As
Ask My Book
Hacker NewsAsk My Book
Hey HN! I’ve spent the past couple weekends building Ask My Book. You can use Ask My Book to ask a question and get an answer in my voice. It's an experiment in using AI to make my book’s content more accessible. Instead of reading 52,000 words, you can ask a question and get a sub 100-word answer. I'd prefer people read my book! But not everyone has the time... Give it a shot, and let me know what you think. APIs used: GPT-3 (+ embeddings), and Resemble for the voice.
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Product HuntOn track for Day 1 leaderboard · Strong signals: using, apis · Missing: mac, agents, macos77%77% 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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released58%58% 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 · Missing: mobile apps, ios, personal47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive30%30% 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, revenue21%21% 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, crypto1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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