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Int'l project combats online antisemitism through artificial intelligence - The Jerusalem Post


The Alfred Landecker Foundation has announced its support for an initiative that will aim to combat the spread of antisemitism and hatred online by using artificial intelligence (AI). Titled "Decoding Antisemitism," the project was financially backed by the Foundation, which donated an additional 3 million Euros to the budget. By supporting the project, the Foundation is joining forces with the Center for Research on Antisemitism at the Technical University of Berlin, King's College London and other renowned scientific institutions in Europe and Israel. The international team, comprised of discourse analysts, computational linguists and historians, is currently focusing its efforts on developing an AI-driven approach to identifying online antisemitism, a feat that may be harder to achieve than expected. Studies have shown that the majority of antisemitic defamation is expressed in implicit ways – through the use of codes for instance ("juice" instead of "Jews") and allusions to certain conspiracy narratives or the reproduction of stereotypes through images.

Artificial Intelligence Enhances Speed of Discoveries For Particle Physics


Researchers at MIT have recently demonstrated that utilizing artificial intelligence to simulate aspects of particles and nuclear physics theories can lead to faster algorithms, and therefore faster discoveries when it comes to theoretical physics. The MIT research team combined theoretical physics with AI models to accelerate the creation of samples that simulate interactions between neutrons, protons, and nuclei. There are four fundamental forces that govern the universe: gravity, electromagnetism, the weak force, and the strong force. The strong, weak, and electromagnetic forces are studied through particle physics. The traditional method of studying particle interactions requires running numerical simulations of these interactions between particles, typically taking place at 1/10th or 1/100th the size of a proton.

Who thought political ads featuring Deepfake Putin and Kim trashing the US was a good idea?


A not-for-profit called RepresentUS, working with creative media agency Mischief @ No Fixed Address, recently used the popular Deepfake AI system to create a pair of political ads featuring actors digitally manipulated to look like Vladmir Putin and Kim Jong Un mocking the current state of US politics. The ads were reportedly slated to air on Fox, CNN, and MSNBC in their DC markets but were "pulled at the last minute" for reasons unknown. Allow me to clear the mystery: they were probably pulled because this is a bad idea. But before we get into that, let's take a moment to break down what's happening in the ads. RepresentUs, the not-for-profit behind the project, says on its website that it brings together "conservatives, progressives, and everyone in between to pass powerful state and local laws that fix our broken elections and stop political bribery. Our strategy is central to ending political corruption, extremism and gridlock."

Teaching Neural Networks to be Humans


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.

7 new ways chatbots can transform insurance


To answer questions on complex policies, handle claims, premium reminders, payments and to make sales, service and support much more effective in insurance? Indeed, there are chatbots that we are developing to do this and a lot more. Currently, a wide variety of chatbots exists across industries, functions and domains. There are a lot of generic bots that have a great design but their bot design is still evolving. However, domain specific bots or good industry bots are few and far between. The leverage of NLP technologies provides for new interaction channels that are not possible in traditional web or mobile apps.

Pentagon Is Clinging to Aging Technologies, House Panel Warns


A bipartisan House panel said on Tuesday that artificial intelligence, quantum computing, space and biotechnology were "making traditional battlefields and boundaries increasingly irrelevant" -- but that the Pentagon was clinging to aging weapons systems meant for a past era. The panel's report, called the "Future of Defense Task Force," is one of many underway in Congress to grapple with the speed at which the Pentagon is adopting new technologies, often using the rising competition with China in an effort to spur the pace of change. Most reach a similar conclusion: For all the talk of embracing new technologies, the politics of killing off old weapons systems is so forbidding -- often because it involves closing factories or bases, and endangers military jobs in congressional districts -- that the efforts falter. The task force said it was concentrating on the next 30 to 50 years, and concluded that the Defense Department and Congress should be "focused on the needs of the future and not on the political and military-industrial loyalties of the past."

Comprehensive Report on Artificial Intelligence in Energy Market 2020


Artificial Intelligence in Energy Market research report is the new statistical data source added by A2Z Market Research. "Artificial Intelligence in Energy Market is growing at a High CAGR during the forecast period 2020-2026. The increasing interest of the individuals in this industry is that the major reason for the expansion of this market". Artificial Intelligence in Energy Market research is an intelligence report with meticulous efforts undertaken to study the right and valuable information. The data which has been looked upon is done considering both, the existing top players and the upcoming competitors.

Great Barrier Reef: Uncovering the secrets of Australia's deep waters

BBC News

The most comprehensive deep-sea study of two marine parks off Australia has given a fascinating glimpse into what lives there. Scientists have told the BBC how they used an underwater robot to make a host of discoveries.

Practical Machine Learning Basics


This article describes my attempt at the Titanic Machine Learning competition on Kaggle. I have been trying to study Machine Learning but never got as far as being able to solve real-world problems. But after I read two newly released books about practical AI, I was confident enough to enter the Titanic competition. The first part of the article describes preparing the data. The second part shows how I used a Support Vector Machine (SVM). I used the SVM to create a model that predicts the survival of the passengers of the Titanic. The model resulted in a score of 0.779907, which got me in the top 28% of the competition.

Difference between Machine Learning and Deep Learning – Story by Data


A machine's ability to mimic human behavior is ARTIFICIAL INTELLIGENCE (AI). Machine Learning (ML) is a subset of AI, & Deep Learning (DL) is a subset of ML. ML provides systems the ability to automatically learn from experience without being explicitly programmed. DL is ML which is capable of learning unsupervised from data that is unstructured or unlabeled. The primary difference between the two is the way we feed data to each.