Turkey


Batman Can't Stop Farting Near Babies - A.I. Generated News - IGN

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When news is slow, we ask a computer to use futuristic intelligence algorithms to generate news stories for us, thanks to a website we found called TalkToTransformer.com. We type in the beginning of a news story, and let the computers do the rest. Now, let us read you some of these stories with our human mouths so the robots will spare us in the great Future War Against Machines in 2077. Today's stories: Donkey Kong Arrested for Animal Abuse, Crash Bandicoot Seriously Injures a Young Man, A Fisherman in Legend of Zelda Is Bitten by an Octopus and Batman Can't Stop Farting Near Babies. We thank our robot overlords for giving us an opportunity to serve and spread the good news they have invented for our human mouths to speak.


Robotics transition for industry underway in Turkey

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Robotic systems are one of the most significant elements accelerating the country's economy toward Industry 4.0. Turkey, having a voice in this competition, aims to increase robot use and its density in the region it's involved in. Prominent Switzerland-based robot producer ABB, which is considered one of the cornerstones of the International Federation of Robotics, laid the foundation of a new company in China on Sept. 11., with the slogan "Robots will teach robots to work." As the world advances through robotization, we spoke with ABB Turkey's Robotics and Manufacturing Automation Group Head Emre Tural about Turkey's potential. Tural spoke on industrial robot usage in Turkey, which is a big economy, the secondhand or thirdhand robot market, machine and production industry's meeting industrial robots and how industrial robots turn into collaborative ones.


Revealed: global video games giants avoiding millions in UK tax

The Guardian

A UK tax policy intended to boost the domestic video games industry has been used by some of the world's largest entertainment companies to avoid paying tens of millions of pounds in corporation tax, a Guardian investigation has found. WarnerMedia, which owns the British game development companies that make the Lego and Batman: Arkham series, has claimed up to £60m in corporation tax relief, according to company filings. Sony, the owner of PlayStation, claimed almost £30m. Japanese multinational Sega claimed up to £20m, according to audits of its UK subsidiaries that make the strategy-based Total War games and the hit sports series Football Manager. Video Games Tax Relief (VGTR), which enables game developers to claim back up to 20% of certain production costs, was introduced in 2014 after years of lobbying by the industry.


Ownership dilemma: Who owns the products produced by AI?

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As it is across the world, the amount of investments made in artificial intelligence (AI) and the number of entrepreneurs using AI to develop new projects is also increasing in Turkey. AI facilitates business and production processes and supports automation. This shows that the number of AI start-ups will increase in the coming years. Therefore, Lale Deliveli Alp, one of the founders of Deliveli Alp Law & Consultancy, answered the following questions to make young entrepreneurs' work easier: By what legal means are AI software developed by technology companies protected? Is it possible to patent a developed AI? Alp answered the question about which many entrepreneurs wonder with the following response: "It is not possible to patent AI, which is software, in accordance with Article No. 82 in the Industrial Property Law. Computer programs are out of patentability. However, if the developed AI does not function separately from the hardware, it can be patented. For example, the AI of a developed robot can be patented since it cannot be used separately from the robot. It is always possible to protect AI software developed apart from this within the scope of copyright law as explained above."


'Racist' AI art warns against bad training data

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An artificial-intelligence art project has been criticised for using racist and sexist tags to classify its users. When they share a selfie with ImageNet Roulette, the web app matches it to the ones it most closely resembles from an enormous library of profile photos. It then reveals the most popular tag, assigned to the matching pictures by human workers using data set WordNet. These include racial slurs, "first offender", "rape suspect", "spree killer", "newsreader", and "Batman". Those responsible for assigning the tags to the library pictures were recruited via a service offered by Amazon, called Mechanical Turk, which pays workers around the world pennies to perform small, monotonous tasks.


Multi-Year Vector Dynamic Time Warping Based Crop Mapping

arXiv.org Machine Learning

Abstract: Recent automated crop mapping via supervised le arning - based methods have demonstrated unprecedented improvement over classical techniques. However, m ost crop mapping studies are limited to same - year crop mapping in which the present year's labeled data is used to predict the same year's crop map. Cross - y ear crop mapping is more useful as it allows the prediction of the following years' crop maps using previously labeled data. We propose Vector Dynamic Time Warping ( VD TW), a novel multi - year classification approach based on warping of angular distances between phenological vectors. The results prove that the proposed VDTW method is robust to temporal and spectral v ariations compensating for different farming practices, climate and atmospheric effects, and measurement errors between years. We also describe a method for determining the most discriminative time window that allows high classification accuracies with lim ited data. We carried out test s of our approach with Lan dsat 8 time - series imagery from years 2013 to 2016 for classification of corn and cotton in the Harran Plain, and corn, cotton, and soybean in the Bismil Plain of Southeastern Turkey. In addition, we tested VDTW corn and soybean in Kansas, the US for 2017 and 2018 with the Harmonized Landsat Sentinel data . The VDTW method achieved 99.85% and 99.74% overall accuracies for the same and cross years, respectively with fewer training samples compared to oth er state - of - the - art approaches, i.e. spectral angle mapp er ( SAM), dynamic time warping ( DTW), time - weighted DTW ( TWDTW), random forest (RF), support vector machine ( SVM) and deep long short - term memory ( LSTM) methods. The proposed method could be expanded for other crop types and/or geographical areas. Keywords: Time series; phenology; multi - year classification; dynamic programming; Landsat; crop mapping; land use; corn; cotton; soybean 1. Introduction T he world population is expected to exceed nine billion in 2050 [1] . Providing adequate nutrition for the increasing human population is a significant concern. Advanced agri cultural technologies, such as precision agriculture and precision irrigation are rapidly emerging to optimize water, fertilizers, and pesticides; thereby enabling higher crop yield. Accurate crop maps are the first requirements of advanced agriculture app lications such as yield forecasting . Early - season crop yield estimates are a crucial factor for food security and monitor ing agricultural subventio ns. Crop maps are also an essential tool for statistical purposes to analyze annual changes in agricultural p roduction. However, there are a variety of field crops with similar phenologies and spectral signatures.


Chinese Newspaper Auto Generating Science News - Robot Writers AI

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China Science Daily is using artificial intelligence to auto-generate news stories, based on article abstracts it finds in major scientific journals. Those journals include some of the most influential scientific publications in the world, including Science, Nature, Cell and the New England Journal of Medicine. So far, China Science Daily has published more than 200 articles using AI. The primary impetus behind the effort: To offer Chinese scientists easy access to scientific research from around the world – devoid of language barriers -- according to Zhang Mingwei, deputy editor-in-chief, China Science Daily. Keaton Patti, who has written for Marvel and Comedy Central, says he trained an AI writing system to be Batman-savvy by having it view approximately 1,000 hours of Batman films.


Chinese Newspaper Auto Generating Science News - Robot Writers AI

#artificialintelligence

China Science Daily is using artificial intelligence to auto-generate news stories, based on article abstracts it finds in major scientific journals. Those journals include some of the most influential scientific publications in the world, including Science, Nature, Cell and the New England Journal of Medicine. So far, China Science Daily has published more than 200 articles using AI. The primary impetus behind the effort: To offer Chinese scientists easy access to scientific research from around the world – devoid of language barriers -- according to Zhang Mingwei, deputy editor-in-chief, China Science Daily. Keaton Patti, who has written for Marvel and Comedy Central, says he trained an AI writing system to be Batman-savvy by having it view approximately 1,000 hours of Batman films.


A Batman Script Was Written by A.I. After 1000 Hours of Viewing Footage

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Ever hear the one about how a group of monkeys could, given enough time, produce the entire works of Shakespeare? Well, apparently an AI being forced to watch 1,000 hours of Batman can be coerced into creating a script. Honestly though it looks like something that might cause the Joker to grimace in utter distaste since it's about one of the most nonsensical things around. Seriously, it's laughable enough that someone might want to pick it up and make a movie out of it, a parody at least. This kind of proves that as much as AI might be a perceived threat to some, there's not much chance that it's going to be much of a threat to writers in the near future since at this point computers still aren't quite expert at thinking around corners.


Human Capital – TAZI

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Tazi is a global supplier and developer of a unique, understandable continuous automated machine learning product. We are a pioneer in the next generation of continuous autonomous machine learning, putting humans at the epicenter of business solutions. Based in Istanbul, Amsterdam and San Francisco, we are seeking for talented and seasoned individuals. Focussing on culture first, we want someone with a soul, who does the right thing, is openminded and without ego. We are seeking for someone we want to hang-out with, laugh with, jam and work hard with.