Sure, it's a fairly useless right wing technology mostly in the service of the ideologies of Von Mises and Austrian Economics but we're all adults here.
Good things can come from anywhere. Stanford, for instance, was founded after a dream where a ghost of a guy's dead teenager appeared (who bears the namesake of the institution[1]) and was initially run by his wife who made her executive decisions by talking to spirits over oujia boards but it'd be foolish to hang that around the instution's neck today and dismiss its contributions.
In the same way, crypto work might have indirect long lasting positive impacts in things such as CPU efficiency, chip design, algorithm research, parallel computing, and machine learning with specific focus on time-series. We should be able to look past the Do Kwon fiasco for that.
[1] it's officially "Leland Stanford Junior University" - who was the ghost - read "Who Killed Jane Stanford?" for more info https://wwnorton.com/books/9781324004332
crypto work might have indirect long lasting positive impacts in things such as CPU efficiency, chip design, algorithm research, parallel computing, and machine learning with specific focus on time-series.
I cannot see any connection between Markel tree algorithms and chip design (or any of the other domains you mention). Can you point me to such work in these areas?
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Sure, it's a fairly useless right wing technology mostly in the service of the ideologies of Von Mises and Austrian Economics but we're all adults here.
Good things can come from anywhere. Stanford, for instance, was founded after a dream where a ghost of a guy's dead teenager appeared (who bears the namesake of the institution[1]) and was initially run by his wife who made her executive decisions by talking to spirits over oujia boards but it'd be foolish to hang that around the instution's neck today and dismiss its contributions.
In the same way, crypto work might have indirect long lasting positive impacts in things such as CPU efficiency, chip design, algorithm research, parallel computing, and machine learning with specific focus on time-series. We should be able to look past the Do Kwon fiasco for that.
[1] it's officially "Leland Stanford Junior University" - who was the ghost - read "Who Killed Jane Stanford?" for more info https://wwnorton.com/books/9781324004332
I cannot see any connection between Markel tree algorithms and chip design (or any of the other domains you mention). Can you point me to such work in these areas?
Work in crypto mining efficiency? That's a pretty substantial field.
I don't do it personally but I know there's lots of research, products, companies and investments in it.