Your question is Diffusion Models vs GANs. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You are discussing image generation approaches for a generative AI product. A teammate asks why many modern systems use diffusion models instead of GANs, and what tradeoffs come with that choice.
How do diffusion models work, and what advantages do they offer over traditional GANs?