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Dublin, June 13, 2022 (GLOBE NEWSWIRE) -- The "Global Artificial Intelligence (AI) Robots Market (2022-2027) by Offering, Robot, Technology, Deployment Mode, Application, Geography, Competitive Analysis, and the Impact of Covid-19 with Ansoff Analysis" report has been added to ResearchAndMarkets.com's offering.

The Global Artificial Intelligence (AI) Robots Market is estimated to be USD 7.1 Bn in 2022 and is projected to reach USD 38.32 Bn by 2027, growing at a CAGR of 40.1%.

Market Dynamics

Market dynamics are forces that impact the prices and behaviors of the Global Artificial Intelligence (AI) Robots Market stakeholders. These forces create pricing signals which result from the changes in the supply and demand curves for a given product or service. Forces of Market Dynamics may be related to macro-economic and micro-economic factors. There are dynamic market forces other than price, demand, and supply. Human emotions can also drive decisions, influence the market, and create price signals.

As the market dynamics impact the supply and demand curves, decision-makers aim to determine the best way to use various financial tools to stem various strategies for speeding the growth and reducing the risks.

Company Profiles

The report provides a detailed analysis of the competitors in the market. It covers the financial performance analysis for the publicly listed companies in the market. The report also offers detailed information on the companies' recent development and competitive scenario. Some of the companies covered in this report are ABB Industries, F&P Personal Robotics, Hanson Robotics, Harman International, IBM, Intel, LG Electronics, Microsoft, Rethink Robotics, SoftbankXilinx,, etc.

Countries Studied

Competitive Quadrant

The report includes Competitive Quadrant, a proprietary tool to analyze and evaluate the position of companies based on their Industry Position score and Market Performance score. The tool uses various factors for categorizing the players into four categories. Some of these factors considered for analysis are financial performance over the last 3 years, growth strategies, innovation score, new product launches, investments, growth in market share, etc.

Ansoff Analysis

The report presents a detailed Ansoff matrix analysis for the Global Artificial Intelligence (AI) Robots Market. Ansoff Matrix, also known as Product/Market Expansion Grid, is a strategic tool used to design strategies for the growth of the company. The matrix can be used to evaluate approaches in four strategies viz. Market Development, Market Penetration, Product Development and Diversification. The matrix is also used for risk analysis to understand the risk involved with each approach.

The report analyses the Global Artificial Intelligence (AI) Robots Market using the Ansoff Matrix to provide the best approaches a company can take to improve its market position.

Based on the SWOT analysis conducted on the industry and industry players, the analyst has devised suitable strategies for market growth.

Why buy this report?

Key Topics Covered:

1 Report Description

2 Research Methodology

3 Executive Summary

4 Market Dynamics4.1 Drivers4.1.1 High Adoption of Robots for Personal Use, Automation and mainly in Healthcare Industry4.1.2 Support to Such Robots from Governments Worldwide4.2 Restraints4.2.1 Absence of Standardized Regulations to Prevent Risks Associated With Networked and Autonomous Robots4.2.2 Reluctance to Adopt New Technologies4.3 Opportunities4.3.1 Focus on Developing Robots with Special Application Cases 4.3.2 Increasing Aging Population Worldwide Boosting the Demand for AI-based Robots for Elderly Assistance4.4 Challenges4.4.1 Developing Ai to Help Robots Make Better Decisions and Make Them Safe for Humans4.4.2 Long Time to Commercialize Robots and High Maintenance Cost

5 Market Analysis5.1 Regulatory Scenario5.2 Porter's Five Forces Analysis5.3 Impact of COVID-195.4 Ansoff Matrix Analysis

6 Global Artificial Intelligence (AI) Robots Market, By Offering6.1 Introduction6.2 Hardware 6.3 Software

7 Global Artificial Intelligence (AI) Robots Market, By Robot7.1 Introduction7.2 Service Robots7.2.1 Ground7.2.2 Aerial7.2.3 Underwater7.3 Industrial Robots7.3.1 Traditional Industrial Robots7.3.2 Collaborative Industrial Robots

8 Global Artificial Intelligence (AI) Robots Market, By Technology8.1 Introduction8.2 Computer Vision8.3 Context Awareness8.4 Machine Learning8.5 Natural Language Processing

9 Global Artificial Intelligence (AI) Robots Market, By Deployment Mode9.1 Introduction9.2 Cloud 9.3 On-Premise

10 Global Artificial Intelligence (AI) Robots Market, By Application10.1 Introduction10.2 Agriculture10.3 Education & Entertainment10.4 Healthcare Assistance10.5 Industrial10.6 Law Enforcement10.7 Military & Defence10.8 Personal Assistance & Care giving10.9 Public Relations10.10 Research & Space exploration10.11 Security & Surveillance10.12 Stock Management

11 Americas' Artificial Intelligence (AI) Robots Market11.1 Introduction11.2 Argentina11.3 Brazil11.4 Canada11.5 Chile11.6 Colombia11.7 Mexico11.8 Peru11.9 United States11.10 Rest of Americas

12 Europe's Artificial Intelligence (AI) Robots Market12.1 Introduction12.2 Austria12.3 Belgium12.4 Denmark12.5 Finland12.6 France12.7 Germany12.8 Italy12.9 Netherlands12.10 Norway12.11 Poland12.12 Russia12.13 Spain12.14 Sweden12.15 Switzerland12.16 United Kingdom12.17 Rest of Europe

13 Middle East and Africa's Artificial Intelligence (AI) Robots Market13.1 Introduction13.2 Egypt13.3 Israel13.4 Qatar13.5 Saudi Arabia13.6 South Africa13.7 United Arab Emirates13.8 Rest of MEA

14 APAC's Artificial Intelligence (AI) Robots Market14.1 Introduction14.2 Australia14.3 Bangladesh14.4 China14.5 India14.6 Indonesia14.7 Japan14.8 Malaysia14.9 Philippines14.10 Singapore14.11 South Korea14.12 Sri Lanka14.13 Thailand14.14 Taiwan14.15 Rest of Asia-Pacific

15 Competitive Landscape15.1 Competitive Quadrant15.2 Market Share Analysis15.3 Strategic Initiatives15.3.1 M&A and Investments15.3.2 Partnerships and Collaborations15.3.3 Product Developments and Improvements

16 Company Profiles 16.1 ABB Industries16.2 Alphabet16.3 Blue Frog Robotics16.4 Boston Dynamics16.5 Comau16.6 Diligent Robotics16.7 F&P Personal Robotics16.8 FANUC16.9 FRANKA EMIKA 16.10 Hanson Robotics 16.11 Harman International16.12 IBM 16.13 Intel 16.14 jibo16.15 KUKA16.16 LG Electronics 16.17 Microsoft 16.18 Neurala16.19 Pal Robotics 16.20 Promobot16.21 Rethink Robotics16.22 Softbank16.23 Staubli16.24 Xilinx

17 Appendix

For more information about this report visit https://www.researchandmarkets.com/r/p6baqx

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The Worldwide Artificial Intelligence (AI) Robots Industry is Expected to Reach $38.3 Billion by 2027 - GlobeNewswire

DUBLIN--(BUSINESS WIRE)--The "Global Artificial Intelligence in Supply Chain Market (2022-2027) by Offering, Technology, Application, Industry, Geography, Competitive Analysis, and the Impact of Covid-19 with Ansoff Analysis" report has been added to ResearchAndMarkets.com's offering.

The Global Artificial Intelligence in Supply Chain Market is estimated to be USD 3.3 Bn in 2022 and is projected to reach USD 10.49 Bn by 2027, growing at a CAGR of 26.02%.

Market dynamics are forces that impact the prices and behaviors of the Global Artificial Intelligence in Supply Chain Market stakeholders. These forces create pricing signals which result from the changes in the supply and demand curves for a given product or service. Forces of Market Dynamics may be related to macro-economic and micro-economic factors. There are dynamic market forces other than price, demand, and supply. Human emotions can also drive decisions, influence the market, and create price signals.

As the market dynamics impact the supply and demand curves, decision-makers aim to determine the best way to use various financial tools to stem various strategies for speeding the growth and reducing the risks.

Competitive Quadrant

The report includes Competitive Quadrant, a proprietary tool to analyze and evaluate the position of companies based on their Industry Position score and Market Performance score. The tool uses various factors for categorizing the players into four categories. Some of these factors considered for analysis are financial performance over the last 3 years, growth strategies, innovation score, new product launches, investments, growth in market share, etc.

Ansoff Analysis

The report presents a detailed Ansoff matrix analysis for the Global Artificial Intelligence in Supply Chain Market. Ansoff Matrix, also known as Product/Market Expansion Grid, is a strategic tool used to design strategies for the growth of the company. The matrix can be used to evaluate approaches in four strategies viz. Market Development, Market Penetration, Product Development and Diversification. The matrix is also used for risk analysis to understand the risk involved with each approach.

The report analyses the Global Artificial Intelligence in Supply Chain Market using the Ansoff Matrix to provide the best approaches a company can take to improve its market position.

Based on the SWOT analysis conducted on the industry and industry players, the analyst has devised suitable strategies for market growth.

Why buy this report?

Market Dynamics

Drivers

Restraints

Opportunities

Challenges

Market Segmentations

The Global Artificial Intelligence in Supply Chain Market is segmented based on Offering, Technology, Application, Industry, and Geography.

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/hx4h3q

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Global Artificial Intelligence in Supply Chain Market (2022 to 2027) - Growing Cloud-Based Applications Adoption Presents Opportunities -...

To many they are arts next big thing digital images of jellyfish pulsing and blurring in a dark pink sea, or dozens of butterflies fusing together into a single organism.

The Argentine artist Sofia Crespo, who created the works with the help of artificial intelligence, is part of the generative art movement, where humans create rules for computers which then use algorithms to generate new forms, ideas and patterns.

The field has begun to attract huge interest among art collectors and even bigger price tags at auction.

US artist and programmer Robbie Barrat a prodigy still only 22 years old sold a work called Nude Portrait#7Frame#64 at Sothebys in March for 630,000 ($821,000).

That came almost four years after French collective Obvious sold a work at Christies titled Edmond de Belamy largely based on Barrats code for $432,500.

Collector Jason Bailey told AFP that generative art was like a ballet between humans and machines.But the nascent scene could already be on the verge of a major shake-up, as tech companies begin to release AI tools that can whip up photo-realistic images in seconds.

Artists in Germany and the United States blazed a trail in computer-generated art during the 1960s.

The V&A museum in London keeps a collection going back more than half a century, one of the key works being a 1968 piece by German artist Georg Nees called Plastik 1.

Nees used a random number generator to create a geometric design for his sculpture.

Nowadays, digital artists work with supercomputers and systems known as Generative Adversarial Networks (GANs) to create images far more complex than anything Nees could have dreamed of.

GANs are sets of competing AIs - one generates an image from the instructions it is given, the other acts as a gatekeeper, judging whether the output is accurate.

If it finds fault, it sends the image back for tweaks and the first AI gets back to work for a second try to beat the gamekeeper.But artists like Crespo and Barrat insist that the artist is still central to the process, even if their working methods are not traditional.

When Im working this way, Im not creating an image. Im creating a system that can create images, Barrat told AFP.

Crespo said she thought her AI machine would be a true collaborator, but in reality it is incredibly tough to get even a single line of code to generate satisfactory results.

She said it was more like babysitting the machine. Tech companies are now hoping to bring a slice of this rarefied action to regular consumers.

Google and Open AI are both touting the merits of new tools they say bring photorealism and creativity without the need for coding skills.

They have replaced GANs with more user-friendly AI models called transformers that are adept at converting everyday speech into images.

Google Imagens webpage is filled with absurdist images generated by instructions such as: A small cactus wearing a straw hat and neon sunglasses in the Sahara desert.

Open AI boasts that its Dalle-2 tool can offer any scenario in any artistic style from the Flemish masters to Andy Warhol.

Although the arrival of AI has led to fears of humans being replaced by machines in fields from customer care to journalism, artists see the developments more as an opportunity than a threat.

Crespo has tried out Dalle-2 and said it was a new level in terms of image generation in general though she prefers her GANs. I very often dont need a model that is very accurate to generate my work, as I like very much when things look indeterminate and not easily recognizable, she said.

Camille Lenglois of Pariss Pompidou Centre Europes largest collection of contemporary art also played down any idea that artists were about to be replaced by machines.

She told AFP that machines did not yet have the critical and innovative capacity, adding: The ability to generate realistic images does not make one an artist.

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Is Artificial Intelligence the future of art? : - The Tico Times

Self-driving cars are nifty. Electric vehicles are cool. And when you think of self-driving electric cars, its hard not to think of Tesla. That said, not everyone associates them with safety. And with how the AIs algorithmic thinking is looking, they may have good reason.

On Thursday, the National Highway Traffic Safety Administration, an agency under the guidance of Transportation Secretary Pete Buttigieg, said it would be expanding a probe and look into830,000 Tesla carsacross all four current model lines, 11% more vehicles than they were previously examining.

Initially the probe started last year in response to Tesla vehicles mysteriously plowing into the scene of an existing accident where first responders were already present.

On Thursday, NHTSA said it had discovered in 16 separate instances when this occurred that Autopilot aborted vehicle control less than one second prior to the first impact, suggesting the driver was not prepared to assume full control over the vehicle.

CEO Elon Musk hasoften claimedthat accidents cannot be the fault of the company, as data it extracted invariably showed Autopilot was not active in the moment of the collision.

At least 26 crashes and 11 deaths appear to involve Teslas autopilot feature. While it is true that drivers should have their hands at 10 and 2 with their eyes on the road, youve gotta admit that there have been some representations of the autopilot feature as a replacement for human inputs. A last-minute shift from AI to UI is exactly the type of childish loopholing masquerading as brilliance youd expect from a guy with an Elden Ring build this bad.

Look, I know Ive made that gag in a prior article where I dunked on Musk for being goofy, BUT TWO MEDIUM SHIELDS?

For fear of being labeled a one-trick Tesla with weak windows this is exactly what youd expect from a guy who was already on trial for killing someone with a car.

Whats next? A special re-issue of O.J. Simpsons If I Did It with an additional chapter from Elon on how hed use tweets to manipulate stock prices?

Cartoonish evil gets satirical responses. In the meantime, it may be worth it to consider electric car alternatives that arent Teslas. And pay attention to the road, damn it.

Elon Musks Regulatory Woes Mount As U.S. Moves Closer To Recalling Teslas Self-Driving Software [Fortune]

Chris Williams became a social media manager and assistant editor for Above the Law in June 2021. Prior to joining the staff, he moonlighted as a minor Memelord in the Facebook groupLaw School Memes for Edgy T14s. He endured Missouri long enough to graduate from Washington University in St. Louis School of Law. He is a former boatbuilder who cannot swim,a published author on critical race theory, philosophy, and humor, and has a love for cycling that occasionally annoys his peers. You can reach him by email atcwilliams@abovethelaw.comand by tweet at@WritesForRent.

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Where Does Legal Accountability Rest Between Tesla's Artificial Intelligence and Human Error? - Above the Law

Throughout history, technology has never advanced as quickly as it is right now. It's becoming harder than ever for investors to track the sheer number of innovative tech companies in the public markets, each offering its own unique vision for the future.

But perhaps no technology is more transformative than artificial intelligence (AI), which is already being deployed to complete highly complex tasks in a fraction of the time that humans can. According to one estimate, up to 70% of companies worldwide will have integrated some form of AI into their businesses by 2030, adding $13 trillion in additional output to the global economy.

There will be no shortage of opportunities in the sector over the next decade, but these two stocks might be a great place to start given they're trading at hefty discounts to their all-time highs amid the broader tech sell-off.

C3ai (AI -9.42%) is a first-of-its-kind enterprise AI company. Its stock is volatile because the company isn't profitable yet, and its revenue growth has underperformed expectations since it was listed on the public markets in December 2020. But that's often part and parcel of breaking ground in a brand-new industry.

C3.ai is a good place to start for investors who want exposure to the artificial intelligence sector because it builds both ready-made and customizable AI applications for 11 different industries. For most of its customers, C3.ai is the one-stop source for their AI needs, and it's possible they wouldn't otherwise have access to the technology.

The oil and gas industry is C3.ai's largest contributor to revenue, making up 54% of its $252 million in fiscal 2022, which ended on April 30. The company's technology helps oil behemoths like Shelltrack thousands of pieces of equipment to predict potentially catastrophic failures, saving time, money, and negative environmental impacts. C3.ai has an entire suite of applications just for the fossil fuel sector, which also helps those companies manage carbon emissions to run cleaner businesses.

But C3.ai has also drawn recognition from the largest tech companies in the world. It has partnerships with both Microsoftand Alphabet'sGoogle to collaboratively develop AI applications to better serve their customers using cloud computing technology.

C3.ai's stock price is down 88% from its all-time high, so it carries inherent risks. The company lost $192 million in fiscal 2022 (which ended April 30), but importantly, it has $959 million in cash, equivalents, and short-term investments on its balance sheet -- which means it can run at that loss rate for the next five years before it needs more money. C3.ai has a high gross profit margin of 81%, so once it achieves scale, it can cut back its operating costs to generate positive earnings. But the key question is how long it will take to get there, if at all. With new businesses in new industries, it's always an unknown.

But C3.ai estimates its AI software opportunity could be worth $596 billion by 2025. Since the company's market value is only $2 billion now, it might be worth a small bet for investors with some risk appetite.

Upstart Holdings (UPST -9.90%) offers a great example of how artificial intelligence is being used to improve decades-old processes. Its AI-powered algorithm is designed to replace Fair Isaac's FICO credit scoring system, which is the traditional means of assessing a potential borrower's creditworthiness. Upstart can analyze as many as 1,600 data points about an applicant to deliver a loan decision almost instantly 74% of the time, a feat that might take human assessors days or even weeks to determine.

Fifty-seven banks and credit unions have signed on to use Upstart's algorithm, and one bank, in particular, has abandoned FICO scores altogether in its favor. This is key because Upstart isn't a lender; it originates loans for its bank partners in exchange for a fee. But the company was forced to deviate from this strategy slightly in the recent first quarter of 2022 amid turbulent credit market conditions. Upstart absorbed $345 million worth of new loans using its own balance sheet, which spooked investors.

This added to the $252 million worth of loans it already held mostly for research and development purposes. Management says the increase is only temporary, and it's important to note the $345 million jump represented just 7% of the total $4.5 billion in originations during the quarter.

It's partly a symptom of Upstart's rapid growth, which is bolstered by its entry into the automotive loan origination space. Since launching its car sales and origination software in 2021 called Upstart Auto Retail, 35 car makers have adopted the platform across 525 dealerships. That's up 224% from 162 dealers in Q1 last year.

Upstart generated $849 million in revenue during 2021, a whopping 264% year-over-year jump. It thinks revenue could top $1.25 billion this year, and while that's a slowdown in growth, consumers are contending with higher interest rates and tougher economic conditions, which could dampen demand for credit.

But the company continues to expand into what it estimates is a $6 trillion addressable opportunity. With its stock price down 90% from its all-time high, it might be a great chance to make a long-term bet on what could be the future of credit assessments.

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2 Artificial Intelligence Growth Stocks to Buy on the Dip - The Motley Fool