Daily Archives: June 1, 2020

As AI has grown from niche to mission-critical technology, the companies that enable it have multiplied and in many cases prospered. A good example of that success is DefinedCrowd, which has gone from the Disrupt stage to globe-spanning AI toolkit to the Fortune 500 in just a couple of years. The company just raised a new $50.5 million B round to further fuel its expansion.

DefinedCrowd doesnt make AI, but rather supplies data used to create it, specializing in natural language processing. After all, someone has to vet the 500 different ways you could ask for the weather otherwise it would be much more difficult for machine learning systems to tell what users mean. The same goes for computer vision, sentiment recognition and other domains for which the company creates and sorts data. DefinedCrowd has a paid community hundreds of thousands strong doing this highly necessary but voluminous work.

As AI has worked its way into everything from creating and editing media to enterprise software, theres been no shortage of companies in search of training data.

The demand for data has consistently been growing over the last couple years companies are more and more aware of the impact that data has on their systems, and have been looking for more languages and domains that werent considered five years ago, co-founder and CEO Daniela Braga told TechCrunch.

She emphasized inclusivity, the potential for bias and more multilingual deployments as drivers of that demand. New markets and applications are opening up constantly and entrants need high-quality data to develop consumer-ready products.

This puts us in a very good position, as our data is agnostic and we can work pretty much across all verticals, Braga said.

As evidence this is not simply wishful thinking, the company reported a tremendous 656% increase in revenue year-over-year. Theyve also nearly tripled the size of their workforce in that time to more than 250 people.

Its toward hiring that Braga expects a great deal of the $50 million round to go: got to have the developers to make the products to follow the road map. That means doubling the employee count again.

I asked whether the present pandemic has had a major effect on DefinedCrowds operations or business. Braga noted that she hasnt noticed a significant downturn in the industry, presumably because product development has continued in anticipation of consumer and enterprise needs returning to normal.

We decided to make our business fully remote before lockdown measures were implemented, she explained. Transferring every employee to remote working in a short space of time was challenging; however, considering we were already a global company with four offices in three different countries, the adaptation phase was fairly smooth, and we were able to maintain full speed during the process.

Semapa Next and Hermes GPE were added this round to the increasingly long list of investors, which now includes Evolution Equity Partners, Kibo Ventures, Portugal Ventures, Bynd Venture Capital, EDP Ventures, IronFire Ventures, Amazon Alexa Fund, Sony Innovation Fund and Mastercard.

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AI is more data-hungry than ever, and DefinedCrowd raises $50M B round to feed it - TechCrunch

Stockholm, June 1, 2020 Anoto Group AB (Anoto or the Company) today announces that Anotos education subsidiary Knowledge AI Inc has added Kyunghee University in South Korea as its full subscription customer for its education solution KAIT.

The contract was entered into between Anotos subsidiary Knowledge AI Inc, through its Korean distribution partner Soltworks Co. Ltd., and the Business School of Kyunghee University, a leading university in Seoul, South Korea. Kyunghee Business School will be using KAITs proprietary assessment and testing platform for its 3,000 business school students starting in the second half of 2020.

This deal shows that our product can be used for the higher education segment. In fact, we saw substantial excitement and demand for this type of platform which expands customer diversification. We believe this university platform could become a major revenue contributor in the near future, says Joonhee Won, CEO of Knowledge AI Inc.

For further information, please contact:

Johannes Haglund, Chief of Staff

For more information about Anoto, please visit http://www.anoto.comor emailir@anoto.com

This information is information that Anoto Group AB (publ) is obliged to make public pursuant to the EU Market Abuse Regulation. The information was submitted for publication, through the agency of the contact person set out above, on June 1, 2020 at 08:00 CET.

About Anoto Group

Anoto is a publicly held Swedish technology company known globally for innovation in the area of information-rich patterns and the optical recognition of those patterns. It is a leader in digital writing and drawing solutions, having historically used its proprietary technology to develop smartpens and the related software. These smartpens enrich the daily lives of millions of people around the world. Now Anoto is a cloud based software solution provider based on its patented dot pattern technology which provides a methodology for accumulating digital big data from analogue inputs. Anoto Cloud includes Anotos four solutions: KAIT the worlds first AI solution for offline education; ACE Anotos new and improved enterprise forms solutions;aDNA Anotos secure interactive marketing solution; and Dr. Watson Anotos biometric authentication and security solution. Anoto is traded on the Small Cap list of Nasdaq Stockholm under ANOT.

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Anoto's subsidiary Knowledge AI Inc expands the customer base for its education solution KAIT by signing a fully paid subscription agreement with a...

Albert Hsiao, M.D., Ph.D., and his colleagues at the University of California San Diego (UCSD) health system had been working for 18 months on anartificial intelligence program designed to help doctors identify pneumonia on a chest X-ray.

When thecoronavirushit the U.S., they decided to see what it could do.

The researchers quickly deployed the application, which dots X-ray images with spots of color where there may be lung damage or other signs of pneumonia. It has now been applied to more than 6,000 chest X-rays, and its providing some value in diagnosis, said Hsiao, director of UCSDs augmented imaging and artificial intelligence data analytics laboratory.

His team is one of several around the country that has pushed AI programs developed in a calmer time into the COVID-19 crisis to perform tasks like deciding which patients face the greatest risk of complications and which can be safely channeled into lower-intensity care.

The machine-learning programs scroll through millions of pieces of data to detect patterns that may be hard for clinicians to discern. Yet few of the algorithms have been rigorously tested against standard procedures. So while they often appear helpful, rolling out the programs in the midst of a pandemic could be confusing to doctors or even dangerous for patients, some AI experts warn.

AI is being used for things that are questionable right now, said Eric Topol, M.D., director of the Scripps Research Translational Institute and author of several books on health IT.

Topol singled out a system created by Epic, a major vendor of electronic health records software, that predicts which coronavirus patients may become critically ill. Using the tool before it has been validated is pandemic exceptionalism, he said.

RELATED:Boston startup using AI, remote monitoring to fight coronavirus

Epic said the companys model had been validated with data from more 16,000 hospitalized COVID-19 patients in 21 healthcare organizations. No research on the tool has been published, but, in any case, it was developed to help clinicians make treatment decisions and is not a substitute for their judgment, said James Hickman, a software developer on Epics cognitive computing team.

Others see the COVID-19 crisis as an opportunity to learn about the value of AI tools.

My intuition is its a little bit of the good, bad and ugly, said Eric Perakslis, Ph.D., a data science fellow at Duke University and former chief information officer at the Food and Drug Administration. Research in this setting is important.

Nearly $2 billion poured into companies touting advancements in healthcare AI in 2019. Investments in the first quarter of 2020 totaled $635 million, up from $155 million in the first quarter of 2019, according to digital health technology funderRock Health.

At least three healthcare AI technology companies have made funding deals specific to the COVID-19 crisis, including Vida Diagnostics, an AI-powered lung-imaging analysis company, according to Rock Health.

Overall, AIs implementation in everyday clinical care is less common than hype over the technology would suggest. Yet the coronavirus crisis has inspired some hospital systems to accelerate promising applications.

UCSD sped up its AI imaging project, rolling it out in only two weeks.

Hsiaos project, with research funding from Amazon Web Services, the University of California and the National Science Foundation, runs every chest X-ray taken at its hospital through an AI algorithm. While no data on the implementation has been published yet, doctors report that the tool influences their clinical decision-making about a third of the time, said Christopher Longhurst, M.D., UCSD Healths chief information officer.

The results to date are very encouraging, and were not seeing any unintended consequences, he said. Anecdotally, were feeling like its helpful, not hurtful.

RELATED:Headlines have touted AI over docs in reading medical images. New review finds evidence is limited

AI has advanced further in imaging than other areas of clinical medicine because radiological images have tons of data for algorithms to process, and more data makes the programs more effective, said Longhurst.

But while AI specialists have tried to get AI to do things like predict sepsis and acute respiratory distressresearchers at Johns Hopkins University recently won a National Science Foundation grantto use it to predict heart damage in COVID-19 patientsit has been easier to plug it into less risky areas such as hospital logistics.

In New York City, two major hospital systems are using AI-enabled algorithms to help them decide when and how patients should move into another phase of care or be sent home.

AtMount Sinai Health System, an artificial intelligence algorithm pinpoints which patients might be ready to be discharged from the hospital within 72 hours, said Robbie Freeman, vice president of clinical innovation at Mount Sinai. Freeman described the AIs suggestion as a conversation starter, meant to help assist clinicians working on patient cases decide what to do. AI isnt making the decisions.

NYU Langone Health has developed a similar AI model. It predicts whether a COVID-19 patient entering the hospital will suffer adverse events within the next four days, said Yindalon Aphinyanaphongs, M.D., Ph.D., who leads NYU Langones predictive analytics team.

The model will be run in a four- to six-week trial with patients randomized into two groups: one whose doctors will receive the alerts, and another whose doctors will not. The algorithm should help doctors generate a list of things that may predict whether patients are at risk for complications after theyre admitted to the hospital, Aphinyanaphongs said.

RELATED:Microsoft launches $40M AI for Health program to accelerate medical research

Some health systems are leery of rolling out a technology that requires clinical validation in the middle of a pandemic. Others say they didnt need AI to deal with the coronavirus.

Stanford Health Careis not using AI to manage hospitalized patients with COVID-19, saidRon Li, M.D., the centers medical informatics director for AI clinical integration. The San Francisco Bay Area hasnt seen the expected surge of patientswho would have provided the mass of data needed to make sure AI works on a population, he said.

Outside the hospital, AI-enabled risk factor modeling is being used to help health systems track patients who arent infected with the coronavirus but might be susceptible to complications if they contract COVID-19.

At Scripps Health in San Diego, clinicians are stratifying patients to assess their risk of getting COVID-19 and experiencing severe symptoms using a risk-scoring model that considers factors like age, chronic conditions and recent hospital visits. When a patient scores 7 or higher, a triage nurse reaches out with information about the coronavirus and may schedule an appointment.

Though emergencies provide unique opportunities to try out advanced tools, its essential for health systems to ensure doctors are comfortable with them, and to use the tools cautiously, with extensive testing and validation, Topol said.

When people are in the heat of battle and overstretched, it would be great to have an algorithm to support them, he said. We just have to make sure the algorithm and the AI tool isnt misleading, because lives are at stake here.

ThisKHNstory first published onCalifornia Healthline, a service of theCalifornia Health Care Foundation.Kaiser Health Newsis a nonprofit news service covering health issues. It is an editorially independent program of the Kaiser Family Foundation, which is not affiliated with Kaiser Permanente.

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Coronavirus tests the value of artificial intelligence in medicine - FierceHealthcare

In January, my coworker received a peculiar email. The message, which she forwarded to me, was from a handful of corporate Walmart employees calling themselves the Concerned Home Office Associates. (Walmarts headquarters in Bentonville, Arkansas, is often referred to as the Home Office.) While its not unusual for journalists to receive anonymous tips, they dont usually come with their own slickly produced videos.

The employees said they were past their breaking point with Everseen, a small artificial intelligence firm based in Cork, Ireland, whose technology Walmart began using in 2017. Walmart uses Everseen in thousands of stores to prevent shoplifting at registers and self-checkout kiosks. But the workers claimed it misidentified innocuous behavior as theft, and often failed to stop actual instances of stealing.

They told WIRED they were dismayed that their employerone of the largest retailers in the worldwas relying on AI they believed was flawed. One worker said that the technology was sometimes even referred to internally as NeverSeen because of its frequent mistakes. WIRED granted the employees anonymity because they are not authorized to speak to the press.

The workers said they had been upset about Walmarts use of Everseen for years, and claimed colleagues had raised concerns about the technology to managers, but were rebuked. They decided to speak to the press, they said, after a June 2019 Business Insider article reported Walmarts partnership with Everseen publicly for the first time. The story described how Everseen uses AI to analyze footage from surveillance cameras installed in the ceiling, and can detect issues in real time, such as when a customer places an item in their bag without scanning it. When the system spots something, it automatically alerts store associates.

Everseen overcomes human limitations. By using state-of-the-art artificial intelligence, computer vision systems, and big data we can detect abnormal activity and other threats, a promotional video referenced in the story explains. Our digital eye has perfect vision and it never needs a day off.

In an effort to refute the claims made in the Business Insider piece, the Concerned Home Office Associates created a video, which purports to show Everseens technology failing to flag items not being scanned in three different Walmart stores. Set to cheery elevator music, it begins with a person using self-checkout to buy two jumbo packages of Reeses White Peanut Butter Cups. Because theyre stacked on top of each other, only one is scanned, but both are successfully placed in the bagging area without issue.

The same person then grabs two gallons of milk by their handles, and moves them across the scanner with one hand. Only one is rung up, but both are put in the bagging area. They then put their own cell phone on top of the machine, and an alert pops up saying they need to wait for assistancea false positive. Everseen finally alerts! But does so mistakenly. Oops again, a caption reads. The filmmaker repeats the same process at two more stores, where they fail to scan a heart-shaped Valentines Day chocolate box with a puppy on the front and a Philips Sonicare electric toothbrush. At the end, a caption explains that Everseen failed to stop more than $100 of would-be theft.

False Positives

The video isnt definitive proof that Everseens technology doesnt work as well as advertised, but its existence speaks to the level of frustration felt by the group of anonymous Walmart employees, and the lengths they went to prove their objections had merit.

In interviews, the workers, whose jobs include knowledge of Walmarts loss prevention programs, said their top concern with Everseen was false positives at self-checkout. The employees believe that the tech frequently misinterprets innocent behavior as potential shoplifting, which frustrates customers and store associates, and leads to longer lines. Its like a noisy tech, a fake AI that just pretends to safeguard, said one worker.

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Walmart Employees Are Out to Show Its Anti-Shoplifting AI Doesn't Work - WIRED

Jheronimus Academy of Data Science, Eindhoven University of Technology, and Tilburg University, together with Utrecht University of Applied Sciences, are creating a Toolkit Artificial Intelligence that should be applicable for the industry. To this end, the public-private partnership CERTIF-AI has been set up, consisting of companies from the high-tech manufacturing industry in addition to the knowledge partners. NWO makes this possible with a four-year subsidy. The toolkit consists of algorithms and methods for industrial applications.

The CERTIF-AI project (Certification of production process quality through Artificial Intelligence) will start on 1 September 2020. The aim is to use the large amounts of data generated by machines and in production processes to certify processes, improve product quality, and identify problems. For the industrial end-users, this means fewer errors in production and therefore lower costs or greater process reliability and therefore a better product or service, the consortium says in an explanatory note. The project is not only academically innovative by applying AI techniques to real-time sensor data, but also JADS and consortium partners contribute to the deployment of AI for concrete industrial applications.

The AI Toolkit is developed and implemented by a research team from JADS, Eindhoven University of Technology, Tilburg University, and Utrecht University of Applied Sciences. Industrial partners Damen Shipyards, Omron, Additive Industries, and VTEC have defined four concrete applications. Sioux Mathware, BrightCape, and UNIT040 are assisting in the implementation of the toolkit together with Hogeschool Utrecht and practical researchers from JADS.

Tim Foreman (Omron) expects the toolkit to deliver efficiency benefits: The Omron IPC is a Build-to-Order product and has thousands of variants. With CERTIF-AI we are automating and integrating the validation process of new variants into the normal production process in order to reduce the delivery time of new variants. Damen Shipyards expects to acquire new knowledge with CERTIF-AI: A more data-driven approach in operational processes is a strategic spearhead for Damen and makes it possible for us to create insights that were not previously possible, says Jasper Schuringa. These insights offer optimization opportunities but also generate additional value for both Damen, the customer, and the customers customer.

According to the initiators, the CERTIF-AI project is a good example of the connecting role that JADS has in the collaboration between the parent universities TU Eindhoven and Tilburg University and the affiliated research institutes such as the Eindhoven AI Systems Institute (EAISI) that focuses, among other things, on the use of AI for high-tech systems.

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Brabant universities designed an AI-Toolkit to support the industry - Innovation Origins

01 Jun 2020 - 8:09

A file photo of Qatar University building.

Qatar Universitys College of Laws Center for Law and Development recently published an article under the title Banking on AI: Mandating a Proactive Approach to AI regulation in the Financial Sector.The best way to encourage a sustainable future in AI innovation in the financial sector is to support a proactive regulatory approach prior to any financial harm occurring. This is what Dr. Jon Truby, Dr. Rafael Brown and Dr. Andrew Dahdal of the Qatar University College of Laws Center for Law and Development, argued in their recent article titled Banking on AI: Mandating a Proactive Approach to AI regulation in the Financial Sector. The article, which was published in Taylor & Francis Financial Markets Review on May 15, 2020, is part of an NPRP grant from the Qatar National Research Fund.The authors discussed the benefits and risks associated with integrating artificial intelligence (AI) into the existing systems and processes of financial institutions. AI for financial institutions offer many benefits such as enhanced fraud detection, more accurate lending and credit assessments, stronger cybersecurity detection, and faster regulatory compliance. However, the authors also emphasize the need to consider AIs inherent risks and threats. They argue that a proactive approach should implement rational regulations that embody jurisdiction-specific rules in line with carefully construed international principles.The authors use a risk-benefit analysis framework to examine three distinct contexts in which AI can be utilized: how financial service providers use AI in relation to their clients, how financial services firms use AI in their compliance efforts, and how regulators use and may use AI in their regulatory efforts.According to the authors, financial intuitions are introducing a plethora of AI-driven financial services, including robo-advising, algorithmic investing and insurance/ credit assessment at a rapid pace and as a first-generation technology. Though governed by existing financial and data protection laws, neither the developers nor the financial institutions have significant legal obligations in any jurisdiction to follow the international principles on AI governance, which in turn have been developed to require accountability, transparency and fairness in the utilisation of AI software in the financial sphere.The authors contemplate it to be prudent and timely for regulators to seriously consider the nature and scope of AI regulation in the financial services sector. They argue that the adoption of rational regulations that encourage innovation whilst ensuring adherence to international principles will significantly reduce the likelihood of development of AI-related risks into systemic problems. To accomplish it efficiently, the article suggests that policymakers intervene early with targeted, proactive but balanced regulatory approaches to AI technology in the financial sector that are consistent with emerging internationally accepted principles on AI governance. To explain attempts to attain such balance, the article provides the analysis of AI regulatory policies in different jurisdictions such as China, India, EU and Japan.Considering that the AI regulation has significant geo-political ramifications, it is contended that it will trigger race for global economic supremacy and will face strong opposition given the stakes at play. Therefore, it is asserted that balancing the risks of AI with the benefits of innovation requires addressing macro and micro level details. Taking account of this, it is proposed that policy makers in individual jurisdictions acknowledge the potential global significance of the sector in formulating their regulatory frameworks.Having provided thorough analysis, the article concludes that in order to avoid distorted and unbalanced outcomes, AI regulation in the financial sector must be implemented in a consistent and balanced manner across all three contexts by taking into consideration the interests of all stakeholders.

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Experts discuss benefits and risks associated with integrating AI - The Peninsula Qatar

The AI Market in Social Media valued at USD 815.33 million in 2019 and is expected to reach USD 3,714.89 million by 2025, recording a CAGR of 28.77%, during the forecast period of 2020-2025

The report discusses many vital industry facets that influence AI in Social Media acutely which includes extensive study of competitive edge, latest technological advancements, region-wise industry environment, contemporary market and manufacturing trends, leading market contenders, and current consumption tendency of the end user. The report also oversees market size, market share, growth rate, revenue, and CAGR reported previously along with its forecast estimation.

The AI in Social Media market is segmented by Technology (Machine Learning and Deep Learning, NLP), Application (Sales and Marketing, Customer Experience Management, Image Recognition, Predictive Risk Assessment), Service (Managed Service, Professional Service).

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https://www.marketinsightsreports.com/reports/08061388713/global-ai-in-social-media-market-size-status-and-forecast-2019-2025/inquiry?Mode=21

North America is expected to have the largest market size in the AI in social media market, while APAC is expected to grow at the highest CAGR during the forecast period. The North American region has shown increased investments in the market. A considerable growth is expected in the region during the forecast period. In North America, the AI in social media technologies is effectively used for various applications, such as sales and marketing, customer experience management, and predictive risk assessment.

AI in Social Media Market Segmentation:

Top leading Manufactures Profiled in AI in Social Media Market Report are:

Google, Facebook, Microsoft, AWS, IBM, Adobe Systems, Baidu, Salesforce, Twitter, Snap, Clarabridge, Converseon, Sprinklr, Unmetric, Isentium, Cluep, Netbase, Spredfast, Synthesio, Crimson Hexagon, Hootsuite, Sprout Social, Vidora, Meltwater, Talkwalker

Market Research Study Focus on these Types:

Machine Learning and Deep LearningNatural Language Processing (NLP)

Market Research Study Focus on these Applications:

Retail and eCommerceBanking, Financial Services, and Insurance (BFSI)Media and AdvertisingEducationPublic UtilitiesOthers

News:

IBM Corporation is set to combine capabilities with Apple Inc. in machine learning, AI and cloud to bring to market two new offerings, IBM Watson Services for Core ML and the IBM Cloud Developer Console for Apple.

Inquire for Discount of AI in Social Media Market Report at:

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How we have factored the effect of Covid-19 in our report:

All the reports that we list have been tracking the impact of COVID-19. Both upstream and downstream of the entire supply chain has been accounted for while doing this. Also, where possible, we will provide an additional COVID-19 update supplement/report to the report in Q3, please check for with the sales team.

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(2020-2025) AI in Social Media Market Insights and Industry Detailed Analysis: Google, Facebook, Microsoft, AWS, IBM, Adobe Systems, Baidu,...