With advances in technology and easy access to paid and free tools to create spin-offs or rewrite content, people can now use Artificial Intelligence (AI) to make fake news, fabricated reviews, and fictitious social media accounts and thereby spreading misinformation. However, an AI can now also detect fake written material! This AI tool named Giant Language model Test Room or GLTR was developed by a collaborative effort of Harvard University and MIT-IBM Watson Lab researchers and developers whose goal was to teach information and raise awareness about generated text. The GLTR tool can determine whether a text is written by a human or is an AI spin generating tool by detecting statistical patterns. The AI text generating programs use an algorithm and specific code to detect data spinning patterns.

Aljosa Smolic 1 smolica@scss.tcd.ie 1 V-SENSE School of Computer Science and Statistics T rinity College Dublin, Ireland 2 University of Houston-Victoria, Victoria, T exas, US 3 CAAD Department of Architecture ETH, Zurich, Switzerland 4 Department of Architecture T arbiat Modares University T ehran, Iran Abstract Scene understanding of full-scale 3D models of an urban area remains a challenging task. While advanced computer vision techniques offer cost-effective approaches to analyse 3D urban elements, a precise and densely labelled dataset is quintessential. The paper presents the first-ever labelled dataset for a highly dense Aerial Laser Scanning (ALS) point cloud at city-scale. This work introduces a novel benchmark dataset that includes a manually annotated point cloud for over 260 million laser scanning points into 100'000 (approx.) Objects are labelled into 13 classes using hierarchical levels of detail from large ( i.e. building, vegetation and ground) to refined ( i.e. window, door and tree) elements. To validate the performance of our dataset, two different applications are showcased. Firstly, the labelled point cloud is employed for training Convolutional Neural Networks (CNNs) to classify urban elements. The dataset is tested on the well-known state-of-the-art CNNs ( i.e. Secondly, the complete ALS dataset is applied as detailed ground truth for city-scale image-based 3D reconstruction. 1 Introduction In computer vision, automated identification of three-dimensional (3D) assets in an unstructured large dataset is essential for scene understanding.

In order to facilitate the accesses of general users to knowledge graphs, an increasing effort is being exerted to construct graph-structured queries of given natural language questions. At the core of the construction is to deduce the structure of the target query and determine the vertices/edges which constitute the query. Existing query construction methods rely on question understanding and conventional graph-based algorithms which lead to inefficient and degraded performances facing complex natural language questions over knowledge graphs with large scales. In this paper, we focus on this problem and propose a novel framework standing on recent knowledge graph embedding techniques. Our framework first encodes the underlying knowledge graph into a low-dimensional embedding space by leveraging generalized local knowledge graphs. Given a natural language question, the learned embedding representations of the knowledge graph are utilized to compute the query structure and assemble vertices/edges into the target query. Extensive experiments were conducted on the benchmark dataset, and the results demonstrate that our framework outperforms state-of-the-art baseline models regarding effectiveness and efficiency.

It's IFA 2019, and that can only mean one thing: Gadgets abound for an entire week straight. LG, as it's apt to do, introduced an incrementally refined phone in the LG G8X (the successor to the LG G8). But the accessory the Seoul company unveiled alongside it is arguably more interesting: an updated version of its snap-on Dual Screen product that improves upon the original in several respects. Pricing has yet to be announced for the G8X and revamped Dual Screen, but we'll keep our eyes peeled for more details. LG anticipates both will ship in Q4.

Intel Distribution of OpenVINO toolkit optimization delivers high-quality image upscaling at higher speeds with Intel Core processors. Photo upscaling has long been limited by the capabilities of existing technology. Once a photo is taken, the size and number of pixels are set in stone. Trying to stretch those pixels into a larger format causes clarity and quality to suffer immediately. Thanks to advancements in machine learning, Topaz Labs has been able to harness the power of artificial intelligence to more elegantly overcome this hurdle.

Thieves stole over $240,000 by using voice-mimicking software to trick a companys employee. The thieves used an AI voice deepfake of a company executive to get the employee to wire money to an offsite account in what researchers say is the first publicly reported AI heist.If you havent heard by now, AI technology like deepfakes are able to accurately mimic or copy the likeness and sound of real people. This is what happened to one companys managing director who received a call from someone he believed was his superior. The superiors voice told the employee to wire the money to a Hungarian bank account to avoid late-payment fines.According to the companys insurer Euler Hermes, who detailed the events of the heist to The Washington Post, the AI-altered voice was able to imitate the voice, and not only the voice: the tonality, the punctuation, the German accent, of the company superior. The heist was first reported by the Wall Street Journal.

It's not because Sophia has a zipper on the back of its head though it illustrates quite well how far we still are from an intelligent and human-like robot. Have you seen already the new attempt of Sophia The Robot and its manufacturer Hanson Robotics to make public believe this automaton has consciousness and intelligence? Just yesterday Sophia got into the news again, starring in a short movie'SophiaWorld' along with'Westworld' actress Evan Rachel Woods. Why it matters to understand that Sophia is not what Hanson Robotics tries to pretend it to be? Discrepancy of what AI is and isn't remains too big to fall for the show. Sophia The Robot does not even act up to its full name.

A group of high-tech scammers used an artificial intelligence program to pull off a $243,000 theft. According to a report in the Wall Street Journal, the thieves called the managing director of an unidentified British Energy company pretending to be his boss, the CEO of the firm's parent company. The scammers used the software to imitate the CEO's voice and managed to convince the director to wire the money to a Hungarian bank account, claiming it was meant to pay a supplier. A source who works for the energy firm's insurance company told the Washington Post that the director thought the request was "rather strange" but completed the transfer because he genuinely believed that he was speaking to his boss. Authorities have not located the people responsible for the theft and are worried that this tactic could be used in the future, especially as voice-replicating software improves and becomes easier to use.

If you were the kind of kid who dreamed about living like the Jetsons, we've got some good news for you. Though machine maids and butlers with human-like intelligence still sound like something from a sci-fi movie, AI has become part of your daily experience. It's that helpful website chatbot that asks if you need any assistance. It helps Amazon curate your recommended book list, and Netflix uses it to suggest your next binge-worthy t.v. Your smartphone camera uses it to capture that picture-perfect sunset.

YouTube will stop selling personalized ads on videos aimed at children as part of a $170 million regulatory settlement on Wednesday. But the company's plan relies on technology that has struggled to make nuanced decisions in the past. The Google unit will use artificial intelligence to identify which videos are aimed at kids, then cut those clips off from targeted ads. It's a plan politicians and consumers have heard before. YouTube has used AI for years to find and take down unwanted content including pornography, terrorist propaganda and extreme violence.