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'Cyborg' technology aims to reduce the opioid epidemic one chip at a time

USATODAY - Tech Top Stories

Tech these days is often accused of encouraging forms of addiction, but emerging "cyborg" technology may offer an answer for treating the opioid epidemic. Embedding microchips in the brains of addicts could help to, essentially, rewire them. He's among millions of people in America affected by what has become a national plague that kills hundreds each day. He hopes, though, that the computer chip in his brain can break him from addiction's hold. His dependence took hold after he dislocated his shoulder when he was 15.


Elements of Artificial Intelligence course gives basic introduction to AI ECHAlliance

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The opportunities created by enhanced computing power, availability of data, and progress in algorithms, have made Artificial Intelligence (AI) the main technological revolution of our times. Artificial Intelligence represents an area of strategic importance and a key driver of economic development. With the help of Elements of AI, the groundbreaking online course made by Reaktor and the University of Helsinki, all EU citizens can acquire basic understanding of Artificial Intelligence. The ambitious goal is to educate 1% of European citizens on Artificial Intelligence by 2021. The course will be made available in all the official EU languages.


AI Year in Review: Highlights of Papers from IBM Research in 2019

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January 17, 2020 Written by: John R. Smith IBM Research has a long history as a leader in the field of Artificial Intelligence (AI). IBM's pioneering work in AI dates back to the field's inception in the 1950s, when IBM developed one of the first instances of machine learning, which was applied to the game of checkers. Since then, IBM has been responsible for achieving major milestones in AI, ranging from Deep Blue – the first chess-playing computer to defeat a reigning world champion, to Watson – the first natural language question and answering system able to win at Jeopardy!, to last year's Project Debater – the first AI system that can build persuasive arguments on its own and effectively engage in debates on complex topics. IBM's leadership in AI continued in earnest in 2019, which was notable for a growing focus on critical topics such as making trustworthy AI work in practice, creating new AI engineering paradigms to scale AI for a broader use, and continuing to advance core AI capabilities in language, speech, vision, knowledge & reasoning, human-centered AI, and more. While recent years have seen incredible progress in "narrow AI," built on technologies like deep learning, IBM Research pushed its AI research in 2019 towards developing a new foundational underpinning of AI for enterprise applications by addressing important problems like learning more from less, enabling trusted AI by ensuring the fairness, explainability, adversarial robustness, and transparency of AI systems, and integrating learning and reasoning as a way to understand more in order to do more.


University diploma Artificial intelligence and intellectual property - CEIPI - University of Strasbourg

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The impact of the development of computer science on the knowledge of law is phenomenal and fundamental. Yet, few lawyers have the expertise to understand the impact of new algorithmic methods in their practice. The objectives of the training are twofold: the first is to transfer knowledge and skills in this high-tech sector, while the second is to provide technical training to lawyers. The university degree "Artificial Intelligence and Intellectual Property" has, on the one hand, a goal to remedy this lack in the field of intellectual property rights. Indeed, if there are many training courses on the digital and the law, none sufficiently understates the new issues of artificial intelligence in the field of intellectual property rights, in order to understand and control the issues of protection of these new types of creation, their usefulness to the implementation of rights, as well as their technical and economic environment.


2019 in Review: 10 AI Papers That Made an Impact

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The volume of peer-reviewed AI research papers has grown by more than 300 percent over the past three decades (Stanford AI Index 2019), and the top AI conferences in 2019 saw a deluge of paper. CVPR submissions spiked to 5,165, a 56 percent increase over 2018; ICLR received 1,591 main conference paper submissions, up 60 percent over last year; ACL reported a record-breaking 2,906 submissions, almost doubling last year's 1,544; and ICCV 2019 received 4,303 submissions, more than twice the 2017 total. As part of our year-end series, Synced spotlights 10 artificial intelligence papers that garnered extraordinary attention and accolades in 2019. Abstract: Finite-horizon lookahead policies are abundantly used in Reinforcement Learning and demonstrate impressive empirical success. Usually, the lookahead policies are implemented with specific planning methods such as Monte Carlo Tree Search (e.g. in AlphaZero).


Research Infographic

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IMAGE: Researchers of the ICAI Group -- Computational Intelligence and Image Analysis -- of the University of Malaga (UMA) have designed an unprecedented method that is capable of improving brain images... view more Researchers of the ICAI Group -Computational Intelligence and Image Analysis- of the University of Malaga (UMA) have designed an unprecedented method that is capable of improving brain images obtained through magnetic resonance imaging using artificial intelligence. This new model manages to increase image quality from low resolution to high resolution without distorting the patients' brain structures, using a deep learning artificial neural network -a model that is based on the functioning of the human brain- that "learns" this process. "Deep learning is based on very large neural networks, and so is its capacity to learn, reaching the complexity and abstraction of a brain", explains researcher Karl Thurnhofer, main author of this study, who adds that, thanks to this technique, the activity of identification can be performed alone, without supervision; an identification effort that the human eye would not be capable of doing. Published in the scientific journal Neurocomputing, this study represents a scientific breakthrough, since the algorithm developed by the UMA yields more accurate results in less time, with clear benefits for patients. "So far, the acquisition of quality brain images has depended on the time the patient remained immobilized in the scanner; with our method, image processing is carried out later on the computer", explains Thurnhofer.


SenseTime's AI generates realistic deepfake videos

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In late 2019, researchers at Seoul-based Hyperconnect developed a tool (MarioNETte) that could manipulate the facial features of a historical figure, a politician, or a CEO using nothing but a webcam and still images. More recently, a team hailing from Hong Kong-based tech giant SenseTIme, Nanyang Technological University, and the Chinese Academy of Sciences' Institute of Automation proposed a method of editing target portrait footage by taking sequences of audio to synthesize photo-realistic videos. As opposed to MarioNETte, SenseTime's technique is dynamic, meaning it's able to better handle media it hasn't before encountered. And the results are impressive, albeit worrisome in light of recent developments involving deepfakes. The coauthors of the study describing the work note that the task of "many-to-many" audio-to-video translation -- that is, translation that doesn't assume a single identity of source video and the target video -- is challenging.


Partners to develop AI hardware and software for autonomous vehicles -- Softei.com

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Videantis, which provides automotive deep learning, computer vision and video coding solutions, has announced that it will partner with the Fraunhofer Institute for Integrated Circuits IIS, Infineon and other leading companies and universities to develop an artificial intelligence (AI) ASIC and software development tools specifically for intelligent autonomous vehicles. The Videantis AI multi-core processor platform and tool flow has been selected for the KI-Flex autonomous driving chip project. Autonomous driving relies on fast and reliable processing and merging of data from several lidar, camera and radar sensors in the vehicle. This data can provide an accurate picture of the traffic conditions and environment to allow the vehicle to make intelligent decisions when driving. The process of intelligently analysing these volumes of sensor data requires high-performance, efficient, and versatile compute solutions.


Etopia News & Entertainment

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The robots are coming...in the form of voice-first, conversational A...I-based chatbots that use Natural Language Processing and Machine Learning to "understand" human commands and questions and respond appropriately, at scale, in real time, on behalf of individuals and institutions. The "Harvard UltraBot" could represent the university to potential applicants, the media, and other universities, through their respective UltraBots. A "LinkedIn UltraBot" from Microsoft could give voice to users and allow them to build and interface with their networks in a direct and intuitive way, by speaking. Harvard, Stanford, and UC Berkeley may soon all be racing to produce prototype and production models of their respective UltraBots. Etopia Media Consulting is advising every 2020 Presidential candidate to read "Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World," by Marco Iansiti and Karim Lakhani, both at Harvard Business School.


2020 Joint Conference on AI Music Creativity (CSMC MuMe) KTH

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The event is hosted by the Division of Speech, Music and Hearing, School of Electrical and Computer Engineering, KTH in collaboration with the Royal Conservatory of Music (KMH). The computational simulation of musical creativity continues to be an exciting and significant area of academic research, and is now making impacts in commercial realms. Such systems pose several theoretical and technical challenges, and are the result of an interdisciplinary effort that encompasses the domains of music, artificial intelligence, cognitive science and philosophy. The 2020 Joint Conference on AI Music Creativity brings together for the first time two overlapping but distinct research forums: The Computer Simulation of Music Creativity conference (est. The principal goal is to bring together scholars and artists interested in the virtual emulation of musical creativity and its use for music creation, and to provide an interdisciplinary platform to promote, present and discuss their work in scientific and artistic contexts.