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Machine learning aids earthquake risk prediction

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Our homes and offices are only as solid as the ground beneath them. When that solid ground turns to liquid--as sometimes happens during earthquakes--it can topple buildings and bridges. This phenomenon is known as liquefaction, and it was a major feature of the 2011 earthquake in Christchurch, New Zealand, a magnitude 6.3 quake that killed 185 people and destroyed thousands of homes. An upside of the Christchurch quake was that it was one of the most well-documented in history. Because New Zealand is seismically active, the city was instrumented with numerous sensors for monitoring earthquakes.


Threats of a Replication Crisis in Empirical Computer Science

Communications of the ACM

Andy Cockburn (andy.cockburn@canterbury.ac.nz) is a professor at the University of Cantebury, Christchurch, New Zealand, where he is head of the HCI and Multimedia Lab. Pierre Dragicevic is a research scientist at Inria, Orsay, France.


The Pope says AI could lead humanity to "barbarism"

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At a conference at the Vatican last week, Pope Francis warned a group of Silicon Valley execs that in the wrong hands, artificial intelligence could have devastating consequences for humanity. "If mankind's so-called technological progress were to become an enemy of the common good, this would lead to an unfortunate regression to a form of barbarism dictated by the law of the strongest," he said, according to Reuters. The development of advanced AI can "raise increasingly significant implications in all areas of human activity," the Pope said. He also called for "open and concrete discussions" to develop "both theoretical and practical moral principles." The conference also grappled with the March 2019 attacks in Christchurch, New Zealand, and how social media platforms helped spread footage taken during the shootings, according to TIME.


Can artificial intelligence algorithms help regulate extreme speech?

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Following the attacks in Christchurch, New Zealand, in March, social media companies have once again come under growing pressure to "do …


AI-Powered Gun Detection Is Coming to Mosques Worldwide Following Christchurch Shootings

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In March, a gunman walked into two mosques in Christchurch, New Zealand, opened fire, and killed dozens of worshippers. According to a police official, the suspected gunman was arrested 36 minutes after police were called to the scene. Now, a tech company believes its smart security cameras can prevent attacks like the tragedy in Christchurch, and says it plans to install its AI-powered systems in mosques around the world. Athena Security, the tech company behind the security system, and Al-Ameri International Trading announced the Keep Mosques Safe initiative last week. Al-Ameri International Trading, along with several Islamic non-profit groups, will fund the Keep Mosques Safe effort.


Future of artificial intelligence becomes key topic at World Economic Forum » Uncensored Publications

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I have a lovely partner and 3 very active youngsters. We live in the earthquake ravaged Eastern Suburbs of Christchurch, New Zealand. I began commenting/posting on Uncensored back in early 2012 looking for discussion and answers on the cause and agendas relating to our quakes. I have always maintained an interest in ancient mysteries, UFOs, hidden agendas, geoengineering and secret societies and keep a close eye on current world events. Since 2013 I have been an active member of theCONTrail.com


Generalized Earthquake Frequency-Magnitude Distribution Described by Asymmetric Laplace Mixture Modelling

arXiv.org Machine Learning

The complete part of the earthquake frequency-magnitude distribution (FMD), above completeness magnitude mc, is well described by the Gutenberg-Richter law. The parameter mc however varies in space due to the seismic network configuration, yielding a convoluted FMD shape below max(mc). This paper investigates the shape of the generalized FMD (GFMD), which may be described as a mixture of elemental FMDs (eFMDs) defined as asymmetric Laplace distributions of mode mc [Mignan, 2012, https://doi.org/10.1029/2012JB009347]. An asymmetric Laplace mixture model (GFMD- ALMM) is thus proposed with its parameters (detection parameter kappa, Gutenberg-Richter beta-value, mc distribution, as well as number K and weight w of eFMD components) estimated using a semi-supervised hard expectation maximization approach including BIC penalties for model complexity. The performance of the proposed method is analysed, with encouraging results obtained: kappa, beta, and the mc distribution range are retrieved for different GFMD shapes in simulations, as well as in regional catalogues (southern and northern California, Nevada, Taiwan, France), in a global catalogue, and in an aftershock sequence (Christchurch, New Zealand). We find max(mc) to be conservative compared to other methods, kappa = k/log(10) = 3 in most catalogues (compared to beta = b/log(10) = 1), but also that biases in kappa and beta may occur when rounding errors are present below completeness. The GFMD-ALMM, by modelling different FMD shapes in an autonomous manner, opens the door to new statistical analyses in the realm of incomplete seismicity data, which could in theory improve earthquake forecasting by considering c. ten times more events.