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by baryphonic
1910 days ago
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Training a decently large ML model requires a huge amount of compute power. There exists specialized hardware for these purposes (e.g. TPUs, FPGAs, bespoke ASICs or even the giant wafer-sized chips from Cerebras). Besides, even after training, inference can also require huge amounts of computing power, with data requirements only a fraction of those during training. The energy usage of ML is astonishingly high, even at inference time. Getting it down to the energy efficiency of human brains is a major area of research, sort of like proof of stake. The parallels between the two domains are very strong for those who are well-versed in them, but some people seem to pick one or the other as "too dangerous to keep around" for some reason, which is literally the Luddite stance. |
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"The Luddites were an early 19th century radical group which destroyed textile machinery as a form of protest. The group was protesting against the use of machinery in a "fraudulent and deceitful manner" to get around standard labour practices."
That's not "because they thought textile machinery was too dangerous to keep around" or "because they hate technology".