Los Alamos National Laboratory’s Post

Some exciting science and modeling that Los Alamos is doing with AI and seismic data.

The Complexity of Earthquake Prediction and #AI's Role Beyond the mathematical elegance that captivates us, the truly compelling aspect of #artificialintelligence and #datascience lies in their capacity to tackle complex issues that carry significant social and technological consequences. This article caught my attention for its exploration of earthquake prediction - a subject somewhat removed from my regular field of work, yet undeniably intriguing. 🌐 #EarthquakePrediction #AIChallenges #MachineLearning Predicting earthquakes has always been a complex and daunting task. The unpredictability of seismic events stems from the intricate and dynamic nature of our planet's geology. Earthquakes occur due to the sudden release of energy in the Earth's crust, creating seismic waves. The factors influencing these events are multifaceted, involving the interplay of geological, hydrological, and atmospheric elements, making it difficult to pinpoint when and where an earthquake will strike. 🔬 Why is it so Complex? #Unpredictable Nature: Earthquakes are the result of a multitude of factors, including tectonic plate movements, stress accumulation, and geological faults. Limited #Data: The lack of historical data and the unique characteristics of each seismic event add to the unpredictability. #Complexsystems: Earth's geological system is highly #complex, with numerous variables interacting in unpredictable ways. However, with advancements in AI and machine learning, we are now exploring new horizons in earthquake prediction. 🌍 #EarthquakePrediction #MachineLearning #AIForGood Researchers are now utilizing artificial intelligence, particularly machine learning, to advance earthquake prediction. This new approach offers hope in a field traditionally marred by unpredictability and complexity. 🔍 The Article's Insight: Early Warning Systems: Leveraging algorithms to send alerts seconds to minutes after an earthquake begins, providing crucial time for preparation and response. #Prediction Challenges: Earthquake prediction is complex due to underground stress and fault line behaviors. Machine Learning's Role: AI is being employed to detect #patterns and signals in seismic data, which were previously hard todecipher. 🤖 #TechForHumanity AI in earthquake prediction represents a beacon of hope. It shows how technology can be used for societal good, addressing concerns beyond privacy, labor, and commercial applications. 💡 #Innovation The integration of AI and machine learning into seismology marks a shift in our understanding and management of earthquakes. It is akin to the revolution brought by the theory of plate tectonics in geology. 🌐 The Bigger Picture: The application of AI in this domain is not just a technical advancement but a step towards saving lives and enhancing our resilience against natural disasters. It underscores AI's potential for positive impact. 🔗 Link to the Article in the first comment  

New Tool Enhances Earthquake Prediction Reliability The beginning of 2024 has proven challenging, marked by a series of consecutive earthquakes encircling the Pacific Plate. In the face of this adversity, humanity seems to have encountered setbacks in its ongoing struggle against the forces of nature. We solemnly remember the victims. Visibly apparent is the transformative impact of AI technology on earthquake prediction. Explore the influence of AI technology on seismic forecasting in this article from #MITtechnology. #machinelearning #disasterprevention #earthquake https://lnkd.in/gbkDBy69

Los Alamos AI takes a big step forward in predicting earthquakes Scientists at Los Alamos National Laboratory have used machine learning to uncover hidden signals that precede earthquakes, focusing on the Kīlauea volcano's 2018 seismic activity. Analyzing data from over 50 quakes recorded by the US Geological Survey, the team identified patterns in continuous seismic waveforms, revealing signals that indicate where in the loading cycle the system is, helping to predict major slips. This study, the first to detect these warning signals in a destructive stick-slip fault, suggests that similar physics across various earthquake faults could allow this method to be applied globally. The findings were published in Geophysical Research Letters. Read more here: https://lnkd.in/gZeahKaD Seismic Features Predict Ground Motions During Repeating Caldera Collapse Sequence https://lnkd.in/giD8Adjr #AI #ArtificialIntelligence #LosAlamos #Earthquakes #MachineLearning #Seismology #KilaueaVolcano #LosAlamosNationalLab #GeophysicalResearch #SeismicActivity #PredictiveModeling

The start of the new year in Japan was marked by a tragic event, as a 7.5 magnitude earthquake struck the Noto peninsula on the country's western edge on 1 January. Numerous aftershocks, ranging between four and six in magnitude, continued to rattle the coastal epicenter for hours. This highlighted the need for earthquake prediction, which scientists believe may soon become a possibility due to the advancements in AI. Has there been any research on this though? Last fall, researchers from the University of Texas at Austin conducted a seven-month trial in China. Their study, published in September in the Bulletin of the Seismological Society of America, revealed that an AI algorithm accurately predicted 70% of earthquakes a week in advance. The researchers trained the AI using five years of seismic recordings and tasked it with identifying upcoming earthquakes based on current seismic activity. Another group of researchers has developed and trained neural networks for forecasting the locations of potential aftershocks following an initial earthquake, while others are employing machine learning to detect and extract seismic waves — the vibrations that travel through the Earth during tectonic activity. For context - As recently as 2013, earthquake prediction was often dismissed as unserious, according to seismologist Allie Hutchison's recent report for MIT Technology Review. Additionally, the U.S. Geological Survey maintains that neither they nor any other scientists have successfully predicted a major earthquake. Nevertheless, the advancements in AI and increasing research on earthquake prediction are fostering optimism among scientists, suggesting the potential for further breakthroughs.

AI-driven earthquake forecasting shows promise in trials: A new attempt to predict earthquakes has raised hopes that artificial intelligence could one day be used to limit earthquakes’ impact on lives and economies. The AI algorithm correctly predicted 70% of earthquakes a week before they happened during a seven-month trial in China. The system is limited because the AI needs an extensive database and years of seismic recordings to train itself on, but researchers said the effort is nonetheless a milestone for AI-driven earthquake forecasting. Researchers will soon begin testing the system at other locations. @Poseidon-US #ScienceDaily #Technology

How machine learning might unlock earthquake prediction

Improved Earthquake Forecasting!🌎 For more than thirty years, the field of earthquake aftershock forecasting has adhered to conventional models, which has become a restraint in the face of the vast and complex datasets that are available today. In response to this limitation, a team of researchers from the University of California, Santa Cruz, and the Technical University of Munich has introduced a groundbreaking deep learning model known as Recurrent Earthquake foreCAST (RECAST) to enhance aftershock prediction. https://lnkd.in/eDY2P4zy

AI Forecasts Earthquake Aftershock Occurrence and Magnitude #Advancements #aftershocks #AI #AItechnology #artificialintelligence #Deeplearningmodels #earthquakeforecasting #llm #machinelearning #neuralnetworkapproach #preparedness #seismicresearch #seismologists

AI Shows Promise in Earthquake Forecasting Trials Researchers from The University of Texas at Austin have used AI to predict earthquakes with 70% accuracy a week before they happen. It's a big step in making earthquake predictions more accurate. The AI learned from real-time seismic data and past earthquakes. During the trial in China, it correctly predicted 14 earthquakes within 200 miles of where it thought they'd occur. That's impressive! But it did make eight wrong predictions and missed one earthquake. This is an important development for earthquake forecasting. Scientists say it's not perfect yet, but it's a significant achievement. It's a bit like solving a very tough puzzle. The AI outperformed 600 other designs in an international competition. It's a promising start, and it can get even better in places with good seismic networks. They want to test it in Texas, a place with many small to medium earthquakes. The goal is to combine AI with what we already know about earthquakes. 🌍🔮 Paper: https://lnkd.in/ekQR3eJe Authors: Omar M. Saad; Yunfeng Chen; Alexandros Savvaidis; Sergey Fomel; Xiuxuan Jiang; Dino Huang; Yapo Abolé Serge Innocent Oboué; Shanshan Yong; Xin’an Wang; Xing Zhang; Yangkang Chen #ai ##earthquake #earthquakeforecasting #science #UTAustin #progress https://lnkd.in/eVj9xmPn