Updated: May 25, 2018:

JD Supra is a legal publishing service that connects experts and their content with broader audiences of professionals, journalists and associations.

This Privacy Policy describes how JD Supra, LLC ("JD Supra" or "we," "us," or "our") collects, uses and shares personal data collected from visitors to our website (located at http://www.jdsupra.com) (our "Website") who view only publicly-available content as well as subscribers to our services (such as our email digests or author tools)(our "Services"). By using our Website and registering for one of our Services, you are agreeing to the terms of this Privacy Policy.

Please note that if you subscribe to one of our Services, you can make choices about how we collect, use and share your information through our Privacy Center under the "My Account" dashboard (available if you are logged into your JD Supra account).

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Your interactions with our Website and Services: As is true of most websites, we gather certain information automatically. This information includes IP addresses, browser type, Internet service provider (ISP), referring/exit pages, operating system, date/time stamp and clickstream data. We use this information to analyze trends, to administer the Website and our Services, to improve the content and performance of our Website and Services, and to track users' movements around the site. We may also link this automatically-collected data to personal information, for example, to inform authors about who has read their articles. Some of this data is collected through information sent by your web browser. We also use cookies and other tracking technologies to collect this information. To learn more about cookies and other tracking technologies that JD Supra may use on our Website and Services please see our "Cookies Guide" page.

We use the information and data we collect principally in order to provide our Website and Services. More specifically, we may use your personal information to:

JD Supra takes reasonable and appropriate precautions to insure that user information is protected from loss, misuse and unauthorized access, disclosure, alteration and destruction. We restrict access to user information to those individuals who reasonably need access to perform their job functions, such as our third party email service, customer service personnel and technical staff. You should keep in mind that no Internet transmission is ever 100% secure or error-free. Where you use log-in credentials (usernames, passwords) on our Website, please remember that it is your responsibility to safeguard them. If you believe that your log-in credentials have been compromised, please contact us at privacy@jdsupra.com.

Our Website and Services are not directed at children under the age of 16 and we do not knowingly collect personal information from children under the age of 16 through our Website and/or Services. If you have reason to believe that a child under the age of 16 has provided personal information to us, please contact us, and we will endeavor to delete that information from our databases.

Our Website and Services may contain links to other websites. The operators of such other websites may collect information about you, including through cookies or other technologies. If you are using our Website or Services and click a link to another site, you will leave our Website and this Policy will not apply to your use of and activity on those other sites. We encourage you to read the legal notices posted on those sites, including their privacy policies. We are not responsible for the data collection and use practices of such other sites. This Policy applies solely to the information collected in connection with your use of our Website and Services and does not apply to any practices conducted offline or in connection with any other websites.

JD Supra's principal place of business is in the United States. By subscribing to our website, you expressly consent to your information being processed in the United States.

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We will make all practical efforts to respect your wishes. There may be times, however, where we are not able to fulfill your request, for example, if applicable law prohibits our compliance. Please note that JD Supra does not use "automatic decision making" or "profiling" as those terms are defined in the GDPR.

Pursuant to Section 1798.83 of the California Civil Code, our customers who are California residents have the right to request certain information regarding our disclosure of personal information to third parties for their direct marketing purposes.

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Some browsers have incorporated a Do Not Track (DNT) feature. These features, when turned on, send a signal that you prefer that the website you are visiting not collect and use data regarding your online searching and browsing activities. As there is not yet a common understanding on how to interpret the DNT signal, we currently do not respond to DNT signals on our site.

For non-EU/Swiss residents, if you would like to know what personal information we have about you, you can send an e-mail to privacy@jdsupra.com. We will be in contact with you (by mail or otherwise) to verify your identity and provide you the information you request. We will respond within 30 days to your request for access to your personal information. In some cases, we may not be able to remove your personal information, in which case we will let you know if we are unable to do so and why. If you would like to correct or update your personal information, you can manage your profile and subscriptions through our Privacy Center under the "My Account" dashboard. If you would like to delete your account or remove your information from our Website and Services, send an e-mail to privacy@jdsupra.com.

We reserve the right to change this Privacy Policy at any time. Please refer to the date at the top of this page to determine when this Policy was last revised. Any changes to our Privacy Policy will become effective upon posting of the revised policy on the Website. By continuing to use our Website and Services following such changes, you will be deemed to have agreed to such changes.

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Continued here:
FTC Provides Guidance on Using Artificial Intelligence and Algorithms - JD Supra

It is clear that the health and social care sectors in the United Kingdom have long been suffering from systematic neglect, and this has predictably resulted in dramatic workforce shortages. These shortages have been exacerbated by the current coronavirus crisis, and will be further compounded by the stricter immigration rules coming into force in January 2021. The Home Office is reportedly considering an unexpected solution to this; replacing staff with tech and artificial intelligence.

To paraphrase Aneurin Bevan, the mark of a civilised society is how it treats its sick and vulnerable. As a result, whenever technology is broached in healthcare, people are sceptical particularly if it means removing that all-important human touch.

Such fears are certainly justified. Technology and AI itself has become fraught with issues: there is a wealth of evidence that points to prove algorithms can become susceptible to absorbing the unconscious human biases of its designers, particularly around gender and race. Even the Home Office has been found using discriminatory algorithms that scan and evaluate visa applications while a similar algorithm utilised in hospitals in the US was found to be systematically discriminating against black people as the software was more likely to refer white patients to care programmes.

Such prejudices clearly present AI as unfit in healthcare. Indeed, technology is by no means a quick fix to staff shortages and should never be used at the expense of human interaction, especially in areas that are as emotionally intensive as care.

However, this does not mean that the introduction of AI into the UK care sector is necessarily a slippery slope to a techno-dystopia. Robotics have already made vital changes in the healthcare sector; surgical robots, breast cancer scanners and algorithms that can detect even the early stages of Alzheimers have proved revolutionary. The coronavirus crisis itself has reinforced just how much we rely on technology as we are able to keep in touch with our loved ones and work from home.

Yet in a more dramatic example of the potential help AI could deliver in the UK, robots have been utilised to disinfect the streets of China amid the coronavirus pandemic and one hospital at the centre of the outbreak in Wuhan outnumbered its doctor workforce with robotic aides to slow the spread of infection.

Evidently, if used correctly, AI and automation could improve care and ease the burden on staff in the UK. The Institute for Public Policy Research even calculated that 30% of work done by adult social care staff could be automated, saving the sector 6 billion. It is important to stress, though, that this initiative cannot be used as a cost cutting exercise if money is saved by automation, it should be put back into the care sector to improve both the wellbeing of those receiving care, and also the working conditions of the carers themselves.

There is much that care robots cannot do, but they can provide some level of companionship, and can serve as assistance with medication prep while smart speakers can remind or alert patients. AI can realistically monitor vulnerable patients safety 24/7 while allowing them to maintain their privacy and sense of independence.

There are examples of tech being used in social care around the world that demonstrate the positive effect that it can have; in Japan specifically, they have implemented the use of a robot called Robear that helps carry patients from their bed to their wheelchairs, a bionic suit called HAL that assists with motor tasks, and Paro a baby harp seal bot that is a therapeutic companion which has been shown to alleviate anxiety and depression in dementia sufferers. Another, a humanoid called Pepper, has been introduced as an entertainer, cleaner and corridor monitor to great success.

It is vital, though, that if automation and AI is to be introduced on a wide scale into the care sector, it must work in harmony with human caregivers. It could transform the care sector for the better if used properly, however the current government does not view it in this way; and the focus on automation is ushered in to coincide with the immigration rules that will prohibit migrant carers from entry. Rolling out care robots across the nation on such a huge scale in the next 9 months is mere blue sky thinking; replacing the fresh-and-blood and hard graft of staff with robots is therefore far-fetched at best, but disastrous to a sector that is suffering under a 110,000 staff shortage at worst. Besides, robots still disappointingly lack the empathy required for the job and simply cannot give the personal, compassionate touch that is so important; they can only ease the burden on carers, and cannot step in their shoes alone.

While in the long term it is possible that automation in the care sector could help ease the burden on staff, and plug gaps as an when it is needed, the best course of action that is currently attainable in order to solve the care crisis is for the government to reconsider just who it classifies as low skilled in relation to immigration as some Conservative MPs have already made overtures towards.

In order to remedy the failing care sector, the government should invest both in home grown talent and relax restrictions on carers from overseas seeking to work in the country. A renovation of the care sector is needed; higher wages, more reasonable hours, more secure contracts, and the introduction of a care worker visa is what is so desperately needed, and if this is implemented in conjunction with support from AI and automation we could see the growing and vibrant care sector for which this country is crying out.

Continued here:
Is artificial intelligence the answer to the care sector amid COVID-19? - Descrier

Updated: May 25, 2018:

JD Supra is a legal publishing service that connects experts and their content with broader audiences of professionals, journalists and associations.

This Privacy Policy describes how JD Supra, LLC ("JD Supra" or "we," "us," or "our") collects, uses and shares personal data collected from visitors to our website (located at http://www.jdsupra.com) (our "Website") who view only publicly-available content as well as subscribers to our services (such as our email digests or author tools)(our "Services"). By using our Website and registering for one of our Services, you are agreeing to the terms of this Privacy Policy.

Please note that if you subscribe to one of our Services, you can make choices about how we collect, use and share your information through our Privacy Center under the "My Account" dashboard (available if you are logged into your JD Supra account).

Registration Information. When you register with JD Supra for our Website and Services, either as an author or as a subscriber, you will be asked to provide identifying information to create your JD Supra account ("Registration Data"), such as your:

Other Information: We also collect other information you may voluntarily provide. This may include content you provide for publication. We may also receive your communications with others through our Website and Services (such as contacting an author through our Website) or communications directly with us (such as through email, feedback or other forms or social media). If you are a subscribed user, we will also collect your user preferences, such as the types of articles you would like to read.

Information from third parties (such as, from your employer or LinkedIn): We may also receive information about you from third party sources. For example, your employer may provide your information to us, such as in connection with an article submitted by your employer for publication. If you choose to use LinkedIn to subscribe to our Website and Services, we also collect information related to your LinkedIn account and profile.

Your interactions with our Website and Services: As is true of most websites, we gather certain information automatically. This information includes IP addresses, browser type, Internet service provider (ISP), referring/exit pages, operating system, date/time stamp and clickstream data. We use this information to analyze trends, to administer the Website and our Services, to improve the content and performance of our Website and Services, and to track users' movements around the site. We may also link this automatically-collected data to personal information, for example, to inform authors about who has read their articles. Some of this data is collected through information sent by your web browser. We also use cookies and other tracking technologies to collect this information. To learn more about cookies and other tracking technologies that JD Supra may use on our Website and Services please see our "Cookies Guide" page.

We use the information and data we collect principally in order to provide our Website and Services. More specifically, we may use your personal information to:

JD Supra takes reasonable and appropriate precautions to insure that user information is protected from loss, misuse and unauthorized access, disclosure, alteration and destruction. We restrict access to user information to those individuals who reasonably need access to perform their job functions, such as our third party email service, customer service personnel and technical staff. You should keep in mind that no Internet transmission is ever 100% secure or error-free. Where you use log-in credentials (usernames, passwords) on our Website, please remember that it is your responsibility to safeguard them. If you believe that your log-in credentials have been compromised, please contact us at privacy@jdsupra.com.

Our Website and Services are not directed at children under the age of 16 and we do not knowingly collect personal information from children under the age of 16 through our Website and/or Services. If you have reason to believe that a child under the age of 16 has provided personal information to us, please contact us, and we will endeavor to delete that information from our databases.

Our Website and Services may contain links to other websites. The operators of such other websites may collect information about you, including through cookies or other technologies. If you are using our Website or Services and click a link to another site, you will leave our Website and this Policy will not apply to your use of and activity on those other sites. We encourage you to read the legal notices posted on those sites, including their privacy policies. We are not responsible for the data collection and use practices of such other sites. This Policy applies solely to the information collected in connection with your use of our Website and Services and does not apply to any practices conducted offline or in connection with any other websites.

JD Supra's principal place of business is in the United States. By subscribing to our website, you expressly consent to your information being processed in the United States.

You can make a request to exercise any of these rights by emailing us at privacy@jdsupra.com or by writing to us at:

You can also manage your profile and subscriptions through our Privacy Center under the "My Account" dashboard.

We will make all practical efforts to respect your wishes. There may be times, however, where we are not able to fulfill your request, for example, if applicable law prohibits our compliance. Please note that JD Supra does not use "automatic decision making" or "profiling" as those terms are defined in the GDPR.

Pursuant to Section 1798.83 of the California Civil Code, our customers who are California residents have the right to request certain information regarding our disclosure of personal information to third parties for their direct marketing purposes.

You can make a request for this information by emailing us at privacy@jdsupra.com or by writing to us at:

Some browsers have incorporated a Do Not Track (DNT) feature. These features, when turned on, send a signal that you prefer that the website you are visiting not collect and use data regarding your online searching and browsing activities. As there is not yet a common understanding on how to interpret the DNT signal, we currently do not respond to DNT signals on our site.

For non-EU/Swiss residents, if you would like to know what personal information we have about you, you can send an e-mail to privacy@jdsupra.com. We will be in contact with you (by mail or otherwise) to verify your identity and provide you the information you request. We will respond within 30 days to your request for access to your personal information. In some cases, we may not be able to remove your personal information, in which case we will let you know if we are unable to do so and why. If you would like to correct or update your personal information, you can manage your profile and subscriptions through our Privacy Center under the "My Account" dashboard. If you would like to delete your account or remove your information from our Website and Services, send an e-mail to privacy@jdsupra.com.

We reserve the right to change this Privacy Policy at any time. Please refer to the date at the top of this page to determine when this Policy was last revised. Any changes to our Privacy Policy will become effective upon posting of the revised policy on the Website. By continuing to use our Website and Services following such changes, you will be deemed to have agreed to such changes.

If you have any questions about this Privacy Policy, the practices of this site, your dealings with our Website or Services, or if you would like to change any of the information you have provided to us, please contact us at: privacy@jdsupra.com.

As with many websites, JD Supra's website (located at http://www.jdsupra.com) (our "Website") and our services (such as our email article digests)(our "Services") use a standard technology called a "cookie" and other similar technologies (such as, pixels and web beacons), which are small data files that are transferred to your computer when you use our Website and Services. These technologies automatically identify your browser whenever you interact with our Website and Services.

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There are different types of cookies and other technologies used our Website, notably:

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The rest is here:
USPTO Rules Artificial Intelligence Cannot Be Named As Inventor for Patent Application - JD Supra

Todays factories are easy to envision as futuristic-seeming hives of automation, where industrial robots mimic the movements and, seemingly, the intentionality of human workers.

Todays robots are not only working faster and more reliably than their human counterparts but also performing tasks beyond human capability altogether, such as microscopically precise assembly. But many of those robots are dumber than they look. That is, they may be more dexterous than humans, but they are programmed to perform a limited range of tasks. Many robots cant safely work in close proximity to humans and literally have to be caged or regulated in ways that safeguard human coworkers.

Artificial intelligence (AI) is just now finding its niche in manufacturing, as the technology matures and costs dropand as manufacturers discover applications for which AI algorithms can make complex decisions. And as it becomes ubiquitous, the future of artificial intelligence in manufacturing is already becoming feasible in emerging markets; showcasing better sensory capabilities; and, off the factory floor, predicting what will be needed and when.

In manufacturing, capital investments are high and profit margins are often thin. Those conditions helped to drive a lot of manufacturing to low-wage countries, where the human-resource costs have been so low that the capital investment in AI and related automation was hard to justify. But rising living standards and wages in places like India have made AI an easier sell. In fact, China is already making significant investments in AI for manufacturing and e-commerce.

And just as US workers have lamented loss of jobs to automation, the same is now happening in Chinese factories. Although many workers will be replaced by robots in the short term, the end game will be to retrain those workers to perform higher-level design, programming, or maintenance tasks. The real driver, however, will be to develop applications for AI in manufacturing that dont just automate tasks, but make entirely new business processes feasiblefor example, custom configuration of products to individual customer requirements.

AI has its roots in the 1950s but only found broad acceptance with the development of machine-learning algorithms that could be loosed on a body of data to discover meaningful patternswithout deliberate programming. Without flexible algorithms, computers can only do what we tell them, says Michael Mendelson, a curriculum developer at the NVIDIA Deep Learning Institute. Many tasks, especially those involving perception, cant be translated into rule-based instructions. In a manufacturing context, some of the more immediately interesting applications will involve perception. This would make factory robots more capable and better able to interact withand take instructions fromhumans.

Machine vision is one of these applications. Devising cameras many times more sensitive than the human eye has been the easy part. What AI adds is the increasingly useful ability to make sense of the images. Landing.ai, a startup formed by Silicon Valley veteran Andrew Ng, focuses on manufacturing problems such as precise quality analysis. It has developed machine-vision tools to find microscopic defects in products such as circuit boards at resolutions well beyond human vision, using a machine-learning algorithm trained on remarkably small volumes of sample images.

Thats a microlevel challenge. A macrolevel problem is training a robot to sense what is going on around it so that it can avoid disruptions or danger. This is analogous to the self-driving-vehicle problem, which is nearing real-world adoption.There is a likelyrole in factories for smart, self-driving forklifts and conveyors to move materials and finished goods around.

Robots often are stationary but are still at risk of crashing into things, or people, wandering into their workspaces. Machine vision or motion sensors can cause robots to stop what they are doing if there is a potential obstruction. But there is increasing demand for truly collaborative robotscobotsthat can work productively with human colleagues. AI is enabling them to take instructions from humans, including novel instructions not anticipated in the robots original programming. For this, robots and humans need a common language, which could increasingly be plain speech. This concept already has been demonstrated at the University of Rochester and at MIT.

As humans, weve got millennia of practice explaining things to each other verbally while written word is a much newer, and often clunkier, technology, Mendelson says. Talking to robots allows us to communicate concepts that we might not be able to as clearly with text.

AI certainly is making robots more capable and easier for humans to collaborate with. But it will have an impact in areas that have nothing to do with robotics. In the supply chain, for example, algorithms can perceive patterns of demand for products across time, geographic markets, and socioeconomic segments while accounting for macroeconomic cycles, political developments, and even weather patterns. The output can be a projection of market demand, which in turn could drive raw material sourcing, human staffing, financing decisions, inventory, maintenance of equipment, and energy consumption.

In manufacturing, AI is also increasingly important in predictive maintenance for equipment, with sensors tracking operating conditions and performance of factory tooling, learning to predict breakdowns and malfunctions, and taking or recommending preemptive actions. In other industries, this is already straightforward, says Som Shahapurkar, director of machine learning at FICO, which has been commercializing AI for more than 40 years. The application has spread across domains, from generating sophisticated consumer email alerts to automobile owners to failure prediction in blades in server farms at Facebook and Google.

Much of the data will come from sensors embedded in the processing equipment not only at the factory but also at suppliers facilities, tracking parts inventories and other front-end inputs and monitoring product-quality issues at distributor locations or retail outlets.

AI can, in fact, provide clues to help manufacturers predict demand before they build products to fill the pipeline. In 2010, informatics professor Johan Bollen and colleagues at Indiana University demonstrated that algorithms could read and interpret sentiment in Twitter feeds precisely enough to accurately predict stock-market movements. Similar sentiment analyses could be used to project demand for products or even specific brands, Bollen says, especially now that consumers are transmitting their sentiments daily by chatting with household AI assistants from Google and Amazon. Much of Bollens recent work has been focused on social-media influence on political opinions, but he has studied consumer behavior, as well.

Still, AIs proponents assert that the technology is only an evolutionary form of automation, an inevitable outcome of the Fourth Industrial Revolution. In the future, AI may be effective at making things, making them better, and making them cheaper. But there is no substitute for human ingenuity in dealing with the unexpected changes in tastes and demandsor in deciding whether to make things at all.

Originally posted here:
Artificial Intelligence (AI) in Manufacturing: A Look at ...

Robots are, in fact, taking over the digital workplace in a good way, for many.PHOTO:Ben Husmann

David Cearley, vice president andGartnerFellow, wrote that promises of artificial intelligence (AI) magically performingintellectual tasks that humans do and dynamically learning as much as humans is "speculative at best."However with 2018 rapidly approaching, AIis clearly on the minds of many businesses. Where are businesses practically applying AI in their digital workplaces?

In October 2017, Cearley noted at theGartner 2017 Symposium/ITxpo in Orlando, FL that Narrow AI currently holds the most promise. Narrow AI is composed of "highly scoped machine-learning solutions that target a specific task (such as understanding language or driving a vehicle in a controlled environment) with algorithms chosen that are optimized for that task," he says. CMSWire's Dom Nicastro spoke with several experts to find some practical use cases of artificial intelligence in the digital workplace.

Chatbots and virtual assistants help us ask our phones and home devices questions. Why not bring this into the workplace setting? That's the thinking behind SAP CoPilot, a digital assistant by SAP designed to help businesses with tasks like purchasing contracts and collaborating with colleagues. Sam Yen, chief design officer at SAP, said in a video interview at SAP TechEd Barcelonathey wanted to do in the enterprise what virtual assistants do for consumers. Questions like, "What's my total spend with vendor X?"can be asked via smartphone app.

SAP goal is to eliminate the need for users to manually interact with multiple work apps to get a job done. SAP CoPilot does this through a virtual human robot powered by artificial intelligence,speech recognition, natural language processing, statistical analysis and machine learning. Users can ask questions and give commands, and SAP CoPilot contextualizes their informal and unstructured speech, analyzes it and then executes actions and presents users with business objects, options and other data.

Business consultancy Deloitteformed a partnership with machine-learning developerKira Systemsto create models that intend to quickly read thousands of complex documents, extracting and structuring textual information for better analysis. David Schatsky, a managing director for Deloitte who analyzes emerging technology and business trends, told CMSWire, companies of all sizes need to review stacks of documents for one reason or another. They look for risks. They look at what kind of contracts they may have with suppliers or counter-parties. AI, he said, now makes it possible to do that kind of work a lot faster and more comprehensively. "It completely changes the way that kind of work is done," he says.

David Schatsky

Traditionally, if a company has 15,000 contracts to be reviewed, an auditor will try to get a representative sample for analysis. With AI partnerships like Deloitte-Kira Systems, natural language processing and machine learning trains the application to recognize the structure of these contracts and to enable it to pick out the key clauses, terms and conditions and the key points within a contract in an automated fashion. "So you leave behind the sort of sampling approach and you get the whole population of documents so you can get much, much better insight and you can lower the risk of missing something," Schatsky said.

Schatsky also shared that it's possible to experiment and keep costs relatively low. Deloitte's playbook was not building AI engines from scratch, but rather a construct based on third party technology that it customized. "There's some pretty low-cost points of entry to experiment there because the big cloud providers are providing basic machine learning in the cloud," he says.

We've all wanted to go back to a recorded call or meeting and find the important talking points without the hassle of trying to guess where something was said. AISense, a Silicon Valley startup founded last year, has released technology that is designed to make voice conversations accessible and searchable through its Ambient Voice Intelligence. The company last month announced it's powering transcription for the Zoom Video Communications platform and is also working to ship a consumer product available in early 2018. It raised a $10 million Series A round last month.

AISense also has in beta an application that integrates with a call-recording smartphone app. It takes recorded calls and, using artificial intelligence, transcribes those calls and curates them for users. Those leveraging the transcribed calls can search for keywords. Users can also search for terms across all their recorded calls.

The integration between AISense and Zoom allows for recorded meetings and transcription.

"This is as about as practical as it gets," says Seamus McAteer, general manager of revenue and partnerships for AISense. Their technology includes automatic speech recognition, speaker identification and separation, speech-and-text sync, deep content search and natural language processing. Userscan see what was said, when and by who and output is shareable. "We believe in a world in the workplace where you can keep a record, when you want, of a conversation. Notes will go away. You can focus on what's being said. We think this can be disruptive in a very good way," says McAteer.

WalkMe, a digital adoption platform, offers an artificial intelligence engine that enables business software to learn about user's individual roles, habits and actions.

Athenahealth uses WalkMe to help customers (doctors and nurses) receive guidance and training on how to use a system. WalkMe integrates with Salesforce, providing personalized guidance to the user on how to create a sales opportunity in the CRM system. It also integrates with a system like Workday by including chat functionality on top, that is designed to guide a user directly to a relevant section.

WalkMe's artificial intelligence engines is designed to help users better grasp business software like Workday.

Bloomin' Brands, a Tampa-based casual dining company that includes 100,000 team members and close to 1,500 restaurants, uses artificial intelligence-driven analytics to help them leverage real-time data on things like equipment, necessary repairs and operator functions. It needs to have restaurant partners, service providers and facilities teams all on the same page, Jon Ahrendt shared in theirBloomin Brands' blog post. Bloomin Brands integratesServiceChannel AI-based automated facilities management technologyinto its facilities management processes for tracking emergencies, costs and for identifying future initiatives.

Niles is a Slack add-on thatlistens and records conversations that happen within the collabortion platform.PPC Protectis an organization that uses Niles often. Every time someone sends a message,it learns, according toMaria Hugh, systems manager, PPC Protect. Users can ask Niles questions, and using AI it will respond with an answer. "What products do we sell? What sizes? How much do we charge? Who's in charge of this department?" Everything is stored in a database and can be recalled in the future. If Niles fails at an answer, users can provide him the right answer so Niles is always up to date. The more you interact and use him the more he learns and gets things right.

Niles, the Slack add-on, in action. Here, he provides the wrong answer by providing the wrong link. AI is always learning.

MESH, a Baton Rouge-based strategic marketing firm, and Not Rocket Science (NRS), a Covington, Louisiana-based software cognitive business solution development firm, have built "Branded Bots," artificial intelligence applications that aim to deliver brand personality through various channels and platforms such as Alexa, Cortana, Siri, IBM Watson, mobile apps, websites and social media. "Our goal is to take a job, order or manufacture from pre-production and proposal through billing with AI technology." said Taylor Bennett, CEO and Founder of MESH. The example they offer is a bot they've developed that focuses on software integration and operations, linking together project management, time tracking and CRM systems.

One user of their technology is Milo Ag, an agricultural company that provides producers access to cognitive solutions, natural language interfaces and blockchain. Milo is their cognitive natural language personal assistant who is an informed expert on trading, options, regulations, compliance, transportation, crop insurance, financing, agronomy, machinery, farm programs, weather, news and more. Milo's goal is to help guide producers and their employees to make the best decisions.

Milo Ag uses AI tech from Rocket Science & MESH to create custom AI/bots for its business.

Werner G. Krebs, Ph.D., CEO of Acculation, a data science software company and consultancy, told CMSWire his company uses data-driven processes to make decisions about content for social media and elsewhere. Data can be used to make social media content decisions and AI and algorithms can actually create the content by themselves, according to Krebs.

The Digital Workplace Experience conference (June 18-20, Chicago) features the latest on artificial intelligence. For more major digital workplace topics, speakers and more, visit http://www.dwexperience.com

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8 Examples of Artificial Intelligence (AI) in the Workplace

What?

CLAIRE is an initiative by the European AI community that seeks to strengthen European excellence in AI research and innovation. To achieve this, CLAIRE proposes the establishment of a pan-European Confederation of Laboratories for Artificial Intelligence Research in Europe that achieves brand recognition similar to CERN.

We believe that artificial intelligence (AI) will fundamentally change the way we live and work. It is also likely to become crucial in addressing societys grand challenges, such as climate, energy and mobility; food and natural resources; health; and inclusive, secure societies.

In addition, AI is a global game changer that has become a major driver of innovation, future growth and competitiveness.

It is sometimes said that the best way to meet the future is to create it. We believe that Europe, with its existing strength across all areas of AI and with its strong universities, research institutions and companies, is in an excellent position to do that. Europe can ensure that many of tomorrows advanced technologies, products, systems and services are European and are based on and reflect European realities, needs and values.

This is particularly important for AI.

If Europe were to fall behind in AI technology, we would be likely to face challenging economic consequences, academic brain drain, reduced transparency, and increasing dependency on foreign technologies, products and values. The CLAIRE initiative presents a proposal for avoiding that.

It is not only Europe that needs AI made in Europe.

The CLAIRE initiative aims to establish a pan-European network of Centres of Excellence in AI, strategically located throughout Europe, and a new, central facility with state-of-the-art, Google-scale, CERN-like infrastructure the CLAIRE Hub that will promote new and existing talent and provide a focal point for exchange and interaction of researchers at all stages of their careers, across all areas of AI. The CLAIRE Hub will not be an elitist AI institute with permanent scientific staff, but an environment where Europes brightest minds in AI meet and work for limited periods of time. This will increase the flow of knowledge among European researchers and back to their home institutions.

HUMANE AI, the FET Flagship Project Proposal for New Ethical and Trustworthy AI Technologies to Enhance Human Capabilities and Empower European Citizens and Society, is a key component of the CLAIRE vision for European excellence in Artificial Intelligence.

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Industry Insights

The global artificial intelligence market size was valued at USD 24.9 billion in 2018 and is anticipated to expand at a CAGR of 46.2% from 2019 to 2025. Significant improvements in commercial aspects of artificial intelligence (AI) advancements and deployment in dynamic artificial intelligence solutions are propelling industry growth. Rapid improvements in high computing power have contributed to the rising adoption of AI and robotics in end-use industries like IT, automotive, healthcare, and manufacturing. Furthermore, the need for recognizing and scrutinizing visual content in order to gain deeper insights is expected to boost the uptake of artificial intelligence technologies over the forecast period.

Machine intelligence is expected to hold immense growth prospects and key players are focusing on developing integrated solutions to include software and hardware. Furthermore, to expand their customer reach, several vendors have collaborated with distributors and end users for product distribution. Increasing prominence of parallel processing applications is leading to growing adoption of intelligence technology in scientific disciplines such as artificial intelligence and data science. Organizations are utilizing AI to extract valuable insights from data for providing innovative products and improving customer experience, thereby increasing revenue opportunities.

Artificial intelligence is gaining rising importance due to its complicated and data-driven applications such as image, face, voice, and speech recognition. The technology offers a significant investment opportunity, as it can be leveraged over other technologies to overcome the challenges of data storage, high data volumes, and high computing power. Rapid adoption of virtual reality (VR) and AI in end-use industries such as retail, healthcare, and automotive is expected to augment market growth. Organizations are making investments to incorporate AI capabilities into their product portfolio. Machine learning offers increasing opportunities for the retail industry by scaling human expertise with its decision support capabilities and real-time learning. The technology enables retailers to provide customized experiences to their customers and is expected to allow a broader range of innovation in the retail industry.

AI has many potential applications in the automotive sector, such as in autonomous driving and Advanced Driver Assistance Systems (ADAS). Neural networks are widely adopted in vehicles for lane detection, facilitating the replacement of expensive sensors. Furthermore, artificial intelligence helps organize large amounts of data collected by IoT sensors and mobile devices to improve the data collection and storage process.

Artificial intelligence hardware includes chipsets such as graphics processing unit (GPU), central processing unit (CPU), application-specific integrated circuits (ASIC), and field-programmable gate array (FPGA). Currently, the artificial intelligence market is dominated by GPUs and CPUs due to their high computing capabilities required for AI frameworks. The segment is projected to grow at a significant rate over the forecast period. AI software solutions include libraries for deploying and designing artificial intelligence applications, such as those for primitives, inference, video analytics, linear algebra, and sparse matrices, and multiple hardware communication capabilities.

Artificial intelligence services include installation, integration, and maintenance and support undertakings. AI service solutions are expected to register the fastest growth rate over the forecast period. Prudent improvements in information storage capacity, high computing power, and parallel processing capabilities have further contributed to the swift uptake of artificial intelligence technology in dynamic end-use verticals. Additionally, the need among enterprises for understanding and analyzing visual content to gain meaningful insights is expected to spur the adoption of artificial intelligence over the forecast period.

The AI market is segmented by core technologies into natural language processing (NLP), machine learning, deep learning, and machine vision archetype. The deep learning technology segment is anticipated to dominate the market in terms of revenue. This technology is gaining prominence on account of its complicated data-driven applications that include text/content, or sound recognition. Deep learning offers lucrative investment opportunities as it helps in overcoming challenges of high data volumes.

Machine learning and deep learning cover major investments in AI. It includes both cognitive applications (including machine learning, tagging, categorization, clustering, filtering, hypothesis generation, question answering, alerting, navigation, and visualization) and AI platforms, which facilitate the development of advisory, intelligent, cognitively enabled solutions. Growing deployment of cloud-based computing platforms and on-premises hardware equipment for the safe and secure restoration of large volumes of data has paved the way for the expansion of the analytics platform. Rising investments in research and development by leading players will also play a crucial role in increasing the uptake of artificial intelligence technologies.

The market for artificial intelligence includes end-use verticals such as healthcare, advertising and media, law, BSFI, retail, automotive and transportation, manufacturing, agriculture, and others. The advertising and media segment dominated the overall market for AI in 2018. However, the healthcare sector is anticipated to gain the leading share by 2025. This segment has been segregated based on use-cases, such as virtual nursing assistants, robot-assisted surgery, dosage error reduction, hospital workflow management, clinical trial participant identifier, preliminary diagnosis, and automated image diagnosis. The BFSI segment includes risk assessment, financial analysis/research, and investment/portfolio management solicitations. Artificial intelligence has witnessed tremendous growth in the recent past due to the need for advancement in the areas of machine translation, object perception, and object recognition.

The landscape of infrastructure and tools for deploying and training of neural networks using machine learning is expected to evolve rapidly. The swift uptake of AI in end-use industries such as retail and business analytics is expected to augment market growth over the next few years. Artificial intelligence technology is extensively deployed by several mobile and online services such as Google Assistant, dialogue and voice recognition of Siri, Microsoft Cortana, image classification in Facebook & Google Photo, and Amazons Alexa. Increasing amount of digital data in the form of speech, videos, and images from different social media sources such as IoT and consumer analytics is driving the need for data mining and analytics.

Based on region, the market is segmented into North America, Europe, Asia Pacific, South America, and Middle East and Africa. In 2018, North America governed the global AI market in terms of revenue in 2018, owing to the presence of leading players in the region, strong technical adoption base, and availability of government funding. Furthermore, rising adoption of cloud services in developed countries such as U.S. and Canada is significantly contributing to the regional market.

In Europe, cloud-based AI deployment is expected to witness significant growth in the coming years due to increasing consumer demand for faster and on-demand access to data and easy document control. Furthermore, several private and public organizations are collecting domain-specific data that comprises issues such as medical informatics, cybersecurity, marketing, national intelligence, and fraud detection. Big data-based AI algorithms help in analyzing such unorganized and unsupervised data by continuously improving each set of data.

Artificial intelligence provides outstanding opportunities for investment firms, companies, and consultants looking for acquisitions or mergers. The persistent need for digital transformation is encouraging mergers and acquisitions at record levels among technical and non-technical AI stake-holding firms. Moreover, several vendors are entering into partnerships with end-use industries to enhance their reach. Key industry participants include Atomwise, Inc.; Lifegraph; Sense.ly, Inc.; Zebra Medical Vision, Inc.; Baidu, Inc.; H2O ai; IBM Watson Health; NVIDIA; Enlitic, Inc.; Google LLC; Intel Corporation; and Microsoft Corporation.

Attribute

Details

Base year for estimation

2018

Actual estimates/Historical data

2014 - 2017

Forecast period

2019 - 2025

Market representation

Revenue in USD Billion, and CAGR from 2019 to 2025

Regional scope

North America, Europe, Asia Pacific, South America, and Middle East & Africa

Country scope

U.S., Canada, Mexico, Germany, U.K., France, China, Japan, India, and Brazil

Report coverage

Revenue forecast, company share, competitive landscape, growth factors, and trends

15% free customization scope (equivalent to 5 analyst working days)

If you need specific information that is not currently within the scope of the report, we will provide it to you as a part of the customization.

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends and opportunities in each of the sub-segments from 2014 to 2025. For the purpose of this study, Grand View Research has segmented the global artificial intelligence market report based on solution, technology, end use, and region:

Solution Outlook (Revenue, USD Billion, 2014 - 2025)

Hardware (HW)

Software (SW)

Services

Technology Outlook (Revenue, USD Billion, 2014 - 2025)

End-use Outlook (Revenue, USD Billion, 2014 - 2025)

Regional Outlook (Revenue, USD Billion, 2014 - 2025)

North America

Europe

Asia Pacific

South America

Middle East & Africa

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Artificial Intelligence Market Size, Share | AI Industry ...

Artificial intelligence has played a central role in the fight against the coronavirus. Cotiviti has leveraged AI to predict COVID-19 hot spots around the country before an outbreak happens.

As the coronavirus continues to spread around the globe, we've seen a surge in the use of cutting edge technologies to track and control the pandemic, especially artificial intelligence. It seems like only a distant memory when artificial intelligence (AI) was being discussed as an emergent "existential threat" to humanity. However, with the rise of a pandemic, we've quickly embraced the ever-expanding capabilities of AI as a part of our first line of defense.

Recently, an AI platform fed mountains of pharmaceutical data and research studies journals determined that a rheumatoid arthritis medication could potentially be used to treat COVID-19 patients. As we reported earlier this month, some companies are deploying surveillance systems harnessing AI to pinpoint potential infections and mitigate the spread of the pandemic.

SEE: Coronavirus: Critical IT policies and tools every business needs (TechRepublic Premium)

One of the tremendous advantages of AI is the ability to absorb databases of information at warp speed. It's simply too labor-intensive (if not virtually impossible) for a human being to review every single study and every clinical trial directly or indirectly related to a medical phenomenon.

"That's how I spend my time between 2 o'clock in the morning and 4 o'clock in the morning, trying to catch up on a lot of the clinical information," explained Dr. Emad Rizk, chairman, president and CEO of Cotiviti.

The healthcare analytics and solution company Cotiviti is now using AI and a mass of health data to predict future coronavirus hot spots around the US before these clusters emerge. During our interview, Rizk expressed his belief that AI and deep learning can greatly benefit mankind, from accelerating treatment to potentially improving current pharmaceuticals, but he does reiterate a sense of caution about the data being fed to the algorithms.

"You have to be careful that the algorithms are not using a small window of data. In other words, using just two to three data elements to come to a conclusion is a lot different than using 100 data elements," Rizk said.

Cotiviti processes patient screening information and medical claims in its Caspian Insights Platform and uses this information to identify trends. The platform leverages machine learning alongside a wide spectrum of healthcare data to illustrate a "longitudinal" view of patient treatment and care outcomes over time.

The platform plays a central role in Cotiviti's recently unveiled COVID-19 Outbreak Tracker. The interactive map provides weekly predictions about potentially hidden hot spots around the US. The map also highlights areas where coronavirus mitigation efforts may be working, illustrating a decreased probability of a hidden outbreak. Cotiviti uses a vast array of medical information including chest X-rays, emergency department visits, CPT codes, ICD-9 codes, and more to pinpoint hotbeds.

For more on mapping, check out our Flipboard magazine, Coronavirus maps

"We're not looking at confirmed cases only, we're looking at leading indicators by using our technology and comprehensive database [to] potentially see anything that might be occurring so we can raise the flag and say [these] ZIP codes look suspicious," Rizk said.

In early March, the company used Caspian data to pinpoint nearly 2 dozen states with signs indicating a potential future coronavirus outbreak. Within two weeks, 80 percent of these predicted hot spots became a reality, according to Cotiviti. Since then the company has refined its algorithm and pinpointed future hot spots with up to 91% accuracy, per Rizk.

New clinical data is available around the clock, and this information can be applied to advance the model as the virus spreads and other hot spots contract. The data will also be closely monitored when it comes to seasonal flu trends and using this information to pinpoint anomalies indicative of potential coronavirus cases. In the coming weeks and months, there will be interesting predictive indicator updates to gauge as cities and states slowly begin to reopen for business.

"When we go to ZIP code X-Y-Z, we can use our model to hone in and begin to see if there was any correlation with opening up that ZIP code to an increase in amplitude and volume of flu-like symptoms using our deep machine learning and our AI incidence," Rizk said.

For this particular crisis, feeding an algorithm the appropriate information to do its task is one challenge. People are also struggling to glean useful insights amid a deluge of seemingly never-ending coronavirus news coverage and, at times, conflicting reports. Rizk concluded our conversation touching on his colleagues and comrades at the forefront of this pandemic and reiterating the importance of taking a comprehensive 360-degree approach to information.

"I have many friends out on the front line serving and doing everything that they can. And we are all trying to get through the bombardment of information out there. Everyone is trying to help. But again, everybody is coming at it from a different lens," he said.

"One angle, you'll only see one angle, not the whole picture," he continued.

Be in the know about smart cities, AI, Internet of Things, VR, AR, robotics, drones, autonomous driving, and more of the coolest tech innovations. Delivered Wednesdays and Fridays

Image: Cotiviti

Originally posted here:
Artificial intelligence is predicting coronavirus outbreaks before they start - TechRepublic

While most countries in the world are fighting exponential growth of coronavirus infections, China seems to have gotten the situation under control.

Thats been largely due to the Chinese governments ability to enforce preventive measures more successfully than Western democracies. Individualism, a patchwork approach and fear of stopping economic growth backfired in the U.S. and some European countries.

An overlooked factor that helped flatten the curve in China: Technology.

Social distancing, contactless transactions, cleaning and gathering diagnostic data have been made possible by automated technologies developed at Chinese companies.

Pudu Technology from Shenzhen employed its repurposed catering robots in more than 40 hospitals across the country. The robots help medical staff deliver supplies and medicine to patients and limit health-care workers exposure.

Another company from Shenzhen, MMC (MicroMultiCopter), used megaphone-equipped drones to patrol the streets, warning groups of people who failed to wear masks to disperse. The drones are capable of spraying disinfectants in public places and measuring individual thermal signatures, helping to reduce the spread of the virus. In addition, the MMC drones monitored traffic, enabling uncongested vehicle movement and faster response rates in case of medical emergencies.

Other technologies have been employed as well. Chengdu city in Sichuan Province armed epidemic-control personnel with high-tech smart helmets that can automatically measure peoples temperature when they enter a five-meter range. The helmet sounds an alarm if anyone has a fever.

If you think that something is missing, youre right. We havent mentioned AI artificial intelligence. Alibaba BABA, -4.04%, the Chinese tech and e-commerce multinational company, has developed AI that allegedly can detect coronavirus infections with 96% accuracy.

Finally, Chinas vast surveillance system is finally being put to a good use: Facial-recognition cameras come equipped with thermal sensors that can detect people with fevers and those not wearing masks.

Mobile apps also play a big role here Tencent TCEHY, -2.98% and Alipay have developed apps that inform users if theyve been in contact with a virus carrier and whether they should stay at home or be allowed in public spaces.

For these apps to work, however, additional personal data need to be provided by the user. Alipays app, which is in use in over 200 cities, classifies people by color codes: Red is for supervised quarantine, yellow is for self-quarantine and green means unrestricted movement.

The lack of transparency of how these codes are generated has already led to much confusion and frustration, which is only amplified by the fact that the data entered in the app are shared with the government and police. The same is true of the surveillance. Privacy was never a big topic in the Peoples Republic of China (PRC), and now the last shreds are being obliterated in the name of public safety. The country may eventually subdue the coronavirus infection, but at what cost?

Still, there are things that we Westerners could learn from the Chinese. Seeing empty streets of European and American cities on the news gives me hope that people are finally realizing this isnt just a flu and that we need to take things seriously.

Tech can help, but this time it plays second fiddle to staying home and abiding by protective measures against the virus. Until a vaccine is approved, this is the best way the curve can be flattened and the burden on health-care professionals can be reduced to a sustainable level. So, until further notice, stay home and stay safe.

Jurica Dujmovic is a MarketWatch columnist.

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How China used robots, drones and artificial intelligence to control the spread of the coronavirus - MarketWatch

The present state of health emergency across the globe has led to a new wave of transformative technologies emerging as a possible solution to contain the epidemic. Bringing an array of fresh opportunities to tackle critical challenges, the revolutionary artificial intelligence is emerging as a prospective saviour of the day.

With new technologies and concepts taking shape every day, is it safe to assume that artificial intelligence (AI) will take centrestage in controlling such pandemics in the future? Yes, it is.

The Indian tech story

In India, the government has already launched an AI-enabled smartphone application called Aarogya Setu, which helps users check if they have crossed paths with patients who have tested positive for the coronavirus. The app uses the phone number of the user, along with the location data of the smartphone and matches his/her movements with the Indian Council of Medical Research (ICMR) data on the backend. The ICMR data already has the movements of patients who have tested positive for the virus.

With Prime Minister Narendra Modi urging innovators to share their ideas with the Union ministry of health and family welfare to help fight the pandemic, Indian startups are also coming up with innovations.

Staqu, a Gurugram-based startup, has launched a unique thermal camera that makes use of advanced technologies such as AI to track potential suspects. Using video analytics, Staqus technology could be a risk-free way to help identify coronavirus suspects as it helps avoid human contact.

India is witnessing a daily increase in the number of cases, and technology can play a crucial role in faster tracking of infections. As the coronavirus is highly contagious, it is necessary to track every individual that the infected person may have met, where such AI-enabled apps can contribute immensely.

AI leading the global fight

According to research firm Gartner, by 2022, smart machines and robots may fill in for some of the highly trained professionals globally. While the report indicates the replacement of some human workforce by robotics, there seems to be a non-anticipated advantage for us in these difficult times where robots can be providing services to infected patients. Thereby, keeping humans away from contracting the dreaded coronavirus.

Robots arent susceptible to the virus, so they are being deployed to complete many tasks such as cleaning and sterilizing and delivering food and medicine to reduce the amount of human-to-human contact. In China, robots are being deployed in the catering industry to serve more than 40 hospitals around the country.

Recently, Canadian AI firm Bluedot was gathering reports from around the world, tracking networks and air passengers to predict places where the virus can next spread. In the present scenario, the need for more secure, fast and efficient processes will merit the implementation of artificial intelligence. A tool built at Boston Childrens Hospital called Healthmap keeps a close eye on social media, procuring informational reports and data about infected cases via online spaces and chatrooms. Furthermore, it transforms data into useful insights displaying and forecasting the diseases hotspots for organizations working to tackle the pandemic, such as the World Health Organization (WHO) and the US Centers for Disease Control and Prevention (CDC).

On the other hand, AI-based solutions from Alibaba research institute ensure proper diagnosis of potential virus patients, paving the way for AI in the medical industry. The AI system from Alibaba, which is supposedly trained with around 5,000 CT scans of coronavirus patients, claims 96% accuracy in differentiating cases of covid-19 and pneumonia viruses. Likewise, Baidu has developed a tool called Linear Fold, slashing the time taken in the detection of coronavirus from 55 minutes to 27 seconds.

AI in the healthcare industry is expected to become a whopping $36.1 billion market by the end of 2025. In fact, startups such as US-based Insilico Medicine have already started using artificial intelligence to rapidly identify molecules that could form the basis of an effective treatment against the coronavirus at the heart of the current outbreak.

In a global pandemic such as covid-19, technologies such as AI and data science have become critical to helping societies effectively deal with the outbreak. From sharing data, fighting misinformation, finding prospective drug molecules to identification, tracking and forecast of covid-19 outbreaks, technology is enabling it all!

Sanjay Gupta is the vice president and India country manager at NXP India Pvt. Ltd.

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Can Artificial Intelligence help rein in pandemics? It seems that it can! - Livemint