NishMath - #forecasting

A new, fully AI-driven weather prediction system called Aardvark Weather is making waves in the field. Developed through an international collaboration including researchers from the University of Cambridge, Alan Turing Institute, Microsoft Research, and the European Centre for Medium-Range Weather Forecasts (ECMWF), Aardvark Weather uses a deep learning architecture to process observational data and generate high-resolution forecasts. The model is designed to ingest data directly from observational sources, such as weather stations and satellites.

This innovative system stands out because it can run on a single desktop computer, generating forecasts tens of times faster than traditional systems and requiring thousands of times less computing power. While traditional weather forecasting relies on Numerical Weather Prediction (NWP) models that use physics-based equations and vast computational resources, Aardvark Weather replaces all stages of this process with a streamlined machine learning model. According to researchers, Aardvark Weather can generate a forecast in seconds or minutes, using only about 10% of the weather data required by current forecasting systems.


References :

• www.computerworld.com: The AI system achieved this by replacing the entire process of weather forecasting with a single machine-learning model; it can take in observations from satellites, weather stations and other sensors and then generate both global and local forecasts.
• www.livescience.com: New AI is better at weather prediction than supercomputers — and it consumes 1000s of times less energy
• www.newscientist.com: AI can forecast the weather in seconds without needing supercomputers
• The Register - Software: PC-size ML prediction model predicted to be as good as a super at fraction of the cost Aardvark, a novel machine learning-based weather prediction system, teases a future where supercomputers are optional for forecasting - but don't pull the plug just yet.
• AIwire: Fully AI-Driven System Signals a New Era in Weather Forecasting
• eWEEK: New AI Weather Forecasting Model is ‘Thousands of Times Faster’ Than Previous Methods
• bsky.app: An #AI based weather forecasting system that is much faster than traditional approaches:
• NVIDIA Technical Blog: From hyperlocal forecasts that guide daily operations to planet-scale models illuminating new climate insights, the world is entering a new frontier in weather...
• I Learnt: DIY weather prediction and strategy selection
• www.bitdegree.org: A new artificial intelligence (AI) based tool called Aardvark Weather is offering a different way to predict weather across the globe.

Classification:

• HashTags: #AI #WeatherForecasting #AardvarkWeather
• Company: University of Cambridge
• Target: Researchers, Weather services
• Product: Aardvark Weather
• Feature: Weather Prediction
• Type: AI
• Severity: Informative

A new mathematical model developed by the University of Rovira i Virgili's SeesLab research group, along with researchers from Northeastern University and the University of Pennsylvania, has made it possible to predict human mobility between cities with high precision. The model offers a simpler and more efficient way than current systems and is a valuable tool for understanding how people move in different contexts, which is crucial for transport planning, migration studies, and epidemiology. The research was published in the journal *Nature Communications*.

The model builds on traditional "gravitational models," which estimate mobility based on population size and distance between cities. While these models are simple, they lack accuracy. Modern approaches leverage artificial intelligence and machine learning to incorporate many variables besides origin and destination, such as the density of restaurants and schools, and the socio-demographic characteristics of the population. The COVID-19 pandemic highlighted the importance of predicting mobility for understanding the spread and evolution of viruses.


References :

• phys.org: Mathematical model improves prediction of human mobility between cities

Classification:

• HashTags: #statistics #bayesian #modeling
• Target: Forecasting
• Product: Statistics
• Feature: Prediction
• Type: Research
• Severity: Medium