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Doc: That’s an interesting name, Mr…
Fletch: Babar.
Doc: Is that with one B or two?
Fletch: One. B-A-B-A-R.
Doc: That’s two.
Fletch: Yeah, but not right next to each other, that’s what I thought you meant.
Doc: Isn’t there a children’s book about an elephant named Babar.
Fletch: Ha, ha, ha. I wouldn’t know. I don’t have any.
Doc: No children?
Fletch: No elephant books.
You asked a stupid question and got a stupid response, seems fine to me.
Yes, nobody asking that question is wonderring about the “straw” part of the word. They’re asking, is the “berry” part one, or two "r"s
“My hammer is not well suited to cut vegetables” 🤷
There is so much to say about AI, can we move on from “it can’t count letters and do math” ?
But the problem is more “my do it all tool randomly fails at arbitrary tasks in an unpredictable fashion” making it hard to trust as a tool in any circumstances.
Your not supposed to just trust it. Your supposed to test the solution it gives you. Yes that makes it not useful for some things. But still immensely useful for other applications and a lot of times it gives you a really great jumping off point to solving whatever your problem is.
The terrifying thing is everyone criticising the LLM as being poor, however it excelled at the task.
The question asked was how many R in strawbery and it answered. 2.
It also detected the typo and offered the correct spelling.
What’s the issue I’m missing?
Uh oh, you’ve blown your cover, robot sir.
The issue that you are missing is that the AI answered that there is 1 ‘r’ in ‘strawbery’ even though there are 2 'r’s in the misspelled word. And the AI corrected the user with the correct spelling of the word ‘strawberry’ only to tell the user that there are 2 'r’s in that word even though there are 3.
Sure, but for what purpose would you ever ask about the total number of a specific letter in a word? This isn’t the gotcha that so many think it is. The LLM answers like it does because it makes perfect sense for someone to ask if a word is spelled with a single or double “r”.
It makes perfect sense if you do mental acrobatics to explain why a wrong answer is actually correct.
Not mental acrobatics, just common sense.
Because you’re using it wrong. It’s good for generative text and chains of thought, not symbolic calculations including math or linguistics
Give me an example of how you use it.
Writing customer/company-wide emails is a good example. “Make this sound better: we’re aware of the outage at Site A, we are working as quick as possible to get things back online”
Dumbing down technical information “word this so a non-technical person can understand: our DHCP scope filled up and there were no more addresses available for Site A, which caused the temporary outage for some users”
Another is feeding it an article and asking for a summary, https://hackingne.ws/ does that for its Bsky posts.
Coding is another good example, “write me a Python script that moves all files in /mydir to /newdir”
Asking for it to summarize a theory or protocol, “explain to me why RIP was replaced with RIPv2, and what problems people have had since with RIPv2”
it’s not good for summaries. often gets important bits wrong, like embedded instructions that can’t be summarized.
