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It does not do any thinking. It is a statistical model, just like the rest of them.
These kind of comments are the equivalent of going to dog owners' forums, analyzing word choices in every post and warning the dog owners about the dangers of anthropomorphizing their pets, an effort as accurate as it is boorish and ineffectual.
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And, perhaps most relevantly, the regulatory environment the people are working in. French people working in America are probably more productive than French people working in France (if for no other reason because they probably work more hours in America than France).
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That's the copium HN thinks. European workers bust their asses for glory not for money.
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Most of french people in engineering jobs in France are working late even tho overtime is never paid.
In the USA they have the famous 9 to 5. Most developers' jobs in France are "9 to 6 with 2 hours to eat in the middle and unpaid overtime," so I would say both countries are equivalent.
But it's worth pointing out that the U.S.'s famous 9-to-5 is completely inapplicable to any sort of high-demand job. For many people in a demanding profession like tech, a 9-to-5 job would be an absolute (and often unattainable) dream. Where I live (Washington, D.C.) people who want a 9-to-5 will generally leave industry altogether and work for the government. (And even there, a true 9-to-5 can be elusive.)
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Not the parent but I would say bad defaults or naming. There are countless posts from newbies wondering why a model doesn’t work as well as it should. It’s usually either because the context size is set very low by default or they didn’t realize that they weren’t running the full model (ollama uses the distilled version in place of the full version but names it after the full version). There’s also been some controve…
> ollama uses the distilled version I've never used ollama, but perhaps you mean quantized and not distilled? Or do they actually use distilled versions?
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>You think that European founders and researchers are like "nah, you know what, we're European, we're not ambitious, we don't want to make money, to hell with equity"? That's the copium HN thinks. European workers bust their asses for glory not for money.
We've asked you several times to stop commenting in this inflammatory style on HN. We don't want to ban you, as we want HN to be open to a broad range of views and discussion styles, but if you keep commenting in ways that break the guidelines and draw valid complaints from other community members, a ban will be the next step we'll have to take.
If you want HN to be a good place to engage in interesting discussions, please do your part to make it better not worse.
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How are you defining "reasoning" such that you are confident that LLMs are definitely not doing it? What evidence do you have to that effect? (And are you certain that none of your reasoning applies to humans as well?)
They don’t ”think”. https://arxiv.org/abs/2503.09211 They don’t ”reason”. https://ml-site.cdn-apple.com/papers/the-illusion-of-thinkin... They don’t even always output their internal state accurately. https://arxiv.org/abs/2505.05410
I am thoroughly unimpressed by this paper. It sets up a vague strawman definition of "thinking" that I'm not aware of anyone using (and makes no claim it applies to humans) and then knocks down the strawman.
It also leans way too heavy on determinism - For one thing, we have no way of knowing if human brains are deterministic (until we solve whether reality itself is). For another, I doubt you would suddenly reverse your position if we created a LoRa composed of atmospheric noise, so it does not support your real position.
> https://ml-site.cdn-apple.com/papers/the-illusion-of-thinkin...
This one is more substantial, but:
"While these models demonstrate improved performance on reasoning benchmarks, their fundamental capabilities, scaling properties, and limitations remain insufficiently understood. [...] Through extensive experimentation across diverse puzzles, we show that frontier LRMs face a complete accuracy collapse beyond certain complexities. [...] We found that LRMs have limitations in exact computation: they fail to use explicit algorithms and reason inconsistently across puzzles."
Starts by saying "we actually don't understand them" (meaning we don't know well enough to give a yes or no) and then proceeds to list flaws that, as I keep saying, also can be applied to most (if not all) humans' ability to reason. Human reasoning also collapses in accuracy above a certain complexities, and certainly are observed to fail to use explicit algorithms, as well as reasoning inconsistently across puzzles.
So unless your definition of anthropomorphization excludes most humans, this is far from a slam dunk.
> They don’t even always output their internal state accurately.
I have some really bad news about humans for you. I believe (Buddha et al, 500 BCE) is the foundational text on this, but there's been some more recent research (Hume, 1739), (Kierkegaard, 1849)
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Are we sure more time butt in office equates to more productivity?
$89,000 GDP per capita vs $46,000 rather proves the point about productivity per butt. US office workers are extraordinarily productive in terms of what their work generates (thanks to numerous well understood things like the outsized US scaling abilities). Measuring beyond that is very difficult due to the variance of every business.
But I wouldn't expect someone like you to know, understand or even acknowledge it.
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They don’t ”think”. https://arxiv.org/abs/2503.09211 They don’t ”reason”. https://ml-site.cdn-apple.com/papers/the-illusion-of-thinkin... They don’t even always output their internal state accurately. https://arxiv.org/abs/2505.05410
> https://arxiv.org/abs/2503.09211 I am thoroughly unimpressed by this paper. It sets up a vague strawman definition of "thinking" that I'm not aware of anyone using (and makes no claim it applies to humans) and then knocks down the strawman. It also leans way too heavy on determinism - For one thing, we have no way of knowing if human brains are deterministic (until we solve whether reality itself is). For another,…
My point was congruent with the argument that LLMs are not humans or possess human-like thinking and reasoning, and you have conveniently demonstrated that.
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We don't know yet. But we do know it's certainly not statistical token prediction. (People can do statistical token prediction too, but that's called "bullshitting", not "thinking". Thinking is a much wider class of activity.)
Do we know that with certainty? Do we actually? Because my understanding is that how "thinking" works is actually still a total mystery. How is it we no for certain that the basis for the analog electric-potential-based computing done by neurons is not based on statistical prediction? Do we have actual evidence of that, or are you just doing "statistical token prediction" yourself?
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>You think that European founders and researchers are like "nah, you know what, we're European, we're not ambitious, we don't want to make money, to hell with equity"? That's the copium HN thinks. European workers bust their asses for glory not for money.
We're getting complaints about several of your recent comments, and this is a prime example of the kind of comment that is not right for HN. It takes a swipe at the whole HN community (on the false pretence that the HN audience is concentrated via country/region or mindset), and makes a moral judgement based on region/culture. We've asked you several times to stop commenting in this inflammatory style on HN. We don't…