weather.gov went through its own overhaul. https://www.weather.gov/redesi...
Way more compute power required to provide the same service.

That's your personal definition of simulation, apparently.

Did they actually assess what *my* skills and *your* skills are, or what skills we use in our jobs? No, of course not, they used representative templates. They generalized what they thought a fast food worker's skills were, or a teacher's skills, or an engineer's skills. And my guess is that they filled in a lot of details using...AI.

I have serious questions about the quality of the input data they used for this analysis. I suspect they missed a few hundred million skills.

I was simply responding to the definition *you* provided, which was:

Now you are moving the goalposts and making the distinction not so simple.

Of course I can't win the debate, you've already made up your mind. That doesn't make you right.

You are still picking and choosing. Poor people, like everyone else, have to buy all kinds of things. Some of those things are rising in price, some are falling. Your hand-picked examples do not prove your point. The Bureau of Labor Statistics, on the other hand, goes to great lengths to select a representative "basket of goods" to include in their inflation indexes. These inflation indicators *do* include the cost of housing, food, medicine, and every other category of things people have to buy.

I know very well what poverty is like. As a child, my family qualified for free school lunches, a threshold that requires a family to be below 130% of the Federal poverty level. Additionally, I work with inner city youth, teaching them trade skills so they can have a better life. While their life is certainly not easy, I can see first hand that their life is better than it was for me as a young person in the 1970's. The BLS numbers also bear this out. I doubt *you* have sufficient experience with poverty to back up your claims.

This is a good exercise for anyone who is worried about the proliferation of AI-written articles. As you experienced, you were able to get the job done using AI. You learned how the process works. And the world is not accidentally landing on AI-written articles, everywhere they look.

Now, if the topic were articles written *with AI assistance* that's a different matter. Those are everywhere, probably the majority by this point.

By this measure, we understand literally *nothing* at a fundamental level. Everything we do as humans is built on incomplete knowledge. Sure, if that's how you're going to frame it, no, we don't understand how LLMs work. But to apply that standard, you'd have to also say we don't understand metallurgy or gravity or electricity. When I say that humans *do* understand how LLMs work, I don't mean to say that they understand everything about them. What I mean to say is that humans know enough to *engineer* them to work according to specification.

Here are two good articles that break down how an LLM works. Maybe these will help.
https://joseparreogarcia.subst...
https://www.understandingai.or...

Sorry, forgot the relevant quote:
"Every program attempts to expand until it can read mail. Those programs which cannot so expand are replaced by ones which can."
-Zawinski's Law

AIs can spit out a thousand articles a minute. But are they worth reading? Are they located on a site where people actually go?

A few years ago, we started to see SEO-driven spam websites, with nothing but regurgitations of other websites' contents. These sites existed just to harvest clicks. But everybody knew they had made a mistake when they happened to land on one of these sites, and clicked away.

This is what I suspect is happening with this "vast number" of AI-written articles. You're certainly not going to see them on sites where people actually go intentionally.

Let's not get ahead of ourselves.

A few years ago, more than half of all websites were SEO-driven automatically-generated spam. The point is, quantity means nothing. Nobody actually read those SEO pages, and clicked away as soon as they mistakenly entered them.

The headline implies that half of all articles *people read* are AI-generated. I highly doubt that. Just because the articles are generated, doesn't mean they are on sites that anybody will actually read.

I agree your illustration is good, if your audience is familiar with "open world" games. Many of us are not, but just about everybody has seen a movie.

It's true that some things have increased in cost faster than inflation. But you don't get to just pick those things, leaving out all the other things that have *decreased* in cost, and claim that life is worse now. Inflation and real wages take into account *all* the things a family needs, not just the ones that have experienced the highest price increases.

This is a gross oversimplification. No, the difference between weather and a simulation is *not* just that the weather can get you wet. If you go into one of those carnival "4-D" rides, the movie can "get you wet" and many of them do. But that fact doesn't make the movie "weather." It's still just a simulation.

I won't respond to all your points, but there are two that I feel are deserving.

Yes, we do know how LLMs work. Maybe you don't, but the engineers at OpenAI and Microsoft and Google etc., absolutely do. The evidence of this is that over the past three years, they have been able to repeatedly and steadily improve the quality of the chatbots' responses, and to correct incorrect responses of the past. One notable example was an early Gemini image generator, which, when asked to render drawings of historic figures like Lincoln, would render an image with the wrong gender or race. The designers had built this into the LLM, but didn't fully anticipate the ultimate fallout. So they fixed the image generator to be more historically accurate, before they brought it back online. This kind of correction would not be possible, if the engineers didn't understand thoroughly how it works.

This statement misunderstands how LLMs work. At one level, you're right, intelligence can't be "simulated." But the responses a chatbot gives, certainly do simulate the responses an actual intelligence would give. But it's an illusion. The LLM simply digests a myriad human responses to the question provided, and synthesizes and adapts the response to *your* question / prompt, based on the patterns it saw in its training data.

We may not fully understand how humans think, but we do know how LLMs work. LLMs are essentially a sophisticated pattern recognition algorithm. Based on their training, they compose sequences of tokens that approximate what would be expected in response to a prompt.

AI is to intelligence, as a movie is to motion. When watching a movie, there is a very convincing appearance of motion, but in fact, nothing on the screen is actually moving. It can be so convincing that viewers using 3D glasses might instinctively recoil when an object appears to fly towards them. But there is no actual motion. The characters have no intent, though humans assign intent to what the "characters" are saying and doing. The point is, it's an illusion. And in the same way, AI is an illusion, a fancy (and very useful) parlor trick.