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Infections and Infectious Diseases


Artificial Intelligence-based Security Market is Booming in Upcoming Year

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Global Artificial Intelligence-based Security Market Size, Status and Forecast 2021-2027, Covid 19 Outbreak Impact research report added by Report Ocean, is an in-depth analysis of market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography. It places the market within the context of the wider Artificial Intelligence-based Security market, and compares it with other markets., market definition, regional market opportunity, sales and revenue by region, manufacturing cost analysis, Industrial Chain, market effect factors analysis, Artificial Intelligence-based Security market size forecast, market data & Graphs and Statistics, Tables, Bar & Pie Charts, and many more for business intelligence. Get complete Report (Including Full TOC, 100 Tables & Figures, and Chart). Artificial Intelligence-based Security market is segmented by company, region (country), by Type, and by Application.


Responsible AI and Government: High Time to Open Discussions?

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Recently, Gartner released a series of Predicts 2021 research reports, including one that highlights the serious, wide-reaching ethical and social problems it predicts artificial intelligence (AI) to cause in the next several years. The race to digital transformation and abundance of data has coerced companies to invest in artificial intelligence technologies. And with that, the concept of leveraging responsible AI took central stage in discussions between government, enterprises and other tech purists and critics. A quick search trends shows that the words like "Ethical AI", and "Responsible AI" have gained popularity in the past five years. But what is the reason behind it? Currently, presence of bias in training data for artificial intelligence models and lack of transparency (black box) threaten the possibility of using AI for good.


Why AI Needs the Human Touch in the Post-COVID Service World - insideBIGDATA

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In this contributed article, Nic Ray, CEO of BrandsEye, observes that in a post-Covid world, organizations will need to ensure they are using tools that allow them to go beyond simple keyword matching to find the customer conversation that matters. Digital service should by no means spell the demise of the human touch, on the contrary, it reminds us of its importance.


Global Artificial Intelligence for Healthcare Applications Market : Intel, Nvidia, Google, IBM, Microsoft, General Vision, Enlitic, Next IT, Welltok, Icarbonx, etc. – The Bisouv Network

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The Global Artificial Intelligence for Healthcare Applications market report enumerates highly classified information portfolios encompassing multi-faceted industrial developments with vivid references of market share, size, revenue predictions along with overall regional outlook. The report illustrates a highly dependable overview of the competition isle, with detailed assessment of business verticals. Post a systematic research initiative and subsequent evaluation overview, the global Artificial Intelligence for Healthcare Applications market mimicking its past growth performance is anticipated to strike a flourishing ROI and is therefore more likely to be on the favorable growth curve in the coming years. This versatile report describing the global Artificial Intelligence for Healthcare Applications market has entailed a range of information portfolios that have been segregated into indispensable and additional information streams that have been represented in the form of tables, pie-charts, graphs and the like to align with maximum reader understanding.


Artificial Intelligence: Global scenario versus Indian landscape

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The retail industry has been one of worst-hit industries by the global pandemic and after an initial knee-jerk pause during the lockdowns, we see a sudden spike in retail brands (across categories of products) globally wanting to adopt and embrace digital transformation initiatives. The age-old model of customer service via call-centre's has been disrupted permanently by Covid-19 and moving to AI solutions that can help retail businesses manage both exponential rise in call volumes while maintaining very high service level quality is the new emerging opportunity. It is, therefore, not a surprise that the conversational AI market alone is expected to grow at 32 percent CAGR to $9.4 billion by 2024 according to market research company markets & markets.


How AI can be used for good

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As an IBM master inventor, professor at UC Irvine, and author of "Own the A.I. Revolution: Unlock Your Artificial Intelligence Strategy to Disrupt Your Competition," Sahota is also a lead artificial intelligence adviser to the United Nations and is helping find ways for AI to provide solutions and prevent future pandemics. Even now, AI is being used to create systems that can impact how treatments for COVID-19 are used. One such AI tool was developed at UC Irvine last year to help predict the probability of patients needing ICU care. This involved collecting the data of patients to get common symptoms of the coronavirus as well as how to accelerate treatment and care options. Other examples include AI-powered walking sticks for the blind, tools to help those who can't speak, and health care apps that use a cell phone to detect diabetes, tuberculosis and skin diseases through the camera and microphone.


How do we keep AI safe from adversaries?

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In the era of Artificial Intelligence, there are several security challenges to keep the machine learning model secure from adversaries. The goal of this paper is to find the solutions to keep AI safe from adversaries. The focus will be on the techniques to defence the adversaries using multi-step approaches. I will begin by explaining what is adversarial in AI and what are the intentions. Then I will explain the taxonomy of it along with strategies.


How FireCompass Is Using AI To Automate Ethical Hacking

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The year 2020 was the'worst year on record' for cybersecurity, with almost two thousand data breaches reported in the first three months alone. On the one hand, the pandemic had fast tracked the digital adoption of organisations, on the other, it exposed the fractures in their digital security systems as they scaled. The cybercriminals had a field day with most of the companies opting for remote work in the aftermath of Covid-19. From Twitter and Zoom data breach to Unacademy, Big Basket, EasyJet and Marriott, the data breaches continued to make headlines in 2020. Consequently, the role of cyber resilience gained more criticality.


Council Post: Four Ways AI And Machine Learning Will Drive Future Innovation And Change

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CTO & MD at AX Semantics, the SaaS-based, Natural Language Generation Platform that creates any content, in any language, at any scale. The pandemic brought on economic, logistical and technological challenges on a massive global scale, leaving businesses scrambling to adapt. Amidst the upheaval, businesses turned to video conferencing platforms like Zoom and Google Meet to stay connected. Technologies like artificial intelligence (AI) and machine learning (ML) helped augment human efforts to take on everything from health to cybersecurity. Equally, businesses looked toward strategic execution and technology to remain agile among industry shifts and provide a greater return on investments.


Internet of Things (IoT) and Artificial Intelligence (AI) : Redefining Business

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If you look around yourself, you will find at least one object which is connected to Internet. It might be a smartphone, television, air conditioner, or even door bells. Collection of these things can be called as IoT or Internet of Things. Its ability to collect, share and receive data, via Internet, is transforming everyday objects into smart devices. However, analyzing massive incoming data from countless IoT devices can make the process much complex.