Honestly going to use this lol

Even somewhere warmer, I’m a 2 year-round, too. I just have one very cool sheet that I use in the summer.

The pot in my ass

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

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.

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 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.

I’m back on my BS is also a solid contributor

That’s fascinating, and I agree with you. Why the US hates the idea of high-speed rail is beyond me, especially because they prided themselves so much on the rail system they put together earlier in their development. In any case, the US can’t do much of anything with its debt-to-GDP as high as it is right now. They can hardly keep from shutting the government down entirely because they won’t even agree to a government budget.

Also, the US is 9.14 million sq. km of land, whereas the EU is 4.29 million sq. km of land

EU is still smaller

But the main reason the US can’t handle the same stuff at a federal level that the EU can is population density. The US government can’t afford to nationalize rural healthcare given how rural the US can be–especially with their debt/GDP at the moment. Give it another few hundred years and the US might catch up to Europe in that respect.

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I’m thinking of shorting it. My friend is definitely shorting it.