IBM and Nasa launch carbon emissions-tracking AI model to monitor climate change

2023-08-09
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A new geospatial foundation AI model designed to improve carbon emission tracking and monitor the impact of climate change has been built by IBM. Using satellite data from Nasa, the open source model is being published on the Hugging Face platform. It is the first time Nasa has collaborated with a tech vendor on such a model.

IBM says foundation models are making it easier to analyse satellite image data and provide more real-time information (Photo: NASA)
IBM says foundation models are making it easier to analyse satellite image data and provide more real-time information. (Photo courtesy of Nasa)

IBM says the model was trained on images from the Harmonized Landsat Sentinel-2 (HLS) satellites from Nasa with images taken over the course of a year. The geospatial foundation model is built on top of enterprise technologies developed by IBM as part of its watsonx.ai platform, launched in May. The platform is being presented by IBM as a solution to a lack of labelled data in both the scientific and enterprise fields.

The models have since been refined on labelled data for flood and burn scar mapping over the same period. With additional fine tuning, the base model can be redeployed for tasks like tracking deforestation, predicting crop yields, or detecting and monitoring greenhouse gases. IBM and Nasa researchers are also working with Clark University to further adapt the open source model for a wider range of applications including time-series segmentation and similarity research.

One of the biggest problems facing companies and climate scientists is a lack of labelled data, or data in an accessible format. A study published earlier this year by Microsoft and Tata Consultancy Services found 80% of businesses were failing to disclose operational emissions targets. This is part due to a lack of data throughout the supply chain and of global trends. IBM argues that AI can help simplify this process.

While foundations models are trained on large datasets of unlabelled data, they can be fine tuned for specific use cases and deployed using labeled data. This means the geospatial model published by IBM can be re-tuned based on company information, or data for a specific scientific use to improve analysis.

While it is being published to Hugging Face, which allows developers to freely share AI models, initially, a commercial version will also be available on watsonx later this year. This, the company says, would allow enterprises to utilise the information in emission tracking and net zero targets.

IBM AI’s role in emission data and tracking

“The essential role of open-source technologies to accelerate critical areas of discovery such as climate change has never been clearer,” said Sriram Raghavan, vice president, IBM Research AI. “By combining IBM’s foundation model efforts aimed at creating flexible, reusable AI systems with Nasa’s repository of Earth-satellite data and making it available on Hugging Face, we can leverage the power of collaboration to implement faster and more impactful solutions that will improve our planet.” 

One of the fine-tuned models already published by Nasa and IBM looks at burn scars across the US. These are marks remaining from wildfires. IBM says the model could be trained with 75% less labelled data than the current state-of-the-art model due to the pre-trained foundation model acting as a base. This will significantly improve tracking and predictions for wildfires and allow the model itself to run more efficiently.

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“AI remains a science-driven field, and science can only progress through information sharing and collaboration,” said Jeff Boudier, head of product and growth at Hugging Face. “This is why open source AI and the open release of models and datasets are so fundamental to the continued progress of AI, and making sure the technology will benefit as many people as possible.”   

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NASA’s chief science data officer Kevin Murphy said foundation models have the potential to change the way observational data is analysed. “By open sourcing the model and making it available to the world, we hope to multiply its impact.” 

Read more: Most AI training data could be synthetic by next year – Gartner

Topics in this article : AI , IBM , NASA

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参考译文
IBM 与 NASA 推出碳排放追踪人工智能模型,用于监测气候变化
IBM 已开发出一种新的地理空间基础人工智能模型,旨在提高碳排放追踪能力并监测气候变化的影响。该模型利用了来自美国国家航空航天局(Nasa)的卫星数据,并以开源形式发布在 Hugging Face 平台上。这是 Nasa 首次与科技供应商合作推出此类模型。IBM 表示,基础模型使得分析卫星图像数据变得更加容易,并能提供更实时的信息。(图片来源:Nasa)IBM 表示,该模型是在 Nasa 的 Harmonized Landsat Sentinel-2(HLS)卫星过去一年拍摄的图像上进行训练的。这个地理空间基础模型基于 IBM 于今年5月推出的 watsonx.ai 平台,该平台是 IBM 企业级技术的一部分,旨在解决科学和企业领域中缺乏标签数据的问题。随后,模型还使用了同一时间段内用于洪水和火灾痕迹地图绘制的标签数据进行了优化。通过进一步的微调,该基础模型可以重新部署用于追踪森林砍伐、预测作物产量,或检测与监测温室气体等任务。IBM 与 Nasa 的研究人员还正与克拉克大学(Clark University)合作,进一步优化这个开源模型,以便在更多应用领域中使用,包括时间序列的分段和相似性研究。公司和气候科学家面临的一个最大问题是缺乏标签数据或数据无法轻松获取。微软和塔塔咨询服务公司今年早些时候发布的一项研究发现,80% 的企业未能披露其运营排放目标。部分原因在于供应链和全球趋势方面的数据不足。IBM 认为,人工智能可以帮助简化这一过程。虽然基础模型是通过未标记的大规模数据集训练而成的,但它们可以针对特定的用例进行微调,并通过标记数据部署。这意味着 IBM 发布的地理空间模型可以根据企业信息或特定科学研究数据进行重新微调,以提升分析效果。尽管该模型已在 Hugging Face 平台上发布,允许开发者自由共享人工智能模型,但 IBM 表示,今年晚些时候,该模型的商业版本也将通过 watsonx 平台推出。这将使企业能够在排放追踪和碳中和目标中利用这些信息。IBM 的 AI 在排放数据和追踪中的作用“开源技术在加速气候变化等关键发现领域中的核心作用,从来没有如此清晰。”IBM 人工智能研究部副总裁 Sriram Raghavan 表示。“通过将 IBM 基础模型项目与 Nasa 的地球卫星数据结合,并在 Hugging Face 上发布,我们可以借助协作的力量,更快、更有效地实施具有更大影响力的解决方案,以改善我们的星球。”NASA 和 IBM 已经发布的一个优化模型,分析了美国范围内的火灾痕迹。这些痕迹是野火留下的印记。IBM 表示,该模型所需的标记数据量比目前最先进的模型减少了75%,因为预训练的基础模型提供了良好的基础。这将显著提高对野火的追踪和预测能力,并使模型本身运行得更高效。来自我们合作伙伴的内容:人工智能将为食品与饮料行业提供一个更具韧性的未来保险公司必须利用数据协作的力量,以实现其商业潜力技术团队如何推动公共部门的可持续发展议程“人工智能仍然是一个以科学为导向的领域,而科学的进步只有通过信息共享和协作才能实现,”Hugging Face 产品与增长主管 Jeff Boudier 表示。“正因如此,开源人工智能以及模型和数据集的开放发布,对人工智能的持续进步至关重要,并确保这项技术能造福尽可能多的人。”查看所有通讯在我们的通讯中注册数据、洞察和分析直接送达您邮箱由 The Tech Monitor 团队提供注册链接Nasa 的首席科学数据官 Kevin Murphy 表示,基础模型有潜力改变观测数据的分析方式。“通过开源模型并将其提供给全世界,我们希望扩大它的影响力。”阅读更多:据 Gartner 预测,到明年,大多数人工智能训练数据可能是合成数据本文主题:人工智能、IBM、Nasa
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