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Artificial Intelligence Is Helping to Spot California Wildfires

#artificialintelligence

As 12,000 lightning strikes pummeled the Bay Area this month, igniting hundreds of fires, fire spotters sprang into action. Their arsenal of tools includes thermal imagery collected by space satellites; real-time feeds from hundreds of mountaintop cameras; a far-flung array of weather stations monitoring temperature, humidity and winds; and artificial intelligence to munch and crunch the vast data troves to pinpoint hot spots. For decades, wildfires in remote regions were spotted by people in lookout towers who scanned the horizon with binoculars for smoke -- a tough and tedious job. They reported potential danger by telephone, carrier pigeon or Morse code signals with a mirror. Now, fire spotting has gone high tech.


Microsoft, Energy Department to Develop Disaster-Response AI Tools

WSJ.com: WSJD - Technology

The First Five Consortium, a nod to the importance of the first five minutes in responding to a natural disaster, aims to build between 10 and 30 different AI-powered systems. Microsoft will provide technological resources, including its Azure cloud for AI model training and inference. Other organizations, including public- and private-sector entities, are expected to participate. The Morning Download delivers daily insights and news on business technology from the CIO Journal team. The announcement comes as California confronts another summer of raging wildfires, while Iowa reels from devastating windstorms.


This Al Gore-supported project uses AI to track the world's emissions in near real time

#artificialintelligence

"Although scientists have a good understanding how much carbon is in the atmosphere, it's surprisingly tough to trace where those emissions come from," says Gavin McCormick, the founder of a nonprofit called WattTime that also makes technology that enables smart devices to automatically reduce emissions. The startup is working with several other climate and tech organizations and the former vice president Al Gore on the new project. Right now, McCormick says, most emissions data is self-reported, and it can sometimes take years for the data to be gathered. "We think that technology, in particular AI and satellites, have the potential to change that pretty profoundly, which can influence sort of any sector that depends on really knowing where emissions are coming from to make good decisions," he says. "The time lag in current data makes it often non-actionable," says Gore, who has been helping structure the project to have the maximum impact on the climate crisis and enlisting partners for financial and strategic support.


Council Post: In EU's Climate Change Fight, The 2 Trillion Euros Was The Easy Part

#artificialintelligence

Bureaucrats -- particularly those from the European Union (EU) -- rarely get the praise they deserve. By their nature, they are reserved, so they do not draw attention to themselves when things go well. When things go poorly, though, they make for a convenient target. So when the EU does something bold, we should give it its due. The EU's boldness in addressing a host of environmental problems head-on is unmatched.


A Survey on Edge Intelligence

arXiv.org Artificial Intelligence

Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis in locations close to where data is captured based on artificial intelligence. The aim of edge intelligence is to enhance the quality and speed of data processing and protect the privacy and security of the data. Although recently emerged, spanning the period from 2011 to now, this field of research has shown explosive growth over the past five years. In this paper, we present a thorough and comprehensive survey on the literature surrounding edge intelligence. We first identify four fundamental components of edge intelligence, namely edge caching, edge training, edge inference, and edge offloading, based on theoretical and practical results pertaining to proposed and deployed systems. We then aim for a systematic classification of the state of the solutions by examining research results and observations for each of the four components and present a taxonomy that includes practical problems, adopted techniques, and application goals. For each category, we elaborate, compare and analyse the literature from the perspectives of adopted techniques, objectives, performance, advantages and drawbacks, etc. This survey article provides a comprehensive introduction to edge intelligence and its application areas. In addition, we summarise the development of the emerging research field and the current state-of-the-art and discuss the important open issues and possible theoretical and technical solutions.


Real-Time Assessment Of Data, ML & AI Can Save The Planet From Climate Emergency

#artificialintelligence

"You must unite behind the science. You must do the impossible. Because giving up can never ever be an option" – Greta Thunberg Most woke Millenials have updated their vocabulary to use terms that more accurately describe the environmental crises facing the world. 'Climate change' has now turned to'climate emergency' – but there are others who haven't yet understood how the situation has worsened over the years. According to a report, seven million people have been displaced globally due to natural disasters including storms and floods between January and June 2019 and the number is estimated to grow more than triple by the end of the year.


Machine Learning Algorithms Help Predict Traffic Headaches

#artificialintelligence

Urban traffic roughly follows a periodic pattern associated with the typical "9 to 5" work schedule. However, when an accident happens, traffic patterns are disrupted. Designing accurate traffic flow models, for use during accidents, is a major challenge for traffic engineers, who must adapt to unforeseen traffic scenarios in real time. A team of Lawrence Berkeley National Lab computer scientists are working with the California Department of Transportation (Caltrans) to use high performance computing (HPC) and machine learning to help improve Caltrans' real-time decision making when incidents occur. The research was done in conjunction with California Partners for Advanced Transportation Technology (PATH), part of UC Berkeley's Institute for Transportation Studies (ITS), and Connected Corridors, a collaborative program to research, develop, and test an Integrated Corridor Management approach to managing transportation corridors in California.


Interview: Abdul Nasser Al Mughairbi, head of digital, Abu Dhabi National Oil Company

#artificialintelligence

The Abu Dhabi National Oil Company (ADNOC) is transforming its business through digital projects that range from deciding where to drill for oil and gas, to helping the company decide where to sell its final products. The state-owned oil company has driven the United Arab Emirates' economy since it was founded almost half a century ago, and its head of digital, Abdul Nasser Al Mughairbi, has been driving digital transformation since 2017. Each day, ADNOC produces three million barrels of oil and processes billions of cubic feet of gas. It has businesses involved in the extraction of raw materials upstream as well as the processing of materials to add value downstream. Add to this the transportation, sales and marketing of oil and gas, and you have a large, complex organisation.


Big Tech's eco-pledges aren't slowing its pursuit of Big Oil

#artificialintelligence

Employee activism and outside pressure have pushed big tech companies like Amazon, Microsoft and Google into promising to slash their carbon emissions. When Microsoft held an all-staff meeting in September, an employee asked CEO Satya Nadella if it was ethical for the company to be selling its cloud computing services to fossil fuel companies, according to two other Microsoft employees who described the exchange on condition they not be named. Such partnerships, the worker told Nadella, were accelerating the oil companies' greenhouse gas emissions. Microsoft and other tech giants have been competing with one another to strike lucrative partnerships with ExxonMobil, Chevron, Shell, BP and other energy firms, in many cases supplying them not just with remote data storage but also artificial intelligence tools for pinpointing better drilling spots or speeding up refinery production. The oil and gas industry is spending roughly $20 billion each year on cloud services, which accounts for about 10% of the total cloud market, according to Vivek Chidambaram, a managing director of Accenture's energy consultancy.


Big Tech's eco-pledges aren't slowing its pursuit of Big Oil

The Japan Times

PROVIDENCE, RHODE ISLAND – Employee activism and outside pressure have pushed big tech companies like Amazon, Microsoft and Google to make promises to slash their carbon emissions. When Microsoft held an all-staff meeting in September, an employee asked CEO Satya Nadella if it was ethical for the company to be selling its cloud computing services to fossil fuel companies, according to two other Microsoft employees who described the exchange on condition they not be named. Such partnerships, the worker told Nadella, were accelerating the oil companies' greenhouse gas emissions. Microsoft and other tech giants have been competing with one another to strike lucrative partnerships with ExxonMobil, Chevron, Shell, BP and other energy firms, in many cases supplying them not just with remote data storage but also artificial intelligence tools for pinpointing better drilling spots or speeding up refinery production. The oil and gas industry is spending roughly $20 billion each year on cloud services, which accounts for about 10 percent of the total cloud market, according to Vivek Chidambaram, a managing director of Accenture's energy consultancy.