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Lambda在线 > 新云天气象 > 机器学习从业者如何应对气候变化?

机器学习从业者如何应对气候变化?

新云天气象 2020-09-16



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机器学习从业者如何应对气候变化?
文章来源:venturebeat.com
What ML practitioners are doing about climate change?
机器学习从业者如何应对气候变化?

机器学习从业者如何应对气候变化?
旧金山的Eli Harik戴着口罩,同时抬头看着挂在加州旧金山市中心Embarcadero上空的深橙色天空。2020年9月9日星期三,由于加州和俄勒冈州的多处野火燃烧.图片来源:Jessica Christian/The San Francisco Chronicle via Getty Images
(中译内容由DeepL支撑)
本周在人工智能领域发生了很多事情。卫报撰文,用GPT-3再次证明,无论OpenAI为训练和创建语言模型付出了多少代价,免费的营销可能更有价值。在输掉与五角大楼的JEDI云合同上诉后,亚马逊任命Keith Alexander为董事会成员,他曾在2013年监督爱德华-斯诺登泄露的国家安全局大规模监控。而波特兰通过了美国历史上最严格的面部识别禁令,禁止政府和企业使用该技术。
然而,《AI周刊》试图深入时代潮流,突出人们心中的问题。本周毫无疑问是美国西部地区笼罩的烟雾和气候变化的根本问题
周三在湾区,烟雾的密度有效地遮住了太阳,投下了暗橙色或红色的光。诡异的场景引来了《银翼杀手2049》等科幻片的对比。
机器学习从业者如何应对气候变化?
当天,原本预报气温会达到八九十度(华氏温度)的高位,但却降到了60度左右,单日气温下降了近30度。白天的大部分时间里,路灯一直亮着,迷迷糊糊的人们在白天的时候都觉得是晚上。对一些人来说,旧金山变成火星标志着一个突破点,是在数周的烟雾和热浪之后的最后压力。所有的一切都在持续的努力之上,以建立种族正义,经济复苏,以及治愈COVID-19。
快速回顾一下。加州北部8月发生的复杂火灾 是该州历史上最大的火灾。CalFire在今天的每日报告中表示,今年燃烧的面积是2019年同期的26倍。周三,国家气象局湾区一度在推特上表示,条件 "超出了我们的模型"。在俄勒冈州,州长凯特-布朗昨天表示,三天内有90万英亩土地被烧毁。她说,在典型的一年中,该州因火灾损失了50万英亩土地。今天,不健康的空气质量绵延整个西海岸,从圣地亚哥到西雅图。周五,波特兰录得全球最差的空气质量。在邻近的州,盐湖城录得历史上最差的空气质量,丹佛居民也受到影响。
自然灾害造成的破坏和健康风险只是看到气候变化后果的一种方式。全球环境也呈现出紧张的状态。世界野生动物基金会在其监测21,000种动物的年度《生活星球》报告中说,过去50年中,野生动物的数量减少了近70%。这种生物多样性的丧失对全球粮食供应构成了威胁。
那么我们能做些什么呢?气候变化人工智能是寻求应用机器学习来解决这一问题的主要举措之一。这个由AI研究人员组成的小组正在探索解决气候变化以及人类流离失所和粮食不安全等相邻问题的方案。在过去的一个月里,小组成员讨论了什么样的创业公司可以应对气候变化,他们正在收集研究人员的数据集愿望清单,为用于训练模型和解决问题的数据提供信息。
2019年6月,来自十多个组织的研究人员联手发布了一篇有800多篇参考文献的论文,试图涵盖机器学习可以帮助应对气候变化的大量方法。论文全文和互动摘要中的重点领域包括电力系统和智能城市的实用模型,以及具有不确定影响的长期项目,如二氧化碳封存或行星控制系统工程。
在去年NeurIPS会议上举行的气候变化人工智能研讨会上,研究人员谈到了将人工智能打造成零碳产业的可能性,并探讨了让机器学习社区将更多注意力放在气候变化上的文化变革。研究人员还分发了用于计算机器学习模型碳足迹的计算器。另一场气候变化人工智能研讨会将于12月在NeurIPS举行。
还有WattTime的工作,WattTime是一个非营利组织,它根据可再生能源的可用时间,自动确定电动汽车、恒温器和电器的活动时间,从而减少家庭的碳足迹。确定这些时间的算法是利用美国环保局的连续污染监测系统的数据进行训练的。WattTime的创建者Gavin McCormick告诉VentureBeat,这项技术目前在加州可用,作为自发电激励计划的一部分,如今加州约有33%的电力来自可再生能源。
"没有人知道美国的连续排放监测系统,但它从70年代开始就已经上线了,这也是为什么像我这样的组织可以编写越来越复杂的人工智能算法来整合更多的可再生能源,并做我们所做的事情,"McCormick在电话中告诉VentureBeat。
去年,WattTime获得了Google.org的AI影响力挑战赛的资助,看看计算机视觉是否能从卫星图像中追踪美国以外的发电厂排放。7月,WattTime联合9个组织和Al Gore成立了Climate Trace,该组织希望追踪全球主要经济部门的排放,比如发电厂和航运业。Climate Trace的目标是在2021年6月之前向公众提供这些数据,为下一轮国际气候谈判做准备。
在我成长的过程中,科技可以改变世界的想法是一个田园诗般的梦想。在过去的几年里,有相当一部分人感到失望,部分原因是初创公司解决了不存在的问题,大规模监控,不同的初创公司创始人普遍缺乏资金,以及大科技公司的一系列违法行为,这里无法一一列举。
但如果你对最近发生的种种灾难感到无奈,想做点什么来改变现状,众多项目(包括上述项目)都需要志愿者。根据耶鲁大学4月发布的一项气候变化沟通调查,人们已经准备好参与到迫使民选官员应对气候变化的努力中来。
本周,"天启 "这个词出现的频率对我来说有点高。人们很容易感觉到事情是可怕的、混乱的、失控的--因为它们确实是--但没有人应该相信他们无法影响变化。单纯的技术并不能拯救我们。人们必须投票给那些政策认真对待气候变化的民选官员,我们也需要采取个人行动来支持这种变化。
知道其他关于气候变化和机器学习的交叉项目吗?请将新闻线索发送给Khari Johnson和Kyle Wiggers以及人工智能编辑Seth Colaner--并且一定要订阅《人工智能周报》,并将我们的人工智能频道加入书签。
感谢您的阅读。
Khari Johnson
高级AI撰稿人

目前已有130+位成员,
快快加入吧!


英文原文
A lot happened this week in the AI space. The Guardian wrote an article with GPT-3 and again demonstrated that no matter what OpenAI paid to train and create the language model, the free marketing might be worth more. After losing the JEDI cloud contract appeal with the Pentagon, Amazon appointed to its board Keith Alexander, who oversaw the National Security Agency mass surveillance revealed by Edward Snowden leaks in 2013. And Portland passed the strictest facial recognition bans in U.S. history, outlawing government and business use of the technology.
However, AI Weekly attempts to reach into the zeitgeist and highlight the issues on people’s minds. This week without question it’s the smoke that has hung over the western United States and the underlying problem of climate change.
In the Bay Area Wednesday, the density of the smoke effectively blocked out the sun and cast a dark orange or red light. The eerie scene drew comparisons to Blade Runner 2049, among other sci-fi parallels.
The same day, the temperature was forecast to reach the high 80s or 90s but instead dropped to around 60, a nearly 30-degree decline in a single day. Street lights stayed on for most of the daylight hours, and disoriented people felt like it was night during the middle of the day. For some, San Francisco turning into Mars marked a breaking point, the final stressor after weeks of smoke and a heat wave. All on top of ongoing efforts to establish racial justice, economic recovery, and a cure to COVID-19.
A quick recap: The August complex fire in northern California is now the largest in state history. CalFire said in its daily report today that 26 times as many acres have burned this year as the same time period in 2019. At one point on Wednesday, National Weather Service Bay Area tweeted that conditions were “beyond our models.” In Oregon, Governor Kate Brown said yesterday that 900,000 acres burned in three days. In a typical year, she said, the state loses 500,000 acres to fire. Today, unhealthy air quality stretched the entirety of the West Coast, from San Diego to Seattle. On Friday, Portland recorded the worst air quality in the world. In neighboring states, Salt Lake City recorded historically bad air quality, and Denver residents were impacted as well.
The destruction and health risks caused by natural disasters is just one way to see the consequences of climate change. The global environment is also showing strain: The World Wildlife Fund said in its annual Living Planet report monitoring 21,000 species of animals that wildlife population levels are down nearly 70% in the past 50 years. That loss of biodiversity poses a threat to global food supplies.
So what can we do about it? Climate Change AI is one of the major initiatives seeking to apply machine learning to the problem. The group of AI researchers is exploring solutions to climate change and adjacent problems like human displacement and food insecurity. In the past month, group members have discussed the kinds of startups that can combat climate change, and they are assembling a data set wish list from researchers to inform the data used to train models and solve problems.
In June 2019, researchers from more than a dozen organizations teamed up to release a paper with over 800 references that attempts to cover the vast swath of ways machine learning can help combat climate change. Areas of focus in the full paper and interactive summary include practical models for electric systems and smart cities, as well as long-term projects with uncertain impact, like CO2 sequestration or engineering a planetary control system.
At a Climate Change AI workshop held at the NeurIPS conference last year, researchers talked about the possibility of making AI a zero-carbon industry and looked at cultural changes that would allow the machine learning community to focus more of its attention on climate change. Researchers also circulated calculators for figuring out the carbon footprint of a machine learning model. Another Climate Change AI workshop is scheduled to take place at NeurIPS in December.
There’s also the work of WattTime, a nonprofit organization that reduces a household’s carbon footprint by automating when electric vehicles, thermostats, and appliances are active based on when renewable energy is available. Algorithms to determine those times are trained using data from the EPA’s continuous pollution monitoring system. The tech is currently available in California, where about 33% of power today comes from renewable energy as part of the Self-Generation Incentive Program, WattTime creator Gavin McCormick told VentureBeat.
“Nobody knows about the U.S. continuous emissions monitoring system, but it’s been live since the ’70s, and it’s why organizations like mine can write increasingly sophisticated AI algorithms to integrate more renewable energy and do what we do,” McCormick told VentureBeat in a phone call.
Last year, WattTime received a grant from Google.org’s AI Impact Challenge to see whether computer vision can track power plant emissions outside the U.S. from satellite imagery. In July, WattTime joined nine organizations and Al Gore to form Climate Trace, a group that wants to trace emissions around the world in major sectors of the economy, like power plants and shipping. Climate Trace’s goal is to make that data available to the public by June 2021, leading up to the next round of international climate negotiations.
When I was growing up, the idea that technology could change the world was an idyllic dream. In years past, there’s been a fair share of disillusionment, in part due to startups solving problems that don’t exist, mass surveillance, a general lack of funding for diverse startup founders, and a laundry list of transgressions by Big Tech companies too long to name here.
But if you’re feeling helpless about all the recent disasters and want to do something to change things, numerous projects (including the above) need volunteers. According to a Yale Climate Change Communication survey released in April, people are ready to get involved in efforts to compel elected officials to address climate change.
The word apocalypse came up a little too often for my liking this week. It’s easy to feel things are dire, chaotic, and out of control — because they are — but nobody should believe there’s nothing they can do to affect change. Technology alone won’t save us. People have to vote for elected officials whose policies take climate change seriously, and we also need to take individual action to support that change.
Know any other projects at the intersection of climate change and machine learning? Send news tips to Khari Johnson and Kyle Wiggers and AI editor Seth Colaner — and be sure to subscribe to the AI Weekly newsletter and bookmark our AI Channel.
Thanks for reading,
Khari Johnson
Senior AI Staff Writer

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