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consumer RAM is not what's creating shortage. Data centers doesn't run electron to train the model or for inference
by throwaw12 8mo ago
consumer RAM is not what's creating shortage. Data centers doesn't run electron to train the model or for inference
- malfist 8mo agoSure, consumer ram isn't causing a shortage, but it's affected by the shortage.
- bayindirh 8mo agoEvery RAM producer is stopping their consumer grade RAM production to provide ECC-RAM and VRAM now. Micron discontinued and closed down Crucial brand as a whole. 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.
- spockz 8mo agoI have a silent hope that because of this change we all will get ECC ram and that consumer CPUs will get proper support for them.
- bayindirh 8mo agoAMD's RYZEN already supports it. ASUStor's latest generation of NAS devices come with AMD x86_64 processors and ECC RAM as a standard, but ECC RAM in SODIMM format was not cheap, even when the RAM was cheap, either.
- spockz 8mo agoI understood that support for ECC ram also depended on the motherboard but not sure. When selecting Ryzens, I only recall seeing many disclaimers for RAM support. Not sure to the causes though.
- wiredpancake 8mo ago[dead]
- eggsome 8mo agoAs someone trying to spec out a Ryzen workstation right now I can tell you it's actually harder because Ryzen (unlike EPIC) uses UDIMM ECC, not RDIMM ECC. It's a niche that very few companies wanted to service before AI ram madness. Now the only vendor I can find is v-color: https://v-color.net/products/ddr5-ecc-oc-u-dimm-server-memory 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 :(
- blibble 8mo agoECC ram uses the same chips, just an extra one on the dimm
- MagicMoonlight 8mo agoThey effectively do. They’re trained by brute forcing 100TB of training data through them, rather than any logical learning technique. A human doesn’t need 100TB of books to learn the alphabet.
- rkomorn 8mo ago> 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.
- bayindirh 8mo agoI used a single letter stencil to learn the alphabet, actually, and nobody strapped me to a chair to watch or listen something 16h a day. Living inside a normal home with my parents was enough for the audio part.
- rkomorn 8mo agoThe 16 hours of audio/video per day was a reference to being alive and hearing/seeing things for years before you actually could learn the alphabet. It was not meant as literally sitting at a screen with audio/video for 16 hours a day.
- bayindirh 8mo agoI know, but the density of the data is much less in human case. 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.
- rkomorn 8mo ago> 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 To me, these statements strongly contradict each other, but I also really do not care enough to debate it.
- mv4 8mo agoThe problem is manufactures are shifting their production capacities towards the more profitable, high-performance "AI" components.