You mean when the training data becomes more complete. But that’s the thing, when this issue was being tested, the’AI’ would swear up and down that the normally filled wine glasses were full, when it was pointed out that it was not indeed full, the ‘AI’ would agree, and change some other aspect of the picture it didn’t fully understand. You got wine glasses where the wine would half phase out of the bounds of the cup. And yet still be just as empty. No amount of additional checks will help without an appropriate reference

I use ‘AI’ extensively, i have one running locally on my computer, i swap out from time to time. I don’t have anything against its use with certain exceptions. But i can not stand people personifying it beyond its scope

Here is a good example. I am working on an APP so every once in a wile i will send it code to check. But i have to be very careful. The code it spits out will be unoptimized like: variable1=IF (variable2 IS true, true, false) .

Some have issues with object permanence, or the consideration of time outside its training data. Its like saying a computer can generate a true random number, by making the function to calculate a number more convoluted.

I mean, they can assume fantasy, and it will hold weight because laws are interpreted by the court, not because the court is correct.

“it was unable to link the concepts until it was literally created for it to regurgitate it out“

-WraithGear

The’ problem was solved before their patch. But the article just said that the model is changed by running it through a post check. Just like what deep seek does. It does not talk about the fundamental flaw in how it creates, they assert if does, like they always did

1 it’s not full, but closer then it was.

2. I specifically said that the AI was unable to do it until someone specifically made a reference so that it could start passing the test so it’s a little bit late to prove much.

Yes, on the second part. Just rearranging or replacing words in a text is not transformative, which is a requirement. There is an argument that the ‘AI’ are capable of doing transformative work, but the tokenizing and weight process is not magic and in my use of multiple LLM’s they do not have an understanding of the material any more then a dictionary understands the material printed on its pages.

An example was the wine glass problem. Art ‘AI’s were unable to display a wine glass filled to the top. No matter how it was prompted, or what style it aped, it would fail to do so and report back that the glass was full. But it could render a full glass of water. It didn’t understand what a full glass was, not even for the water. How was this possible? Well there was very little art of a full wine glass, because society has an unspoken rule that a full wine glass is the epitome of gluttony, and it is to be savored not drunk. Where as the reference of full glasses of water were abundant. It doesn’t know what full means, just that pictures of full glass of water are tied to phrases full, glass, and water.

It can, the only thing stopping it is if it is specifically told not to, and this consideration is successfully checked for. It is completely capable of plagiarizing otherwise.

If a human did that it’s still plagiarism.

If what you are saying is true, why were these ‘AI’s” incapable of rendering a full wine glass? It ‘knows’ the concept of a full glass of water, but because of humanities social pressures, a full wine glass being the epitome of gluttony, art work did not depict a full wine glass, no matter how ai prompters demanded, it was unable to link the concepts until it was literally created for it to regurgitate it out. It seems ‘AI’ doesn’t really learn, but regurgitates art out in collages of taken assets, smoothed over at the seams.