GP

GPTKit – ChatGPT and AI Generated Text Detection Tool

Hacker News

GPTKit – ChatGPT and AI Generated Text Detection Tool

Hey, HN community, We are thrilled to introduce GPTKit, our AI text generation detection tool that helps users identify human-written and machine-generated text. With GPTKit, detecting generated text is easy and accurate. Our tool uses 6 distinct methods to classify text with a 90% accuracy rate, based on testing a dataset of 100K samples. We would love to hear your thoughts on GPTKit, please give it a try and let us know your feedback. You can check it out at https://gptkit.ai Cheers!

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Actual performance

4points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
83%83% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: mac, user, chatgpt · Missing: agents, macos, agent
44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
27%27% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat, introduce · Missing: web3, crypto, cryptocurrency
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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