligence (AI): A Powerful Combination Notable Trends in the Artificial Intelligence Market Big Data Trends to Shape Future of Artificial Intelligence AI Exudes Potential to Mitigate Adversities Amid COVID-19 AI in Retail Market: Multi-Channel Retailing and e-Commerce Favor Segment Growth AI for a Competitive Edge for Retail Organizations Online Retailers Eye on Artificial Intelligence to Boost Business in Post-COVID-19 Era AI & Analytics Help Retailers Survive Economic & Operational Implications of COVID-19 AI for Fashion Retail and Beauty AI for Grocery, Electronics, and Home & Furniture Financial Sector: AI and Machine Learning Offer Numerous Gains Fintech Deploys AI to Target Millennials AI in Media & Advertising: Targeting Customers with Right Marketing Content COVID-19 Impacts Advertising Industry, Affects AI Investments EXHIBIT 15: COVID-19 Impact on Global Ad Spending: March 2020 Possibilities Galore for AI in Digital Marketing Marketing Functions Where AI is Yet Impossible to Deploy AI-Enabled CRM Market: Promising Growth Opportunities in Store Artificial Intelligence to Transform Delivery of Healthcare Services Healthcare AI Market to Experience Remarkable Expansion EXHIBIT 16: Global Healthcare AI Market - Percentage Breakdown by Application for 2020 EXHIBIT 17: Worldwide Current & Required Healthcare Spending as % of GDP AI in Medical Diagnostics and Pharmaceutical Sectors COVID-19 Spurs New Developments and Expedites AI Adoption in Healthcare Industry Developments Impacting AI in Healthcare Domain Artificial Intelligence Holds Potential to Accelerate Detection & Treatment of COVID-19 Detecting Personalized Therapeutic Targets Rising Prevalence of Diabetes to Drive AI Adoption in Diabetes Management Market EXHIBIT 18: World Diabetes Prevalence (2000-2045P) Barriers Restraining AI Adoption in Healthcare Sector Automotive AI Market: Need to Enhance Customer Experience and Increasing Focus on Autonomous Vehicles Propels Growth EXHIBIT 19: Automotive AI Market By Segment Slowdown in Automobile Production Hit AI Investments in Auto Sector EXHIBIT 20: Automobile Production % YoY Change Across Select Countries: 2020 Vs 2019 EXHIBIT 21: Reduction in Automotive Demand in 2020 (In Million Vehicles) EXHIBIT 22: World Automobile Production in Million Units: 2008 -2022 COVID-19 Outbreak to Speed up Digitalization & Automation in Automotive Sector Driverless Cars: The Ultimate Future of AI in Auto industry Automakers Focus on Integrating AI-Powered Driver Assist Features in Vehicles AI to Enhance Connectivity, Provide Infotainment and Enhance Safety in Vehicles AI for Smart Insurance Risk Assessment of Vehicles Artificial Intelligence Steps into Manufacturing Space to Transform Diverse Aspects Industrial IoT, Robotics and Big Data to Stimulate AI Implementations EXHIBIT 23: Global Investments on Industry 4.0 Technologies (in US$ Billion) for the Years 2017, 2020, & 2023 AI Moves from Factory Floor to Supply Chain and Beyond Machine Learning: Growing Role in Smart Manufacturing AI as a Service Market: Obviating the Need to Make Huge Initial Investments AI in Education Market to Exhibit Strong Growth EXHIBIT 24: Global Market for AI in Healthcare Sector (2019): Percentage Breakdown of Revenues by End-Use - Higher Education and K-12 Sectors Focus on ITS, IAL and Chatbots Favors Market Growth Agriculture Sector: A Promising Market for AI Implementations AI Technologies Used in Agricultural Activities - A Review AI Poised to Create Smarter Agriculture Practices in Post- COVID-19 Period Food & Beverage Industry to Leverage AI Capabilities to Resolve Production Issues and Match Up to Customer Expectations AI Adoption Gains Acceptance in Modern Warfare Systems in the Defense Sector Energy & Utilities: Complex Landscape and High Risk of Malfunctions Enhances Need for AI-based Systems COVID-19 Raises Demand for AI Technologies in Oil & Gas Sector AI in Construction Sector: Need for Cost Reduction and Safety at Construction Sites Drive Focus onto the Use of AI-based Solutions AI Contributing in Sustaining Critical Infrastructure Amid COVID-19

4. GLOBAL MARKET PERSPECTIVE Table 1: World Current & Future Analysis for Artificial Intelligence (AI) by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 2: World Historic Review for Artificial Intelligence (AI) by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 3: World 12-Year Perspective for Artificial Intelligence (AI) by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets for Years 2015, 2021 & 2027

Table 4: World Current & Future Analysis for Services by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 5: World Historic Review for Services by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 6: World 12-Year Perspective for Services by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 7: World Current & Future Analysis for Software by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 8: World Historic Review for Software by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 9: World 12-Year Perspective for Software by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 10: World Current & Future Analysis for Hardware by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 11: World Historic Review for Hardware by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 12: World 12-Year Perspective for Hardware by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 13: World Current & Future Analysis for Computer Vision by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 14: World Historic Review for Computer Vision by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 15: World 12-Year Perspective for Computer Vision by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 16: World Current & Future Analysis for Machine Learning by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 17: World Historic Review for Machine Learning by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 18: World 12-Year Perspective for Machine Learning by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 19: World Current & Future Analysis for Context Aware Computing by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 20: World Historic Review for Context Aware Computing by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 21: World 12-Year Perspective for Context Aware Computing by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 22: World Current & Future Analysis for Natural Language Processing by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 23: World Historic Review for Natural Language Processing by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 24: World 12-Year Perspective for Natural Language Processing by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 25: World Current & Future Analysis for Advertising & Media by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 26: World Historic Review for Advertising & Media by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 27: World 12-Year Perspective for Advertising & Media by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 28: World Current & Future Analysis for BFSI by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 29: World Historic Review for BFSI by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 30: World 12-Year Perspective for BFSI by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 31: World Current & Future Analysis for Healthcare by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 32: World Historic Review for Healthcare by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 33: World 12-Year Perspective for Healthcare by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 34: World Current & Future Analysis for Retail by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 35: World Historic Review for Retail by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 36: World 12-Year Perspective for Retail by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 37: World Current & Future Analysis for Automotive & Transportation by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 38: World Historic Review for Automotive & Transportation by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 39: World 12-Year Perspective for Automotive & Transportation by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 40: World Current & Future Analysis for Manufacturing by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 41: World Historic Review for Manufacturing by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 42: World 12-Year Perspective for Manufacturing by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 43: World Current & Future Analysis for Agriculture by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

Table 44: World Historic Review for Agriculture by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 45: World 12-Year Perspective for Agriculture by Geographic Region - Percentage Breakdown of Value Revenues for USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World for Years 2015, 2021 & 2027

Table 46: World Current & Future Analysis for Other End-Uses by Geographic Region - USA, Canada, Japan, China, Europe, Asia-Pacific and Rest of World Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2020 through 2027 and % CAGR

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Global Artificial Intelligence (AI) Market to Reach US$291.5 Billion by the Year 2026 - Yahoo Finance

Chennai:

Now that the former Google executive has a book out Tuesday on The Age of AI, written with Henry Kissinger and Daniel Huttenlocher, I wanted to ask him the same question about AI: Friend or foe? AI is imprecise, which means that it can be unreliable as a partner, he said when we met at his Chelsea office. Its dynamic in the sense that its changing all the time. Its emergent and does things that you dont expect. And, most importantly, its capable of learning. It will be everywhere. What does an AI-enabled best friend look like, especially to a child? What does AI-enabled war look like? Does AI perceive aspects of reality that we dont? Is it possible that AI will see things that humans cannot comprehend? I agree with Elon Musk that when we build AI without a kill switch, we are summoning the demon and that humans could end up, as Steve Wozniak said, as the family pets. (If were lucky.)

Talking about the alarms raised by the likes of Musk and Stephen Hawking, Schmidt said that they think that by unleashing AI, eventually, youll end up with a robot overlord thats 10 or 100 or 1,000 times smarter than the humans. My answer is different. I think all the evidence is that these AI systems are going to think, not like humans, but theyre going to be very smart. Were going to have to coexist. You dont think Siri and Alexa are going to kill us one night? No, he said. But they might become your childs best friend. Opinions on AI are wildly divergent. Jaron Lanier, the father of virtual reality, rolls his eyes at the digerati in Silicon Valley obsessed with the science-fiction fantasy of AI It can sometimes become a giant, false god, he told me. Youve got these nerdy guys who have an awful reputation for how they treat women, who get to be the life creators. You women with your petty little biological wombs cant stand up to us. Were making the big life here. Were the supergods of the future. We have known for a while that Silicon Valley is taking us down the drain. Preposterous claims that once could not have gotten traction on everything from Democratic paedophilia rings to rigged elections to vaccine conspiracy theories now spread at the speed of light. Teenage girls can be sent spiralling into depression by the glossy, deceptive world of Instagram, owned by the manipulative and greedy company formerly known as Facebook.

Schmidt said an Oxford student told him, about social media poison, The union of boredom and anonymity is dangerous. Especially at the intersection of addiction and envy. The question of whether we will lose control to AI may be pass. Technology is already manipulating us. Schmidt admits that the lack of foresight among the lords of the cloud about where technology was headed was foolish. Ill say, 10 years ago, when I worked really hard on these social networks, maybe this is just navet, but we never thought that governments would use them against citizens, like in 2016, with interference from the Russians.

We didnt think it would then stitch these special interest groups together with these violently strong belief systems. No one ever discussed it. I dont want to make the same mistake again with a new foundational technology.

He said that the National Security Commission on Artificial Intelligence, which he chaired earlier this year, concluded that America is still a little bit ahead of China in the technology race but China is overinvesting against us. The authors write that they are most worried about other countries developing AI-facilitated weapons with substantial destructive potential that may be able to adapt and learn well beyond their intended targets.

Dowd is a Columnist with NYT2021

The New York Times

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Implementation of artificial intelligence in healthcare is the most valuable discovery and invention of all time. Reading and comprehending diagnostic reports, medical advisories and efficient diagnosis are some crucial features endowed by the use of artificial intelligence algorithms. Consolidation of artificial intelligence and human management are together responsible for saving preventable deaths since its convergence. The strength to analyze big data makes artificial intelligence smarter and beyond useful.

Buoy Health is a US-based application that is empowered with efficient machine learning capabilities to detect diagnostic conditions of the patient. This healthcare application detects a probable disease by asking questions based on the answers to the preceding ones. Subsequently, guide the users on how to proceed further.

This application measures the consumption of medicines in ones body and analyses potential threats on excessive or deficient intake. It also successfully recognizes different combinations of medicines and food habits associated with them as safe or unsafe. Lastly, it rewards the users for having medicines on time.

Asthmapolis is a smart inhaler aided with a sensor that automatically responds given that it is in sync with your smartphone. It manifests feedback and asthma-related information including warnings in certain environments. The phone also detects the tool whenever it is nearby to ease the trouble to find it.

This is an initiative by the Government of India to contain the spread of novel coronavirus by detecting the contamination and identifying carriers of it. This further warns the user and also informs them about any developments in the body complying with the symptoms of the virus. This has gained considerable popularity and appreciation mainly amongst the Indians because of its proven efficacy.

Babylon is a UK-based health assistant that is effective in comparing symptoms with a large database of common illnesses to identify the disease occurring in the users body. This advises further steps depending on the users medical history.

Nursing facilities are extended in the form of a virtual health assistant like Sesne.ly. This virtual nurse takes care of the users daily with the medicines and monitors the developments in the body of the user within the interval of doctor visits. This has a crucial role to play in the expansion of health tech in 2021.

Aicure is a popular health assistant amongst patients with serious illnesses who tend to skip medicines and practices prescribed by their doctor. This application is assisted by the phones camera to track the behaviors of the patient that is in accordance with or against the doctors advice. This exhibits the endless extent of progress that can be brought in by artificial intelligence.

This is a Wearable health assistant that records the physical activities of an individual to display their fitness. The degree of exercise and calories burnt are exclusively measured to reflect their agility. This could be used by doctors to realize the users potential. Calculating the movement of an individual is empowered by robust algorithms furnishing artificial intelligence.

Binah.in is an efficient health assistant application that uses a smartphone camera to diagnose health problems by scanning the users face from side to side and reporting the health conditions that they are undergoing. However minor health issues can get immediate and effective consultation without having to commute to the doctor and wait in a long queue.

Youper is a health assistant that is empowered to cure mental health illnesses and instability. psychological counseling is an important phenomenon of this application. This functions by carrying out compassionate conversations with the user and suggesting practices that would further help them in overcoming the inner conflicts in a subtle way that appears appealing to the users. Clinical assistance to deal with psychological issues is in high demand and thus this healthcare application has considerably fulfilled the requirement.

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Reliable Health Assistants Yielded by Artificial Intelligence - Analytics Insight

The global wound care solutions market is estimated to garner $30.5 billion in revenue by 2026 at a compound annual growth rate of 6.7%, finds Frost & Sullivan

SAN ANTONIO, Oct. 18, 2021 /PRNewswire/ --Frost & Sullivan's recent analysis, Global Wound Care Solutions and New-age Technology Growth Opportunities, finds that participants in the wound care industry are investing heavily in technologies and solutions that require minimal/no medical intervention and can be used by patients, family and care providers. Primarily contributed by basic and advanced wound care solutions product types, the global wound care solutions market is estimated to garner $30.5 billion in revenue by 2026 from $20 billion in 2020, an uptick at a compound annual growth rate (CAGR) of 6.7%.

With technological advancements and a diverse array of traditional and advanced wound care solutions comprising apps, software, services, devices, and wearables, North America will dominate the wound care market by 2026. Also, the European wound care market will witness stable growth as the market becomes saturated due to technological advancements. Asia-Pacific will see a maximum growth rate as countries across the region adopt wound care solutions rapidly. Similarly, a surge in demand for faster wound recovery and advanced wound dressings in the Middle East and Latin America, respectively, will drive the wound care solutions market in the rest of the world over the forecast period.

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"The requirement for faster, less-invasive wound healing is boosting the demand for advanced wound care solutions," said Suchismita Das, Healthcare & Life Sciences Research Analyst at Frost & Sullivan. "Additionally, the resumption of elective surgeries that were placed on hold during the pandemic will further boost the post-pandemic demand for surgical wound care solutions."

Das added: "As end-users increasingly prefer 'at-home' solutions, simple and effective wound monitoring devices and solutions that require less intervention from clinicians are gaining traction. Further, the artificial intelligence (AI)-enabled solutions, sensor-based devices/wearables, and wound assessment devices aid care providers with clinical decision support (CDS) for faster diagnosis of complex wounds, leading to effective care pathways."

Government and corporate funding for developing next-gen wound care solutions that primarily enable early wound detection and prevention is set to increase, presenting the following growth opportunities for market participants:

Global Wound Care Solutions and New-age Technology Growth Opportunitiesis the latest addition to Frost & Sullivan's Healthcare & Life Sciences research and analyses available through the Frost & Sullivan Leadership Council, which helps organizations identify a continuous flow of growth opportunities to succeed in an unpredictable future.

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Camille Nebeker, Ed.D., associate professor with appointments in the UC San Diego Herbert Wertheim School of Public Health and Human Longevity Science and the Design Lab

The University of California Presidential Working Group on Artificial Intelligence was launched in 2020 by University of California President Michael V. Drake and former UC President Janet Napolitano to assist UC in determining a set of responsible principles to guide procurement, development, implementation, and monitoring of artificial intelligence (AI) in UC operations.

To support these goals, the working group developed a set of UC Responsible AI Principles and explored four high-risk application areas: health, human resources, policing, and student experience. The working group has published a final report that explores current and future applications of AI in these areas and provides recommendations for how to operationalize the UC Responsible AI Principles. The report concludes with overarching recommendations to help guide UCs strategy for determining whether and how to responsibly implement AI in its operations.

Camille Nebeker, Ed.D., associate professor with appointments in the UC San Diego Herbert Wertheim School of Public Health and Human Longevity Science and the Design Lab, was a member of the working groups health subcommittee.

The use of artificial intelligence within the UC campuses cuts across human resources, procurement, policing, student experience and healthcare. We, as an organization, did not have guiding principles to support responsible decision-making around AI, said Nebeker, who co-founded and directs the Research Center for Optimal Digital Ethics Health at UC San Diego, a multidisciplinary group that conducts research and provides education to support ethical digital health study practices.

The UC Presidential Working Group on AI has met over the past year to develop principles to advance responsible practices specific to the selection, implementation and management of AI systems.

With universities increasingly turning to AI-enabled tools to support greater efficiency and effectiveness, UC is setting an important precedent as one of the first universities, and the largest public university system, to develop governance processes for the responsible use of AI. More info is available on the UC Newsroom.

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UC adopts recommendations for the responsible use of Artificial Intelligence - Preuss School Ucsd

Policymakers around the world are developing guidelines for use of artificial intelligence in health care.

Baymax, the robotic health aide and unlikely hero from the movie Big Hero 6, is an adorable cartoon character, an outlandish vision of a high-tech future. But underlying Baymaxs character is the very realistic concept of an artificial intelligence (AI) system that can be applied to health care.

As AI technology advances, how will regulators encourage innovation while protecting patient safety?

AI does not have a precise definition, but the term generally describes machines that have the capacity to process and respond to stimulation in a manner similar to human thought processes. Many industriessuch as the military, academia, and health carerely on AI today.

For decades, health care professionals have used AI to increase efficiency and enhance the quality of patient care. For example, radiologists employ AI to identify signs of certain diseases in medical imaging. Tech companies are also partnering with health care providers to develop AI-based predictive models to increase the accuracy of diagnoses. A recent study applied AI to predict COVID-19 based on self-reported symptoms.

In the wake of the COVID-19 pandemic and the rise of telemedicine, experts predict that AI technology will continue to be used to prevent and treat illness and will become more prevalent in the health care industry.

The use of AI in health care may improve patient care, but it also raises issues of data privacy and health equity. Although the health care sector is heavily regulated, no regulations target the use of AI in health care settings. Several countries and organizations, including the United States, have proposed regulations addressing the use of AI in health care, but no regulations have been adopted.

Even beyond the context of health care, policymakers have only begun to develop rules for the use of AI. Some existing data privacy laws and industry-specific regulations do apply to the use of AI, but no country has enacted AI-specific regulations. In January 2021, the European Union released its proposal for the first regulatory framework for the use of AI. The proposal establishes a procedure for new AI products entering the market and imposes heightened standards for applications of AI that are considered high risk.

The EUs suggested framework provides some examples of high-risk applications of AI that are related to health care such as the use of AI to triage emergency aid. Although the EUs proposal does not focus on the health care industry in particular, experts predict that the EU regulations will serve as a framework for future, more specific guidelines.

The EUs proposal strikes a balance between ensuring the safety and security of the AI market, while also continuing to promote innovation and investment in AI. These conflicting values also appear in U.S. proposals to address AI in health care. Both the U.S. Food and Drug Administration (FDA) and the U.S. Department of Health and Human Services (HHS) more broadly have begun to develop guidelines on the use of AI in the health industry.

In 2019, FDA published a discussion paper outlining a proposed regulatory framework for modifications to AI-based software as a medical device (SaMD). FDA defines AI-based SaMD as software intended to treat, diagnose, cure, mitigate, or prevent disease. In the agencys discussion paper, FDA asserts its commitment to ensure that AI-based SaMD will deliver safe and effective software functionality that improves the quality of care that patients receive. FDA outlines the regulatory approval cycle for AI-based SaMD, which requires a holistic evaluation of the product and the maker of the product.

Earlier this year, FDA released an action plan for the regulation of AI-based SaMD that reaffirmed its commitment to encourage the development of AI best practices. HHS has also announced its strategy for the regulation of AI applied in health care settings. As with FDA and the EU, HHS balances the health and well-being of patients with the continued innovation of AI technology.

The United States is not alone in its attempt to monitor and govern the use of AI in health care. Countries such as China, Japan, and South Korea have also released guidelines and proposals seeking to ensure patient safety. In June 2021, the World Health Organization (WHO) issued a report on the use of AI in health care and offered six guiding principles for AI regulation: protecting autonomy; promoting safety; ensuring transparency; fostering responsibility; ensuring equity; and promoting sustainable AI.

Scholars are also discussing the use of AI in health care. Some experts have urged policymakers to develop AI systems designed to advance health equity. Others warn that algorithmic bias and unequal data collection in AI can exacerbate existing health inequalities. Experts argue that, to mitigate the risk of discriminatory AI practices, policymakers should consider the unintended consequences of the use of AI.

For example, AI systems must be trained to recognize patterns in data, and the training data may reflect historical discrimination. One study showed that women are less likely to receive certain treatments than men even though they are more likely to need them. Similarly biased data would train an AI system to perpetuate this pattern of discrimination. Health care regulators must address the need to protect patients from potential inequalities without discouraging the development of life-saving innovation in AI.

As the use of AI becomes more prominent in health care, regulators in the United States and elsewhere find themselves considering more robust regulations to ensure quality of care.

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How Will Health Care Regulators Address Artificial Intelligence? - The Regulatory Review

PUNE, India, Oct. 19, 2021 /PRNewswire/ -- According to a recent market study published by Up Market Research titled, "Global Artificial Intelligence Marketby Technology (Machine Learning, Deep Learning, Machine Vision, Natural Language Processing), by Solution (Services, Hardware, Software), by End Use (BFSI, Automotive & Transportation, Advertising & Media, Agriculture, Manufacturing, Retail, Healthcare, Law) and Region: Size, Share, Trends and Opportunity Analysis, 2018-2028", As per the study the market value was USD 62.35 million in 2020. It is expected to grow at a compound annual rate (CAGR) of 40.2% between 2021 and 2028. Tech giants have been directing continuous research and innovation to drive the adoption of new technologies across a variety of industries, including automotive, healthcare, finance, and manufacturing. Technology has been an integral part of these industries for centuries, but Artificial Intelligence has put technology at the heart of many organizations. AI is now being integrated into almost every program and apparatus, from autonomous vehicles to life-saving medical equipment. AI has been proven to be the key element of the digital revolution.

The report covers comprehensive data on emerging trends, market drivers, growth opportunities, and restraints that can change the market dynamics of the industry. It provides an in-depth analysis of the market segments which include products, applications, and competitor analysis.

Key Market Players Profiled in the Report

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This report also includes a complete analysis of industry players that cover their latest developments, product portfolio, pricing, mergers, acquisitions, and collaborations. Moreover, it provides crucial strategies that are helping them to expand their market share.

Highlights on the segments of the Artificial Intelligence Market

Based on Solution, the market is divided into Hardware, Software, and Services. Software solutions dominated the artificial intelligence market, accounting for over 38.0% of global revenue in 2020. This is due to prudent improvements in information storage capacity and high computing power. Parallel processing capabilities are used to deliver high-end AI software for dynamic end-use verticals. Services in artificial intelligence include integration, maintenance, and support. This segment is expected to grow at an impressive rate during the forecast period. AI hardware comprises chipsets like Graphics Processing Unit (GPU), CPU and application-specific integrated circuits.

On the basis of Technology,the market is divided intoDeep Learning, Machine Learning, Natural Language Processing, and Machine Vision. Deep learning dominated the market, accounting for 38.0% of global revenue in 2020. Its complex data-driven applications such as speech recognition and text/content are responsible for the market's high share. This technology allows for the resolution of data volume challenges and offers attractive investment opportunities. Deep learning and machine learning are important investments in AI. This includes AI platforms as well as cognitive applications. These include tagging and clustering, categorization and hypothesis generation. Alerting, filtering and navigation are all part of the AI platform. They allow for the creation of intelligent, advisory and cognitively-enabled solutions.

Based on End Use, the market is divided into Healthcare, BFSI, Law, Retail, Advertising & Media, Automotive & Transportation, Agriculture, Manufacturing, and Others. Advertising and media dominated the market, accounting for over 18.0% of global revenue in 2020. The growing popularity of AI marketing applications is responsible for this high share. The healthcare sector will continue to hold a significant share of the market by 2028. BFSI includes financial analysis, risk assessment and investment/portfolio solicitations. Due to the high demand in this sector for compliance and risk applications, artificial intelligence has seen a significant increase in the BFSI. Retail, law, transportation, agriculture and other verticals are also possible for artificial intelligence systems. Conversational AI platforms are the most popular in each vertical.

On the basis of Regions,the market is categorized as Asia Pacific, North America, Latin America, Europe, and Middle East & Africa. North America was the dominant market, accounting for more than 40.0% of global revenue in 2020. This is due to government initiatives that encourage adoption of AI across different industries. As the United States' strategy to promote leadership in artificial intelligence, the American AI Initiative was launched by President Donald J. Trump in February 2019. Also, In the coming years, significant growth is expected in Asia Pacific. The significant increase in investments in artificial intelligence is responsible for this growth.

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Global Artificial Intelligence Market Is Expected To Set A New Benchmark With A CAGR Of 40.2% By 2028 | Up Market Research - PRNewswire

West Virginia University researchers are using artificial intelligence and other advanced technologies to help diagnose people with autism.

The program is aimed at more easily identifying phenotypes related to Autism Spectrum Disorder. These phenotypes are noticeable traits or characteristics a person with ASD might have.

Autism phenotyping is something we are still in the dark ages with. We have no clue how many different types of autism we are dealing with, said WVU professor Xin Li, one of the projects head researchers.

Technology like neural imaging and behavior imaging, along with eye-tracking data will help identify these specific traits. Li says he hopes this data will find different types of ASD and help reduce the gap between a childs birth and their diagnosis. The average age of a child newly diagnosed with ASD is 4 years old -- Li says part of the goal of this research is to reduce that age in half, aiming for diagnoses at 2 years old. The earlier the diagnosis, Li says, the more effective the treatment.

Li says this research is important because of how little is known about ASD compared to other disorders. The better the technology available to diagnose those with ASD, the better phenotypes can be successfully grouped into ASD subtypes.

If we think about something were familiar with for example, a butterfly a butterfly can have different wings, have different patterns, colors Those are the easy traits for laymen to tell a different species from one butterfly to another one, Li said.

Recent data from the Centers for Disease Control and Prevention says 1 in 54 children in the U.S. are diagnosed with ASD.

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