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AI Software Development – What Does The Data Say? (codemanship.wordpress.com)

submitted 1 day ago* (last edited 1 day ago) by rimu@piefed.social to c/programming@programming.dev

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studies show a clear trend – output is up (more code, more commits, bigger diffs), but outcomes don’t reflect that trend. If anything, the average team is taking longer to ship worse software

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[–] blarghly@lemmy.world 1 points 1 day ago (1 children)

I was gonna say - the bulk of weather forcasting is done by governments. Commercial weather channels/sites/apps draw from these predictions and give them a nice interface, and sometimes apply some proprietary prediction algorithm (eg, a lot of commercial weather services bump up chance of rain, because people are angrier when it rains when you said it wouldnt, versus doesnt rain when you said it would).

But I wouldnt expect government forecasts to have changed due to AI tools. Except maybe in the US due to the DOGE debacle - but even then, why fuck with it?

[–] WhatAmLemmy@lemmy.world 1 points 21 hours ago

I wasn't implying that LLM's have damaged the science or statistics of forecasting. I was implying that they could have degraded the software at any point in the chain from data collection device firmware, to ingestion pipelines, to the app on your device; perhaps even impacting the meteorologists ability to perform quality work themselves.

Except maybe in the US due to the DOGE debacle - but even then, why fuck with it?

Changing ANY data source will always have some degree of impact on ALL statistical modeling that utilises it. Global meteorologists have depended on data captured from NASA/NOAA satellites in some capacity since the 1970's, by virtue of Americas lead in the space race and soft power in offering this data freely to everyone since the 1970's.

DOGE/Fascist crimes specifically targeted government scientific institutions and their ability to operate.

https://www.abc.net.au/news/2025-08-08/australian-weather-forecast-under-threat-from-us-cuts/105611736