I thought we could have the model play a little game where it first generates a puzzle to solve, then we ask another instance of the model to try to solve the problem that it generated.

我想我們可以讓模型玩一個小遊戲，它先生成一個謎題，然後我們讓模型的另一個實例嘗試解決它生成的問題。

So, yeah, I'll ask it, generate, say, a 5x5 nonogram, where the final answer is the letter M.

所以，是的，我會問它，生成一個 5x5 的非圖形，最終答案是字母 M。

We'll see what it comes up with.

我們將拭目以待。

All right, we see it just gave us a little puzzle.

好了，我們看到它給了我們一個小謎題。

We'll go ahead and copy this, open up another window of O1, ask it, solve the following puzzle, and let's say, visualize the answer in some pretty way, why not?

我們繼續複製這個，打開 O1 的另一個窗口，向它提問，解決下面的難題，比方說，以某種漂亮的方式將答案可視化，為什麼不呢？

This puzzle doesn't look like it's too hard, but the way that a nonogram works is for each list of numbers, and the numbers tell you how many squares are filled in, and if the squares are consecutive, then you'll see a 2.

這道謎題看起來並不難，但 "非圖形 "的工作原理是，在每一列數字中，數字會告訴你有多少個方格被填滿，如果這些方格是連續的，那麼你就會看到一個 "2"。

For two consecutive squares, if there's a space between them, you'll see a 1, 1.

對於兩個連續的方格，如果中間有空格，就會出現 1、1。

And so you're supposed to just try to figure out which squares do I indeed have to fill in, and it looks like the model got this right.

是以，你應該試著找出哪些方格是我必須填寫的，看起來模型是正確的。

It illustrated a nice little letter M.

它繪製了一個漂亮的小字母 M。

But I think one of the things that is nice about examples like this is it's similar to Sudoku or a crossword, for example, where you have to make a guess and then see if that's a right guess or a wrong guess, and then backtrack if you get it wrong.

但我認為，這樣的例子有一點很好，那就是它類似於數獨或填字遊戲，比如，你必須先做一個猜測，然後看看是猜對了還是猜錯了，如果猜錯了，還可以反推。

And so any type of task where you have to search through a space where you have different pieces pointing in different directions, but there are mutual dependencies, so you might get a bit of information that tells you that these two pieces contradict each other.

是以，在任何類型的任務中，你都必須在一個空間中進行搜索，在這個空間中，你有不同的碎片指向不同的方向，但又存在相互依賴關係，是以你可能會得到一些資訊，告訴你這兩個碎片是相互矛盾的。

A model like O1 is really good at trying to refine the search space here.

像 O1 這樣的模型可以很好地完善搜索空間。