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I guess each digit is a word?

For example, how does the explanation in the article produce a module that can solve this:

“ To calculate the hypotenuse of a triangle with one side that is 12 inches long and another i S side that is 36 centimeters long, a 6th grader might say something like this: "First, we need to convert the 36 centimeters into inches so that both sides of the triangle are in the same units. We can do this by dividing 36 by 2.54, which is the number of centimeters in one inch. This gives us 14.173228 inches. Then, we can use the Pythagorean theorem to find the length of the hypotenuse. The Pythagorean theorem says that in a right triangle, the square of the length of the hypotenuse is equal to the sum of the squares of the lengths of the other two sides. So we can use this formula to find the length of the hypotenuse: a^2 + b^2 = c^2. In our triangle, the length of one side is 12 inches, and the length of the other side is 14.173228 inches. So we can plug those numbers into the formula like this: 12^2 + 14.173228^2 = c^2. Then we just need to do the math to find the value of c. 12^2 is 144, and 14.173228^2 is 201.837296. So if we add those two numbers together, we get 346.837296. And if we take the square root of that number, we get the length of the hypotenuse, which is 18.816199 inches.”




Well, it's wrong for one: It correctly gets the division (I assume it has that fact memorized) but 14.173228^2 is 200.88 not 201.83. it then also does the addition wrong, and the square root is also wrong.

You gotta be REAL careful with ChatGPT output that sounds convincing and technical. It's very good at convincingly making stuff up, even math-y science-y sounding stuff.


It's still hard for me to comprehend that it gets as close as it did. Was there enough training data on 14 or so squared that it let it get close at 200.88?

Agree it's quite convincing.


> I guess each digit is a word?

In many cases each word has a number/token associated with it, but some words get broken up into several tokens. Same with longer numbers.

You can check out their tokenizer under the following domain. It probably gives you an idea why GPT is not very good at dealing with numbers.

https://beta.openai.com/tokenizer




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