121–130 of 167 posts
Earlier quoted context omitted.
No GLM?
no, I'm pretty skeptical that it's better than qwen3 coder but if you have evidence that it could be, I'm down to test it
Not “may be”: just look how swe-bench scores drop to single digits once it in C# https://arxiv.org/html/2506.12286v3
Personally I don't look at or respect LLM benchmarks at all. I've seen SOTA models fail in incredibly shocking ways even recently. Those moments immediately bring me out of the delusion that LLMs have thinking capacity or an understanding of code.
It’s such a strange delusion too, because it’s easy to get caught up in for a moment and it’s easy to remember “oh no this thing is as smart as a bag of bricks”.
What strikes me more is how these companies sell their AI offerings - we watched an OpenAI presentation about spec-driven development recently and the presenter was fairly, idk, fine enough if maybe a bit grandiose. But what really nagged me was the way he ended his presentation with something along the lines of “we’re excited to see AGI continue to grow” and it’s honestly A) depressing and B) downright fraud - there is no current AGI to speak of, it’s all just guessing the string of words that sound best together and this OpenAI rep _knows this_.
They know that no amount of up-front spec writing will prevent bugs.
They know that their LLM doesn’t “know” anything in an actually meaningful way.
They know that calling what they have “AGI” is aspirational at best and lying at worst.
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They really did a "trust me bro" and "do your own research" huh
the strange thing to me is that people would have it any other way. if you don't trust someone, why would you trust them to do the research for you? bit of entitlement if you ask me
No one owes anyone anything, but if you want to represent something; answering the question more in detail would have either closed the issue or raised more scrutiny, both of which are a good thing when trying to figure something out.
I don't have to trust someone to check their research and look at how they worked. If the work doesn't pass muster, likely the results don't either. Again, you can view it as entitlement, but if you're not going to bother backing up your claim, why make the claim to start with?
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Because they are. But stochastic parrots are awesome.
I challenge you! Try giving this exact prompt to GPT-5-Thinking (medium or high reasoning if API). It is able to (without external code tools) solve a never before seen cypher that is not present in its training data. I think this pretty clearly demonstrates that the “stochastic parrot” is no longer an apt description of its capabilities in generalization: ———— You are given a character-by-character decode table `map…
No one should ever make claims such as "X is not in 's training set". You don't know. Even if your idea is indeed original, nothing prevents someone from having though of it before, and published it. The history of science is full of simultaneous discoveries, and we're talking cutting-edge research.
Earlier quoted context omitted.
Because they are. But stochastic parrots are awesome.
I challenge you! Try giving this exact prompt to GPT-5-Thinking (medium or high reasoning if API). It is able to (without external code tools) solve a never before seen cypher that is not present in its training data. I think this pretty clearly demonstrates that the “stochastic parrot” is no longer an apt description of its capabilities in generalization: ———— You are given a character-by-character decode table `map…
That the answers have been available to them in the environment, and they’re still not hitting 100% on this benchmark is a damning indictment of SOTA model performance.
It really isn't. Do you expect SOTA models to answer any answered question on the internet with 100% accuracy? Congrats you just compressed the whole internet (at least a few zettabytes) into a model (a few TB at most?).
It's perfectly reasonable to expect a level of performance concordant with the marketing of these tools. Claiming this is superintelligence, while also excusing its poor performance is dishonest and false advertising.
Earlier quoted context omitted.
Because they are. But stochastic parrots are awesome.
I challenge you! Try giving this exact prompt to GPT-5-Thinking (medium or high reasoning if API). It is able to (without external code tools) solve a never before seen cypher that is not present in its training data. I think this pretty clearly demonstrates that the “stochastic parrot” is no longer an apt description of its capabilities in generalization: ———— You are given a character-by-character decode table `map…
Grok 4 heavy Thought for 4m 17s
{"decoded_prefix": "nqxznhzhvqvvjddqiterrqdboctzzmoxmhyzlcfe", "last_10": "kfohgkrkoj", "vowel_counts": {"a": 7, "e": 18, "i": 7, "o": 12, "u": 6}}
it did count another e, but that's a known point of failure for LLMs which i assume you put in intentionally.
>Counting e's shows at least 10 more, so total e's are 17.
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If it's a possibility and you don't want to dig deeper better to sit out and not comment anything at all, lest you risk defamation. Thinking out loud also doesn't make defamation acceptable.
It's fine, this is an american site so JAQing is in fact safe under free speech. You're welcome to ask b "would none rid me of this meddlesome priest" with no fear