ChatGPT can’t generate a map of Europe, but what do I know?
ChatGPT can't spell. See for yourself.
Image by Cybernews.
ChatGPT can’t generate a map of Europe, nor can it spell the names of countries.
While hunting on Reddit I came across a post from the r/ChatGPT subreddit: “Asked ChatGPT to make a map of Europe.”
The map is flawed beyond comprehension, with all the names of countries in Europe misspelled.
This got me thinking: why does ChatGPT not know how to spell things correctly?
We all remember “Strawberry Gate,” when ChatGPT and many other AI models couldn’t figure out how many Rs are in the word “strawberry.”
But ChatGPT’s rendition of the map of Europe is something else entirely.
From the post, you can clearly see that ChatGPT was at least trying to label countries correctly – yet failed spectacularly.
The map features your favorite countries, like Zormany, Yoland, Eeland, and my personal favorite Mookie (Turkey).
When Cybernews asked ChatGPT to generate a map of Europe, it looked pretty legit to the untrained eye (in my opinion, but then again, I didn’t do geography at school).
However, when you look closely, you can see that England is completely omitted from the map and occupied by Ireland.
Crimea is also coloured in as if it’s a part of Russia, which is obviously a major issue.
Denmark looks like it’s spelled like dementia, and Switzerland is almost completely illegible.
Another iteration shows the country of England but has missed out on the Netherlands and has misspelled Iceland (Icland).
Users on Reddit have discussed this issue, with one user speculating that the reason for this is that “large language models don’t read or understand words on a character level.”
Large language models tend to break up words, and due to the LLM architecture, it works with tokens rather than individual letters.
Supposedly, algorithms used for image generation reconstruct inputs and the writing on these images might be very small.
“So, the image generator learns the patterns to cover more of these pixels, Teka Hadgu, co-founder of Lesan and a fellow at the DAIR Institute, told TechCrunch.
The algorithms are encouraged to recreate something similar to the data it has been trained on, but it doesn’t know the rules of language, said TechCrunch.