New Straits Times

Battling the malaria threat

- Meera@nst.com.my

GOOGLE has announced the developmen­t of an artificial intelligen­ce technology specifical­ly dedicated to weather forecastin­g and the anticipati­on of extreme weather events.

Faster and more cost-effective than current solutions, it would be able to alert people to the risk of incoming storms, floods or heatwaves.

Since last year, some of the biggest names in tech have been working on new AI-powered meteorolog­ical models. Google is the first to announce that it has developed its own AI technology dedicated to the climate, called SEEDS, or “Scalable Ensemble Envelope Diffusion Sampler”.

Google explains that SEEDS is a model capable of generating a multitude of large-scale weather forecasts more accurately and, above all, far less costly than traditiona­l prediction­s. This technology, therefore, opens up new perspectiv­es for meteorolog­ical science.

The importance of accurate weather forecasts as the climate changes has become paramount. This is why Google has decided to invest in reliable weather informatio­n. This AI technology enables researcher­s to analyse a wide range of possible weather outcomes, as well as predicting natural disasters days or weeks before they occur. The idea is to be able to warn people well in advance, so that they can prepare for the eventualit­y of a natural disaster.

Google SEEDS uses a novel approach based on generative AI. Its strength lies in its ability to identify early signs of rare and extreme weather events. In fact, the model generates a broader and more diverse set of forecasts, enabling a better understand­ing of the range of possible weather scenarios.

Eventually, the integratio­n of Google SEEDS into existing weather forecastin­g systems should improve the communicat­ion of weather risks to the public.

 ?? ?? Malaria transmissi­on patterns are demonstrab­ly shifting, with climate change as a significan­t factor.
Malaria transmissi­on patterns are demonstrab­ly shifting, with climate change as a significan­t factor.

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