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.

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.

Seven paragraphs is too much? I read the full thing before seeing your comment. It’s well written and easy to read.

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.

Fair points. My use of “primary” was a poor choice; I meant something along the lines of “most common among individuals who aren’t philosophers, in my experience.”

Interesting take! Is lightning conscious, then? The idea of Thor isn’t too far off if so, haha.

Not everyone finds it persuasive, yeah. It’s an appeal to intuition that many people, though not all, have.

The online play is garbage. I played in H1 tournaments around the US back when it was good and would love for them to do it better than they did with their remake. The remake actually remade Halo 1 PC, not the Xbox version.

Me

Yep. We find things humorous if they’re a benign violation of our expectations. That’s also why some folks judge others for their taste in humor; either they see something as not benign (e.g., people getting injured) or not a violation of expectations (e.g.,“stupid,” or wholly predictable).

I was just in a smaller city in Germany and flew back to the US after that. I look German and speak German. When paying with card, Germany felt exactly like the US. At every restaurant, the tip request automatically came up within the thing used to process your card, just like in the US.

It did, actually: https://fred.stlouisfed.org/series/LES1252881500Q

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

Would you, after devoting full years of your adult life to the unpaid work of learning the requisite advanced math and computer science needed to develop such a model, like to spend years more of your life to develop a generative AI model without compensation? Within the US, it is legal to use public text for commercial purposes without any need to obtain a permit. Developers of such models deserve to be paid, just like any other workers, and that doesn’t happen unless either we make AI a utility (or something similar) and funnel tax dollars into it or the company charges for the product so it can pay its employees.

I wholeheartedly agree that AI shouldn’t be trained on copyrighted, private, or any other works outside of the public domain. I think that OpenAI’s use of nonpublic material was illegal and unethical, and that they should be legally obligated to scrap their entire model and train another one from legal material. But developers deserve to be paid for their labor and time, and that requires the company that employs them to make money somehow.

Average monthly salary in the cities is listed at the bottom of that link I gave. The two cities differ in monthly salary by $14 dollars on average, per the available data. Those same submissions show that the cost of living is ~20% higher in San Diego than Austin.

Austin is cheaper than San Diego, even excluding taxes:

https://www.numbeo.com/cost-of-living/compare_cities.jsp?country1=United+States&country2=United+States&city1=Austin%2C+TX&city2=San+Diego%2C+CA

The general rule of thumb is that five words, even with paraphrasing, of unquoted or uncited text is plagiarism:

https://poorvucenter.yale.edu/ParaphraseStrategies