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Morning Bob – A Daily News 1930s Style Radio Show Example

Hacker News

Morning Bob – A Daily News 1930s Style Radio Show Example

All - Wanted to share an example of a news show in the style of old radio. Not sure if its worth doing but I was thinking of starting a YouTube channel around it. Oh, this is HN so the tech: Bing News API to fetch todays articles based on categories Gemini to process them to get a script Elevenlabs (on Sieve) for the voice over Remotion to create video with image, audio visualizer, audio files and a lil bit of radio static. Would appreciate any feedback! What do you think would make this more compelling? Thanks!

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Actual performance

2points
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, visual, elevenlabs · Missing: mac, agents, macos
68%68% 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 · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting
63%63% predicted probability of success on Indie Hackers, 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.
TrustMRRLess likely to generate early MRR · Strong signals: video, visualize · Missing: mobile apps, ios, personal
38%38% 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
32%32% 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: audio · Missing: web3, chat, crypto
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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