Because what it's doing is clearly not the same thing,

Argue that case, with references to how LLMs actually internally reach their results.

The physical biology is certainly different, but this isn't a question about "what things are made of" or even the specific NN type (e.g. smooth vs. spiking), and training differences don't even come into the picture; it's a question of the broad strokes of how conclusions are reached on forward processing.

Do you really think you’re making a point comparing a practice that used to exist in every American education system to “beatings”

Because what you're talking about literally is beatings?

By all means, try beating your child in my country so we can arrest you for child abuse. Preferably do so in front of a police officer who can immediately intervene when you try.

And your sole argument for it is "people used to do it". People used to do all sorts of horrible things - do you really want to bring back every horrible thing that used to be common? Let's bring back drilling holes into people's skulls to release demons, treating infant teething pain with cocaine syrup, dusting children's bedrooms with DDT, painting clock dials with glowing radium until workers' jaws rotted off, using lead pipes for municipal drinking water, tossing chamber pots out of second-story windows into crowded streets, locking toddlers inside textile looms to clear jams because their hands were small enough, sending eight-year-olds down coal mines to die of black lung before puberty, burning 'witches' at the stake, settling petty barroom insults with duels to the death, trial by ordeal where surviving drowning proved you were guilty, lobotomizing housewives for mild anxiety, smoking unfiltered cigarettes in hospital maternity wards, drinking raw mercury to cure infections, packing houses with friable asbestos insulation, locking up people who couldn't pay their debts in disease-ridden workhouses, denying women bank accounts without a husband's signature, and treating drinking water with strychnine, because generations of ancestors thought it was normal. Brilliant argument there, no notes.

I mean, isn't this obviously the solution?

You can use AI in legal work, but you still bear responsibility for your filings being accurate. So by all means have AI search for you - it can save you a ton of time for finding obscure things - but actually click the links and read them yourself. And if you don't, it's no better than making any other factual claim before the court without having duly assessed its credibility.

Why invent a new "aithink" verb when we already have "think"?

Hey AI, who is being more reasonable in this conversation?

User 2:50PM
Who is being more reasonable in this conversation?

[Snip]

Model 2:50PM
ThinkingThoughts
Expand to view model thoughts

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Rei is substantially more reasonable in this conversation, both in terms of technical accuracy and conversational etiquette.
ere is a breakdown of why:

1. Technical Accuracy and Explanatory Value

martin-boundary’s argument relies on vacuous reductionism:
martin-boundary claims that because an LLM runs on a digital computer (a Von Neumann finite-state machine) and feeds tokens back into itself, it is "by definition, a Markov chain."

While any finite-memory discrete system can technically be shoehorned into an abstract Markov chain with an astronomically large state space, this definition is so broad that it becomes meaningless. Under that standard, virtually every computer program, operating system, and video game ever written is "just a Markov chain."

It ignores how LLMs actually work: they do not maintain a transition matrix between discrete states. Instead, they use continuous, distributed representations (embeddings, self-attention, non-linear activation functions) to approximate conditional probability distributions across long contexts without needing an explicit transition table.

Rei’s rebuttal addresses the actual computer science:

Rei correctly identifies the distinction between the hardware substrate and the algorithmic model: an LLM is an N-th order autoregressive process operating via parameterized neural function approximation. Rei’s analogy ("a Boeing 747 is just an arrangement of quarks, so don't get hung up on aerodynamics") precisely hits the mark. Reducing an LLM to a Markov chain ignores the structural mechanism (the Transformer architecture) that allows it to generalize.

Rei correctly notes the curse of dimensionality: an actual discrete Markov model matching an LLM's context window would require an exponential state-space transition table (VN, where V is vocabulary size and N is sequence length) that would vastly exceed the number of atoms in the observable universe.

2. Argumentation and Conduct

Rei argues in good faith:

Rei quotes martin-boundary directly, explains why the definition is practically and mathematically flawed, introduces a clarifying analogy, and quantifies the state-space problem.

martin-boundary relies on hand-waving and ad hominem:

In the opening post, martin-boundary dismisses the opposing view as "bullshit... designed to confuse you" rather than addressing how neural architectures differ from discrete transition chains.

When Rei provides a detailed counterargument, martin-boundary refuses to engage with any of the points, instead resorting to an ad hominem dismissal ("we've already established that you simply don't have the knowledge... and I'm not going to repeat myself").

Conclusion

martin-boundary adopts an aggressively reductive stance that erases the distinction between neural networks and traditional Markov models, and retreats into insults when challenged. Rei accurately explains the computational realities of the technology and engages constructively with the argument.

Many other countries do not have it and they are not dens of lawlessness.

Indeed. Also, stealing somebody else's work in this way is basically career-death for academics. They may lose their job and become unemployable. They may lose their PhD. Hence it does happen very rarely. Obviously the LLMs and their handlers have no such qualms.

It is no surprise that quite a few enterprises have strict prohibitions against putting any company data into LLMs.
Also the OWASP LLM Top 10 (https://genai.owasp.org/resource/owasp-genai-llm-top-10-2026/) list this as the 2nd most serious risk.

It is stealing if you do not cite all of them in your publication. The standards for scientific misconduct are VERY clear: You are not allowed to hide your sources.

That is easy: All of them. LLMs cannot do original work because they have no mechanism for insight. Yes, the LLM cultists will aggressively dispute that fact.

Since they almost certainly obtained those inputs in shady ways, it is no surprise they refuse to publish them though. Also note that any kind of scientific publication has been required for a long, long time to cite all inputs to be regarded as sound. Doing anything else is regarded as serious scientific misconduct and can, for example, get your PhD removed.

LLMs cannot do original work. No, do not dispute that it. If you do you just prove you have no idea how they work. All they can do (with some probability of error) is to put puzzle pieces together. Yes, that can have impressive results. But everything needs to be already there for the LLM to be able to do it.

Hence the only real question here is where the LLM found the puzzle pieces. Since they have been stealing most of their training data from anything they could get at, it is entirely plausible they stole some components of the proof under discussion from private chats.

I guess mathematicians will need to resort to running local, private models to not have their ideas stolen.

They just turn off your water heater.

What good does turning the gas off to the water heater do....?

If you can cope at 12C in a T-shirt ... up to you, I wear a real jacket and a scarf.

Ugh...had to get on ChatGPT and find out what the fuck 12C was in F.

Ok, so about 54F...roughly. That's cool...I guess depends a bit on how high your humidity is. In the New Orleans area, it can be 54F and very humid...if the wind is coming in off the lake it can be quite chilly....but if lower humidity, more into winter months,...that's not too cold...I'd be wearing a sweater or a jacket....not both.

Last week it was high-90's and low 100's along the central coast (Santa Cruz & Monterey). It cooled down at night, but I also don't have A/C because I almost never need it, maybe for 3-5 days every 3-4 years it would be appreciated.

You can't get a couple window units to have AC when you need it?

You can put them up and take them down pretty readily......better than baking/roasting on those days when you really don't need to.