Stories by AI, fiction written with GPT-3 and illustrated with DALL-E 2

Hacker News

Hi HN! I and a couple of friends finally launched a project that's been kicking around since late last year: Stories by AI The spark of the idea was actually inspired by another Show HN ("I had some time yesterday so I made a GPT3 podcast to help you sleep" https://news.ycombinator.com/item?id=29428910 ). With the emergence of nice tools for co-writing fiction with GPT-3, I really liked the idea of publishing a bunch of short fiction where the AI largely did the writing. I still find the surreal fever-dream esque weirdness of language models really entertaining, and hope we can capture that in story form. And now these weird stories can be illustrated with DALL-E 2, which adds another layer to the fun. It took a while, but today we are launching our substack newsletter and podcast! The podcast has audio versions of the stories made with Text to Speech, of course. That's about it, would love to hear your feedback / thoughts about this.

Visit product View on Hacker NewsAug 1, 2022

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, new, models · Missing: mac, agents, macos

70%70% 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, podcasting

67%67% predicted probability of success on Indie Hackers, 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

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.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

42%42% 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

34%34% 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

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto

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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