{"id":3395,"date":"2024-03-19T17:58:31","date_gmt":"2024-03-19T17:58:31","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2024\/03\/19\/climate-pioneers-3-startups-harnessing-nvidias-ai-and-earth-2-platforms\/"},"modified":"2024-03-19T17:58:31","modified_gmt":"2024-03-19T17:58:31","slug":"climate-pioneers-3-startups-harnessing-nvidias-ai-and-earth-2-platforms","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2024\/03\/19\/climate-pioneers-3-startups-harnessing-nvidias-ai-and-earth-2-platforms\/","title":{"rendered":"Climate Pioneers: 3 Startups Harnessing NVIDIA\u2019s AI and Earth-2 Platforms"},"content":{"rendered":"<div id=\"bsf_rt_marker\">\n<p>To help mitigate climate change \u2014 one of humanity\u2019s greatest challenges \u2014 researchers are turning to AI and <a href=\"https:\/\/blogs.nvidia.com\/blog\/what-is-green-computing\/\" target=\"_blank\" rel=\"noopener\">sustainable computing<\/a> to accelerate and operationalize their work.<\/p>\n<p>At this week\u2019s <a href=\"https:\/\/www.nvidia.com\/gtc\/\" target=\"_blank\" rel=\"noopener\">NVIDIA GTC<\/a> global AI conference, startups, enterprises and scientists are highlighting their environmental sustainability initiatives and latest climate innovations. Many are using <a href=\"https:\/\/www.nvidia.com\/en-us\/high-performance-computing\/earth-2\/\" target=\"_blank\" rel=\"noopener\">NVIDIA Earth-2<\/a>, a full-stack, open platform for accelerating climate and weather simulation and predictions.<\/p>\n<p>Earth-2 comprises GPU-accelerated numerical weather and climate prediction models, including ICON and IFS; state-of-the-art AI-driven weather models, such as FourCastNet, GraphCast and Deep Learning Weather Prediction, offered through the <a href=\"https:\/\/developer.nvidia.com\/modulus\" target=\"_blank\" rel=\"noopener\">NVIDIA Modulus<\/a> framework; and large-scale, interactive, high-resolution data visualization and simulation enabled by the <a href=\"https:\/\/www.nvidia.com\/en-us\/omniverse\/\" target=\"_blank\" rel=\"noopener\">NVIDIA Omniverse<\/a> platform. These capabilities are also available via cloud APIs, or application programming interfaces.<\/p>\n<p>Various members of <a href=\"https:\/\/www.nvidia.com\/en-us\/startups\/\" target=\"_blank\" rel=\"noopener\">NVIDIA Inception<\/a> \u2014 a free, global program for cutting-edge startups \u2014 are pioneering climate AI advancements with Earth-2. It\u2019s critical work, as extreme-weather events are <a href=\"https:\/\/authors.library.caltech.edu\/records\/k959a-53q45\" target=\"_blank\" rel=\"noopener\">expected<\/a> to take a million lives and cost $1.7 trillion per year by 2050.<\/p>\n<h2><b>Tomorrow.io Powers Weather Predictions of Tomorrow<\/b><\/h2>\n<p><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2024\/03\/tomorrow.io_.jpeg\" alt=\"\" width=\"512\" height=\"358\"><\/p>\n<p>Boston-based <a href=\"http:\/\/tomorrow.io\" target=\"_blank\" rel=\"noopener\">Tomorrow.io<\/a> provides actionable, weather-related insights to countries, businesses and individuals by applying advanced AI and machine learning models to a proprietary global dataset collected from satellites, radar and other sensors. Its weather intelligence and climate adaptation platform delivers high-resolution, accurate weather forecasts across time zones for both short- and long-term projections.<\/p>\n<p>The startup is using Earth-2 to study the potential impacts of its suite of satellites on global model forecasts. By conducting observing-system simulation experiments, or OSSEs, with Earth-2 AI forecast models, Tomorrow.io can identify the optimal configurations of satellites and other instruments to improve weather-forecasting conditions. The work ultimately aims to offer users precision and simplicity, helping them easily understand complex weather situations and make the right operational decisions at the right time.<\/p>\n<p>Learn more about Tomorrow.io\u2019s work with Earth-2 by joining the GTC session, \u201c<a href=\"https:\/\/www.nvidia.com\/gtc\/session-catalog\/?search=tenika&amp;tab.allsessions=1700692987788001F1cG&amp;search=tenika#\/session\/1696445353484001C0A2\" target=\"_blank\" rel=\"noopener\">Global Strategies: Startups, Venture Capital, and Climate Change Solutions<\/a>,\u201d taking place today, March 19, at 3 p.m. PT, at the San Jose Convention Center and online.<\/p>\n<h2><b>ClimaSens Advances Flood-Risk Management With AI<\/b><\/h2>\n<p><a href=\"https:\/\/climasens.com\/\" target=\"_blank\" rel=\"noopener\">ClimaSens<\/a>, based in Melbourne, Australia, and New York, fuses historical, real-time and future climate and weather information using advanced AI models. FloodSens, its upcoming flood risk analysis model, informs clients about the probability of flooding from rainfall, offering high-resolution assessments of flash flooding, riverine flooding and all types of flooding in between.<\/p>\n<p><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2024\/03\/FloodSens-672x210.png\" alt=\"\" width=\"672\" height=\"210\"><\/p>\n<p>FloodSens, now in beta, was developed using Earth-2 APIs and the FourCastNet model for high-fidelity, physically accurate representations of future weather conditions, as well as an ensemble of other models for assessing the probabilities of low-likelihood, high-impact flooding events. Through this work, the startup aims to enable a more resilient, sustainable future for communities worldwide.<\/p>\n<h2><b>North.io Garners Ocean Insights With AI and Accelerated Modeling<\/b><\/h2>\n<p><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2024\/03\/north.io_.jpeg\" alt=\"\" width=\"512\" height=\"288\"><\/p>\n<p>Based in Kiel, Germany, <a href=\"http:\/\/north.io\" target=\"_blank\" rel=\"noopener\">north.io<\/a> is helping to map the Earth\u2019s largest carbon sink: oceans. Only about 25% of the ocean floor \u2014 a critical source of the world\u2019s renewable energy and food security \u2014 has been mapped so far.<\/p>\n<p>North.io is collecting and analyzing massive amounts of data from autonomous underwater vehicles (AUVs) and making it accessible, shareable, visualizable and understandable for users across the globe through its TrueOcean platform.<\/p>\n<p>Using Earth-2 APIs, north.io is developing AI weather forecasts for intelligent operational planning, system management and risk assessment for its AUVs. The combination of high-precision weather modeling and the use of autonomous systems drastically reduces human safety risks in rough, offshore environments.<\/p>\n<p><i>Learn more about the latest AI, <\/i><a href=\"https:\/\/www.nvidia.com\/gtc\/sessions\/hpc\/\" target=\"_blank\" rel=\"noopener\"><i>high performance computing<\/i><\/a><i> and <\/i><a href=\"https:\/\/www.nvidia.com\/gtc\/sessions\/sustainable-computing\/\" target=\"_blank\" rel=\"noopener\"><i>sustainable computing<\/i><\/a><i> advancements for climate research at GTC, running through Thursday, March 21.<\/i><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>https:\/\/blogs.nvidia.com\/blog\/climate-startups-ai-earth-2\/<\/p>\n","protected":false},"author":0,"featured_media":3396,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3],"tags":[],"_links":{"self":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/3395"}],"collection":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/comments?post=3395"}],"version-history":[{"count":0,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/3395\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media\/3396"}],"wp:attachment":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media?parent=3395"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/categories?post=3395"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/tags?post=3395"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}