eleitl

joined 4 years ago
MODERATOR OF
[–] eleitl@lemmy.ml 2 points 8 months ago

Looks nice, thanks.

[–] eleitl@lemmy.ml 21 points 8 months ago
[–] eleitl@lemmy.ml 6 points 8 months ago

If it's not Covid-19 it's Russia's "unprovoked attack".

Actually it's a systemic crisis, which is not solvable in principle. UK is just somewhat ahead of the rest on the way down.

[–] eleitl@lemmy.ml 3 points 8 months ago

She's definitely the right person to lose the war. She has a professional track record of screwing things up.

[–] eleitl@lemmy.ml 2 points 8 months ago

The sanctions are working. We need more of them.

[–] eleitl@lemmy.ml 2 points 8 months ago

8 tons? I wonder how InP on mylar PV would scale up for power density to mass. It would probably be dual-useable as a solar sail too.

[–] eleitl@lemmy.ml 1 points 8 months ago

Interesting numbers. I wonder what the current ceiling would be if WSI maxed out a la Cerebras. We're getting close to what is doable with classical crunch in semiconductor photolithography at reasonable (MW not GW) power footprint and while still borderline affordable. There is some very limited stacking potential with WSI and some potential with architecture (analog compute and spiking networks) to improve things. Maybe two orders of magnitude in total.

[–] eleitl@lemmy.ml 1 points 8 months ago

https://www.nature.com/articles/s41467-024-46349-x

Pitfalls in diagnosing temperature extremes

Lukas Brunner & Aiko Voigt

Nature Communications volume 15, Article number: 2087 (2024)

Abstract

Worsening temperature extremes are among the most severe impacts of human-induced climate change. These extremes are often defined as rare events that exceed a specific percentile threshold within the distribution of daily maximum temperature. The percentile-based approach is chosen to follow regional and seasonal temperature variations so that extremes can occur globally and in all seasons, and frequently uses a running seasonal window to increase the sample size for the threshold calculation. Here, we show that running seasonal windows as used in many studies in recent years introduce a time-, region-, and dataset-depended bias that can lead to a striking underestimation of the expected extreme frequency. We reveal that this bias arises from artificially mixing the mean seasonal cycle into the extreme threshold and propose a simple solution that essentially eliminates it. We then use the corrected extreme frequency as reference to show that the bias also leads to an overestimation of future heatwave changes by as much as 30% in some regions. Based on these results we stress that running seasonal windows should not be used without correction for estimating extremes and their impacts.

[–] eleitl@lemmy.ml 6 points 8 months ago

I use a LineageOS phone with nanogapps which can run a TAN app but I use a hardware TAN generator instead which is far more secure.

My tablet is pure LineageOS without any Google services.

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#272: “Peak almost everything”, part two (surplusenergyeconomics.wordpress.com)
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Stragedy Unfolds (thehonestsorcerer.substack.com)
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