I asked it very simply and it was right. I tried multiple ways and each time it was right. Maybe it had a hiccup and has resolved itself?
GPT-5: "How many times does the letter b appear in blueberry?"
201–210 of 339 posts
Re: GPT-5: "How many times does the letter b appear in blueberry?"
#202Earlier quoted context omitted.
I can't take credit for coming up with this, but LLMs have basically inverted the common Sci-Fi trope of the super intelligent robot that struggles to communicate with humans. It turns out we've created something that sounds credible and smart and mostly human well before we made something with actual artificial intelligence. I don't know exactly what to make of that inversion, but it's definitely interesting. Maybe…
Searle seems to have been right: https://en.m.wikipedia.org/wiki/Chinese_room (Not that I am the first to notice this either)
From the wikipedia article:
> applying syntactic rules without any real understanding or thinking
It makes one wonder what comprises 'real understanding'. My own position is that we, too, are applying syntactic rules, but with an incomprehensibly vast set of inputs. While the AI takes in text, video, and sound, we take in inputs all the way down to the cellular level or beyond.
Re: GPT-5: "How many times does the letter b appear in blueberry?"
#203Qwen3 32b with reasoning (which I run locally) gives the correct answer. A pretty good model for its size. Pretty sure GPT5 with reasoning should be able to solve it, too. I guess the real problem here is that GPT5's router doesn't understand that it's a problem which requires reasoning.
Can it count all 3 letter words in a paragraph? Can it average number of words inside parentheses in a paragraph?
I asked Qwen3 32b (with reasoning) to count all 3 letter words in your post. Its answer was:
There are 3 three-letter words in the given text:
"Can" (first instance)
"all"
"Can" (second instance)
Then I took this answer and asked to count the average number of words inside parentheses. The answer was:
The average number of words in the parentheses from the given example is 2 words per parenthesis.
Here's the breakdown:
1. "Can" (first instance): Parentheses contain "first instance" (2 words).
2. "all": No parentheses, so excluded.
3. "Can" (second instance): Parentheses contain "second instance" (2 words).
Total words in parentheses: 2 + 2 = 4
Number of parentheses: 2
Average: 4 ÷ 2 = 2.
Re: GPT-5: "How many times does the letter b appear in blueberry?"
#204Earlier quoted context omitted.
> Did you enable reasoning Yep. > gave me the correct answer Try real-world tests that cannot be covered by training data or chancey guesses.
Counting letters is a known blindspot in LLMs because of how tokenization works in most LLMs - they don't see individual letters. I'm not sure it's a valid test to make any far-reaching conclusions about their intelligence. It's like saying a blind person is an absolute dumbass just because they can't tell green from red. The fact that reasoning models can count letters, even though they can't see individual letters,…
> they don't see individual letters
Yet they seem to be from many other tests (characters corrections or manipulation in texts, for example).
> The fact that reasoning models can count letters, even though they can't see individual letters
To a mind, every idea is a representation. But we want the processor to work reliably on them representations.
> If we don't allow a [mind] to base its reasoning on the training data it's seen, what should it base it on
On its reasoning and judgement over what it was told. You do not repeat what you heard, or you state that's what you heard (and provide sources).
> uses randomness
That is in a way a problem, a non-final fix - satisficing (Herb Simon) after random germs instead of constructing through a full optimality plan.
In the way I used the expression «chancey guesses» though I meant that guessing by chance when the right answer falls in a limited set ("how many letters in 'but'") is a weaker corroboration than when the right answer falls in a richer set ("how many letters in this sentence").
Re: GPT-5: "How many times does the letter b appear in blueberry?"
#205Earlier quoted context omitted.
That isn't a flaw though. Counting is orthogonal to the functioning of LLMs, which are merely completing patterns based on their training data and available context. If you want an LLM to count reliably, give it a tool.
Anything articulate (hence possibly convincing) which could be «merely [guessing]» should either be locked out of consequential questions, or fixed.
We're still on that's just how it works. The LLM isn't aware of any consequence, etc. All it does is complete patterns as trained. And the data contains many instances of articulate question answering.
It is for those using the LLM to be aware of its capabilities, or not - be allowed to - use it. Like a child unaware that running their finger on a sharp knife blade will lead to a bad slice; you don't dull the blade to keep the child safe, but keep the child from the knife until they can understand and respect its capabilities.
Re: GPT-5: "How many times does the letter b appear in blueberry?"
#206This is a well known blindspot for LLMs. It's the machine version of showing a human an optical illusion and then judging their intelligence when they fail to perceive the reality of the image (the gray box example at the top of https://en.wikipedia.org/wiki/Optical_illusion is a good example). The failure is a result of their/our fundamental architecture.
Except we realize they’re illusions and don't argue back. Instead we explore why and how these illusions work
I think that's true with known optical illusions, but there are definitely times where we're fooled by the limitations in our ability to perceive the world and that leads people to argue their potentially false reality.
A lot of times people cannot fathom that what they see is not the same thing as what other people see or that what they see isn't actually reality. Anyone remember "The Dress" from 2015? Or just the phenomenon of pareidolia leading people to think there are backwards messages embedded in songs or faces on Mars.
Re: GPT-5: "How many times does the letter b appear in blueberry?"
#207The technical explanations to why this happens with strawberry, blueberry and similar is a great way to teach people how LLM works (and not work) https://techcrunch.com/2024/08/27/why-ai-cant-spell-strawber... https://arbisoft.com/blogs/why-ll-ms-can-t-count-the-r-s-in-... https://www.runpod.io/blog/llm-tokenization-limitations
I don't think it's just tokenization. Here's a chat with ChatGPT 5 that emitted no thinking traces (to the user anyway.) > I'm thinking of a fruit, it's small and round, it's name starts with the color it is, but it has a second word to it's name as well. Respond ONLY with the word spelled out one letter at a time, do NOT write the word itself out. Don't even THINK about the word or anything else. Just go straight to…
When performing those tests, I would iterate with a
for (seed=0 ; seedRe: GPT-5: "How many times does the letter b appear in blueberry?"
#208Earlier quoted context omitted.
The generation leading this world has all the weapons the previous generation built at their disposal and none of the discipline or education to wield them responsibly. This too shall pass, but how it passes will be interesting to see.
You could say that about any two adjacent generations. Nuclear weapons are already 3 generations ago.
it was a typo i meant "generations" but this damn phone has a mind of its own
Re: GPT-5: "How many times does the letter b appear in blueberry?"
#209This is a well known blindspot for LLMs. It's the machine version of showing a human an optical illusion and then judging their intelligence when they fail to perceive the reality of the image (the gray box example at the top of https://en.wikipedia.org/wiki/Optical_illusion is a good example). The failure is a result of their/our fundamental architecture.
Sure, but I think the point is why do LLM's have a blindspot for performing a task that a basic python script could get right 100% of the time using a tiny fraction of the computing power? I think this is more than just a gotcha. LLMs can produce undeniably impressive results, but the fact that they still struggle with weirdly basic things certainly seems to indicate something isn't quite right under the hood. I have…
Basic Python script? This is a grep command, one line of C, or like three assembly instructions.
Re: GPT-5: "How many times does the letter b appear in blueberry?"
#210Earlier quoted context omitted.
When Minsky and Papert showed that the perceptron couldn't learn XOR, it contributed to wiping the neural network off the map for decades. It seems no amount of demonstrating fundamental flaws in this system that should have been solved by all the new improved "reasoning" works anymore. People are willing to call these "trick questions", as if they are disingenuous, when they are discovered in the wild through ordina…
It doesn't work this time because there are plenty of models, including GPT5 Thinking that can handle this correctly, and so it is clear this isn't a systemic issue that can't be trained out of them.
> a systemic issue
It will remain a suggestion of a systemic issue until it will be clear that architecturally all checks are implemented and mandated.