Twisted Riddles
Pattern Matching vs. Reasoning
We’ve seen how well MyGPT handled the classic riddles. But was it actually solving them, or just remembering them? Let’s investigate with a clever twist!
The Twisted Riddle
Here’s the first riddle from before, but with the words switched around:
I’m short when I’m young, and I’m tall when I’m old. What am I?
Think about this for a moment - is this even a riddle anymore? Almost any living thing starts small and grows taller with age!
Let’s Experiment
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Before asking MyGPT, what do you think it will answer?
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Now, start a new chat with MyGPT and ask it the riddle. What did it answer?
Pattern Matching at Work
This reveals something fascinating about LLMs: they often rely heavily on pattern matching rather than true logical reasoning. When presented with variations of well-known patterns (like these classic riddles), they might stick to the familiar answers even when the logic has been completely reversed.
Your Challenge
Can you think of a way to help MyGPT break free from this pattern matching and actually reason about the riddle? Try adjusting your prompt and see if you can get a more logical answer!
LLMs: True reasoning machines, or amazing pattern matchers?
This experiment shows us that:
- LLMs excel at recognizing and completing familiar patterns
- LLMs’ “understanding” is more about statistical correlation than logical reasoning
- With the right approach, we can help AI models think more carefully
Keep these limitations in mind as you work with LLMs in more complex scenarios!