This spring, in a canyon over 2,000 feet beneath the Indian Ocean surface, a robot happened upon a fantastical, coiled creature. This siphonophore, found laying like loosely piled rope on the seabed, might be the longest animal ever discovered. The discovery, made by scientists aboard the R/V Falkor, a vessel operated by the marine research organization the Schmidt Ocean Institute, was one of many unique sightings in, or newly published research about, the deep sea this year. The worst pandemic in a century may have canceled many marine expeditions, but discoveries in the ocean deep -- abetted by robotic explorers -- continued apace in 2020. Marine scientists candidly admit humanity has "barely scratched the surface" of what transpires in the ocean's "twilight zone," a place extending some 660 to 3,300 feet below the surface.
Robin Murphy (featured in 2013), is the Raytheon Professor of Computer Science and Engineering in Texas A & M and Director of the non-profit Humanitarian Robotics and AI Laboratory, (formerly known as Center for Robot-Assisted Search and Rescue (CRASAR). She is a distinguished Disaster Roboticist pioneering the advancement of AI and mobile robotics in unstructured and extreme environments. At CRASAR, she has been actively supplying her rescue robot since 9/11 in 2001 and has now participated in more than 30 disasters which include building collapses, earthquakes, floods, hurricanes, marine mass casualty events, nuclear accidents, tsunamis, underground mine explosions, and volcanic eruptions, in five different countries. And she has developed and taught classes in robotics for emergency response and public safety for over 1,000 members of 30 agencies from seven countries.
Sundance Multiprocessor Technology has joined Digital Catapult's Machine Intelligence Garage business incubator, in a move that will help to deepen its expertise in the deployment of AI (artificial intelligence) and ML (machine learning) techniques across a diverse range of embedded systems applications. In addition to Sundance's embedded platforms optimised for running deep learning algorithms used for performing autonomous navigation and other computer vision applications, these companies are working on a range of applications that include video analytics for improved livestock welfare management, solutions for reducing greenhouse emissions, interactive podcasting and neural networking. Digital Catapult is the UK's advanced digital technology innovation centre and connects start-up and scaleup companies with large businesses, investors, government and public organisations, and research and academia. Its Machine Intelligence Garage aims to provide support in the AI/ML arena as well as provide access to the compute-intensive power needed by these enterprises to develop and test their models. It is delivered as part of London's CAP-AI project and is part funded through the European Regional Development Fund. "We started the Machine Intelligence Garage to address the challenges the UK's promising early stage AI and ML companies face, accelerating their growth and helping them realise their true potential by providing access to high-level computational power, relevant expertise, mentoring and networking opportunities," said Jeremy Silver, CEO of Digital Catapult.
This article contains a proposal to add coinduction to the computational apparatus of natural language understanding. This, we argue, will provide a basis for more realistic, computationally sound, and scalable models of natural language dialogue, syntax and semantics. Given that the bottom up, inductively constructed, semantic and syntactic structures are brittle, and seemingly incapable of adequately representing the meaning of longer sentences or realistic dialogues, natural language understanding is in need of a new foundation. Coinduction, which uses top down constraints, has been successfully used in the design of operating systems and programming languages. Moreover, implicitly it has been present in text mining, machine translation, and in some attempts to model intensionality and modalities, which provides evidence that it works. This article shows high level formalizations of some of such uses. Since coinduction and induction can coexist, they can provide a common language and a conceptual model for research in natural language understanding. In particular, such an opportunity seems to be emerging in research on compositionality. This article shows several examples of the joint appearance of induction and coinduction in natural language processing. We argue that the known individual limitations of induction and coinduction can be overcome in empirical settings by a combination of the the two methods. We see an open problem in providing a theory of their joint use.
Social media popularity and importance is on the increase, due to people using it for various types of social interaction across multiple channels. This social interaction by online users includes submission of feedback, opinions and recommendations about various individuals, entities, topics, and events. This systematic review focuses on the evolving research area of Social Opinion Mining, tasked with the identification of multiple opinion dimensions, such as subjectivity, sentiment polarity, emotion, affect, sarcasm and irony, from user-generated content represented across multiple social media platforms and in various media formats, like text, image, video and audio. Therefore, through Social Opinion Mining, natural language can be understood in terms of the different opinion dimensions, as expressed by humans. This contributes towards the evolution of Artificial Intelligence, which in turn helps the advancement of several real-world use cases, such as customer service and decision making. A thorough systematic review was carried out on Social Opinion Mining research which totals 485 studies and spans a period of twelve years between 2007 and 2018. The in-depth analysis focuses on the social media platforms, techniques, social datasets, language, modality, tools and technologies, natural language processing tasks and other aspects derived from the published studies. Such multi-source information fusion plays a fundamental role in mining of people's social opinions from social media platforms. These can be utilised in many application areas, ranging from marketing, advertising and sales for product/service management, and in multiple domains and industries, such as politics, technology, finance, healthcare, sports and government. Future research directions are presented, whereas further research and development has the potential of leaving a wider academic and societal impact.
NIR Calibration-Model Services Spectroscopy and Chemometrics News Weekly 46, 2020 NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry foodindustry Analysis Lab Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK Get the Spectroscopy and Chemometrics News Weekly in real time on Twitter @ CalibModel and follow us. Near-Infrared Spectroscopy (NIRS) "Near infrared absorption spectroscopy for the quantification of unsulfated alcohol in sodium lauryl ether sulfate" LINK "Estimation of Organic Carbon in Anthropogenic Soil by VIS-NIR Spectroscopy: Effect of Variable Selection" LINK "Near infrared spectroscopy (NIRS) based high-throughput online assay for key cell wall features that determine sugarcane bagasse digestibility") LINK "Authentication of barley-finished beef using visible and near infrared spectroscopy (Vis-NIRS) and different discrimination approaches" LINK "Energetic Distribution of States in Irradiated Low-Density ...
Windfall Geotek (formerly Albert Mining) is a Canadian corporation offering a proven and industry-leading digital platform leveraging Artificial Intelligence (AI) technologies to significantly improve outcomes in the exploration, development, operations and financing of geologically focused projects. Principal markets encompass the global resource mining industry including virtually all forms of mineralization including oil and gas exploration. Recent advances have led to the detection of water sources and aquifers especially in drought regions, and of anti-personnel landmines and related deadly legacy hazards in conflict zones. Our applied machine learning technology offers a revolutionary approach to geologic discovery and a markedly positive economic impact on operational efficiencies. Since 2004 our Company has added value to over 30 client discoveries and more than 80 target generation projects around the globe.
Predictiv AI Inc. (TSX VENTURE: PAI) (OTC: INOTF) (FRANKFURT: 71TA) ("Predictiv AI" or the "Company"), www.predictiv.ai, a software and solutions provider in the artificial intelligence and industrial IoT markets, is pleased to provide a sales update on ThermalPass www.thermalpass.com, Predictiv AI is delivering units, against five initial orders, over the next 45 days. The initial customer base consists of a wide cross-section of businesses and organizations which include a convention center, a hospital, a mining company, two manufacturing plants and a leading industrial conglomerate. The internal sales and marketing team has also built an extensive pipeline since ThermalPass' commercial launch 30 days ago. In addition, the Company has entered into seven strategic reseller contracts with established sales channels in Canada, the United States and Europe.
Devastated by industrial crisis, America's former "steel city" has reinvented itself as an innovation hub. But today its main challenge is to keep its "One Pittsburgh" promise by ensuring that everybody in its diverse population shares the benefits of new growth. Pittsburgh is back from the brink. A flagship of triumphant industrialisation in the early 20th century, the city has since seen its steel mills decline and then shut down. As the economy lurched from one crisis to another, Pennsylvania's rusting "steel city" became an emblem of decline, like other urban "dead stars" in the rustbelt of America's Middle West. But Pittsburgh never gave up.
While Artificial Intelligence (AI) is a much touted technology in mining, it would seem that the sector is yet to fully embrace this advance technology. Why is this and how can we insure that AI can be beneficial to mining in Africa. According to Prof. Frederick Cawood, Director of Wits Mining Institute at the University of the Witwatersrand, it will take a policy change to ensure that it can benefit mining in Africa. Cawood was a panellist on a recent Mining Review Africa webinar titled Mining 2025: A 5-year vision for AI in mining. Cawood was joined on the panel by Eric Croeser, MD for Africa at Accenture Industry X and Jean-Jacques Verhaeghe, programme manager for real-time information management systems at Mandela Mining Precinct.