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Original tweet by @emollick: https://twitter.com/emollick/status/1669939043243622402

Tweet text: One reason AI is hard to "get" is that LLMs are bad at tasks you would expect an AI to be good at (citations, facts, quotes, manipulating and counting words or letters) but surprisingly good at things you expect it to be bad at (generating creative ideas, writing with "empathy").

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[-] vcmj@programming.dev 0 points 2 years ago

?? Literally the entire purpose of the transformer architecture is to manipulate text, how is it bad at that? Am I misunderstanding this? Summarization, thematic transformation, language translation etc are all things AI is fantastic at...

[-] sisyphean@programming.dev 1 points 2 years ago* (last edited 2 years ago)

The problem is that they "see" the text at the token level instead of the level of characters. That's why they are bad at reversing strings or counting characters, for example. They perceive tokens as the atomic units of text instead of characters. For example, see how this comment gets tokenized:

With the token IDs shown:

The current ChatGPTs got pretty good at these tasks but they are still hard for them.

Here is an example of a (admittedly more complicated) character-level task failing:

Source: https://www.reddit.com/r/ChatGPT/comments/11z9tuk/chatgpt_vs_reversed_text/ (It's from the devil's website, so don't open it)

Related tweet by @karpathy:

https://twitter.com/karpathy/status/1657949234535211009

Text reversing example from a tweet by @npew:

EDIT: sorry for the infodump, I just find these topics fascinating.

this post was submitted on 20 Jun 2023
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