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Energy Policy


Can we rely on machine intelligence to fix our climate?

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As more and more industries take on artificial intelligence to solve some of their biggest challenges, can machines help us understand and fix climate change issues? So your phone recognises your face, and your bank can block any transaction unlike your spending habits. And your online supermarket nudges you with their vegan products just because you've bought that oat milk once, while your online movie platform keeps throwing B-movies at you after you watched that soap opera last month. A growing number of our devices and services are relying on artificial intelligence (AI), a technology that continues to branch out and pop up in more and more areas of our lives. Scientists, entrepreneurs, and governments are leveraging AI to explore solutions for some of society's biggest challenges.


Sizing up a green carbon sink

Science

Forests are having their moment. Because trees can vacuum carbon from the atmosphere and lock it away in wood, governments and businesses are embracing efforts to fight climate change by reforesting cleared areas and planting trees on a massive scale. But scientists have warned that the enthusiasm and money flowing to forest-based climate solutions threaten to outpace the science. Two papers published this week seek to put such efforts on a firmer footing. One study quantifies how much carbon might be absorbed globally by allowing forests cleared for farming or other purposes to regrow. The other calculates how much carbon could be sequestered by forests in the United States if they were fully “stocked” with newly planted trees. Each strategy has promise, the studies suggest, but also faces perils. To get a worldwide perspective on the potential of second-growth forests, an international team led by ecologist Susan Cook-Patton of the Nature Conservancy (TNC) assembled data from more than 13,000 previously deforested sites where researchers had measured regrowth rates of young trees. The team then trained a machine-learning algorithm on those data and dozens of variables, such as climate and soil type, to predict and map how fast trees could grow on other cleared sites where it didn't have data. > Can the forest regenerate naturally, or can we do something to help? > > Susan Cook-Patton , the Nature Conservancy A TNC-led team had previously calculated that some 678 million hectares, an area nearly the size of Australia, could support second-growth forests. (The total doesn't include land where trees might not be desirable, such as farmland and ecologically valuable grasslands.) If trees were allowed to take over that entire area, new forests could soak up one-quarter of the world's fossil fuel emissions over the next 30 years, Cook-Patton and colleagues report in Nature . That absorption rate is 32% higher than a previous estimate, based on coarser data, produced by the Intergovernmental Panel on Climate Change. But the total carbon drawdown is 11% lower than a TNC-led team estimated in 2017. The study highlights “what nature can do all on its own,” Cook-Patton says. And it represents “a lightning step forward” in precision compared with earlier studies, says geographer Matthew Fagan of the University of Maryland, Baltimore County, who was not involved in the work. But, Fagan adds, “Natural regrowth is not going to save the planet.” One problem: There is often little economic incentive for private landowners to allow forests to bounce back. Under current policies and market pricing, “nobody will abandon cattle ranching or agriculture for growing carbon,” says Pedro Brancalion, a forest expert at the University of São Paulo in Piracicaba, Brazil. And even when forests get a second life, they often don't last long enough to store much carbon before being cleared again. Fagan notes that even in Costa Rica, renowned as a reforestation champion for doubling its forest cover in recent decades, studies have found that half of second-growth forests fall within 20 years. Given such realities, some advocates are pushing to expand tree planting in existing forests. To boost that concept, a team of researchers at the U.S. Forest Service (USFS) quantified how many additional trees U.S. forests could hold. Drawing on a federal inventory, they found that more than 16% of forests in the continental United States are “understocked”—holding fewer than 35% of the trees they could support. Fully stocking these 33 million hectares of forest would ultimately enable U.S. forests to sequester about 18% of national carbon emissions each year, up from 15% today, the team reports in the Proceedings of the National Academy of Sciences . But for that to happen, the United States would have to “massively” expand its annual tree-planting efforts, from about 1 billion to 16 billion trees, says lead author Grant Domke, a USFS research forester in St. Paul, Minnesota. Cook-Patton says planting trees might make sense in some places, but natural regeneration, where possible, provides more bang for the buck. “For any given site,” she says, “we should always ask ourselves first: ‘Can the forest regenerate naturally, or can we do something to help?’”


How can artificial intelligence help to fight climate change?

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Climate change is the planet's biggest challenge and Artificial Intelligence (AI) could provide the right tools in the global fight. There is still a lot we don't know about planet Earth, and advanced machine learning and AI could offer a'silver bullet' to help us unravel the mysteries of our atmosphere, oceans and cryosphere. AI will become key for scientists in predicting extreme weather, alerting them to severe rainfalls, hurricanes and other events as the world warms. AI is also being developed to track where air pollution is also coming from. In this live chat, you'll meet AI experts who're using the power of artificial intelligence and machine learning to reveal the secrets of our climate and weather systems.


How ensembles can reduce machine learning's carbon footprint - Dataconomy

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Commercial and industrial applications of artificial intelligence and machine learning are unlocking economic opportunities, transforming the way we do business, and even helping to solve complex social and environmental problems. In fact, generative applications of this technology have become tools for environmental sustainability. With machine learning's capability to analyze and make predictions using massive pools of data, these applications are now able to accurately model climate change and fluctuations, so that energy infrastructures and energy consumption can be re-engineered accordingly. Ironically, training large-scale models via deep neural networks requires vast computational power. It also produces a great deal of thermal energy from each of the associated graphics processing units (GPUs) or tensor processing units (TPUs) used.


Breakthrough Days - AI for Good Global Summit 2020

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The 2020 Breakthrough Days event aims to generate and fuel meaningful projects in each of this year's three AI for Good Global Summit domains – Gender, Food, and Pandemics – that will advance progress on the UN Sustainable Development Goals (SDGs). Hear from keynote speakers and participate in interactive workshops designed to launch solutions to some of the world's greatest challenges. "Beneficial AI to advance SDGs" Keynote Speaker: Stuart Russell, Professor of Computer Science at UC Berkeley Moderator: Amir Banifatemi, Chief Innovation Officer, XPRIZE; Chair of the AI for Good Programme Committee In an effort to allow teams to prepare for main stage presentations on Monday and Tuesday, we have designated Friday 25 September as a time for teams and attendees to converse individually. Please use the AI for Good workspace on Slack to continue the conversation. Join us on Monday 28 September as we hear from teams in each of this year's AI for Good Breakthrough Track "What is AI for Good Anyway?" Keynote Speaker: Sasha Luccioni, Postdoctoral Researcher – AI for Humanity, Université de Montréal, Mila – Quebec AI Institute Moderator: Amir Banifatemi, Chief Innovation Officer, XPRIZE; Chair of the AI for Good Programme Committee Keynote Address Keynote Speaker: Peter H. Diamandis, entrepreneur, founder and executive chairman of the XPRIZE Foundation, Bestselling author of "Abundance – The Future Is Better Than You Think" Moderator: Amir Banifatemi, Chief Innovation Officer, XPRIZE; Chair of the AI for Good Programme Committee Interested individuals and teams from around the world have submitted project ideas to the Gender, Food and Pandemics Breakthrough Tracks. After being mentored by world-renowned experts and Brain Trusts, the top three finalists in each domain have been selected to present their project proposals in a series of interactive workshops during the Breakthrough Days event.


Global Big Data Conference

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Amazon's 2019 Climate Pledge calls for a commitment to net zero carbon across their businesses by 2040. Since then, the company has reduced the weight of their outbound packaging by 33%, eliminating 915,000 tons of packaging material worldwide, or the equivalent of over 1.5 billion shipping boxes. With less packaging used throughout the supply chain, volume per shipment is reduced and transportation becomes more efficient. The cumulative impact across Amazon's enormous network is a dramatic reduction in carbon emissions. To make this happen, the customer packaging experience team partnered with AWS to build a machine learning solution powered by Amazon SageMaker.


MusicalAmerica - Press Releases

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"Rich and vibrant in texture, it again draws on this ensemble's deep palette of vocal colours" – Gramophone Magazine New York, NY (September 17, 2020) -- GRAMMY-nominated vocal quartet New York Polyphony announces the release of Aleph Earth, a groundbreaking audiovisual work developed in collaboration with the University of Oregon's Artificial Intelligence Creative Practice Research Group (AICP). A poignant statement on the global climate crisis, the project uses as a soundtrack New York Polyphony's world premiere recording of Spanish Renaissance composer Francisco de Peñalosa's Lamentationes Jeremiae Feria V from their critically acclaimed September 2019 album on BIS Records, Lamentationes. Aleph Earth premiered at the 2020 Currents New Media Festival in August and September, and is available for presenters to book as a virtual concert or educational event through Opus 3 Artists. In creating the 12-minute visual presentation, AICP drew inspiration from Lamentationes Feria V's compositional complexity, as well as the subject matter of the text. "It's a setting of the poetic reflections of the Prophet Jeremiah on the destruction of Jerusalem in 586 BC," explains New York Polyphony's bass and University of Oregon music professor Craig Phillips.


Can AI solve the climate crisis?

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The numbers are well known by now: the world has warmed by 1.1 degrees Celsius compared to pre-Industrial levels at the time of writing, and is on track for the worst case scenarios projected. This year, we saw astonishing temperature records in the Arctic Circle and an ever ongoing loss of biodiversity. Simultaneously, we've seen massive leaps in technology. Artificial intelligence, in particular, has captured worldwide attention: from deep fakes and AI twitter bots influencing elections, to its increased use by companies to gain a competitive edge. We're at the start of the fourth industrial revolution, driven by AI; fundamentally impacting our lives and society as a whole.


How Amazon is using machine learning to eliminate 915,000 tons of packaging

#artificialintelligence

Amazon's 2019 Climate Pledge calls for a commitment to net zero carbon across their businesses by 2040. Since then, the company has reduced the weight of their outbound packaging by 33%, eliminating 915,000 tons of packaging material worldwide, or the equivalent of over 1.5 billion shipping boxes. With less packaging used throughout the supply chain, volume per shipment is reduced and transportation becomes more efficient. The cumulative impact across Amazon's enormous network is a dramatic reduction in carbon emissions. To make this happen, the customer packaging experience team partnered with AWS to build a machine learning solution powered by Amazon SageMaker.


Has Artificial Intelligence helped meteorologists predict future weather patterns?

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The process of predicting accurate weather patterns has always been a challenge for meteorologists. The complexity is in observing and processing vast amounts of data, and because most of the weather stations would never be able to collect, process and store so much information. With traditional models, the systems have to read huge data sets from several weather stations that would take many hours to predict the weather accurately. The good news is artificial intelligence (AI) has been able to outperform these traditional methods by streamlining the weather forecasting process while bringing accuracy and reliability in assessing weather reports. The amount of data received from global sensors, weather stations, satellites, and radar, is staggering. The estimation often goes well beyond trillions of data points and is expected to continue to grow.