To be very clear, I never said open-source is a problem.
In fact, Rubbrband started as an open-source project.
Each member of our team are ML researchers who have committed tens of thousands of lines to open-source.
I think you're conflating open-source with local installations. Our founding team was not fan of the interfaces that a lot of these projects have for our use cases. Not to mention, our hardware just doesn't run them.
yeah we went through a few pivots actually - Rubbrband was initially a mobile app for musicians. It would listen to your practice sessions and give feedback. We pivoted out of this primarily because of issues with the technology and market.
We don't offer any non-free-to-use checkpoints/LORAs on the platform out-of-the-box. If you wanted to import a model/lora to your own account from a CivitAI link you can do so, but we're at this point letting users do this under good faith that they have permission to use these models.
We also have face IP-adapter nodes in our app!
I would say there are a lot of more minor UX differences about our app than other offerings. One particular favorite of mine is the ability to switch between the Node Editor screen and the Playground screen using cmd+p.
We built this feature mainly bc the node editor isn't great for generating images, but it's awesome for dialing in the exact aesthetic you want with different nodes/settings. We built the Playground screen for generating images once you have a workflow you like.
gotcha thanks. any suggestions there? our goal is to have more levers than something like Midjourney, but without the complexity of comfy. Hard to convey this in a tagline lol
There's a few companies that provide APIs for image-gen. Personally I've been using the Kandinsky model off Replicate. It's really high quality, I'd recommend it: https://replicate.com/ai-forever/kandinsky-2.2
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.