61–70 of 339 posts
Me: How many R's in strawberry ChatGPT said: 3
Me: How many B's in blueberry? ChatGPT said: 2
Me: How many C's in coconut? ChatGPT said: 2
Me: How many D's in Diamond? ChatGPT said: 2
Me: How many A's in Banana? ChatGPT said: 3
https://chatgpt.com/share/6897cc40-6650-8006-aae3-ea2b8278d5...
Isn't that just an artifact caused by the tokenization of the training and input data? See https://platform.openai.com/tokenizer https://github.com/openai/tiktoken
No, it's the entire architecture of the model. There's no real reasoning. It seems that reasoning is just a feedback loop on top of existing autocompletion. It's really disingenuous for the industry to call warming tokens for output, "reasoning," as if some autocomplete before more autocomplete is all we needed to solve the issue of consciousness. Edit: Letter frequency apparently has just become another scripted out…
For what it's worth, it got it right when I tried it. >simple question should be easy for a genius like you. have many letter b's in the word blueberry? ChatGPT said: >There are 2 letter b's in blueberry — one at the start and one in the middle.
To me that makes it worse. Why would two people get wildly different answers to a simple factual observation query.
For what it's worth, it got it right when I tried it. >simple question should be easy for a genius like you. have many letter b's in the word blueberry? ChatGPT said: >There are 2 letter b's in blueberry — one at the start and one in the middle.
To me that makes it worse. Why would two people get wildly different answers to a simple factual observation query.
I tried and was unable to replicate. Me: How many R's in strawberry ChatGPT said: 3 Me: How many B's in blueberry? ChatGPT said: 2 Me: How many C's in coconut? ChatGPT said: 2 Me: How many D's in Diamond? ChatGPT said: 2 Me: How many A's in Banana? ChatGPT said: 3 https://chatgpt.com/share/6897cc40-6650-8006-aae3-ea2b8278d5...
Seems like they just fixed it: [1]. A "thinking longer for a better answer" message appeared before giving the answer. [1] https://chatgpt.com/share/6897c38b-12b8-800d-9cc2-571adb13bc...
It's still easy to trip up. The model's tendency to respond positively to user impact will have it do stuff like this: https://chatgpt.com/share/6897cc42-ba34-8009-afc6-41986f5803...
Because apparently the model doesn't know about the actual verb (https://en.wiktionary.org/wiki/blueberry#English), it decides to treat the request as some kind of fantasy linguistics, making up its own definition on the fly. It provides grammatically incorrect examples inconsistent with the grammatically incorrect table of conjugations it generates next.
These are always amazing when juxtaposed with apparently impressive LLM reasoning, knowledge, and creativity. You can trivially get them to make the most basic mistakes about words and numbers, and double down on those mistakes, repeatedly explaining that they're totally correct. Have any systems tried prompting LLMs with a warning like "You don't intuitively or automatically know many facts about words, spelling, or…
This is a great idea. Like, if someone asked me to count the number of B's in your paragraph, I'd yeet it through `grep -o 'B' file.txt | wc -l` or similar, why would I sit there counting it by hand? As a human, if you give me a number on screen like 100000000, I can't be totally sure if that's 100 Million or 1 Billion without getting close and counting carefully. Should ought have my glasses. Mouse pointer helps som…
I become mildly infuriated when computers show metrics (or any large number) without thousands separators.
Worse still, I often see systems that mix units, don’t right-align, and occasionally blend in a few numbers with decimals together with whole numbers! Then, update everything every second to make things extra spicy.
I tried and was unable to replicate. Me: How many R's in strawberry ChatGPT said: 3 Me: How many B's in blueberry? ChatGPT said: 2 Me: How many C's in coconut? ChatGPT said: 2 Me: How many D's in Diamond? ChatGPT said: 2 Me: How many A's in Banana? ChatGPT said: 3 https://chatgpt.com/share/6897cc40-6650-8006-aae3-ea2b8278d5...
Earlier quoted context omitted.
No, it's the entire architecture of the model. There's no real reasoning. It seems that reasoning is just a feedback loop on top of existing autocompletion. It's really disingenuous for the industry to call warming tokens for output, "reasoning," as if some autocomplete before more autocomplete is all we needed to solve the issue of consciousness. Edit: Letter frequency apparently has just become another scripted out…
Please define “real reasoning”? Where is the distinction coming from?
There's prior art for formal logic and knowledge representation systems dating back several decades, but transformers don't use those designs. A transformer is more like a search algorithm by comparison, not a logic one.
That's one issue, but the other is that reasoning comes from logic, and the act of reasoning is considered a qualifier of consciousness. But various definitions of consciousness require awareness, which large language models are not capable of.
Their window of awareness, if you can call it that, begins and ends during processing tokens, and outputting them. As if a conscious thing could be conscious for moments, then dormant again.
That is to say, conscious reasoning comes from awareness. But in tech, severing the humanities here would allow one to suggest that one, or a thing, can reason without consciousness.
Isn't that just an artifact caused by the tokenization of the training and input data? See https://platform.openai.com/tokenizer https://github.com/openai/tiktoken
No, it's the entire architecture of the model. There's no real reasoning. It seems that reasoning is just a feedback loop on top of existing autocompletion. It's really disingenuous for the industry to call warming tokens for output, "reasoning," as if some autocomplete before more autocomplete is all we needed to solve the issue of consciousness. Edit: Letter frequency apparently has just become another scripted out…
Wrong, it's an artifact of tokenizing. The model doesn't have access to the individual letters, only to the tokens. Reasoning models can usually do this task well - they can spell out the word in the reasoning buffer - the fact that GPT5 fails here is likely a result of it incorrectly answering the question with a non-reasoning version of the model.
> There's no real reasoning.
This seems like a meaningless statement unless you give a clear definition of "real" reasoning as opposed to other kinds of reasoning that are only apparant.
> It seems that reasoning is just a feedback loop on top of existing autocompletion.
The word "just" is doing a lot of work here - what exactly is your criticism here? The bitter lesson of the past years is that relatively simple architectures that scale with compute work surprisingly well.
> It's really disingenuous for the industry to call warming tokens for output, "reasoning," as if some autocomplete before more autocomplete is all we needed to solve the issue of consciousness.
Reasoning and consciousness are seperate concepts. If I showed the output of an LLM 'reasoning' (you can call it something else if you like) to somebody 10 years ago they would agree without any doubt that reasoning was taking place there. You are free to provide a definition of reasoning which an LLM does not meet of course - but it is not enough to just say it is so. Using the word autocomplete is rather meaningless name-calling.
> Edit: Letter frequency apparently has just become another scripted output, like doing arithmetic. LLMs don't have the ability to do this sort of work inherently, so they're trained to offload the task.
Not sure why this is bad. The implicit assumption seems to be that an LLM is only valueable if it literally does everything perfectly?
> Edit: This comment appears to be wildly upvoted and downvoted. If you have anything to add besides reactionary voting, please contribute to the discussion.
Probably because of the wild assertions, charged language, and rather superficial descriptions of actual mechanics.