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Channel 784, infinite AI generated fake news

Hacker News

Channel 784, infinite AI generated fake news

I was inspired by Nothing Forever to make something while it's off air - Channel 784. It's a parody of evening news. How it works: I have a Node server that generates headlines, then expands each one and creates an intro and outro based on them, and then passes the headlines to DALL-E to generate pictures for each story and the stories to Google Cloud to generate speech. Then I save that as a JSON and load it into Unreal Engine. I'm not sure it's as funny as Nothing Forever, it's a bit more structured. If anyone's got any suggestions I'd love to hear them.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
75%75% 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: io · Missing: https docs, excited, just released
55%55% 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 HuntOn track for Day 1 leaderboard · Strong signals: google, new · Missing: mac, agents, macos
55%55% predicted probability of success on Product Hunt, 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.
TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal
29%29% 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
19%19% 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
8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

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