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AI is already building a more resilient post-pandemic world - Watson Blog

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For some organizations, AI tools may have been perceived as "nice-to-have" technologies prior to 2020. In a 2019 IBM/Morning Consult survey of businesses, 22% of respondents worldwide reported they are not currently using or exploring the use of AI. But in a future characterized by uncertainty, only organizations that embrace the most advanced AI tools will be able to weather future storms. The COVID-19 pandemic remains an immediate threat, but all kinds of organizations are looking ahead to build resilient systems that can better withstand future pandemics, as well as natural disasters, cyberthreats, and other destabilizing scenarios. The current crisis is an opportunity to examine the performance of the technological systems that we use to manage the various aspects of human existence.


Council Post: The Technology Pillars Of Digital Singularity And Opportunities Created For Humanity

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We have an opportunity to lead revolutionary change -- to disrupt business models, solve global and economic challenges and fundamentally transform human experiences. It enables us to extend not only ourselves and our abilities, but also our connection with the world. Consider the current global Covid-19 pandemic and the way the world shifted online in an instant. Despite the closure of physical borders, we have become more open. Technology has created a boundaryless global community, allowing us to instantly connect and communicate, irrespective of geography.


Teaching Neural Networks to be Humans

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The Fourth Industrial Revolution (Industry 4.0) has become a framework related challenge for scientific researchers. Industry 4.0 is principally portrayed by evolution and convergence of nano-, bio-, information and cognitive technologies to upgrade great transformations in economic, social, cultural and humanitarian spheres. Experts managing advancement and introduction of the sixth technological paradigm technologies decide by and large whether our nation can ride the influx of Industry 4.0 developments. For as long as 25 years, the creators have been building up the concept of systematic computer simulation training at schools and educators' training colleges. The idea thoughts have been summed up and introduced in the course reading.


Intel Lab Transforms Your Phone into a Robot for $50

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Have you ever dreamed of owning a personal robot? Boston Dynamic's doglike Spot would be a great choice were it not for the hefty US$74,500 price tag. But don't worry -- a couple of Intel Labs researchers have proposed a novel method for building a robot called "OpenBot" on just a US$50 budget. Complete design and implementation information has been open-sourced, all you need to supply is the brain and sensory system -- your smartphone. Inspired by projects such as Google Cardboard that plug standard smartphones into cheap physical enclosures, the researchers developed and validated a design for a mobile robot that leverages a smartphone for sensory and computational abilities, communication channels and access to a software ecosystem. The robot is capable of mobile navigation with real-time onboard sensing and computation, and can perform tasks such as person-following and real-time autonomous navigation in unstructured environments.


Implement Artificial Intelligence using Artificial Intelligence – IAM Network

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Transforming a business into one controlled by Artificial Intelligence (AI) requires everybody's interest and commitment. Despite the fact that transformation requires significant investment, various strategies can start democratizing AI immediately. It has often been said that crises uncover real character, both in people and in companies. Crises force companies to reevaluate how they work and are often the source of enduring change and development. The Covid-19 pandemic is a humanitarian crisis more huge than any recently experienced.


Yale researchers develop AI technology for adults with autism

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Researchers from several American universities are collaborating to develop artificial intelligence based software to help people on the autism spectrum find and hold meaningful employment. The project is a collaboration between experts at Vanderbilt, Yale, Cornell and the Georgia Institute of Technology. It consists of developing multiple pieces of technology, each one aimed at a different aspect of supporting people with Autism Spectrum Disorder (ASD) in the workplace, according to Nilanjan Sarkar, professor of engineering at Vanderbilt University and the leader of the project. "We realized together that there are some support systems for children with autism in this society, but as soon as they become 18 years old and more, there is a support cliff and the social services are not as much," Sarkar said. The project began a year ago with preliminary funding from the National Science Foundation. The NSF initially invested in around 40 projects, but only four -- including this one -- were chosen to be funded for a longer term of two years.


IBM Joins Effort by UN and Vatican to Use Ethical AI in Fight Against Hunger

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The Vatican's Pontifical Academy for Life, which began the year by urging the ethical development and application of artificial intelligence (AI), has announced an effort to use technology to fight world hunger, which has worsened during the pandemic. The Vatican institution, in collaboration with IBM, Microsoft and the UN Food and Agriculture Organization, or FAO, is encouraging governments, nonprofits and corporations to assure that technology is used to feed everyone, and to make farmers' lives more efficient and productive. In its quest to assure the transparent, responsible and inclusive use of AI, the Vatican and FAO are pushing for solutions in agriculture that will benefit not just the well off, but also the poor. "We need to face the biggest challenges on the planet," said John E. Kelly III, executive vice president of IBM. Kelly, who participated in the FAO and Pontifical Academy's Sept. 24 virtual conference announcing the effort against hunger, was one of the signers of the Vatican's call for AI ethics in February. The Vatican's effort to promote ethical AI for social good includes a new program to use digital technology to ensure a more sustainable and efficient global food supply.


Machine learning approaches classify clinical malaria outcomes based on haematological parameters

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Background: Malaria is still a major global health burden, with more than 3.2 billion people in 91 countries remaining at risk of the disease. Accurately distinguishing malaria from other diseases, especially uncomplicated malaria (UM) from non-malarial infections (nMI) remains a challenge. Furthermore, the success of rapid diagnostic tests (RDT) is threatened by Pfhrp2/3 deletions and decreased sensitivity at low parasitemia. Analysis of haematological indices can be used to support identification of possible malaria cases for further diagnosis, especially in travelers returning from endemic areas. As a new application for precision medicine, we aimed to evaluate machine learning (ML) approaches that can accurately classify nMI, UM and severe malaria (SM) using haematological parameters.


Microsoft unveils updates across Azure Cognitive Services and Azure Machine Learning

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During its Ignite 2020 conference, which kicked off virtually this morning, Microsoft announced updates to Azure Cognitive Services and Azure Machine Learning aimed at streamlining business processes during the coronavirus pandemic. The company also launched two features in Azure Cognitive Search -- Private Endpoints and Managed Identities -- plus enhancements to Bot Framework Composer and the broader Azure Bot Service. "We're seeing AI touching every business across the planet, and so one of the key focuses we have with Azure Machine Learning is to provide our customers with the tools to really simplify the ability to create new models because we know they're going to need them in every area of their business," Microsoft corporate vice president Eric Boyd told VentureBeat in a phone interview. "This continues to be a key theme for us -- how we will really help our customers, enable more of their developers, and even more of their data analysts to build machine learn models and apply them in all aspects of their business." Private Endpoints in Cognitive Search, which is generally available as of today, allow a client on a virtual network to access data in an index over a private link.


Deep learning for next-generation sleep diagnostics

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Currently, the diagnosis of sleep disorders relies on polysomnographic recordings with a time-consuming manual analysis with low reliability between different manual scorers. Throughout the night, sleep stages are identified manually in non-overlapping 30-second epochs starting from the onset of the recording based on electroencephalography (EEG), electro-oculography (EOG), and chin electromyography (EMG) signals which require meticulous placement of electrodes. Moreover, the diagnosis of many sleep disorders relies on outdated guidelines. When assessing the severity of obstructive sleep apnea (OSA), the patients are classified based on thresholds of the apnea-hypopnea index (AHI), i.e. the number of respiratory disruptions during sleep. These thresholds are not fully based on solid scientific evidence and remain the same across different measurement techniques.