Maybe that makes them human..
replyhttps://www.booooooom.com/2016/05/09/bicycles-built-based-on...
I've fed a couple of those chicken-scratch sketches to nanobanana with prompt "Treat attached as a technical drawing of a bicycle. Produce photo-realistic image of the actual bike manufactured to that spec. Try to stay close to the input, where possible", and... wow, results are not great.
replyThat was very fun, thanks for the link
replyNo. But it reveals something about how this technology works, its statistical properties, from which you can infer the limitations.
replyHumans aren't machines trained on the entire stolen corpus of human knowledge. We expect that a human will do poorly at arbitrary tasks they have no experience doing – especially drawing, which many (most?) humans aren't trained in at all. The same isn't true of AI, where its proponents, priests and proselytizers have spent time, energy and billions of dollars attempting to convince us it can do anything better than humans.
replyPelican enjoyers didn't like this one lol
replyI don’t know what datasets are available to these LLMs, but I’d imagine if there was training on CAD code, text, and images, a prompt steered towards that probably could get it pretty good.
replyI am not a mechanical engineer, so even prompting well with ME lingo probably will take some effort.
Shhh...you'll alert the models :)
replyTotally agree though, anyone with a vague understanding of how bikes works ignores the pelican because they know the bike is unrideable in the first place.
Yes, but I think the idea here is that most models produce very similar pelicans on bicycles, so a different test might be more useful in gauging the differences in models.
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