Plato's Euthyphro Highly Abridged

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SOCRATES: Then tell me, how do you define piety and impiety?...do you recollect that what I urged you to do was not to tell me about one or two of these many pious actions, but to describe the actual feature that makes all pious actions pious? EUTHYPHRO: ...I should say that piety is what all the gods love, and that the opposite, what all the gods hate, is impiety. SOCRATES:...Is what is pious loved by the gods because it is pious, or is it pious because it is loved?...Do we speak of things as carried and carrying, led and leading, seen and seeing? and do you understand that in all such pairs of terms each is different from the other, and in what way they are different?...So we don't see a thing because it is a seen thing, but...it is a seen thing because we see it...if anything is...acted upon in any way...it is not acted upon because it is the object of an action, but it is the object of an action because it is acted upon...isn't a loved thing...the object of some action?... Then what is god-beloved is not the same as what is pious...Because we agree that what is pious is loved because it is pious, and not pious because it is loved...And...what is god-beloved is god-beloved because the gods love it, from the very fact of their loving it; and that they do not love it because it is god-beloved... But if what is god-beloved were identical with what is pious...then if what is pious were loved because it was pious, what is god-beloved would be loved because it is god-beloved...As it is, you can see that the relation between them is just the opposite; which shows that they are entirely different from each other.

Visit product View on Hacker NewsMay 20, 2020

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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