Identity-based patterns for which a computational model needs to output some feature together with a copy of that feature are computationally challenging, but pose no problems to human learners and are common in world's languages. In this paper, we test whether a neural network can learn an identity-based pattern in speech called reduplication. To our knowledge, this is the first attempt to test identity-based patterns in deep convolutional networks trained on raw continuous data. Unlike existing proposals, we test learning in an unsupervised manner and we train the network on raw acoustic data. We use the ciwGAN architecture (Begu\v{s} 2020; arXiv:2006.02951) in which learning of meaningful representations in speech emerges from a requirement that the deep convolutional network generates informative data. Based on four generative tests, we argue that a deep convolutional network learns to represent an identity-based pattern in its latent space; by manipulating only two categorical variables in the latent space, we can actively turn an unreduplicated form into a reduplicated form with no other changes to the output in the majority of cases. We also argue that the network extends the identity-based pattern to unobserved data: when reduplication is forced in the output with the proposed technique for latent space manipulation, the network generates reduplicated data (e.g., it copies an [s] e.g. in [si-siju] for [siju] although it never sees any reduplicated forms containing an [s] in the input). Comparison with human outputs of reduplication show a high degree of similarity. Exploration of how meaningful representations of identity-based patterns emerge and how the latent space variables outside of the training range correlate with identity-based patterns in the output has general implications for neural network interpretability.

In recent years the phrase "data science" has become a buzzword in the tech industry. The demand for data scientists has surged since the late 1990s, presenting new job opportunities and research areas for computer scientists. Before we delve into the computer science aspect of data science, it's useful to know exactly what data science is and to explore the skills required to become a successful data scientist. Data science is a field of study that involves the processing of large sets of data with statistical methods to extract trends, patterns, or other relevant information. In short, data science encapsulates anything related to obtaining insights, trends, or any other valuable information from data.

Artificial Intelligence Platform Market report is a comprehensive analysis of global market has newly added by IT Intelligence Markets to its extensive repository. The statistical report offers a prime wellspring of applicable information for global business progress. Global Artificial Intelligence Platform Market research reports growth rates and market value based on market dynamics, growth factors. Complete knowledge is based on the latest innovations in the industry, opportunities and trends. In addition to SWOT analysis by key suppliers, the report contains a comprehensive market 0061nalysis and major player's landscape. Ask for Sample Copy of This Report: https://www.itintelligencemarkets.com/request_sample.php?id 28007 The purpose of this study is to define the overview of the Global Artificial Intelligence Platform Market with respect to market size, shares, sales patterns, and pricing structures.

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At present, more African elephants are dying than being born. Over the last century, the world's elephant population has declined 97% from trophy hunters, ruthless ivory mercenaries, and even terrorist groups. The Wildlife Conservation Society has pointed out that the global ivory trade leads to the death of up to 35,000 elephants a year in Africa. It's easy to point a finger at China as the biggest market for poached ivory in the world, yet only five years ago more than a ton of confiscated ivory was crushed in New York's Times Square by the Wildlife Conservation Society.

Deepfakes is a class of synthetic media generated by AI and represents another dark side of technology -- this form of Artificial Intelligence stole the headlines last year when a LinkedIn user by the name Katie Jones, who appeared on the platform & started connecting with the Who's Who of the political elite in Washington DC. It was alarming, how deep learning created a real-life image of a person & then penetrated the social media spreading misinformation. With the U.S presidential elections looming, lawmakers in the country are worried about how deepfakes can greatly jeopardize the transparency of the democratic process. Many of the leading tech companies have been asked for help and are working on developing tools that can detect this fake synthetic media. Global software giant, Microsoft, has now released two new tools that can spot if a certain media has been artificially manipulated.

The pandemic is helping to usher in a new era of food-production forecasts that rely more on satellite data and artificial intelligence and less on information gathered by people. The crop world, including major trading houses and statisticians at the U.S. Department of Agriculture, has long depended on scouts trudging through fields to count corn kernels and soybean pods. But travel restrictions and new virus safety measures have cut participation in field tours at a time of increasing scrutiny over food security. "Covid-19 is disrupting agricultural supply chains in developing countries, and observers on the ground can no longer report on crop conditions," said Lillian Kay Petersen, a student at Harvard University. She won the top prize of this year's Regeneron Science Talent Search, a 79-year-old competition for high school students held by the Society for Science and the Public, for her model that uses daily satellite images to predict crop yields in Africa.

Music preferences are strongly shaped by the cultural and socio-economic background of the listener, which is reflected, to a considerable extent, in country-specific music listening profiles. Previous work has already identified several country-specific differences in the popularity distribution of music artists listened to. In particular, what constitutes the "music mainstream" strongly varies between countries. To complement and extend these results, the article at hand delivers the following major contributions: First, using state-of-the-art unsupervised learning techniques, we identify and thoroughly investigate (1) country profiles of music preferences on the fine-grained level of music tracks (in contrast to earlier work that relied on music preferences on the artist level) and (2) country archetypes that subsume countries sharing similar patterns of listening preferences. Second, we formulate four user models that leverage the user's country information on music preferences. Among others, we propose a user modeling approach to describe a music listener as a vector of similarities over the identified country clusters or archetypes. Third, we propose a context-aware music recommendation system that leverages implicit user feedback, where context is defined via the four user models. More precisely, it is a multi-layer generative model based on a variational autoencoder, in which contextual features can influence recommendations through a gating mechanism. Fourth, we thoroughly evaluate the proposed recommendation system and user models on a real-world corpus of more than one billion listening records of users around the world (out of which we use 369 million in our experiments) and show its merits vis-a-vis state-of-the-art algorithms that do not exploit this type of context information.

Hyperbolic space is a natural setting for mining and visualizing data with hierarchical structure. In order to compute a hyperbolic embedding from comparison or similarity information, one has to solve a hyperbolic distance geometry problem. In this paper, we propose a unified framework to compute hyperbolic embeddings from an arbitrary mix of noisy metric and non-metric data. Our algorithms are based on semidefinite programming and the notion of a hyperbolic distance matrix, in many ways parallel to its famous Euclidean counterpart. A central ingredient we put forward is a semidefinite characterization of the hyperbolic Gramian -- a matrix of Lorentzian inner products. This characterization allows us to formulate a semidefinite relaxation to efficiently compute hyperbolic embeddings in two stages: first, we complete and denoise the observed hyperbolic distance matrix; second, we propose a spectral factorization method to estimate the embedded points from the hyperbolic distance matrix. We show through numerical experiments how the flexibility to mix metric and non-metric constraints allows us to efficiently compute embeddings from arbitrary data.

SCI COMMUN### Astronomy Talk about a sharper image: A recently constructed imaging sensor array (above) that will be used when the Vera C. Rubin Observatory in Chile opens in 2021 has captured a world-record 3200 megapixels in a single shot. It recorded a variety of objects, including a Romanesco broccoli, at that resolution, which is detailed enough to show a golf ball clearly from 24 kilometers away. The sensor array's focal plane is more than 60 centimeters wide, much larger than the 3.5-centimeter sensors on high-end consumer digital cameras, says the SLAC National Accelerator Laboratory, which built the array. When the telescope, funded by the U.S. National Science Foundation, begins operating next year, it will image the entire southern sky every few nights for 10 years, cataloguing billions of galaxies each time. The surveys will shed light on mysterious dark energy and dark matter, which make up most of the universe's mass. With its repeat coverage, the telescope will make the equivalent of an astronomical movie in order to discover objects that suddenly appear, move, or go bang. ### Biomedicine Corticosteroids given orally or intravenously should be the standard therapy for people with “severe and critical” COVID-19, the World Health Organization (WHO) said in new guidelines issued last week—but they should not be given to patients with mild cases. In June, a large U.K. trial named Recovery first showed that the steroid dexamethasone cut deaths among ventilated COVID-19 patients by 35% after 28 days of treatment. That result was confirmed by a WHO-sponsored metaanalysis published in JAMA on 2 September that included Recovery and six other studies testing dexamethasone, as well as two other corticosteroids—hydrocortisone and methylprednisolone. Many countries, including the United States, had already included corticosteroids in their national treatment guidelines. But WHO's recommendations will be important as a signal to low- and middle-income countries, says Martin Landray, one of Recovery's principal investigators. ### Public health COVID-19 virus particles drifting through a Chinese apartment building's plumbing may have infected some residents, a study has found, raising fears of yet another way that the disease could spread. The case echoes a 2003 outbreak of severe acute respiratory syndrome (SARS) that spread through the pipes of a Hong Kong apartment building. Such transmission is difficult to prove. But scientists suspect that aerosolized coronavirus may have spread from the bathroom of a Guangzhou family of five through a floor drain and into the building's wastewater pipes. Two middle-aged couples living in apartments above the family later contracted COVID-19. The study appeared last week in Annals of Internal Medicine . ### Conservation A plan to reforest a cross-continental strip of Africa to hold back expansion of the Sahara Desert and the semi-arid Sahel has made little progress—even though the project is halfway toward its planned completion date in 2030, a report says. Participating countries have planted only 4 million hectares of trees and other vegetation for the Great Green Wall, well short of the 100 million planned to stretch 7000 kilometers from Senegal to Djibouti, says the report by the Climatekos consulting firm, presented on 7 September at a meeting of the countries' ministers. Supporters predicted the project would also create jobs and capture carbon dioxide. Scientists have said creating grasslands may be more effective than planting trees to resist desertification, The Guardian reported. ### Philanthropy Rice University last week received a $100 million gift for materials science. It is the largest to date in that discipline recorded in a database of gifts for engineering maintained by The Chronicle of Philanthropy . The funding will be used to pair materials science with artificial intelligence to advance the design and manufacturing of new materials, for applications that include sustainable water systems, energy, and telecommunications. The donor was the Robert A. Welch Foundation, which supports chemistry research in Texas. ### Conservation Scientists hailed a move last week by the European Union to ban the use of lead ammunition near wetlands and waterways. The European Chemicals Agency has estimated that as many as 1.5 million aquatic birds die annually from lead poisoning because they swallow some of the 5000 tons of lead shot that land in European wetlands each year. Its persistence in the environment is also considered a human health hazard. The EU Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) committee approved the ban after years of controversy. The German delegation, which had abstained in a July vote on the issue, changed its stance to support the measure after a letter from 75 scientists and petitions signed by more than 50,000 people called for it to do so. The European Commission and the European Parliament are expected to formally approve the ban, allowing it to go into effect in 2022. REACH may debate a complete ban on lead ammunition and fishing weights later this year. ### Chemical weapons Alexei Navalny, a Russian opposition politician, was poisoned with a nerve agent “identified unequivocally in tests” as a Novichok, an exotic Sovietera chemical weapon, German Chancellor Angela Merkel said on 2 September. Navalny fell ill on 20 August after drinking a cup of tea at a Siberian airport. He was flown to Berlin and this week emerged from a coma. German military scientists at the Bundeswehr Institute of Pharmacology and Toxicology in Munich haven't released details of their tests, but they had clear targets to hunt for: Like other nerve agents, Novichoks bind to the enzymes acetylcholinesterase and butyrylcholinesterase, creating a telltale conjugate compound. Novichok agents came to wide public notice in 2018 after one was used in an assassination attempt against former Russian spy Sergei Skripal in the United Kingdom. The attack prompted nations to push for a crackdown on Novichok agents, and last year they were added to the list of toxic chemicals regulated under the Chemical Weapons Convention. ### COVID-19 In one of the largest surveys of Americans since COVID-19 lockdowns began, a majority reported having some symptoms of depression, up from one-quarter in a prepandemic survey. The prevalence of symptoms graded as moderate to severe tripled, to 27.8% of respondents. A research team compared results from two surveys used to screen for depression: one administered to more than 5000 people in 2017 and 2018 by the U.S. Centers for Disease Control and Prevention, the other given to 1400 people in early April by NORC at the University of Chicago. Prevalence of depression symptoms rose in all demographic groups and especially among individuals facing financial problems, job loss, or family deaths. The increases in self-reported symptoms are larger than those recorded in previous surveys after large-scale traumatic events in other countries, including outbreaks of the severe acute respiratory syndrome, H1N1, and Ebola, the authors write in the 2 September issue of JAMA Network Open . ### A U.S. vaccine leader's vow: Politics stays out “I would immediately resign if there is undue interference in this process.” So said Moncef Slaoui, scientific director of Operation Warp Speed, the U.S. effort to quickly develop a vaccine for COVID-19, in an interview with Science . To date, Warp Speed has invested more than $10 billion in eight vaccine candidates. Three are now in large-scale efficacy trials, and interim reviews of their data by independent safety and monitoring boards could reveal evidence of protection as early as October. Slaoui, an immunologist who formerly headed vaccine development at GlaxoSmithKline, answered questions from Science last week about how Warp Speed operates and addressed concerns that political pressure before the 3 November U.S. presidential election may lead to an emergency use authorization of a COVID-19 vaccine before it is proven safe and effective. (On 8 September, nine companies developing vaccines for the pandemic coronavirus pledged not to seek a premature authorization.) “It needs to be absolutely shielded from the politics,” Slaoui says. “Trust me, there will be no [authorization request] filed if it's not right. … The science is what is going to guide us. … And at the end of the day, the facts and the data will be made available to everyone who wants to look at them and will be transparent.” Slaoui defended Warp Speed's decision to not consider vaccines made of whole, inactivated viruses, a time-tested approach. China has three such vaccines in efficacy trials, but he worries they could cause serious side effects in people who receive them. Slaoui also said if it had been his choice, the United States would have participated in COVAX, a mechanism for countries to invest collectively in vaccines and share them; the Trump administration declined to join. The full interview—one of Slaoui's most detailed since taking the job in May—is at .