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Create short form videos on any topic using Generative AI

Hacker News

Create short form videos on any topic using Generative AI

Hey HN, Long time lurker first time posting. This is a streamlit app I wrote as a side project. It's a Generative AI webapp for creating short 30 second informative videos on any topic or subject under the sun. It's not perfect by any means, but a cool demo. It takes around a minute to generate so please be patient. Email is optional, only if you want link to watermark removed completed video clip. Any feedback/suggestions would be appreciated. Thanks! JD P.S. I am actively looking for Senior Python/DevOps/MLOps roles in California. Contact info in my profile. Thanks.

Visit productView on Hacker NewsSep 28, 2023
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: email, using · Missing: mac, agents, macos
76%76% 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
55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal
41%41% 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
39%39% predicted probability of success on AppSumo, 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
29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: active · 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
7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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