Twenty questions using GPT-3 API

Hacker News

Hi, I build the twenty questions game using GPT-3. It was a fun trying to use GPT-3 to provide specific answers. To play - I found it works best if you ask full question. It is not 100% fool proof. It gets confused with few questions - like it may say No to both "is player retired" or "is player active" If question is single word but it is somehow associated with the word to be guessed, it would say Yes. Once the game is over (or if you give up) it would show the final answer and few lines of information. I hope you like it. Any suggestions / issues welcome. Thanks!

Visit product View on Hacker NewsJan 3, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: single, using · Missing: mac, agents, macos

75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

67%67% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

59%59% 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

41%41% 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

39%39% 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 · Strong signals: active · Missing: arr, mrr, revenue

13%13% 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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