Cloud Hosting

French VFX powerhouse MacGuff, with headquarters in Paris, is using proprietary artificial intelligence tools, in particular Face Engine and Body Engine, in a broad range of VFX projects.

Current projects in the pipeline include Season 2 of Lupin for Netflix, Htel du temps for France Tlvisions, and Christian Carions Une belle course, starring Dany Boon. The studio also used AI tools in ric Rochants political thriller series The Bureau.

Htel du temps is a perfect example of the power of Face Engine since it brings historic figures back to life, such as late actor Jean Gabin and Princess Diana, to be interviewed by hard-hitting French journalist Thierry Ardisson.

MacGuff has an in-house R&D department that has been developing proprietary AI tools by mixing open-source software with proprietary code. The AI developments are being overseen by co-founder and joint director Rodolphe Chabrier and MacGuffs veteran VFX supervisor Martial Vallanchon.

MacGuff recently received a 200,000 euros ($230,000) grant from Frances CNC to expand its AI engine, as part of the CNCs $11.4 million technological modernization scheme launched in 2021, which has provided support for 20 French studios and digital post-production companies.

Our AI tools can make people look younger and older, or even bring people back to life! explains Philippe Sonrier, MacGuffs other co-founder and joint director. We were the first studio to develop these tools in Europe. They deliver new narrative options and the chance to make more complex characters.

Sonrier adds: AI is totally different from the method that we have known for the past 30 years, primarily based on complex and time-consuming synthesis methods [modeling, rigging, motion capture, photoreal rendering]. AI brings elements of reality in effects. Its amazing how it makes the images more natural. For example, you can film the movements of an actor and a dancer and then merge the two. Its going to revolutionize our industry.

MacGuff was founded in Paris in 1986. In mid-2011 it split into two companies. Universal bought the animation department, renamed as Illumination MacGuff, run by Jacques Bled.

Sonrier is also co-president of FranceVFX, the French visual effects vendors association, created in 2017, which represents 12 studios: MacGuff, BUF, Digital District, Mikros Image, Trimaran, Solidanim, The Yard, Autre Chose, Les Androds Associs, Reepost, La Plante Rouge and D-Seed.

FranceVFX is a lobby for VFX interests and also serves as a liaison mechanism between the participating members. It has facilitated joint cooperation on more ambitious VFX projects.

One recent example was Martin Bourboulons historical drama Eiffel, with 560 VFX shots made by Buf, MacGuff and CGEV, for which the overall VFX supervisor was Olivier Cauwet. Major VFX work is also being developed for Bourboulons upcoming The Three Musketeers DArtagnan and The Three Musketeers Milady, a $85 million two-part saga based on Alexandre Dumas masterpiece.

Collaboration on VFX projects between various studios is a new model for France that has been tested successfully in the U.S., Canada and the U.K., explains Sonrier. It permits us to be more secure. If one vendor has a problem with a project, we can help each other out. The position of the VFX supervisor is emerging in France.

MacGuff works on major international projects as well as French films and series. It produced VFX work on Julia Ducournaus 2021 Cannes Palme dOr winner, Titane, including the CGI sequences that created the car baby.

Our culture is inevitably very French, explains Sonrier. We like to be very close to the creative decisions and become involved in each project as soon as possible. Thats part of our DNA. Titane is a good example. Initially the director tried out animatronics solutions but wasnt happy with them. We used CGI to create the car baby. Its something wed previously tried out in 2006 when creating a fetus for the French documentary Lodysse de la Vie by Nils Tavernier.

VFX work is always very risky in both creative and financial terms, says Sonrier. This is particularly true in the French tradition, because of the status of the director as the auteur and supreme decision-maker.

For major international films and series, Sonrier considers that it is easier to lock down the logistics, but sometimes at the cost of becoming more like a factory pipeline. MacGuff has forged a strong relationship with Netflix, which was cemented by its VFX work on its gentleman thief series Lupin. Another major VFX job produced for Netflix was Alexandre Ajas 2021 survival thriller Oxygen, where the VFX work alone was budgeted at over 1 million ($1.14 million).

MacGuff is now working on a major international series, which involves coordination between several VFX studios. It is also working on a major animation project between France, Belgium and Canada, and an ambitious French robot-themed project that will begin lensing in mid-2022.

More international projects are coming to France in the wake of the change introduced in 2020 to Frances Tax Rebate for International Production (TRIP) scheme, which now offers a 40% rebate on all eligible expenses including for live action spends that are not VFX related for international projects whose VFX expenses surpass 2 million ($2.27 million) spent in France.

High-profile projects attracted by this change include Ridley Scotts 14th century period epic The Last Duel, with VFX work done by Mikros Image. Another example is the 16th-century Medici drama Serpent Queen, produced for Starz by Lionsgate Television and 3 Arts Entertainment.

Smaller-scale international projects can apply for other support mechanisms such as the CVS scheme for ambitious visual and sound projects. The CVS scheme was used on the Lithuanian-French production Vesper Seeds, for which the VFX work was shared with Mathematic, Mikros Liege and Excuse My French.

This dystopian pic, set after the collapse of the Earths ecosystem, is the third feature from Lithuanian helmer Kristina Buozyte and French helmer Bruno Samper, who co-directed a short segment for the 2014 American horror anthology ABCs of Death 2.

MacGuff is also producing VFX work for the documentary Corridor of Power, produced by Dror Moreh, having previously worked on other projects produced by him, such as Oscar-nominee The Gatekeepers and The Human Factor, which won the Grand Prix at Fipadoc 2020.

Other recent French productions handled by the studio include Nicolas Girauds Lastronaute, starring Giraud and Mathieu Kassovitz.

MacGuff is a long-time collaborator of French-Argentine helmer Gaspar No and did the VFX work on his latest feature film, Vortex, in terms of stabilization of the frames, rotations, small morphs, retiming and adjustments to the split screen images.

The studio also provides VFX for documentaries, such as La rafle des notables, produced by Victor Roberts 10.7 Productions, based on Anne Sinclairs book about French concentration camps during World War II. It is also working on a docufiction from 10.7 Productions The Last Secrets of Humanity, directed by Jacques Malaterre, about the prehistoric period in China, including VFX work to recreate prehistoric animals, jointly produced by Mikros and MacGuff.

The company is developing VR/AR and immersive projects, primarily commercials, via its subsidiary Small.

Excerpt from:
MacGuffs Philippe Sonrier on How Artificial Intelligence Tools Will Revolutionize the VFX Industry - Variety

Artificial intelligence and drones are useful for transforming Indian policing in 2022

AI can be a powerful tool for law enforcement and help in addressing many types of crimes. It can help law enforcement to optimize their resources in specific areas and at specific times, to cover as much ground as possible with the same or even fewer resources. Drones with sensors, for instance, can also be used to detect illegal movements such as illegal border crossings, human traffickers, and vessels illegally fishing. Location is a powerful piece of information for AI systems. In India too, artificial intelligence tools are increasingly being put to use. The police departments use of technology is not just limited to facial recognition. It has also been using tools for predictive policing such as crime mapping, analytics, and predictive system, a predictive system that analyses data from past and current phone calls to police hotlines to predict the time and nature of criminal activities in hotspots across the city.

When the respondents were asked about the lack of an Indian police force, the majority of them i.e. 45.8% of 251 respondents, voted for relationship between police and the public as the key factor lacking in the Indian police force. Out of the total, 27.1% respondents selected police accountability. 13.5% of the total respondents selected overburdened force and vacancies, while 11.5% think the process involved in investigation of crime is a lacking factor for the Indian police. The remaining 2.1% think its the infrastructure where Indian police lack.

public

There are numerous solutions for the Indian police force that can make it better. From the survey, it is observed that 63% of 251 respondents think that limiting the political executives power of superintendence over police forces will be the best solution for the Indian police force. 15.2% responded to the specialized investigating units as the key solution to the Indian police force. 11.6% of the respondents selected the Community policing model while the rest 10.2% selected Outsourcing and redistributing functions as the best solution for the Indian police force.

From the survey, it is found that 56% of the total respondents think that AI cops must be given a chance over the regular police force, 29.2% think that AI cops may be given a chance, while the remaining 14.6% think that AI cops should not be given a chance over the regular police force.

Share This ArticleDo the sharing thingy

About AuthorMore info about author

Analytics Insight is an influential platform dedicated to insights, trends, and opinions from the world of data-driven technologies. It monitors developments, recognition, and achievements made by Artificial Intelligence, Big Data and Analytics companies across the globe.

Read the original:
The Future of Indian Policing with Artificial Intelligence in 2022 and Beyond - Analytics Insight

We have accepted the use of artificial intelligence (AI) in complex processes from health care to our daily use of social media often without critical investigation, until it is too late. The use of AI is inescapable in our modern society, and it may perpetuate discrimination without its users being aware of any prejudice. When health-care providers rely on biased technology, there are real and harmful impacts.

This became clear recently when a study showed that pulse oximeters which measure the amount of oxygen in the blood and have been an essential tool for clinical management of COVID-19 are less accurate on people with darker skin than lighter skin. The findings resulted in a sweeping racial bias review now underway, in an attempt to create international standards for testing medical devices.

There are examples in health care, business, government and everyday life where biased algorithms have led to problems, like sexist searches and racist predictions of an offenders likelihood of re-offending.

AI is often assumed to be more objective than humans. In reality, however, AI algorithms make decisions based on human-annotated data, which can be biased and exclusionary. Current research on bias in AI focuses mainly on gender and race. But what about age-related bias can AI be ageist?

In 2021, the World Health Organization released a global report on aging, which called for urgent action to combat ageism because of its widespread impacts on health and well-being.

Ageism is defined as a process of systematic stereotyping of and discrimination against people because they are old. It can be explicit or implicit, and can take the form of negative attitudes, discriminatory activities, or institutional practices.

The pervasiveness of ageism has been brought to the forefront throughout the COVID-19 pandemic. Older adults have been labelled as burdens to societies, and in some jurisdictions, age has been used as the sole criterion for lifesaving treatments.

Digital ageism exists when age-based bias and discrimination are created or supported by technology. A recent report indicates that a digital world of more than 2.5 quintillion bytes of data is produced each day. Yet even though older adults are using technology in greater numbers and benefiting from that use they continue to be the age cohort least likely to have access to a computer and the internet.

Read more: Online arts programming improves quality of life for isolated seniors

Digital ageism can arise when ageist attitudes influence technology design, or when ageism makes it more difficult for older adults to access and enjoy the full benefits of digital technologies.

There are several intertwined cycles of injustice where technological, individual and social biases interact to produce, reinforce and contribute to digital ageism.

Barriers to technological access can exclude older adults from the research, design and development process of digital technologies. Their absence in technology design and development may also be rationalized with the ageist belief that older adults are incapable of using technology. As such, older adults and their perspectives are rarely involved in the development of AI and related policies, funding and support services.

The unique experiences and needs of older adults are overlooked, despite age being a more powerful predictor of technology use than other demographic characteristics including race and gender.

AI is trained by data, and the absence of older adults could reproduce or even amplify the above ageist assumptions in its output. Many AI technologies are focused on a stereotypical image of an older adult in poor health a narrow segment of the population that ignores healthy aging. This creates a negative feedback loop that not only discourages older adults from using AI, but also results in further data loss from these demographics that would improve AI accuracy.

Even when older adults are included in large datasets, they are often grouped according to arbitrary divisions by developers. For example, older adults may be defined as everyone aged 50 and older, despite younger age cohorts being divided into narrower age ranges. As a result, older adults and their needs can become invisible to AI systems.

In this way, AI systems reinforce inequality and magnify societal exclusion for sections of the population, creating a digital underclass primarily made up of older, poor, racialized and marginalized groups.

We must understand the risks and harms associated with age-related biases as more older adults turn to technology.

The first step is for researchers and developers to acknowledge the existence of digital ageism alongside other forms of algorithmic biases, such as racism and sexism. They need to direct efforts towards identifying and measuring it. The next step is to develop safeguards for AI systems to mitigate ageist outcomes.

There is currently very little training, auditing or oversight of AI-driven activities from a regulatory or legal perspective. For instance, Canadas current AI regulatory regime is sorely lacking.

This presents a challenge, but also an opportunity to include ageism alongside other forms of biases and discrimination in need of excision. To combat digital ageism, older adults must be included in a meaningful and collaborative way in designing new technologies.

With bias in AI now recognized as a critical problem in need of urgent action, it is time to consider the experience of digital ageism for older adults, and understand how growing old in an increasingly digital world may reinforce social inequalities, exclusion and marginalization.

Continued here:
Artificial intelligence can discriminate on the basis of race and gender, and also age - The Conversation CA

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:

See more here:
Teaching Stream Faculty in Artificial Intelligence job with KING ABDULLAH UNIVERSITY OF SCIENCE & TECHNOLOGY | 278533 - Times Higher Education...

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