Part 3/8:
Enter diffusion models, which break free from these constraints. Instead of generating responses token-by-token, diffusion LLMs generate an entire response at once in a rough form before iteratively refining it. This methodology mirrors how diffusion models function in text-to-image generation, starting with a noisy image and gradually refining it until it becomes recognizable.
In this context, Inception Labs has pioneered the first production-grade diffusion-based large language model. Traditional autoregressive LLMs generate each token sequentially, often taking too long to produce a comprehensive response. On the other hand, diffusion-based models can complete an initial rough draft rapidly and improve upon it significantly in fewer iterations.