This is a new diffusion-based language model from Inception. I don't know how well it works compared to an autoregressive LM of a similar size, but the inference process looks badass:

@InceptionAILabs Finally something which is not just one upping the benchmarks.

A little more thought, a little more effort, a little more care. If there’s a better, more sustainable way to make a shingle, we intend to find it. #AnythingButStandard #Innovate #EcoFriendlyRoofing #Greener #SustainableInnovation #SustainableRoofing #SustainableShingles @Holcim

@InceptionAILabs The fact that approach like "start with a random set of characters and tweak until it works" is working for coding blow my mind.

I’m beyond excited by their work! Been working on adapting a GAN model to work with discrete data (since 2023) but it’s been a nightmare! It’s genius actually to use diffusion models to capitalise on noise to boost the quality and speed of outputs in LLMs! I’m just dying to know how they solved the discrete/continuous duality in practice!

@InceptionAILabs Look at the way it generates the answer, this would be a large shift from the old way. imagine adding thinking to it too.

@InceptionAILabs I asked it to create a react component. It queued the request (probably because if everyone on X trying it), but when it started it was lightning fast.

@InceptionAILabs what is the advantage or disadvantage of using diffusion here?

@InceptionAILabs They should make it even more like the matrix 💪

@InceptionAILabs actually, worked on this for a few days, gave up in the end

@InceptionAILabs don't miss this one too, also launched on the same day seems like something's in the air with these dllms

@InceptionAILabs Yeah, I don’t get it, why do you need to enable the “diffusion effects”? Seems like a frontend gimmick otherwise it’s just like other LLMs?