CFR Explorer – Finding aviation answers using AI

Hacker News

I've been wondering how can recent advances in AI can help with exploring regulations (currently related to aviation). Here is a beta app which uses embeddings to search and then uses GPT to quickly provide pilots with answers to aviation regulations in Title 14. Please note that this is a beta version, so errors may occur and you should always verify the response. I welcome feedback and suggestions to help improve the app. If you find an answer helpful, don't forget to give it a thumbs up, and if you think an answer could be improved, please give it a thumbs down.

Visit product View on Hacker NewsDec 29, 2022

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5points

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

59%59% predicted probability of success on TrustMRR, 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 · Strong signals: using · Missing: mac, agents, macos

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

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

40%40% 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

37%37% predicted probability of success on AppSumo, 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

32%32% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

12%12% 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.

Correct prediction on native model

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