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Coronavirus Spurs Energy Transition Through Artificial Intelligence - AI Summary

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We are trying to use the data that is recorded on the wind turbines to predict failures," Kalyan Veeramachaneni, principal research scientist in the Laboratory for Information and Decision Systems of the Massachusetts Institute of Technology, told DW. Ewald Hesse, CEO of Berlin-based Grid Singularity, says several countries in Africa would leapfrog the development phase of European energy systems, similar to what happened to landline phones. "In developing countries, there is no stringent regulation in the energy sector, and we don't need to convince the government of allowing a new approach to energy production and consumption. Still, local communities would benefit from one PV system in the surrounding area, which, combined with sensors to measure energy consumption, would create a localized market. "Whatever comes out in the energy field in developing countries will be by far smarter and more practical than what we have in Germany," said Hesse, adding that several companies contributed to unlocking potential markets and significant investments in developing countries.


Energy markets post-COVID 19: Recovery may take time, transition to continue

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As oil markets have crashed, the experts believe the oil prices will come down drastically and continue making the energy transition a financial burden for many economies for a couple of years.  However, the market alone was never the sole force behind the energy transition. Global warming and climate change played a major role in the energy transition and are the most likely to prevail as the biggest motivators in post-COVID 19 pandemic world.


Conversational Agents: Theory and Applications

arXiv.org Artificial Intelligence

In this chapter, we provide a review of conversational agents (CAs), discussing chatbots, intended for casual conversation with a user, as well as task-oriented agents that generally engage in discussions intended to reach one or several specific goals, often (but not always) within a specific domain. We also consider the concept of embodied conversational agents, briefly reviewing aspects such as character animation and speech processing. The many different approaches for representing dialogue in CAs are discussed in some detail, along with methods for evaluating such agents, emphasizing the important topics of accountability and interpretability. A brief historical overview is given, followed by an extensive overview of various applications, especially in the fields of health and education. We end the chapter by discussing benefits and potential risks regarding the societal impact of current and future CA technology.


Frequent Itemset-driven Search for Finding Minimum Node Separators in Complex Networks

arXiv.org Artificial Intelligence

Finding an optimal set of critical nodes in a complex network has been a long-standing problem in the fields of both artificial intelligence and operations research. Potential applications include epidemic control, network security, carbon emission monitoring, emergence response, drug design, and vulnerability assessment. In this work, we consider the problem of finding a minimal node separator whose removal separates a graph into multiple different connected components with fewer than a limited number of vertices in each component. To solve it, we propose a frequent itemset-driven search approach, which integrates the concept of frequent itemset mining in data mining into the well-known memetic search framework. Starting from a high-quality population built by the solution construction and population repair procedures, it iteratively employs the frequent itemset recombination operator (to generate promising offspring solution based on itemsets that frequently occur in high-quality solutions), tabu search-based simulated annealing (to find high-quality local optima), population repair procedure (to modify the population), and rank-based population management strategy (to guarantee a healthy population). Extensive evaluations on 50 widely used benchmark instances show that it significantly outperforms state-of-the-art algorithms. In particular, it discovers 29 new upper bounds and matches 18 previous best-known bounds. Finally, experimental analyses are performed to confirm the effectiveness of key algorithmic modules of the proposed method.


2021 highlights in science and technology

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Despite the ongoing disruption from COVID-19, many impressive breakthroughs in science and technology occurred this year. Below we have listed our top 20 most viewed blogs of 2021, in reverse order. In June, researchers from Google reported a new machine learning technique for microchip floorplanning that can outperform human experts. In November, the world's first electric and self-piloting container ship – Yara Birkeland – undertook its maiden voyage in the Oslo Fjord. This will cut 1,000 tonnes of CO2 and replace 40,000 trips by diesel-powered trucks a year.


Forecasting: theory and practice

arXiv.org Machine Learning

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases.


CES kicks of with its 'Unveiled' event that showcased Airxom Mask, Morari Medical and iMediSync

Daily Mail - Science & tech

The Consumer Electronics Show (CES) 2022 is underway, kicking off with its'Unveiled' vent on Monday evening that provided a sneak peak into what we can expect to be showcased at the tech conference. Attendees saw several new technologies including a Star Wars-like face mask that protects against pollution and the coronavirus, a wearable that stops premature ejaculation and a brain scanning device that can detect early signs of mental conditions. Monday's event also hosted several innovations that were awarded the CES 2022 Innovation Award, which was given to Kura for its AR glasses and solar shingles that can be nailed directly to the roof. CES, which is held in Las Vegas, is expected to host more than 50,000 people and 2,200 exhibitors, but is also closing its doors a day early due to coronavirus cases spiking around the US. Among those showcasing their latest and greatest innovations was Airxom Mask - a mask with a white plastic shell that covers the mouth and nose.


CASC Newsletter

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The press is abuzz with new hardware announcements from industry, and the latest Top500 and Green500 results are announced with much fanfare and, lately, intrigue. All of this focus on the technology is, of course, well-deserved, but we should never lose sight of the fact that innovative advances in software and algorithms further amplify these technological gains. Reducing the computational complexity of a problem through clever algorithms can provide payoffs far beyond the speed-ups from hardware. In fact, that's really why the possibility quantum computing is so attractive: It's not that the hardware is faster per se; it's that the hardware could support algorithms that have polynomial complexity for problems that, classically, have super-polynomial cost (i.e., exact solutions are impractical to compute for all but the smallest problems). Furthermore, for as impressive as modern supercomputers are, when it comes to using them, they are rather opaque and finicky creatures lurking behind a seemingly simple command line prompt.


Global stakeholders should use AI to mitigate impact of heat islands in cities – TechCrunch

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If human societies do nothing, in just a few decades, the planet could warm to levels it hasn't reached in at least 34 million years, leading to more melting glaciers and floods than ever before -- as well as the dire effect of urban heat waves. In 2021, in the U.S. alone, there were already 18 extreme climate-related disasters with losses exceeding $1 billion each, according to the National Oceanic and Atmospheric Administration. When looking at the world's natural calamities on a consequence and frequency scale, floods and earthquakes have a more devastating effect on people and property, but they occur less frequently than heat waves, which generally take the form of urban heat islands (UHIs). These are also known as heat pockets, which are found across cities' downtown areas, where temperatures are higher than the peripheries. With urbanized areas warming up fast, many more populations globally are bound to face the deadly consequences of the heat-island effect, highlighting urban public health disparities.