Big Data, Small World: Kirk Borne at TEDxGeorgeMasonU

| May 26, 2016

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Dr. Kirk Borne is a Multidisciplinary Data Scientist and an Astrophysicist. He is Professor of Astrophysics and Computational Science in the George Mason University School of Physics, Astronomy, and Computational Sciences (SPACS)…

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Kernel Analytics

Our everyday actions generate large amounts of data: the things we buy, the trips we make, the people we call, and many others. At Kernel Analytics we believe all this information has the potential to change the world and we want to contribute with our expertise in data analysis and the development of predictive models to make this change happen. We are driven by the will to improve the world and a taste for high quality work.

OTHER ARTICLES

A Tale of Two Data-Centric Services

Article | April 13, 2020

The acronym DMaaS can refer to two related but separate things: data center management-as-a-service referred to here by its other acronym, DCMaaS and data management-as-a-service. The former looks at infrastructure-level questions such as optimization of data flows in a cloud service, the latter refers to master data management and data preparation as applied to federated cloud services.DCMaaS has been under development for some years; DMaaS is slightly younger and is a product of the growing interest in machine learning and big data analytics, along with increasing concern over privacy, security, and compliance in a cloud environment.DMaaS responds to a developing concern over data quality in machine learning due to the large amount of data that must be used for training and the inherent dangers posed by divergence in data structure from multiple sources. To use the rapidly growing array of cloud data, including public cloud information and corporate internal information from hybrid clouds, you must aggregate data in a normalized way so it can be available for model training and processing with ML algorithms. As data volumes and data diversity increase, this becomes increasingly difficult.

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Living upto Learn, Re Learn and Unlearn

Article | March 23, 2021

Learn, re Learn and Unlearn The times we are living in, we have to upgrade ourselves constantly in order to stay afloat with the industry be it Logistics, Traditional business, Agriculture, etc.. Technology is constantly changing our lives the way we used to live, living and will live. Anyone who thinks technology is not their cup of tea then I would say he /she will have no place in the world to live. It’s a blessing or curse on human race, only time will tell but effects are already surfacing in the market in the form of Job cut, poverty, some roles are no longer needed or replaced with. Poor is getting poorer and rich is getting richer. Covid19 has not only brought the curse on human race but it has been a blessing in disguise for Tech giants and E-commerce. Technology not only changing the business but every human’s outlook towards life, family structure, the globalization of talents etc. It is nerve wrenching to imagine just what the world will look like in coming 20 years from now. Can all of us adapt to learn, re learn and unlearn quote? Or we have to depend upon countries/Governments to announce Minimum Wage to sustain our basic needs? Uncertainties are looming as the world is coming closer due to technology but emotionally going far. It’s sad to see children, colleagues communicating via emails and messages in the same home and office. Human is losing its touch and feel. Repercussion to resists of learning, unlearning and relearning can bring down choices to none in the long run. Delay in adapting to change can be increasingly expensive as one can lose their place in a world earlier than one think. From 1992, where fewer people used to have facility of internet around , People used to stay in jobs for life but same people are now not wanted in the jobs when they go for interview as they lack in experience just because they have been doing what they were doing in one job without exposing themselves to the world’s new requirement of learn , re learn and unlearn. Chances of this group, getting a job will be negative. World has thrown different types of challenges to people, community, jobs, businesses , those people used to be applauded for remaining On one job for life ,same group of people are looked differently by corporate firms as redundant due to technology. So should people keep changing jobs after few years to just get on to learn, re learn and unlearn or continue waiting for their existing companies to face challenges and go off from the market? Only time and technology will determine what is store for human race next. According to some of the studies, its shown the longer the delay in adopting technology for any given nation, the lower the per capita income of that nation. It shows extreme reliance on Technology but can all of us adopt to the technology at the same rate as its been introduced to us? Can our children or upcoming next generations adopt technology at same scale? Or future is Either Technology or nothing, in Short Job or Jobless there is no in between option? Stephen Goldsmith, director of the Innovations in Government Program and Data-Smart City Solutions at the John F. Kennedy School of Government at Harvard University, said that in some areas, technological advancements have exceeded expectations made in 2000. The Internet also has exploded beyond expectations. From 2000 to 2010, the number of Internet users increased 500 percent, from 361 million worldwide to almost 2 billion. Now, close to 4 billion people throughout the world use the Internet. People go online for everything from buying groceries and clothes to finding a date. They can register their cars online, earn a college degree, shop for houses and apply for a mortgage but again same question is arising , Can each one of us at the same scale use or advance their skill to use technology or we are leaving our senior generations behind and making them cripple in today’s society? Or How about Mid age people who are in their 50s and soon going to take over senior society , Can they get the job and advance their skill to meet technology demands or learn, unlearn and re learn or Not only pandemic but even Technology is going to make human redundant before their actual retirement and their knowledge, skill obsolete. There should be a way forward to achieve balance, absolute reliance on Technology is not only cyber threat to governments but in long term, Unemployment, Creating Jobs or paying minimum wage to unemployed mass will be a huge worry. At the end of the day, humans need basic and then luxury. Technology can bring ease of doing business, connecting businesses and out flows, connecting Wholesalers to end users but in between many jobs, heads will be slashed down and impact will be dire. Therefore Humans have to get themselves prepared to learn, unlearn and re learn to meet today’s technology requirement or prepare themselves for early retirement.

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Self-supervised learning The plan to make deep learning data-efficient

Article | March 23, 2020

Despite the huge contributions of deep learning to the field of artificial intelligence, there’s something very wrong with it: It requires huge amounts of data. This is one thing that both the pioneers and critics of deep learning agree on. In fact, deep learning didn’t emerge as the leading AI technique until a few years ago because of the limited availability of useful data and the shortage of computing power to process that data.Reducing the data-dependency of deep learning is currently among the top priorities of AI researchers.

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KAIST Develops Technology for AI-based High-resolution Image Creation

Article | April 7, 2020

The Korea Advanced Institute of Science and Technology (KAIST) announced on April 6 that professor Yoo Hoi-jun and his research team have succeeded in developing a generative adversarial networks processing unit (GANPU) as an AI chip processing GAN with low power and high efficiency. The AI chip is capable of quickly processing arithmetic operations required for image synthesis and restoration on a mobile basis. The single chip is capable of realizing image recognition, inference, learning and determination with low power and high efficiency and is expected to contribute to the use of AI in mobile devices for more purposes.

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Spotlight

Kernel Analytics

Our everyday actions generate large amounts of data: the things we buy, the trips we make, the people we call, and many others. At Kernel Analytics we believe all this information has the potential to change the world and we want to contribute with our expertise in data analysis and the development of predictive models to make this change happen. We are driven by the will to improve the world and a taste for high quality work.

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