Talk to Me Human – my game about social persuasion

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Hey all, I recently graduated from a good PhD program studying NLP. Unlike any sane person who would go become a professor or make a gazillion dollars in industry, I decided to try bootstrapping my own software business. This is my first product. The inspiration was from my research on computers understanding social norms. When ChatGPT came out, I was amazed how well it could understand social etiquette. I thought it'd be fun to make a game where you have to talk your way out of sticky situations - like you miss your friend's birthday party, or your boss catches you trying to leave work at 2pm. I made a prototype in a couple days, and it was super fun to play with. I thought I'd spend a "couple months" making a game for others to play online. Now, only 10 months and 923.3 hours of work later, it's playable in early access. In the game, you talk out loud (ASR), and the NPCs (LLM + TTS) talk back at you. It is fun to play with a friend! And because it's just talking, non-gamers do great, often better than gamers. I really want to have a free demo, but no time yet to implement. For now, it's purchase only ($4.99). If anyone decides to try it, I'd really love to get more feedback. It was an enormous learning experience, especially targeting the web - so many partially supported web APIs and browser inconsistencies! Still feels like 2008 in some ways. Also happy to answer questions of course. Thanks, and enjoy the weekend!

Visit product View on Hacker NewsApr 19, 2024

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

92%92% 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 · Strong signals: computer, chatgpt, apis · Missing: mac, agents, macos

84%84% 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

51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

46%46% predicted probability of success on TrustMRR, 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.

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

19%19% 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 · Missing: web3, crypto, cryptocurrency

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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