Category Archives: Artificial Intelligence

Nijeer Parks was bewildered when he was arrested and taken into custody in February 2019. Apparently, hed been accused of shoplifting and attempting to hit a police officer with a car at a Hampton Inn, as the New York Times reported. But Woodbridge, New Jersey, where the crime had taken place, was 30 miles from his home, and Parks had neither a car nor a drivers license at the time, according to NBC News. Court documents indicated that he had no idea how hed been implicated in a crime he knew he didnt commit until he discovered that the case against him was based solely on a flawed facial-recognition match. According to a December report by the Times, this was the third-known instance of a wrongful arrest caused by facial recognition in the U.S. All three of those victims were Black men.

Algorithms failed Parks twice: First, he was mistakenly identified as the suspect; then, he was robbed of due process and jailed for 10 days at the recommendation of a risk assessment tool used to assist pretrial release decisions. These tools have been adopted by courts across the country despite evidence of racial bias and a 2018 letter signed by groups like the ACLU and NAACP cautioning against their use. At one point, Parks told the Times, he even considered pleading guilty. The case was ultimately dropped, but hes now suing the Woodbridge Police Department, the city of Woodbridge, and the prosecutors involved in his wrongful arrest.

These are the costs of algorithmic injustice. Were approaching a new reality, one in which machines are weaponized to undermine liberty and automate oppression with a pseudoscientific rubber stamp; in which opaque technology has the power to surveil, detain, and sentence, but no one seems to be held accountable for its miscalculations.

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U.S. law enforcement agencies have embraced facial recognition as an investigative aid in spite of a 2018 study from MIT that discovered software error rates ranging from 0.8% for light-skinned men to 34.7% for dark-skinned women. In majority-Black Detroit, the police chief approximated a 96% error rate in his departments software last year (though the company behind the software told Vice they dont keep statistics on the accuracy of its real-world use), but he still refuses a ban.

Artificial intelligence (AI) works by supplying a computer program with historical data so it can deduce patterns and extrapolate from those patterns to make predictions independently. But this often creates a feedback loop of discrimination. For example, so-called predictive policing tools are purported to identify future crime hot spots and optimize law enforcement resource allocation, but because training data can reflect racially disparate levels of police presence, they may merely flag Black neighborhoods irrespective of a true crime rate. This is exactly what Minority Report warned us about.

Princeton University sociologist Ruha Benjamin has sounded the alarm about a new Jim Code, a reference to the Jim Crow laws that once enforced segregation in the U.S. Others have alluded to a tech-to-prison pipeline, making it crystal clear that mass incarceration isnt going away its just being warped by a sophisticated, high-tech touch.

Thats not to say that AI cant be a force for good. It has revolutionized disease diagnosis, helped forecast natural disasters, and uncovered fake news. But the misconception that algorithms are some sort of infallible silver bullet for all our problems technochauvinism, as data journalist Meredith Broussard put it in her 2018 book has brought us to a place where AI is making high-stakes decisions that are better left to humans. And in the words of Silicon Valley congressman Ro Khanna (D-CA), the technological illiteracy of most members of Congress is embarrassing, precluding effective governance.

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Artificial Intelligence in Policing Is the Focus of Encode Justice - Teen Vogue

Canon Medical is expanding the clinical reach of its artificial intelligence programs designed to improve MRI image quality, saying it can now be used in 96% of all scanning procedures.

The companys Advanced intelligent Clear-IQ Engine, or AiCE, aims to sharpen scans taken by lower-dose, 1.5 Tesla MRIs, to bring their image quality up to par with 3.0 Tesla machines.

The system was previously cleared by the FDA for certain brain- and knee-focused indications, using Canon Medicals Vantage Orian 1.5 Tesla system. Now its applications span all joints, as well as cardiac, abdomen, spine and pelvic scans.

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In todays environment, making images easy to read and acquire is more important than ever, and this is the latest demonstration of our commitment to offering accessible AI that clinicians can use to make the greatest impact on patient care, said Jonathan Furuyama, managing director of Canon Medicals MR business unit.

RELATED: Canon gets FDA nod for high-resolution CT system

The expansion follows two recent FDA clearances for Canon Medical in December and January, including an AI-equipped, large-bore CT scanner and software designed to boost 3D MRI imaging times.

The companys Speeder software, also for its Vantage Orian 1.5 Tesla system, was cleared to help accelerate surgical planning and orthopedic applicationsby reconstructing full resolution images from under-sampled data. This allows technicians to perform a scan at least twice as fast, the company said. The software also includes an application to help clinicians quantify fatty liver disease.

The companys Aquilion Exceed large-bore CT system, meanwhile, uses AiCE technology to provide more distinct images with an opening nearly one meter wide, with an extended field-of-view of 90 centimeters.

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Canon Medical expands reach of its MRI artificial intelligence programs - FierceBiotech

TORONTO, Feb. 02, 2021 (GLOBE NEWSWIRE) -- Skinopathy, a Canadian medical company founded in 2020, has filed a provisional patent with the United States Patent and Trademark Office (USPTO) for Artificial Intelligence (AI) and Augmented Reality (AR) technology that will help guide surgeons when performing skin cancer excisions.

Healthcare practitioners will be able to use the AI technology which determines, pixel by pixel, the boundaries of cancerous skin tissue by simply taking a picture with their smartphones. The AR technology will then provide surgeons with an overlay of those boundaries through the screen.

Next level healthcare Cancerous skin tissue can sometimes extend beyond the measurable lesion and is typically unseen to even the most eagle-eyed surgeon.

That is why some surgeons choose to be overly cautious and remove more skin than might be necessary to prevent the need for further surgery, which can lead to visible scarring and other disfigurements. Conversely, it is possible that cancerous tissue remains following an excision due to the vagaries of the human body, quality-of-life considerations, or experience of the surgeon. This can potentially lead to continued growth and additional excisions in the future.

Once ready, surgeons will have access to cutting-edge technology that will lead to more informed medical decisions and significantly reduce the hardships felt by the patient and the strain levied on the healthcare system.

This will revolutionize skin cancer treatment, says Alexander Shevchenko, Lead Engineer at Skinopathy. We are providing surgeons with an additional skin cancer fighting tool they can carry in their pockets every day.

Preventing advanced stages of skin cancer Skin cancer is more prevalent than colon, lung, breast, and prostate cancers combined and typically present in very unspectacular ways.

Moles, skin tags, and rashes are rarely viewed as causes for concern and are often dismissed until the discomfort becomes greater than the hassle of seeing a doctor. But it is during that time of latency where dangerous conditions can fester and become deadly. When people finally take action, they are often subject to long wait times or need to travel hundreds (if not thousands) of kilometres to access physicians in a major urban centre.

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Using this technology, people will be able to take pictures of their skin lesion and get an immediate and accurate analysis that will advise on the severity of their condition and provide online access to healthcare practitioners in a matter of days, sometimes even hours.

This is a tremendous milestone for skin cancer, says Dr. Colin Hong, Co-Founder and Chief Medical Officer of Skinopathy. We are using technology to streamline the medical bureaucracy to ensure no one slips through the cracks.

It now takes weeks, sometimes months, to see a skin cancer specialist, and during that time cancerous tissue can grow rapidly and spread to other organs. Making matters worse is the ongoing COVID-19 pandemic which has added more delays and obstacles.

Geographically agnostic technologySkinopathy is using the same kind of technology used for the Re-Captcha security feature found on many websites. However, instead of using AI to determine the difference between a fire hydrant and a bus, Skinopathy is using it to determine the miniscule differences between a mole and a cancerous lesion.

Using real-world images taken by physicians and beta users using their smartphones, the Skinopathy prototypes have yielded 87% accuracy for nine different skin conditions, such as keratosis, and performed even more impressively for basal cell carcinoma, squamous cell carcinoma, and melanoma with accuracy rates ranging from 87% to 96%.

We are very excited about these results, says Dr. Rakesh Joshi, Lead Data Scientist at Skinopathy. There are very subtle nuances on how skin lesions present on the skin, and our models are able to detect the smallest of variances.

Since the technology being developed is geographically agnostic, it can be deployed anywhere in the world and bring needed medical care to under-serviced regions. You can learn more about the technology here.

Skin cancer facts and statsThe Canadian Skin Cancer Foundation states that 1 in 3 cancers diagnosed worldwide is skin cancer and that they outnumber lung, breast, prostate, and colon cancers combined.

Data from the Public Health Agency of Canada suggests the costs associated with skin and subcutaneous tissue diseases was over 2 Billion Dollars in 2010.

Research suggests there is a skin cancer epidemic in the elderly.

About Skinopathy Founded in 2020, Skinopathy is a medical company creating Artificial Intelligence (AI), Augmented Reality (AR), and automation technology that will ensure people and healthcare practitioners receive convenient, reliable, and State-Of-The-Art skin cancer mitigation tools. Its first service, GetSkinHelp.com, is already helping patients connect with specialists through its virtual platform.

ContactKeith LooCo-Founder & Chief Executive Officer(833) 272-7546 x700keith@skinopathy.com

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Skinopathy Files Provisional Patent for Artificial Intelligence and Augmented Reality Powered Technology that will Guide Skin Cancer Surgeries - Yahoo...

Bingo and AI The changing relation between entertainment and artificial intelligence

Artificial Intelligence has been on the tech agenda for more than two decades now, although its impact on our day-to-day lives is perhaps yet to be fully realized. Perceptions of AIs innovation are broad and have altered over time.

For many, AI is an exciting new tool that will improve the quality of our lives, at home and work, by being able to deliver functions that will save us time and enhance our experiences in the world of leisure and entertainment. But for others, AI is perceived as a threat to our livelihoods. Old-fashioned perceptions push the narrative that technology must be managed and developed slowly or not developed at all to protect our ways of life.

This has contributed to AI receiving only sporadic funding and being dismissed by some as a pipe dream. However, we will discuss the positive impact that AI is having on the world of digital entertainment, and in particular in the world of bingo and online casino gaming.

Although many may not realize AI is already readily utilized as a part of several mainstream digital entertainment experiences. For example, Netflix viewers will receive recommendations of what to watch next based on the technology. AI is used to interpret data and produce an algorithm that displays film and TV suggestions that will likely appeal to the user based on their previous habits. In this instance, AI is helping to deliver a much more bespoke, personalized experience to paying subscribers.

In gaming, AI can be used to set a difficultly level based on the players abilities and can make configuration recommendations to enhance the players experience. Where human guidance is not possible, AI helps to keep new players on track.

Source: Pexels

Other gaming sectors, such as online casino gaming, have contrasting relationships with AI. Some platforms utilize the technology in a similar way to traditional console titles to automatically change personalization. It can also be usedto speed up manualprocesses, such as repeating a previous bet or warning the player against twisting in a game of blackjack when they have a good hand.Others instead use more tried and tested innovations such as random number generators to ensure games are fair.

Some businesses in the casino sector have adopted the technology to try and enhance the experience for players. Sue Dawson from Best New Bingo Sites explains how In real money online gaming, AI can be used for targeting marketing and advertising so that players receive promotional offers that are tailored to their preferences and behavior. For instance, you might receive an offer of free spins for the slot game you play most oftenat the time of day youre most likely to play. The games themselves are strictly regulated, though, and must use verified RNG to ensure that all players have the same chance of winning.

Source: Pexels

As is the case in any area of technology, its fascinating to speculate what the future may hold for AI. Already developers are experimenting with its use in spheres like art and even literature. Art AI Gallery offers images for sale that have been generated by artificial intelligence, while developers have experimented with using AI to write plays, make music, and script films.

Its clear from the evidence that AI is already a major part of many lives, and as the technology behind it advances, its likely that will see further leaps forward taken in the years and decades to come.

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Bingo and AI: The changing relation between entertainment and artificial intelligence - Analytics Insight

Artificial intelligence (AI) is poised to change lives. From fueling medical discoveries to smart collars that can decipher and display the emotions of our household pets, this emerging technology is enabling organisations to innovate. According to IDC[1], by 2025, AI-powered enterprises will see a 100% increase in productivity and new product introduction success rates, higher than those of their non-intelligent peers. By being able to anticipate the market and operational changes with AI, organisations will respond much faster than their competitors. They will be agile enough to adapt to changes in the market and innovate.

Hence, accelerating AI solutions for businesses should be the focus for organizations in India. For example, HPC workloads are becoming more data centric and adding AI technologies to advance the capabilities of traditional HPC modeling and simulation. In the next few years, HPC technologies, such as HPC-enabled machine learning training, will go from experimentation models to production models. As CTOs and CIOs in India look to create an enterprise infrastructure that provides robust performance and scalability for large and highly complex AI models while keeping deployment costs low, the answer may lie in HPC for three key reasons:

Data analytics: Businesses relying heavily on data analytics generate new insights which improve efficiencies and give them a competitive edge. However, when it comes to analysing large sets of unstructured data that are exponentially increasing in volume and velocity, traditional IT infrastructure is often hamstrung due to slow storage speeds. To adapt to significantly larger data sets and compute-intensive analytics processes, researchers are looking to exascale computing systems, capable of performing one quintillion calculations per second. Powered with HPC, these advanced performance systems are expected to have a profound impact in the faster identification of pandemics, discovery of effective medication and indication of hazardous weather conditions before they happen.

Acceleration of AI deployments: According to a study, in India, almost 70% of organisations are currently investing in Artificial Intelligence to deliver better business results. As HPC and AI continue to converge and evolve to involve more use cases across industries, the possibilities are nearly endless. Organisations are increasingly looking for pre-designed and pre-validated solutions to generate value instead of constructing IT infrastructure. To help companies with roadblocks involved in setting up an AI system, large vendors are also beginning to introduce reference architectures together with HPC infrastructure for data scientists and researchers working. With HPC and software combined, launching new AI applications is becoming easier and faster. Technology vendors are helping data scientists focus less on maintaining AI systems but more on experimenting, exploring and uncovering insights. Organizations do not need to walk their AI journey alone. By collaborating and working with end-to-end technology infrastructure providers, organisations can co-design and customise unique HPC infrastructures to meet AI research, development and AI model deployment needs.

Growing support for HPC globally and in India: The business benefits of AI are being increasingly recognised, with infrastructure providers now helping the research community and customers capitalise on HPC, expanding it from a niche market to a broader audience. More than ever, customers and partners have access to guidance from technology vendors on how to kick-start their AI initiatives including design, installation, maintenance and most importantly, delivering tangible business outcomes for their organisations. Organisations are focused on promoting open collaboration, bringing together the wide-ranging experience and knowledge of technology developers, service providers and end-users in a worldwide forum that promotes the advancement of innovative, powerful HPC and AI solutions.

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Harnessing the Power of Artificial Intelligence with High-Performance Computing: Dell Technologies - CRN - India - CRN.in

Trend Spotting

Taking into account the fast-changing fashion trends, it goes without saying that anticipating fashion trends is not only tricky but also a time-consuming task. Manually researching the previously popular styles, social media fashion trends, and customer preferences, analysts were expected to spot the upcoming trends. The guesswork done by the professionals may or may not be ac

curate. Besides the hassles of manual work, spotting fashion trends can also pose cost issues before fashion brands if not forecasted rightly. Instead, if the brands invest in leveraging AI, they can cut down all the problems quickly.

The AI tool, trained with quality and quantity data, will analyze past fashion data, check out the customer demand and preferences, gauge competitors moves, and identify the market trends. After processing the data, the AI tool will give accurate details on trendy styles and designs within minutes. With AI, fashion brands can bolster their apparel business by tracking the latest fashion trends in just minutes, which would otherwise take days or even months.

Realizing the potential of AI in design, many tech giants are already making big moves by integrating the technology for their benefit. For instance, a group of professionals inAmazon developed an AI toolthat is capable of analyzing and learning the images that are entered, and then generating an altogether new fashion design by itself. Besides, the industry behemoth - Amazon - has developed another AI application that can analyze and process the fed pictures, thereby giving a conclusion on whether a particular style will look trendy or not. Not only Amazon, but there are dozens of other such tech giants who have already embarked on their AI journey, streaming their design creation process completely.IBM, in collaboration with Tommy Hilfiger and The Fashion Institute of Technology (FIT) is using AIto empower designers in boosting the pace of the product development lifecycle.

With customers becoming restless, irritated, and grumpy on not receiving quick assistance or service, fashion retailers are faced with constant pressure to offer what customers want almost instantaneously. Several industry giants have already come up with the newest technology-powered applications that promote enhanced customer experience, one that goes beyond personalized ads, notification alerts on price drops, or chatbot assistance. Using this sophisticated technology, fashion brands strive to put customization at the forefront for customers during their buying journey. There areAI-powered personal stylist appsin the market that allow users to browse clothes online or to click pictures of their clothes. Giving these images as inputs, the app will recommend the best style according to the user's body type, complexion, and preferences while keeping the fashion trends in mind. From providing customers with personalized advertisement notifications to alerting them on price drops to clearing their doubts or queries with chatbots to now being a personal stylist and providing instant outfit suggestions, fashion brands can meet their aim ofelevating customer experience with the help of AI. With AI being able to act as both, design assistants for designers and personal stylist for consumers, it is pretty much clear that the impact of the technology is more than what we ever imagined.

The emergence of trend-setting technology, AI, has changed the way businesses carry out their processes. And, the discussion weve had, is a proof of the fact that the apparel industry is no exception. With a majority of big fashion brands already tapping into the benefits and applications of AI, it is undeniable that soon the technology will become mainstream in medium-sized companies and startups also. So, for garment companies, who haven't planned to adopt AI yet, the right time to plan and kick-start their digital transformation journey is today. After all, no one would want to be left behind in the digital race, isnt it?

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How Artificial intelligence is Transforming the Apparel Industry - BBN Times

Pilot-less jetliners may still be far off in the future due to several reasons, public trust in automated systems not being the least of them. However, this does not mean the software technology to support such operations has not developed in leaps and bounds. While there are several start-ups in tech-driven unmanned airborne vehicles, lets take a look at how the two main aircraft manufacturers use artificial intelligence in the quest for safe autonomous flight.

Artificial Intelligence (AI) is a divisive subject. Some herald it as the key solution to everything from Alzheimers and cancer to food shortages and climate change. Others, more pessimistically or dystopically inclined, say it will be the end of humanity or, at the very least, take most of our jobs.

One thing is for certain, though; AI is here to stay, and it will have a massive impact on our everyday lives in the future. Aviation is often critiqued for having been slow on the ball when it comes to AI. However, things have begun to change, and its various applications will transform the industry in the decades to come.

Data-driven sophisticated algorithms will revolutionize everything from ticket pricing, air traffic control, crew and maintenance schedules to aircraft assembly, natural language processing in the cockpit. And, of course, it will have an enormous impact on more advanced technology such as autonomous vision-based navigation or pilot-less planes, if you will.

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A little over a year ago, on January 16th, 2020, Airbus completed the first fully automatic vision-based take-off and landing within the framework of its Autonomous Taxi, Take-Off and Landing (ATTOL) project. Rather than relying on an Instrument Landing System (ILS), the AI-controlled take-off was governed by image-recognition software installed on the aircraft.

Image recognition is softwares ability to identify people, places, objects, etc., in images. You are involved in it every time you respond to a prompt to identify yourself as a human online by clicking on all the images containing a cross-walk, traffic light, or motorcycle. In the video below, it is clearly distinguishable how the software reads the visual input of the aircrafts surroundings to perform the take-off procedure.

The ATTOL project was completed in June last year. However, Airbus has stated that its goal is for autonomous technologies to improve flight operations and overall performance not to reach autonomous flight as a target in itself. Pilots, the planemaker says, will remain at the heart of operations.

Over in the other corner, in December 2020, Boeing completed a series of test-flights exploring how high-performance uncrewed aircraft can operate together controlled by AI using onboard command and data sharing. Aircraft were added one by one over a period of ten days until five operated as an autonomous unit, reaching speeds of up to 167 miles per hour.

The tests demonstrated our success in applying artificial intelligence algorithms to teach the aircrafts brain to understand what is required of it, Emily Hughes, director of Phantom Works, Boeings prototyping arm for its defense branch, said in a statement shared with Vision Systems Design at the time.

With the size, number and speed of aircraft used in the test, this is a very significant step for Boeing and the industry in the progress of autonomous mission systems technology, Hughes continued.

While Decembers test-flights were part of its defense part of the business, Boeing stated that the technologies developed from the program would not only inform its developmental Airpower Teaming System (ATS) but apply to all future autonomous aircraft.

Meanwhile, Boeings subsidiary Aurora Flight Sciences, part of Boeing NeXt, is building smaller autonomous flight vehicles. This includes the Centaur, configured for autonomous flight featuring a detect-and-avoid technology supported by radar.

How soon would you get on a crewless aircraft? Are you excited about the prospects of autonomous flight? What do you consider to be the main issues? Let us know in the comments.

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How Airbus And Boeing Are Using Artificial Intelligence To Advance Autonomous Flight - Simple Flying

BASEL, Switzerland--(BUSINESS WIRE)--Syngenta Crop Protection is collaborating with artificial intelligence (AI) and deep learning company Insilico Medicine to accelerate the invention and development of new, more effective crop protection solutions that protect crops from diseases, weeds and pests, while also protecting ecosystems. By bringing new solutions to farmers faster and more efficiently through innovation, Syngenta will help them meet the ongoing challenges they face, in order to enhance productivity and meet global demand for affordable, quality food.

This collaboration with Insilico Medicine means that Syngenta can harness the immense potential and scope of AI to develop the next generation of sustainable crop protection solutions as part of Syngentas $2bn commitment to innovation and sustainability, said Camilla Corsi, Head Crop Protection Research at Syngenta. This will further transform agriculture by providing farmers around the world with the tools they need to produce healthy, nutritious, affordable and sustainably grown food in the most efficient way, while also minimizing the environmental impact.

Insilico Medicine has a proven track record and has delivered significant advances in pharmaceutical research, using AI and deep learning to design, synthesize and validate new ingredients. The same approach also has the potential to transform the development of new crop protection solutions that help keep plants safe, from planting to harvesting. Working closely with Syngenta, Insilico Medicine will use their AI-powered small molecule generative chemistry technology not only to invent molecules for active ingredients faster, but also actively design molecules that are more sustainable and environmentally friendly.

We are very happy to collaborate with a company that is dedicated to developing safe and sustainable solutions for growers, said Alex Zhavoronkov, PhD, founder, and CEO, Insilico Medicine. Our artificial intelligence is designed from the ground up to produce very precise chemistry to protect human health, while ensuring short-term and long-term safety. This expertise is extremely valuable for crop sciences, and especially so for businesses whose top priority is the safety of their products. Syngenta is a progressive company with many brilliant scientists, and we will be working together to use artificial intelligence for the benefit of agriculture.

Our reputation as a global leader in innovation is built on a foundation of collaboration and our understanding of the challenges faced by growers, Camilla Corsi also noted. Working together with Insilico Medicine, combining our skills, knowledge and technologies, will help ensure that new and more effective crop protection solutions will be in the hands of farmers sooner.

About Syngenta

Syngenta is one of the worlds leading agriculture companies, comprising of Syngenta Crop Protection and Syngenta Seeds. Our ambition is to help safely feed the world while taking care of the planet. We aim to improve the sustainability, quality and safety of agriculture with world class science and innovative crop solutions. Our technologies enable millions of farmers around the world to make better use of limited agricultural resources. Syngenta Crop Protection and Syngenta Seeds are part of Syngenta Group with 49,000 people in more than 100 countries and is working to transform how crops are grown. Through partnerships, collaboration and The Good Growth Plan we are committed to accelerating innovation for farmers and nature, striving for carbon neutral agriculture, helping people stay safe and healthy and partnering for impact.

To learn more visit http://www.syngenta.com and http://www.goodgrowthplan.com

Follow us on Twitter at http://www.twitter.com/Syngenta and http://www.twitter.com/SyngentaUS

About Insilico Medicine

Insilico Medicine develops software that leverages generative models, reinforcement learning (RL), and other modern machine learning techniques for the generation of new molecular structures with specific properties. Insilico Medicine also develops software for the generation of synthetic biological data, target identification, and the prediction of clinical trials outcomes. The company integrates two business models; providing AI-powered drug discovery services and software through its Pharma.AI platform (www.insilico.com/platform/) and developing its own pipeline of preclinical programs. The preclinical program is the result of pursuing novel drug targets and novel molecules discovered through its platforms. Since its inception in 2014, Insilico Medicine has raised over $52 million and received multiple industry awards. Insilico Medicine has also published over 100 peer-reviewed papers and has applied for over 25 patents. Website http://insilico.com/

Data protection is important to us. You are receiving this publication on the legal basis of Article 6 para 1 lit. f GDPR (legitimate interest). However, if you do not wish to receive further information about Syngenta, just send us a brief informal message and we will no longer process your details for this purpose. You can also find further details in our privacy statement.

Cautionary Statement Regarding Forward-Looking Statements

This document may contain forward-looking statements, which can be identified by terminology such as expect, would, will, potential, plans, prospects, estimated, aiming, on track and similar expressions. Such statements may be subject to risks and uncertainties that could cause the actual results to differ materially from these statements. For Syngenta, such risks and uncertainties include risks relating to legal proceedings, regulatory approvals, new product development, increasing competition, customer credit risk, general economic and market conditions, compliance and remediation, intellectual property rights, implementation of organizational changes, impairment of intangible assets, consumer perceptions of genetically modified crops and organisms or crop protection chemicals, climatic variations, fluctuations in exchange rates and/or commodity prices, single source supply arrangements, political uncertainty, natural disasters, and breaches of data security or other disruptions of information technology. Syngenta assumes no obligation to update forward-looking statements to reflect actual results, changed assumptions or other factors.

2021 Syngenta. Rosentalstrasse 67, 4002 Basel, Switzerland. The Syngenta logo are trademarks of a Syngenta Group Company. All other trademarks are the property of their respective owners.

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Syngenta Crop Protection and Insilico Medicine to Harness Artificial Intelligence to Transform Sustainable Product Innovation - Business Wire

Over 40,000 CT scans, MRIs, and x-rays from more than 10,000 patients have been brought together by NHSX throughout the pandemic to create a National COVID-19 Chest Imaging Database (NCCID). Hospitals and universities across the country are using the database to track patterns and markers of COVID-19 in patients, to quickly create treatment plans, and to better understand whether a patient will end up in a critical condition.

TheNCCIDis also helping researchers from universities in University College London, and in Bradford, to developAItools that could help doctors improve the treatment for patients with COVID-19.

Clinicians at Addenbrookes Hospital in Cambridge are developing an algorithm based on theNCCIDdatabase that will help to inform a more accurate diagnosis of patients when they present with potential COVID-19 symptoms without a positive test. This will help clinicians to implement earlier medical interventions, including giving patients oxygen and medication before reaching a critical stage of the illness.

The database can also help clinicians predict the need for additional ICU capacity, enabling the management of beds and staff resource in those settings.

Matt Hancock, Secretary of State for Health and Social Care, said: The use of artificial intelligence is already beginning to transform patient care by making the NHS a more predictive, preventive, and personalised health and care service. It is vital we always search for new ways to improve care, especially as we fight the pandemic with the recovery beyond. This excellent work is testament to how technology can help to save lives in the UK.

Carola-Bibiane Schonlieb, Professor of Applied Mathematics and head of theCambridge Image Analysisgroup at the University of Cambridge, said: TheNCCIDhas been invaluable in accelerating our research and provided us with a diverse, well-curated, dataset of UK patients to use in our algorithm development. The ability to access the data for 18 different trusts centrally has increased our efficiency and ensures we can focus most of our time on designing and implementing the algorithms for use in the clinic for the benefit of patients.

By understanding in the early stages of disease whether a patient is likely to deteriorate we can intervene earlier to change the course of their disease and potentially save lives as a result.

The database is also helping with the development of a national AI imaging platform that will allow for the safe collecting and sharing of data, developingAItechnologies to address a number of other conditions such as heart disease and cancers.

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Artificial Intelligence to transform treatment of COVID-19 patients - Health Europa

It could be argued artificial intelligence (AI) is already the indispensable tool of the 21st century. From helping doctors diagnose and treat patients to rapidly advancing new drug discoveries, its our trusted partner in so many ways.

Now it has found its way into the once exclusively-human domain of love and relationships. With AI-systems as matchmakers, in the coming decades it may become common to date a personalised avatar.

This was explored in the 2014 movie Her, in which a writer living in near-future Los Angeles develops affection for an AI system. The sci-fi film won an Academy Award for depicting what seemed like a highly unconventional love story.

In reality, weve already started down this road.

The online dating industrty is worth more than US$4 billion and there are a growing number of players in this market. Dominating it is the Match Group, which owns OkCupid, Match, Tinder and 45 other dating-related businesses.

Match and its competitors have accumulated a rich trove of personal data, which AI can analyse to predict how we choose partners.

The industry is majorly embracing AI. For instance, Match has an AI-enabled chatbot named Lara who guides people through the process of romance, offering suggestions based on up to 50 personal factors.

Tinder co-founder and CEO Sean Rad outlines his vision of AI being a simplifier: a smart filter that serves up what it knows a person is interested in.

Dating website eHarmony has used AI that analyses peoples chat and sends suggestions about how to make the next move. Happn uses AI to rank profiles and show those it predicts a user might prefer.

Loveflutters AI takes the guesswork out of moving the relationship along, such as by suggesting a restaurant both parties could visit. And Badoo uses facial recognition to suggest a partner that may look like a celebrity crush.

Dating platforms are using AI to analyse all the finer details. From the results, they can identify a greater number of potential matches for a user.

They could also potentially examine a persons public posts on social media websites such as Facebook, Twitter and Instagram to get a sense of their attitudes and interests.

This would circumvent bias in how people represent themselves on matchmaking questionnaires. Research has shown inaccuracies in self-reported attributes are the main reason online dating isnt successful.

While the sheer amount of data on the web is too much for a person to process, its all grist to the mill for a smart matchmaking AI.

Read more: Looking for love on a dating app? You might be falling for a ghost

As more user data is generated on the internet (especially on social media), AI will be able to make increasingly accurate predictions. Big players such as Match.com would be well-placed for this as they already have access to large pools of data.

And where there is AI there will often be its technological sibling, virtual reality (VR). As both evolve simultaneously, well likely see versions of VR in which would-be daters can practice in simulated environments to avoid slipping up on a real date.

This isnt a far stretch considering virtual girlfriends, which are supposed to help people practice dating, have already existed for some years and are maturing as a technology. A growing number of offerings point to a significant degree of interest in them.

With enough user data, future AI could eventually create a fully-customised partner for you in virtual reality one that checks all your boxes. Controversially, the next step would be to experience an avatar as a physical entity.

It could inhabit a life-like android and become a combined interactive companion and sex partner. Such advanced androids dont exist yet, but they could one day.

Read more: Robots with benefits: how sexbots are marketed as companions

Proponents of companion robots argue this technology helps meet a legitimate need for more intimacy across society especially for the elderly, widowed and people with disabilities.

Meanwhile, critics warn of the inherent risks of objectification, racism and dehumanisation particularly of women, but also men.

Another problematic consequence may be rising numbers of socially reclusive people who substitute technology for real human interaction. In Japan, this phenomenon (called hikikomori) is quite prevalent.

At the same time, Japan has also experienced a severe decline in birth rates for decades. The National Institute of Population and Social Security Research predicts the population will fall from 127 million to about 88 million by 2065.

Concerned by the declining birth rate, the Japanese government last month announced it would pour two billion yen (about A$25,000,000) into an AI-based matchmaking system.

The debate on digital and robotic love is highly polarised, much like most major debates in the history of technology. Usually, consensus is reached somewhere in the middle.

But in this debate, it seems the technology is advancing faster than we are approaching a consensus.

Generally, the most constructive relationship a person can have with technology is one in which the person is in control, and the technology helps enhance their experiences. For technology to be in control is dehumanising.

Humans have leveraged new technologies for millenia. Just as we learned how to use fire without burning down cities, so too we will have to learn the risks and rewards accompanying future tech.

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Love in the time of algorithms: would you let your artificial intelligence choose your partner? - The Conversation AU