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Isn't this product kind of impossible? Like a compression program that compresses compressed files? If you have an algorithm for determining whether a generated image is good or bad couldn't the same logic be incorporated into the network so that it doesn't generate bad images?
E: or how it's supposed to work.
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We're building prompt alignment models too so you can objectively see how well SDXL follows your prompt :)
Are you building prompt alignment model alignment models so I can objectively see how well what your prompt alignment model is judging SDXL’s interpretation of my prompt against aligns with my prompt? Quis custodiet ipsos custodes?
Isn't this product kind of impossible? Like a compression program that compresses compressed files? If you have an algorithm for determining whether a generated image is good or bad couldn't the same logic be incorporated into the network so that it doesn't generate bad images?
Fundamentally it sounds like you built an ML model(s) and are trying to monetize it behind an API. How does that work medium-term? Are you expecting there won't be open source alternatives, is your value in hosting the model (and if so will you open source yours) or is there another angle. I've built ML models and looked into how to monetize them, and overall it seems like a tough play without the model being part of…
The way we think about it is that we're building a product for organizations in scaling mode, and they have deep needs on the product-side. Flexibility on filtering, different client-libraries, a clean observability interface, etc...
It's possible that we open-source parts of our models, but fundamentally we think we can capture value by building a great all-around web product, and not just a set of eval models.
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Are you building prompt alignment model alignment models so I can objectively see how well what your prompt alignment model is judging SDXL’s interpretation of my prompt against aligns with my prompt? Quis custodiet ipsos custodes?
Its how your prompt aligns with the SDXL image output, not how your prompt aligns with SDXL's interpretation of your prompt
Isn't this product kind of impossible? Like a compression program that compresses compressed files? If you have an algorithm for determining whether a generated image is good or bad couldn't the same logic be incorporated into the network so that it doesn't generate bad images?
We’re optimistic about using our own algorithms and models to evaluate another model. In theoretical computer science, it is easier to verify a correct solution than to generate a correct solution (P vs NP problem).
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actually very cool to me that you remember these pivots. From the inside these pivots were about solving problems we faced with our previous idea. We mainly pivoted either because we discovered the market wasn't great, or we didn't have founder-market fit with the idea. There's a gut feeling aspect that plays in there as well, but it's mostly been analytical approach.
Thank you for answering. Best of luck with this idea!