Ruth MottramMar 9

Machine Learning techniques are upending multiple scientific fields. Operational 5-day forecasting of air quality in 1 minute in this paper from Chinese researchers.

This is awesome work with very clear public health implications.

EDIT for clarity: I am.not suggesting LLMs have anything to do with this work, but many people hear AI and imagine LLMs. And many of them.are perhaps rightly sceptical of AI as a result.
But AI or ML techniques can be useful for lots of things, not just chatbots. And we should probably invest more in those.


https://www.nature.com/articles/s41586-026-10234-y

Advancing operational global aerosol forecasting with machine learning - Nature

Reliable 5-day, 3-hourly forecasts of aerosol optical components and surface concentrations are obtained in 1 minute using a machine-learning-driven forecasting system.

Nature
Show threadValentin
@Ruth_Mottram Even just the tooling: running large inversions can be orders of magnitude faster when using tinygrad or torch instead of numpy and the code basically looks the same. Being able to do something in a few seconds instead of hours means you can run more/different scenarios.
Mar 9 at 11:42amWeb