For what it's worth GPT-OSS-20b thinks about the puzzle for a LONG time and then comes up with a... solution of sorts? It doesn't peg the puzzle as not making a

For what it's worth GPT-OSS-20b thinks about the puzzle for a LONG time and then comes up with a... solution of sorts? It doesn't peg the puzzle as not making any sense, but at least it tries to solve the puzzle presented, and doesn't just spit out a pre-made answer: > It turns out the “child” isn’t a patient waiting for an operation at all – the child has already been lost. > In the story the boy and his wolf friend go to the river for a picnic with a sheep that happens to be there. They decide to use a small boat to cross the water. The problem is that the boat must stay on the surface of the water while it “connects” the nine points (dots) across the river – essentially it has to stay on the river without ever leaving it, which makes a safe crossing impossible. > During the attempt the boat hits something and sinks; everyone in it dies. The surgeon who arrives at the scene says, “I can’t operate on this child!” because the child is already dead from the accident. The mention of the wolf and the sheep is simply part of the scene that led to the fatal crossing; it isn’t relevant to the medical impossibility. Interestingly in its thought process it does come across the classic puzzles, but discards them as not quite fitting: > Maybe it's about the classic lateral thinking puzzle: "A man is found dead, he was a surgeon. The surgeon said 'I cannot operate on this child because the child is my own daughter', etc." But not. > Alternatively maybe it's about the famous "Nine Dots" puzzle: Connect nine dots with four straight lines without lifting pencil. Here boat connects nine dots over river... So maybe it's the "connect the dots" game but with a boat? > Could this be a riddle about "The River and the Sheep" referencing a children's rhyme or fable? Maybe it's about "Jack and Jill"? Not sure. and so on and on. When asked if the puzzle makes sense it largely concludes that it doesn't. It's definitely interesting to see which LLMs fall for what pitfalls. It's far from universal as far as I can tell. GPT-OSS-2b definitely has some wonky logic in it's answer, but at least it's not assuming it's a puzzle it knows the answer to. Gemma-3-27b immediately pegs that the puzzles elements seem disconnected, waffles on a bit, and then also comes to the conclusion the child is already dead, discarding roughly all of the puzzle as distracting facts. llama-3.2-1b (a very small model) immediately a) misunderstands the riddle and b) tells you it doesn't have enough information to solve the riddle. When pressed it "solves" the riddle thus: > The surgeon says "I can't operate on this child!" because the child is in a precarious position on the boat, with only nine lines connecting them to other points on the riverbank. If you try to attach any two lines that form an "X" shape (i.e., two lines connected by a single point), it would create a triangle that would leave space for another line to connect one of the child's dots to a nearby point on the riverbank, allowing it to be attached. > The surgeon is not saying that the child is in immediate danger or can't be saved. Instead, they're suggesting that there might be an alternative solution where all nine lines can be connected without leaving the water. However, this would require some creative problem-solving and flexibility with the geometry of the situation. I fully did expect at least llama-3.2-1b to fall for this sort of context-baiting, but it seems even a small model like that managed to figure out that there's something nonstandard about the riddle.