alecmg

the mechanism of it is not that paper is saturated with water, but that while there is water in the container, paper doesn't get hotter than 100C and a bit, not enough to ignite.

nothing like Russian, South Asian maybe

oh great, they are not using a confusing name anymore... wait, now they are using a stupid name!

Could it be quantified how much UK is using coal power of other countries?

Since industry is moved outside, the products we consume use power of producer country, mostly China. Is there a correlation in reduction of local coal power and amount of energy intensive products imported?

I WISH it would be prefetching video in background while showing ads.

But no, always goes to spinny wheel buffering after ad ends. Oh, and thats after having some spinny wheel to load the ad in first place ffs.

~100 MB/s write speeds?

what use case needs an SD card that can be written for 40000 seconds?

> The new 4K 32" 3rd gen QD-OLED panels seem to be the closest to perfection, but I'm not sure if they're suitable for long sessions of programming, web browsing and reading documentation (i.e. displaying static UI elements for hours) due to burn-in and temporary image retention.

Wouldn't worry about burn-in. 3rd gen should be more durable and equipped with all kind of burn-in mitigation tech. And a 2-3 year burn-in warranty

My concern about OLED used to be the weird pixel layout, not great for text. But on 4k QD-OLED pixels are smaller, so text fringing is not noticeable. And LG WOLED coming this year should have no problem at all.

Not an issue if they have a means of propulsion capable of delivering 1g the whole way

Which is necessary to go any meaningful distance in space anyway

ahh, I wish they included speed comparison to numpy.average

I know, thats not the point and average was only picked as a simple example, but still...

definite deja vu from Optane

Capacity and price killed it, no word about these in the article

I saw comments that if introduced together with Faster CPython single thread performance optimisations, nogil would end up no slower than previous version. So it is best time to implement

maybe its a reference to Amdahl's law?

If you can parallelise 90% of your code, you get only 10x improvement even on infinite number of cores

I think that site opted for consistent graphs - points lower on the graph is faster/better, indicated by blue down arrow

without knowing much of either, sounds like petalisp to lisp relation is numba to python. Or numba to numpy?