{"id":3343,"date":"2024-02-05T17:42:24","date_gmt":"2024-02-05T17:42:24","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2024\/02\/05\/new-study-cites-ai-as-strategic-tool-to-combat-climate-change\/"},"modified":"2024-02-05T17:42:24","modified_gmt":"2024-02-05T17:42:24","slug":"new-study-cites-ai-as-strategic-tool-to-combat-climate-change","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2024\/02\/05\/new-study-cites-ai-as-strategic-tool-to-combat-climate-change\/","title":{"rendered":"New Study Cites AI as Strategic Tool to Combat Climate Change"},"content":{"rendered":"<div id=\"bsf_rt_marker\">\n<p>A new study underscores the potential of AI and <a href=\"https:\/\/blogs.nvidia.com\/blog\/what-is-accelerated-computing\/\">accelerated computing<\/a> to deliver <a href=\"https:\/\/www.nvidia.com\/en-us\/glossary\/energy-efficiency\/\">energy efficiency<\/a> and combat climate change, efforts in which NVIDIA has long been deeply engaged.<\/p>\n<p>The <a href=\"https:\/\/itif.org\/publications\/2024\/01\/29\/rethinking-concerns-about-ai-energy-use\/\">study<\/a>, called \u201cRethinking Concerns About AI\u2019s Energy Use,\u201d provides a well-researched examination into how AI can \u2014 and in many cases already does \u2014 play a large role in addressing these critical needs.<\/p>\n<p>Citing dozens of sources, the study from the Information Technology and Innovation Foundation (ITIF), a Washington-based think tank focused on science and technology policy, calls for governments to accelerate adoption of AI as a significant new tool to drive energy efficiency across many industries.<\/p>\n<p>AI can help \u201creduce carbon emissions, support clean energy technologies, and address climate change,\u201d it said.<\/p>\n<h2><b>How AI Drives Energy Efficiency<\/b><\/h2>\n<p>The report documents ways machine learning is already helping many sectors reduce their impact on the environment.<\/p>\n<p>For example, it noted:<\/p>\n<ul>\n<li>Farmers are using AI to lessen their use of fertilizer and water.<\/li>\n<li>Utilities are adopting it to make the electric grid more efficient.<\/li>\n<li>Logistics operations use it to optimize delivery routes, reducing the fuel consumption of their fleets.<\/li>\n<li>Factories are deploying it to reduce waste and increase energy efficiency.<\/li>\n<\/ul>\n<p>In these and many other ways, the study argues that AI advances energy efficiency. So, it calls on policymakers \u201cto ensure AI is part of the solution, not part of the problem, when it comes to the environment.\u201d<\/p>\n<p>It also recommends adopting AI broadly across government agencies to \u201chelp the public sector reduce carbon emissions through more efficient digital services, smart cities and buildings, intelligent transportation systems, and other AI-enabled efficiencies.\u201d<\/p>\n<h2><b>Reviewing the Data on AI<\/b><\/h2>\n<p>The study\u2019s author, Daniel Castro, saw in current predictions about AI a repeat of exaggerated forecasts that emerged during the rise of the internet more than two decades ago.<\/p>\n<figure id=\"attachment_69584\" aria-describedby=\"caption-attachment-69584\" class=\"wp-caption alignleft\"><a href=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2024\/02\/Daniel-Castro-ITIF-scaled.jpg\"><\/p>\n<p><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2024\/02\/Daniel-Castro-ITIF-150x150.jpg\" alt=\"Daniel Castro, ITIF\" width=\"150\" height=\"150\"><\/p>\n<p><\/a><figcaption id=\"caption-attachment-69584\" class=\"wp-caption-text\">Daniel Castro<\/figcaption><\/figure>\n<p>\u201cPeople extrapolate from early studies, but don\u2019t consider all the important variables including improvements you see over time in digitalization like energy efficiency,\u201d said Castro, who leads ITIF\u2019s Center for Data Innovation.<\/p>\n<p>\u201cThe danger is policymakers could miss the big picture and hold back beneficial uses of AI that are having positive impacts, especially in regulated areas like healthcare,\u201d he said.<\/p>\n<p>\u201cFor example, we\u2019ve had electronic health records since the 1980s, but it took focused government investments to get them deployed,\u201d he added. \u201cNow AI brings big opportunities for decarbonization across the government and the economy.\u201d<\/p>\n<h2><b>Optimizing Efficiency Across Data Centers<\/b><\/h2>\n<p>Data centers of every size have a part to play in maximizing their energy efficiency with AI and accelerated computing.<\/p>\n<p>For instance, NVIDIA\u2019s AI-based weather-prediction model, <a href=\"https:\/\/arxiv.org\/abs\/2202.11214\">FourCastNet<\/a>, is about 45,000x faster and consumes 12,000x less energy to produce a forecast than current techniques. That promises efficiency boosts for supercomputers around the world that run continuously to provide regional forecasts, Bjorn Stevens, director of the Max Planck Institute for Meteorology, said in <a href=\"https:\/\/blogs.nvidia.com\/blog\/ai-efficient-weather-predictions\/\">a blog<\/a>.<\/p>\n<p>Overall, data centers could save a whopping 19 terawatt-hours of electricity a year if all AI, high performance computing and networking offloads were run on GPU and <a href=\"https:\/\/blogs.nvidia.com\/blog\/whats-a-dpu-data-processing-unit\/\">DPU<\/a> accelerators instead of CPUs, according to <a href=\"https:\/\/blogs.nvidia.com\/blog\/what-is-green-computing\/\">NVIDIA\u2019s calculations<\/a>. That\u2019s the equivalent of the energy consumption of 2.9 million passenger cars driven for a year.<\/p>\n<p>Last year, the U.S. Department of Energy\u2019s lead facility for open science documented its advances with accelerated computing.<\/p>\n<p>Using <a href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/a100\/\">NVIDIA A100 Tensor Core GPUs<\/a>, energy efficiency improved 5x on average across four key scientific applications <a href=\"https:\/\/blogs.nvidia.com\/blog\/gpu-energy-efficiency-nersc\/\">in tests<\/a> at the National Energy Research Scientific Computing Center. An application for weather forecasting logged gains of nearly 10x.<\/p>\n<figure id=\"attachment_69588\" aria-describedby=\"caption-attachment-69588\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2024\/02\/Energy-efficiency-of-NVIDIA-GPUs-over-time.jpg\"><\/p>\n<p><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/blogs.nvidia.com\/wp-content\/uploads\/2024\/02\/Energy-efficiency-of-NVIDIA-GPUs-over-time-672x365.jpg\" alt=\"Chart showing the energy efficiency of GPUs has increased dramatically over time.\" width=\"672\" height=\"365\"><\/p>\n<p><\/a><figcaption id=\"caption-attachment-69588\" class=\"wp-caption-text\">The energy efficiency of GPUs has increased dramatically over time.<\/figcaption><\/figure>\n<h2><b>AI, Accelerated Computing Advance Climate Science<\/b><\/h2>\n<p>The combination of accelerated computing and AI is creating new scientific instruments to help understand and combat climate change.<\/p>\n<p>In 2021, NVIDIA <a href=\"https:\/\/blogs.nvidia.com\/blog\/earth-2-supercomputer\/\">announced<\/a> Earth-2, an initiative to build a <a href=\"https:\/\/www.nvidia.com\/en-us\/omniverse\/solutions\/digital-twins\/\">digital twin<\/a> of Earth on a supercomputer capable of simulating climate on a global scale. It\u2019s among a handful of similarly <a href=\"https:\/\/blogs.nvidia.com\/blog\/digital-twins-climate-collaboration\/\">ambitious efforts<\/a> around the world.<\/p>\n<p>An example is <a href=\"https:\/\/www.ecmwf.int\/en\/about\/what-we-do\/environmental-services-and-future-vision\/destination-earth\">Destination Earth<\/a>, a pan-European project to create digital twins of the planet, that\u2019s using accelerated computing, AI and \u201ccollaboration on an unprecedented scale,\u201d said the project\u2019s leader, Peter Bauer, a veteran with more than 20 years at Europe\u2019s top weather-forecasting center.<\/p>\n<p>Experts in the utility sector agree AI is key to advancing sustainability.<\/p>\n<p>\u201cAI will play a crucial role maintaining stability for an electric grid that\u2019s becoming exponentially more complex with large numbers of low-capacity, variable generation sources like wind and solar coming online, and two-way power flowing into and out of houses,\u201d said Jeremy Renshaw, a senior program manager at the Electric Power Research Institute, an independent nonprofit that collaborates with more than 450 companies in 45 countries, in <a href=\"https:\/\/blogs.nvidia.com\/blog\/ai-energy-grids\/\">a blog<\/a>.<\/p>\n<p>Learn more about <a href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/sustainable-computing\/\">sustainable computing<\/a> as well as <a href=\"https:\/\/images.nvidia.com\/aem-dam\/Solutions\/documents\/FY2023-NVIDIA-Corporate-Responsibility-Report-1.pdf\">NVIDIA\u2019s commitment<\/a> to use 100% renewable energy starting in fiscal year 2025. And watch the video below for more on how AI is accelerating efforts to combat climate change.<\/p>\n<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>https:\/\/blogs.nvidia.com\/blog\/ai-energy-study\/<\/p>\n","protected":false},"author":0,"featured_media":3344,"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\/3343"}],"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=3343"}],"version-history":[{"count":0,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/3343\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media\/3344"}],"wp:attachment":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media?parent=3343"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/categories?post=3343"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/tags?post=3343"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}