Category Archives: Artificial Intelligence
Teaching Stream Faculty in Artificial Intelligence job with KING ABDULLAH UNIVERSITY OF SCIENCE & TECHNOLOGY | 278533 – Times Higher Education…
King Abdullah University of Science and Technology: Faculty Positions: Center for Teaching and Learning
Location
King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Deadline
Feb 28, 2022 at 11:59 PM Eastern Time
Description
The Center for Teaching and Learning at KAUST seeks to appoint one or more teaching stream faculty members in the field of artificial intelligence. Such a faculty member will teach in the underlying methodology of machine learning, and modern AI, as well as its application in software, using modern tools like TensorFlow and Pytorch. The faculty member will educate students in how to use these algorithms and software to implement advanced machine learning and AI methods on modern computing platforms, including graphical processor units (GPUs). The principal teaching will be on neural networks, for applications in image and natural language processing, but also in other areas, like medicine and geoscience. While the faculty member need not be an expert in all of these application areas, he/she should have deep enough understanding of the underlying methodology to adapt to a diverse set of applications.
The teaching responsibilities will come in several forms. The faculty member may teach up to one class each semester within a KAUST academic program, like Computer Science. Additionally, the faculty member will help lead small workshops at KAUST on AI training for a wide audience of scientists and engineers, for people who hope to apply the technology, but need not wish to become experts. Finally, KAUST is seeking to expand its exposure to the Saudi community outside the KAUST campus. AI training and development of micro-credentials will be performed for short periods in Saudi cities like Riyadh, accessible to a wide audience of technical people, as well as business leaders who hope to learn about what can be achieved with AI, but who do not seek to become experts themselves. These teaching opportunities outside of KAUST are meant to address the need for AI training throughout the Kingdom, and will help KAUST meet its expanded mission to help upskill a broad segment of the Saudi community. The faculty member will help design these training opportunities, and with KAUST colleagues will assist in their delivery. In this context, there may be opportunities to perform on-site training for employees at major Saudi companies.
For a teaching stream faculty member, it is anticipated that one would typically teach 2 to 3 classes per semester. However, the individual who fills the role described here will typically teach one class per semester. Therefore, the remaining time commitment is meant to address the development and implementation of AI workshops at KAUST, as well as the aforementioned training opportunities planned for Saudi cities like in Riyadh, and possibly targeted training for Saudi companies.
This teaching stream faculty position is full-time, over the 12 month calendar year, with vacation periods consistent with all KAUST faculty. The summer period will be a particularly important time for developing and executing the teaching to be performed outside KAUST.
Qualifications
We welcome candidates with a PhD in Computer Scienceor related areas, with a strong background in Artificial Intelligence and Data Science.
Application Instructions
To apply for this position, please complete the interfolio application form and upload the following materials:
Global Marketing Automation Market Report 2021-2026 – Integration of Artificial Intelligence (AI) is Anticipated to Drive the Market -…
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RadNet Completes the acquisitions of Aidence Holding BV – GlobeNewswire
LOS ANGELES, Jan. 24, 2022 (GLOBE NEWSWIRE) -- RadNet, Inc. (NASDAQ: RDNT), a national leader in providing high-quality, cost-effective, fixed-site outpatient diagnostic imaging services through a network of 350 owned and operated outpatient imaging centers, today reported that it has acquired two unrelated Dutch technology companies, Aidence Holding B.V., (Aidence), a leading radiology artificial intelligence (AI) company focusing on clinical solutions for pulmonary nodule management and lung cancer screening and Quantib B.V., (Quantib), a leading radiology AI and machine learning company focusing on clinical solutions forprostate cancer and neurodegeneration.
Founded in 2015 and based in Amsterdam, Netherlands, Aidence is developing and deploying AI clinical applications to empower interpreting medical images and improving patient outcomes. Aidences first commercialized product, Veye Lung Nodules, is an AI-based solution for lung nodule detection and management. This product is CE marked in Europe, where it has a leading position for lung cancer AI screening tools. Aidences solution analyzes thousands of CT scans each week, with customers in seven European countries including France, the Netherlands and the United Kingdom (UK). In 2020, Aidence received an AI Award to help the UKs National Health Service improve lung cancer prognosis, and is playing a leading role in large-scale deployments of regional lung cancer screening programs. Aidences Veye solution was submitted in December for FDA 510(k) clearance in the United States. Upon successful clearance, Aidences solution would be available for use in the United States.
Founded in 2012 and based in Rotterdam, Netherlands, Quantib has multiple AI-based solutions with both CE mark and FDA 510(k) clearance, including Quantib Prostate for analysis of prostate MR images and Quantib Brain and Quantib ND to quantify brain abnormalities on MRI. Quantib has customers in more than 20 countries worldwide, including the United States. All of Quantibs solutions are deployed through Quantibs AI Node platform which allows for efficient workflow integration and more accelerated regulatory clearance of future products. Quantib Prostate summarizes multiparametric MRI results into an AI heat map, which highlights areas of concern, enabling for faster and more accurate diagnosis of prostate disease. Currently, approximately one in every eight men is being diagnosed with prostate cancer in his lifetime, and according to the American Cancer Society estimates, there will be 268,490 new cases of prostate cancer in the United States in 2022. In addition to Quantib Prostate, Quantib Brain and Quantib Brain ND, Quantib is in advanced development of an AI algorithm for MRI of the breast, which could be complementary to Deep Healths solutions for mammography.
Aidence and Quantib will join RadNets AI division, formed after the earlier acquisition of DeepHealth in 2020, which to date has focused on breast cancer screening and detection. The acquisitions of Aidence and Quantib will further enable RadNets leadership in the development and deployment of AI to improve the care and health of patients.
Dr. Howard Berger, Chairman and Chief Executive Officer of RadNet, noted, We remain convinced that artificial intelligence will have a transforming impact on diagnostic imaging and the field of radiology. We are very pleased to expand our portfolio of AI software into two other cancer screening domains. With the addition of Aidence and Quantib, we will now have effective screening solutions for the three most prevalent cancers. We believe that large population health screening will play an important role for health insurers, health systems and large employer groups in the near future. As the largest owner of diagnostic imaging centers in the United States, RadNet has relationships that can serve to make large-scale screening programs, similar to what mammography is for breast cancer screening, a reality.
Dr. Berger continued, As we have explained in the past, the benefit of cancer screening for population health is evident, driving improved patient outcomes while lowering costs. Specifically, the data showing the benefit of lung cancer screening with chest CT is robust. While RadNet performs more than 100,000 chest CT scans per year, lung cancer screening is dramatically underutilized, and even more so now that screening guidelines have been expanded to include over 14 million people in the US. Though annual lung cancer screening with low dose CT is recommended for high-risk populations by the US Preventative Services Task Force, too few patients are following the screening guidelines. Furthermore, we believe that lung screening will play an important role for those who suffered from COVID-19 and who may have a requirement to monitor longer-term issues with their lungs. We believe the amount of chest CTs could significantly increase if high-risk patients and patients with long-term COVID-19 effects have access to low-cost, effective screening programs that we believe Aidences solutions can facilitate.
Prostate cancer remains another major cause of morbidity and mortality, and MRI has been shown to have a critical role in the diagnosis and management of prostate cancer. While prostate MRI is a growing area of our overall MRI business, the opportunity to create a lower-cost, more accurate service offering to Medicare and private payors allows for a conversation about creating large-scale screening programs for appropriately-qualified male patient populations, akin to how mammography is utilized today to detect and manage breast disease in women. Quantibs Prostate solutions further these objectives. Furthermore, Quantibs commercialized products for brain MRI will be important tools for our business and could have an impact with monitoring Alzheimers patients, particularly those who will undergo some of the newer drug and treatment therapies being developed in the marketplace today, Dr. Berger stated.
Mark-Jan Harte, co-founder and CEO of Aidence added, "The Aidence team, my co-founder, Jeroen van Duffelen and I are enthusiastic about joining forces with the RadNet experts. RadNet is a leader in medical imaging and is committed to furthering the use of AI in radiology. Together, we will accelerate our growth and innovation pipeline to serve clinicians with automated and integrated AI solutions for oncology. Our vision is that data is key to improving the prevention, management and treatment of disease. As an outgrowth of operating 350 facilities in some of the busiest and most populous U.S. markets and performing close to nine million exams per year, RadNets database of images and radiologist reports is one of the largest and most diverse we have identified. I see unprecedented opportunities to further scale adoption, leveraging RadNets capabilities.
Arthur Post Uiterweer, CEO of Quantib noted, "We are thrilled to join the RadNet family. Quantib aims to enable more accurate and efficient clinical decision-making. Being part of RadNet enables us to take a major step towards distributing our solutions and making a much greater impact on patient health and outcomes. We believe our AI Node technology and substantial clinical experience from serving our customers can improve the rate at which future AI innovations are shared across RadNets hundreds of locations and the radiology industry at large.
Dr. Berger concluded, We areexcited to add the Aidence and Quantib teams to our AI family. The addition of Aidence and Quantib to our already world-class AI efforts will accelerate the transformation of our business.
Conference Call
Dr. Howard Berger, President and CEO of RadNet, Inc., Dr. Gregory Sorensen, President of DeepHealth and head of RadNets AI Division, Mark-Jan Harte, Chief Executive Officer of Aidence and Arthur Post Uiterweer, Chief Executive Officer of Quantib, will host a conference call to discuss RadNets Artificial Intelligence strategy on Thursday, January 27th, 2022 at 8:00 a.m. Pacific Time (11:00 a.m. Eastern Time).
Conference Call Details:
Date: Thursday, January 27, 2022Time: 11:00 a.m. Eastern TimeDial In-Number: 888-254-3590International Dial-In Number: 929-477-0448
It is recommended that participants dial in approximately 5 to 10 minutes prior to the start of the call. There will also be simultaneous and archived webcasts available at https://viavid.webcasts.com/starthere.jsp?ei=1526026&tp_key=150580c62fAn archived replay of the call will also be available and can be accessed by dialing 844-512-2921 from the U.S., or 412-317-6671 for international callers, and using the passcode 558728.
Forward Looking Statements
This press release contains forward-looking statements within the meaning of the safe harbor provisions of the U.S. Private Securities Litigation Reform Act of 1995. Forward-looking statements are expressions of our current beliefs, expectations and assumptions regarding the future of our business, future plans and strategies, projections, and anticipated future conditions, events and trends. Forward-looking statements can generally be identified by words such as: anticipate, intend, plan, goal, seek, believe, project, estimate, expect, strategy, future, likely, may, should, will and similar references to future periods. Forward-looking statements in this press release include, among others, statements or inferences we make regarding:
Forward-looking statements are neither historical facts nor assurances of future performance. Because forward-looking statements relate to the future, they are inherently subject to uncertainties, risks and changes in circumstances that are difficult to predict and many of which are outside of our control. Our actual results and financial condition may differ materially from those indicated in the forward-looking statements. Therefore, you should not place undue reliance on any of these forward-looking statements. Important factors that could cause our actual results and financial condition to differ materially from those indicated or implied in the forward-looking statements include, those factors, identified in the Annual Report on Form 10-K, Quarterly Report on Form 10-Q and other reports that RadNet, Inc files from time to time with the Securities and Exchange Commission.
Any forward-looking statement contained in this press release is based on information currently available to us and speaks only as of the date on which it is made. We undertake no obligation to publicly update any forward-looking statement, whether written or oral, that we may make from time to time, whether as a result of changed circumstances, new information, future developments or otherwise, except as required by applicable law.
About RadNet, Inc.
RadNet, Inc. is the leading national provider of freestanding, fixed-site diagnostic imaging services and related information technology solutions (including artificial intelligence) in the United States based on the number of locations and annual imaging revenue. RadNet has a network of 350 owned and/or operated outpatient imaging centers. RadNet's markets include California, Maryland, Delaware, New Jersey, New York, Florida and Arizona. Together with affiliated radiologists, and inclusive of full-time and per diem employees and technicians, RadNet has a total of approximately 9,000 employees. For more information, visit http://www.radnet.com.
CONTACTS:
RadNet, IncMark Stolper, 310-445-2800Executive Vice President and Chief Financial Officer
Original post:
RadNet Completes the acquisitions of Aidence Holding BV - GlobeNewswire
Lior Cole Is the Model Combining Artificial Intelligence With Religion – Vogue
Cole explains that the Robo Rabbi taps into the boundlessness of A.I. Thanks to the GPT-3 A.I. technologya natural-language processorthe parsha lessons and challenges come from the A.I. technology itself, allowing Cole to view herself as simply the messenger. Rarely does A.I. touch spirituality and religion, says Cole. I am doing other projects that touch into the sentient dimensions, but there has yet to be a computer that is entirely human, that is sentient, or has human abilities. According to Cole, a computer having its own point of view isnt unheard of. There are computers that can mimic humanlike capabilities, Cole says. The technology has a perspective and is articulating that perspective of knowledge on the internet, so it isnt unique. Those opinions can be channeled into a medium like Robo Rabbi, which is meant as an enlightening teaching mechanism.
Coles other projects include a childrens book about computer science. I was looking at a childrens book for computer science, and it is math and coding centric. I am such a computer nerd, but I dont like coding, she says. Kids should be exposed to the more human side [of computers]. She is also creating a coffee-table book to train an A.I. algorithm to program its own art and is involved in a fashion collective at Cornell, where she is developing a digital model that will be available on the NFT marketplace. Her other A.I.-minded project? Well, that she signed an NDA for.
As for modeling, Cole wants to pursue it as long as possible and considers it another curious path for her to explore. When I was younger, I wasnt like, Oh, I want to be a computer scientist when Im older. I figured that out when I was in college, she says. And now that I got scouted, Im like, This is cool too!
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Lior Cole Is the Model Combining Artificial Intelligence With Religion - Vogue
Artificial Intelligence and Sophisticated Machine Learning Techniques are Being Used to Develop Pathogenesi… – Physician’s Weekly
Most scientific areas now use big data analysis to extract knowledge from complicated and massive databases. This method is now utilized in medicine to investigate big groups of individuals. This review helped to understand that the employed artificial intelligence and sophisticated machine learning approaches to investigate physio pathogenesis-based therapy in pSS. The procedure also estimated the evolution of trends in statistical techniques, cohort sizes, and the number of publications throughout this time span. In all, 44,077 abstracts and 1,017 publications were reviewed. The mean number of chosen articles each year was 101.0 (S.D. 19.16), but it climbed dramatically with time (from 74 articles in 2008 to 138 in 2017). Only 12 of them focused on pSS, but none on the topic of pathogenesis-based therapy. A thorough assessment of the literature over the last decade collected all papers reporting on the application of sophisticated statistical analysis in the study of systemic autoimmune disorders (SADs). To accomplish this job, an automatic bibliography screening approach has been devised.To summarize, whereas medicine is gradually entering the era of big data analysis and artificial intelligence, these techniques are not yet being utilized to characterize pSS-specific pathogenesis-based treatment. Nonetheless, big multicenter studies using advanced algorithmic methods on large cohorts of SADs patients are studying this feature.
Reference:www.tandfonline.com/doi/full/10.1080/21645515.2018.1475872
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Artificial Intelligence and Sophisticated Machine Learning Techniques are Being Used to Develop Pathogenesi... - Physician's Weekly
Insights on the Healthcare Artificial Intelligence Global Market to 2026 – Featuring Google, IBM and Intel Among Others – GlobeNewswire
Dublin, Jan. 04, 2022 (GLOBE NEWSWIRE) -- The "Healthcare Artificial Intelligence (AI) Market - Global Outlook & Forecast 2021-2026" report has been added to ResearchAndMarkets.com's offering.
The healthcare artificial intelligence market is expected to reach USD 44.5 billion by 2026, growing at a CAGR of 46.21%.
Several pharmaceutical companies are implementing innovative technologies to boost their growth in the global healthcare industry. Collaboration of GSK with Exscientia identified a small compound for targeted therapeutics and its characteristics towards the specific target using the AI platform. AI is becoming an incredible platform in the pharmaceutical industry.
For instance, Novartis announced Microsoft as a strategic partner in AI and data science to set up an AI innovation lab. Since the last year, over 50+ companies have got machine learning and AI algorithms approvals. During the COVID-19 pandemic, AI played a significant role in the healthcare industry. An analytics study by Accenture combined with clinical applications demonstrated the potential of AI to reduce approximately USD 150 billion per annum by 2026 in the US healthcare system.
The following factors are likely to contribute to the growth of the healthcare artificial intelligence market during the forecast period:
Key Highlights
The study considers a detailed scenario of the present healthcare artificial intelligence market and its market dynamics for the period 2021?2026. It covers a detailed overview of several market growth enablers, restraints, and trends. The report offers both the demand and supply aspects of the market. It profiles and examines leading companies and other prominent ones operating in the market.
Vendor Analysis
Giant players are focusing on pursuing organic growth strategies to enhance their product portfolio in the healthcare artificial intelligence (AI) market. Several initiatives by the players will complement growth strategies, which are gaining traction among end-users in the market. Rising growth of startups collaborating with key vendors in promoting their artificial intelligence in healthcare applications creating heavy competition in the market.
Key Questions Answered:1. How big is the healthcare artificial intelligence (AI) market?2. Which region has the highest share in the healthcare artificial intelligence market?3. Who are the key players in the healthcare AI market?4. What are the latest market trends in the healthcare artificial intelligence market?5. What is the use of AI in the healthcare market?
Key Topics Covered:
1 Research Methodology
2 Research Objectives
3 Research Process
4 Scope & Coverage4.1 Market Definition4.1.1 Inclusions4.1.2 Exclusions4.1.3 Market Estimation Caveats4.2 Base Year4.3 Scope Of The Study4.3.1 Market Segmentation By Component4.3.2 Market Segmentation By Application4.3.3 Market Segmentation By Technology4.3.4 Market Segmentation By End-User4.3.5 Market Segmentation By Geography
5 Report Assumptions & Caveats5.1 Key Caveats5.2 Currency Conversion5.3 Market Derivation
6 Market At A Glance
7 Introduction7.1 Healthcare Artificial Intelligence (AI)
8 Market Opportunities & Trends8.1 Rising Investments In Advanced Drug Discovery & Development Processes8.2 Mergers, Acquisitions, & Collaborations With Life Science & Medical Device Companies8.3 Influx/Emergence Of Many Startups In The Healthcare AI Industry
9 Market Growth Enablers9.1 Increase In Patient Volume & Complexities Associated With Data9.2 Shrinking Operational Workforce In Healthcare Facilities9.3 Technological Advancements & Innovations In AI9.4 Growing Need To Reduce Healthcare Costs Using It & AI Technologies
10 Market Restraints10.1 High Installation & Implementation Cost Of AI & Related Platforms10.2 Lack Of Skilled AI Workforce & Resistance Among Healthcare Professionals10.3 Stringent & Ambiguous Regulations For Healthcare Software & AI Technologies10.4 Absence Of Interoperability Among Commercially Available Ai Solutions Coupled With Data Privacy Issues
11 Market Landscape11.1 Market Overview11.2 Market Size & Forecast11.3 Five Forces Analysis11.3.1 Threat Of New Entrants11.3.2 Bargaining Power Of Suppliers11.3.3 Bargaining Power Of Buyers11.3.4 Threat Of Substitutes11.3.5 Competitive Rivalry
12 Component12.1 Market Snapshot & Growth Engine12.2 Market Overview12.3 Hardware12.3.1 Market Overview12.3.2 Market Size & Forecast12.3.3 Hardware: Geography Segmentation12.4 Software & Services12.4.1 Market Overview12.4.2 Market Size & Forecast12.4.3 Software & Services: Geography Segmentation
13 Application13.1 Market Snapshot & Growth Engine13.2 Market Overview13.3 Hospital Workflow Management13.3.1 Market Overview13.3.2 Market Size & Forecast13.3.3 Hospital Workflow Management: Geography Segmentation13.4 Medical Imaging & Diagnosis13.4.1 Market Overview13.4.2 Market Size & Forecast13.4.3 Medical Imaging & Diagnosis: Geography Segmentation13.5 Drug Discovery & Precision Medicine13.5.1 Market Overview13.5.2 Market Size & Forecast13.5.3 Drug Discovery & Precision Medicine: Geography Segmentation13.6 Patient Management13.6.1 Market Overview13.6.2 Market Size & Forecast13.6.3 Patient Management: Geography Segmentation
14 Technology14.1 Market Snapshot & Growth Engine14.2 Market Overview14.3 Machine Learning14.3.1 Market Overview14.3.2 Market Size & Forecast14.3.3 Machine Learning: Geography14.4 Querying Method14.4.1 Market Overview14.4.2 Market Size & Forecast14.4.3 Querying Method: Geography Segmentation14.5 Natural Language Processing14.5.1 Market Overview14.5.2 Market Size & Forecast14.5.3 Natural Language Processing: Geography Segmentation14.6 Other Technology14.6.1 Market Overview14.6.2 Market Size & Forecast14.6.3 Other Technology: Geography Segmentation
15 End-User15.1 Market Snapshot & Growth Engine15.2 Market Overview15.3 Healthcare Providers15.3.1 Market Overview15.3.2 Market Size & Forecast15.3.3 Healthcare Providers: Geography Segmentation15.4 Pharma-Biotech & Medical Device Companies15.4.1 Market Overview15.4.2 Market Size & Forecast15.4.3 Pharma-Biotech & Medical Device Companies: Geography Segmentation15.5 Payers15.5.1 Market Overview15.5.2 Market Size & Forecast15.5.3 Payers: Geography Segmentation15.6 Others15.6.1 Market Overview15.6.2 Market Size & Forecast15.6.3 Other End User: Market By Geography
16 Geography16.1 Market Snapshot & Growth Engine16.2 Geographic Overview
17 North America
18 Europe
19 APAC
20 Latin America
21 Middle East & Africa
22 Competitive Landscape22.1 Competition Overview22.2 Market Share Analysis22.2.1 Google22.2.2 IBM22.2.3 Intel22.2.4 Medtronic22.2.5 Microsoft22.2.6 NVIDIA22.2.7 Siemens Healthineers
23 Key Company Profiles23.1 GOOGLE23.1.1 Business Overview23.1.2 Product Offerings23.1.3 Key Strategies23.1.4 Key Strengths23.1.5 Key Opportunities23.2 INTERNATIONAL BUSINESS MACHINES (IBM)23.2.1 Business Overview23.2.2 Product Offerings23.2.3 Key Strategies23.2.4 Key Strengths23.2.5 Key Opportunities23.3 INTEL CORPORATION23.3.1 Business Overview23.3.2 Product Offerings23.3.3 Key Strategies23.3.4 Key Strengths23.3.5 Key Opportunities23.4 MEDTRONIC23.4.1 Business Overview23.4.2 Product Offerings23.4.3 Key Strategies23.4.4 Key Strengths23.4.5 Key Opportunities23.5 MICROSOFT CORPORATION23.5.1 Business Overview23.5.2 Product Offerings23.5.3 Key Strategies23.5.4 Key Strengths23.5.5 Key Opportunities23.6 NVIDIA CORPORATION23.6.1 Business Overview23.6.2 Product Offerings23.6.3 Key Strategies23.6.4 Key Strengths23.6.5 Key Opportunities23.7 SIEMENS HEALTHINEERS23.7.1 Business Overview23.7.2 Product Offerings23.7.3 Key Strategies23.7.4 Key Strengths23.7.5 Key Opportunities
24 Other Prominent Vendors24.1 ARTERYS24.1.1 Business Overview24.1.2 Product Offerings24.2 CAPTION HEALTH24.2.1 Business Overview24.2.2 Product Offerings24.3 ENLITIC24.3.1 Business Overview24.3.2 Product Offerings24.4 CATALIA HEALTH24.4.1 Business Overview24.4.2 Product Offerings24.5 GENERAL VISION24.5.1 Business Overview24.5.2 Product Offerings24.6 PHILIPS24.6.1 Business Overview24.6.2 Product Offerings24.7 STRYKER24.7.1 Business Overview24.7.2 Product Offerings24.8 SHIMADZU RECURSION PHARMACEUTICALS24.8.1 Business Overview24.8.2 Product Offerings24.9 GE HEALTHCARE24.9.1 Business Overview24.9.2 Product Offerings24.10 REMEDY MEDICAL24.10.1 Business Overview24.10.2 Product Offerings24.11 SUBTLE MEDICAL24.11.1 Business Overview24.11.2 Product Offerings24.12 NETBASE QUID24.12.1 Business Overview24.12.2 Product Offerings24.13 BIOSYMETRICS24.13.1 Business Overview24.13.2 Product Offerings24.14 SENSELY24.14.1 Business Overview24.14.2 Product Offerings24.15 INFORMAI24.15.1 Business Overview24.15.2 Product Offerings24.16 BIOCLINICA24.16.1 Business Overview24.16.2 Product Offerings24.17 OWKIN24.17.1 Business Overview24.17.2 Product Offerings24.18 BINAH.AI24.18.1 Business Overview24.18.2 Product Offerings24.19 ONCORA MEDICAL24.19.1 Business Overview24.19.2 Product Offerings24.20 QURE.AI TECHNOLOGIES24.20.1 Business Overview24.20.2 Product Offerings24.21 LUNIT24.21.1 Business Overview24.21.2 Product Offerings24.22 CARESYNTAX24.22.1 Business Overview24.22.2 Product Offerings24.23 ANJU SOFTWARE24.23.1 Business Overview24.23.2 Product Offerings24.24 IMAGIA CYBERNETICS24.24.1 Business Overview24.24.2 Product Offerings24.25 DEEP GENOMICS24.25.1 Business Overview24.25.2 Product Offerings24.26 WELLTOK INC.24.26.1 Business Overview24.26.2 Product Offerings24.27 MDLIVE24.27.1 Business Overview24.27.2 Product Offerings24.28 MAXQ AI24.28.1 Business Overview24.28.2 Product Offerings24.29 QVENTUS24.29.1 Business Overview24.29.2 Product Offerings24.30 WORKFUSION24.30.1 Business Overview24.30.2 Product Offerings
25 Report Summary25.1 Key Takeaways25.2 Strategic Recommendations
26 Quantitative Summary
27 Appendix
For more information about this report visit https://www.researchandmarkets.com/r/it4jn7
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Insights on the Healthcare Artificial Intelligence Global Market to 2026 - Featuring Google, IBM and Intel Among Others - GlobeNewswire
Robo-dogs and therapy bots: Artificial intelligence goes cuddly – CBS News
TOKYO As pandemic-led isolation triggers an epidemic of loneliness, Japanese are increasingly turning to "social robots" for solace and mental healing.
At the city's Penguin Cafe, proud owners of the electronic dog Aibo gathered recently with their cyber-pups in Snuglis and fancy carryalls. From camera-embedded snouts to their sensor-packed paws, these high-tech hounds are nothing less than members of the family, despite a price tag of close to $3,000 mandatory cloud plan not included.
It's no wonder Aibo has pawed its way into hearts and minds. Re-launched in 2017, Aibo's artificial intelligence-driven personality is minutely shaped by the whims and habits of its owner, building the kind of intense emotional attachments usually associated with kids, or beloved pets.
Noriko Yamada rushed to order one, when her mother-in-law began showing signs of dementia several years ago. "Mother had stopped smiling and talking," she told CBS News. "But when we switched the dog on, and it gazed up at her, she just lit up. Her behavior changed 180 degrees."
And a few months ago, when the mother-in-law was hospitalized for heart disease, Koro the robot again came to the rescue. "Because of COVID, we couldn't visit her. The nurse said Mother was responding to pictures of Koro, and asked us to bring in the dog. So, Koro was the last person in our family to see Mother alive."
Robots as companions are an easier leap for Japanese, many manufacturers and users say, because the country is steeped in friendly androids, like the long-running TV cartoon "Doraemon," in which a cute, roly-poly pal provides not only constant company, but an endless supply of useful tricks.
But one robot startup is proving looks aren't everything. Despite having neither head, arms nor legs, the Qoobo bot sold more than 30,000 units by September, many to stressed-out users working from home under COVID restrictions. The retail price starts at about $200.
Yukai Engineering CEO Shunsuke Aoki told CBS News that Qoobo leverages the most pleasing parts of a pet a fluffy torso, and a wagging tail. "At first, it seemed weird," he said. "But when you pet an animal like a cat, you usually don't bother to look at its face."
Frazzled adults aren't the only Japanese turning to robots. At Moriyama Kindergarten in the central Japanese city of Nagoya, robots are replacing the traditional class guinea pig or bunny. Teachers told CBS News that the bots reduce anxiety and teach kids to be more humane.
Two years ago, the preschool bought a pair of Lovot brand bots named Rice Cake and Cocoa. Weighing as much as an infant, with the price tag of a French bulldog, the cybernetic machines are designed to love-bomb their owners -- or, in this case, a roomful of fidgety five-year-olds.
"Our kids think the robots are alive," said principal Kyoshin Kodama. "The bots have encouraged the kids to take better care of things, be kinder to each other, and cooperate more."
Lovot is a so-called "emotional robot" programmed to autonomously navigate its surroundings, remember its owners and respond to hugs and other affection, gazing out with its oversized, quivering, high-resolution eyes. Over the last year sales have jumped 11-fold.
"Their body temperature is set to 98.6 degrees," Groove X company spokesperson Miki Ikegami told CBS News. "Robots are usually hard, cold and inhuman. But since our bots are built to soothe, we made them warm and soft."
Japan's oldest and most successful social robot is an FDA-approved device called Paro.
Resembling an ordinary plush toy, the artificial intelligence-powered bot customizes its response as it gets to "know" each patient. Inventor Takanori Shibata, based at Japan's National Institute of Advanced Industrial Science and Technology, told CBS News that clinical trials have backed the device's benefits as a non-drug therapy. "Interaction with Paro can improve depression, anxiety, pain and also improve the mood of the person."
Since launching in 1998, thousands of Paro robots have gone into service, worldwide, relieving stress among children in ICUs, treating U.S. veterans suffering from PTSD, and helping dementia patients.
Like real flesh-and-blood pets, Paro has been shown to stimulate brain activity, helping reconnect damaged areas. "One lady didn't speak for more than ten years," Shibata said. "When she interacted with Paro, she started to talk to Paro and she recovered her speech and she spoke to others."
Neuroscientist Julie Robillard, who studies social robots for children and seniors, told CBS News that robotics experts are trying to tease out the exact nature of the human-robot relationship and the notion of machines as friends is not as farfetched as it might seem.
"We can be attached to various types of devices and objects," said Robillard, an assistant professor of neurology at the University of British Columbia. "Some people have given names to their robot vacuums Some people feel strongly about their cars or about their wedding bands."
Evidence supports the use of social robots, she said, in areas like imparting social skills to children with autism, or teaching exercises to rehab patients offering instruction without judgment.
But in other areas, it's unclear how well social robots really work, she said. "What we can say from the science right now is that robots have a huge amount of potential."
And discovering that potential is all the more urgent now, in the covid era, as robots offer the promise of social connection without social contact.
Creators say intelligent social robots will never replace humans. But when companions, caregivers or therapists aren't available, robots are lending a friendly paw and are already earning their keep.
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Robo-dogs and therapy bots: Artificial intelligence goes cuddly - CBS News
The role of artificial intelligence in the future of content – TechTarget
Rather than simple text and images, modern content management encompasses different types of information -- like photos, interactive graphics, videos, audio and other digitized assets -- that systems can assemble dynamically.
Modern content management serves a business purpose and streamlines how organizations create and distribute digital experiences. And, in the future of content management, AI plays a key role. Organizations must control the content that travels through their networks to improve digital work and create business value, which may mean embracing more advanced technologies.
Initially, content management sought to separate technical tasks -- like website launches -- from editorial tasks, like information updates. Web administrators and IT support staff also needed easy ways to hand off routine chores, like webpage maintenance, to nontechnical users, which content management made easier.
Over the years, aspects of content management have evolved, including types of content and required skills, relevant tools and storage.
Content management continues to support two audiences: technical professionals and line-of-business users. Yet, content has evolved from information on static webpages into dynamic experiences across multiple devices, business channels and customer touchpoints.
The content evolution developed new tasks, which require new business roles. And, within IT and line-of-business groups, more professionals with different technical and nontechnical skills perform computational tasks, produce content and embrace innovative business apps.
With those innovative business apps, digital marketers, sales executives and other line-of-business managers expect to combine content from disparate sources for purpose-built apps. For example, marketers can launch digital campaigns with interactive webpages, targeted emails and personalized offers based on buyers' intent.
Content management no longer limits file storage to self-contained repositories and content to predefined webpages, but encompasses multiple cloud-based repositories.
A modern approach to content management supports the following four key computational capabilities known as MACH:
AI encompasses many computational capabilities to create and analyze information. Organizations can use AI and machine learning (ML) to recognize patterns in data and metadata in the following ways:
While AI algorithms require employees with the expertise to implement and maintain them, this technology doesn't exist in a vacuum. Instead, organizations tie AI to predefined tasks and activities to save workers time and effort.
Independent software vendors, ranging from industry stalwarts to startups, embed AI capabilities in their tools. They condense specific algorithms into microservices, making these services accessible through APIs, and rely on cloud connections to control content flows.
To develop content-powered apps, organizations must focus on app integration. AI aims to create next-generation business apps with microservices and APIs connected through cloud environments to back-end content repositories -- a MACH-based architecture. This architecture could simplify how AI integrates into content flows from disparate sources, like apps, and weaves together metadata.
AI can make apps more useful, but organizations won't produce content-powered apps overnight. Organizations should consider four trends to assess how AI will affect operations to prepare for the future.
Content management depends on explicit and implicit metadata. As organizations develop business apps, they define metadata categories through information architectures.
AI algorithms can automate metadata management to read through documents, scan images, extract meaning from text, recognize objects within digital assets and assign relevant categories to content. AI can enable app developers to access more relevant content to build smarter apps.
AI can create micro-experiences to automate tasks, actions and activities.
With a shoppable content micro-experience, customers could buy items directly in an app without a storefront or website. For example, a person might see a sweater in a photo, tap it and then buy it -- all without visiting the brand's website.
Similarly, writers may rely on writing support tools to check spelling and grammar, get advice on tone-of-voice, verify brand terminology, check style guidelines and recommend revisions. AI could expedite editorial tasks that proofreaders and editors typically perform and reduce production costs.
With MACH, content management could combine content from more disparate sources, and AI could make that content actionable.
Even with innovative AI-powered tools, human insight matters.
Thus, compliance teams may rely on AI to monitor and decrypt large document collections stored within content repositories. Marketing teams can automatically verify digital image rights before they approve them for distribution, add them to websites and include them in advertising campaigns.
However, organizations may struggle to design smart processes that separate business problems into tasks, combine content from disparate sources and determine how AI algorithms can enhance work. Additionally, organizations must focus on people and how they handle processes.
Even with innovative AI-powered tools, human insight matters. Organizations will require new roles for employees, contractors and business partners beyond the technical and line-of-business silos.
Instead, these roles should add specialized skills that combine computational and business expertise to work with innovative content management technologies. Improving work could lead to next-generation content-powered apps, staffed and managed with human intelligence.
As content has evolved, so have the skills and tools required to manage it. In the future, AI and ML will help enrich content, develop micro-experiences, enable smart processes and create new roles for employees. But this isn't a change that will happen overnight. Instead, organizations must prepare for a steady and inevitable progression.
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The role of artificial intelligence in the future of content - TechTarget
Will Artificial Intelligence Take Over Your Job in 2022? – Digital Information World
We have been worried about artificial intelligence (AI) and other kinds of robots taking over our jobs for quite some time now. Techno paranoia is by no means a new phenomenon, and it manifests itself in a wide range of ways including situations where people will be concerned about the impact that automation might have on their careers. With the new year right around the corner, what are the chances that AI might make you unemployed in 2022? Peoples opinions on this are quite varied.
The group that is perhaps most fearful of losing their jobs to an AI based program is that of college graduates. Over 69% of people that have completed a college degree fear that they might not be able to get a job or that AI will make their job more or less redundant in the coming years since it would more than likely be able to do whatever job they can handle in a much more efficient manner and they would cost a lot less too.
If you look at all of the respondents to the survey as a whole, you would notice that the average is around 55% for people that are afraid to losing jobs to AI. Hence, college graduates seem to be disproportionately worried about this sort of thing occurring with all things having been considered and taken into account. However, if we were to break down the responses and sort them out by the category of job that we are looking at, it becomes clear that virtually everyone is fearful of the impact of AI.
For example, about 63% of respondents felt that the role of cashiers will be fulfilled by AI in the coming years. This has already started to occur, with Amazon creating stores that you can walk in and out of and your payment will be automatically calculated and deducted from your bank account or some other source of funds. The practicality of such a setup is yet to be tested, but suffice it to say that it already exists in the modern day and many fast food companies are experimenting with this as well.
52% of respondents also said that they felt that the jobs of drivers could be automated and made redundant. This might have something or the other to do with the rise of driverless cars which use a computer program and an algorithm to make it so that you dont have to take the wheel. While these types of cars still have a long way to go before they can become the global standard, they have been getting better on a regular basis and might make traffic jams less prevalent than they are right now.
With all of that having been said and now out of the way, it is important to note that not all of the views that people have about AI are negative. If we were to take the example of the economy, around 45% of respondents felt that AI could do a lot of good in this regard. These respondents felt that if AI were made responsible for things like fiscal policy and the like it could reduce the prevalence of corruption and create a smoother type of system for everyone to enjoy.
However, that doesnt mean that everyone agrees that this is a good idea. 29% of respondents felt that doing so would be disastrous for the economy, but a plurality appear to think otherwise. The fact of the matter is that opinions regarding AI are mixed, but this has absolutely no impact on its growth this year. It will continue to grow in 2022 and the changes that are coming would need to be dealt with as and when they arrive so that people can get accustomed to a new way of living. Take a look at below charts more insights on fear of artificial intelligence and its trends, which comes courtesy of Tidio.
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Will Artificial Intelligence Take Over Your Job in 2022? - Digital Information World
Artificial intelligence is restoring lost works by Klimt, Picasso and Rembrandt, but not everyone is happy about it – Bowling Green Daily News
Country
United States of AmericaUS Virgin IslandsUnited States Minor Outlying IslandsCanadaMexico, United Mexican StatesBahamas, Commonwealth of theCuba, Republic ofDominican RepublicHaiti, Republic ofJamaicaAfghanistanAlbania, People's Socialist Republic ofAlgeria, People's Democratic Republic ofAmerican SamoaAndorra, Principality ofAngola, Republic ofAnguillaAntarctica (the territory South of 60 deg S)Antigua and BarbudaArgentina, Argentine RepublicArmeniaArubaAustralia, Commonwealth ofAustria, Republic ofAzerbaijan, Republic ofBahrain, Kingdom ofBangladesh, People's Republic ofBarbadosBelarusBelgium, Kingdom ofBelizeBenin, People's Republic ofBermudaBhutan, Kingdom ofBolivia, Republic ofBosnia and HerzegovinaBotswana, Republic ofBouvet Island (Bouvetoya)Brazil, Federative Republic ofBritish Indian Ocean Territory (Chagos Archipelago)British Virgin IslandsBrunei DarussalamBulgaria, People's Republic ofBurkina FasoBurundi, Republic ofCambodia, Kingdom ofCameroon, United Republic ofCape Verde, Republic ofCayman IslandsCentral African RepublicChad, Republic ofChile, Republic ofChina, People's Republic ofChristmas IslandCocos (Keeling) IslandsColombia, Republic ofComoros, Union of theCongo, Democratic Republic ofCongo, People's Republic ofCook IslandsCosta Rica, Republic ofCote D'Ivoire, Ivory Coast, Republic of theCyprus, Republic ofCzech RepublicDenmark, Kingdom ofDjibouti, Republic ofDominica, Commonwealth ofEcuador, Republic ofEgypt, Arab Republic ofEl Salvador, Republic ofEquatorial Guinea, Republic ofEritreaEstoniaEthiopiaFaeroe IslandsFalkland Islands (Malvinas)Fiji, Republic of the Fiji IslandsFinland, Republic ofFrance, French RepublicFrench GuianaFrench PolynesiaFrench Southern TerritoriesGabon, Gabonese RepublicGambia, Republic of theGeorgiaGermanyGhana, Republic ofGibraltarGreece, Hellenic RepublicGreenlandGrenadaGuadaloupeGuamGuatemala, Republic ofGuinea, RevolutionaryPeople's Rep'c ofGuinea-Bissau, Republic ofGuyana, Republic ofHeard and McDonald IslandsHoly See (Vatican City State)Honduras, Republic ofHong Kong, Special Administrative Region of ChinaHrvatska (Croatia)Hungary, Hungarian People's RepublicIceland, Republic ofIndia, Republic ofIndonesia, Republic ofIran, Islamic Republic ofIraq, Republic ofIrelandIsrael, State ofItaly, Italian RepublicJapanJordan, Hashemite Kingdom ofKazakhstan, Republic ofKenya, Republic ofKiribati, Republic ofKorea, Democratic People's Republic ofKorea, Republic ofKuwait, State ofKyrgyz RepublicLao People's Democratic RepublicLatviaLebanon, Lebanese RepublicLesotho, Kingdom ofLiberia, Republic ofLibyan Arab JamahiriyaLiechtenstein, Principality ofLithuaniaLuxembourg, Grand Duchy ofMacao, Special Administrative Region of ChinaMacedonia, the former Yugoslav Republic ofMadagascar, Republic ofMalawi, Republic ofMalaysiaMaldives, Republic ofMali, Republic ofMalta, Republic ofMarshall IslandsMartiniqueMauritania, Islamic Republic ofMauritiusMayotteMicronesia, Federated States ofMoldova, Republic ofMonaco, Principality ofMongolia, Mongolian People's RepublicMontserratMorocco, Kingdom ofMozambique, People's Republic ofMyanmarNamibiaNauru, Republic ofNepal, Kingdom ofNetherlands AntillesNetherlands, Kingdom of theNew CaledoniaNew ZealandNicaragua, Republic ofNiger, Republic of theNigeria, Federal Republic ofNiue, Republic ofNorfolk IslandNorthern Mariana IslandsNorway, Kingdom ofOman, Sultanate ofPakistan, Islamic Republic ofPalauPalestinian Territory, OccupiedPanama, Republic ofPapua New GuineaParaguay, Republic ofPeru, Republic ofPhilippines, Republic of thePitcairn IslandPoland, Polish People's RepublicPortugal, Portuguese RepublicPuerto RicoQatar, State ofReunionRomania, Socialist Republic ofRussian FederationRwanda, Rwandese RepublicSamoa, Independent State ofSan Marino, Republic ofSao Tome and Principe, Democratic Republic ofSaudi Arabia, Kingdom ofSenegal, Republic ofSerbia and MontenegroSeychelles, Republic ofSierra Leone, Republic ofSingapore, Republic ofSlovakia (Slovak Republic)SloveniaSolomon IslandsSomalia, Somali RepublicSouth Africa, Republic ofSouth Georgia and the South Sandwich IslandsSpain, Spanish StateSri Lanka, Democratic Socialist Republic ofSt. HelenaSt. Kitts and NevisSt. LuciaSt. Pierre and MiquelonSt. Vincent and the GrenadinesSudan, Democratic Republic of theSuriname, Republic ofSvalbard & Jan Mayen IslandsSwaziland, Kingdom ofSweden, Kingdom ofSwitzerland, Swiss ConfederationSyrian Arab RepublicTaiwan, Province of ChinaTajikistanTanzania, United Republic ofThailand, Kingdom ofTimor-Leste, Democratic Republic ofTogo, Togolese RepublicTokelau (Tokelau Islands)Tonga, Kingdom ofTrinidad and Tobago, Republic ofTunisia, Republic ofTurkey, Republic ofTurkmenistanTurks and Caicos IslandsTuvaluUganda, Republic ofUkraineUnited Arab EmiratesUnited Kingdom of Great Britain & N. IrelandUruguay, Eastern Republic ofUzbekistanVanuatuVenezuela, Bolivarian Republic ofViet Nam, Socialist Republic ofWallis and Futuna IslandsWestern SaharaYemenZambia, Republic ofZimbabwe
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Artificial intelligence is restoring lost works by Klimt, Picasso and Rembrandt, but not everyone is happy about it - Bowling Green Daily News