Category Archives: Artificial Intelligence
Regulation of Artificial Intelligence in Europe – What’s in the pipeline? – Lexology
Shortly after her inauguration, the new European Commissions president, Ursula von der Leyen, expressed the intent of the new commission to come up with a Digital Strategy addressing Artificial Intelligence regulation within 100 days from beginning of her presidency. Keeping this promise, the European Commission published a first White Paper on Artificial Intelligence A European approach to excellence and trust in February 2020. Statements on such White Paper were collected until 31 May 2020. Together with the White Paper the Commission Report on safety and liability implications of AI, the Internet of Things and Robotics was published, providing more details on the gaps the Commission has identified in existing laws.
What are we talking about?
A definition of Artificial Intelligence was provided by the European Commissions AI High Level Expert Group (AI HLEG) on 8 April 2019, when this group provided Ethics guidelines for trustworthy AI. The Commissions papers are referring to AI HLEG, which defines AI as follows:
Artificial intelligence (AI) systems are software (and possibility also hardware) systems
These defining aspect of AI form the basis of an evaluation of legal gaps and possible requirements for new regulation.
Where are the legal gaps?
The Commission Report on safety and liability implications of AI, the Internet of Things and Robotics identified legal gaps mainly in the following respect:
The European Parliament published a further Report on Intellectual property rights for the development of artificial intelligence technologies, evaluating the status quo and identifying various gaps in IP law. The report found, for example, gaps in respect to the question whether AI is or can be protected by IP, whether IP protected content can be food for AI training and whether someone owns rights to works created by AI.
What kind of regulation do we have to expect?
Upon identification of the various gaps, the EU intends to issue a comprehensive legislative package on AI, which will include new regulations for those who build and deploy AI. First hints on what could be part of such package can be taken from three resolutions the European parliament adopted on 20 October: the Framework of ethical aspects of artificial intelligence, robotics and related technologies; the Civil liability regime for artificial intelligence and the Intellectual property rights for the development of artificial intelligence technologies.
Looking at these Resolution, the following topics might be seen as key to build an ecosystem of trust and enhance the general social acceptance of AI:
When?
A first draft of such new AI legal framework is expected for the first quarter of 2021, whereas some parts could already be reflected in the Digital Services Act, for which a first draft is already expected in December 2020.
Who?
Addressee of such obligations might not always be the software developer, but could be the actor who is best placed to address potential risks. Obligations could therefore also be imposed on the deployer or the service provider. And the obligations will have to be obeyed by all economic operators providing AI-enabled products or services in the EU, regardless of whether they are established in the EU or not.
What to do?
Anyone engaged or interested in AI should monitor closely the developments of the upcoming months, as the new laws will most certainly have impact on AI systems that are currently trained or are even already on the market.
In practice, contractual frameworks for AI systems should therefore already be examined and might include clauses anticipating future developments. Certain upcoming liability risks might also already be taken into account.
Read more:
Regulation of Artificial Intelligence in Europe - What's in the pipeline? - Lexology
Core Banking Software Market to Reach USD 28.83 Billion by 2027; Adoption of Artificial Intelligence & Cloud in Banking Industry to Aid Growth:…
Pune, Dec. 04, 2020 (GLOBE NEWSWIRE) -- The global core banking software market is set to gain impetus from the increasing adoption of innovative technologies, such as cloud, artificial intelligence, and machine learning in the banking industry. This information is given by Fortune Business Insights in a new study, titled, Core Banking Software Market Size, Share & COVID-19 Impact Analysis, By Deployment (SaaS/Hosted, Licensed), By Banking Type (Large Banks, Midsize Banks, Small Banks, Community Banks, and Credit Unions), By End-user (Retail Banking, Treasury, Corporate Banking, and Wealth Management), and Regional Forecast, 2020-2027. The study further mentions that the market size was USD 8.17 billion in 2019 and is projected to reach USD 28.83 billion by 2027, exhibiting a CAGR of 17.4% during the forecast period.
Click here to get the short-term and long-term impact of COVID-19 on this market.
Please visit: https://www.fortunebusinessinsights.com/core-banking-software-market-104392
COVID-19 Pandemic to Hinder Growth by Changing Interest Rates
The emergence of the COVID-19 pandemic has changed the work culture of various industries across the globe. Numerous financial and baking institutes are implementing the work from home (WFH) policy. Besides, delays in lease payments and changes in interest rates would affect growth negatively. We are delivering accurate reports to help you gain more insights into the current situation of the market.
To get to know more about the short-term and long-term impact of COVID-19 on this market, please visit:
How Did We Develop This Report?
The market for core banking software houses regulatory firms and processors in its supply chain. We have used both primary and secondary research to obtain quantitative and qualitative data about the supply and demand sides. We have also analyzed competitive developments, such as collaborations, new product launches, mergers & acquisitions, joint ventures, collaborations, and agreements. Lastly, the report includes profiles of the prominent organizations and the strategies adopted by them to increase sales.
Get Sample PDF Brochure: https://www.fortunebusinessinsights.com/enquiry/request-sample-pdf/core-banking-software-market-104392
Drivers & Restraints-
Increasing Need to Monitor Banking Processes Efficiently Will Bolster Growth
The increasing adoption of SaaS-based or cloud-based core banking software solutions provided by various manufacturers, such as Temenos AG and Finastra would propel the market growth in the near future. These help banks in monitoring transactions and payments effectively. However, the surging concerns about mobile malware, application vulnerabilities, information loss, and unencrypted data may obstruct the demand for core banking software solutions.
Segment-
Large Banks Segment to Grow Rapidly Fueled by Higher Penetration of Internet
Based on the banking type, the large bank's segment generated 34.8% in terms of the core banking software market share. It is likely to remain at the forefront stoked by the rising penetration of the internet and the increasing usage of connected devices for analyzing banking processes.
Speak to Analyst: https://www.fortunebusinessinsights.com/enquiry/speak-to-analyst/core-banking-software-market-104392
Regional Insights-
North America to Dominate Backed by Presence of Prominent Manufacturers
Geographically, in 2019, North America procured USD 3.71 billion in terms of revenue and is set to lead throughout the forthcoming years. This growth is attributable to the presence of reputed core banking software providers, such as VSoft Corporation, Fidelity National Information Services, Inc., and others in the region. Asia Pacific, on the other hand, is expected to be the fastest-growing market because of the increasing adoption of mobile and web-based business applications in the banking sector.
Competitive Landscape-
Key Players Focus on Launching Novel Core Banking Software to Intensify Competition
This market contains a large number of companies. They are mainly focusing on the development of innovative software solutions to cater to the high demand worldwide. Some of the others are also engaged in the partnership strategy to enhance their positions. Below are the two latest industry developments:
List Of Key Companies profiled in Core Banking Software Market Are:
Quick Buy Core Banking Software Market Research Report: https://www.fortunebusinessinsights.com/checkout-page/104392
Detailed Table of Content:
TOC Continued..
Get your Customized Research Report:
https://www.fortunebusinessinsights.com/enquiry/customization/core-banking-software-market-104392
Have a Look at Related Research Insights:
Customer Experience Management Market Size, Share & Industry Analysis, By Component (Solution, Services), By Deployment (On-Premises, Cloud), By Organization Size (SMEs, Large Enterprises), By Touchpoint (Telephone, Email, Web, Social Media, and Others), By End-User (BFSI, Retail, IT and Telecommunications, Healthcare, Manufacturing, Government, Travel and Transportation and Others) and Regional Forecast, 2019-2026
Customer Data Platform Market Size, Share & COVID-19 Impact Analysis, By Component (Platform and Services), By Deployment (Cloud, On-premises), By Type (Access, Analytics, and Campaign) By Industry (Banking, Financial Services and Insurance (BFSI), Retail and ecommerce, Information Technology (IT) and Telecom, Media and Entertainment, Travel and Hospitality, Healthcare, and Others (Government and Education)), and Regional Forecast, 2020-2027
Professional Service Automation Software Market Size, Share & Industry Analysis, By Application (Consulting Firms, Marketing and Communication Firms, IT Firms, Architecture and Construction Firms, Research Firms, Accounting Firms, Others), By Deployment Type (Cloud, On-premise) and Regional Forecast, 2019-2026
Artificial Intelligence (AI) Market Size, Share and Industry Analysis By Component (Hardware, Software, Services), By Technology (Computer Vision, Machine Learning, Natural Language Processing, Others), By Industry Vertical (BFSI, Healthcare, Manufacturing, Retail, IT & Telecom, Government, Others) and Regional Forecast, 2019-2026
Digital Payment Market Size, Share & Industry Analysis, By Payment Type (Mobile Payment, Online Banking, Point of Sale, Digital Wallet), By Industry (Media & Entertainment, Retail, BFSI, Automotive, Medical & Healthcare, Transportation, Consumer Electronics, Others), and Regional Forecast, 2019-2026
About Us:
Fortune Business Insightsoffers expert corporate analysis and accurate data, helping organizations of all sizes make timely decisions. We tailor innovative solutions for our clients, assisting them address challenges distinct to their businesses. Our goal is to empower our clients with holistic market intelligence, giving a granular overview of the market they are operating in.
Our reports contain a unique mix of tangible insights and qualitative analysis to help companies achieve sustainable growth. Our team of experienced analysts and consultants use industry-leading research tools and techniques to compile comprehensive market studies, interspersed with relevant data.
At Fortune Business Insights, we aim at highlighting the most lucrative growth opportunities for our clients. We therefore offer recommendations, making it easier for them to navigate through technological and market-related changes. Our consulting services are designed to help organizations identify hidden opportunities and understand prevailing competitive challenges.
Contact Us:Fortune Business Insights Pvt. Ltd.308, Supreme Headquarters,Survey No. 36, Baner,Pune-Bangalore Highway,Pune- 411045, Maharashtra,India.Phone:US: +1-424-253-0390UK: +44-2071-939123APAC: +91-744-740-1245Email:sales@fortunebusinessinsights.comFortune Business InsightsLinkedIn|Twitter|Blogs
See the article here:
Core Banking Software Market to Reach USD 28.83 Billion by 2027; Adoption of Artificial Intelligence & Cloud in Banking Industry to Aid Growth:...
Artificial Intelligence Predicts Drug Combinations That Kill Cancer Cells More Effectively – SciTechDaily
AI methods can help us perfect drug combinations. Credit: Matti Ahlgren, Aalto University
A machine learning model developed in Finland can help us treat cancer more effectively.
When healthcare professionals treat patients suffering from advanced cancers, they usually need to use a combination of different therapies. In addition to cancer surgery, the patients are often treated with radiation therapy, medication, or both.
Medication can be combined, with different drugs acting on different cancer cells. Combinatorial drug therapies often improve the effectiveness of the treatment and can reduce the harmful side-effects if the dosage of individual drugs can be reduced. However, experimental screening of drug combinations is very slow and expensive, and therefore, often fails to discover the full benefits of combination therapy. With the help of a new machine learning method, one could identify best combinations to selectively kill cancer cells with specific genetic or functional makeup.
Researchers at Aalto University, University of Helsinki and the University of Turku in Finland developed a machine learning model that accurately predicts how combinations of different cancer drugs kill various types of cancer cells. The new AI model was trained with a large set of data obtained from previous studies, which had investigated the association between drugs and cancer cells. The model learned by the machine is actually a polynomial function familiar from school mathematics, but a very complex one, says Professor Juho Rousu from Aalto University.
The research results were published in the prestigious journalNature Communications, demonstrating that the model found associations between drugs and cancer cells that were not observed previously. The model gives very accurate results. For example, the values of the so-called correlation coefficient were more than 0.9 in our experiments, which points to excellent reliability, says Professor Rousu. In experimental measurements, a correlation coefficient of 0.8-0.9 is considered reliable.
The model accurately predicts how a drug combination selectively inhibits particular cancer cells when the effect of the drug combination on that type of cancer has not been previously tested. This will help cancer researchers to prioritize which drug combinations to choose from thousands of options for further research, says researcher Tero Aittokallio from the Institute for Molecular Medicine Finland (FIMM) at the University of Helsinki.
The same machine learning approach could be used for non-cancerous diseases. In this case, the model would have to be re-taught with data related to that disease. For example, the model could be used to study how different combinations of antibiotics affect bacterial infections or how effectively different combinations of drugs kill cells that have been infected by the SARS-Cov-2 coronavirus.
Reference: 1 December 2020, Nature Communications.
DOI: 10.1038/s41467-020-19950-z
Excerpt from:
Artificial Intelligence Predicts Drug Combinations That Kill Cancer Cells More Effectively - SciTechDaily
iHealthScreen’s Artificial Intelligence (AI) Based Tool Can Accurately Diagnose Age-Related Macular Degeneration (AMD) and Help Prevent Blindness -…
RICHMOND HILL, N.Y.--(BUSINESS WIRE)--iHealthScreen CEO Alauddin Bhuiyan, Ph.D. along with collaborators at New York Eye and Ear Infirmary at Mount Sinai (NYEEI), presented a prospective study for early diagnosis of AMD at the annual conference of AAO, 2020. The results presented during the prestigious Original Paper Session demonstrated 88.7% accuracy, compared to ophthalmologist gradings, on detecting referable AMD.
AMD, with no early signs or symptoms, is a leading cause of adult blindness in the developed world. Early detection can enable preventative measures in time and stop AMD incident. Currently, AMD diagnosis has been limited to retinal examination by an ophthalmologist. AMD cases in the U.S. are expected to grow from 2.1 million to 5.4 million in the next ten years, and there is an increasing need for large scale screening and identification of individuals who are at risk of developing late AMD. iHealthScreens AI based tool can facilitate this screening and help prevention of late AMD.
In an interview, Dr. Bhuiyan spoke about the study and the findings: We are encouraged by the results and believe that the new AI-based technology can diagnose early AMD in primary care settings, which enables the timely preventative measures by ophthalmologist and prevent this deterioration of vision. We want to express our sincerest thanks to the participants and professional staff who were involved in this clinical trial and gathered the data.
These results speak to the feasibility of this approach, said Theodore Smith, M.D., Ph.D., Trials Principal-investigator and Professor at Icahn School of Medicine at Mount Sinai. I believe that the ease of use of iHealthScreens AI tool will contribute to its adoption in the wider primary care community.
About iHealthScreen
iHealthScreen is a private, clinical-stage, medical diagnostic/device company. iHealthScreen has developed iPredict, an AI and telemedicine-based HIPAA compliant platform for automated screening and prediction of individuals at risk of developing late age-related AMD, diabetic retinopathy (DR), glaucoma, cardiovascular heart disease and stroke.
Continue reading here:
iHealthScreen's Artificial Intelligence (AI) Based Tool Can Accurately Diagnose Age-Related Macular Degeneration (AMD) and Help Prevent Blindness -...
Artificial Intelligence the new season is out – Jordan Times
Artificial Intelligence (AI) is changing computers from calculators to thinking, decision-making systems.
After years of being a more or less theoretical topic, AI has become reality. Forget about Steven Spielbergs A.I. Artificial Intelligence movie from 2001 that was merely entertainment, though with valid examples and illustrations of AI. The technology now is very much in self-driving vehicles, in the analysis of our online shopping and browsing habits on social media, and of course in advanced banking applications, to name only a few. Indeed, the sky is the limit when it comes to AI.
I still keep a copy of the excellent Artificial Intelligence textbook by Elaine Rich from the University of Texas in Austin, that got me to start reading and learning about the subject years ago. As enlightening, good, accurate, and genuinely scientific as it was back then, it seems like it was written centuries ago, given all the concrete progress achieved since!
There are a few, notable landmarks along the fascinating journey with computers and digital high-technology that started in the late 1940s.
The first was the personal computers revolution of the 1980s. Then came the Internet (cabled and slow at the beginning), almost in parallel with the early portable computers that had little to do with the current crop of laptops in terms of processing power, storage capability and weight. Today wireless, fast Internet, with powerful and truly portable devices, combined with the IoT (Internet of Things), and social media, constitute the most recent, most significant landmark on the digital timeline. By any measure, AI is the next big thing, one that is already upon us.
AI is more about software than it is about hardware, though it is common today to talk about AI chips. It simply means that the circuitry is hard-programmed with AI algorithms, Whereas traditional programming processes data and generates reports, in a rather straightforward manner, to put is simply, AI can go further by analysing data huge amounts of it more deeply, in a more intelligent way, and come up with decisions or suggestions, somewhat like a human being would hence the expression.
Tesla electric cars constitute a good example of AI applications. As explained on analyticssteps.com: The Tesla system consists of two AI chips in order to support it for better road performance. Each of the AI chips makes a separate assessment of the traffic situation for guiding the car accordingly.
In banking, AI solutions are helping banks and credit lenders make smarter underwriting decisions by utilising a variety of factors that more accurately assess traditionally underserved borrowers, like millennials, in the credit decision making process. (builtin.com/artificial-intelligence).
Just like old, traditional computing systems did, AI is now is raising a few questions, on the social side of things. The main one being, of course: To what extent will AI replace human work and negatively impact on unemployment?
Instead of trying desperately to answer this otherwise perfectly legitimate and justified question, one can be more pragmatic and think of all that AI can bring. If there is only one major advantage that AI will bring when it comes to smart self-driving cars, it will be a significant drop in road accidents and casualties. This alone is a priceless plus.
Original post:
Artificial Intelligence the new season is out - Jordan Times
Artificial intelligence solved a protein puzzle; why it matters – Business Standard
Theres long been speculation if artificial intelligence (AI) could perform scientific tasks beyond the understanding of human beings. A paper in Nature indicates this may now have happened. Since 1994, bio-scientists have held a biennial contest called CASP (Critical Assessment of Structure Prediction).
Teams use computers to predict the ways in which given proteins will fold. The 100 or so problems presented at each CASP are those of proteins where the structure has already been determined, but not yet made public. The participating computer programs are judged on the basis of ...
Key stories on business-standard.com are available to premium subscribers only.
MONTHLY STAR
Business Standard Digital Monthly Subscription
Complete access to the premium product
Convenient - Pay as you go
Pay using Master/Visa Credit Card & ICICI VISA Debit Card
Auto renewed (subject to your card issuer's permission)
Cancel any time in the future
Note: Subscription will be auto renewed, you may cancel any time in the future without any questions asked.
Requires personal information
SMART MONTHLY
Business Standard Digital - 12 Months
Get 12 months of Business Standard digital access
Single Seamless Sign-up to Business Standard Digital
Convenient - Once a year payment
Pay using an instrument of your choice - Credit/Debit Cards, Net Banking, Payment Wallets accepted
Exclusive Invite to select Business Standard events
Note: Subscription will be auto renewed, you may cancel any time in the future without any questions asked.
Business Standard has always strived hard to provide up-to-date information and commentary on developments that are of interest to you and have wider political and economic implications for the country and the world. Your encouragement and constant feedback on how to improve our offering have only made our resolve and commitment to these ideals stronger. Even during these difficult times arising out of Covid-19, we continue to remain committed to keeping you informed and updated with credible news, authoritative views and incisive commentary on topical issues of relevance.We, however, have a request.
As we battle the economic impact of the pandemic, we need your support even more, so that we can continue to offer you more quality content. Our subscription model has seen an encouraging response from many of you, who have subscribed to our online content. More subscription to our online content can only help us achieve the goals of offering you even better and more relevant content. We believe in free, fair and credible journalism. Your support through more subscriptions can help us practise the journalism to which we are committed.
Support quality journalism and subscribe to Business Standard.
Digital Editor
First Published: Thu, December 03 2020. 06:08 IST
Read the original:
Artificial intelligence solved a protein puzzle; why it matters - Business Standard
Europe Artificial Intelligence in Healthcare Diagnosis Markets, 2019-2020 & 2027 – AI in Epidemic Outbreak Prediction and Response Gaining…
DUBLIN, Nov. 30, 2020 /PRNewswire/ -- The "Europe Artificial Intelligence in Healthcare Diagnosis Market Forecast to 2027 - COVID-19 Impact and Regional Analysis by Diagnostic Tool; Application; End User; Service; and Country" report has been added to ResearchAndMarkets.com's offering.
The Europe Radiology Information Systems (RIS) market is projected to reach from US$ 315.32 million in 2019 to US$ 574.44 million by 2027. This represents a CAGR of 8.0% from 2020 to 2027.
The growth of the Europe Radiology Information Systems (RIS) market is primarily attributed to advancements in diagnostic imaging solutions coupled with rising number of diagnostic procedures, and increasing partnerships and collaborations are driving the adoption of radiology information systems.
The healthcare industry has always been a leader in innovation. The constant mutating of diseases and viruses makes it difficult to stay ahead of the curve. However, with the help of artificial intelligence and machine learning algorithms, it continues to advance, creating new treatments and helping people live longer and healthier. Medical imaging is a vital part of medical care and treatment across the globe. Rising awareness regarding early diagnosis of diseases has led to an increase in the total number of diagnostic tests procedures performed around the world.
For instance, as per NHS England report, in 2018, ~42.7 million imaging tests were performed in England, an increase of 1.4% than the previous year. X-ray was the most performed method with 22.9 million procedures, followed by diagnostic ultrasonography (9.51 million), CT Scan (5.15 million), and magnetic resonance imaging (3.46 million).
In 2019, the Integrated RIS segment held a considerable share of the for Europe Radiology Information Systems (RIS) market, by the product. This segment is also predicted to dominate the market by 2027 owing to rising demand for AI based application for radiology.
Key Topics Covered:
1. Introduction
1.1 Scope of the Study
1.2 Report Guidance
1.3 Market Segmentation
2. Europe Artificial Intelligence in Healthcare Diagnosis Market - Key Takeaways
3. Research Methodology
3.1 Coverage
3.2 Secondary Research
3.3 Primary Research
4. Europe Artificial Intelligence in Healthcare Diagnosis Market - Market Landscape
4.1 Overview
4.2 PEST Analysis
4.3 Expert Opinion
5. Europe Artificial Intelligence in Healthcare Diagnosis Market - Key Market Dynamics
5.1 Market Drivers
5.1.1 Rising Adoption of Artificial Intelligence (AI) in Disease Identification and Diagnosis
5.1.2 Increasing Investment in AI Healthcare Start ups
5.2 Market Restraints
5.2.1 Lack of skilled AI Workforce and Ambiguous Regulatory Guidelines for Medical Software
5.3 Market Opportunities
5.3.1 Increasing Potential in Emerging Economies
5.4 Future Trends
5.4.1 AI in Epidemic Outbreak Prediction and Response
5.5 Impact analysis
6. Europe Artificial Intelligence in Healthcare Diagnosis Market - By Diagnostic Tool
6.1 Overview
6.2 Europe Artificial Intelligence in Healthcare Diagnosis Market Revenue Share, by Diagnostic Tool (2019 and 2027)
6.3 Medical Imaging Tool
6.3.1 Overview
6.3.2 Medical Imaging Tools: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)
6.4 Automated Detection System
6.4.1 Overview
6.4.2 Automated Detection System: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)
6.5 Others
6.5.1 Overview
6.5.2 Others: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)
7. Europe Artificial Intelligence in Healthcare Diagnosis Market Analysis, by Application
7.1 Overview
7.2 Artificial Intelligence in Healthcare Diagnosis Market Revenue Share, by Application (2019 and 2027)
7.3 Eye Care
7.3.1 Overview
7.3.2 Eye Care: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)
7.4 Oncology
7.5 Radiology
7.6 Cardiovascular
8. Europe Artificial Intelligence in Healthcare Diagnosis Market - By End-User
8.1 Overview
8.2 Artificial Intelligence in Healthcare Diagnosis Market, by End-User, 2019 and 2027 (%)
8.3 Hospital and Clinic
8.3.1 Overview
8.3.2 Hospital and Clinic: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)
8.4 Diagnostic Laboratory
8.5 Home Care
8.5.1 Overview
8.5.2 Home Care: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)
8.5.3 Doctors
8.5.4 Patients
9. Europe Artificial Intelligence in Healthcare Diagnosis Market - By Service
9.1 Overview
9.2 Artificial Intelligence in Healthcare Diagnosis Market, by Service, 2019 and 2027 (%)
9.3 Tele-Consultation
9.3.1 Overview
9.3.2 Tele-Consultation: Artificial Intelligence in Healthcare Diagnosis Market - Revenue and Forecast to 2027 (US$ Million)
9.4 Tele-Monitoring
9.5 Others
10. Europe Artificial Intelligence in Healthcare Diagnosis Market - Country Analysis
11. Impact Of COVID-19 Pandemic on Europe Artificial Intelligence in Healthcare Diagnosis Market
11.1 Europe: Impact Assessment Of COVID-19 Pandemic
12. Company Profiles
12.1 Key Facts
12.2 Business Description
12.3 Products and Services
12.4 Financial Overview
12.5 SWOT Analysis
12.6 Key Developments
For more information about this report visit https://www.researchandmarkets.com/r/dj2zk7
Research and Markets also offers Custom Research services providing focused, comprehensive and tailored research.
Media Contact:
Research and Markets Laura Wood, Senior Manager [emailprotected]
For E.S.T Office Hours Call +1-917-300-0470 For U.S./CAN Toll Free Call +1-800-526-8630 For GMT Office Hours Call +353-1-416-8900
U.S. Fax: 646-607-1907 Fax (outside U.S.): +353-1-481-1716
SOURCE Research and Markets
Drones and artificial intelligence show promise for conservation of farmland bird nests – Jill Lopez
Farmland bird species are declining over most of Europe. Birds breeding on the ground, are particularly vulnerable because they are exposed to mechanical operations, like ploughing and sowing, which take place in spring and often accidentally destroy nests.
Locating nests on the ground is challenging for the human eye, and highly time-consuming
Researchers flew a drone carrying a thermal camera over agricultural fields to record images. These were then fed to an artificial intelligence algorithm capable of accurately identifying nests, a first step to aid their protection. Researchers tested the system in Southern Finland near University of Helsinki's Lammi Biological Station, using wild nests with eggs of the Lapwing Vanellus vanellus.
"We have been involved in conservation of ground-nesting farmland birds for years, and realized how difficult it is to locate nests on the ground. At least at high latitudes, the temperature of these nests is typically higher than that of the surrounding environment. Hence, we thought that thermal cameras could assist. A small pilot study indicated that thermal vision is hampered by vegetation and objects on the ground. Therefore to make this an efficient system, we thought that the camera could be flown using a drone, and artificial intelligence could help to analyse the resulting thermal images. We show that this works. However, the system performed best under cloudy and cold conditions, and on even grounds," says Andrea Santangeli, an Academy of Finland fellow at the Finnish Museum of Natural History Luomus, University of Helsinki.
Drone technology becoming rapidly popular in conservation
It is possible to map in near real-time the spread of diseases on crops in agricultural areas using drones with various sensors. The latter is an integral part of precision agriculture, a new way of crop production that makes large use of drone technology to monitor crops and maximize production efficiency.
Studies like this one can help pave the way to integrate bird nest detection within the drone borne sensors used in precision agriculture, and automate a system for saving those nests.
"The conservation community must be ready to embrace technology and work across disciplines and sectors in order to seek efficient solutions. This is already happening, with drone technology becoming rapidly popular in conservation. A next and most challenging step will be to test our system in different environments and with different species. Our auspice is that this system will be, one day, fully integrated into agricultural practices, so that detecting and saving nests from mechanical destruction will become a fully automated part of food production," says Andrea Santangeli.
View post:
Drones and artificial intelligence show promise for conservation of farmland bird nests - Jill Lopez
Artificial intelligence and the classroom of the future | BrandeisNOW – Brandeis University
By Tessa Venell '08Nov. 19, 2020
Imagine a classroom in the future where teachers are working alongside artificial intelligence partners to ensure no student gets left behind.The AI partners careful monitoring picks up on a student in the back who has been quiet and still for the whole class and the AI partner prompts the teacher to engage the student. When called on, the student asks a question. The teacher clarifies the material that has been presented and every student comes away with a better understanding of the lesson.This is part of a larger vision of future classrooms where human instruction and AI technology interact to improve educational environments and the learning experience.James Pustejovsky, the TJX Feldberg Professor of Computer Science, is working towards that vision with a team led by the University of Colorado Boulder, as part of the new $20 million National Science Foundation-funded AI Institute for Student-AI Teaming.The research will play a critical role in helping ensure the AI agent is a natural partner in the classroom, with language and vision capabilities, allowing it to not only hear what the teacher and each student is saying, but also notice gestures (pointing, shrugs, shaking a head), eye gaze, and facial expressions (student attitudes and emotions).
Pustejovsky took some time to answer questions from BrandeisNOW about his research.
How does your research help build this classroom of the future?For the past five years, we have been working to create a multimodal embodied avatar system, called Diana, that interacts with a human to perform various tasks. She can talk, listen, see, and respond to language and gesture from her human partner, and then perform actions in a 3D simulation environment called VoxWorld. This is work we have been conducting with our collaborators at Colorado State University, led by Ross Beveridge in their vision lab. We are working together again (CSU and Brandeis) to help bring this kind of embodied human computer interaction into the classroom. Nikhil Krishnaswamy, my former Ph.D. student and co-developer of Diana, has joined CSU as part of their team.How does it work in the context of a classroom setting?At first its disembodied, a virtual presence on an iPad, for example, where it is able to recognize the voices of different students. So imagine a classroom: Six to 10 children in grade school. The initial goal in the first year is to have the AI partner passively following the different students, in the way they're talking and interacting, and then eventually the partner will learn to intervene to make sure that everyone is equitably represented and participating in the classroom.Are there other settings that Diana would be useful in besides a classroom?Let's say I've got a Julia Child app on my iPad and I want her to help me make bread. If I start the program on the iPad, the Julia Child avatar would be able to understand my speech. If I have my camera set up, the program allows me to be completely embedded and embodied in a virtual space with her so that she can help me.
Screenshot of the embodied avatar system Diana."
How does she help you?She would look at my table and say, Okay, do you have everything you need. And then Id say, I think so. So the camera will be on, and if you had all your baking materials laid out on your table, she would scan the table. She'd say, I see flour, yeast, salt, and water, but I don't see any utensils: you're going to need a cup, you're going to need a teaspoon. After you had everything you needed, she would tell you to put the flour in that bowl over there. And then she'd show you how to mix it.
Is that where Diana comes in?Yes, Diana is basically becoming an embodied presence in the human-computer interaction: she can see what you're doing, you can see what she's doing. In a classroom interaction, Diana could help with guiding students through lesson plans, through dialogue and gesture, while also monitoring the students progress, mood, and levels of satisfaction or frustration.Does Diana have any uses in virtual learning in education?
Using an AI partner for virtual learning could be a fairly natural interaction. In fact, with a platform such as Zoom, many of the computational issues are actually easier since voice and video tracks of different speakers have already been segmented and identified. Furthermore, in a Hollywood Squares display of all the students, a virtual AI partner may not seem as unnatural, and Diana might more easily integrate with the students online.What stage is the research at now?Within the context of the CU Boulder-led AI Institute, the research has just started. Its a five-year project, and its getting off the ground. This is exciting new research that is starting to answer questions about using our avatar and agent technology with students in the classroom.
The research is funded by the National Science Foundation, and partners with CU Boulder on the research include Brandeis University, Colorado State University, the University of California, Santa Cruz, UC Berkeley, Worcester Polytechnic Institute, Georgia Institute of Technology, University of Illinois at Urbana-Champaign, and University of Wisconsin-Madison.
Read the original post:
Artificial intelligence and the classroom of the future | BrandeisNOW - Brandeis University
Artificial Intelligence and Machine Learning, 5G and IoT will be the Most Important Technologies in 2021, According to new IEEE Study – PRNewswire
PISCATAWAY, N.J., Nov. 19, 2020 /PRNewswire/ --IEEE, the world's largest technical professional organization dedicated to advancing technology for humanity, today released the results of a survey of Chief Information Officers (CIOs) and Chief Technology Officers (CTOs) in the U.S., U.K., China, India and Brazil regarding the most important technologies for 2021 overall, the impact of the COVID-19 pandemic on the speed of their technology adoption and the industries expected to be most impacted by technology in the year ahead.
2021 Most Important Technologies and ChallengesWhich will be the most important technologies in 2021? Among total respondents, nearly one-third (32%) say AI and machine learning, followed by 5G (20%) and IoT (14%).
Manufacturing (19%), healthcare (18%), financial services (15%) and education (13%) are the industries that most believe will be impacted by technology in 2021, according to CIOs and CTOS surveyed. At the same time, more than half (52%) of CIOs and CTOs see their biggest challenge in 2021 as dealing with aspects of COVID-19 recovery in relation to business operations. These challenges include a permanent hybrid remote and office work structure (22%), office and facilities reopenings and return (17%), and managing permanent remote working (13%). However, 11% said the agility to stop and start IT initiatives as this unpredictable environment continues will be their biggest challenge. Another 11% cited online security threats, including those related to remote workers, as the biggest challenge they see in 2021.
Technology Adoption, Acceleration and Disaster Preparedness due to COVID-19CIOs and CTOs surveyed have sped up adopting some technologies due to the pandemic:
The adoption of IoT (42%), augmented and virtual reality (35%) and video conferencing (35%) technologies have also been accelerated due to the global pandemic.
Compared to a year ago, CIOs and CTOs overwhelmingly (92%) believe their company is better prepared to respond to a potentially catastrophic interruption such as a data breach or natural disaster. What's more, of those who say they are better prepared, 58% strongly agree that COVID-19 accelerated their preparedness.
When asked which technologies will have the greatest impact on global COVID-19 recovery, one in four (25%) of those surveyed said AI and machine learning,
CybersecurityThe top two concerns for CIOs and CTOs when it comes to the cybersecurity of their organization are security issues related to the mobile workforce including employees bringing their own devices to work (37%) and ensuring the Internet of Things (IoT) is secure (35%). This is not surprising, since the number of connected devices such as smartphones, tablets, sensors, robots and drones is increasing dramatically.
Slightly more than one-third (34%) of CIO and CTO respondents said they can track and manage 26-50% of devices connected to their business, while 20% of those surveyed said they could track and manage 51-75% of connected devices.
About the Survey"The IEEE 2020 Global Survey of CIOs and CTOs" surveyed 350 CIOs or CTOs in the U.S., China, U.K., India and Brazil from September 21 - October 9, 2020.
About IEEEIEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Through its highly cited publications, conferences, technology standards, and professional and educational activities, IEEE is the trusted voice in a wide variety of areas ranging from aerospace systems, computers, and telecommunications to biomedical engineering, electric power, and consumer electronics
SOURCE IEEE
Read the original here:
Artificial Intelligence and Machine Learning, 5G and IoT will be the Most Important Technologies in 2021, According to new IEEE Study - PRNewswire