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Man & Machine Podcast Episode 1.13

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In today's episode Dr. Bett and Matt take us onto the frontlines and into the battle with COVID-19. Utilizing X-Rays, A.I. can help determine a positive diagnosis of the disease and reduce the severity of the disease. Can A.I. help us win the war against this pandemic? Only if we let allow it. 


Working with NLP datasets in Python

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In the field of Deep Learning, datasets are an essential part of every project. To train a neural network that can handle new situations, one has to use a dataset that represents the upcoming scenarios of the world. An image classification model trained on animal images will not perform well on a car classification task. Alongside training the best models, researchers use public datasets as a benchmark of their model performance. I personally think that easy-to-use public benchmarks are one of the most useful tools to help facilitate the research process.


How does Big Data Analytics use Machine Learning?

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Big data refers to incredibly broad collections of structured and unstructured data that can not be managed using conventional methods. Big data research can make sense of data by uncovering trends and patterns. Machine learning can accelerate this process by decision-making algorithms. It can categorize incoming data, identify trends, and convert data into insights that are useful for business operations. Machine learning algorithms are useful for gathering, analyzing, and incorporating data for large organizations.


When Does Predictive Technology Become Unethical?

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Machine learning can ascertain a lot about you -- including some of your most sensitive information. For instance, it can predict your sexual orientation, whether you're pregnant, whether you'll quit your job, and whether you're likely to die soon. Researchers can predict race based on Facebook likes, and officials in China use facial recognition to identify and track the Uighurs, a minority ethnic group. Now, do the machines actually "know" these things about you, or are they only making informed guesses? And, if they're making an inference about you, just the same as any human you know might do, is there really anything wrong with them being so astute?


Go Beyond Artificial Intelligence: Why Your Business Needs Augmented Intelligence

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The nasal test for Covid-19 requires a nurse to insert a 6-inch long swab deep into your nasal passages. Now, imagine that your nurse is a robot. A few months ago, a nasal swab robot was developed by Brain Navi, a Taiwanese startup. The company's intent was to minimize the spread of infection by reducing staff-patient contact. So, here we have a robot autonomously navigating the probe down into your throat, and carefully avoiding channels that lead up to the eyes.


How police departments are using facial recognition to identify protesters breaking the law

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Police departments across the country are using facial recognition technology to identify protesters they say are breaking the law. NBC News' Jacob Ward explains how it works.Oct.


Machine Learning set to change dynamics of Indian E-commerce market

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It is no brainer that the e-commerce market has transformed the Indian market like never before. Thanks to factors like rising smartphone penetration, the launch of 4G network, and increasing consumer wealth, analytics-driven customer engagement, and digital payment, the e-commerce sector is on an upward trajectory. It is projected that this industry will surpass the US to become the second-largest E-commerce market in the world by 2034. According to the PWC survey, with Internet penetration expected to almost double to 60% by 2022, the nation is arguably the world's most promising Internet economy, with a rapidly increasing'netizen' population. Further owing to improving data affordability, consumption growth, and newer financial products, the e-commerce market is set to grow, be it across e-tail, travel, consumer services or online financial services.


Artificial intelligence helps classify new craters on Mars – IAM Network

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An innovative artificial intelligence (AI) tool developed by NASA has helped identify a cluster of craters on Mars that formed within the last decade.The new machine-learning algorithm, an automated fresh impact crater classifier, was created by researchers at NASA's Jet Propulsion Laboratory (JPL) in California -- and represents the first time artificial intelligence has been used to identify previously unknown craters on the Red Planet, according to a statement from NASA. Scientists have fed the algorithm more than 112,000 images taken by the Context Camera on NASA's Mars Reconnaissance Orbiter (MRO). The program is designed to scan the photos for changes to Martian surface features that are indicative of new craters. In the case of the algorithm's first batch of finds, scientists think these craters formed from a meteor impact between March 2010 and May 2012. Related: Latest photos from NASA's Mars Reconnaissance Orbiter"AI can't do the kind of skilled analysis a scientist can," Kiri Wagstaff, JPL computer scientist, said in the statement.


Closing The B2B Credit Gap: AI, Machine Learning

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Although the COVID era continues to have an outsized impact on small businesses, frontline lending experts say SMBs have recently begun to catch a break when it comes to getting loans through FinTechs and other non-bank lenders. Ken So, founder and CEO of Flowcast, told PYMNTS that today's $3 trillion worldwide SMB "credit gap" is narrowing because the criteria to secure loans are changing, and increasingly, embracing alternative data sources."For "In contrast, the big banks have gone in the other direction."He said this credit gap has only emerged in the past month or so, but its timing couldn't be better given the dichotomy he sees between big companies that are doing well and small, young companies (as well as certain industries) that are often left struggling with cash flow."Retail,


Artificial intelligence helps classify new craters on Mars

#artificialintelligence

An innovative artificial intelligence (AI) tool developed by NASA has helped identify a cluster of craters on Mars that formed within the last decade. The new machine-learning algorithm, an automated fresh impact crater classifier, was created by researchers at NASA's Jet Propulsion Laboratory (JPL) in California -- and represents the first time artificial intelligence has been used to identify previously unknown craters on the Red Planet, according to a statement from NASA. Scientists have fed the algorithm more than 112,000 images taken by the Context Camera on NASA's Mars Reconnaissance Orbiter (MRO). The program is designed to scan the photos for changes to Martian surface features that are indicative of new craters. In the case of the algorithm's first batch of finds, scientists think these craters formed from a meteor impact between March 2010 and May 2012.