Gistpod: Lost Einstein – Who Becomes an Inventor in USA?

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Hello HN, I am a policy person who is often found reading papers. I built this app to curate papers that have piqued my interests to share them with wider audience. One thing that I have repeatedly heard academics say is that no one reads their research. So I thought may be this is one way to consume for everyone that I genuinely find beautiful: answers to really important questions. As I read this particular paper, for example, I kept thinking, how big our productivity gains shall be if we could improve education in the more underprivileged areas of the world. I hope you like it as much I loved reading it! Paper link here too: https://www.nber.org/papers/w24062

Visit product View on Hacker NewsJul 24, 2025

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

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: answers, way, education · Missing: mobile apps, ios, personal

57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

14%14% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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