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Url changed from https://bsky.app/profile/kjhealy.co/post/3lvtxbtexg226 , which points to this.
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…
Of course then you ask her to write it and of course things get fixed. But strange.
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…
I had a fun experience recently. I asked one of my daughters how many r's there are in strawberry. Her answer? Two ... Of course then you ask her to write it and of course things get fixed. But strange.
That is to say, you can obtain the same process by talking to "non-reasoning" models.
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
Tokenization makes the problem difficult, but not solving it is still a reasoning/intelligence issue
It's just not sustainable for OpenAI to run GPT at the best of its abilities on every request. Their new router is not trying to give you the most accurate answer, but a balance of speed/accuracy/sustainable cost on their side.
(kind of) a similar thing happened when 4o came out, they often tinkered with it and the results were sometimes suddenly a lot worse, it's not that the model is bad, they're just doing all kind of optimizations/tricks because they can barely afford to run it for everyone.
When sama says he believe it to have a PhD level, I almost believe him, because he have full access and can use it at 100% of its power all the time.
Even OSS 20b gets it right the first time, I think the author was just mistakenly routed to the dumbest model because it seemed like an easy unimportant question.
The 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
1) these people think so little of everyone else's areas of expertise they are willing to claim their technology has PhD-level expertise in them, apparently unironically.
2) actually in LLM world, PhDs are what you have if you're too stupid not to take the FAANG money in your second year when the quick wins are done, you've done a couple of posters and now you realise you're papering over the cracks with them: worthless. So why would anyone else want a PhD when PhDs are so worthless based on their bubble experience? We can just replace them with GPT-5.
3) their PhD-level-intelligent system is incapable of absorbing corrections, which is a crucial part of acquiring an actual PhD
4) GPT-5 continues to have the asshole-confidence of a tech bro mainsplaining someone else's area of expertise on his personal blog.
We're now at the point where marketing is celebrating software that has had so much effort spent on crushing hallucination that in fact it has become delusionally confident.
I love everything about this.
ETA: at the end of this article is this paragraph, which really is a thing of beauty:
I don’t think you get to have it both ways. That is, you don’t get to, as it were, borrow charisma from all the hype and then disavow every failure to live up to it as someone else’s naive mistake for believing the hype.
Bravo.
I think the concrete issue this points to is the thing that dynamically decides when to use reasoning failed to choose it in this instance. Sam Altman said it was broken on release day.