No, it’s not misreading anything. It isn’t reading at all. It just sees a string that is similar to other strings that it’s trained on, and knows the most likely sequence to follow is what it output. There is not comprehension. There is no reading. There is no thought. The process isn’t similar to what a human might do, only the result is.
If that was true, wouldn’t every AI get the answer wrong? It’s actually around 50/50. The leading “reasoning” models almost always get it right, the others often don’t.
It depends on what’s asked. What’s “around 50/50”? What is “it” that they almost always get right? I think you’ve bought into their marketing. It can often do math problems, that are worded properly, well. That doesn’t mean it’s intelligent though. It means that the statistical algorithm is useful for solving those problems. It isn’t thinking. Getting correct answers isn’t thought.
For the example in the OP, that is the correct answer, if correct is what you expect to follow a string that looks like this. For a statistical model, it did well. For a thinking machine (which it isn’t) it’s wrong. It accurately gave a string that is expected following the previous string, it just happens to not be the correct answer.
No, it’s not misreading anything. It isn’t reading at all. It just sees a string that is similar to other strings that it’s trained on, and knows the most likely sequence to follow is what it output. There is not comprehension. There is no reading. There is no thought. The process isn’t similar to what a human might do, only the result is.
If that was true, wouldn’t every AI get the answer wrong? It’s actually around 50/50. The leading “reasoning” models almost always get it right, the others often don’t.
It depends on what’s asked. What’s “around 50/50”? What is “it” that they almost always get right? I think you’ve bought into their marketing. It can often do math problems, that are worded properly, well. That doesn’t mean it’s intelligent though. It means that the statistical algorithm is useful for solving those problems. It isn’t thinking. Getting correct answers isn’t thought.
For the example in the OP, that is the correct answer, if correct is what you expect to follow a string that looks like this. For a statistical model, it did well. For a thinking machine (which it isn’t) it’s wrong. It accurately gave a string that is expected following the previous string, it just happens to not be the correct answer.