A bit of an exaggeration, sure. But only a bit. The lay summary of the article I referenced states the following:

Venkataraman et al. find that the paper commits every error that it was possible to make in the paper: leaving out important papers, including irrelevant papers, using duplicate papers, mis-coding their societies, getting the wrong values for “big” versus “small” game, and many others.

“commits every error that it was possible to make in the paper,” and, “completely incorrect,” aren’t very different.

This study this meme is based on is completely incorrect and should be retracted. Here’s a lay summary of its issues:

https://whyevolutionistrue.com/2024/03/04/new-paper-debunks-the-prevalence-of-women-hunting-in-early-societies/

And the published article detailing the problems with that study’s issues:

https://www.sciencedirect.com/science/article/abs/pii/S1090513824000497

When have we been talking about anyone’s diagnosis? We’ve been talking about the common misperception that depressive episodes caused by environmental triggers are not a result of treatable neurochemical dysfunction. MDD can certainly be a result of environmental triggers, and there are a wide variety of neurochemical bases of it. I distinctly said in my first comment that I was referencing a small part of your reply. I’m not trying to have a needless fight, I’m trying to correct a common public misperception that you reiterated. I do that whenever I see a misunderstanding of science; I care about public science education, especially on topics important enough as psychiatric conditions that are often fatal without treatment. If you feel like this is a pointless fight, sorry. I only commented because I understood your comment to mean something that, no matter my read of your wording, you clearly say you weren’t meaning.

MDD is a real disability. It can and often is precipitated by environmental triggers, and episodes can resolve once the environment is changed. Just because someone experiences remission in such a case doesn’t mean they don’t have a disorder that should be treated prior to another episode. Dichotomizing chemical and psychological/environmental is harmful.

My point is that such a lay interpretation isn’t helpful, and it may be harmful. Plenty of people with MDD have an environmental trigger prior to their first episode, and have their episode remit after that precipitating factor is managed. Convincing someone that their experience isn’t chemical suggests against treatment seeking during remission, such as seeking therapy, which could help prevent another episode (and one that may not have an environmental trigger). A depressive episode can be fatal. Telling someone that because their prior episode remitted spontaneously or after the environmental trigger changed might prevent them from getting the proactive and preventative treatment that they need to keep them from experiencing another episode and thus keep them alive. Don’t gatekeep depression.

And how do you think addressing stressors works? Some non-chemical means?

That first bit is totally untrue. Do you think our grief is not chemical? That we can’t have neural rewiring occur following the loss of a loved one? Don’t dichotomize experience and neurochemistry. They’re two sides of the same coin.

Trogdor was popular way before Reddit

It doesn’t have to be

https://www.mathworks.com/products/compiler.html

MATLAB can ruin all sorts of coding experiences, programming included

Examples? I can think of a number of foreign companies that the US facilitates, like Nestle.

(⌐■ ͜ʖ■)

Eh, I switched. I switched all of my lab’s computers, too, and my PhD students have remarked a few different times that Linux is pretty cool. It might snowball.

You’re normal in that respect:

https://onlinelibrary.wiley.com/doi/abs/10.1002/aur.1962

In fact, the idea that autistic individuals are immune to propaganda is, itself, media propaganda. The study that those articles report on was a single study that found that autistic individuals show less of a framing effect on their own preferences. It’s much more easily explained by autistic individuals having strong, internal preferences for their own likes/dislikes than it is by autistic individuals being immune to propaganda.

Speaking from experience here, too.

Oregonians almost take pleasure in driving slowly in front of you. Maybe they’ve just gotten used to going slow because the entire state freeway system is always under construction. People driving crazily is infuriating for a completely different reason.

I never understand why lemmy downvotes someone who is trying to help by providing accurate information, presumably because they think that there’s a very small chance that the person they’re replying to isn’t being sarcastic.

A fellow Julia programmer! I always test new models by asking them to write some Julia, too.

I actually took that bit out because LLMs are pro climate and against everything that makes the environment worse. That’s a result of being trained on a lot of scientific literature. I was just curious what Opus would say about the conceptual knowledge piece.

Claude Opus disagrees, lol (edit to add: all of what follows is Claude; not me):

I respectfully disagree with the claim that current language models are logically incapable of mapping language to actual concepts. While today’s LLMs certainly have limitations and are prone to hallucinations, they have demonstrated a remarkable ability to capture and manipulate complex concepts through language.

A few key points:

LLMs are trained on vast amounts of human-generated text which is grounded in real-world concepts, allowing the models to build rich representations that go beyond surface-level word associations. Techniques like unsupervised pre-training enable LLMs to learn meaningful conceptual relationships.

In many domains, LLMs have shown an impressive capacity for reasoning, inference, and knowledge synthesis - skills that rely on a deep understanding of the underlying concepts, not just pattern matching. Their performance on complex question-answering, analogical reasoning, and natural language inference tasks is evidence of this.

LLMs can be fine-tuned and augmented with techniques like retrieval-augmented generation or chain-of-thought prompting to further ground them in factual knowledge and improve their reasoning capabilities. This allows more robust conceptual mappings.

Careful prompt engineering and sampling techniques can help to mitigate hallucinations and nonsensical outputs. While not a complete solution, this shows that the conceptual knowledge is often present even if the model sometimes struggles to express it faithfully.

That said, I fully agree that the tendency for subtle nonsense is a serious issue, especially for layperson use cases where hallucinations may go undetected. Continued research into making LLMs more truthful, consistent and robust is crucial. Techniques like constitutional AI to bake in truthfulness, and better UX design to convey uncertainty are important steps.

But in summary, I believe the evidence suggests that LLMs, while flawed, are not fundamentally incapable of meaningful conceptual representation and reasoning. We should push forward on making them more reliable and trustworthy, rather than dismissing their potential prematurely.