How artificial intelligence is being used for divorce and separations with apps like Amica, Adieu and Penda – Newcastle Herald

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Artificial intelligence is being used to help divorcing couples divide assets and develop a parenting plan for their children. The technology has the potential to make family law matters cheaper and less stressful. University of Newcastle researchers Professor Tania Sourdin and Dr Bin Li have examined this technology, including the apps Amica, Adieu and Penda. Their work was part of a major research project on justice apps at Newcastle Law School. The Newcastle academics say complex family law cases can "cost each party more than $200,000". "There is a need for cheaper, smarter dispute resolution options in the family law area," said Professor Sourdin, who is Dean of the university's law school. Asked if the apps could improve family law, Professor Sourdin said: "Yes, for some people an app can help". "In a way it may make it easier because the time frames might be shorter. "Also not having to talk with your former partner can be helpful where there are no children." Some apps also support "easy referral to counselling, mediation and other services, which can be very useful". "Often people who are self represented need support and there is evidence that a lot of people have difficulty finalising arrangements without a lawyer," she said. Apps can help reduce legal costs while ensuring that people have access to a lawyer when needed. The coronavirus pandemic has put a spotlight on relationships, amid reports that lockdown and job losses has led to more strain between couples and separations. The use of apps to settle family law disputes seem suited to the times. "It is where society is heading. Many people want to access the justice system from their home 24-7," Professor Sourdin said. "Apps can help with this and also provide referral to professionals when needed." Dr Li said the trend towards such apps was "much clearer" in the pandemic. The federal government is supporting apps with artificial intelligence to "empower separating couples to resolve their family law disputes online". Attorney-General Christian Porter issued a press release last month about the Amica app. National Legal Aid developed Amica with $3 million in federal funding. This app is suitable for couples whose relationship is "relatively amicable". "Amica uses artificial-intelligence technology to suggest the split of assets," Mr Porter said. He added that Amica considers a couple's circumstances, agreements reached by couples in similar situations and how courts generally handle disputes of the same nature. "The tool can also assist parents to develop a parenting plan for their children." The Morrison government wants to improve the family law system to make it "faster, simpler, cheaper and much less stressful for separating couples and their children". The government believes Amica will help couples resolve disputes between themselves and avoid court. The app is aimed at reducing legal bills for separating couples and pressure on family law courts. Dr Li, a lecturer at the university's law school, said there had been "extensive discussion and debate on the reform of the family law system in Australia". He said the apps could "alleviate the burden of courts and the load on judges". Professor Sourdin said the apps "need to be carefully developed". "There are concerns they may not function well and that the data used to power the AI [artificial intelligence] is deficient," she said. "There are also real issues about how effective justice apps can be where there is a lack of agreement about what the issues are or what evidence is correct. "Law can be very complex and requires contextual understandings." There are also concerns about digital literacy and access to technology. However, Professor Sourdin was surprised when their review of the Adieu justice app showed users were older than expected. "For example 41 per cent of the 800 or so people who had used the Adieu app had a relationship of more than 15 years," she said. Dr Li said there was also concern about data and privacy protection. "What if the data collected by apps are hijacked and used by an unauthorised third party?", he said. Nevertheless, they say apps in the justice sector can have many benefits. Professor Sourdin said justice apps could be used to "help people with their legal rights". "The DoNotPay app that is used in the US is a good example. This app can help people with simple matters - from parking fines to travel refunds," she said.

https://nnimgt-a.akamaihd.net/transform/v1/crop/frm/3AijacentBN9GedHCvcASxG/3a380c63-19c6-4322-9665-f43828eb021a.jpg/r48_0_4729_2645_w1200_h678_fmax.jpg

Artificial intelligence is being used to help divorcing couples divide assets and develop a parenting plan for their children.

The technology has the potential to make family law matters cheaper and less stressful.

University of Newcastle researchers Professor Tania Sourdin and Dr Bin Li have examined this technology, including the apps Amica, Adieu and Penda.

Their work was part of a major research project on justice apps at Newcastle Law School.

The Newcastle academics say complex family law cases can "cost each party more than $200,000".

"There is a need for cheaper, smarter dispute resolution options in the family law area," said Professor Sourdin, who is Dean of the university's law school.

Asked if the apps could improve family law, Professor Sourdin said: "Yes, for some people an app can help".

"In a way it may make it easier because the time frames might be shorter.

"Also not having to talk with your former partner can be helpful where there are no children."

Some apps also support "easy referral to counselling, mediation and other services, which can be very useful".

"Often people who are self represented need support and there is evidence that a lot of people have difficulty finalising arrangements without a lawyer," she said.

Apps can help reduce legal costs while ensuring that people have access to a lawyer when needed.

The coronavirus pandemic has put a spotlight on relationships, amid reports that lockdown and job losses has led to more strain between couples and separations.

The use of apps to settle family law disputes seem suited to the times.

"It is where society is heading. Many people want to access the justice system from their home 24-7," Professor Sourdin said.

"Apps can help with this and also provide referral to professionals when needed."

Dr Li said the trend towards such apps was "much clearer" in the pandemic.

The federal government is supporting apps with artificial intelligence to "empower separating couples to resolve their family law disputes online".

Attorney-General Christian Porter issued a press release last month about the Amica app.

National Legal Aid developed Amica with $3 million in federal funding.

This app is suitable for couples whose relationship is "relatively amicable".

"Amica uses artificial-intelligence technology to suggest the split of assets," Mr Porter said.

He added that Amica considers a couple's circumstances, agreements reached by couples in similar situations and how courts generally handle disputes of the same nature.

"The tool can also assist parents to develop a parenting plan for their children."

The Morrison government wants to improve the family law system to make it "faster, simpler, cheaper and much less stressful for separating couples and their children".

The government believes Amica will help couples resolve disputes between themselves and avoid court.

The app is aimed at reducing legal bills for separating couples and pressure on family law courts.

Dr Li, a lecturer at the university's law school, said there had been "extensive discussion and debate on the reform of the family law system in Australia".

He said the apps could "alleviate the burden of courts and the load on judges".

Professor Sourdin said the apps "need to be carefully developed".

"There are concerns they may not function well and that the data used to power the AI [artificial intelligence] is deficient," she said.

"There are also real issues about how effective justice apps can be where there is a lack of agreement about what the issues are or what evidence is correct.

"Law can be very complex and requires contextual understandings."

There are also concerns about digital literacy and access to technology.

However, Professor Sourdin was surprised when their review of the Adieu justice app showed users were older than expected.

"For example 41 per cent of the 800 or so people who had used the Adieu app had a relationship of more than 15 years," she said.

Dr Li said there was also concern about data and privacy protection.

"What if the data collected by apps are hijacked and used by an unauthorised third party?", he said.

Nevertheless, they say apps in the justice sector can have many benefits.

Professor Sourdin said justice apps could be used to "help people with their legal rights".

"The DoNotPay app that is used in the US is a good example. This app can help people with simple matters - from parking fines to travel refunds," she said.

Continued here:

How artificial intelligence is being used for divorce and separations with apps like Amica, Adieu and Penda - Newcastle Herald

Global Artificial Intelligence for Automotive Market 2020 Size, Share, Trends, Growth and Outlook with Company Analysis and Forecast to 2026 – Express…

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Global Artificial Intelligence for Automotive Market 2020 Size, Share, Trends, Growth and Outlook with Company Analysis and Forecast to 2026 - Express...

Global Automotive Artificial Intelligence Market Analysis by Emerging Trends, Size, Share, Future Growth, Current Statistics, Brand Endorsements and…

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Major Players Of Automotive Artificial Intelligence Market

Hyundai Motor CompanyInternational Business Machines CorporationUber TechnologiesBayerische Motoren Werke AGTeslaDaimler AGHarman International IndustriesFord Motor CompanyToyota Motor CorporationVolvo Car CorporationMicrosoft CorporationStart-Up EcosystemDidi ChuxingAlphabetAudi AGGeneral Motors CompanyIntel CorporationHonda MotorXilinxQualcomm

This report covers the Types as well as Application data for Automotive Artificial Intelligence Market along with the country level information for the period of 2020-2026

Market Segmented By Types and By its Applications:

Global Automotive Artificial Intelligence Market Segmentation: By Types

HumanMachine InterfaceSemi-autonomous DrivingAutonomous Driving

Global Automotive Artificial Intelligence Market Segmentation: By Applications

Deep LearningMachine LearningContext AwarenessComputer VisionNatural Language Processing

Global Automotive Artificial Intelligence Market Scope and Features

Global Automotive Artificial Intelligence Market Introduction and Overview Includes Automotive Artificial Intelligence market Definition, Market Scope and Market Size Estimation and region-wise Automotive Artificial Intelligence Value and Growth Rate history from 2015-2026,

Automotive Artificial Intelligence market dynamics: Drivers, Limitations, challenges that are faced, emerging countries of Automotive Artificial Intelligence, Industry News and Policies by Regions.

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Global Automotive Artificial Intelligence Market Analysis by Product Type and Application It gives Automotive Artificial Intelligence market share, value, status, production, Automotive Artificial Intelligence Value, and Growth Rate analysis by type from 2015-2019. Although downstream market overview, Automotive Artificial Intelligence consumption, Market Share, growth rate, by an application (2015-2019).

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Automotive Artificial Intelligence Market Analysis and Forecast by Region Includes Market Value and Consumption Forecast (2014-2026) of Automotive Artificial Intelligence market Of the following region and sub-regions including North America, Europe(Germany, UK, France, Italy, Spain, Russia, Poland), China, Japan, Southeast Asia (Malaysia, Singapore, Philippines, Indonesia, Thailand, Vietnam) the Middle East and Africa(Saudi Arabia, United Arab Emirates, Turkey, Egypt, South Africa, Nigeria), India, South America(Brazil, Mexico, Colombia)

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Table Of Content

1 Automotive Artificial Intelligence Introduction and Market Overview

2 Industry Chain Analysis

3 Global Automotive Artificial Intelligence Value (US$ Mn) and Market Share, Production , Value (US$ Mn) , Growth Rate and Average Price (US$/Ton) analysis by Type (2015-2019E)

4 Automotive Artificial Intelligence Consumption, Market Share and Growth Rate (%) by Application (2015-2019E) by Application

5 Global Automotive Artificial Intelligence Production, Value (US$ Mn) by Region (2015-2019E)

6 Global Automotive Artificial Intelligence Production (K Units), Consumption (K Units), Export (%), Import (%) by Regions (2015-2019E)

7 Global Automotive Artificial Intelligence Market Status by Regions

8 Competitive Landscape Analysis

9 Global Automotive Artificial Intelligence Market Analysis and Forecast by Type and Application

10 Automotive Artificial Intelligence Market Analysis and Forecast by Region

11 New Project Feasibility Analysis

12 Research Finding and Conclusion13 Appendix13.1 Methodology13.2 Research Data Source

Table of Content & Table Of Figures

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Opinion: Artificial intelligence is the hope 2020 needs – Crain’s Cleveland Business

This year is likely to be remembered for the COVID-19 pandemic and for a significant presidential election, but there is a new contender for the most spectacularly newsworthy happening of 2020: the unveiling of GPT-3. As a very rough description, think of GPT-3 as giving computers a facility with words that they have had with numbers for a long time, and with images since about 2012.

The core of GPT-3, which is a creation of OpenAI, an artificial intelligence company based in San Francisco, is a general language model designed to perform autofill. It is trained on uncategorized internet writings, and basically guesses what text ought to come next from any starting point. That may sound unglamorous, but a language model built for guessing with 175 billion parameters 10 times more than previous competitors is surprisingly powerful.

The eventual uses of GPT-3 are hard to predict, but it is easy to see the potential. GPT-3 can converse at a conceptual level, translate language, answer email, perform (some) programming tasks, help with medical diagnoses and, perhaps someday, serve as a therapist. It can write poetry, dialogue and stories with a surprising degree of sophistication, and it is generally good at common sense a typical failing for many automated response systems. You can even ask it questions about God.

Imagine a Siri-like, voice-activated assistant that actually did your intended bidding. It also has the potential to outperform Google for many search queries, which could give rise to a highly profitable company.

GPT-3 does not try to pass the Turing Test by being indistinguishable from a human in its responses. Rather, it is built for generality and depth, even though that means it will serve up bad answers to many queries, at least in its current state. As a general philosophical principle, it accepts that being weird sometimes is a necessary part of being smart. In any case, like so many other technologies, GPT-3 has the potential to rapidly improve.

It is not difficult to imagine a wide variety of GPT-3 spinoffs, or companies built around auxiliary services, or industry task forces to improve the less accurate aspects of GPT-3. Unlike some innovations, it could conceivably generate an entire ecosystem.

There is a notable buzz about GPT-3 in the tech community. One user in the U.K. tweeted: "I just got access to gpt-3 and I can't stop smiling, i am so excited." Venture capitalist Paul Graham noted coyly: "Hackers are fascinated by GPT-3. To everyone else it seems a toy. Pattern seem familiar to anyone?" Venture capitalist and AI expert Daniel Gross referred to GPT-3 as "a landmark moment in the field of AI."

I am not a tech person, so there is plenty about GPT-3 I do not understand. Still, reading even a bit about it fills me with thoughts of the many possible uses.

It is noteworthy that GPT-3 came from OpenAI rather than from one of the more dominant tech companies, such as Alphabet/Google, Facebook or Amazon. It is sometimes suggested that the very largest companies have too much market power but in this case, a relatively young and less capitalized upstart is leading the way. (OpenAI was founded only in late 2015 and is run by Sam Altman).

GPT-3 is also a sign of the underlying health and dynamism of the Bay Area tech world, and thus of the U.S. economy. The innovation came to the U.S. before China and reflects the power of decentralized institutions.

Like all innovations, GPT-3 involves some dangers. For instance, if prompted by descriptive ethnic or racial words, it can come up with unappetizing responses. One can also imagine that a more advanced version of GPT-3 would be a powerful surveillance engine for written text and transcribed conversations. Furthermore, it is not an obvious plus if you can train your software to impersonate you over email. Imagine a world where you never know who you are really talking to "Is this a verified email conversation?" Still, the hope is that protective mechanisms can at least limit some of these problems.

We have not quite entered the era where "Skynet goes live," to cite the famous movie phrase about an AI taking over (and destroying) the world. But artificial intelligence does seem to have taken a major leap forward. In an otherwise grim year, this is a welcome and hopeful development. Oh, and if you would like to read more, here is an article about GPT-3 written by GPT-3.

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Opinion: Artificial intelligence is the hope 2020 needs - Crain's Cleveland Business

AI in the Field of Transportation – a Review – AI Daily

The applications for AI in urban mobility are extensive. The opportunity is thanks to a mixture of factors: urbanization, a focus on environmental sustainability, and growing motorization in developing countries, which results in congestion. The rising predominance of the sharing economy is another contributor. Ride-hailing or ride-sharing services enable drivers to access riders through a digital platform that also facilitates mobile money payments. Some examples in developing countries include Swvl, an Egyptian start-up that enables riders heading an equivalent direction to share fixed-route bus trips, and Didi, the Chinese ride-hailing service. These can help optimize utilization of assets where they are limited in EMs, and increase the standard of obtainable transportation services.

By 2020, it is estimated that there will be 10 million self-driving vehicles and more than 250 million smart cars on the road. Tesla, BMW, and Mercedes have already launched their autonomous cars, and they have proven to be very successful. We can gain tremendous productivity improvements in several industrial areas. As the transport industry becomes more data-driven, the talent profile will also shift as new skills will be needed in the workforce to keep up with ongoing changes. AI is already helping to form transport safer, more reliable and efficient, and cleaner. Some applications include drones for quick life-saving medical deliveries in Sub-Saharan Africa, smart traffic systems that reduce congestion and emissions in India, and driverless vehicles that shuttle cargo between those who make it and people who pip out in China. With great potential to extend efficiency and sustainability, among other benefits, comes many socio-economic, institutional, and political challenges that have got to be addressed to ensure that countries and their citizens can all harness the power of AI for economic process and shared prosperity.

Reference: How Artificial Intelligence is Making Transport Safer, Cleaner, More Reliable and Efficient in Emerging Markets- by Maria Lopez Conde and Ian Twinn, International Financial Corporation (IFC), World Bank Group.

Thumbnail credit: Forbes.com

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AI in the Field of Transportation - a Review - AI Daily

Loop Insights and ImagineAR Sign MOU To Integrate Artificial Intelligence and Augmented Reality, Creating Real-Time Actionable Data For Brands To…

VANCOUVER, BC, July 20, 2020 /CNW/ -Loop Insights Inc. (TSXV: MTRX) (the "Company" or "Loop"), a provider of contactless solutions and Artificial Intelligence ("AI") to drive marketing and real-time consumer insights, is pleased to announce the signing of an MOU with ImagineAR (CSE: IP); (OTCQB: IPNFF) an Augmented Reality ("AR") mobile platform.

The integration of each company's respective technologies into a singular platform will deliver personalized promotions and targeted engagement, leading to higher conversions and transaction revenue in the professional sports, entertainment, and retail industries.

Both companies are well supported and positioned with Loop recently becoming a member of the Amazon Partner Network and ImagineAR being a Microsoft co-sell Azure partner. ImagineAR clients include NBA Sacramento Kings, AT&T, Mall of America, and the Basketball Hall of Fame.

LOOP INSIGHTS ENTERING COMMERCIALIZATION WITH TIER-1 CUSTOMERS AND NORTH AMERICAN TELECOM GIANTS

On July 13, 2020, Loop announced the acceleration of conversations and projects with two of Canada's largest telecommunications companies, as well as, two of the largest network providers in the United States. Moreover, the Company is in advanced discussions with major organizations in the NFL, NHL, NCAA, and a globally renown Casino company.

Loop Insights CEO Rob Anson stated: "Loop Insights utilization of Artificial Intelligence and IoT technology was already turning heads in retail with our ability to deliver dynamic, personalized promotions in real-time. With ImagineAR's immersive AR applications, we can create a whole new world of engagement that does not exist today. Together, our innovative solution unlocks engagement strategies that consumers simply have not previously experienced. This is the convergence of AI, IoT, and AR that technology companies have been promising the retail industry for years."

THE COMBINED OFFERING AND MARKET OPPORTUNITY

ImagineAR allows its clients real-time engagement with their consumer using mobile augmented reality. Loop Insights enhances the AR solution with artificial intelligence to make the customer experience hyper-personalized promotions for the purpose of generating a higher average spend. Loop and ImagineAR will jointly introduce their platform to each other's global client networks to increase reach and accelerate scalability. Revenues will be driven through onboarding and annual licensing fees, both companies will also benefit from monthly Software as a Service (SaaS) and managed service fees.

ImagineAR CEO Paul Silverrstieen added: "Both of our companies are already focused on the sports, entertainment and retail industries. ImagineAR's platform solution captures fan and consumer attention with its immersive experiential AR activations. Now with Loop's integration, we can offer highly personalized, dynamic targeted promotions to increase loyalty and consumer spend, as well as marketing attribution to create detailed fan loyalty profiles, for our shared global clients."

Together, the companies plan on seizing huge market opportunities in AR and AI. According toAllied Market Research, in 2017, the global augmented and virtual reality market size was $11.35 billion and is now projected to reach $571.42 billion by 2025growing at a CAGR of 63.3%. The global artificial intelligence market size was estimated at $39.9 billion in 2019 and is expected to reach 62.3 billion by the end of this year (2020) alone. The companies are set on capturing meaningful market share by merging their respective groundbreaking technologies, which are already achieving 3rd party validation.

About ImagineAR Inc.ImagineAR is an augmented reality (AR) platform that enables businesses of any size to create and implement their own AR campaigns with no programming or technology experience. Every organization, from professional sports franchises to small retailers, can develop interactive AR campaigns that blend the real and digital worlds. Customers simply point their mobile device at logos, signs, buildings, products, landmarks, and more to instantly engage videos, information, advertisements, coupons, 3-D holograms, and any interactive content all hosted in the cloud and managed using a menu-driven portal.

About Loop Insights: Loop is a Vancouver-based technology company that provides transformative artificial intelligence services and IoT solutions to the brick and mortar retail industry to support its longevity in the face of a growing online consumer culture. At the core of its solution is the Fobi IoT technology, which has the unique ability to connect company-wide data with in-store transactional data in real time. This disruptive capability creates revenue-generating insights, which can be actioned through Loop's automated personalized marketing platform to increase foot traffic, wallet share, loyalty and spend.

Forward-Looking Statements/Information:

This news release contains certain statements which constitute forward-looking statements or information.Such forward-looking statements are subject to numerous risks and uncertainties, some of which are beyond Loop's control, including the impact of general economic conditions, industry conditions, and competition from other industry participants, stock market volatility and the ability to access sufficient capital from internal and external sources. Although Loop believes that the expectations in its forward-looking statements are reasonable, they are based on factors and assumptions concerning future events which may prove to be inaccurate. Those factors and assumptions are based upon currently available information. Such forward-looking statements are subject to known and unknown risks, uncertainties and other factors that could influence actual results or events and cause actual results or events to differ materially from those stated, anticipated or implied in the forward-looking statements. As such, readers are cautioned not to place undue reliance on the forward-looking statements, as no assurance can be provided as to future results, levels of activity or achievements. The forward-looking statements contained in this news release are made as of the date of this news release and, except as required by applicable law, Loop does not undertake any obligation to publicly update or to revise any of the included forward-looking statements, whether as a result of new information, future events or otherwise. The forward-looking statements contained in this document are expressly qualified by this cautionary statement. Trading in thesecurities of Loop should be considered highly speculative. There can be no assurance that Loop will be able to achieve all or any of its proposed objectives.

Neither the TSX Venture Exchange nor its Regulation Services Provider (as that term is defined in the policies of the TSX Venture Exchange) accepts responsibility for the adequacy or accuracy of this release.

SOURCE LOOP Insights Inc.

For further information: Loop Insights Inc., Rob Anson, CEO, T: +1 877-754-5336 Ext. 4, E: [emailprotected]; LOOP Website: http://www.loopinsights.ai, Facebook: @LoopInsights, Twitter: @LoopInsights, LinkedIn: @LoopInsights

https://www.loopinsights.ai/

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Loop Insights and ImagineAR Sign MOU To Integrate Artificial Intelligence and Augmented Reality, Creating Real-Time Actionable Data For Brands To...

How Artificial Intelligence Can Be Used In Public Transport- Will People Be Able To Commute Safely After Covid-19? – Inventiva

As it has been observed that many cities are forced to go back to lockdown again with the rise of the number of cases of coronavirus. Due to the emerging lockdowns, public transport will be facing new challenges in the days ahead. They have to avoid overcrowding buses and trains to prevent the virus from spreading ensuring to maintain the overall number of passengers to sustain the system. Meanwhile, the commuters are temporarily returning to public transport but it can be used widely if they see it as a safe way to reach their destinations.

According to the safety measure rules to protect against Covid-19 are to maintain social distancing. Overcrowding poses the risk to the major transmission of coronavirus and other diseases. Therefore, there is a need to flatten the typical morning and evening peak hours of passenger numbers. With the lack of passengers, this means the public transport companies have to put relatively frequent trains and buses all day long rather than back-to-back transport rush.

An all-day service provides special benefits and reduces passenger density resulting in social distancing. This also benefits drivers as they are less likely to change their shifts and passengers can rely on fairly frequent buses all day long. However, with the surge in the cases of Covid-19 infection, it can anytime affect the ridership demand. This can happen so quickly that transport companies wont have that much time to prepare and adjust. Therefore, there is a need to maintain the flexibility to reach within days or even hours and implements the changes that usually take months of preparation. Here is when digital technologies like Artificial Intelligence comes in the view.

Artificial Intelligence can help in maintaining a large amount of data the level of passengers demand, number of drivers on duty, availability of buses and trains, maximum hours driver can work between breaks, as well as the length of each break- and many more which are needed to be taken care of.

With the help of some algorithms, scenarios can be created. They can change the routes and travel times, the update on the schedules will be updated automatically. They can compare the revenue and costs based on different scenarios. It will help to take steps quickly as the circumstances changes, be it lockdown or staggered shifts, like quickly putting extra trains and buses if needed.

AI can also help to solve the unmanageable transport problems. For example, if any transport company wants to add 5% more trips to get passenger numbers over their journey. But they have 14% fewer drivers at hand. It seems impossible to handle. However, AI-driven software can found a way to add more trips with fewer drivers by optimizing the schedule and extending the average shifts by 45 minutes, and providing a necessary break time.

The Artificial Intelligence system that is added to buses is mainly to operate as quickly as possible by providing extra buses when needed to maintain social distancing. Though it sounds simple, it is not. It requires planning in the form of complex algorithms. These algorithms will generate alternative scenarios to figure out which part of the transportation network is needed to be modified to ensure extra vehicles and drivers to be available.

However, transport providers have to make sure that people reach their destination on time even if the schedule changes in a short period. The increase in time duration can lead to unhappy customers. This does not sound any good for business.

There is no saying what transit demand will be there in the upcoming months but cooperating with local government and private institutes to flatten peak hours, using AI for different scenarios management, and monitoring the impact whenever the service changes, will somehow help transportation providers to move ahead. This will actually help the general public to commute safely during the lockdown. Implementing such measures will give public transportation a move towards digitalization.

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How Artificial Intelligence Can Be Used In Public Transport- Will People Be Able To Commute Safely After Covid-19? - Inventiva

[Webinar] ACEDS Detroit Chapter: Fundamentals of Artificial Intelligence and Issues of Bias – August 4th, 1:00 pm – 2:30 pm ET – JD Supra

August 4th, 2020

1:00 PM - 2:30 PM ET

Today, data-driven decisions are used in everything from credit to education to housing to employment to policing and beyond. This 90-minute session will cover what AI is, how it works, different ways AI is being used today in the legal industry, and some of the challenges with AI, focusing, in particular, on the issue of bias. Our presenter will address whether data-driven decisions are objective and fair, or whether they simply perpetuate bias and the status quo. Using the example of risk-based assessment tools applied in the criminal justice system, she will explore how to balance the competing considerations of the need for broad, representative data sets with the need to protect individual privacy, and what technologists, lawyers, and regulators can and should be doing to meet the challenges and opportunities inherent in data-driven decision-making.

*This webinar will be presented via Zoom - details will be sent via email once registration has been completed.

Speaker:

Maura R. GrossmanResearch ProfessorUniversity of Waterloo

Maura is a Research Professor in the David R. Cheriton School of Computer Science at the University of Waterloo, in Ontario, as well as an e-discovery attorney and consultant in New York City. Previously, Grossman was of counsel at Wachtell, Lipton, Rosen & Katz, where for 17 years, she represented Fortune 100 companies and major financial services institutions in corporate and securities litigation and white-collar criminal and regulatory investigations, and advised the firms lawyers and clients on legal, technical, and strategic issues involving e-discovery and information governance, both domestically and abroad. Grossman is a well-known and influential e-discovery lawyer and a pioneer in the use and evaluation of technology-assisted review.

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[Webinar] ACEDS Detroit Chapter: Fundamentals of Artificial Intelligence and Issues of Bias - August 4th, 1:00 pm - 2:30 pm ET - JD Supra

Connecting the Digital and the Real World With Artificial Intelligence – Devdiscourse

Infineon and Invest India successfully concluded an AI Challenge to build an Intelligent Document Finder tool Bangalore, Karnataka, India Business Wire India Infineon Technologies, a world leader in semiconductors, deepens engagement with the startup community including startups from Germany and Singapore in the field of Artificial Intelligence (AI) with its latest AI Challenge program, organized in collaboration with Startup India and AGNIi- housed under Invest India. Invest India is the National Investment Promotion and Facilitation Agency of India and acts as the single first point of reference for investors in the country. The challenge sought a working solution for the Intelligent Document Finder tool with an exceptionally novel approach. As a partner, Infineon is helping startups worldwide to turn their ideas into reality, offering semiconductor solutions and network building with decision-makers to accelerate their ideas into business. Innovations across a range of applications are not limited to pure semiconductors but also encompass software and system designs that optimize performance and process efficiency. Some of the technologies under development include radar-based blood pressure sensors and low latency & always-on voice applications requiring high sensitivity to varied noise and audio inputs.

Vinay Shenoy, Managing Director, Infineon Technologies, India said, "Artificial intelligence has already found its way into many areas of our daily lives, which in turn impacts the way we work- on the one hand influencing our future product portfolio, and on the other hand elevating our way of working to a new level. AI is a valuable ally for achieving digital transformation as it helps faster analysis of complex digital data and generates valuable insights. This challenge has been a great platform as it leverages a wide array of experts and talent in this field to validate our hypothesis from multiple perspectives. We are proud to have Invest India as our partner for this program." Deepak Bagla, MD & CEO of Invest India, said, "Entrepreneurship is one of the underlying pillars of India's growth story. It continues to create new jobs besides introducing new services, products, processes, and business models. The growth of the ecosystem is facilitated by initiatives like Startup India and AGNIi. These initiatives help in connecting the industry leaders with startups across the country to develop solutions for real-life problems. We are delighted to have partnered with Infineon for their AI Challenge- which has provided many promising entrepreneurs to showcase their capabilities" Rohit Girdhar, VP Strategy M&A, Infineon Technologies Asia Pacific, elaborated, "We have been impressed by the quality of entries received for the inaugural edition of Infineon's AI challenge. This is a testament to the rich pool of technology talent that India possesses. All three winning teams were able to demonstrate their innovative approach towards the problem statement and the readiness of their respective product for deployment. The winning solution will now be piloted by us and if successful, deployed across Infineon offices globally. We hope to continue working with the dynamic team at Invest India on similar challenges in the future." With the aim to offer an engaging solution to connect the digital with the real and provide Indian start-ups a platform to showcase their talent in the AI domain, Infineon launched the AI Challenge in December 2019. The challenge sought an Intelligent Document Finder tool that can provide easy and intelligent searches among the document files. The main idea behind this problem statement was to combine human tagging with an automated semantic search for efficient document finding. The initiative was started in collaboration with Startup India and AGNIi and several preliminary rounds later, Infineon selected ten finalists from over 250 start-up applications. Young entrepreneurs from across the country submitted their solutions to a jury whose members included AI experts from Infineon.

Kalyankar Analytics Pvt Ltd won the challenge while Resonova Technologies Pvt Ltd secured the first runner-up spot. The second runner-up and a special category awarding Best All Women's Team included student groups from across the country. The winning teams were awarded gadgets worth INR 3 lakh, along with a paid pilot of INR 5 lakh and an opportunity to intern with Infineon Technologies India. Infineon has been actively engaging with the startup and entrepreneur ecosystem in India since 2017. Over the past few years, the company has partnered with the Atal Innovation Mission (AIM) at Niti Aayog and various incubators across India including Electropreneur Park, NSRCEL, and AIC-Sangam to foster and nurture promising start-ups and drive tomorrow's solutions addressing some key societal concerns like climate change. Most recently, Infineon has been actively funding technology-based healthcare solutions developed by premier institutes to enable India to fight the COVID-19 pandemic.

About Infineon Technologies Infineon Technologies AG is a world leader in semiconductor solutions that make life easier, safer, and greener. Microelectronics from Infineon is the key to a better future. In the 2019 fiscal year (ending 30 September), the Company reported sales of 8.0 billion with around 41,400 employees worldwide. Infineon is listed on the Frankfurt Stock Exchange (ticker symbol: IFX) and in the USA on the over-the-counter market OTCQX International Premier (ticker symbol: IFNNY). Further information is available at http://www.infineon.com to Follow us: Twitter - Facebook - LinkedIn About Invest India, is the National Investment Promotion and Facilitation Agency of India and acts as the first point of reference for investors in India. Invest India focuses on sector-specific investor targeting and the development of new partnerships to enable sustainable investments in India. Invest India also partners with substantial investment promotion agencies and multilateral organizations. Invest India also actively works with several Indian states to build capacity as well as bring in global best practices in investment targeting, promotion, and facilitation areas. Invest India, set up in 2009, is a non-profit venture under the Department for Promotion of Industry and Internal Trade, Ministry of Commerce and Industry, Government of India.

Startup India, housed under Invest India, is a flagship initiative of the Government of India, intends to build a strong ecosystem for nurturing innovation and entrepreneurship and to drive sustainable economic growth by generating large scale employment opportunities. Through this initiative, the Government aims to empower startups to grow through innovation, design, and entrepreneurship. Accelerating Growth of New India's Innovation (AGNIi) is a flagship initiative under the office of the Principal Scientific Adviser to the Government of India. It is one of the nine missions launched under the Prime Minister's Science, Technology and Innovation Advisory Council (PM-STIAC) and is housed at Invest India. AGNIi focuses on supporting innovation commercialization, helping government, enterprise and non-profit sectors benefit from emerging technology innovations from Indian start-ups and the public R&D ecosystem.

Originally posted here:

Connecting the Digital and the Real World With Artificial Intelligence - Devdiscourse

Global Artificial Intelligence Software System Market 2020 Trends Analysis and Coronavirus (COVID-19) Effect Analysis | KEY PLAYERS MARKET WITH…

The globalArtificial Intelligence Software System marketreport has been updated by theMarket Data Analyticsowing to the changed market conditions because of COVID-19. Although, the world is still in hope that everything will come back to normal but the WHO finds no positive signs. The WHO has clearly mentioned that people will have to start living with this disease as there are very less chances that the coronavirus infection will go. The conditions in the global market have changed drastically and every single country is facing economic crunch owing to the slowing down of the business. Thus, it was necessary to update the Artificial Intelligence Software System market report.

Click Here To Access The Free Sample PDF Report (including COVID19 Impact Analysis, full TOC, Tables and Figures)@https://www.marketdataanalytics.biz/worldwide-artificial-intelligence-software-system-market-report-2020-industry-31680.html#request-sample

The latest report consists of the following parts:

Part 1In the first part of the Artificial Intelligence Software System market report the market introduction or the market overview is included. In this part the target audience for the Artificial Intelligence Software System market is also defined for better understanding the market and clients.

Part 2In the second part the research methodologies and the market tools that were incorporated for studying the market is explained in detail. There are also details about the primary and secondary researches that were conducted by the research analysts.

Read Detailed Index of full Research Study at::https://www.marketdataanalytics.biz/worldwide-artificial-intelligence-software-system-market-report-2020-industry-31680.html

Part 3In the third part the qualitative information about the Artificial Intelligence Software System market is included. This information is mainly about the Artificial Intelligence Software System market drivers, restraints, opportunities, and challenges.

Part 4The fourth part of the report deals with the market segmentation. The Artificial Intelligence Software System market includes the following segmentations:{On-Premise, Cloud-based};{Voice Processing, Text Processing, Image Processing}. A detailed analysis of every single category in the market segments has been included. The data includes both statistics and qualitative information which are depicted in the form of tables and figures in the report.

Part 5Geographical presence of the Artificial Intelligence Software System market in the major regions such as North America, Europe, Latin America, Asia Pacific, and the Middle East and Africa is described in detail.

Part 6The major market players in the Artificial Intelligence Software System market includeGoogle, Baidu, IBM, Microsoft, SAP, Intel, Salesforce, Brighterion, KITT.AI, IFlyTek, Megvii Technology, Albert Technologies, H2O.ai, Brainasoft, Yseop, Ipsoft, NanoRep(LogMeIn), Ada Support, Astute Solutions, IDEAL.com, Wipro. Along with these many other industry players are profiled in this section.

Part 7The last part deals with the market conclusions. The conclusions mainly include the observations and the comments from the research analysts and the market experts.

For Any Query Regarding the Artificial Intelligence Software System Market Report? Contact Us at:https://www.marketdataanalytics.biz/worldwide-artificial-intelligence-software-system-market-report-2020-industry-31680.html#inquiry-for-buying

Note In order to provide a more accurate market forecast, all our reports will be updated before delivery by considering the impact of COVID-19.

(*If you have any special requirements, please let us know and we will offer you the report as you want.)

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Global Artificial Intelligence Software System Market 2020 Trends Analysis and Coronavirus (COVID-19) Effect Analysis | KEY PLAYERS MARKET WITH...

Nagarro launches machine vision-based artificial intelligence solutions that mitigate COVID-19 risks and enhance workplace safety – PRNewswire

SAN JOSE, Calif., July 23, 2020 /PRNewswire/ --Nagarro, a global leader in digital engineering and technology solutions, announced the launch of AI-powered solutions to help organizations kick-start work and life amid the COVID-19 crisis. Based on machine vision technology, these solutions provide powerful workplace interventions quickly and effectively, and have the potential to transform how we work and interact by ensuring better health and safety of employees and visitors.

Nagarro's COVID-AI suite of solutions is designed to leverage state-of-the-art AI models running on low-cost edge devices and can be deployed at scale in a matter of weeks, with very little overhead. It has mechanisms to ensure social distancing behaviour, encourage PPE practices such as wearing masks, and monitor as well as mitigate high risk scenarios such as large collections of people.

Nagarro's COVID-AI suite of solutions includes:

"As the world grapples with COVID-19, every ounce of technological innovation and ingenuity harnessed to fight this pandemic brings us one step closer to overcoming it. AI and ML are playing a key role in better understanding and addressing the COVID-19 crisis, " said Anurag Sahay, VP & Global Head - AI & Data Sciences, Nagarro. "Organizations, businesses and establishments are finding new ways to operate effectively. At Nagarro, we are using AI powerfully to help bring some of these interventions in place. We believe that machine vision-based AI platforms have significant potential to transform how we work and live during the new normal."

Nagarro recently conducted a webinar highlighting how the COVID-AI suite of solutions can help organizations accelerate the adaptation to the new normal. To view the webinar recording, click here https://www.nagarro.com/webinar/ai-to-the-rescue-during-covid

Write to [emailprotected] for more information about Nagarro COVID-AI solutions.

About Nagarro

Nagarro drives technology-led business breakthroughs for industry leaders and challengers. When our clients want to move fast and make things, they turn to us. Today, we are more than 7,000 experts across 22 countries. Together we form Nagarro, the global services division of Munich-based Allgeier SE.

Contact:

Megha Jha [emailprotected]

SOURCE Nagarro

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Nagarro launches machine vision-based artificial intelligence solutions that mitigate COVID-19 risks and enhance workplace safety - PRNewswire

Why Its Time to Start Using Artificial Intelligence in Your Greenhouse – Greenhouse Grower

Luna by iUNU is a greenhouse AI platform using aerial robots on tracks that scan the entire production area several times a day using computer vision.Photo courtesy of Sunrise Greenhouses

With todays automated climate-control systems, managing the greenhouse environment and its systems has never been easier. The management of all equipment under one system, including heating, venting, and irrigation, provides optimal efficiency and precision in terms of systems management and data collection.

The development of these technologies allows growers to be more focused on their crops and provides control at their fingertips. Digital parameters are defined by crop level observations, which represent the modern-day dynamic between plants, the grower, and technology.

Increasing development of artificial intelligence (AI) has allowed the greenhouse sector to further improve efficiency and precision, thereby changing that dynamic. Thanks to the work of researchers and private companies, AI is allowing plants to communicate directly with climate-control systems, as well as the grower. It notifies them when there are issues within the crop relating to growth rate, pests, and disease. AI is not only helping growers identify when there is a problem, it is also predicting long-term effects of the issue via harvest forecasting.

Who Is Developing AI for the Greenhouse?

Wageningen University and Research (WUR) is one of the academic institutions leading the way in the development of AI-controlled cultivation. In 2018, WUR hosted an autonomous growing competition where Microsoft took first place over several other teams, including a team of Dutch growers.

A host of private companies including Motorleaf, LetsGrow.com, and Illumitex already have commercially available platforms. Sunrise Greenhouses has been an early adopter of the technology, integrating AI in two areas of its production. The decision to start using AI was driven by the desire for improved efficiency and to help manage skilled labor shortages by expanding employee capacity.

The first system, Luna by iUNU, is a greenhouse AI platform using aerial robots on tracks that scan the entire production area several times a day using computer vision. Images are uploaded for analysis using algorithms customized to production requirements and translated for access on any device. Historical data is used to identify anomalies within the crop, alerting the grower or the climate-control system and providing an unprecedented level of oversight.

The second technology, Watchdog by Bold Robotic Solutions, is a production line AI system developed to monitor equipment for production issues and efficiency. Watchdog is currently installed on our potting line, monitoring pots moving from the potting machine to the tagger, transplanter, and placing robots. The system provides visual and audible alarms for issues such as an empty pot dispenser or pots that have fallen over. A series of sensors also allows the system to observe patterns and make timing corrections by controlling the equipment, thus removing repetitive corrective burdens from the operator.

What Are the Challenges?

In the upcoming years, there is no doubt the role AI will play in the evolution of the greenhouse industry. That being said, these game-changing technologies will not come without challenges, specifically during the early years of technology adoption.

While both solutions have different functions, they are based on the same self-learning technology that uses neural networks and machine learning. Like us, it takes time for the systems to learn patterns and crop cycles. As a seasonal grower with product cycles of up to two years in duration, patience is necessary. It takes time to collect the data for these systems to work and learn.

Greenhouse environments are also challenging for technology implementation due to broad temperature and humidity ranges, which influence both the electronic and mechanical components that contribute to their ongoing development. This can be a frustration for staff trying to complete their weekly plans.

AI solutions for greenhouse growers are still in their initial phases of development and have been mostly implemented by early adopters. As more players in the industry move toward the latest greenhouse technologies, we can expect the number of out-of-the-box AI solutions on the market to increase. For now, AI adopters will likely require some patience as the product learns the intricacies specific to their growing environment before it produces state-of-the-art results.

How Are Staff Trained?

The integration of these systems requires changes to processes, which can be disruptive to production, so flexibility and managing expectations is important among staff. When identifying new equipment, we involve staff in the process. When staff understand what we are trying to accomplish and can provide input, the transition is generally much smoother. People are more willing to adapt when they understand how the technology will make their lives easier. That said, providing people with training and, more importantly, ongoing support is key to the successful integration of these new technologies into your business.

The high level of granularity in digital crop surveillance can save money through early identification of problems related to pests, disease, moisture management, and climate. Photo courtesy of Sunrise Greenhouses

What Are the Benefits?

Having systems that continuously monitor equipment and cultivation allows staff to focus on less redundant tasks, which improves efficiency and the experience and quality of work. The high level of granularity in terms of crop surveillance has saved money due to the early identification of problems related to pests, disease, moisture management, and climate. This allows issues to be dealt with before they proliferate.

Working with iUNU, both our Production Manager and Sales Manager can access inventory in real-time, which has uncoupled departments in our facility that were previously dependent on one another for decision making. This is just one example of the increase in efficiency we are seeing as a result of these technologies.

Facilities that are focused on crop yields, such as vegetable growers, can benefit from AI developed by companies like Motorleaf, who offer yield-predicting products. They consider variables such as historical weather forecasts, nutrient ratios, daily temperatures, and humidity levels. These products train themselves to predict harvest yields with accuracies that are far superior to what is achieved by traditional forecasting methods.

Lee Fisher is the Innovations Manager at Sunrise Greenhouses Ltd., a 250,000 square-foot ornamentals operation in Vineland Station, Ontario, Canada. His background is in computer software engineering, as well as integrated pest management. See all author stories here.

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Why Its Time to Start Using Artificial Intelligence in Your Greenhouse - Greenhouse Grower

Is Artificial Intelligence really ‘intelligent’? – TheArticle

When Artificial Intelligence was in its infancy it was quite natural to give it a sonorous name. It needed to attract money and talent. It has since become a mainstream subject that seeks to imitate human intelligence. See a recent definition:Artificial Intelligence is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

Speech recognition, I remember the first steps. It was the late 1950s. I worked in industry. A colleague of mine, two benches away, had the job of recognising and printing out some limited speech consisting of the numbers from one to ten. He talked to an oscilloscope and watched the appearing waveform. He hoped to identify the numbers from the zero crossings on the oscilloscope, ie when the waveform changed sign. One day he told me that the problem had been solved. His machine had been able to recognise all those numbers. May I try it? I asked. By all means, he said. I tried, and counted up to ten. The machine ignored me. Several other people tried and failed too. As it turned out later, the machine could only work if addressed in a Polish accent. That was a long time ago. Since then software has been commercially available that understands not only those born in this country but also Hungarians, known to be mercilessly massacring the English language.

Machines can of course do a lot more nowadays than understand the spoken word. But are they intelligent? Where should our quest for intelligence take us? Games are good candidates. Let us look at a number of them starting with a simple one: Noughts and Crosses.

It is a trivial example. There are only nine squares. The machine can look at all combinations of moves and countermoves. They amount to about 35,000.Draughts is a game incomparably more complicated, but there are too many possible moves. Brute force, ie looking at all the possibilities, does not work. So what can be done?

A strategy was envisaged by Arthur Samuel whose first program goes back to 1959. He introduced a score function, which assessed the chances that any given move would eventually lead to a win. The function took into account the number of kings and how close any of the pieces were to becoming king. Samuel also introduced machine learning. He fed thousands of games into the computer, pinpointing winning strategies. He did his programming on an IBM computer. His machine could beat amateurs but not professionals. But even this partial success led to IBM stock rising, with the birth of this new computer application: games.

The game that stands above them all is chess. There is no chance of exhausting all possible moves, so it comes down to Samuels methods, a score function and learning from examples. Oddly enough this way of learning was first practised by a fictional character in Stefan Zweigs Schachnovelle published in 1941 (recently mentioned by Raymond Keene in a column in these pages). The main character, an Austrian aristocrat, was imprisoned by the Nazis. While in solitary confinement he managed to get hold of a book containing all the moves in a high level Chess Tournament. Not having anything else to read, he just played them in his mind again and again and again. When he was released, his mental state was affected, but his play was good enough to beat the World Champion. Deep Blue, IBMs computer trained to play chess, beat Kasparov, the reigning champion in the real world, in 1997 in a six-game match. Deep Blue had a three-way strategy. It played countless games (like the Austrian aristocrat), it had a score function and used Brute Force to evaluate the game six or seven moves ahead.

The machines victory is regarded as the greatest triumph of Artificial Intelligence, although it was somewhat marred by Kasparovs claim that IBM cheated. He said that the machine must have been occasionally overruled by a human player, and this amounted to cheating because he would play differently against a human player than against a machine. The controversy was never resolved. IBM dismantled the machine very soon after the end of the match. Was Deep Blue intelligent? Not really, because it just did what it was programmed for. Its main advantage was speed. The programmers were intelligent (even if they cheated), Deep Blue was not.

So lets go to GO, regarded by orientals as the supreme game. The computer, Deep Mind, challenged grandmasters including the world champion about three years ago. The computer won hands down. The main reason for winning was that a lot has happened in AI since Deep Blue. There has been a radical change in programming philosophy, It started with no knowledge of the game and built up its expertise by studying millions of actual games. It trained itself for the singular purpose of playing GO. It was a radical departure from previous approaches by not feeding into the computer any preliminary information on the nature of the game in question. It started from scratch, just like a non-swimmer thrown in at the deep end of a swimming pool.

Games are games. They are excellent demonstrations of how to solve problems where the criteria of success are well defined, and the rules are known. But let us widen our scope and look at a much-predicted product of Artificial Intelligence driverless cars. If perfected, could this be regarded as matching human intelligence? I think the answer is yes. Driverless cars would, no doubt, be a great improvement over human-driven cars. They have many advantages. They would never be under the influence of alcohol nor drugs, they would never race a fellow-driverless car. They would never try to show off to impress a girl-friend and they would never fall asleep.

Even so, we are still very far from the driverless stage. When will they be ready? In a year or two? In ten years? In thirty years? Next century, perhaps? Part of the reason is technical. How can they be trained? Not like GO. Driverless cars cannot learn by going up and down a street a million times. Even a thousand times would not go down well with those living there. And even if everything goes well with the first two thousand journeys down a street, something new the development of a new junction might invalidate all that training. And that was only one street.

If that wasnt enough, there is a psychological barrier as well the fear of accidents. It may very well happen that driverless cars turn out to be safer than those driven by ordinary mortals. They might cause only, say, 900 fatal accidents in a year in contrast to the 1,700 caused by human drivers in the UK. Will we be happy? Unlikely. We accept human errors because we often commit them ourselves. But if there were ever a fatal accident caused by a driverless car we would blame the manufacturers and demand that their product should be banned from the roads.

Much of what goes on at the moment as Artificial Intelligence is hype. Many of the functional applications already in existence need no intelligence, but use instead the assiduous collection of data combined with known techniques of automation. On the whole I would claim that the programmers are intelligent, but the machines are not. In one application, driving cars, machine intelligence might indeed surpass human intelligence but that application may never come. Machines could of course help humans in arriving at decisions, say diagnoses in medicine, but very few patients would be happy if the decisions were made by machines alone.

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Is Artificial Intelligence really 'intelligent'? - TheArticle

Connecting the Digital and the Real World With Artificial Intelligence – Outlook India

(Eds: Disclaimer: The following press release comes to you under an arrangement with Business Wire India. PTI takes no editorial responsibility for the same.) Infineon and Invest India successfully concluded an AI Challenge to build an Intelligent Document Finder tool Bangalore, Karnataka, India Business Wire IndiaInfineon Technologies, a world leader in semiconductors, deepens engagement with the startup community including startups from Germany and Singapore in the field of Artificial Intelligence (AI) with its latest AI Challenge program, organized in collaboration with Startup India and AGNIi- housed under Invest India. Invest India is the National Investment Promotion and Facilitation Agency of India and acts as the single first point of reference for investors in the country. The challenge sought a working solution for the Intelligent Document Finder tool with exceptional novel approach. As a partner, Infineon is helping startups worldwide to turn their ideas into reality, offering semiconductor solutions and network building with decision makers to accelerate their ideas into business. Innovations across a range of applications are not limited to pure semiconductors but also encompass software and system designs that optimize performance and process efficiency. Some of the technologies under development include radar-based blood pressure sensors and low latency & always-on voice applications requiring high sensitivity to varied noise and audio inputs. Vinay Shenoy, Managing Director, Infineon Technologies, India said, Artificial intelligence has already found its way into many areas of our daily lives, which in turn impacts the way we work- on the one hand influencing our future product portfolio, and on the other hand elevating our way of working to a new level. AI is a valuable ally for achieving digital transformation as it helps faster analysis of complex digital data and generates valuable insights. This challenge has been a great platform as it leverages a wide array of experts and talent in this field to validate our hypothesis from multiple perspectives. We are proud to have Invest India as our partner for this program. Deepak Bagla, MD & CEO of Invest India, said, Entrepreneurship is one of the underlying pillars of Indias growth story. It continues to create new jobs besides introducing new services, products, processes, and business models. The growth of the ecosystem is facilitated by initiatives like Startup India and AGNIi. These initiatives help in connecting the industry leaders with startups across the country to develop solutions for real-life problems. We are delighted to have partnered with Infineon for their AI Challenge- which has provided many promising entrepreneurs to showcase their capabilities Rohit Girdhar, VP Strategy M&A, Infineon Technologies Asia Pacific, elaborated, We have been impressed by the quality of entries received for the inaugural edition of Infineons AI challenge. This is a testament to the rich pool of technology talent that India possesses. All three winning teams were able to demonstrate their innovative approach towards the problem statement and the readiness of their respective product for deployment. The winning solution will now be piloted by us and if successful, deployed across Infineon offices globally. We hope to continue working with the dynamic team at Invest India on similar challenges in the future. With the aim to offer an engaging solution to connect the digital with the real and provide Indian start-ups a platform to showcase their talent in the AI domain, Infineon launched the AI Challenge in December 2019. The challenge sought an Intelligent Document Finder tool that can provide easy and intelligent searches among the document files. The main idea behind this problem statement was to combine human tagging with an automated semantic search for efficient document finding. The initiative was started in collaboration with Startup India and AGNIi and several preliminary rounds later, Infineon selected ten finalists from over 250 start-up applications. Young entrepreneurs from across the country submitted their solutions to a jury whose members included AI experts from Infineon. Kalyankar Analytics Pvt Ltd won the challenge while Resonova Technologies Pvt Ltd secured the first runner-up spot. The second runner-up and a special category awarding Best All Women''s Team included student groups from across the country. The winning teams were awarded gadgets worth INR 3 lakh, along with a paid pilot of INR 5 lakh and an opportunity to intern with Infineon Technologies India. Infineon has been actively engaging with the startup and entrepreneur ecosystem in India since 2017. Over the past few years, the company has partnered with the Atal Innovation Mission (AIM) at Niti Aayog and various incubators across India including Electropreneur Park, NSRCEL and AIC-Sangam to foster and nurture promising start-ups and drive tomorrows solutions addressing some key societal concerns like climate change. Most recently, Infineon has been actively funding technology-based healthcare solutions developed by premier institutes to enable India to fight the COVID-19 pandemic.About Infineon TechnologiesInfineon Technologies AG is a world leader in semiconductor solutions that make life easier, safer and greener. Microelectronics from Infineon is the key to a better future. In the 2019 fiscal year (ending 30 September), the Company reported sales of 8.0 billion with around 41,400 employees worldwide. Infineon is listed on the Frankfurt Stock Exchange (ticker symbol: IFX) and in the USA on the over-the-counter market OTCQX International Premier (ticker symbol: IFNNY).Further information is available at http://www.infineon.com Follow us: Twitter - Facebook - LinkedIn About Invest IndiaInvest India, is the National Investment Promotion and Facilitation Agency of India and act as the first point of reference for investors in India. Invest India focuses on sector-specific investor targeting and development of new partnerships to enable sustainable investments in India. Invest India also partners with substantial investment promotion agencies and multilateral organizations. Invest India also actively works with several Indian states to build capacity as well as bring in global best practices in investment targeting, promotion and facilitation areas. Invest India, set up in 2009, is a non-profit venture under the Department for Promotion of Industry and Internal Trade, Ministry of Commerce and Industry, Government of India. Startup India, housed under Invest India, is a flagship initiative of the Government of India, intends to build a strong ecosystem for nurturing innovation and entrepreneurship and to drive sustainable economic growth by generating large scale employment opportunities. Through this initiative, the Government aims to empower startups to grow through innovation, design and entrepreneurship. Accelerating Growth of New Indias Innovation (AGNIi) is a flagship initiative under the office of the Principal Scientific Adviser to the Government of India. It is one of the nine missions launched under the Prime Ministers Science, Technology and Innovation Advisory Council (PM-STIAC) and is housed at Invest India. AGNIi focuses on supporting innovation commercialization, helping government, enterprise and non-profit sectors benefit from emerging technology innovations from Indian start-ups and the public R&D ecosystem. PWRPWR

Disclaimer :- This story has not been edited by Outlook staff and is auto-generated from news agency feeds. Source: PTI

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Connecting the Digital and the Real World With Artificial Intelligence - Outlook India

Global Artificial Intelligence In Fashion Retail Market will Witness Steady Growth Till 2027 Post COVID 19 Pandemic, Top Manufactures ALIBABA,…

Artificial Intelligence In Fashion Retail Market report involves all together a different chapter on COVID 19 Impact. The Covid-19 (coronavirus) pandemic is impacting society and the overall economy across the world. The impact of this pandemic is growing day by day as well as affecting the supply chain. The COVID-19 crisis is creating uncertainty in the stock market, massive slowing of supply chain, falling business confidence, and increasing panic among the customer segments. The overall effect of the pandemic is impacting the production process of several industries including Life Science, and many more. Trade barriers are further restraining the demand- supply outlook. nicolas.shaw@cognitivemarketresearch.com or call us on +1-312-376-8303.Download The report Copy form the webstie: https://cognitivemarketresearch.com/servicesoftware/artificial-intelligence-in-fashion-retail-market-report

The major players profiled in this report include: ALIBABA, Walmart, TRUEFIT, STITCH FIX, Nike, Snap, Adidas, STYLUMIA, FINERY, Goody Box, GRABIT, Burberry, LVMH, Levis, HOOK

Market segment by type can be split into: Predictive Sales, Show Ads, Market Forecast, In Store Visual Monitoring, Marketing Positioning, Other

Market segment by the application can be split into: Online, Offline

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As government of different regions have already announced total lockdown and temporarily shutdown of industries, the overall production process being adversely affected; thus, hinder the overall Artificial Intelligence In Fashion Retail globally. This report on Artificial Intelligence In Fashion Retail provides the analysis on impact on Covid-19 on various business segments and country markets. The report also showcases market trends and forecast to 2027, factoring the impact of COVID-19 situation.

Artificial Intelligence In Fashion Retail Market report provide an in-depth understanding of the cutting-edge competitive analysis of the emerging market trends along with the drivers, restraints, and opportunities in the market to offer worthwhile insights and current scenario for making right decision. The report covers the prominent players in the market with detailed SWOT analysis, financial overview, and key developments of last three years. Moreover, the report also offers a 360 outlook of the market through the competitive landscape of the global industry player and helps the companies to garner Artificial Intelligence In Fashion Retail Market revenue by understanding the strategic growth approaches.

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Report provides industry analysis, important insights, and a competitive and useful advantage to the pursuers. The report analyzes different segments and offers the current and future prospects of each segment. Furthermore, this research report contains an in depth analysis of the top players with data such as product specification, company profiles and product picture, sales area, and base of manufacturing in the global Artificial Intelligence In Fashion Retail market. The impact on the supply and demand of the raw materials, due to the COVID-19 is also analyzed in the global Artificial Intelligence In Fashion Retail market.

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Objectives of Artificial Intelligence In Fashion Retail Market Report:To justifiably share in-depth info regarding the decisive elements impacting the increase of industry (growth capacity, chances, drivers and industry specific challenge and risks)To know the Artificial Intelligence In Fashion Retail Market by pinpointing its many sub segmentsTo profile the important players and analyze their growth plansTo endeavor the amount and value of the Artificial Intelligence In Fashion Retail Market sub-markets, depending on key regions (various vital states)To analyze the Global Artificial Intelligence In Fashion Retail Market concerning growth trends, prospects and also their participation in the entire sectorTo inspect and study the Global Artificial Intelligence In Fashion Retail Market size form the company, essential regions/countries, products and applications, background information and also predictions to 2027Primary worldwide Artificial Intelligence In Fashion Retail Market manufacturing companies, to specify, clarify and analyze the product sales amount, value and market share, market rivalry landscape, SWOT analysis and development plans for the next coming yearsTo examine competitive progress such as expansions, arrangements, new product launches and acquisitions on the market

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Follow is the chapters covered in Artificial Intelligence In Fashion Retail Market:Chapter 1 Artificial Intelligence In Fashion Retail Market OverviewChapter 2 COVID 19 ImpactChapter 3 Artificial Intelligence In Fashion Retail Segment by Types (Product Business)Chapter 4 Global Artificial Intelligence In Fashion Retail Segment by ApplicationChapter 5 Global Artificial Intelligence In Fashion Retail Market by Regions (2015-2027)Chapter 6 Global Artificial Intelligence In Fashion Retail Market Competition by ManufacturersChapter 7 Company (Top Players) Profiles and Key DataChapter 8 Global Artificial Intelligence In Fashion Retail Revenue by Regions (2015-2020)Chapter 9 Global Artificial Intelligence In Fashion Retail Revenue by TypesChapter 10 Global Artificial Intelligence In Fashion Retail Market Analysis by ApplicationChapter 11 North America Artificial Intelligence In Fashion Retail Market Development Status and OutlookChapter 12 Europe Artificial Intelligence In Fashion Retail Market Development Status and OutlookChapter 13 Asia Pacific Artificial Intelligence In Fashion Retail Market Development Status and OutlookChapter 14 South America Artificial Intelligence In Fashion Retail Market Development Status and OutlookChapter 15 Middle East & Africa Artificial Intelligence In Fashion Retail Market Development Status and OutlookChapter 16 Artificial Intelligence In Fashion Retail Manufacturing Cost AnalysisChapter 17 Marketing Strategy Analysis, Distributors/ TradersChapter 18 Global Artificial Intelligence In Fashion Retail Market Forecast (2020-2027)Chapter 19 Research Findings and ConclusionGet detailed TOC for Artificial Intelligence In Fashion Retail Market Report @ https://cognitivemarketresearch.com/servicesoftware/artificial-intelligence-in-fashion-retail-market-report#table_of_contents.

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Global Artificial Intelligence In Fashion Retail Market will Witness Steady Growth Till 2027 Post COVID 19 Pandemic, Top Manufactures ALIBABA,...

The Global Artificial Intelligence in Aviation Market is expected to grow from USD 273.37 Million in 2019 to USD 1,751.48 Million by the end of 2025…

New York, July 23, 2020 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Artificial Intelligence in Aviation Market Research Report by Technology, by Offering, by Application - Global Forecast to 2025 - Cumulative Impact of COVID-19" - https://www.reportlinker.com/p05913258/?utm_source=GNW

On the basis of Technology, the Artificial Intelligence in Aviation Market is studied across Computer Vision, Context Awareness Computing, Machine Learning, and Natural Language Processing (Nlp). The Machine Learning further studied across Deep Learning, Reinforcement Learning, Semi-Supervised Learning, Supervised Learning, and Unsupervised Learning.

On the basis of Offering, the Artificial Intelligence in Aviation Market is studied across Hardware, Services, and Software. The Hardware further studied across Memory, Networks, and Processors. The Services further studied across Deployment & Integration and Support & Maintenance.

On the basis of Application, the Artificial Intelligence in Aviation Market is studied across Dynamic Pricing, Flight Operations, Manufacturing, Smart Maintenance, Surveillance, Training, and Virtual Assistants.

On the basis of Geography, the Artificial Intelligence in Aviation Market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas region is studied across Argentina, Brazil, Canada, Mexico, and United States. The Asia-Pacific region is studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, South Korea, and Thailand. The Europe, Middle East & Africa region is studied across France, Germany, Italy, Netherlands, Qatar, Russia, Saudi Arabia, South Africa, Spain, United Arab Emirates, and United Kingdom.

Company Usability Profiles:The report deeply explores the recent significant developments by the leading vendors and innovation profiles in the Global Artificial Intelligence in Aviation Market including Airbus, Amazon, Boeing, Garmin, GE, IBM, Intel, Lockheed Martin, Micron, Microsoft, Nvidia, Samsung Electronics, Thales, and Xilinx.

FPNV Positioning Matrix:The FPNV Positioning Matrix evaluates and categorizes the vendors in the Artificial Intelligence in Aviation Market on the basis of Business Strategy (Business Growth, Industry Coverage, Financial Viability, and Channel Support) and Product Satisfaction (Value for Money, Ease of Use, Product Features, and Customer Support) that aids businesses in better decision making and understanding the competitive landscape.

Competitive Strategic Window:The Competitive Strategic Window analyses the competitive landscape in terms of markets, applications, and geographies. The Competitive Strategic Window helps the vendor define an alignment or fit between their capabilities and opportunities for future growth prospects. During a forecast period, it defines the optimal or favorable fit for the vendors to adopt successive merger and acquisition strategies, geography expansion, research & development, and new product introduction strategies to execute further business expansion and growth.

Cumulative Impact of COVID-19:COVID-19 is an incomparable global public health emergency that has affected almost every industry, so for and, the long-term effects projected to impact the industry growth during the forecast period. Our ongoing research amplifies our research framework to ensure the inclusion of underlaying COVID-19 issues and potential paths forward. The report is delivering insights on COVID-19 considering the changes in consumer behavior and demand, purchasing patterns, re-routing of the supply chain, dynamics of current market forces, and the significant interventions of governments. The updated study provides insights, analysis, estimations, and forecast, considering the COVID-19 impact on the market.

The report provides insights on the following pointers:1. Market Penetration: Provides comprehensive information on sulfuric acid offered by the key players2. Market Development: Provides in-depth information about lucrative emerging markets and analyzes the markets3. Market Diversification: Provides detailed information about new product launches, untapped geographies, recent developments, and investments4. Competitive Assessment & Intelligence: Provides an exhaustive assessment of market shares, strategies, products, and manufacturing capabilities of the leading players5. Product Development & Innovation: Provides intelligent insights on future technologies, R&D activities, and new product developments

The report answers questions such as:1. What is the market size and forecast of the Global Artificial Intelligence in Aviation Market?2. What are the inhibiting factors and impact of COVID-19 shaping the Global Artificial Intelligence in Aviation Market during the forecast period?3. Which are the products/segments/applications/areas to invest in over the forecast period in the Global Artificial Intelligence in Aviation Market?4. What is the competitive strategic window for opportunities in the Global Artificial Intelligence in Aviation Market?5. What are the technology trends and regulatory frameworks in the Global Artificial Intelligence in Aviation Market?6. What are the modes and strategic moves considered suitable for entering the Global Artificial Intelligence in Aviation Market?Read the full report: https://www.reportlinker.com/p05913258/?utm_source=GNW

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The Global Artificial Intelligence in Aviation Market is expected to grow from USD 273.37 Million in 2019 to USD 1,751.48 Million by the end of 2025...

The Automation Revolution That Wasnt? – National Review

(VasilyevD/iStock/Getty Images Plus)A new study casts doubts on the notion that automation is fundamentally altering American life.

NRPLUS MEMBER ARTICLEEarly in the 2010s, academics and entrepreneurs began to raise concerns about the economic consequences of artificial intelligence. Technological advances, the thinking went, would soon render vast swathes of the labor force obsolete, deepening income inequality and destabilizing society. Proponents of the automation revolution thesis called on policymakers to cushion workers from the effects of technological displacement through fiscal transfers and increased job training for technical fields.

MIT economist Erik Brynjolfsson, a pioneer in the economics of AI, said in 2014 that job loss due to automation would be the biggest challenge of our society for the next decade. Six years into the decade in question, it is time to take stock of his prediction. Is it true, as former Secretary of the Treasury Lawrence Summers said, that rapid automation isnt some hypothetical future possibility but something thats emerging before us right now?

Not quite, say economists Keller Scholl and Robin Hanson. In a paper published last month, they found that over the past 20 years, both the level and growth rate of job automation have been more or less flat. According to their analysis of 1,505 expert reports published by the Occupational Information Network (O*NET), while many workers are losing their jobs to machines, they are doing so at roughly the same rate as in the past.

Among the 261 occupational characteristics reported by O*NET such as the degrees to which jobs require creativity, physical strength, or numeracy two stand out in predicting automation: the importance of machinery and the importance of routine tasks. Unsurprisingly, assembly-line workers and data-entry clerks are particularly vulnerable to automation.

But factory work has seen a trend of automation going back several decades. Those sounding the alarms on AI have warned that not only factory workers but also skilled knowledge workers would face competition from machines. Indeed, algorithms are said to be capable of customer service, medical diagnostics, and news writing, among numerous other tasks. Yet the analysis of Scholl and Hanson indicates that workers are far more likely to be displaced by relatively dated technologies: manufacturing machinery, word processors, and spreadsheets. In other words, the types of jobs being automated havent changed much, despite technological advances.

The study also considers the vulnerability of jobs to automation by computers and machine-learning algorithms in light of two metrics devised by academics, called computerizability and machine-learning suitability. While the potential of digital technologies and AI to replace a given occupation appears to be a strong predictor of automation, its significance disappears when other factors, such as routineness, are taken into consideration. Which is to say that the threat posed by artificial intelligence is more or less the same as that posed by older technologies.

The fundamental nature of automation hasnt changed over the past 20 years, Hanson tells National Review. Theres this AI media story thats been played over and over again for the last decade, and people are so familiar with it that they dont bother to research it.

These finding calls into question the need for policies to address automation, such as former Democratic presidential candidate Andrew Yangs flagship universal-basic-income (UBI) proposal. Endorsed by a growing number of politicians and technologists, UBI is premised on the belief that automation will eliminate millions of jobs. The evidence doesnt suggest the need for such large-scale structural changes to the U.S. economy, but the threat of automation serves as an easy talking point for politicians. People pitch what they want to pitch, and frame it in terms of automation, Hanson argues. You can be pretty confident that those recommending a certain policy response to AI wont change their minds in light of his studys findings.

Because it relies on subjective reporting, the paper does not definitively disprove the automation-revolution hypothesis. In general, it is hard to get an objective picture of the magnitude of automation, and it is possible that labor experts have underestimated the rate at which it is happening. Scholl and Hanson do find that the average job is significantly more susceptible to automation today than 20 years ago, even as the level of automation remains somewhat constant. And the papers central finding that jobs dependent on technology are more likely to be automated raises the possibility of a feedback loop in which automation begets automation, potentially spurring exponential growth in the number of jobs replaced by machines.

But that possibility remains remote, and the burden of proof lies with those arguing that technology is fundamentally transforming American life, and that we must fundamentally transform public policy in response. Until they can marshal convincing evidence, we should be skeptical of proposals that would remake the economy to fit their vision.

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The Automation Revolution That Wasnt? - National Review

Artificial Intelligence Market Size, Growth | Analysis 2026

Artificial intelligence market growth is driven by an increasing adoption of cloud-based applications and services, and rise in the connected device market. Additionally, considerable investments in 5G technology and increase in demand for intelligent virtual assistants are playing key role in AI market development. For instance, in March 2019 Apple Inc. acquired machine learning startup Laserlike of Silicon Valley which is aimed to strengthen its artificial intelligence efforts, including the companys virtual assistant called Siri.

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Artificial intelligence is based on complex mathematical models that requires large amount of data. This requirement of data can be easily fulfilled by cloud technology in secure and reliable environment at low cost. Key players such as Microsoft Corporation, IBM Corporation, and Amazon are focusing on integrating cloud computing with artificial intelligence. Some of the AI cloud services are Amazon AWS AI, Google Cloud Machine Learning, and HPE HavenOnDemand. These cloud computing services are backed up by Analytics as a Service (AaaS) offerings and allow users to quickly develop and run intelligent applications.

Big data has a key role in data mining, management, handling the enormous data generated and is considered among leading trends in the artificial intelligence market landscape. The robust increasing volume of structured and unstructured data is creating huge demand for big data applications. Big data, when enabled with AI, allows user to enhance and automate complex descriptive and predictive analytical tasks. Due to this, enterprises are inclining towards the adoption and implementation of big data enabled AI solutions.

"Focus on Improving Operational Efficiency and Customer Service to Augment AI Market Development"

The number of AI technology experts is limited at present. The key artificial intelligence market opportunities include the potential of improving operational efficiency in the manufacturing industry and improving customer service in the retail sector. The market is likely to gain traction from the rising availability of high-quality and personalized AI-enhanced products and services.

Further, increasing implication of machine learning (M2M, M2P) applications in manufacturing industries is anticipated to drive the market in the forecast period. For instance, in 2018, IBM Corporation acquired Armanta Inc. with an aim to provide AI-based cloud computing platform to financial services firms to fulfil business demands such as CECL (Current Expected Credit Loss Model), FRTB (Fundamental Review of the Trading Book), traded credit risk, and liquidity, portfolio management and more.

"Development of AI-powered Industrial Robots to Drive Market"

The demand for customized robots has increased robustly over the past decade. Several key players in developed countries are currently focusing on manufacturing and supplying AI-powered industrial robots. For instance, in 2016, China supplied around 87,000 units of industrial robots worldwide. Similarly, in 2016, South Korea and Japan supplied around 41,400 and 38,600 units respectively. These industrial robots require artificial intelligence platform for their functioning. This, in turn is augmenting the artificial intelligence technology adoption.

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"Difficulty in Data Labelling and Limited Application in Complex Models to Restrict Market Growth"

Critical challenges affecting the growth of artificial intelligence market include concerns regarding data privacy and unreliability of AI algorithms. In some cases, artificial intelligence is unable to perform automated labelling for underlying data. For this service, professionals are hired to handle the labelling. Further, due to its complex model, AI implementation remains low in applications where extensive explanatory features are required. Another factor inhibiting the growth of this market is lack of AI skilled professionals.

"AI-based Services to Gain Momentum during the Forecast Period"

Based on the component, the market is classified into hardware, software, and services. Software segment accounts for the maximum share of the market. In the case of AI-based services, the initial investment is comparatively low while there are high returns. By incorporating AI in cloud services and enterprise software, companies can implement/deploy cognitive technology with low initial cost and minimal risk. For instance, Netflix used AI to improve search results, thereby reducing subscription cancellations and saving around USD 1 billion in a year from potential revenue loss.

"Natural Language Processing to Account for Maximum Share"

By technology, the market segments include computer vision, machine learning, natural language processing, and others. Computer vision in AI function identifies patterns along with acquiring, analyzing and synthesizing realistic interactive interfaces and then uses ID tags to present photos of related items. In natural language processing, AI techniques function to analyze natural language in both spoken and written forms.

This segment accounts for the maximum share since it serves many essential applications such as machine translation, text parsing, semantic disambiguation, speech processing, and Informational Retrieval (IR). Among technologies, machine learning is expected to be the fastest-growing segment. It enhances the machines ability to learn and improve without the need for human intervention or developing new programming languages.

"AI Adoption to Increase Majorly in BFSI and Government Sectors "

Global artificial intelligence market based on end-user industry includes healthcare, retail, advertising & media, BFSI, automotive & transportation, government, manufacturing, and others. Of these, advertising & media, retail, and BFSI together occupy for nearly half of the market share. Advances in AI have garnered extensive interest from the private and public sectors, which suggests market growth in the government segment. AI adoption trend in retail has the potential to foster mass production of consumer goods and other labor-intensive activities from which human potential can be freed. Several industry players are focusing on developing and deploying Industry 4.0 which is augmenting the growth of AI-enabled devices in the manufacturing sector.

The findings based on our research methodology indicate North America to hold the largest share in the global artificial intelligence (AI) market during the forecast period. North America, being technologically advanced in terms of analytical tools, machine learning, and natural language processing technologies shows signs of emerging as dominant geography throughout the forecast period. Moreover, awareness about the advantages of artificial intelligence tools is widespread in the region. Europe is expected to hold the second position in this market by witnessing moderate growth in long-term period.

North America Artificial Intelligence (AI) Market, 2018 (USD Billion)

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As per our market research study, Asia Pacific is expected to witness healthy growth in terms of AI implementation. The Chinese government is supporting an AI intelligence plan by merging with Baidu, Inc., to create a national deep learning laboratory comprising of intelligent logistics, smart agriculture, manufacturing, military, and other end use applications. A growing number of biopharma companies in Asia Pacific are using AI to streamline the drug discovery process. AI algorithms can analyze large volumes of data sets from health records, clinical trials, pre-clinical studies, and genetic profiles. Trends and pattern observed within this data can help develop theories and suggestions at a much faster rate compared to the human research process while delivering quick insights. Further, developed countries such as Japan are increasingly investing in AI, thereby accounting for the majority of market share in the region.

"Apple Inc. Focusses on Strategic Acquisition of Innovative Startups to Strengthen its AI Solution Offerings"

"Key Players to Maintain their Strong Position Across Different AI-related Areas"

Key companies are investing considerable sums in artificial intelligence. Software and information technology services firms and AI-focused startups have been gaining interest and support from investors. Further, the majority of startup companies working in the AI market are focusing on applications for machine learning, a type of artificial intelligence tool that allows computers to function without human assistance.

At present, the global artificial intelligence market is dominated by the top ten market players holding nearly half of the share. The dominance of key players is dependent on their spending in the research & development of advanced AI tools, operational efficiency, technology upgradation, and innovative strategic partnerships and acquisitions.

AI functionality based system and tools based on different technologies have been offered by key players which eliminate the possibility of human errors from operations to a great extent. At present, the key objective of market innovators is to create expert artificial intelligence systems by using deep learning and neural networks algorithms. These are some of the crucial factors expected to affect the market positioning of players.

The field of artificial intelligence is shifting towards building smart ecosystem, to efficiently collaborate with humans, and educate them about new technologies and their related benefits. AI integration is likely to improve end-to-end supply chain visibility and accelerated information sharing and decision making. This can be achieved by means of cognitive technology, predictive analytics, collaboration technology, and generating automated reports.

The report offers qualitative and quantitative insights on artificial intelligence solutions and services and the detailed analysis of market size & growth rate for all possible segments in the market.

An Infographic Representation of Artificial Intelligence Market

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Along with this, the report provides an elaborative analysis of market dynamics, emerging trends, and competitive landscape. Key insights offered in the report are the adoption trends of AI solutions by individual segments, recent industry developments such as partnerships, mergers & acquisitions, consolidated SWOT analysis of key players, Porters five forces analysis, business strategies of leading market players, macro and micro-economic indicators, and key industry trends.

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ATTRIBUTE

DETAILS

Study Period

2015-2026

Base Year

2018

Forecast Period

2019-2026

Historical Period

2015-2017

Unit

Value (USD billion)

Segmentation

By Component

By Technology

By Industry Vertical

By Region

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Artificial Intelligence Market Size, Growth | Analysis 2026

John Allen and Darrell West discuss artificial intelligence on The Lawfare Podcast – Brookings Institution

John Allen and Darrell West discuss artificial intelligence on The Lawfare Podcast Skip to main content Editor's Note:

This podcast episode originally appeared on the Lawfare blog.

Darrell West and John Allen recently spoke about their new Brookings book Turning Point: Policymaking in the Era of Artificial Intelligence with Benjamin Wittes on The Lawfare Podcast. Darrell West is a senior fellow in the Center for Technology Innovation and the vice president and director of Governance Studies at the Brookings Institution. John Allen is the president of Brookings and a retired U.S. Marine Corps four-star general. In this podcast episode, West and Allen describes what AI is, how it is being deployed, why people are anxious about it, and what we can do to move forward. You can download or listen to the episode in the podcast player below.

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John Allen and Darrell West discuss artificial intelligence on The Lawfare Podcast - Brookings Institution