Ri

Riffusion with Lyrics

Hacker News

Riffusion with Lyrics

Almost a year ago someone stumbled upon our hobby project and posted it to HN (edit: https://news.ycombinator.com/item?id=33999162 ). It was magical to see so many of you enjoy something we built for our love of music. We’re back today with a real product and are excited to see what you think! riffusion.com lets you create original music via short, shareable audio clips called “riffs”. You describe the lyrics and a musical style to generate riffs complete with singing and custom artwork in a few seconds. From inspiring musicians, to wishing your mom a ‘good morning!’, we are having a lot of fun with riffs as a form of expression and communication. We hope you have as much of a blast traveling the latent space of music as we did making it. You can generate music from text, remix other riffs, or record your own lyric timings. A riff for HN: https://www.riffusion.com/riffs/ac7ff4c3-d86d-4dfa-884e-bb19... Hayk + Seth

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Actual performance

186points
49comments
Made the leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: excited, io · Missing: https docs, just released, exist
67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos
46%46% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
45%45% 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
14%14% 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
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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