> It seems we will run out of hardware by March?
What happens when an unstoppable force (building everything in Electron because hardware is cheap) meets an immovable object (oh no hardware is expensive now)?
What happens when an unstoppable force (building everything in Electron because hardware is cheap) meets an immovable object (oh no hardware is expensive now)?
Resource constraints have often helped me come up with stuff that I'm actually proud of.
A human doesn’t need 100TB of books to learn the alphabet.
A human does need 16ish hours per day of audio/video content for several years to learn the alphabet.
Living inside a normal home with my parents was enough for the audio part.
It was not meant as literally sitting at a screen with audio/video for 16 hours a day.
IOW, humans still learn more effectively with less information, because there are innate mechanisms which process this data continuously and extract new meanings from the same data. This is part of both intelligence and consciousness.
LLMs lack both.
> because there are innate mechanisms which process this data continuously and extract new meanings from the same data
To me, these statements strongly contradict each other, but I also really do not care enough to debate it.
Have a nice day.
Is that really the case? How much data is it for 4k video, high bitrate auditory, spacial mapping, internal and external nervous system, emotions, and a dataset to correlate all of these in time?
So, getting systems with higher RAM capacity is getting harder (from laptops to smartphones). So, for a couple of years, we need to stop using Electron so much and use what we have efficiently.
Data centers, esp. AI hyperscalers do not care about efficiency for now, because they can suffocate consumer-grade part of the hardware marketplace and get anything and everything they want. When their bubble pops, or the whole capacity ends, they need to learn to be efficient, too.
For reference, a well-optimized cluster runs at ~90% efficiency even though they have thousands of users. AI hyperscalers are not there. Maybe 60% efficient, at most. They waste a lot of resources to keep their momentum.
https://v-color.net/products/ddr5-ecc-oc-u-dimm-server-memor...
But they no longer have 6000mhz stuff in stock (which is ideal for Ryzen due to the 1 to 1 speed match to the memory controller).
It's frustrating :(
https://users.rust-lang.org/t/energy-consumption-in-programm...
Also, Typescript 5 times worse than Javascript? That doesn't really make sense, since they share the same runtime.
See this example as one demonstration: https://www.typescriptlang.org/play/?q=8#example/enums
The TS code looks very different from the JS code (which obviously is the point), but given that, not hard to imagine they have different runtime characteristics, especially for people who don't understand the inside and outs of JavaScript itself, and have only learned TypeScript.
One thing to consider, is that with JavaScript you put it in a .js file, point a HTML page at it, and that's it.
TypeScript uses a ton more than that, which would impact the amount of energy usage too, not to mention everything running the package registries and what not. Not sure if this is why the difference is bigger, as I haven't read the paper myself :)
But if you do, please do share what you find out about their methodology.
The resource consumption b/w rust and golang would be pretty minimal to figure out actually for most use cases imho.