11–20 of 77 posts
This wasn’t just “add more details”—it was “make this mechanically coherent.” The overall text doesn’t appear to be AI written, making this all the more confusing. Is AI making people write this way now on their own? Or is it actually written by an LLM and just doesn’t look like it?
This wasn’t just “add more details”—it was “make this mechanically coherent.” The overall text doesn’t appear to be AI written, making this all the more confusing. Is AI making people write this way now on their own? Or is it actually written by an LLM and just doesn’t look like it?
This is a better version of what I tried but suffers from the same problem - the models seem to stick close to their original shapes and add new details rather than creating an image from scratch that's a significantly better variant of what they tried originally.
What I take from this is that LLMs are somewhat miraculous in generation but terrible at revision. Especially with images, they are very resistant to adjusting initial approaches. I wonder if there is a consistent way to force structural revisions. I have found Nano Banana particularly terrible at revisions, even something like "change the image dimensions to..." it will confidently claim success but do nothing.
If first output is crappy, the next 3 iterations will improve the same crap.
This was not a good test.
I tried an experiment like this a while back (for the GPT-5 launch) and was surprised at how ineffective it was. This is a better version of what I tried but suffers from the same problem - the models seem to stick close to their original shapes and add new details rather than creating an image from scratch that's a significantly better variant of what they tried originally.
For the svg generation, it would be an interesting experiment to seed it with increasingly poor initial images and see at what point if any the models don’t anchor on the initial image and just try something else
I tried an experiment like this a while back (for the GPT-5 launch) and was surprised at how ineffective it was. This is a better version of what I tried but suffers from the same problem - the models seem to stick close to their original shapes and add new details rather than creating an image from scratch that's a significantly better variant of what they tried originally.
I feel like I’ve seen this with code too, where it’s unlikely to scrap something and try a new approach a more likely to double down iterating on a bad approach. For the svg generation, it would be an interesting experiment to seed it with increasingly poor initial images and see at what point if any the models don’t anchor on the initial image and just try something else
This wasn’t just “add more details”—it was “make this mechanically coherent.” The overall text doesn’t appear to be AI written, making this all the more confusing. Is AI making people write this way now on their own? Or is it actually written by an LLM and just doesn’t look like it?
I tried an experiment like this a while back (for the GPT-5 launch) and was surprised at how ineffective it was. This is a better version of what I tried but suffers from the same problem - the models seem to stick close to their original shapes and add new details rather than creating an image from scratch that's a significantly better variant of what they tried originally.
I’d be curious if the approach would be improved by having the model generate a full pelican from scratch each time and having it judge which variation is an improvement. Or if something should be altered in each loop, perhaps it should be the prompt instead