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Breathtaking!

First, your (Lina's) intro is perfect in honestly and briefly explaining your work in progress.

Second, the example I tried had a perfect interpretation of the text meaning/sentiment and translated that to vocal and facial emphasis.

It's possible I hit on a pre-trained sentence. With the default manly-man I used the phrase, "Now is the time for all good men to come to the aid of their country."

Third, this is a fantastic niche opportunity - a billion+ memes a year - where each variant could require coming back to you.

Do you have plans to be able to start with an existing one and make variants of it? Is the model such that your service could store the model state for users to work from if they e.g., needed to localize the same phrase or render the same expressivity on different facial phenotypes?

I can also imagine your building different models for niches: faces speaking, faces aging (forward and back); outside of humans: cartoon transformers, cartoon pratfalls.

Finally, I can see both B2C and B2B, and growth/exit strategies for both.




Thank you! You captured the things we're excited about really well. And I'm glad your video was good! Honestly, I'd be surprised if that sentence was in the training data... but that default guy tends to always look good.

Yes, we plan on allowing people to store their generations, make variations, mix-and-match faces with audios, etc. We have more of an editor-like experience (script-to-video) in the rest of our web app but haven't had time to move the new V2 model there yet. Soon!




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