Artificial Intelligence
Global Artificial Intelligence (AI) Infrastructure Market to Reach $165.2 Billion by 2030
New York, July 03, 2023 (GLOBE NEWSWIRE) — Reportlinker.com announces the release of the report “Global Artificial Intelligence (AI) Infrastructure Industry” – https://www.reportlinker.com/p06030751/?utm_source=GNW
Hardware, one of the segments analyzed in the report, is projected to record a 23.3% CAGR and reach US$75.4 Billion by the end of the analysis period. Taking into account the ongoing post pandemic recovery, growth in the Software segment is readjusted to a revised 26.3% CAGR for the next 8-year period.
The U.S. Market is Estimated at $9 Billion, While China is Forecast to Grow at 32.7% CAGR
The Artificial Intelligence (AI) Infrastructure market in the U.S. is estimated at US$9 Billion in the year 2022. China, the world`s second largest economy, is forecast to reach a projected market size of US$38.2 Billion by the year 2030 trailing a CAGR of 32.7% over the analysis period 2022 to 2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 18.9% and 20.7% respectively over the 2022-2030 period. Within Europe, Germany is forecast to grow at approximately 22% CAGR.
Select Competitors (Total 140 Featured)
– Advanced Micro Devices (AMD)
– Amazon Web Services
– ARM
– Cadence Design Systems
– Cambricon Technologies
– CISCO Corporation
– Dell
– Google
– Graphcore
– Gyrfalcon Technology Inc.
– Habana Labs
– HPE
– IBM Corporation
– Imagination Technologies
– Intel Corporation
– Micron Technology
– Microsoft Corporation
– NVIDIA Corporation
– S K Hynix Inc.
– Samsung Electronics
– Synopsys Inc
– Tenstorrent
– Toshiba
– Wave Computing
– Xilinx
Read the full report: https://www.reportlinker.com/p06030751/?utm_source=GNW
I. METHODOLOGY
II. EXECUTIVE SUMMARY
1. MARKET OVERVIEW
From Pandemic to War & Inflation: ?Gloomy Outlook for 2023
Despite Signs of Easing Inflationary Conditions?
Here?s How Inflationary Pressures Affect the Economy
Russia-Ukraine War, the Primary Culprit Responsible for the
Hardships
Although Past Peak in 2023, Efforts to Solve the Inflation
Puzzle Should Continue
Here?s What?s Causing Inflationary Pressures in the Global Market
Shaken by the War, Global Oil Prices Spiral and Feed
Inflationary Pressures, Guiding the World Towards a Cost of
Living Crisis: Global Average Annual Brent Crude Oil Price
(In US$ Per Barrel) for Years 2017 through 2024
War-Induced Commodity Price Increases & Broad Based Price
Pressures Mark the Return of Global Inflation to the Highest
Level Seen Since 1996: Global Inflation Rates (In %) for the
Years 2019 Through 2024
Although Facing a Lower Recession Risk, Global Economic Growth
in 2023 to Slowdown Amid War, Inflation, Elevated Interest
Rates & Marginal Easing of Inflation: World Economic Growth
Projections (Real GDP, Annual % Change) for the Years 2020
Through 2024
Recession Triggered by Uncontrolled Inflation or Unemployment,
Which is the Greater Evil? Inflation Battling Policy Measures
to Slowdown Post Pandemic Recovery in Unemployment Rates:
Global Number of Unemployed People (In Million) for Years
2019 Through 2024
COVID-19 Pandemic Tips the Scale in Favor of AI Infrastructure
Market
Competitive Scenario
Select Innovations and Advancements
Artificial Intelligence (AI) Infrastructure – Global Key
Competitors Percentage Market Share in 2023 (E)
Competitive Market Presence – Strong/Active/Niche/Trivial for
Players Worldwide in 2023 (E)
Artificial Intelligence Continues to be on an Upward Trend
Global Market for Artificial Intelligence (AI) (In US$ Billion)
for Years 2023, 2025 & 2027
AI Infrastructure of the Future Trending Towards Becoming More
Modular
Steep Rise of AI Carves Pathway to Grand Success for Global AI
Infrastructure Market: Prospects & Outlook
Dynamic Factors Bringing Excitement for Global AI
Infrastructure Market: Drivers, Restraints, Opportunities, and
Challenges
Parallel Computing in AI Datacenters
Rising Uptake of AI Systems, Hardware & Software
Better Access to Cloud Applications
Focus on Customer Satisfaction & Cloud Applications
Rising Popularity of FPGAs
Shortage of Skilled Professionals & AI Hardware Experts
Increasing Requirement of Co-Processors
Industry-AL/ML Provider Partnerships
Data Privacy Issues & Lack of Quality Data
Analysis by Component
World Intelligence (AI) Infrastructure Market by Component
(2023 & 2030): Percentage Breakdown of Revenues for Hardware,
Software, and Services
Analysis by Technology
World Intelligence (AI) Infrastructure Market by Technology
(2023 & 2030): Percentage Breakdown of Revenues for Machine
Learning, and Deep Learning
Analysis by Deployment
World Intelligence (AI) Infrastructure Market by Deployment
(2023 & 2030): Percentage Breakdown of Revenues for Cloud,
Hybrid and On-Premise
Cloud Unleashing Advanced Machine Learning Capabilities
Regional Analysis
World Intelligence (AI) Infrastructure Market by Region (2023 &
2030): Percentage Breakdown of Revenues for Developed and
Developing Regions
World Artificial Intelligence (AI) Infrastructure Market –
Geographic Regions Ranked by CAGR (Revenues) for 2022-2030:
China, Asia-Pacific, Latin America, Rest of World, USA,
Europe, Canada, and Japan
Artificial Intelligence (AI): A Prelude
Technologies Enabling AI
Interconnection is Crucial to Develop AI Successfully
Artificial Intelligence Infrastructure Gains Momentum
Recent Market Activity
2. FOCUS ON SELECT PLAYERS
3. MARKET TRENDS & DRIVERS
Accelerating Pace of Digital Transformation to Benefit Demand
for AI
Digital Transformation by Industry: 2022E
Industry Adoption of Artificial Intelligence (AI) by Function:
2020
Accelerating AI Growth Backed by Future Secure Digital
Infrastructure
Industrial IoT, Robotics and Big Data to Stimulate AI
Implementations
Global Investments on Industry 4.0 Technologies (in US$
Billion) for the Years 2017, 2020, & 2023
Demand for Artificial Intelligence, Machine Learning, and Deep
Learning Gains Momentum
Purpose-Built AI Infrastructure Gaining Importance in Modern
Enterprises
AI/ML Offers Significant ROI Possibilities for Enterprises
AI-ready Infrastructure Utilization Help Accelerating the Journey
Can AI Be Trusted for Implementation in Critical Infrastructures?
Increasing Adoption of AI Technology to Boost AI Chipsets Market
Use of Graphic Processing Units (GPUs) Witnesses a Robust Increase
AI as a Service Market: Obviating the Need to Make Huge Initial
Investments
Growing Adoption of AI Due to Pandemic to Drive Long Term Growth
Barriers Restraining AI Adoption in Healthcare Sector
Increasing investments and R&D in AI Start-Ups to Jack up
Market Demand
Number of AI Startups with $1 Billion Valuations for the Years
2014-2020
AI Cumulative Funding (in US$ Billion) by Category (As of 2020)
AI Applications and Major Startups
Industry Collaboration with AI & ML Solutions to Optimize
Digital Transformation Strategies
Growth Linked to Growing Focus on Parallel Computing in AI Data
Centers
Global Market for Modular Data Centers (In US$ Million) for
Years 2023, 2025 and 2027
Machine Learning and AI-Assisted Platforms Personalize Customer
Experiences in Marketing Applications
Ranking of Business Outcomes Realized through AI Application in
Marketing
New and Improved Concepts in ML and AI take Stage
Low-Cost, High-Performance Machine Learning Infrastructure
Continues Speeding Up Innovations in the Cloud
Rapid Shifting to Cloud-based Infrastructure is Vital to
Leverage Full Potential of Machine Learning
The Ways by Which AWS Assists Its Customers in Their Rapid AI/
ML Transformation
Deep Learning and Digital Assistant Technologies Present
Significant Growth Potential
Deep Learning & ML-Based Tools Fuel Self-Service Automation
Major Challenges Confronting Artificial Intelligence
Key Challenges Associated With AI Implementation
Increasing Use of Artificial Intelligence Leads to Regulation
Concern in Enterprises
4. GLOBAL MARKET PERSPECTIVE
Table 1: World Artificial Intelligence (AI) Infrastructure
Market Analysis of Annual Sales in US$ Million for Years 2018
through 2030
Table 2: World Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Geographic
Region – USA, Canada, Japan, China, Europe, Asia-Pacific, Latin
America and Rest of World Markets – Independent Analysis of
Annual Revenues in US$ Million for Years 2022 through 2030 and
% CAGR
Table 3: World Historic Review for Artificial Intelligence (AI)
Infrastructure by Geographic Region – USA, Canada, Japan,
China, Europe, Asia-Pacific, Latin America and Rest of World
Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2018 through 2021 and % CAGR
Table 4: World 12-Year Perspective for Artificial Intelligence
(AI) Infrastructure by Geographic Region – Percentage Breakdown
of Value Revenues for USA, Canada, Japan, China, Europe,
Asia-Pacific, Latin America and Rest of World Markets for Years
2018, 2023 & 2030
Table 5: World Recent Past, Current & Future Analysis for
Hardware by Geographic Region – USA, Canada, Japan, China,
Europe, Asia-Pacific, Latin America and Rest of World Markets –
Independent Analysis of Annual Revenues in US$ Million for
Years 2022 through 2030 and % CAGR
Table 6: World Historic Review for Hardware by Geographic
Region – USA, Canada, Japan, China, Europe, Asia-Pacific, Latin
America and Rest of World Markets – Independent Analysis of
Annual Revenues in US$ Million for Years 2018 through 2021 and
% CAGR
Table 7: World 12-Year Perspective for Hardware by Geographic
Region – Percentage Breakdown of Value Revenues for USA,
Canada, Japan, China, Europe, Asia-Pacific, Latin America and
Rest of World for Years 2018, 2023 & 2030
Table 8: World Recent Past, Current & Future Analysis for
Software by Geographic Region – USA, Canada, Japan, China,
Europe, Asia-Pacific, Latin America and Rest of World Markets –
Independent Analysis of Annual Revenues in US$ Million for
Years 2022 through 2030 and % CAGR
Table 9: World Historic Review for Software by Geographic
Region – USA, Canada, Japan, China, Europe, Asia-Pacific, Latin
America and Rest of World Markets – Independent Analysis of
Annual Revenues in US$ Million for Years 2018 through 2021 and
% CAGR
Table 10: World 12-Year Perspective for Software by Geographic
Region – Percentage Breakdown of Value Revenues for USA,
Canada, Japan, China, Europe, Asia-Pacific, Latin America and
Rest of World for Years 2018, 2023 & 2030
Table 11: World Recent Past, Current & Future Analysis for
Services by Geographic Region – USA, Canada, Japan, China,
Europe, Asia-Pacific, Latin America and Rest of World Markets –
Independent Analysis of Annual Revenues in US$ Million for
Years 2022 through 2030 and % CAGR
Table 12: World Historic Review for Services by Geographic
Region – USA, Canada, Japan, China, Europe, Asia-Pacific, Latin
America and Rest of World Markets – Independent Analysis of
Annual Revenues in US$ Million for Years 2018 through 2021 and
% CAGR
Table 13: World 12-Year Perspective for Services by Geographic
Region – Percentage Breakdown of Value Revenues for USA,
Canada, Japan, China, Europe, Asia-Pacific, Latin America and
Rest of World for Years 2018, 2023 & 2030
Table 14: World Recent Past, Current & Future Analysis for
On-Premise by Geographic Region – USA, Canada, Japan, China,
Europe, Asia-Pacific, Latin America and Rest of World Markets –
Independent Analysis of Annual Revenues in US$ Million for
Years 2022 through 2030 and % CAGR
Table 15: World Historic Review for On-Premise by Geographic
Region – USA, Canada, Japan, China, Europe, Asia-Pacific, Latin
America and Rest of World Markets – Independent Analysis of
Annual Revenues in US$ Million for Years 2018 through 2021 and
% CAGR
Table 16: World 12-Year Perspective for On-Premise by
Geographic Region – Percentage Breakdown of Value Revenues for
USA, Canada, Japan, China, Europe, Asia-Pacific, Latin America
and Rest of World for Years 2018, 2023 & 2030
Table 17: World Recent Past, Current & Future Analysis for
Cloud by Geographic Region – USA, Canada, Japan, China, Europe,
Asia-Pacific, Latin America and Rest of World Markets –
Independent Analysis of Annual Revenues in US$ Million for
Years 2022 through 2030 and % CAGR
Table 18: World Historic Review for Cloud by Geographic Region –
USA, Canada, Japan, China, Europe, Asia-Pacific, Latin
America and Rest of World Markets – Independent Analysis of
Annual Revenues in US$ Million for Years 2018 through 2021 and
% CAGR
Table 19: World 12-Year Perspective for Cloud by Geographic
Region – Percentage Breakdown of Value Revenues for USA,
Canada, Japan, China, Europe, Asia-Pacific, Latin America and
Rest of World for Years 2018, 2023 & 2030
Table 20: World Recent Past, Current & Future Analysis for
Hybrid by Geographic Region – USA, Canada, Japan, China,
Europe, Asia-Pacific, Latin America and Rest of World Markets –
Independent Analysis of Annual Revenues in US$ Million for
Years 2022 through 2030 and % CAGR
Table 21: World Historic Review for Hybrid by Geographic Region –
USA, Canada, Japan, China, Europe, Asia-Pacific, Latin
America and Rest of World Markets – Independent Analysis of
Annual Revenues in US$ Million for Years 2018 through 2021 and
% CAGR
Table 22: World 12-Year Perspective for Hybrid by Geographic
Region – Percentage Breakdown of Value Revenues for USA,
Canada, Japan, China, Europe, Asia-Pacific, Latin America and
Rest of World for Years 2018, 2023 & 2030
Table 23: World Recent Past, Current & Future Analysis for
Machine Learning by Geographic Region – USA, Canada, Japan,
China, Europe, Asia-Pacific, Latin America and Rest of World
Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2022 through 2030 and % CAGR
Table 24: World Historic Review for Machine Learning by
Geographic Region – USA, Canada, Japan, China, Europe,
Asia-Pacific, Latin America and Rest of World Markets –
Independent Analysis of Annual Revenues in US$ Million for
Years 2018 through 2021 and % CAGR
Table 25: World 12-Year Perspective for Machine Learning by
Geographic Region – Percentage Breakdown of Value Revenues for
USA, Canada, Japan, China, Europe, Asia-Pacific, Latin America
and Rest of World for Years 2018, 2023 & 2030
Table 26: World Recent Past, Current & Future Analysis for Deep
Learning by Geographic Region – USA, Canada, Japan, China,
Europe, Asia-Pacific, Latin America and Rest of World Markets –
Independent Analysis of Annual Revenues in US$ Million for
Years 2022 through 2030 and % CAGR
Table 27: World Historic Review for Deep Learning by Geographic
Region – USA, Canada, Japan, China, Europe, Asia-Pacific, Latin
America and Rest of World Markets – Independent Analysis of
Annual Revenues in US$ Million for Years 2018 through 2021 and
% CAGR
Table 28: World 12-Year Perspective for Deep Learning by
Geographic Region – Percentage Breakdown of Value Revenues for
USA, Canada, Japan, China, Europe, Asia-Pacific, Latin America
and Rest of World for Years 2018, 2023 & 2030
Table 29: World Recent Past, Current & Future Analysis for
Inference by Geographic Region – USA, Canada, Japan, China,
Europe, Asia-Pacific, Latin America and Rest of World Markets –
Independent Analysis of Annual Revenues in US$ Million for
Years 2022 through 2030 and % CAGR
Table 30: World Historic Review for Inference by Geographic
Region – USA, Canada, Japan, China, Europe, Asia-Pacific, Latin
America and Rest of World Markets – Independent Analysis of
Annual Revenues in US$ Million for Years 2018 through 2021 and
% CAGR
Table 31: World 12-Year Perspective for Inference by Geographic
Region – Percentage Breakdown of Value Revenues for USA,
Canada, Japan, China, Europe, Asia-Pacific, Latin America and
Rest of World for Years 2018, 2023 & 2030
Table 32: World Recent Past, Current & Future Analysis for
Training by Geographic Region – USA, Canada, Japan, China,
Europe, Asia-Pacific, Latin America and Rest of World Markets –
Independent Analysis of Annual Revenues in US$ Million for
Years 2022 through 2030 and % CAGR
Table 33: World Historic Review for Training by Geographic
Region – USA, Canada, Japan, China, Europe, Asia-Pacific, Latin
America and Rest of World Markets – Independent Analysis of
Annual Revenues in US$ Million for Years 2018 through 2021 and
% CAGR
Table 34: World 12-Year Perspective for Training by Geographic
Region – Percentage Breakdown of Value Revenues for USA,
Canada, Japan, China, Europe, Asia-Pacific, Latin America and
Rest of World for Years 2018, 2023 & 2030
III. MARKET ANALYSIS
UNITED STATES
Artificial Intelligence (AI) Infrastructure Market Presence –
Strong/Active/Niche/Trivial – Key Competitors in the United
States for 2023 (E)
Table 35: USA Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Component –
Hardware, Software and Services – Independent Analysis of
Annual Revenues in US$ Million for the Years 2022 through 2030
and % CAGR
Table 36: USA Historic Review for Artificial Intelligence (AI)
Infrastructure by Component – Hardware, Software and Services
Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2018 through 2021 and % CAGR
Table 37: USA 12-Year Perspective for Artificial Intelligence
(AI) Infrastructure by Component – Percentage Breakdown of
Value Revenues for Hardware, Software and Services for the
Years 2018, 2023 & 2030
Table 38: USA Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Deployment –
On-Premise, Cloud and Hybrid – Independent Analysis of Annual
Revenues in US$ Million for the Years 2022 through 2030 and %
CAGR
Table 39: USA Historic Review for Artificial Intelligence (AI)
Infrastructure by Deployment – On-Premise, Cloud and Hybrid
Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2018 through 2021 and % CAGR
Table 40: USA 12-Year Perspective for Artificial Intelligence
(AI) Infrastructure by Deployment – Percentage Breakdown of
Value Revenues for On-Premise, Cloud and Hybrid for the Years
2018, 2023 & 2030
Table 41: USA Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Technology –
Machine Learning and Deep Learning – Independent Analysis of
Annual Revenues in US$ Million for the Years 2022 through 2030
and % CAGR
Table 42: USA Historic Review for Artificial Intelligence (AI)
Infrastructure by Technology – Machine Learning and Deep
Learning Markets – Independent Analysis of Annual Revenues in
US$ Million for Years 2018 through 2021 and % CAGR
Table 43: USA 12-Year Perspective for Artificial Intelligence
(AI) Infrastructure by Technology – Percentage Breakdown of
Value Revenues for Machine Learning and Deep Learning for the
Years 2018, 2023 & 2030
Table 44: USA Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Function –
Inference and Training – Independent Analysis of Annual
Revenues in US$ Million for the Years 2022 through 2030 and %
CAGR
Table 45: USA Historic Review for Artificial Intelligence (AI)
Infrastructure by Function – Inference and Training Markets –
Independent Analysis of Annual Revenues in US$ Million for
Years 2018 through 2021 and % CAGR
Table 46: USA 12-Year Perspective for Artificial Intelligence
(AI) Infrastructure by Function – Percentage Breakdown of Value
Revenues for Inference and Training for the Years 2018, 2023 &
2030
CANADA
Artificial Intelligence (AI) Infrastructure Market Presence –
Strong/Active/Niche/Trivial – Key Competitors in Canada for
2023 (E)
Table 47: Canada Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Component –
Hardware, Software and Services – Independent Analysis of
Annual Revenues in US$ Million for the Years 2022 through 2030
and % CAGR
Table 48: Canada Historic Review for Artificial Intelligence
(AI) Infrastructure by Component – Hardware, Software and
Services Markets – Independent Analysis of Annual Revenues in
US$ Million for Years 2018 through 2021 and % CAGR
Table 49: Canada 12-Year Perspective for Artificial
Intelligence (AI) Infrastructure by Component – Percentage
Breakdown of Value Revenues for Hardware, Software and Services
for the Years 2018, 2023 & 2030
Table 50: Canada Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Deployment –
On-Premise, Cloud and Hybrid – Independent Analysis of Annual
Revenues in US$ Million for the Years 2022 through 2030 and %
CAGR
Table 51: Canada Historic Review for Artificial Intelligence
(AI) Infrastructure by Deployment – On-Premise, Cloud and
Hybrid Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2018 through 2021 and % CAGR
Table 52: Canada 12-Year Perspective for Artificial
Intelligence (AI) Infrastructure by Deployment – Percentage
Breakdown of Value Revenues for On-Premise, Cloud and Hybrid
for the Years 2018, 2023 & 2030
Table 53: Canada Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Technology –
Machine Learning and Deep Learning – Independent Analysis of
Annual Revenues in US$ Million for the Years 2022 through 2030
and % CAGR
Table 54: Canada Historic Review for Artificial Intelligence
(AI) Infrastructure by Technology – Machine Learning and Deep
Learning Markets – Independent Analysis of Annual Revenues in
US$ Million for Years 2018 through 2021 and % CAGR
Table 55: Canada 12-Year Perspective for Artificial
Intelligence (AI) Infrastructure by Technology – Percentage
Breakdown of Value Revenues for Machine Learning and Deep
Learning for the Years 2018, 2023 & 2030
Table 56: Canada Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Function –
Inference and Training – Independent Analysis of Annual
Revenues in US$ Million for the Years 2022 through 2030 and %
CAGR
Table 57: Canada Historic Review for Artificial Intelligence
(AI) Infrastructure by Function – Inference and Training
Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2018 through 2021 and % CAGR
Table 58: Canada 12-Year Perspective for Artificial
Intelligence (AI) Infrastructure by Function – Percentage
Breakdown of Value Revenues for Inference and Training for the
Years 2018, 2023 & 2030
JAPAN
Table 59: Japan Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Component –
Hardware, Software and Services – Independent Analysis of
Annual Revenues in US$ Million for the Years 2022 through 2030
and % CAGR
Table 60: Japan Historic Review for Artificial Intelligence
(AI) Infrastructure by Component – Hardware, Software and
Services Markets – Independent Analysis of Annual Revenues in
US$ Million for Years 2018 through 2021 and % CAGR
Table 61: Japan 12-Year Perspective for Artificial Intelligence
(AI) Infrastructure by Component – Percentage Breakdown of
Value Revenues for Hardware, Software and Services for the
Years 2018, 2023 & 2030
Table 62: Japan Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Deployment –
On-Premise, Cloud and Hybrid – Independent Analysis of Annual
Revenues in US$ Million for the Years 2022 through 2030 and %
CAGR
Table 63: Japan Historic Review for Artificial Intelligence
(AI) Infrastructure by Deployment – On-Premise, Cloud and
Hybrid Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2018 through 2021 and % CAGR
Table 64: Japan 12-Year Perspective for Artificial Intelligence
(AI) Infrastructure by Deployment – Percentage Breakdown of
Value Revenues for On-Premise, Cloud and Hybrid for the Years
2018, 2023 & 2030
Table 65: Japan Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Technology –
Machine Learning and Deep Learning – Independent Analysis of
Annual Revenues in US$ Million for the Years 2022 through 2030
and % CAGR
Table 66: Japan Historic Review for Artificial Intelligence
(AI) Infrastructure by Technology – Machine Learning and Deep
Learning Markets – Independent Analysis of Annual Revenues in
US$ Million for Years 2018 through 2021 and % CAGR
Table 67: Japan 12-Year Perspective for Artificial Intelligence
(AI) Infrastructure by Technology – Percentage Breakdown of
Value Revenues for Machine Learning and Deep Learning for the
Years 2018, 2023 & 2030
Table 68: Japan Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Function –
Inference and Training – Independent Analysis of Annual
Revenues in US$ Million for the Years 2022 through 2030 and %
CAGR
Table 69: Japan Historic Review for Artificial Intelligence
(AI) Infrastructure by Function – Inference and Training
Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2018 through 2021 and % CAGR
Table 70: Japan 12-Year Perspective for Artificial Intelligence
(AI) Infrastructure by Function – Percentage Breakdown of Value
Revenues for Inference and Training for the Years 2018, 2023 &
2030
CHINA
Artificial Intelligence (AI) Infrastructure Market Presence –
Strong/Active/Niche/Trivial – Key Competitors in China for
2023 (E)
Table 71: China Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Component –
Hardware, Software and Services – Independent Analysis of
Annual Revenues in US$ Million for the Years 2022 through 2030
and % CAGR
Table 72: China Historic Review for Artificial Intelligence
(AI) Infrastructure by Component – Hardware, Software and
Services Markets – Independent Analysis of Annual Revenues in
US$ Million for Years 2018 through 2021 and % CAGR
Table 73: China 12-Year Perspective for Artificial Intelligence
(AI) Infrastructure by Component – Percentage Breakdown of
Value Revenues for Hardware, Software and Services for the
Years 2018, 2023 & 2030
Table 74: China Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Deployment –
On-Premise, Cloud and Hybrid – Independent Analysis of Annual
Revenues in US$ Million for the Years 2022 through 2030 and %
CAGR
Table 75: China Historic Review for Artificial Intelligence
(AI) Infrastructure by Deployment – On-Premise, Cloud and
Hybrid Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2018 through 2021 and % CAGR
Table 76: China 12-Year Perspective for Artificial Intelligence
(AI) Infrastructure by Deployment – Percentage Breakdown of
Value Revenues for On-Premise, Cloud and Hybrid for the Years
2018, 2023 & 2030
Table 77: China Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Technology –
Machine Learning and Deep Learning – Independent Analysis of
Annual Revenues in US$ Million for the Years 2022 through 2030
and % CAGR
Table 78: China Historic Review for Artificial Intelligence
(AI) Infrastructure by Technology – Machine Learning and Deep
Learning Markets – Independent Analysis of Annual Revenues in
US$ Million for Years 2018 through 2021 and % CAGR
Table 79: China 12-Year Perspective for Artificial Intelligence
(AI) Infrastructure by Technology – Percentage Breakdown of
Value Revenues for Machine Learning and Deep Learning for the
Years 2018, 2023 & 2030
Table 80: China Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Function –
Inference and Training – Independent Analysis of Annual
Revenues in US$ Million for the Years 2022 through 2030 and %
CAGR
Table 81: China Historic Review for Artificial Intelligence
(AI) Infrastructure by Function – Inference and Training
Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2018 through 2021 and % CAGR
Table 82: China 12-Year Perspective for Artificial Intelligence
(AI) Infrastructure by Function – Percentage Breakdown of Value
Revenues for Inference and Training for the Years 2018, 2023 &
2030
EUROPE
Artificial Intelligence (AI) Infrastructure Market Presence –
Strong/Active/Niche/Trivial – Key Competitors in Europe for
2023 (E)
Table 83: Europe Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Geographic
Region – France, Germany, Italy, UK, Spain, Russia and Rest of
Europe Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2022 through 2030 and % CAGR
Table 84: Europe Historic Review for Artificial Intelligence
(AI) Infrastructure by Geographic Region – France, Germany,
Italy, UK, Spain, Russia and Rest of Europe Markets –
Independent Analysis of Annual Revenues in US$ Million for
Years 2018 through 2021 and % CAGR
Table 85: Europe 12-Year Perspective for Artificial
Intelligence (AI) Infrastructure by Geographic Region –
Percentage Breakdown of Value Revenues for France, Germany,
Italy, UK, Spain, Russia and Rest of Europe Markets for Years
2018, 2023 & 2030
Table 86: Europe Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Component –
Hardware, Software and Services – Independent Analysis of
Annual Revenues in US$ Million for the Years 2022 through 2030
and % CAGR
Table 87: Europe Historic Review for Artificial Intelligence
(AI) Infrastructure by Component – Hardware, Software and
Services Markets – Independent Analysis of Annual Revenues in
US$ Million for Years 2018 through 2021 and % CAGR
Table 88: Europe 12-Year Perspective for Artificial
Intelligence (AI) Infrastructure by Component – Percentage
Breakdown of Value Revenues for Hardware, Software and Services
for the Years 2018, 2023 & 2030
Table 89: Europe Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Deployment –
On-Premise, Cloud and Hybrid – Independent Analysis of Annual
Revenues in US$ Million for the Years 2022 through 2030 and %
CAGR
Table 90: Europe Historic Review for Artificial Intelligence
(AI) Infrastructure by Deployment – On-Premise, Cloud and
Hybrid Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2018 through 2021 and % CAGR
Table 91: Europe 12-Year Perspective for Artificial
Intelligence (AI) Infrastructure by Deployment – Percentage
Breakdown of Value Revenues for On-Premise, Cloud and Hybrid
for the Years 2018, 2023 & 2030
Table 92: Europe Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Technology –
Machine Learning and Deep Learning – Independent Analysis of
Annual Revenues in US$ Million for the Years 2022 through 2030
and % CAGR
Table 93: Europe Historic Review for Artificial Intelligence
(AI) Infrastructure by Technology – Machine Learning and Deep
Learning Markets – Independent Analysis of Annual Revenues in
US$ Million for Years 2018 through 2021 and % CAGR
Table 94: Europe 12-Year Perspective for Artificial
Intelligence (AI) Infrastructure by Technology – Percentage
Breakdown of Value Revenues for Machine Learning and Deep
Learning for the Years 2018, 2023 & 2030
Table 95: Europe Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Function –
Inference and Training – Independent Analysis of Annual
Revenues in US$ Million for the Years 2022 through 2030 and %
CAGR
Table 96: Europe Historic Review for Artificial Intelligence
(AI) Infrastructure by Function – Inference and Training
Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2018 through 2021 and % CAGR
Table 97: Europe 12-Year Perspective for Artificial
Intelligence (AI) Infrastructure by Function – Percentage
Breakdown of Value Revenues for Inference and Training for the
Years 2018, 2023 & 2030
FRANCE
Table 98: France Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Component –
Hardware, Software and Services – Independent Analysis of
Annual Revenues in US$ Million for the Years 2022 through 2030
and % CAGR
Table 99: France Historic Review for Artificial Intelligence
(AI) Infrastructure by Component – Hardware, Software and
Services Markets – Independent Analysis of Annual Revenues in
US$ Million for Years 2018 through 2021 and % CAGR
Table 100: France 12-Year Perspective for Artificial
Intelligence (AI) Infrastructure by Component – Percentage
Breakdown of Value Revenues for Hardware, Software and Services
for the Years 2018, 2023 & 2030
Table 101: France Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Deployment –
On-Premise, Cloud and Hybrid – Independent Analysis of Annual
Revenues in US$ Million for the Years 2022 through 2030 and %
CAGR
Table 102: France Historic Review for Artificial Intelligence
(AI) Infrastructure by Deployment – On-Premise, Cloud and
Hybrid Markets – Independent Analysis of Annual Revenues in US$
Million for Years 2018 through 2021 and % CAGR
Table 103: France 12-Year Perspective for Artificial
Intelligence (AI) Infrastructure by Deployment – Percentage
Breakdown of Value Revenues for On-Premise, Cloud and Hybrid
for the Years 2018, 2023 & 2030
Table 104: France Recent Past, Current & Future Analysis for
Artificial Intelligence (AI) Infrastructure by Technology –
Machine Learning and Deep Learning – Independent Analysis of
Annual Revenues in US$ Million for the Years 2022 through 2030
and % CAGR
Table 105: France Historic Review for Artificial Intelligence
(AI) Infrastructure by Technology – Machine Learning and Deep
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Artificial Intelligence
Dubai World Trade Centre Drives Impact as Economic Output Surges to US$4.98 Billion in 2023, up 40% YoY
DUBAI, UAE, May 20, 2024 /PRNewswire/ — Dubai World Trade Centre (DWTC), a global leader in the events and exhibitions industry, has once again demonstrated its significant impact on Dubai’s economy in 2023, welcoming 2.47 million participants and hosting 301 events, 76 of which, were large-scale events that attracted 1.54 million attendees, with 46% from overseas.
DWTC’s 2023 Economic Impact Assessment (EIA) Report, based on its 76 large-scale events (2000 or more attendees) revealed an impressive surge in the total economic output, reaching US$4.98 billion, marking an incredible 40% YoY increase, with high returns for adjacent industries such as Travel, Accommodation and Retail, connected to the Meetings Incentives Conferences and Exhibitions (MICE) ecosystem.
DWTC’s large-scale events generated a substantial US$2.87 billion Gross Value Added (GVA) to Dubai’s GDP, retaining an impressive 58% of the total economic output locally. International participation soared by 53%, with overseas visitors driving 6.2 times more contribution than domestic counterparts.
Events hosted at DWTC supported 69,281 jobs, generating US$915 million in disposable household income for the city’s residents. The substantial economic impact of these events extends beyond direct revenue generation, fostering socio-economic development and contributing to Dubai’s status as a leading global business hub.
His Excellency Helal Saeed Almarri, Director General of DWTC Authority, said: “Aligned with Dubai’s Economic Agenda D33, we continue to spearhead efforts in sector diversification, reinforcing the city’s stature as a leading global business hub. The remarkable accomplishments of 2023, presented in the ‘DWTC Economic Impact Assessment Report’ demonstrate that Dubai’s MICE sector, driven by DWTC, remains a vital pillar of financial resilience and growth underscoring our accelerated strides towards sustainable socio-economic development. The increase in international participation, along with the significant economic impact generated across diverse sectors such as travel, accommodation and retail, highlights the city’s steadfast commitment to propelling business tourism.”
The venue’s formidable events portfolio strategically aligned with Dubai’s economic priorities, showcasing Healthcare, Medical, and Scientific; Information Technology (IT); and Food, Hotel, and Catering as the top contributors. These leading sectors collectively accounted for 59% (US$1.71 billion) of the GVA to Dubai’s economy, and 49% (747,468) of the total large-scale event visitation.
Adjacent sectors, including hotels, air travel, and local transportation experienced a significant boost in economic activity. The direct revenue generated through expenditure was nearly US$2.94 billion.
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View original content:https://www.prnewswire.co.uk/news-releases/dubai-world-trade-centre-drives-impact-as-economic-output-surges-to-us4-98-billion-in-2023–up-40-yoy-302150038.html
Artificial Intelligence
Aramco signs agreement with Pasqal to deploy first quantum computer in the Kingdom of Saudi Arabia
DHAHRAN, Saudi Arabia, May 20, 2024 /PRNewswire/ — Aramco, one of the world’s leading integrated energy and chemicals companies, has signed an agreement with Pasqal, a global leader in neutral atom quantum computing, to install the first quantum computer in the Kingdom of Saudi Arabia.
The agreement will see Pasqal install, maintain, and operate a 200-qubit quantum computer, which is scheduled for deployment in the second half of 2025.
Ahmad Al-Khowaiter, Aramco EVP of Technology & Innovation, said: “Aramco is delighted to partner with Pasqal to bring cutting-edge, high-performance quantum computing capabilities to the Kingdom. In a rapidly evolving digital landscape, we believe it is crucial to seize opportunities presented by new, impactful technologies and we aim to pioneer the use of quantum computing in the energy sector. Our agreement with Pasqal allows us to harness the expertise of a leading player in this field, as we continue to build state-of-the-art solutions into our business. It is also further evidence of our contribution to the growth of the digital economy in Saudi Arabia.”
Georges-Olivier Reymond, Pasqal CEO & Co-founder, said: “The era of quantum computing is here. No longer confined to theory, it’s transitioning to real-world applications, empowering organisations to solve previously intractable problems at scale. Since launching Pasqal in 2019, we have directed our efforts towards concrete quantum computing algorithms immediately applicable to customer use cases. Through this agreement, we’ll be at the forefront of accelerating commercial adoption of this transformative technology in Saudi Arabia. This isn’t just any quantum computer; it will be the most powerful tool deployed for industrial usages, unlocking a new era of innovation for businesses and society.”
The quantum computer will initially use an approach called “analog mode.” Within the following year, the system will be upgraded to a more advanced hybrid “analog-digital mode,” which is more powerful and able to solve even more complex problems.
Pasqal and Aramco intend to leverage the quantum computer to identify new use cases, and have an ambitious vision to establish a powerhouse for quantum research within Saudi Arabia. This would involve leading academic institutions with the aim of fostering breakthroughs in quantum algorithm development — a crucial step for unlocking the true potential of quantum computing.
The agreement also accelerates Pasqal’s activity in Saudi Arabia, having established an office in the Kingdom in 2023, and follows the signing of a Memorandum of Understanding between the companies in 2022 to collaborate on quantum computing capabilities and applications in the energy sector. In 2023, Aramco’s Wa’ed Ventures also participated in Pasqal’s Series B fundraising round.
About Aramco
Aramco is a global integrated energy and chemicals company. We are driven by our core belief that energy is opportunity. From producing approximately one in every eight barrels of the world’s oil supply to developing new energy technologies, our global team is dedicated to creating impact in all that we do. We focus on making our resources more dependable, more sustainable and more useful. This helps promote stability and long-term growth around the world. www.aramco.com
About PASQAL
Pasqal is a leading Quantum Computing company that builds quantum processors from ordered neutral atoms in 2D and 3D arrays to bring a practical quantum advantage to its customers and address real-world problems. Pasqal was founded in 2019, out of the Institut d’Optique, by Georges-Olivier Reymond, Christophe Jurczak, Professor Dr. Alain Aspect – Nobel Prize Laureate Physics, 2022, Dr. Antoine Browaeys and Dr. Thierry Lahaye. Pasqal has secured more than €140 million in financing to date. To learn more about Pasqal, visit www.pasqal.com.
Disclaimer
The press release contains forward-looking statements. All statements other than statements relating to historical or current facts included in the press release are forward-looking statements. Forward-looking statements give the Company’s current expectations and projections relating to its capital expenditures and investments, major projects, upstream and downstream performance, including relative to peers. These statements may include, without limitation, any statements preceded by, followed by or including words such as “target,” “believe,” “expect,” “aim,” “intend,” “may,” “anticipate,” “estimate,” “plan,” “project,” “can have,” “likely,” “should,” “could,” and other words and terms of similar meaning or the negative thereof. Such forward-looking statements involve known and unknown risks, uncertainties and other important factors beyond the Company’s control that could cause the Company’s actual results, performance or achievements to be materially different from the expected results, performance, or achievements expressed or implied by such forward-looking statements, including the following factors: global supply, demand and price fluctuations of oil, gas and petrochemicals; global economic conditions; competition in the industries in which Saudi Aramco operates; climate change concerns, weather conditions and related impacts on the global demand for hydrocarbons and hydrocarbon-based products; risks related to Saudi Aramco’s ability to successfully meet its ESG targets, including its failure to fully meet its GHG emissions reduction targets by 2050; conditions affecting the transportation of products; operational risk and hazards common in the oil and gas, refining and petrochemicals industries; the cyclical nature of the oil and gas, refining and petrochemicals industries; political and social instability and unrest and actual or potential armed conflicts in the MENA region and other areas; natural disasters and public health pandemics or epidemics; the management of Saudi Aramco’s growth; the management of the Company’s subsidiaries, joint operations, joint ventures, associates and entities in which it holds a minority interest; Saudi Aramco’s exposure to inflation, interest rate risk and foreign exchange risk; risks related to operating in a regulated industry and changes to oil, gas, environmental or other regulations that impact the industries in which Saudi Aramco operates; legal proceedings, international trade matters, and other disputes or agreements; and other risks and uncertainties that could cause actual results to differ from the forward-looking statements in this press release, as set forth in the Company’s latest periodic reports filed with the Saudi Stock Exchange. For additional information on the potential risks and uncertainties that could cause actual results to differ from the results predicted please see the Company’s latest periodic reports filed with the Saudi Stock Exchange. Such forward-looking statements are based on numerous assumptions regarding the Company’s present and future business strategies and the environment in which it will operate in the future. The information contained in the press release, including but not limited to forward-looking statements, applies only as of the date of this press release and is not intended to give any assurances as to future results. The Company expressly disclaims any obligation or undertaking to disseminate any updates or revisions to the press release, including any financial data or forward-looking statements, whether as a result of new information, future events or otherwise, unless required by applicable law or regulation. No person should construe the press release as financial, tax or investment advice. Undue reliance should not be placed on the forward-looking statements.
Aramco Contact Information:
@aramco
View original content:https://www.prnewswire.co.uk/news-releases/aramco-signs-agreement-with-pasqal-to-deploy-first-quantum-computer-in-the-kingdom-of-saudi-arabia-302150019.html
Artificial Intelligence
Compact Solutions, Mighty Results: Cervoz Unleashes the Power of Edge Computing
TAIPEI, May 20, 2024 /PRNewswire/ — Cervoz Technology, a leader in industrial-grade storage, memory, and expansion solutions, is powering the evolution of edge computing with its innovative solutions.
In today’s data-rich landscape, businesses rely on insights from IoT devices. With advancements in AI and 5G, data volumes surge, straining traditional cloud computing with bandwidth and latency issues. Edge Computing emerges as a solution, processing data at its source for real-time insights crucial for applications like digital twins, autonomous vehicles, and smart healthcare.
What is Edge Computing?
Edge Computing is a decentralized IT architecture that processes data near its origin, often at the network’s edge. This approach divides tasks from central data centers to edge devices and nodes. It enables faster, deeper insights and enhances responsiveness, improving speed and reducing latency compared to centralized clouds. Typically, an Edge Computing system comprises three layers: device, edge, and cloud.
The Device Layer
The device layer, situated closest to the physical world, comprises endpoint devices such as sensors, controllers, and cameras, among others. The layer prioritizes data collection and initial processing for real-time response and efficiency. It requires highly reliable, compact, and energy-efficient components. Cervoz’s M.2 2230 (A+E key /B+M key) NVMe SSDs and DDR4 SO-DIMM modules optimize this setup with fast data access and efficient storage in space-saving designs. They operate reliably across a wide temperature range (-40°C to 85°C) and feature additional conformal coating and anti-vibration filling for enhanced performance in harsh environments.
The Edge Layer
The edge layer, composed of edge servers and gateways, serves as a crucial link between device-layer data sources and cloud-based operations. It is designed for extensive data handling, filtering, and analytics, emphasizing quick operations and real-time responses to minimize reliance on remote data centers. For optimal performance, components must manage high processing loads with minimal latency and maximum stability. NVMe SSDs boasting PCIe Gen3 or higher, such as the Cervoz NVMe PCIe Gen3x4 SSD, with compact M.2 form factors, advanced DRAM cache buffer, and LDPC ECC technology, are perfectly suited for the edge layer. These SSDs enable efficient directory and error correction during high-speed data transfers, thus enhancing data accuracy and reliability.
The Cloud Layer
The cloud layer requires intensive processing and long-term storage, performing analytics, operating AI and machine learning, and managing extensive data systems across various edge locations. It demands high-performing and reliable components. Cervoz NVMe PCIe Gen4x4 SSDs excel with Read/Write speeds of up to 7,100/6,190 MB/s and 4K random IOPS up to 1,000K, with aluminum heatsinks and thermal throttling for overheating issues. DDR5-5600 DRAM boosts this setup with high data throughput and efficient power use, satisfying rigorous computational needs.
Interlayer Connectivity
Reliable, low-latency network connectivity is crucial as data flows between the device layer, edge, and cloud. Cervoz 10GbE Low-Profile Ethernet Card provides high-speed, stable wired connections in high-bandwidth, low-latency environments. Additionally, the new PCIe Compact Low-Profile Ethernet Card is ideal for narrow edge device enclosures. For areas where wiring is impractical, M.2 Wi-Fi cards offer essential wireless flexibility. These connectivity options ensure a solid foundation for seamless data management across all layers.
Cervoz offers comprehensive solutions to enhance edge computing capabilities. From compact NVMe SSDs and DRAM modules, to advanced modular expansion cards, enabling seamless integration, optimized performance, and unmatched reliability in edge computing deployments.
About Cervoz
Based in Taiwan, Cervoz Technology boasts almost twenty years of expertise in developing and providing industrial-grade storage, memory, and expansion solutions across a myriad of global industrial sectors.
ContactsSales: [email protected]
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View original content:https://www.prnewswire.co.uk/news-releases/compact-solutions-mighty-results-cervoz-unleashes-the-power-of-edge-computing-302147340.html
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