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Joined 1 year ago
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Cake day: June 12th, 2023

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  • Machine Learning tech has been around for decades. It just became sorta a little bit useful (outside of super specialized uses like photo post-processing or chess engines) around 2017 or so, and since then has exploded in capability, at a speed that the public is kind of incapable of comprehending.

    It went from the approximate intelligence of a toddler to a smart high schooler in about 4.5 years, in the last 1.5 years it has nearly reached the level of a STEM PHD in several areas, if the latest whitepapers are to be trusted. And of course it’s been much faster than us at reading, interpreting context and summarizing information accurately for a couple years as well.

    DeepMind cracked the Protein Folding problem, and that’s old news.

    I honestly don’t think people are ready for how fast AI has been improving.







  • Depends on how it’s implemented. If they have a version of Proton that translates all x86 windows syscalls to ARM Linux, some operations could be extremely efficient.

    There’s definitely got to be more overhead overall, though. Especially for devices with memory page sizes other than 4K, like the M-series Apple chips do (they use 16K as their page size), likely a VM will need to be sandwiched in there to ensure memory alignment. It’ll more fully be emulation and not just translation.