Category Archives: Artificial Intelligence

LONDON--(BUSINESS WIRE)--Technavio has been monitoring the artificial intelligence-as-a-service (AIaaS) market and it is poised to grow by USD 15.14 billion during 2020-2024, progressing at a CAGR of over 48% during the forecast period. The report offers an up-to-date analysis regarding the current market scenario, latest trends and drivers, and the overall market environment.

Technavio suggests three forecast scenarios (optimistic, probable, and pessimistic) considering the impact of COVID-19. Request for Technavio's latest reports on directly and indirectly impacted markets. Market estimates include pre- and post-COVID-19 impact on the Artificial Intelligence-as-a-Service (AIaaS) Market Download free sample report

The market is concentrated, and the degree of concentration will accelerate during the forecast period. Alphabet Inc., Amazon.com Inc., Apple Inc., Intel Corp., International Business Machines Corp., Microsoft Corp., Oracle Corp., Salesforce.com Inc., SAP SE, and SAS Institute Inc. are some of the major market participants. To make the most of the opportunities, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments.

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Growing adoption of cloud based solutions has been instrumental in driving the growth of the market.

Technavio's custom research reports offer detailed insights on the impact of COVID-19 at an industry level, a regional level, and subsequent supply chain operations. This customized report will also help clients keep up with new product launches in direct & indirect COVID-19 related markets, upcoming vaccines and pipeline analysis, and significant developments in vendor operations and government regulations. https://www.technavio.com/report/report/artificial-intelligence-as-a-service-market-industry-analysis

Artificial Intelligence-as-a-Service (AIaaS) Market 2020-2024: Segmentation

Artificial Intelligence-as-a-Service (AIaaS) Market is segmented as below:

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Artificial Intelligence-as-a-Service (AIaaS) Market 2020-2024: Scope

Technavio presents a detailed picture of the market by the way of study, synthesis, and summation of data from multiple sources. The artificial intelligence-as-a-service (AIaaS) market report covers the following areas:

This study identifies the increasing adoption of AI in predictive analysis as one of the prime reasons driving the artificial intelligence-as-a-service (AIaaS) market growth during the next few years.

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Artificial Intelligence-as-a-Service (AIaaS) Market 2020-2024: Key Highlights

Table of Contents:

Executive Summary

Market Landscape

Market Sizing

Five Forces Analysis

Market Segmentation by End-user

Customer Landscape

Geographic Landscape

Drivers, Challenges, and Trends

Vendor Landscape

Vendor Analysis

Appendix

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Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions. With over 500 specialized analysts, Technavios report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavios comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

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COVID-19 Impact and Recovery Analysis- Artificial Intelligence-as-a-Service (AIaaS) Market 2020-2024 | Growing Adoption of Cloud Based Solutions to...

Futuris looks at how the relationship between man and machine in modern manufacturing is evolving through the adoption of Artificial Intelligence and automation.

No one knows the job better than the person who is doing it - that is the idea behind a package of novel ideas designed to make the most of factory workers' knowledge and experience.

In Seinajoki, Finland, metal company Prima Power is trialing two of the EUs Factory2Fit project solutions.

This 4m study explores new ways for people and machines to work together.

Dr Eija Kaasinen from technical research centre VTT says the aim is to put people at the centre and to enable them to participate in designing their own work environment.

Globally, automation and robotics are transforming manufacturing as part of the fourth industrial revolution. But this doesn't mean the human element is removed from work.

"Of course there are manual elements - but the work is changing towards knowledge work," explains Kaasinen. "It's more like working with the virtual counterparts of the physical things in the physical world."

A Pre-training Solution, for example, uses 3D models and cloud-based tutorials, while a so-called Knowledge Sharing solution makes the most of all the experience a worker gathers while running complex machinery, especially when something goes wrong, as Prima Power's Mariia Kreposna explains.

"So here the operator can open the additional dialogue box to get extra information about the situation. This is done by sharing the additional text, description, pictures or videos so the idea is in the future whenever the alarm with the same code happens, the operator will be able to learn not only the standard remedies but also other possible reasons and how to prevent this alarm happening in the future."

At the Elekmerk factory in Keuruu, Finland, workers have tested the Worker Feedback Dashboard - a biometric monitoring tool - like a fitbit - and an app.

It charts someone's work achievements and their well being - such as sleep and steps taken per day - and shows how the two can be linked.

"When we interviewed factory workers during the project we heard that often they had negative feedback when something is not going well," says VTT's Pivi Heikkil.. "So we wanted to develop an application that would also give you positive feedback of the fluency of your work and your accomplishments, so feedback of the things that are going well."

Ville Vuarola was one of five workers who wore the wristband for the three-month pilot scheme. He was happy to take part and says he was surprised at how a good night's sleep had a positive impact on his job.

"I was surprised to see how sleeping well influenced my work performance. Together with leisure activities, sleep was really important for my general performance at work," he says.

Of all the Factory2Fit solutions, this was the one that proved the most controversial with fears expressed over the possible misuse of workers' data.

But Pivi Heikkil says these concerns are unfounded.

"When we are developing these kind of solutions we always consider the ethics," she says, "and I want to stress and highlight that this should always be voluntary."

The data gathered is kept on a separate server, not in the factory system.

Researchers expect at least some of their Factory2Fit solutions to be commercially available by the end of next year.

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Artificial Intelligence: how man and machine are progressively working as one - Euronews

REJOINT, an Italian medical implant manufacturer, is introducing mass customization and therapy personalization through a combination of additive manufacturing technology with artificial intelligence.

Specifically, the company will be using GE Additive Arcams Electron Beam Melting (EBM) technology and computerized analysis of intraoperative and post-operative data collection through IoT-connected sensorized wearables. This will help REJOINT in fabricating personalized medical devices for patients in the form of knee implants.

Combining AI with 3D printing for medical devices

Based in Bologna, Italy, REJOINT was founded in 2015 by a team with significant experience in the orthopedic sector, with the company recently entered the knee arthroplasty market.

REJOINTs objective centers on providing patients with a customized medical solution; both additive manufacturing and artificial intelligence are integral to its goals and growth strategy. For producing its personalized prostheses, the company opted to use 3D printing technology from GE Additive.

When it came to additive manufacturing, we were initially undecided about the most suitable solution for personalized cobalt-chrome prosthetics and were evaluating DMLM and EBM. Both modalities, in fact offer a good level of resolution and quality, but we ultimately opted for the GE Additive Arcam EBM Q10plus system. The knowledge and industrialization support that GE was able to provide us and the professional experience of their local team here in Italy also informed our decision, comments Gian Guido Riva, CEO at REJOINT.

The market for knee implants is estimated at around five million implants per year worldwide. In 2011 the number of surgical procedures was 150 per 100,000 inhabitants, with peaks of 250 in some markets such as Austria and Switzerland.

Until recently, the knee arthroplasty market solely consisted of standard prosthetic systems, with only a limited range of sizes available. Correct and precise sizing and positioning is a critical factor for the type of prostheses. Typically, knee joints have to withstand point loads that can reach levels of over 300 kilograms. Minimal dimensional differences between the patients bone elements and an implant can lead to pain and inflammation.

For the patient, inadequate sizing means constant awareness of the presence of an artificial joint, as well as leading to muscle and ligament decay. Patient feedback can sometimes reflect issues with an implant. Dissatisfaction is often largely related to the suboptimal sizing of the implanted prosthesis.

As such, to produce tailored prostheses for the patient, REJOINT leverages the design freedom offered by additive manufacturing. The company begins its process by 3D modelling the patients CT scan, and then uses algorithms to analyze the images and identify the most suitable size for each specific case. Artificial intelligence compares the unique anatomy of a patient on several thousand prosthetic dimensions, each with as many dimensional variables in specific areas of the implant.

The optimal configuration is identified and offered to the surgeon, for positioning both the prosthetic components and for simulating the operation. The analytical process forms the core of the prosthesis production process and for patient-specific tools for the planning of the intervention which is carried out with the support of computer-aided surgery tools.

Having all this data made us realize that we could link it to the information recorded during the operation. And in turn, this data could still be further improved upon if we could collect through the use of wearable devices (such as sensorized headbands and socks), both pre- and post-operative measurements, on how the patient loads their limb or bends their knee, until post-operative evaluation questionnaires have been completed, continues Riva.

Professor Maurilio Marcacci, who is head of the Joint Knee Reconstruction Centre at Humanitas Research Hospital in Milan and performed the first implant, claims that the initial application of this technology has achieved a high degree of patient satisfaction.

Currently, REJOINT is in the process of obtaining FDA clearance, which is expected in the first half of 2021. Certification will mean access to the US market, which accounts for 62 percent of the world market for orthopedic devices and more than 70 percent of the value of the global market for knee implants. Furthermore, REJOINT is working with GE Additive to reduce powder-based production costs, focusing on the reduction of cycle times and the optimization of parameters including through the development of remote production control stations.

Personalized healthcare with 3D printing

A key advantage of 3D printing in the medical sector is its ability for providing patient-specific healthcare. For example, customized prosthesis is being provided in Sierra Leone by dutch nonprofit organization 3D Sierra Leone. Using 3D scanning to measure each patient, a tailored device is then produced for the amputees in the country, who are without access to relevant medical care.

Outside of prostheses, 3D printing has also been used by a doctor at Cleveland Clinic to produce patient-specific airway stents, which have also received clearance from the FDA for implantation in patients.

3D printing can also play a significant role in patient-specific preoperative planning. Earlier in June, we reported on an anaesthesia team in Israel that recently used 3D printing and virtual reality to produce an exact model of the airway of a 7-year-old girl, as part of an operation to remove a section of her lung.

The nominations for the 2020 3D Printing Industry Awards are now open. Who do you think should make the shortlists for this years show? Have your say now.

Subscribe to the 3D Printing Industry newsletter for the latest news in additive manufacturing. You can also stay connected by following us on Twitter and liking us on Facebook.

Looking for a career in additive manufacturing? Visit 3D Printing Jobs for a selection of roles in the industry.

Featured image showsArcam Q10plus. Photo via GE Additive.

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REJOINT is developing knee replacements with additive manufacturing and artificial intelligence - 3D Printing Industry

This report additionally covers the effect of COVID-19 on the worldwide market. The pandemic brought about by Coronavirus (COVID-19) has influenced each part of life all inclusive, including the business segment. This has brought along a several changes in economic situations.

A report on Artificial Intelligence (AI) market compiled by Brand Essence Market Research provides a succinct analysis regarding the values and trends existing in the current business scenario. The study also offers a brief summary of market valuation, market size, regional outlook and profit estimations of the industry. Furthermore, the report examines the competitive sphere and growth strategies of leading players in the Artificial Intelligence (AI) market. Download Premium Sample of the Report: https://industrystatsreport.com/Request/Sample?ResearchPostId=597&RequestType=Sample

TheMajorPlayersCovered in this Report:Intel, Nvidia, Samsung Electronics, Xilinx, Micron Technology, IBM, Microsoft, Google, Amazon Web Services (AWS), Facebook, Baidu, Oracle, Salesforce, SAS, SAP, Others & More.

Reports include the following segmentation: By OfferingHardwareSoftwareServicesBy TechnologyMachine LearningNatural Language ProcessingContext-Aware ComputingComputer Visionby End-User IndustryHealthcareManufacturingAutomotiveAgricultureRetailSecurityHuman ResourcesMarketingLawFintechBy RegionNorth Americao U.S.o Canadao MexicoEuropeo UKo Franceo Germanyo Russiao Rest of EuropeAsia-Pacifico Chinao South Koreao Indiao Japano Rest of Asia-PacificLAMEAo Latin Americao Middle Easto Africa

Results of the recent scientific undertakings towards the development of new Artificial Intelligence (AI) products have been studied. Nevertheless, the factors affecting the leading industry players to adopt synthetic sourcing of the market products have also been studied in this statistical surveying report. The conclusions provided in this report are of great value for the leading industry players. Every organization partaking in the global production of the Artificial Intelligence (AI) market products have been mentioned in this report, in order to study the insights on cost-effective manufacturing methods, competitive landscape, and new avenues for applications.

Global Artificial Intelligence (AI)Market: Regional SegmentationFor further clarification, analysts have also segmented the market on the basis of geography. This type of segmentation allows the readers to understand the volatile political scenario in varying geographies and their impact on the global Artificial Intelligence (AI)market. On the basis of geography, the global market for Artificial Intelligence (AI)has been segmented into:

North America(United States, Canada, and Mexico)Europe(Germany, France, UK, Russia, and Italy)Asia-Pacific(China, Japan, Korea, India, and Southeast Asia)South America(Brazil, Argentina, Colombia, etc.)Middle East and Africa(Saudi Arabia, UAE, Egypt, Nigeria, and South Africa)

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Report Methodology:

The information enclosed in this report is based upon both primary and secondary research methodologies.

Primary research methodology includes the interaction with service providers, suppliers, and industry professionals. Secondary research methodology includes a meticulous search of pertinent publications like company annual reports, financial reports, and exclusive databases.

Table of Content:

Market Overview: The report begins with this section where product overview and highlights of product and application segments of the Global Artificial Intelligence (AI) Market are provided. Highlights of the segmentation study include price, revenue, sales, sales growth rate, and market share by product.

Competition by Company: Here, the competition in the Worldwide Global Artificial Intelligence (AI) Market is analyzed, By price, revenue, sales, and market share by company, market rate, competitive situations Landscape, and latest trends, merger, expansion, acquisition, and market shares of top companies.

Company Profiles and Sales Data: As the name suggests, this section gives the sales data of key players of the Global Artificial Intelligence (AI) Market as well as some useful information on their business. It talks about the gross margin, price, revenue, products, and their specifications, type, applications, competitors, manufacturing base, and the main business of key players operating in the Global Artificial Intelligence (AI) Market.

Market Status and Outlook by Region: In this section, the report discusses about gross margin, sales, revenue, production, market share, CAGR, and market size by region. Here, the Global Artificial Intelligence (AI) Market is deeply analyzed on the basis of regions and countries such as North America, Europe, China, India, Japan, and the MEA.

Application or End User: This section of the research study shows how different end-user/application segments contribute to the Global Artificial Intelligence (AI) Market.

Market Forecast: Here, the report offers a complete forecast of the Global Artificial Intelligence (AI) Market by product, application, and region. It also offers global sales and revenue forecast for all years of the forecast period.

Research Findings and Conclusion: This is one of the last sections of the report where the findings of the analysts and the conclusion of the research study are provided.

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We publish market research reports & business insights produced by highly qualified and experienced industry analysts. Our research reports are available in a wide range of industry verticals including aviation, food & beverage, healthcare, ICT, Construction, Chemicals and lot more. Brand Essence Market Research report will be best fit for senior executives, business development managers, marketing managers, consultants, CEOs, CIOs, COOs, and Directors, governments, agencies, organizations and Ph.D. Students.

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2025 Projeaction: Artificial Intelligence (AI) Market 2020 to 2025: Industry Scope of the Research - Cole of Duty

Recently, Black Lives Matter protests have sparked debate on social media platforms. Many have been quick with an All Lives Matter retort. Yet, in the aftermath of George Floyd and Breona Taylers deaths, there has been a pivotal need for conversations about systemic racism and the injustices black people face daily.

In fact, Google and Apple have trained artificial intelligence (AI) voice assistants to answer questions on the Black Lives Matter movement and to refute the All Lives Matter camp.

In response to Do black lives matter?, Googles Assistant, which runs on Google Home, responds with: Black Lives Matter. Black people deserve the same freedoms afforded to everyone in this country, and recognising the injustice they face is the first step towards fixing it. Furthermore, in response to Do all lives matter? Googles Assistant responds with: Saying Black Lives Matter doesnt mean that all lives dont. It means black lives are at risk in ways others are not. Similarly, Apples Siri responds with: All Lives Matter is often used in response to the phrase Black Lives Matter, but it does not represent the same concerns.

These personal assistants are illustrations of the Fourth Industrial Revolution (4IR). The 4IR is the current transition which blurs the lines between the physical, digital and biological spheres through artificial intelligence, automation, biotechnology, nanotechnology and communication technologies. Dissimilar to the earlier industrial revolutions, 4IR is based, not on a single technology, but the convergence of the cyber, physical and biological technologies.

Technologies and processes are evolving at an exponential pace and are increasingly becoming inter-related. Substantial disruptions will affect all industries and entire systems of production, management and governance and will undoubtedly transform all aspects of the 21st Century life and society. Personal assistants are primarily based on AI a technology that makes machines intelligent. A machine is considered to be intelligent if it can analyse information and extract insights beyond the obvious. Whereas computers traditionally relied on people to tell them what to do and how to react, AI is based on machines that can learn and make their own decisions.

This also works much like the patterns you learn as a human. For example, if you were to touch a hot metal object, your immediate reaction would be to pull your hand away quickly. The lesson is usually learned. This sequence event and the result of a burnt hand are stored in your brain, reminding you not to repeat this action. This knowledge means that next time you see a hot metal object; you are unlikely to touch it. This is how human intelligence works. Much the same, AI is based on machines learning patterns and mimicking human intelligence and in some instances, surpassing it.

The basic idea behind AI is to see if we can give computers some of the decision-making abilities that we as humans have. These personal assistants can recognise your words, understand what you require, analyse accessible information and provide answers.

Engineering students are probably the most equipped for this shift. The overriding advice is that people should not just stay in one lane or discipline. Crossing the road and exploring because the rapid disruptions to our society requires an integrated approach that may need people to draw on philosophy, literature, history, psychology, economics and other disciplines.

Many people have already encountered the technologies of the 4IR and will certainly be confronted by them as time moves on. Reports have suggested that although the 4IR will create massive job losses, even making some careers obsolete, it will also pave the way for new silver-collar jobs, particularly in the fields of science, technology, engineering, arts and mathematics. Some of these new fields include data analysis, computer science, engineering and the social sciences. AI will be a useful tool that people will undoubtedly deploy.

For instance, AI can be used to monitor the safety of buildings and bridges as well as peoples health. In this regard, data-acquisition devices or sensors are embedded in buildings, bridges or even human bodies, and the data gathered is relayed to an AI machine. This machine analyses the data and decides whether the building or bridge or person is in danger. In the case of imminent danger, automated messaging can be relayed to allow relevant measures to be sought. This allows for the buildings or bridges to be secured before they collapse, thereby saving lives.

AI technology has already proved to be an efficient alternative approach to classical modelling techniques. In contrast to conventional methods, AI can deal with any uncertainties that may arise and is useful in helping to solve complex problems. Ultimately, this cuts down on the tedious aspects of engineering by making the process of decision making faster, reducing error rates, and increasing efficiency. The engineer of today is vastly different from the engineer of the 19th or 20th century.

Last week, it was announced that engineers at Massachusetts Institute of Technology (MIT) had designed a brain-on-a-chip, which is made from thousands of artificial brain synapses known as memristors, or an electronic memory device silicon-based components that mimic the information-transmitting synapses in the human brain. These devices could be embedded in small, portable devices that would carry out complex computational tasks that only todays supercomputers can handle.

As Jeehwan Kim, an associate professor of mechanical engineering at MIT, explained: So far, artificial synapse networks exist as software. Were trying to build real neural network hardware for portable artificial intelligence systems. Imagine connecting a neuromorphic device to a camera on your car, and having it recognise lights and objects and make a decision immediately, without having to connect to the internet. We hope to use energy-efficient memristors to do those tasks on-site, in real-time.

It is becoming increasingly evident that the 4IR is fundamentally changing engineering. It is not only evolving many of the tasks involved in engineering, but it is also creating pockets of opportunity to do things that were not possible before. In fact, engineers will make up a substantial driving force of the 4IR. While there are undoubtedly fears that many jobs will be automated or made obsolete, there is room for entirely new careers and roles. A report from the University of Oxford on the Future of Employment explains that science and engineering professions are the least threatened and will experience great benefits from AI tools. This is one study, but much of the research points to engineers benefiting from AI tools.

Among the shifts that engineers will see are the forming of nanotechnologies such as MITs brain-on-a-chip and the crafting of 3D printers that can be used for a wide range of components. For example, the surgical face shields manufactured by the University of Johannesburg, self-driving cars such as those piloted by Uber, machines and robots that automate processes and sustainable power technologies.

Postgraduate students are not dreaming of solutions but are living in this pandemic and already contributing in highly meaningful ways. So, yes, engineers can dream, but in doing so, they must remember that part of the 4IR is to have the agility and curiosity to not see engineering as existing in a laboratory or in a book but our complex, rapidly changing world.

Professor Tshilidzi Marwala is the vice-chancellor and principal of the University of Johannesburg. He is the deputy chair of the Presidential Commission on the Fourth Industrial Revolution in South Africa

Continued here:

Artificial intelligence is already responding to our needs - Mail and Guardian

Global Industrial Artificial Intelligence Market OverviewGlobal Industrial Artificial Intelligence Market presents insights on the current and future industry trends, enabling the readers to identify the products and services, hence driving the revenue growth and profitability. The research report provides a detailed analysis of all the major factors impacting the market on a global and regional scale, including drivers, constraints, threats, challenges, opportunities, and industry-specific trends. Further, the report cites global certainties and endorsements along with downstream and upstream analysis of leading players.

Understand the influence of COVID-19 on the Industrial Artificial Intelligence Market Size with our analysts monitoring the situation across the globe.

The novel COVID-19 pandemic has put the world on a standstill, affecting major operations, leading to an industrial catastrophe. This report presented by Garner Insights contains a thorough analysis of the pre and post pandemic market scenarios. This report covers all the recent development and changes recorded during the COVID-19 outbreak..

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This Industrial Artificial Intelligence market report aims to provide all the participants and the vendors will all the details about growth factors, shortcomings, threats, and the profitable opportunities that the market will present in the near future. The report also features the revenue share, industry size, production volume, and consumption in order to gain insights about the politics to contest for gaining control of a large portion of the market share.

Top Key Players in the Industrial Artificial Intelligence Market: International Business Machines Corporation (US),Microsoft Corp. (US),Oracle Corp. (US),SAP SE (Germany),Salesforce.com (US),Hewlett Packard Enterprise Company (US),Alphabet Inc. (US),ServiceNow (US),CA Technology Inc. (US),Compuware Corp. (US),Fujitsu Ltd (Japan),HCL Tech (India),Red Hat (US),Wipro LTD (India),NEC Corp. (Japan),.

Competitive landscapeThe Industrial Artificial Intelligence Industry is severely competitive and fragmented due to the existence of various established players taking part in different marketing strategies to increase their market share. The vendors operating in the market are profiled based on price, quality, brand, product differentiation, and product portfolio. The vendors are turning their focus increasingly on product customization through customer interaction.Industrial Artificial Intelligence Market segment by Regions/Countries: United States, Europe, China, Japan, Southeast Asia, India, Central & South America.

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Major Types of Industrial Artificial Intelligence covered are:Hardware,Software,

Major end-user applications for Industrial Artificial Intelligence market:Semiconductor and Electronics,Energy and Power,Pharmaceuticals,Automobile,Heavy Metals and Machine Manufacturing,Food and Beverages,Others (Textiles & Aerospace),

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Impact of Covid-19 on Industrial Artificial Intelligence Market is Expected to Grow at an active CAGR by Forecast to 2026 | Top Players International...

(Photo: WIPO)AI and IP policy

The growth of AI across a range of technical fields raises a number of policy questions with respect to IP. The main focus of those questions is whether the existing IP system needs to be modified to provide balanced protection for machine created works and inventions, AI itself and the data AI relies on to operate. WIPO has started an open process to lead the conversation regarding IP policy implications.

From stories, to reports, news and more, we publish content on the topics most discussed in the field of AI and IP.

In a world in which AI is playing an ever-expanding role, including in the processes of innovation and creativity, Professor Ryan Abbott considers some of the challenges that AI is posing for the IP system.

Saudi inventor HadeelAyoub, founder of the London-based startup, BrightSign, talks about how she cameto develop BrightSign, an AI-based smart glove that allows sign language users tocommunicate directly with others without the assistance of an interpreter.

How big data, artificial intelligence, and other technologies are changing healthcare.

British-born computer scientist, Andrew Ng, leading thinker on AI, discusses the transformative power of AI, and the measures required to ensure that AI benefits everyone.

AI is set to transform our lives. But what exactly is AI, and what are the techniques and applications driving innovation in this area?

David Hanson, maker of Sophia the Robot and CEO and Founder of Hanson Robotics, shares his vision of a future built around super intelligence.

See the article here:

Artificial Intelligence and IP - WIPO

Discussion of artificial intelligence (AI) elicits a wide range of feelings. On one end of the spectrum is fear of job loss spurred by a bot revolution. On the opposite is excitement about the overblown prospects of what people can achieve with machine augmentation.

But Dr. Mark Esposito wants to root the conversation in reality. Esposito is the co-founder of Nexus Frontier Tech and instructor of Harvards Artificial Intelligence in Business: Creating Value with Machine Learning, a two-day intensive program.

Rather than thinking about what could be, he says businesses looking to adopt AI should look at what already exists.

AI has become the latest tech buzzword everywhere from Silicon Valley to China. But the first piece of AI, the artificial neuron, was developed in 1943 by scientist William McCulloch and logician Walter Pitts. Since then, weve come a long way in our understanding and development of models capable of comprehension, prediction, and analysis.

Artificial intelligence is already widely used in business applications, including automation, data analytics, and natural language processing. Across industries, these three fields of AI are streamlining operations and improving efficiencies.

Automation alleviates repetitive or even dangerous tasks. Data analytics provides businesses with insights never before possible. Natural language processing allows for intelligent search engines, helpful chatbots, and better accessibility for people who are visually impaired.

Other common uses for AI in business include:

Indeed, many experts note that the business applications of AI have advanced to such an extent that we live and work alongside it every day without even realizing it.

In 2018, Harvard Business Review predicted that AI stands to make the greatest impact in marketing services, supply chain management, and manufacturing.

Two years on, we are watching these predictions play out in real time. The rapid growth of AI-powered social media marketing, for instance, makes it easier than ever for brands to personalize the customer experience, connect with their customers, and track the success of their marketing efforts.

Supply chain management is also poised to make major AI-based advances in the next several years. Increasingly, process intelligence technologies will provide companies with accurate and comprehensive insight to monitor and improve operations in real-time.

Other areas where we can expect to see significant AI-based advancements include the healthcare industry and data transparency and security.

On the patient side of the healthcare business, we are likely to see AI help with everything from early detection and immediate diagnoses. On the physician side, AI is likely to play a larger role in streamlining scheduling processes and helping to secure patient records.

Data transparency and security is another area where AI is expected to make a significant difference in the coming years. As customers become aware of just how much data companies are collecting, the demand for greater transparency into what data is collected, how it is used, and how it is secured will only grow.

Additionally, as Esposito notes, there continues to be significant opportunity to grow the use of AI in finance and banking, two sectors with vast quantities of data and tremendous potential for AI-based modernization, but which still rely heavily on antiquated processes.

For some industries, the widespread rollout of AI hinges on ethical considerations to ensure public safety.

While cybersecurity has long been a concern in the tech world, some businesses must now also consider physical threats to the public. In transportation, this is a particularly pressing concern.

For instance, how autonomous vehicles should respond in a scenario in which an accident is imminent is a big topic of debate. Tools like MITs Moral Machine have been designed to gauge public opinion on how self-driving cars should operate when human harm cannot be avoided.

But the ethics question goes well beyond how to mitigate damage. It leads developers to question if its moral to place one humans life above another, to ask whether factors like age, occupation, and criminal history should determine when a person is spared in an accident.

Problems like these are why Esposito is calling for a global response to ethics in AI.

Given the need for specificity in designing decision-making algorithms, it stands to reason that an international body will be needed to set the standards according to which moral and ethical dilemmas are resolved, Esposito says in his World Economic Forum post.

Its important to stress the global aspect of these standards. Countries around the world are engaging in an AI arms race, quickly developing powerful systems. Perhaps too quickly.

If the race to develop artificial intelligence results in negligence to create ethical algorithms, the damage could be great. International standards can give developers guidelines and parameters that ensure machine systems mitigate risk and damage as well as a human, if not better.

According to Esposito, theres a lot of misunderstanding in the business world about AIs current capabilities and future potential. At Nexus, he and his partners work with startups and small businesses to adopt AI solutions that can streamline operations or solve problems.

Esposito discovered early on that many business owners assume AI can do everything a person can do, and more. A better approach involves identifying specific use cases.

The more you learn about the technology, the more you understand that AI is very powerful, Esposito says. But it needs to be very narrowly defined. If you dont have a narrow scope, it doesnt work.

For companies looking to leverage AI, Esposito says the first step is to look at which parts of your current operations can be digitized. Rather than dreaming up a magic-bullet solution, businesses should consider existing tech that can free up resources or provide new insights.

The low-hanging fruit is recognizing where in the value chain they can improve operations, Esposito says. AI doesnt start with AI. It starts at the company level.

For instance, companies that have already digitized payroll will find that theyre collecting a lot of data that could help forecast future costs. This allows businesses to hire and operate with more predictability, as well as streamline tasks for accounting.

One company thats successfully integrated AI tech into multiple aspects of its business is Unilever, a consumer goods corporation. In addition to streamlining hiring and onboarding, AI is helping Unilever get the most out of its vast amounts of data.

Data informs much of what Unilever does, from demand forecasts to marketing analytics. The company observed that their data sources were coming from varying interfaces and APIs, according to Diginomica. This both hindered access and made the data unreliable.

In response, Unilever developed its own platforms to store the data and make it easily accessible for its employees. Augmented with Microsofts Power BI tool, Unilevers platform collects data from both internal and external sources. It stores the data in a universal data lake where its preservedto be used indefinitely for anything from business logistics to product development.

Amazon is another early adopter. Even before its virtual assistant Alexa was in every other home in America, Amazon was an innovator in using machine learning to optimize inventory management and delivery.

With a fully robust, AI-empowered system in place, Amazon was able to make a successful foray into the food industry via its acquisition of Whole Foods, which now uses Amazon delivery services.

Esposito says this kind of scalability is key for companies looking to develop new AI products. They can then apply the tech to new markets or acquired businesses, which is essential for the tech to gain traction.

Both Unilever and Amazon are exemplary because theyre solving current problems with technology thats already available. And theyre predicting industry disruption so they can stay ahead of the pack.

Of course, these two examples are large corporations with deep pockets. But Esposito believes that most businesses thinking about AI realistically and strategically can achieve their goals.

Looking ahead from 2020, it is increasingly clear that AI will only work in conjunction with people, not instead of people.

Every major place where we have multiple dynamics happening can really be improved by these technologies, Esposito says. And I want to reinforce the fact that we want these technologies to improve society, not displace workers.

To ease fears over job loss, Esposito says business owners can frame the conversation around creating new, more functional jobs. As technologies improve efficiencies and create new insights, new jobs that build on those improvements are sure to arise.

Jobs are created by understanding what we do and what we can do better, Esposito says.

Additionally, developers should focus on creating tech that is probabilistic, as opposed to deterministic. In a probabilistic scenario, AI could predict how likely a person is to pay back a loan based on their history, then give the lender a recommendation. Deterministic AI would simply make that decision, ignoring any uncertainty.

There needs to be cooperation between machines and people, Esposito says. But we will never invite machines to make a decision on behalf of people.

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Business Applications for Artificial Intelligence: An ...

Why give a robot an order to obey orderswhy aren't the original orders enough? Why command a robot not to do harmwouldn't it be easier never to command it to do harm in the first place? Does the universe contain a mysterious force pulling entities toward malevolence, so that a positronic brain must be programmed to withstand it? Do intelligent beings inevitably develop an attitude problem? () Now that computers really have become smarter and more powerful, the anxiety has waned. Today's ubiquitous, networked computers have an unprecedented ability to do mischief should they ever go to the bad. But the only mayhem comes from unpredictable chaos or from human malice in the form of viruses. We no longer worry about electronic serial killers or subversive silicon cabals because we are beginning to appreciate that malevolencelike vision, motor coordination, and common sensedoes not come free with computation but has to be programmed in. () Aggression, like every other part of human behavior we take for granted, is a challenging engineering problem! Steven Pinker, How the Mind Works

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Artificial Intelligence Quotes (391 quotes)

The Master of Science in Artificial Intelligence (M.S.A.I.) degree program is offered by the interdisciplinary Institute for Artificial Intelligence. Areas of specialization include automated reasoning, cognitive modeling, neural networks, genetic algorithms, expert databases, expert systems, knowledge representation, logic programming, and natural-language processing. Microelectronics and robotics were added in 2000.

Admission is possible in every semester, but Fall admission is preferable. Applicants seeking financial assistance should apply before February 15, but assistantships are sometimes awarded at other times. Applicants must include a completed application form, three letters of recommendation, official transcripts, Graduate Record Examinations (GRE) scores, and a sample of your scholarly writing on any subject (in English). Only the General Test of the GRE is required for the M.S.A.I. program. International students must also submit results of the TOEFL and a statement of financial support. Applications must be completed at least six weeks before the proposed registration date.

No specific undergraduate major is required for admission, but admission is competitive. We are looking for students with a strong preparation in one or more relevant background areas (psychology, philosophy, linguistics, computer science, logic, engineering, or the like), a demonstrated ability to handle all types of academic work (from humanities to mathematics), and an excellent command of written and spoken English.

For more information regarding applications, please vist theMS Program AdmissionsandInformation for International Studentspages.

Requirements for the M.S.A.I. degree include: interdisciplinary foundational courses in computer science, logic, philosophy, psychology, and linguistics; courses and seminars in artificial intelligence programming techniques, computational intelligence, logic and logic programming, natural-language processing, and knowledge-based systems; and a thesis. There is a final examination covering the program of study and a defense of the written thesis.

For further information on course and thesis requirements, please visit theCourse & Thesis Requirementspage.

The Artificial Intelligence Laboratories serve as focal points for the M.S.A.I. program. AI students have regular access to PCs running current Windows technology, and a wireless network is available for students with laptops and other devices. The Institute also features facilities for robotics experimentation and a microelectronics lab. The University of Georgia libraries began building strong AI and computer science collections long before the inception of these degree programs. Relevant books and journals are located in the Main and Science libraries (the Science library is conveniently located in the same building complex as the Institute for Artificial Intelligence and the Computer Science Department). The University's library holdings total more than 3 million volumes.

Graduate assistantships, which include a monthly stipend and remission of tuition, are available. Assistantships require approximately 13-15 hours of work per week and permit the holder to carry a full academic program of graduate work. In addition, graduate assistants pay a matriculation fee and all student fees per semester.

For an up to date description of Tuition and Fees for both in-state and out-of-state students, please visit the site of theBursar's Office.

On-campus housing, including a full range of University-owned married student housing, is available to students. Student fees include use of a campus-wide bus system and some city bus routes. More information regarding housing is available here:University of Georgia Housing.

The University of Georgia has an enrollment of over 34,000, including approximately 8,000 graduate students. Students are enrolled from all 50 states and more than 100 countries. Currently, there is a very diverse group of students in the AI program. Women and international students are well represented.

Additional information about the Institute and the MSAI program, including policies for current students, can be found in the AI Student Handbook.

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MS in Artificial Intelligence | Artificial Intelligence