ChatGPT - Water Sector Applications
Explore AI and large language models in water industry applications, including ChatGPT capabilities, live demos, software integration, and potential risks and opportunities.
Machine Learning and Earth System Modeling - From Parameter Calibration to Feature Detection
Explore machine learning applications in Earth system modeling, from parameter calibration to feature detection, enhancing climate predictions and understanding of complex environmental processes.
Lessons and Outlook for ML Parameterization of Sub Grid Atmospheric Physics From the Vantage of Emulating Cloud Superparameterization - Mike Pritchard
Exploring machine learning for atmospheric physics parameterization, focusing on cloud superparameterization emulation. Discusses challenges, strategies, and lessons learned in applying ML to climate modeling.
Interpretable and Generalizable Machine Learning for Fluid Dynamics - Steven Brunton
Explore interpretable and generalizable machine learning techniques for fluid dynamics, focusing on sparse identification of nonlinear dynamics and incorporating physical constraints for improved accuracy.
Physics-Guided Deep Learning for Fluid Dynamics - Rose Yu
Explores physics-guided deep learning for fluid dynamics, focusing on accelerating turbulence simulations and incorporating symmetry for generalization in ocean current forecasting.
Introduction to Volcano: Cloud Native Batch System
Explore Volcano, a cloud-native batch system for high-performance workloads on Kubernetes. Learn about its architecture, features, use cases, and recent developments in this comprehensive introduction.
Volcano for FinTech Big Data on Kubernetes
Explore how Volcano enhances FinTech BigData operations on Kubernetes, optimizing resource management and workflow efficiency for financial technology applications.
Efficient Scheduling of High Performance Batch Computing for Analytics Workloads with Volcano
Explore how ING uses Volcano scheduler for efficient, multi-tenant large-scale processing in advanced analytics, enabling dynamic allocation and resource fairness for over 300 internal projects.
Explainable AI for the Geosciences
Explore machine learning interpretation techniques in geoscience, focusing on climate science applications and their potential for scientific discovery and increased trust in AI outputs.
Modeling Flow and Transport in Fractured Rock Using Machine Learning
Integrating computational physics, machine learning, and graph theory to model flow and transport in fractured rock systems, offering a paradigm shift from high-fidelity models to efficient coarse-scale graphs.
Machine Learning for Analysis of High-Dimensional Spatiotemporal Chaotic Dynamical Systems
Discover how machine learning techniques can analyze and predict complex chaotic systems, with insights from cutting-edge research in physics and data science.
Automated Testing and Continuous Integration/Delivery: Lessons Learned
Explore lessons learned in implementing automated testing and CI/CD for embedded Linux, including GitLab CI, Jenkins, Artifactory, and LAVA infrastructure for hardware testing.
Dragon-Kings, Black-Swans and Prediction - Lorenz Lecture
Explore extreme events, their predictability, and impact on complex systems through statistical physics and nonlinear dynamics in this insightful lecture by D. Sornette.
Machine Learning in Fluid Dynamics and Climate Physics
Explore machine learning applications in fluid dynamics and climate modeling, including physics-informed approaches, data integration, and simulation validation techniques.
Challenges for AI in Computational Sustainability
Explore computational sustainability's role in balancing environmental, economic, and societal needs through AI models and methods, from wildlife conservation to renewable energy materials discovery.
Building a Boards Farm: Continuous Integration and Remote Control
Explore the creation of a boards farm for kernel continuous integration, contributing to KernelCI, and implementing remote board control using LAVA infrastructure.
Introducing the Lab in a Box Concept for Continuous Integration
Simplifying board farm setup for continuous integration in embedded Linux development. Explores motivations, challenges, and benefits of the "Lab in a Box" concept, with a demo of its implementation.
Testing Remote Embedded Devices Using Open-Hardware MuxPi
Discover MuxPi, an open-hardware solution for remote access to embedded devices. Learn about Tizen's testing laboratory components and simplify device flashing, debugging, and power management.
Introducing the Lab in a Box Concept for Continuous Integration
Simplifying Continuous Integration for embedded systems with "Lab in a Box" - a turnkey solution for setting up LAVA board farms, reducing complexity and improving test automation.
Computer Vision for Global-Scale Biodiversity Monitoring
Exploring AI-driven earth observation systems for real-time biodiversity monitoring and conservation, addressing challenges in ecological data analysis and promoting collaborative, interdisciplinary approaches.
Take Control of Your Maps with Docker
Discover how to deploy custom world maps using Docker and OpenStreetMap. Learn to create, style, and scale map services without vendor lock-in for web and mobile applications.