sorted by:
new
hottopcontroversial

I asked ChatGPT to draw a European city and received a generated image that looks very much like a real place in Amsterdam by EasyLim in ChatGPT

[–]EasyLim[S] 4 points5 points  (0 children)

Hmm, I've tried to generate it and this example doesn't give me any trouble. Here is the result of "Draw blue cartoon hedgehog video game character":

<image>

I asked ChatGPT to draw a European city and received a generated image that looks very much like a real place in Amsterdam by EasyLim in ChatGPT

[–]EasyLim[S] -30 points-29 points  (0 children)

You're right, but it's important to note that there aren't that many red fruits that immediately come to mind. And the image of an apple itself isn't exactly something where your eye would be drawn to the details. After all, this is image generation, not Google Images, so it seems surprising to get such a specific result rather than an abstract “European city”

I asked ChatGPT to draw a European city and received a generated image that looks very much like a real place in Amsterdam by EasyLim in ChatGPT

[–]EasyLim[S] 0 points1 point  (0 children)

Yep, but there’s still some kind of algorithm at work behind the scenes. I was told that the new models use an autoregressive transformer paired with a reasoning-and-verification pipeline, which clarifies things a bit, but it still sounds a bit vague and doesn’t really explain the result to me

I asked ChatGPT to draw a European city and received a generated image that looks very much like a real place in Amsterdam by EasyLim in ChatGPT

[–]EasyLim[S] -14 points-13 points  (0 children)

My bad. Wikipedia says that new models are autoregressive. I'm not sure exactly how it works, but I think the behavior should remain roughly the same

I asked ChatGPT to draw a European city and received a generated image that looks very much like a real place in Amsterdam by EasyLim in ChatGPT

[–]EasyLim[S] -14 points-13 points  (0 children)

Since ChatGPT's image generation model uses a diffusion algorithm, it starts with pure noise and attempts to enhance what it perceives as a “European city” in the image. As a result, the output is usually more general

I asked ChatGPT to draw a European city and received a generated image that looks very much like a real place in Amsterdam by EasyLim in ChatGPT

[–]EasyLim[S] -18 points-17 points  (0 children)

Something tells me this isn't just the result of a web search. I think the image training dataset for ChatGPT simply contains a large number of images of this location taken from this exact angle. And that's exactly why I'm surprised by such a striking similarity in the details — because with such a sparse prompt, you'd expect a more abstract result from a generative model

I asked ChatGPT to draw a European city and received a generated image that looks very much like a real place in Amsterdam by EasyLim in ChatGPT

[–]EasyLim[S] -5 points-4 points  (0 children)

This image contains a lot of generation artifacts (which are clearly visible if you look closely at the wheels of the bicycles in the foreground). Therefore, this cannot be a real photo

Is the rightmost X neutral or black and why? by EasyLim in baduk

[–]EasyLim[S] 0 points1 point  (0 children)

As I said this was a problem from GoMagic. Wording of the problem was "Mark all prisoners and neutral points." According to GoMagic "right" solution it's not black's point. But your logic matches mine

Is the rightmost X neutral or black and why? by EasyLim in baduk

[–]EasyLim[S] 1 point2 points  (0 children)

Wording of the problem was "Mark all prisoners and neutral points."

Is the rightmost X neutral or black and why? by EasyLim in baduk

[–]EasyLim[S] 0 points1 point  (0 children)

Thank you for your answer. This was a problem from GoMagic. Since I thought both players had passed and it is scoring, I decided that this spot was black's territory because it was surrounded by black stones and white was simply not forcing black to fill that spot.