Scalable AI for Environmental and Social Impact
Explore Microsoft's AI contributions to Apache Spark and Machine Learning, focusing on environmental and social impact projects like art exploration and endangered species protection.
Asiacrypt 2022 - Lattice Algorithms and Cryptanalysis
Explore lattice algorithms and cryptanalysis, covering topics like psychotomic fields, quantum decomposition, and optimization frameworks in this comprehensive talk from Asiacrypt 2022.
Machine Learning Methods for Climate Science - Lecture 4
Explore machine learning applications in climate science, focusing on advanced techniques for analyzing and predicting complex atmospheric and oceanic processes.
Machine Learning Methods for Climate Science - Lecture 2
Explore machine learning applications in climate science, focusing on advanced techniques and their impact on understanding and predicting climate phenomena.
Machine Learning Methods for Climate Science - Lecture 3
Explore machine learning applications in climate science, focusing on advanced techniques for analyzing and predicting complex atmospheric and oceanic processes.
How Far Can We Scale Up? Deep Learning's Diminishing Returns
Explores the limits of scaling up deep learning, discussing computational costs, CO2 emissions, and potential solutions to overcome diminishing returns in AI model performance.
Navigating the AI Council's AI Roadmap
Experts discuss AI's role in UK society, addressing climate change, resilience, mental health, diversity, and skills development while exploring strategies to build public trust and make actionable impact.
Machine Learning and the Earth David Hall
Explore machine learning's potential in addressing urgent global challenges like climate change, with insights on strategies, risks, and implications for various fields.
Why We Need Architects and Architecture on Agile Projects
Explores the role of architects in agile projects, emphasizing stewardship, sustainable development, and techniques for managing architectural tasks and risks in complex software development.
Marsha Berger - Towards Adaptive Simulations of Dispersive Tsunami Propagation
Explore adaptive simulations for tsunami propagation, focusing on shallow water equations, mesh refinement, and Boussinesq models. Learn about computational techniques for predicting tsunami impacts from various sources.
Machine Learning and Game Theory for Social Impact
Explore machine learning and game theory applications in security, sustainability, and food rescue, featuring real-world deployments and innovative solutions for societal challenges.
Chasing Cows - Making Africa Smarter With Embedded ML
Explore embedded ML applications in African agriculture and conservation, from cow health monitoring to elephant tracking, addressing unique challenges and local solutions.
TinyML Talks Kenya - TinyML and the Developing World
Explore TinyML's potential in developing countries for medicine, agriculture, and conservation. Learn about low-cost, battery-powered machine learning applications adaptable to local needs.
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.
Benefits of Saying I Don't Know When Analyzing and Modeling the Climate System With ML - Elizabeth Barnes
Explore the benefits of acknowledging uncertainty in climate system analysis using machine learning. Learn about state-dependent predictability and controlled abstention networks for improved modeling accuracy.
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.
Be the Change Our Planet Seeks: How You Can Contribute to Running Environment-Friendly Workloads on Kubernetes
Discover sustainable software engineering principles for Kubernetes workloads and learn actionable steps to reduce carbon footprint in your projects, contributing to a greener tech industry.
Evaluating the Energy Footprint of GitOps Architectures - A Benchmark Analysis
Explore the energy consumption and CO2 emissions of GitOps architectures through benchmark analysis, providing insights for eco-friendly decision-making in cloud-native environments.
GitOps Sustainability with Flux and ARM64
Explore GitOps sustainability using Flux and arm64, covering performance benefits, cost savings, and environmental impact. Learn steps to recompile workloads and implement best practices for efficient cloud-native operations.
Solving for Climate: Chasing Hurricanes Through Computational Modeling
Computational modeling of hurricanes and natural hazards, exploring their response to atmospheric dynamics and climate change impacts on economic and social outcomes.
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.