Monthly Archives: May 2022

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Abstract: Whats New for 2022? - Global competitiveness and key competitor percentage market shares. - Market presence across multiple geographies - Strong/Active/Niche/Trivial.

New York, May 11, 2022 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Artificial Intelligence (AI) Industry" - https://www.reportlinker.com/p05478480/?utm_source=GNW - Online interactive peer-to-peer collaborative bespoke updates - Access to our digital archives and MarketGlass Research Platform - Complimentary updates for one yearGlobal Artificial Intelligence (AI) Market to Reach US$341.4 Billion by the Year 2027

- Amid the COVID-19 crisis, the global market for Artificial Intelligence (AI) estimated at US$46.9 Billion in the year 2020, is projected to reach a revised size of US$341.4 Billion by 2027, growing at a CAGR of 32.8% over the analysis period 2020-2027.Services, one of the segments analyzed in the report, is projected to grow at a 32.6% CAGR to reach US$142.7 Billion by the end of the analysis period.After an early analysis of the business implications of the pandemic and its induced economic crisis, growth in the Software segment is readjusted to a revised 30.4% CAGR for the next 7-year period. This segment currently accounts for a 37.9% share of the global Artificial Intelligence (AI) market.

- The U.S. Accounts for Over 41.2% of Global Market Size in 2020, While China is Forecast to Grow at a 39.1% CAGR for the Period of 2020-2027

- The Artificial Intelligence (AI) market in the U.S. is estimated at US$19.3 Billion in the year 2020. The country currently accounts for a 41.22% share in the global market. China, the world second largest economy, is forecast to reach an estimated market size of US$64.7 Billion in the year 2027 trailing a CAGR of 39.1% through 2027. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 27.6% and 29% respectively over the 2020-2027 period. Within Europe, Germany is forecast to grow at approximately 31.2% CAGR while Rest of European market (as defined in the study) will reach US$64.7 Billion by the year 2027.

- Hardware Segment Corners a 19.9% Share in 2020

- In the global Hardware segment, USA, Canada, Japan, China and Europe will drive the 36.6% CAGR estimated for this segment. These regional markets accounting for a combined market size of US$7.7 Billion in the year 2020 will reach a projected size of US$68.5 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$46.7 Billion by the year 2027.

- Select Competitors (Total 865 Featured) AIBrain, Inc. Advanced Micro Devices, Inc. Amazon Web Services Baidu, Inc. Cisco Systems, Inc. eGain Corporation General Electric Company Google, Inc. Intel Corporation International Business Machines Corporation (IBM) Meta (Facebook company is now Meta) Micron Technology, Inc. Microsoft Corporation Nippon Telegraph and Telephone Corporation Nuance Communications, Inc. NVIDIA Corporation Omron Corporation Oracle Corporation Rockwell Automation, Inc. Salesforce.com, inc. Samsung Electronics Co., Ltd. SAP SE SAS Institute Inc. Siemens AG

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 With IMF Making an Upward Revision of Global GDP for 2022, Companies Remain Bullish About an Economic Comeback EXHIBIT 1: World Economic Growth Projections (Real GDP, Annual % Change) for 2020 through 2022 Artificial Intelligence Gains Significant Interest as Industries Expedite Digital Transformation Strategies A Peek into Application of AI in War Against the Pandemic Machine Learning Benefits Healthcare Organizations COVID-19-Led Budgetary Reticence Dampens Spending, but AI Enjoys Resilient Interest in Banking Sector Retailers Rely on AI to Stay Afloat & Embrace New Normal Emphasis on Technology Adoption Elicits AI Implementation in Manufacturing Industry Competition AI Marketplace Characterized by Intense Competition EXHIBIT 2: Artificial Intelligence (AI) - Global Key Competitors Percentage Market Share in 2022 (E) Growing Focus on AI by Leading Tech Companies with Huge Financial Resources AI Presents Compelling Opportunities for Established & Startup Companies Competitive Market Presence - Strong/Active/Niche/Trivial for 300 Players Worldwide in 2022 (E) Funding Landscape Remains Vibrant in the AI Technology Space EXHIBIT 3: Global AI Investment (in US$ Billion) for the Years 2015 through 2021 EXHIBIT 4: Distribution of Global Investment in AI by Region/ Country: 2021 EXHIBIT 5: Number of AI Startups with $1 Billion Valuations for the Years 2014-2020 EXHIBIT 6: AI Cumulative Funding (in US$ Billion) by Category (As of 2020) AI Applications and Major Startups Artificial Intelligence (AI): A Prelude Technologies Enabling AI Market Outlook Prominent Factors with Implications for Evolution & Future of Artificial Intelligence 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 World Brands Recent Market Activity

2. FOCUS ON SELECT PLAYERS

3. MARKET TRENDS & DRIVERS Accelerating Pace of Digital Transformation to Benefit Demand for AI EXHIBIT 7: Digital Transformation by Industry: 2020 EXHIBIT 8: Industry Adoption of Artificial Intelligence (AI) by Function: 2020 Noteworthy Technological Trends to Watch-for in Artificial Intelligence Space Machine Learning and AI-Assisted Platforms Personalize Customer Experiences in Marketing Applications EXHIBIT 9: Ranking of Business Outcomes Realized through AI Application in Marketing Businesses to Gain from Application of AI in Predictive Marketing Analytics and Demand Forecasting Growing Role of AI in the Metaverse AI Hosting at Edge to Drive Growth EXHIBIT 10: 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 11: 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 12: Global Breakdown of Investments in Manufacturing IoT (in US$ Billion) for the Years 2016, 2018, 2020 and 2025 EXHIBIT 13: Industry 4.0 Technologies with Strongest Impact on Organizations: 2020 Increasing Adoption of AI Technology to Boost AI Chipsets Market Combination of Robotics and AI Set to Cause Significant Disruption in Various Industries AI Innovations Widen Prospects Blockchain & Artificial Intelligence (AI): A Powerful Combination Big Data Trends to Shape Future of Artificial Intelligence AI in Retail Market: Multi-Channel Retailing and e-Commerce Favor Segment Growth EXHIBIT 14: Digital Transformation in Retail Industry Promises Lucrative Growth Opportunities: Global Retail IT Spending (In US$ Billion) for the Years 2018, 2020, 2022 & 2024 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 Ecommerce Attracts Strong Growth Detailed Insight into How e-commerce Makes use of AI EXHIBIT 15: Global B2C e-Commerce Market Reset & Trajectory - Growth Outlook (In %) For Years 2019 Through 2025 EXHIBIT 16: Retail M-Commerce Sales as % of Retail E-commerce Sales Worldwide for the Years 2016, 2018, 2020 & 2022 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 Possibilities Galore for AI in Digital Marketing AI-Enabled CRM Market: Promising Growth Opportunities in Store Artificial Intelligence Set to Transform Delivery of Healthcare Services AI to Play a Significant Role in Automation and Improving Clinical Outcomes EXHIBIT 17: Global Healthcare AI Market - Percentage Breakdown by Application for 2020 AI in Pharmaceutical Sector COVID-19 Spurs New Developments and Expedites AI Adoption in Healthcare Industry Artificial Intelligence Holds Potential to Accelerate Detection & Treatment of COVID-19 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 Propels Growth EXHIBIT 19: Automotive AI Market By Segment Demand Recovery in Automobile Sector Steers Growth Opportunities EXHIBIT 20: World Automobile Production in Million Units: 2008- 2022 Increasing Focus on Electric Vehicles and Autonomous Vehicles Provide the Perfect Platform to Shape Future Growth EXHIBIT 21: Global Autonomous Vehicle Sales (In Million) for Years 2020, 2025 & 2030 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 AI to Influence Manufacturing in a Major Way Industrial IoT, Robotics and Big Data to Stimulate AI Implementations EXHIBIT 22: Global Investments on Industry 4.0 Technologies (in US$ Billion) for the Years 2017, 2020, & 2023 EXHIBIT 23: Global Predictive Maintenance by Market in US$ Billion for Years 2020, 2022, 2024, and 2026 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 EXHIBIT 25: Top Technology Investments in Oil and Gas Sector: 2020 AI in Construction Sector: Need for Cost Reduction and Safety at Construction Sites Drive Focus onto the Use of AI-based Solutions

4. GLOBAL MARKET PERSPECTIVE Table 1: World Recent Past, 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 Recent Past, 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 Recent Past, 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 Recent Past, 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 Recent Past, 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 Recent Past, 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 Recent Past, 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 Recent Past, 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 Recent Past, 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 Recent Past, 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 Recent Past, 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 Recent Past, 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 Recent Past, 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 Recent Past, 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 Recent Past, 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 Recent Past, 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

Table 47: World Historic Review 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 2015 through 2019 and % CAGR

Table 48: World 12-Year Perspective for Other End-Uses 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

III. MARKET ANALYSIS

UNITED STATES Artificial Intelligence (AI) Market Presence - Strong/Active/ Niche/Trivial - Key Competitors in the United States for 2022 (E) Artificial Intelligence Market: An Overview Healthcare: A Promising Application Market for AI Technology Funding for AI Startups Continues to Grow EXHIBIT 26: Top Funded AI Startups in the US: 2021 Market Analytics Table 49: USA Recent Past, Current & Future Analysis for Artificial Intelligence (AI) by Component - Services, Software and Hardware - Independent Analysis of Annual Revenues in US$ Million for the Years 2020 through 2027 and % CAGR

Table 50: USA Historic Review for Artificial Intelligence (AI) by Component - Services, Software and Hardware Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 51: USA 12-Year Perspective for Artificial Intelligence (AI) by Component - Percentage Breakdown of Value Revenues for Services, Software and Hardware for the Years 2015, 2021 & 2027

Table 52: USA Recent Past, Current & Future Analysis for Artificial Intelligence (AI) by Technology - Computer Vision, Machine Learning, Context Aware Computing and Natural Language Processing - Independent Analysis of Annual Revenues in US$ Million for the Years 2020 through 2027 and % CAGR

Table 53: USA Historic Review for Artificial Intelligence (AI) by Technology - Computer Vision, Machine Learning, Context Aware Computing and Natural Language Processing Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 54: USA 12-Year Perspective for Artificial Intelligence (AI) by Technology - Percentage Breakdown of Value Revenues for Computer Vision, Machine Learning, Context Aware Computing and Natural Language Processing for the Years 2015, 2021 & 2027

Table 55: USA Recent Past, Current & Future Analysis for Artificial Intelligence (AI) by End-Use - Advertising & Media, BFSI, Healthcare, Retail, Automotive & Transportation, Manufacturing, Agriculture and Other End-Uses - Independent Analysis of Annual Revenues in US$ Million for the Years 2020 through 2027 and % CAGR

Table 56: USA Historic Review for Artificial Intelligence (AI) by End-Use - Advertising & Media, BFSI, Healthcare, Retail, Automotive & Transportation, Manufacturing, Agriculture and Other End-Uses Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 57: USA 12-Year Perspective for Artificial Intelligence (AI) by End-Use - Percentage Breakdown of Value Revenues for Advertising & Media, BFSI, Healthcare, Retail, Automotive & Transportation, Manufacturing, Agriculture and Other End-Uses for the Years 2015, 2021 & 2027

CANADA Market Overview Top-Tier Canadian Cities Primed for AI Growth Market Analytics Table 58: Canada Recent Past, Current & Future Analysis for Artificial Intelligence (AI) by Component - Services, Software and Hardware - Independent Analysis of Annual Revenues in US$ Million for the Years 2020 through 2027 and % CAGR

Table 59: Canada Historic Review for Artificial Intelligence (AI) by Component - Services, Software and Hardware Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 60: Canada 12-Year Perspective for Artificial Intelligence (AI) by Component - Percentage Breakdown of Value Revenues for Services, Software and Hardware for the Years 2015, 2021 & 2027

Table 61: Canada Recent Past, Current & Future Analysis for Artificial Intelligence (AI) by Technology - Computer Vision, Machine Learning, Context Aware Computing and Natural Language Processing - Independent Analysis of Annual Revenues in US$ Million for the Years 2020 through 2027 and % CAGR

Table 62: Canada Historic Review for Artificial Intelligence (AI) by Technology - Computer Vision, Machine Learning, Context Aware Computing and Natural Language Processing Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 63: Canada 12-Year Perspective for Artificial Intelligence (AI) by Technology - Percentage Breakdown of Value Revenues for Computer Vision, Machine Learning, Context Aware Computing and Natural Language Processing for the Years 2015, 2021 & 2027

Table 64: Canada Recent Past, Current & Future Analysis for Artificial Intelligence (AI) by End-Use - Advertising & Media, BFSI, Healthcare, Retail, Automotive & Transportation, Manufacturing, Agriculture and Other End-Uses - Independent Analysis of Annual Revenues in US$ Million for the Years 2020 through 2027 and % CAGR

Table 65: Canada Historic Review for Artificial Intelligence (AI) by End-Use - Advertising & Media, BFSI, Healthcare, Retail, Automotive & Transportation, Manufacturing, Agriculture and Other End-Uses Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 66: Canada 12-Year Perspective for Artificial Intelligence (AI) by End-Use - Percentage Breakdown of Value Revenues for Advertising & Media, BFSI, Healthcare, Retail, Automotive & Transportation, Manufacturing, Agriculture and Other End-Uses for the Years 2015, 2021 & 2027

JAPAN Artificial Intelligence (AI) Market Presence - Strong/Active/ Niche/Trivial - Key Competitors in Japan for 2022 (E) Market Analytics Table 67: Japan Recent Past, Current & Future Analysis for Artificial Intelligence (AI) by Component - Services, Software and Hardware - Independent Analysis of Annual Revenues in US$ Million for the Years 2020 through 2027 and % CAGR

Table 68: Japan Historic Review for Artificial Intelligence (AI) by Component - Services, Software and Hardware Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 69: Japan 12-Year Perspective for Artificial Intelligence (AI) by Component - Percentage Breakdown of Value Revenues for Services, Software and Hardware for the Years 2015, 2021 & 2027

Table 70: Japan Recent Past, Current & Future Analysis for Artificial Intelligence (AI) by Technology - Computer Vision, Machine Learning, Context Aware Computing and Natural Language Processing - Independent Analysis of Annual Revenues in US$ Million for the Years 2020 through 2027 and % CAGR

Table 71: Japan Historic Review for Artificial Intelligence (AI) by Technology - Computer Vision, Machine Learning, Context Aware Computing and Natural Language Processing Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 72: Japan 12-Year Perspective for Artificial Intelligence (AI) by Technology - Percentage Breakdown of Value Revenues for Computer Vision, Machine Learning, Context Aware Computing and Natural Language Processing for the Years 2015, 2021 & 2027

Table 73: Japan Recent Past, Current & Future Analysis for Artificial Intelligence (AI) by End-Use - Advertising & Media, BFSI, Healthcare, Retail, Automotive & Transportation, Manufacturing, Agriculture and Other End-Uses - Independent Analysis of Annual Revenues in US$ Million for the Years 2020 through 2027 and % CAGR

Table 74: Japan Historic Review for Artificial Intelligence (AI) by End-Use - Advertising & Media, BFSI, Healthcare, Retail, Automotive & Transportation, Manufacturing, Agriculture and Other End-Uses Markets - Independent Analysis of Annual Revenues in US$ Million for Years 2015 through 2019 and % CAGR

Table 75: Japan 12-Year Perspective for Artificial Intelligence (AI) by End-Use - Percentage Breakdown of Value Revenues for Advertising & Media, BFSI, Healthcare, Retail, Automotive & Transportation, Manufacturing, Agriculture and Other End-Uses for the Years 2015, 2021 & 2027

CHINA Artificial Intelligence (AI) Market Presence - Strong/Active/ Niche/Trivial - Key Competitors in China for 2022 (E) Market Overview China Continues Investments in AI Startups EXHIBIT 27: Chinese AI Market: Funding for AI Startups (in $ Billion): 2016-2020

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Global Artificial Intelligence (AI) Market to Reach US$341.4 Billion by the Year 2027 - Yahoo Finance

During one of the many live collaboration panels of MUSCs 2022 Innovation Week, an interesting discussion ensued, mirroring a common debate in health care and that is: How does artificial intelligence (AI) fit in?

Last week, as several clinicians and key members of the Clemson-MUSC AI Hub which was formed in 2021 were on hand at the Gazes Cardiac Research Institute, it became quickly evident that AI is gaining traction throughout the world of heath care. But equally evident was the fact that theres still some skepticism from the mainstream when it comes to the best ways to use it.

For congenital cardiologist G. Hamilton Baker, M.D., associate professor of pediatrics, AI remains a tremendous untapped resource.

AI is such a blanket term, he said in an interview right after the formation of the Clemson-MUSC AI Hub last year. Were leveraging data science and wrangling those giant databases with appropriately applied machine learning methods.

Baker has been utilizing AI in his work for several years now, working on a number of different AI+Biomedical projects ranging from congenital heart disease to diabetic eye disease.

I feel very strongly about education on AI. The goal is to teach clinicians how to understand and utilize AI. We arent asking people to learn how to code, we simply want them to learn how AI can work for them, Baker said.

At the Gazes, the topic quickly centered on AI and bias. Some clinicians believe the most elegant aspect of AI is that it removes unintended biases by letting the computers which are inherently without bias because theyre metal and silicone do the data crunching and leaving the treatment to the physicians.

When two clinicians might disagree on something, AI can help uncover unknown biases and dispel others, said MUSC Public Health Sciences assistant professor Paul Heider, Ph.D. AI just looks at the data and makes decisions that are based on that alone.

However, others argued that those AI programs were written by humans, and those inadvertent biases almost certainly were sprinkled in.

Trustworthiness is a key word that we need to be focusing on here, said Brian Dean, Ph.D., chairman of the Division of Computer Science at Clemson University. Because the AI system is becoming less of a smart sensor that provides input to the medical decision-making process and more of a teammate. So we have to be super careful because, after all, AI was trained based on human expert opinion, which is biased.

Dean agreed that AI is an extremely valuable tool for the medical field, cautioning all to simply be judicious with its use.

Jihad Obeid, M.D., co-director of the Biomedical Informatics Center at MUSC, agreed. If you use it as a decision aid, rather than a decision-maker, he said, AI can be a real asset.

Regardless of the differences of opinion in the room, panel members agreed that AI has unlimited potential for researchers and clinicians alike.

When it comes to AI in health care, its so tempting to talk about the hype, all the big stuff it can do, Baker said. But the truth of the matter is there are plenty of easy, smart projects where AI could really make a significant difference, and we just need more people on board.

According to MUSC provost Lisa K. Saladin, PT, Ph.D., MUSC is already using AI to develop techniques that can help to diagnose and treat a range of ills, including cancer, Alzheimers disease, substance abuse, child abuse, epilepsy, aphasia, inflammatory skin conditions and cardiac issues.

Baker said that clinicians who are interested in implementing AI into their research or practice should look into the AI Hub, as it offers a host of resources, including funding for AI. During this years Innovation Week, the Clemson-MUSC AI Hub gave out $100,000 worth of grants to five worthy projects.

We want people to know about this, he said. I know there are lots of people out there who could really use our help. We want to accelerate the adoption of AI for those who are interested."

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Can Artificial Intelligence remove unintended bias from health care? Clinicians optimistic, but wary - Medical University of South Carolina

Adam Oliner, co-founder and CEO of Graft used to run machine learning at Slack, where he helped build the companys internal artificial intelligence infrastructure. Slack lacked the resources of a company like Meta or Google, but it still had tons of data to sift through and it was his job to build something on a smaller scale to help put AI to work on the dataset.

With a small team, he could only build what he called a miniature solution in comparison to the web scale counterparts. After he and his team built it, however, he realized that it was broadly applicable and could help other smaller organizations tap into AI and machine learning without huge resources.

We built a sort of mini Graft at Slack for driving semantic search and recommendations throughout the product. And it was hugely effective And that was when we said, this is so useful, and so powerful if we can get this into the hands of most organizations, we think we could really change the way people interact with their data and interact with AI, Oliner told me.

Last year he decided to leave Slack and go out on his own and started Graft to solve the problem for many companies. He says the beauty of the solution is that it provides everything you need to get started. Its not a slice of a solution or one that requires plug-ins to complete. He says it works for companies right out of the box.

The point of Graft is to make the AI of the 1% accessible to the 99%. he said. What he means by that is giving smaller companies the ability to access and put to use modern AI, and in particular pre-trained models for certain specific tasks, something he says offers a tremendous advantage.

These are sometimes called trunk models or foundation models, a term that a group at Stanford is trying to coin. These are essentially very large pre-trained models that encode a lot of semantic and structural knowledge about a domain of data. And this is useful because you dont have to start from scratch on every new problem, he said.

The company is still a work in progress, working with beta customers to refine the solution, but expects to launch a product later this year. For now they have a team of 11 people, and Oliner says that its never too early to think about building a diverse team.

When he decided to start the company, the first person he sought out was Maria Kazandjieva, former head of engineering at Netflix. I have been working at building the rest of the founding team and also hiring others with an eye toward diversity and inclusion. So, you know, just [the other day], we were talking with recruiting communities that are focused on women and people of color, partly because we feel like investments now in building diverse team will just make it so much easier later on, he said.

As the journey begins for Graft, the company announced what it is calling a pre-seed investment of $4.5 million led by GV with help from NEA, Essence VC, Formulate Ventures and SV Angel.

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Slacks former head of machine learning wants to put AI in reach of every company - TechCrunch

The AI Collaborative brings together Leading Health System executives in an experiential community around the efficient, responsible, and future-focused deployment of artificial intelligence and machine learning.

BURLINGTON, Mass., May 11, 2022 /PRNewswire/ -- The growth of artificial intelligence (AI) and machine learning (ML) in healthcare points to a future in which these technologies will consistently aid clinical decision-making, workforce support and planning, patient experience, and overall business strategy. With the goal of creating a novel initiative around market forces and breakthrough innovations for AI and ML, The Health Management Academy (The Academy) has partnered with Nuance, a Microsoft company, to launch The AI Collaborative, which brings together senior leaders from the nation's Leading Health Systems (LHS) who are deploying these technologies in the clinical and operational settings, as well as planning for future use-cases.

Having joined forces this year, Microsoft and Nuance represent two of the most trusted and innovative technology organizations in the world. With decades of experience bringing cutting-edge cloud and AI technology to the healthcare, retail, financial services and telecommunications industries, Nuance and Microsoft are ideal partners in the effort to create a progressive peer community anchored in collaboration with key LHS executives and experts across the healthcare ecosystem.

The potential for AI in healthcare is clear across LHS in The Academy network, many of whom have already begun investing in AI-powered solutions. This investment has elevated the need for regular touchpoints with peers across the nation to share questions, successes, and challenges in real time. The AI Collaborative will commence in September 2022 and will include a visit to Microsoft's corporate headquarters and annual summits in subsequent years. These events will include key stakeholders across LHS leadership teams embedded in analytics, digital strategy, and clinical transformation, along with subject-matter experts from the med-tech, payer, and life sciences sectors.

Learning opportunities at The AI Collaborative Summits will anchor around stakeholders who are deeply committed to embracing AI as a transformative and disruptive tool in healthcare. Via workshops, learning exercises, and instant insights generation, The AI Collaborative Summits will empower attendees with tactical strategies to utilize patient-specific data and insights to augment care delivery, reduce care variation, and support operational improvements.

"Our members have expressed their desire for a dedicated space to explore AI in healthcare and its enormous potential to improve outcomes and clinical workflow," said Renee DeSilva, CEO of The Academy. "We are thrilled to expand our partnership with Microsoft and Nuance to introduce The AI Collaborative, a new program at The Academy designed exclusively for clinical and operational executives who lead their organization's approach to investing in AI as a strategic initiative."

Nuance is a technology pioneer with market leadership in conversational AI and ambient intelligence, and a full-service partner of 77 percent of U.S. hospitals and trusted by over 500,000 physicians daily. Microsoft provides trusted and secure cloud and AI capabilities with the goal to empower people and organizations to address the complex challenges facing the healthcare industry today.

With a long-term commitment to leveraging cloud and AI technologies to enhance patient engagement and outcomes, reduce clinician burnout, improve clinical quality and safety, and enhance financial performance, Nuance and Microsoft are leaders in the future-focused healthcare ecosystem and well-equipped to ensure The AI Collaborative members are at the front-end of education and learning on the evolution of AI in healthcare.

"The key to successful healthcare innovation using AI is understanding at a deep level the problems that you're trying to solve and focusing on the outcomes you want to achieve," said Peter Durlach, Chief Strategy Officer of Nuance. "With the combined engineering, market and domain expertise of Nuance and Microsoft, The AI Collaborative can bring together multiple technical, business and clinical stakeholders to prioritize deployment of solutions for clinician burnout, patient engagement and health system financial stability, while accelerating innovation in precision medicine, drug discovery, clinical decision support and other promising use cases across the entire healthcare ecosystem."

About The Health Management AcademyAt The Academy, we power our community to drive health forward. Our community is made up of healthcare's most influential changemakers including executives from the top 150 U.S. health systems and the most innovative industry partners. We power our members by building our community and fostering connections through executive peer learning. We support professional growth through talent and development. We accelerate understanding by delivering timely and actionable data and insights on key challenges. And we catalyze transformation by building alliances in areas where the power of the collective is greater than the power of one. Learn more at hmacademy.com.

About Nuance CommunicationsNuance Communications is a technology pioneer with market leadership in conversational AI and ambient intelligence. A full-service partner trusted by 77 percent of U.S. hospitals and 85 percent of the Fortune 100 companies worldwide, Nuance creates intuitive solutions that amplify people's ability to help others. Nuance is a Microsoft company.

ContactFor The Health Management AcademyGregory KantorContent and Communications Manager[emailprotected]

For NuanceDayna McCoubrey[emailprotected]

SOURCE Nuance Communications, Inc.

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The Academy and Nuance, a Microsoft Company, Partner to Launch The AI Collaborative - PR Newswire

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today!

Qulacomm said it is launching new platform support for advanced robotics products, 5G wireless networking and edge-AI applications.

The company unveiled the Qualcomm Robotics solutions at its annual Qualcomm 5G Summit event as it recognizes the ways in which 5G is proliferating beyond smartphones.

The San Diego, California-based company took the wraps off its Qualcomm Robotics RB6 Platform and the Qualcomm RB5AMR reference design, which can be used to build advanced edge-AI and robotics products using Qualcomms chips.

The solutions will help unlock new commercial markets for autonomous mobile robots, delivery robots, highly automated manufacturing robots, collaborative robots, unmanned aircraft, industrial drone infrastructure, autonomous defense solutions and beyond.

The platform combines Qualcomm AI Engine and 5G chip capabilities for cutting-edge applications and possibilities, including smarter and safer robots and environments.

The tech can be used to enable autonomy for delivery robots roaming the streets; fleet management coordination across autonomous mobile robots in industrial spaces; real-time data and insights that empower critical decision-making across manufacturing and logistics and intelligence to support autonomous urban air mobility transportation.

The Qualcomm Robotics RB6 Platform and the Qualcomm RB5 AMR reference design will support evolving applications for robot manufacturers that are looking to integrate ground robots in industrial use cases across sectors. This could include government service applications, logistics, healthcare, retail, warehousing, agriculture, construction, utilities and more.

The new solutions will accelerate the digital transformation of industries and serve as a key enabler for what Qualcomm calls Industry 4.0.

Building on the successful growth and traction of Qualcomm Technologies leading robotics solutions, our expanded roadmap of solutions will help bring enhanced AI and 5G technologies to support smarter, safer, and more advanced innovations across robotics, drones and intelligent machines, said Dev Singh, head of autonomous robotics, drones and intelligent machines at Qualcomm Technologies, in a statement. We are fueling robotics innovations with 5G connectivity and premium edge-AI that will transform how we think and approach challenges and ever-evolving industry expectations in the digital economy.

The Qualcomm Robotics RB6 platform is aimed at taking enterprise and industrial robotics innovation to the next level with enhanced AI and5G. The new solution delivers 5G connectivity with support for global sub-6GHz and millimeter-wave bands in the mainstream, enterprise, and private networks.

Weve been experiencing a lot of massive growth and traction in robotics space, said Singh, in a press event. What we have is another proof point on how we continue to expand our portfolio while delivering the solution that addresses the pain point of the ecosystem.

He said diversifying beyond smartphones to robotics is part of a general diversification strategy for Qualcomm.

Qualcomm is becoming a de facto choice for robotics applications, Singh said. Our technology is at [the] heart of all and serves as the brain of all cutting-edge robotics deployments and trends across industries.

Qualcomm is working with Adlink, Akasha Imaging (an Alphabet company), Cyngn, ForwardX, FutureMind, Hyundai Robotics, inVia Robotics, LG Electronics, Microsoft Azure private MEC, ModalAI, Naver Labs, PuduRobotics, Samsung Electronics, Teledyne Flir, Thundercomm, and more.

The Qualcomm RB5 AMR Reference Design is available for pre-sale now through ModalAI and the Qualcomm Robotics RB6 development kit is available for sale through Thundercomm.

As more and more robotics are being rolled out, we see that the robotics applications evolve into new areas, like the delivery robot for first mile and last mile, the urban air mobility, smart manufacturing, and also wireless factories, Singh said. Advancements in all of these areas are going to be significantly aiding humanity and generating a lot of economic output as well. And its going to make our lives better and simpler by simplifying logistics, transportation, manufacturing, and others.

VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Learn more about membership.

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Qualcomm goes beyond smartphones with 5G and edge-AI robotics solutions - VentureBeat

For many litigators, legal research remains one of the most tedious aspects of practicing law. From not knowing whether youve exhausted your search to consuming large chunks of time, research can be draining in terms of time and financesmany clients just arent willing to pay hefty legal research bills.

Sluggish legal research continues to weigh lawyers down, despite the fact that we live in the age of Google and Alexa. If technology gives us the ability to have any question answered in seconds, why cant we find the case law we need just as easily?

While this has been the case for decades, theres been an evolutionary shift in the last few years due to an innovative few leveraging modern AI to make legal practice more efficient. Advanced AI has been used to bring forth what many see as a technological revolution in practice of law.

The modern AI behind new, intelligent legal tech includes machine learning (a branch of AI) and other sophisticated technologies. Rather than delve into the mechanics here, its more useful for litigators to know how this technology drives efficiency in a law practice, so they can stop fearing AI-powered legal tech and instead reap its benefits.

AI-powered search engines allow lawyers to conduct concept-based searches of legal databases, instead of trying to find the perfect keywords or Boolean operators. This gives lawyers the power to research quickly and intuitively by searching how they think. Lawyers can research faster and find cases they wouldnt have found using traditional search platforms.

This concept-based searching also applies to searching a law firms brief bank. This means lawyers can search a concept and find a brief theyve already written with similar issues and arguments, so they dont have to reinvent the wheel.

Certain litigation tasks can be automated through AI, including brief-drafting. Smart tools can even help lawyers write the first draft of their brief in less than 30 minutes.

Concept-based searching comes into play here, too. Searching by concepts allows lawyers to find exactly what they are looking for in millions of documents. Basically, AI actually finds the needle in the haystack, and does so instantly.

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Fear AI? Embrace it instead and watch your law firm thrive - JD Supra

TigerGraph, Inc.

Thousands of Attendees Expected at Global Celebration of the Power of Graph and AI; Virtual Event Set for May 24-26

REDWOOD CITY, Calif., May 11, 2022 (GLOBE NEWSWIRE) -- TigerGraph, provider of a leading graph analytics platform, today announced the complete agenda for Graph + AI Summit 2022, the industrys only open conference focused on accelerating analytics, AI and machine learning with graph algorithms. The roster includes confirmed speakers from the worlds most innovative organizations, including US Bank, Xbox, Intuit, Constellation Research, Gartner, and many more. The virtual conference, set for May 24-26, will feature keynotes from industry visionaries as well as breakout sessions, use cases, and panels led by data, analytics, and AI professionals.

The mission for Graph + AI Summit has always been to organize an open industry event to democratize and accelerate analytics, AI, and machine learning with graph algorithms. It is back, bringing together thought leaders, technical experts, and business innovators from the worlds largest and most successful organizations to share their graph-related experiences, best practices, ideas, and more, said Dr. Yu Xu, founder and CEO of TigerGraph. We will also announce and highlight the winning projects from the Graph for All Million Dollar Challenge at the summit. The challenge showcases how critical graph and AI are to addressing global issues, such as healthcare, the economy, and climate change. The submissions are astounding and were ready to give away one million dollars and share these ideas with the world!

Past Graph + AI Summits have attracted thousands of global graph enthusiasts from 70+ countries, all united in their commitment to using, advancing, and innovating with graph technology. Data scientists, data engineers, architects, and business and IT executives from over 180 of the Fortune 500 companies participated in the last event alone. Past speakers from Amazon, Capgemini, Gartner, Google, Microsoft, UnitedHealth Group, JPMorgan Chase, Mastercard, NewDay, Intuit, Jaguar Land Rover, Pinterest, Stanford University, Forrester Research, Accenture, KPMG, Intel, Dell, and Xilinx along with many others have shared how their organizations reaped the benefits of graph. Watch all 2021 sessions on demand here.

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Graph + AI Summit 2022 includes keynote presentations, executive roundtables, technical breakout sessions, industry tracks, and live workshops for advanced analytics and machine learning.

Keynote speakers presenting during conference general sessions include:

Jesse Janosov, general manager, Xbox Community at Microsoft, will discuss graph in gaming.

Afraz Jaffri, research director at Gartner, will present understanding when graph analytics and AI are best for your business.

Ray Wang, founder, chairman and principal analyst at Constellation Research, will deliver a keynote on the case for digital velocity.

Alaina Percival, founder and CEO of Women Who Code, will discuss diversity in data science and technology.

Notable roundtables and panel sessions include:

Connecting Data and Adapting to an Uncertain World: Speakers from Collibra, Databricks, and Kubrick will share the skills and knowledge needed to adapt to the challenges we face today.

How Are Business Leaders Implementing Digital Transformation?: Chris Preimesberger, editor for ZDNet and VentureBeat, will moderate a panel with executives from Capgemini, InfoSys, and Morrisons about how executives can achieve their strategic goals and embed digital in their business operations DNA to stay competitive.

Graph in Cybersecurity: Jonathan Swartz, senior reporter at MarketWatch, will moderate a panel with executives from Splunk, Data Connectors, and IBM about how graph analytics can help Chief Information Security Officers do more to understand and root out undetected advanced persistent threats.

Impact of AI on the Retail Industry: Executives from Capgemini, Google Cloud, and Reltio will discuss the challenges and opportunities retailers face today and the new technologies driving their success.

Defi, NFT, Metaverse - Where Do We Go From Here?: Speakers from Capgemini, Tempo Storm Esports, Rethink Ledgers, and Tokeny will examine graph-related topics, including taxonomy, digital asset creation, and blockchain, with examples derived from financial services, eSports, healthcare, and other industries during this dynamic, interactive panel discussion.

Additional sessions include speakers from AWS, Google, HPE, IBM, Intuit, Microsoft, US Bank, Verizon, and many more. The full agenda can be found here.

For more information on Graph + AI Summit or to register, please visit https://www.tigergraph.com/graphaisummit/

Graph for All Million Dollar Challenge Winners to be Announced at Graph + AI Summit

Last week, TigerGraph announced the finalists of the Graph for All Million Dollar Challenge, a global search for innovative ways to harness the power of graph technology and machine learning to solve real-world problems. The challenge brought together brilliant minds to build innovative solutions to better our future by answering one question: How will you change the world with graph? The challenge gained major traction worldwide with over 1,500 registrations from 100+ countries. Participants represent a wide range of backgrounds including data scientists, developers of all kinds full stack, front-end, back-end, mobile, product managers, designers, data engineers, machine learning engineers, and students. TigerGraph narrowed nearly 150 submissions down to the most innovative, game-changing, and applicable solutions. TigerGraph will reveal and feature all 15 winners of the challenge at the Graph + AI Summit 2022 event. For more information on the challenge and to see all finalists, please visit https://www.tigergraph.com/graph-for-all/.

Helpful Links

About TigerGraph TigerGraph is a platform for advanced analytics and machine learning on connected data. Based on the industrys first and only distributed native graph database, TigerGraphs proven technology supports advanced analytics and machine learning applications such as fraud detection, anti-money laundering (AML), entity resolution, customer 360, recommendations, knowledge graph, cybersecurity, supply chain, IoT, and network analysis. The company is headquartered in Redwood City, California, USA. Start free with tigergraph.com/cloud.

Media Contacts:

North AmericaTanya CarlssonOffleash PRtanya@offleashpr.com+1 (707) 529-6139

EMEAAnne HardingThe Message Machineanne@themessagemachine.com +44 7887 682943

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Graph + AI Summit 2022 Unveils Agenda Featuring Sessions and Speakers from US Bank, Xbox, Intuit, Constellation Research, Gartner, and More - Yahoo...