Sora Videos – Generated by the Sora AI model, currently with 107

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一、Website Features The website has compiled basically all the videos currently generated by Sora (some videos are not fully displayed because they are just regenerated by changing some parameters, and there are many similar parts). Currently, there are 107+ videos, and newly generated videos will be updated in time. 1、Timely updates: New videos generated using Sora will be updated on the website in a timely manner, currently it should be the most up-to-date and comprehensive; 2、Video categorization: Videos are categorized according to the way they are generated: text-generated videos, image-generated videos, video-to-video stitching parts, and parts where there are some defects in the currently generated videos. This allows for a more convenient experience of its different capabilities; 3、Includes prompt words: Videos with prompt words also display the corresponding prompt words under the video, and you can try using the same prompt words in other video generation software; 4、Source display: The source of each video is displayed. Most of the early videos were released by the official openAI, so the source and time are the first time Sora was released; subsequent videos were released by the main creators on Twitter; 5、Display release time: Each video has a corresponding release time, sorted in reverse chronological order, so you can see the latest videos every time you come in; Everyone is welcome to experience online: https://soravideos.media If you have any ideas or suggestions, you are also very welcome to leave a message.

Visit product View on Hacker NewsFeb 19, 2024

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting

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48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: video, way, para · Missing: mobile apps, ios, personal

48%48% predicted probability of success on TrustMRR, 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

25%25% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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