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I wonder whether such problems really test the reasoning capabilities of ChatGPT, or its capabilities to abstract. It is after all trained as a _language_ model. I tested the following and found the results remarkable - though designing analogies to the more complex abstract problems would be a fair bit of work:

Human:

Here is a riddle: Please fill in the blank. For Valentine's day, Marcy gives to Aaaron a feather, a nest, and an egg. Aaaron gives to Marcy a leaf, a flowerpot, and _________ .

ChatGPT:

Aaaron gives to Marcy a leaf, a flowerpot, and soil.

Human:

Here is a riddle: Please fill in the blank. Marcy and Aaaron like to exchange gifts. Marcy has a pawn, a rook, a peach, and a bishop. She gives to Aaaron as a gift the pawn, the rook, and the bishop. Aaaron has a spoon, a knife, a fork, and a book. He gives to Marcy as a gift _____________ .

ChatGPT:

Aaaron gives to Marcy as a gift the spoon, the knife, and the fork.

Nice.

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The version of ChatGPT used here was presumably GPT 3.5 based, and the "soil" answer seems merely a related word, rather than completing an analogy.

GPT-4 (Bing/Creative) gives the much better answer of "seed".

"That’s a tricky riddle. I think the answer is a seed. The items that Marcy and Aaaron give to each other are related to the life cycle of a plant and a bird. A feather, a nest, and an egg are part of a bird’s life cycle. A leaf, a flowerpot, and a seed are part of a plant’s life cycle."

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