With the widespread use of intelligent systems, such as smart speakers, addressee recognition has become a concern in human-computer interaction, as more and more people expect such systems to understand complicated social scenes, including those outdoors, in cafeterias, and hospitals. Because previous studies typically focused only on pre-specified tasks with limited conversational situations such as controlling smart homes, we created a mock dataset called Addressee Recognition in Visual Scenes with Utterances (ARVSU) that contains a vast body of image variations in visual scenes with an annotated utterance and a corresponding addressee for each scenario. We also propose a multi-modal deep-learning-based model that takes different human cues, specifically eye gazes and transcripts of an utterance corpus, into account to predict the conversational addressee from a specific speaker's view in various real-life conversational scenarios. To the best of our knowledge, we are the first to introduce an end-to-end deep learning model that combines vision and transcripts of utterance for addressee recognition. As a result, our study suggests that future addressee recognition can reach the ability to understand human intention in many social situations previously unexplored, and our modality dataset is a first step in promoting research in this field.

Artificial intelligence is a modern technology that is utilized in various fields of medicine [1-3]. At the meantime, Chinese Traditional Medicine (TCM) is now widely considered as a promising alternative medicine for complementary treatment in cancers or chronic diseases due to the effective methodology practically developed by generations of doctors for almost 4000 years [4]. Based on previous verification, it is undeniable that there are many correlations between the TCM syndromes and western diseases, turning out novel approaches for enhancing the treatment efficiency and developing medicines regarding with TCM methodologies [5]. Unfortunately, hindered by the remarkable gap between the modern informatics and the fundament of TCM: antient Chinese philosophy, such correlations are still too elusive to be formulated precisely. Therefore, recently, in order to figure out the deep connection between modern science and TCM, the research combining TCM with AI for valid knowledge acquisition and mining attracts extremely attention, and hereby, leading to many profound works, such as ontology information system design [6], latent tree models design [7], TCM warehouse for AI application [8], and digital knowledge graph development [2]. On the other hand, researchers face, however, many difficulties in setting up AI for TCM in terms of directly interpreting TCM semantic system (almost recorded by ancient Chinese doctrines) into structured database. Because in this way, considerable workload must be undertaken by limited numbers of experts who are proficient in both AI and TCM to translate the TCM terminologies and then formulate the modern model thereof. In contrast, as shown in Figure 1, the digestion of using TCM methodology in dealing with issues of modern science, new medicine design for example, is relatively lacking and thus of significant worth to explore.

Kespry announced the availability of the pulp and paper industry's first drone-based aerial intelligence solution. The new industry-specific solution improves the profitability of pulp and paper operations by delivering more accurate and timely supply chain material inventory data, while improving site operations and safety. "Measuring chip piles at a pulp mill has always been a challenge. In the past, a team of surveyors would climb onto the chip pile and arrive at a manual measurement," said Mitch Dunlop, Accounting Manager, Celgar, a leading North American pulp and paper organization. "This method is slow, poses safety concerns and is not very accurate.

I asked the smartest people I know for their tech predictions for the next 20 years (2018 – 2038). What are the breakthroughs we can expect on our countdown to the Singularity? I compiled 50 predictions in a document distributed to my Abundance 360 and Abundance Digital communities. Quantum Supremacy Achieved: The first demonstration of a quantum computation that can't be simulated with classical supercomputers is announced. Flying car operations take off in a dozen cities in the world.

I learned a few things from reading an excerpt from Yuval Noah Harari's book, 21 Lessons for the 21st Century, published in the October issue of The Atlantic. One is that it took a Google machine-learning program just four hours to teach itself and master chess, once the pinnacle of centuries of human intellectual effort, easily defeating the top-ranked computer chess engine in the world. Another is that artificial intelligence systems may be inherently anti-democratic and anti-human. New heights of computing power and data processing make it more efficient to centralize systems in authoritarian governments, Harari says, and will render humans increasingly irrelevant. "By 2050," he writes, "a useless class might emerge, the result not only of a shortage of jobs or a lack of relevant education but also of insufficient mental stamina to continue learning new skills."

By Snehal Shah In the movie Avengers: Age of Ultron, the Iron Man and Bruce Banner – a genius scientist when he wasn't playing Hulk – built an artificial intelligence system named'Ultron' to help protect the earth. But Ultron – the peacekeeping programme embedded in a synthetic body – turned hostile, making it his mission to eradicate humans from the face of the earth. As earth's fate hung in the balance, the mightiest of Avengers had to come together to save the planet from complete annihilation. Does this, another Marvel Comic story turned into a sci-fi Hollywood film, have a semblance of realism? A couple of years ago a unique experimental self-driving car was released on New Jersey roads, that was not coded or programmed by engineers.

This essay is the winner of The Economist's Open Future essay competition in the category of Open Progress, responding to the question: "Do the benefits of artificial intelligence outweigh the risks?" The winner is Frank L. Ruta, 24 years old, from America. Upgrade your inbox and get our Daily Dispatch and Editor's Picks. Towards the end of the second world war, a group of scientists in America working to develop an atomic bomb for the Manhattan Project warned that using the weapon would inevitably lead to a geopolitical landscape characterised by a nuclear arms race. This would force America, they said, to outpace other nations in building up nuclear armaments. They recommended that if the military did choose to use the weapon, an international effort for nuclear non-proliferation should promptly be established.

Daniel Wagner and Keith Furst, frequent contributors to this website, exhaustively explore the inner workings and implications of AI (artificial intelligence) in their new book, AI Supremacy: Winning in the Era of Machine Learning. Each chapter focuses on the current and future state of AI within a specific industry, country or society in general. Special emphasis is placed on how AI will shape the domestic, diplomatic and military landscapes of the United States, the European Union, and China. The first half of the book tackles AI as it pertains to commerce. There are chapters on globalization, manufacturing, finance, the sciences and communication.

TOKYO (WASHINGTON POST) - Japan is working to develop technology that will fully utilise artificial intelligence (AI) to detect suspicious vessels, according to sources. Aimed at strengthening maritime surveillance capabilities in waters around Japan, the envisioned technology is projected to be used for such purposes as monitoring North Korean ship-to-ship cargo transfers in international waters, the sources said. The government aims to start testing the AI-based technology in fiscal year 2021 using vessels of the Self-Defence Forces. The system will analyse information automatically transmitted by radio from the Automatic Identification System on board many ships. The AI will learn an enormous amount of information on the location and speed of ships, making it possible to automatically detect abnormalities such as ships navigating far away from ordinary routes or in the opposite direction. The Self-Defence Forces will identify suspicious ships by comparing the AI-collected data with information gathered by warning radar, and will dispatch destroyers and patrol aircraft for warning and surveillance activities.

The idea that Artificial Intelligence (AI) and robots will take our jobs and eventually conquer the world makes for a great summer blockbuster, but this fear of AI-robot overlords is grossly exaggerated. I personally welcome the AI and robot revolution. Robots won't replace our talented construction craft. Instead, a new generation of robots will strengthen our builders by performing highly repetitive, monotonous, hazardous, and less-productive tasks. In the same sense, AI – which performs decision-making tasks traditionally reserved for humans – won't render our knowledge workers irrelevant.