AWS Certified AI Practitioner AIF-C01 Practice Question

Diffusion models are trained to reverse a gradual noising process. At generation time, they start with pure random noise in the latent space. The model then performs a series of learned denoising steps that progressively remove noise, conditioning on the text prompt, until the noise is transformed into a coherent image. The other options do not describe the characteristic iterative denoising process: drawing pixels on a blank canvas is more like autoregressive image generation, retrieving and restyling an existing picture is nearest-neighbour plus style transfer, and a single decoding pass without iterations omits the fundamental step-by-step refinement that defines diffusion models.