> And for those opposed to generative AI on principled or functional grounds, putting similar energy into millions of Nvidia AI servers probably seems like just

> And for those opposed to generative AI on principled or functional grounds, putting similar energy into millions of Nvidia AI servers probably seems like just as big of an energy waste. while there is value and money-grifting involved in both crypto and genAI, there is a major differentiating factor between the wastage argument - artificially-adjusted proof of work, which is/was used for major cryptocurrencies. people spend time and energy (figuratively and literally) on the internet on many ways one could define as wastefully (take scrolling down the "for you" feed for example). but for majority of cases, the "efficiencies" or their lack of are not done intentionally and are often improved on (e.g. new codecs like AV1 needing less bandwidth). but to make crypto tokens work, the original decision of using PoW has led to a massive surge of energy consumption to achieve the same results. while there might be some work on countering its negatives (e.g. with eth network), it is still a major driving force, despite an arms race to make more efficient hardware. while a lot of current AI has major inefficiencies (will be too long to list down here!), the root cause is often the fast-moving innovations and everyone building on someone's imperfect work. coming back to the original argument, you should expect more dedicated hardware to do the underlying matrix multiplications to make AI work. for most people who would only care about inference, it is already becoming a reality at consumer level. but expect people to push the new stuff to its limit to stay competitive, whether you find all of this ridiculous or not.