Humans know more about deep space than we know about Earth��s deepest oceans. But scientists have plans to change that��with the help of AI. ��We have better maps of Mars than we do of our own exclusive economic zone,�� said Nick Rotker, chief BlueTech strategist at MITRE, a US government-sponsored nonprofit research organization. ��Around 70% of the Earth is covered in water and we��ve explored��
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At GTC 2025, a panel of industry leaders from across the tech ecosystem shared how they��re using AI to mitigate and prepare customers for the increasingly disruptive impact of climate change. Tenika Versey, the global head of sustainable futures for the NVIDIA Inception program, led a panel that included Colin le Duc, founding partner at Generation Investment Management, Suzanne DiBianca��
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From hyperlocal forecasts that guide daily operations to planet-scale models illuminating new climate insights, the world is entering a new frontier in weather and climate resilience. The combination of space-based observations and GPU-accelerated AI delivers near-instant, context-rich insights to enterprises, governments, researchers, and solution providers worldwide. It also marks a rare��
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Inland flooding causes significant economic and societal impacts annually. Of the eight natural disasters costing the insurance industry over $1 billion in 2024, six of these were categorized as flood events, with three of these occurring in Europe alone. Catastrophe modeling aims to quantify the risk of flood events to enable preparedness for the financial and insurance industries.
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Large ensembles are essential for predicting rare, high-impact events that cannot be fully understood through historical data alone. By simulating thousands of potential scenarios, they provide the statistical depth necessary to assess risks, prepare for extremes, and build resilience against once-in-a-century disasters. Global insurance group AXA is conducting simulations with cutting-edge��
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In the United Arab Emirates (UAE), extreme weather events disrupt daily life, delaying flights, endangering transportation, and complicating urban planning. High daytime temperatures limit human activity outdoors, while dense nighttime fog is a frequent cause of severe and often fatal car crashes. Meanwhile, 2024 saw the heaviest precipitation event in the country in 75 years��
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From mitigating climate change to improving disaster response and environmental monitoring, AI is reshaping how we tackle critical global challenges. Advancements in fast, high-resolution climate forecasting, real-time monitoring, and digital twins are equipping scientists, policy-makers, and industry leaders with data-driven tools to understand, plan for, and respond to a warming planet.
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Supercomputers are the engines of groundbreaking discoveries. From predicting extreme weather to advancing disease research and designing safer, more efficient infrastructures, these machines simulate complex systems that are impractical to test in the real world due to their size, cost, and material requirements. Since the introduction of the GPU in 1999, NVIDIA has continually pushed the��
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Flooding poses a significant threat to 1.5 billion people, making it the most common cause of major natural disasters. Floods cause up to $25 billion in global economic damage every year. Flood forecasting is a critical tool in disaster preparedness and risk mitigation. Numerical methods have long been developed that provide accurate simulations of river basins. With these, engineers such as those��
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Learn from energy leaders using HPC and AI to boost exploration, production, and fuel delivery, while enhancing power grid reliability and resiliency.
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Each year, the world recycles only around 13% of its two billion-plus tons of municipal waste. By 2050, the world��s annual municipal waste will reach 3.88B tons. But the global recycling industry is far from efficient. Annually, as much as $120B of potentially recoverable plastic��let alone paper or metals��ends up in landfills rather than within new products made with recycled materials.
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As global electricity demand continues to rise, traditional sources of energy are increasingly unsustainable. Energy providers are facing pressure to reduce reliance on fossil fuels while ensuring a fully supplied and stable grid. In this context, solar energy has emerged as a vital renewable resource, being one of the most abundant clean energy sources available. However��
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Christopher Bretherton, Senior Director of Climate Modeling at the Allen Institute for AI (AI2), highlights how AI is revolutionizing climate science. In this NVIDIA GTC 2024 session, Bretherton presents advancements in machine learning-based emulators for predicting regional climate changes and precipitation extremes. These tools accelerate climate modeling, making it faster, more efficient��
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Dale Durran, a professor in the Atmospheric Sciences Department at the University of Washington, introduces a breakthrough deep learning model that combines atmospheric and oceanic data to set new climate and weather prediction accuracy standards. In this NVIDIA GTC 2024 session, Durran presents techniques that reduce reliance on traditional parameterizations, enabling the model to bypass��
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New research from the University of Washington is refining AI weather models using deep learning for more accurate predictions and longer-term forecasts. The study, published in Geophysical Research Letters, shows how adjusting initial atmospheric data enables advanced AI models to extend current forecast limits. As extreme weather becomes increasingly more severe and frequent due to climate��
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Electric vehicle (EV) charging is getting a jolt with an innovative new AI algorithm that boosts efficiency, reduces cost, and keeps the grid from short-circuiting under pressure. Developed by a team of researchers from the Royal Military College of Canada (RMC), the real-time smart solution optimizes charging schedules for large parking lots, balancing quick charging with energy availability.
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NVIDIA designed the NVIDIA Grace CPU to be a new kind of high-performance, data center CPU��one built to deliver breakthrough energy efficiency and optimized for performance at data center scale. Accelerated computing is enabling giant leaps in performance and energy efficiency compared to traditional CPU computing. To deliver these speedups, full-stack innovation at data center scale is��
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NVIDIA PhysicsNeMo v24.09 delivers utilities to physics-inform training and validation of any model, plus other enhancements.
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Antarctica plays a crucial role in regulating ?Earth��s climate. Most climate research into the world��s coldest, most windswept continent focuses on the surrounding Southern Ocean��s carbon dioxide absorption, or its vast, sunlight-reflecting glaciers. A group of Australian scientists is taking a different approach. Researchers are diving deep into Antarctic moss beds, using an AI-powered edge��
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Global energy technology company SLB has announced the next milestone in its long-standing collaboration with NVIDIA to develop and scale generative AI solutions for the energy industry. The collaboration accelerates the development and deployment of energy industry-specific generative AI foundation models across SLB global platforms, including its Delfi digital platform and SLB��s new Lumi��
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Machine Learning algorithms are beginning to revolutionize modern agriculture. Enabling farmers to combat pests and diseases in real time, the technology is improving crop production and profits, while reducing waste, greenhouse gas emissions, and pesticide use. Around 6% of the world��s CO2 emissions come from farming. And every year, up to 40% of crops are lost due to pests and disease.
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As the world faces the urgent need to combat climate change, carbon capture and storage (CCS) has emerged as a crucial technology for achieving net-zero emissions. The CCS technology��which involves capturing carbon dioxide (CO2), either from industrial emissions or through direct air capture (DAC), and securely storing it in the subsurface��can drive much-needed decarbonization strategies and help��
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Large language models (LLMs) are emerging as a tool for safeguarding critical infrastructure systems, such as renewable energy, healthcare, or transportation, according to a new study from the Massachusetts Institute of Technology (MIT). The research introduces a zero-shot LLM model that detects anomalies in complex data. Using AI-driven diagnostics for monitoring and flagging potential��
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The exponential growth in data processing demand is projected to reach 175 zettabytes by 2025. This contrasts sharply with the slowing pace of CPU performance improvements. For more than a decade, semiconductor advancements have not kept up with the pace predicted by Moore��s Law, leading to a pressing need for more efficient computing solutions. NVIDIA GPUs have emerged as the most efficient��
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NVIDIA PhysicsNeMo 24.07 brings new GNN enhancements and application samples for training with large meshes.
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Despite the continuous improvement of weather forecasts over the last few decades, uncertainties due to meteorological measurements and models mean that ensemble forecasts remain critical to weather forecasting. Ensemble forecasts estimate this uncertainty by running multiple simulations over the same forecast horizon. Comparing the different outcomes then paints a more detailed picture of the��
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Mathematical optimization is a powerful tool that enables businesses and people to make smarter decisions and reach any number of goals��from improving operational efficiency to reducing costs to increasing customer satisfaction. Many of these are everyday use cases, such as scheduling a flight, pricing a hotel room, choosing a GPS route, routing delivery trucks, and more. However��
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The world��s energy system is increasingly complex and distributed due to increasing renewable energy generation, decentralization of energy resources, and decarbonization of heavy industries. Energy producers are challenged to optimize operational efficiency and costs within hybrid power plants generating both renewable and carbon-based electricity. Grid operators have less time to dispatch energy��
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With the growing emphasis on environmental, social, and governance (ESG) investments and initiatives, manufacturers are looking for new ways to increase energy efficiency and sustainability across their operations. One area of opportunity in electronics manufacturing is the performance of run-in test rooms, which are essential for ensuring the reliability, quality, and safety of the world��s��
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PhysicsNeMo v24.04 delivers an optimized CorrDiff model and Earth2Studio for exploring weather AI models.
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In the context of global warming, NVIDIA Earth-2 has emerged as a pivotal platform for climate tech, generating actionable insights in the face of increasingly disastrous extreme weather impacts amplified by climate change. With Earth-2, accessible insights into weather and climate are no longer confined to experts in atmospheric physics or oceanic dynamics. You can now harness advanced��
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In 2022, the city of Lismore, Australia bore the brunt of devastating floods, leaving over 3K homes damaged and communities shattered. With $6B in losses, this was the second-costliest event in the world for insurers in 2022 and the most expensive disaster in Australian history. With each passing year, natural disaster events such as those experienced in Lismore grow in rate and scale across��
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Hear from ExxonMobil, Honeywell, Siemens Energy, and more as they explore AI and HPC innovation in oil, gas, power, and utilities.
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NVIDIA PhysicsNeMo 24.01 updates distributed utilities and samples for physics informing DeepONet and GNNs.
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Virtual seismology has only been around for a few years, and it has already had a significant impact on earthquake monitoring. Historically, seismic phase picking��the task of annotating seismograms with seismic wave arrival times that underpins earthquake monitoring operations globally��was a manual process. As such, it was labor-intensive, fraught with subjectivity, and prone to errors.
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Now available, NVIDIA PhysicsNeMo 23.11 introduces a diffusion modeling framework and novel architectures.
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The world of computing is on the precipice of a seismic shift. The demand for computing power, particularly in high-performance computing (HPC), is growing year over year, which in turn means so too is energy consumption. However, the underlying issue is, of course, that energy is a resource with limitations. So, the world is faced with the question of how we can best shift our computational��
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AI is quickly becoming an integral part of diverse industries, from transportation and healthcare to manufacturing and finance. AI powers chatbots, recommender systems, computer vision applications, fraud prevention, and autonomous vehicles. It also has broad applications in engineering and science. Physics-informed machine learning (physics-ML) leverages knowledge of the physical world to��
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Simulations are quintessential for complex engineering challenges, like designing nuclear fusion reactors, optimizing wind farms, developing carbon capture and storage techniques, or building hydrogen batteries. Designing such systems often requires many iterations of scientific simulations that are computationally expensive to run. Solvers and parameters must often be tuned individually to each��
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NVIDIA PhysicsNeMo 23.09 is now available, providing ease-of-use updates, fixes, and other enhancements.
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Machine learning-based weather prediction has emerged as a promising complement to traditional numerical weather prediction (NWP) models. Models such as NVIDIA FourCastNet have demonstrated that the computational time for generating weather forecasts can be reduced from hours to mere seconds, a significant improvement to current NWP-based workflows. Traditional methods are formulated from��
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If you are looking to take your machine learning (ML) projects to new levels of speed and scalability, GPU-accelerated data analytics can help you deliver insights quickly with breakthrough performance. From faster computation to efficient model training, GPUs bring many benefits to everyday ML tasks. Update: The below blog describes how to use GPU-only RAPIDS cuDF��
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NVIDIA PhysicsNeMo is a framework for building, training, and fine-tuning deep learning models for physical systems, otherwise known as physics-informed machine learning (physics-ML) models. PhysicsNeMo is available as OSS (Apache 2.0 license) to support the growing physics-ML community. The latest PhysicsNeMo software update, version 23.05, brings together new capabilities��
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This version 23.05 update to the NVIDIA PhysicsNeMo platform expands support for physics-ML and provides minor updates.
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Most drone inspections still require a human to manually inspect the video for defects. Computer vision can help automate and accelerate this inspection process. However, training a computer vision model to automate inspection is difficult without a large pool of labeled data for every possible defect. In a recent session at NVIDIA GTC, we shared how Exelon is using synthetic data generation��
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Accurate weather modeling is essential for companies to properly forecast renewable energy production and plan for natural disasters. Ineffective and non-forecasted weather cost an estimated $714 billion in 2022 alone. To avoid this, companies need faster, cheaper, and more accurate weather models. In a recent GTC session, Microsoft, and TempoQuest detailed their work with NVIDIA to address��
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CO2 capture and storage technologies (CCS) catch CO2 from its production source, compress it, transport it through pipelines or by ships, and store it underground. CCS enables industries to massively reduce their CO2 emissions and is a powerful tool to help industrial manufacturers achieve net-zero goals. In many heavy industrial processes, greenhouse gas (GHG) emissions cannot be avoided in the��
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Physics-informed machine learning (physics-ML) is transforming high-performance computing (HPC) simulation workflows across disciplines, including computational fluid dynamics, structural mechanics, and computational chemistry. Because of its broad applications, physics-ML is well suited for modeling physical systems and deploying digital twins across industries ranging from manufacturing to��
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In collaboration with the United Nations, DLI is offering a new free online course focused on applying deep learning methods to generate accurate flood detection models.
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Marine biologists have a new AI tool for monitoring and protecting coral reefs. The project��a collaboration between Google and Australia��s Commonwealth Scientific and Industrial Research Organization (CSIRO)��employs computer vision detection models to pinpoint damaging outbreaks of crown-of-thorns starfish (COTS) through a live camera feed. Keeping a closer eye on reefs helps scientists address��
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A recent study from researchers at ETH Zurich��s EcoVision Lab is the first to produce an interactive Global Canopy Height map. Using a newly developed deep learning algorithm that processes publicly available satellite images, the study could help scientists identify areas of ecosystem degradation and deforestation. The work could also guide sustainable forest management by identifying areas for��
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Climate change mitigation is about reducing greenhouse gas (GHG) emissions. The worldwide goal is to reach net zero, which means balancing the amount of GHG emissions produced and the amount removed from the atmosphere. On the one hand, this implies reducing emissions by using low-carbon technologies and energy efficiency. On the other hand, it implies deploying negative emission technologies��
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Powerful airborne sensors could be key in helping farmers sustainably manage maize across the US Corn Belt, according to a University of Illinois research team. The study, which employs remote sensors combined with newly developed deep learning models, gives an accurate and speedy prediction of crop nitrogen, chlorophyll, and photosynthetic capacity. Published in the International Journal of��
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New weather-forecasting research using AI is fast-tracking global weather predictions. The study, recently published in the Journal of Advances in Modeling Earth Systems, could help identify potential extreme weather 2�C6 weeks into the future. Accurate predictions of extreme weather with a longer lead time give communities and critical sectors such as public health, water management, energy��
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At NVIDIA GTC last week, Jensen Huang laid out the vision for realizing multi-Million-X speedups in computational performance. The breakthrough could solve the challenge of computational requirements faced in data-intensive research, helping scientists further their work. Million-X unlocks new worlds of potential and the applications are vast. Current examples from NVIDIA include��
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You may soon be able to see how future flooding could hit your city with a newly developed AI model. The study, from a team of Canadian and U.S. researchers, uses generative adversarial networks (GANs) to produce realistic images of climate change-induced flooding. Named ClimateGAN, the team developed the model to underscore the destruction of extreme weather events and prompt collective action��
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Wildfire evacuees and disaster response groups could soon have the power to remotely scan a town for structural damage within minutes, using the newly developed AI tool DamageMap. A collaboration between researchers at Stanford University and California Polytechnic State University, San Luis Obispo��the project uses aerial imagery and a deep learning algorithm to pinpoint building damage after��
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A new AI-mapping tool is helping scientists assess how cities across the globe are using rooftops to combat climate change. Named Roofpedia, the research creates an open-source and scalable map of sustainable rooftops��a promising strategy for climate mitigation. Identifying areas with solar or green installations could help guide urban development, while also boosting community health, prosperity��
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New research from a group of scientists at UC Berkeley is giving data-poor regions across the globe the power to analyze data-rich satellite imagery. The study, published in Nature Communications, introduces a machine learning model that resource-constrained organizations and researchers can use to draw out regional socioeconomic and environmental information. Being able to evaluate local��
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To support its efforts to become climate neutral by 2050, the European Union has launched a Destination Earth initiative to build a detailed digital simulation of the planet that will help scientists map climate development and extreme weather events with high accuracy. The decade-long project will create a digital twin of the Earth, rendered at one-kilometer scale and based on continuously��
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This year at GTC, you will join speakers and panelists considered to be pioneers of AI, technologists, and creators who are re-imagining what is possible in higher education and research. By registering for this free event you��ll get access to these top sessions, and more: Visit the GTC website to view more recommended��
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From weather forecasting and energy exploration, to computational chemistry and molecular dynamics, NVIDIA compute and networking technologies are optimizing nearly 2,000 applications across a broad-range of scientific domains and industries. By leveraging GPU-powered parallel processing, users can accelerate advanced, large-scale applications efficiently and reliably, paving the way to scientific��
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To accurately forecast heat waves and cold spells, Rice University engineers developed a deep learning-based system that can accurately predict extreme weather events up to five days in advance with 85% accuracy. ��When you get these heat waves or cold spells, if you look at the weather map, you are often going to see some weird behavior in the jet stream, abnormal things like large waves or a��
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New Zealand��s National Institute of Water and Atmospheric Research (NIWA) is upgrading their supercomputers with three new energy efficient systems that will be used for weather forecasting and climate research. $18 million will be used to purchase three Cray systems, the most powerful being the 1.4 petaflop Cray XC50 supercomputer equipped with NVIDIA Tesla P100 accelerators that will installed��
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Three times faster than its predecessor, Blue Crystal 4 (BC4) at University of Bristol can perform 600 trillion calculations per second and will accelerate the work of more than 1,000 researchers and engineers. According to Dr. Christopher Woods, EPSRC Research Software Engineer Fellow at the University of Bristol, ��research that used to take a month, now takes a week, and what took a week��
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A team of researchers led by Jeroen Tromp at Princeton University used a GPU-accelerated supercomputer to create a detailed 3D picture of Earth��s interior. ��This is the first global seismic model where no approximations �� other than the chosen numerical method �� were used to simulate how seismic waves travel through the Earth and how they sense heterogeneities,�� said Ebru Bozdag��
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Sangram Ganguly, a senior research scientist at the NASA Ames Research Center shares how they are analyzing satellite imagery with deep learning to gain a better understanding of our planet. As a founding member of NASA Earth Exchange (NEX), which utilizes NASA��s GPU-accelerated Pleiades supercomputer, Ganguly helped develop the collaboration platform that combines state-of-the-art supercomputing��
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Texas A&M installed a new $2.1 million supercomputer with 10 times the processing power of their previous system Eos, which was launched in 2009. Nicknamed ��Terra,�� the new supercomputer will support projects that include developing new materials, discovering new drugs, forecasting storm surges and managing energy resources. ��Terra represents a new supercomputer iteration deployed at Texas A&M,����
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Australian scientists made a significant discovery hiding behind the world-famous Great Barrier Reef. The discovery was made using cutting-edge surveying technology, which revealed vast fields of doughnut-shaped mounds measuring up to 300 meters across and up to 10 meters deep. ��We��ve known about these geological structures in the northern Great Barrier Reef since the 1970s and 80s��
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Global warming and pollution are causing severe stress to coral reefs across the world. Researchers from the University of California Berkeley and University of Queensland developed a deep learning process that automatically analyzes reef photos that will help measure reef health and changes over time. Reefs provide food and shelter for more than a quarter of all marine species.
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The Earth isn��t getting any bigger, so we need to start finding more efficient ways to feed the projected 10 billion people by 2050 using the same amount of land. WIRED recently published an article highlighting several examples of how artificial intelligence technology can be used to tackle this challenge: Crop Disease Diagnosis Researchers from EPFL in Switzerland and Penn State University��
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Understanding the critical genetic traits of agricultural crops will help develop crops faster in order to handle the world��s population growth and climate change. In a collaboration between Biochemist Alex Feltus and Computer Engineering PhD student Karan Sapra, the Clemson University researchers have created an interactive visualization tool using NVIDIA GPUs that allows them to look at complex��
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Peter Vincent of the Department of Aeronautics at Imperial College London shares how they are using NVIDIA Tesla GPUs to accelerate Computational Fluid Dynamics simulations that will improve the design processes used by companies that design aircrafts or Formula One race cars. Learn more about PyFR, the open-source CFD package developed by Vincent��s lab, that employs new super��
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Flood risk assessment is important in minimizing damages and economic losses caused by flood events. A team of researchers from Vienna University of Technology and visual computing firm VRVis, are using GPUs to run fast simulations of large-scale scenarios, including river flooding, storm-water events and underground flows. The researcher��s primary interest is in decision-making systems��
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Sea levels have traditionally been measured by marks on land �C but the problem with this approach is that parts of the earth��s crust move too. A group of researchers from Chalmers University of Technology in Sweden are using GPS receivers along the coastline in combination with reflections of GPS signals that bounce off the water��s surface. NVIDIA GPUs then crunch those data signals to compute��
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Thomas Schulthess, of ETH Zurich and Director of the Swiss National Supercomputing Centre (CSCS) discusses how they are using GPU-accelerated supercomputers for more detailed weather forecasts. Watch Thomas�� talk ��From ��Piz Daint�� to ��Piz Kesch��: The Making of a GPU-based weather forecasting system�� in the NVIDIA GPU Technology Theater at SC15: Watch Now Share your GPU��
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Thanks to GPUs, the Swiss have made significant advancements in their ability to predict storms and other weather hazards with higher levels of accuracy. The Swiss Federal Office of Meteorology and Climatology, MeteoSwiss, is the first major national weather service to deploy a GPU-accelerated supercomputer to improve its daily weather forecasts. The new system, powered by NVIDIA Tesla K80 GPU��
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