117 karma · joined June 17, 2016
You stated it wasn’t getting better for byd. From the article:
BYD revenues in Q3 (July to September) 2024 were 201 billion yuan ($AU42.85 billion) – a record high for the brand and a jump of 24 per cent over the same period in 2023.
More on byds ascent from earlier this year: https://www.afr.com/companies/transport/byd-s-hybrid-ute-jum...
Going from not having market to be the no. 6 best selling is by definition getting better.
So yes you are wrong and sales are improving for byd.
It’s very obviously improving for BYD.
People making up their own benchmarks for these things has confirmed one thing for me: The bias that people think they mostly have original thoughts is extremely strong. I find if I have a “good” idea someone has probably already thought of it as well and maybe even written about it. About 0.01% of the time do I have an idea that one may consider novel and even that’s probably my own bias and overstated. This example just confirms that these models don’t really seem to reason and have a really hard time doing the basic generalization they can with fewer examples.
https://www.amnesty.org/en/latest/news/2022/06/el-salvador-p...
https://www.businessinsider.com/doge-savings-estimate-websit...
https://www.axios.com/2025/02/19/doge-musk-audit-mistake-sav...
https://www.cbsnews.com/amp/news/doge-wall-of-receipts-shows...
So yeah they are lying; whether intentionally or unintentionally. At this point I’m not sure what is worse.
This is essentially what the courts are doing through the interrogation of the limits of the offices power. If that’s what you are looking for it’s already WAI.
Why I would lie about plugging in your problem into an LLM or solve it is beyond me; you know I don’t lose anything by admitting you’re right? In fact I would stand to gain from learning something new. I think you should examine how you approach an argument because every time you’ve replied it’s made it look like you’re just more desperate for someone to agree and are trying to bully people into agreeing by making ad hominem attacks. Despite it all I think you have merit as a person — even if you can’t make a cogent argument and just chase your tail on this topic.
I’m going to stop engaging with you for now on, but just as a piece of perspective for you: both o3 and Gemini pointed out how your problem is a derivation when asked — perhaps you might be overestimating its novelty. Gemini even cited derivations out the gate.
I responded to your post with my thoughts and my own reframing of the question to try and open the conversation; you entirely ignored this in your response. Maybe you think this info is new to me but it’s not and it doesn’t prove anything for many more reasons than just the ones I cited in my prior response.
> Not sure if you are trolling now.
Nope just saying that adding “seem” to your postulation and repeating your point doesn’t make it right.
> I've had more productive conversations will LLMs.
The ad-hominem attacks really just serve to underscore how you have nothing of substance to argue.
Also generalization is not always reasoning: I can make a generalization that is not reasoned; I can also make one that is poorly reasoned. Generalization is considered well-defined in regards to reasoning: https://www.comm.pitt.edu/reasoning
Your example still fails to actually demonstrate reasoning given its highly derivative nature, though.
I guess the real question is “does moving down a stochastic gradient of probabilities suffice as reasoning to you” and my awnser is no because you don’t need reason to find the nearest neighbor in this architecture. In this case the model is not actively comparing and inferring its simply associating without “knowing”
“And it is also unlikely you solved it” well I guess you overestimated your abilities on two counts today then.
> It’s a variation on a well known problem in the sense that I just added some unique rules to it.
> No training data exists.
No it definitely does but is a variation. You kinda just confirmed what we already knew. Given enough data about a thing these LLMs can generalize somewhat.
Your quote: “This is a unique problem I came up with. It’s a variation on counting islands.” You then say: “ as I came up with it so no variation of it really exists anywhere else.”
So not sure what to take away from your text but I do think this is a variation of a well-known problem type so I would be pretty amazed if there was something very close to this in the training data. Given it’s an interview question and those are written about ad-nauseum I’m not surprised then that it was able to generalize to the provided case. The COT researchers did see the ability to generalize in some cases just not necessarily actually use the COT tokens to reason and/or failed on generalizing on variations which they thought it should have given its ability to generalize in others and the postulation that it was using reasoning and not just a larger corpus to pattern match with.