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https://dam.stanford.edu/memory-prices.html

Pretty sure those devs were saying the same thing way before 2017 as well, which seems to be ~ the last time RAM was this expensive.

Now RAM in the cloud, now you're really paying the Java premium.

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Price per GiB is skewed by definition. 10 Years ago, 8GiB was enough and cost between $10 and $20. For the longest time this century, a cheap build was in the $250 to $350 range. Nowadays I'm having trouble with that price range building from used parts.
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According to your link, DDR5 today has the same price in real US $ as DDR3 was in 2014, during a brief spike towards high prices.

Since that peak in 2014 until today, the prices were lower than now. The peak in 2017 was more than 10% lower than today.

To reach permanently higher prices than today, we must go backwards until 2011.

So we have already regressed at least 12 years into the past, but more likely 15 years, and it is unknown how much more we will regress.

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> we have already regressed at least...

It seems worth noting here that DDR5 RAM is faster than DDR3 RAM, and was not even available until 2020.

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Thanks to AI, we can now one-shot convert electron to native apps ;-)
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Recipe for delicious pizza:

1. Make extra greasy pizza. Nauseating-level of grease.

2. Put pizza through De-Greasinator 5000.

Sounds efficient.

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You only need to make the app once before running it on a million computers. So it's more like greasy flavor development, then de-greasinating the recipe before going into mass production. It's not a big efficiency impact overall, it's more about how you like to spend your flavor development time.
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The grease is vaporised and inhaled by one randomly chosen Memphis resident, who permanently gets chronic asthma.
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Maybe they should start with Claude.
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"it converted my gambling app into a three-armed bandit!"
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Yeah would someone like to explain why there's an octopus in the break room?
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OK I’ll take the bait.

Were devs supposed to optimize RAM for a shortage that might come? I’m guessing you had enough foresight to stockpile RAM?

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What’s implied here is that devs were supposed to optimize for user resources, not for developer convenience.
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Maybe we can have AI rewrite those programs and optimize for low ram usage
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They were supposed to optimize for the situation in which they weren't the only program running on a computer, and they failed to do it.
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Can you blame them? Users didn't care. Heck, developers didn't care - look at how popular vscode is.
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Honestly, despite being Electron VSCode manages to outspeed every other editor on my machine (by qualitative metrics), even stuff like Zed (which manages to lag on stuff VSCode doesn’t despite performance being its main selling point)
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Revealed preferences aside, every dev comment section for 10 years HAS been full of people loudly insulting Electron.
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Time to bring back 32 bit OS, that way you only need 4GB RAM per computer!
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640k ought to be enough for anybody. Sorry had to be said.
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Bad times for the two-space copying garbage collectors.
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Are there any of those left? The popular VMs for Java, Javascript and dotnet are all very mature heavily tuned designs.
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My benchmark:

1) .net app, one text field, one button; private bytes 22mb, working set 27mb

2) native app, two text fields, three buttons; private bytes 1.2mb, working set 7.3mb

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3) electron, about:blank, 1.2GiB
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electron, about:blank, 90mb

Just tested

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That's better than the GTK4 hello world I tried out last year.
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Seconded, the only 1.2 GB electron app I’ve made had a ~500MB ML model’s weights embedded in it
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They're heavily tuned but I think having the generational hypothesis and copying longer-lived objects is still standard? As is allowing a fair amount of garbage to accumulate to increase throughput and reduce copying at the cost of memory footprint?

Posting instead of researching in hopes someone smarter can chime in, because I'm lazy.

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That's tech... Moore Law was steadily going until raw CPU got stuck for a few years, switching from single core to multicore then heterogeneous cpus, all those requiring to rewrite software in a scalable manner and then consider newer schedulers switching between performance/efficiency cores and changing CPU freqs.

Also, you have Meta and Google investing in simplified performant versions of their stack for developing countries which is similar.

What's funny though, I see people that sometimes says it's cheaper to build the app they need in a single prompt than to search for it.

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You know that Moore's law is about transistor count? What worked really well for CPU in eg the 1990s was Dennard scaling. That drove the Hz higher. And Dennard scaling is what stopped working.

Moore's law is alive and well.

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It also was just an observation, not a strict rule set in stone
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Moore's "Law" is not a law, it's just an observation of market forces at a particular time.
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