Borealid

U2F does not support PINs. You may be thinking of FIDO2, which does.

"The AI" cannot "refuse" any more than a hammer can refuse. If you use a hammer to kill someone, you commit a crime and the hammer is unprosecuted. If you design a hammer to kill people and then give it away, you are partially liable for the deaths it causes. If you make a normal hammer and someone uses it to kill, you bear no blame.

I don't see why these standards should change when the hammer also emits text messages.

The grandparent comment is correctly pointing out the sentence is an LLM tell.

"Membership is a question they ask a server" is a bogus sentence. "membership" is not a "question". It's syntactically valid semantic nonsense.

"Membership is dictated by a server" is one of several human sentences saying what that one is trying to.

I think the DOI system provides a stable identifier for a paper that is not specific to arXiv?

it just requires a few cryptographic primitives and a set of device-bound keys

Question: how do you make sure the keys are device-bound if you have no attestation about the hardware or operating environment?

I was a bit upset to see vitriolic opposition online to systemd adding a field to store, entirely locally to a Linux system, the user's age.

I think opponents to these bills frame it as current state vs complete, invasive third-party identity verification. That's a very unfortunate framing because, as you say, it would be possible to take the wind out of the identity-verification proponents' sails by implementing better on-device controls.

That issue cannot be a bug in the game, because the operating system should not allow a game to (by any means) produce that type of behaviour. So it's a bug in your OS, potentially the network card driver.

There are fewer of those on Linux but they still exist.

I'm sorry it affects you directly, but the number of people who live in the whole state of Wyoming is around a half-million (even ignoring "rural"). If every single person in the entire state were affected, that would be 1/650th of the population of the United States affected, to say nothing of the world.

There's just no way it's a significant factor in overall sentiment.

What percentage of people do you think are affected by AI datacenters?

That argument applies better to blast furnaces than to data centers, but I don't see people complaining about steel. Data centers just don't take up much space or power in the scope of industrial manufacturing.

Your other arguments are legitimate, but "it's a waste of electricity" and "data centers make some significant difference to a nontrivial number of people" are not the same propositions.

If you want yourself to be the root of trust, you CAN generate and use your own keys for secure boot.

The IPs are Cloudflare, the TLS fingerprint is uTLS Chrome, and the number of connections with xhttp is the same as your normal browsing.

If you are willing to block browsing all ordinary web sites fronted with a CDN, then yes you can block reality/xhttp. You cannot, however, differentially block it via any of the three things you mentioned.

I will have a stab at legitimately explaining the viewpoint you profess not to understand.

"Institutional" or "structural" racism doesn't just mean racism by one or two people in power. It's the idea that the majority of society demonstrates some kind of racial bias, by whatever means.

Society is made up of people.

One of two things must, logically, be true:

1. A SUBSTANTIAL portion of the people who make up society exhibit some kind of racist behavior, or

2. Structural racism is not a widespread issue

Which one of these two propositions must one believe is likely if one is researching the impact of structural racism? Keep in mind people do not generally don't go looking for things they do not believe exist.

In other words, people don't like other people believing they-en-masse discriminate (even IF they do), so taking actions that only make sense if you think that poorly of the everyman offends them. It's not about what someone wants to be true, it's that investigating implies a level of distrust in society some members of that society find uncivil.

To use a blunt analogy, "why not let me check your underwear to make sure you haven't soiled it? Do you just not want it to be true?".

The state of the art, "xray-reality", is not blockable. It's a legit tls connection with data smuggled inside it.

Technically no, because selling a thing is both a risk and a cost (of time and money).

Okay, understood. You are making a variant of the Chinese Room argument in which you allow some types of computer programs (but not others) to have reason/sentience. I'm not entirely sure what specific lines you're drawing between the programs (what makes a deterministic transformer with sampling temperature zero "not a recording" but a hash table "a recording"?) but that's not super important.

There is nothing wrong about having that philosophy, and I respect it, but personally I think if it's impossible to tell two things apart using any external observation there is not a meaningful difference between those two things. "Smells like a rose" and all that.

Just to make sure I've understood you... Are you arguing that with a set of identically-behaving black boxes, one could be "reasoning" and one could be "not reasoning", and a person would need to look inside the boxes at how they function to decide?

Remember, if the mapping from input to output is identical, there exists no test operating on the machines' output that can differentiate them. You can't tell from "conversing with" a machine whether it is or is not doing what you say around "inspecting" the input.

The paper presents a constructive transformation from any finite-input (finite vocab, bounded length) transformer to an equivalent Markov chain.

Do you have some concrete example of a transformer that cannot be represented as a mapping from inputs to probability distribution of outputs?

I say they're equivalent because it is possible to losslessly convert one to the other by wasting massive amounts of disk space and time.

As a second example proving the point, imagine you sampled a transformer's output for a certain context 85 trillion times, and put the output token frequencies in a table. Repeat for all possible inputs (of which there are a finite number). Then you built literally a hash map looking up the context and spitting out the distribution. That certainly is NOT a transformer any more (it's a hash map!!!), but the output approaches indistinguishability as the sample count increases - if the transformer is reasoning, so is the hash map built from it.

I'm not talking hot air here, they really are provably equivalent because a 1:1, onto mapping exists.

For the record, "X is more expressive than Y" means "there exists at least one thing that Y cannot represent and X can". Nothing to do with size or time.

No, not nonsense.

Both are a lookup table whose key is the entire context window and whose value is a probability distribution for what the next token should be.

You can say the choice of probability distribution in the value is "leveraging the internal structure of the context" or not, but the same tokens in two different orders are two different lookup keys and saying it's impossible to achieve some result with a Markov chain is factually incorrect.

https://arxiv.org/pdf/2410.02724 describes the equivalence formally.

There is absolutely nothing stopping someone from distilling a modern LLM into a very effective Markov chain. The physical size of the model would explode because a context window containing C tokens of size B would need B^C Markov prior states, but the actual output would be a deterministic version of the LLM's with top-n n=1 sampling.

In other words, a Markov chain and a Transformer model are exactly equivalent in power (there is NOTHING that can be done with one and not the other). The Transformer model is just better pretrained and a more efficient compression/generation.

The point is that the output is text that is statistically correlated with the input.

The capability of the LLM is not to reason, it's to generate text that matches the patterns seen in the training corpus. It's possible that all you need to "reason" is plausible text generation. I'm not saying it's not. But nothing the LLM does fails to be explained by plausible-text-generation.

I contend that the best way to understand an LLM's capabilities is to understand the nature of the probability distribution that produced it. For instance, why does an "angry" prompt tend to produce more help than a "polite" one? Trying to explain that in terms of emotions or reasoning doesn't make sense, but it's readily possible to explain through the connections between text in the training corpus...

I completely agree that humans sometimes are not applying reasoning to things.

I'm not trying to argue a model cannot "reason" or have "cognition", whatever those things are. I'm only saying that it's absolutely the case that whatever those things are, they come from its mechanism of predicting one token at a time ad infinitum, and that throwing away a deep understanding in favor of a shallow one is foolish. Just because it might seem to be "reasoning" does not mean it IS doing so, and certainly giving the appears of reasoning does not mean it is NOT a token predictor.

If I knew deeply how the human brain works I would use that understanding instead of saying things like "this person reasons" or "this person thinks".

In summary, I'm not "caught up in" anything - I'm just trying to point out that the original poster here is incorrect in saying that clearly LLMs aren't working through token prediction. They are, and all their behavior is 100% explained by token prediction. That's more than enough for interesting behavior!

No. The how is relevant here because it leads to understanding of the resulting behavior.

If you train the LLM on a corpus that shows people saying the sky is red, you get an LLM that is predisposed to say the sky is red. This is true even if it's also trained on all of the science that explains how and why the sky is blue.

If it were to "figure out" or "reason", it would not have such a predisposition to emit "red" after "the sky is" just because that matches the reward during training.

In other words, the token prediction is important because it both explains the successes AND the failures of the LLM. If there were situations in which a bird could fail to fly, then how it tried to fly would also be crucial knowledge.

Your casual understanding is imprecise.

At all times the LLM is, indeed, predicting the next token. Anything it does emerges from that.

It did not "figure anything out". It predicted that text describing the use of a radial gradient was likely to follow text describing your problem.

Most spreadsheet engines are turing complete, so you could use them to run an LLM.

I don't think many people would say an LLM written in Python is conscious BUT an LLM written in Excel is not.

People just don't ascribe consciousness to things that can't converse (or at least emote or give the appearance of emoting), and spreadsheets don't do that.

The reason people are debating the consciousness of LLMs is - obviously - that the LLMs generate sufficiently plausible text that people using them think they're having a two-part conversation. Like I think I might be having a two-part conversation now. Turning your question around, why do you think Hacker News posters are conscious? You have no direct evidence they are.

The Framework 16 lets you put a pad with twenty-four additional buttons on it next to the keyboard. These 24 buttons can be programmed to do whatever you want with reprogrammable firmware.

Also, there are twenty-three different keyboard layouts available (IN ADDITION TO the 24-key macropad).

I think there are legitimate arguments against Framework, but this one clearly isn't cogent.

I said the owners can't be held liable, I meant the owners can't be held liable.

You can "in certain circumstances" (negligence, overt criminality...) go after the managers. You probably can't go after the managers for things like producing a business plan they could have plausibly believed was legal and causing the company to incur civil liability.

In the situation described in this article, probably both the owners and the managers (likely the same people!) get away without being held accountable, and the victims have no recompense because the company folds.

The post to which you're replying is implying that the lift shafts are entirely opaque to the wireless signal.

So it's fine if the user doesn't have a shaft between them and the AP. When they move so a straight line from the device to the AP crosses through a lift shaft, they enter the wireless "shadow" cast by that shaft, preventing them from contacting the AP. When they take another step forward the device might "come out of the shadow".

This is a difficult situation to deal with in roaming, where the visible AP set changes rapidly as the user moves a small amount.

TL;DR: I'm pretty sure the parent you're replying to "got it" and you didn't understand what they were trying to say.

As a slight hint, one of the more common types of corporation is an "LLC". LLC stands for Limited Liability Company.

If the company's owners had unlimited liability for problems the company caused, that wouldn't be much of an LLC, would it? The primary purpose of an LLC is to make it so that the owners (often the founders) cannot personally be held responsible for debts the company incurs, even debts incurred through their instructions.

This also includes debts caused by punishment for the company breaking civil contracts, but doesn't make individuals who use the company to break the law immune to criminal charges. But the standard of evidence for prosecuting that type of malfeasance is pretty high...

The interior of the house is a private space. Things under your clothes are too. Revealing either of these things through whatever technology is a search.

The standard is whether something expected to be private is revealed. What your eyes look like (even in detail) is not that. There isn't a point on some line where the photograph becoming higher-quality applies a different standard than a low-resolution photo would.

No, looking up your face in a list of faces is searching FOR you, not searching you.

Searching you means taking an inventory of the items on your person. It does not mean looking at you. In some cases, imaging you can be a "search" even where there is no physical contact (for example: a millimeter-wave scanner), but a photograph in a public place has never qualified as a "search" in the USA.

I understand your feelings, but so far as I know things like gait recognition, facial recognition, or even an iris scan derived from an ordinary photograph have never qualified as a "search" under U.S. law. Feel free to correct me if I am wrong on this: it's quite difficult to prove something has _not_ happened.

I think the legal line is not when it "becomes biometrics" or becomes identification. The legal line is when you are revealing a private property about an individual (for example, their blood type, or the contents of their pockets). Nothing visible to the naked eye in public is considered private, so nothing that derives identity from that public information is a "search".

As a nice easy example... an officer smelling alchohol on the breath of a person in the course of a conversation is not a "search". An officer compelling that same person to breathe into a breathalyzer machine is. Applying the same standard to faces, you cannot make an individual put their eye to a scanner without reasonable suspicion, but if you can get a biometric scan from the invidual as they happen to walk about their day, doing that isn't searching them...