Borealid

The data necessary to determine a face had previously been seen are biometric data.

If we're going to be precise, the word "data" is plural and its singular is "datum". But treating it as a substance noun does not change the argument I made in any way - "I gave away the water" does not mean "I gave away some of the water (and kept some for myself)".

The sentence says "the [...] data [...] are automatically and immediately deleted". It does not say "some of the data are automatically deleted". It would be a staight lie to delete some, but not all, of the data and then issue the statement that "the data are deleted". This is not an ambiguous case or weasel-wording: it is an unambiguous falsehood.

If you have two coins and you spend one, you cannot truthfully say "I spent the coins". The definite article "the" means all of something you have in this usage, not a single member of a class of something you have. It would be true to say "I spent a coin" or "I spent some of the coins".

Question: what is the ratio of US wine imported into the EU vs US wine imported into Canada, by dollar value?

Question: what is the percentage increase in tariff amounts on wine between the pre- and post-USMCA state of play between the US and Canada?

Sometimes seeing why something has happened requires considering wider context, which is why it's usually good for a nation to ensure primary education includes solid economics, history, media literacy, etc curricula.

Countries other than the US have, for reasons that you may choose to find mysterious, imposed tariffs on products exported from the US.

Tariffs raise the consumer-visible price of those goods. This then, due to demand elasticity, causes consumers in those non-US countries to buy fewer of those products.

Some impact may be badwill as well but quite a bit is first-order impact of second-order tariffs.

I meant vfio-pci.

The percentage-overhead comparison is pretty choice nonsense. It has only percentages to try and "explain" that overheads don't matter if the system is slow anyhow.

A fair comparison would be this project vs virtio.

There absolutely are still rich-people brands that sell absurd quality at absurd price.

See, for example, Marine Layer in San Francisco, or boutiques like Red Ants Pants.

I can believe that, I'm just here to point out that some of the laws being not-broken are the laws of thermodnamics. You can cool a room cheaply with dry ice, for instance. There are tricks.

There do exist "evaporative coolers", sometimes called "swamp coolers". The trick is that they require water and raise the humidity of their surroundings. But they tick all the boxes you listed - plenty of delta-t, extremely low power, no external tubes or parts.

It's not magic because it relies on the "fuel" of cool water to evaporate.

It's a bias even if the true population distribution isn't linear.

For example, if you have a training corpus where 50% of the text follows "black bobblehead" with "arrested" and 20% of the text follows "white bobblehead" with "arrested", and your LLM is trained such that it produces "arrest" 50% of time after "<color> bobblehead" regardless of color, that's a bias - the output frequency distribution fails to match the "population" (training) frequency distribution. This has nothing to do with races, ethnicities, whatever - it's just statistics and text. To be unbiased, it would need to be less likely to produce the text "arrested" after "white bobblehead" than after "black bobblehead".

A die is supposed to land on each face evenly - a linear probability distribution. So anything other than a linear distribution is biased. But bias can exist for any desired probability distribution. And for an LLM the desired probability distribution of the model output is one that exactly matches the infinitely-many distributions of the various facets of the training data.

Your point about how in the absense of information a token shouldn't influence the distribution is spot-on. But unfortunately almost any token does condition the output, which means you get biased output all the time.

No, a "bias" is a statistical term meaning a probability distribution that has an expected value differing from the population's expected value.

A human's discriminatory bias against an ethnicity is just one type of bias. The LLM isn't a racist, it merely produces text where that text does not perfectly reflect the training data's frequencies.

The reason nuclear reactors are dangerous is because if you turn off the power cooling them down, they react (and radiate) more.

If you turn off the power cooling a data center, the servers within rapidly stop doing any computing.

Positive feedback loops are dangerous. Negative ones self-regulate.

My comment is literally explaining the result of the paper, in which it is shown that LLMs can and do develop biases based on text appearing in their training data set even where such text is not in any training example connected with a systematically more positive or systematically more negative outcome.

In other words, if the text "X is wet" and the text "Y is wet" and the text "X is dry" and the text "Y is dry" each appeared exactly one time in the corpus, it's still possible for a model to end up being produced that is more likely to write wet-like words when it sees X in the context window than when it sees Y.

On a side note, it's very unrewarding to try to explain this type of statistical observation when it feels like (anecdotally, hypocritcally...) the entire world wants to use words like "think" and "understand" and "pick up on" to describe inference and training processes. I'm not making a stochastic-parrot argument here, just pointing out that understanding an LLM's behavior is best done by understanding its conditioning.

I think you're missing the point of TFA.

The LLMs take in text which conditions their output. That means even nonsense text - such as a "tribal affiliation" to a tribe that may not have ever existed - ALSO condition the output, because the tribe name is a token in the context window and there's no such thing as a perfectly neutral token.

Taking away the race/ethnicity layer for a moment, it might be that an LLM develops a predisposition to emit positive terms (like "accept") when the prompt contains "banananow", and negative terms when it contains "pearian". That's the very definition of bias, and hacking those biases could give individuals serious socioeconomic benefits!

That's not how training works.

Training tries to produce something that scores highly in training evaluations. With one data point, the evaluation is solely how closely the model output resembles the single input text.

Let's say you do that, and the training text is 58,100 tokens long. Let's say you ask the model to produce 58,101 tokens. Will it "reproduce [the] text verbatim"? No, it can't, because of the dissimilar requested length. Something "new" will come out.

It's also entirely possible that no matter how long you train, the model never converges on generating exactly the same output as its training data - you could end up with an average loss value of 0.001 instead of 0.0. It's not a perfectly deterministic process.

You're correct in principle, but in reality even with limited training data real-world models produce something that isn't exactly their training, especially when sampled stochastically. They're biased toward their training data, not forced to it.

KYC stands for Know Your Customer, the regulations that require institutions moving money between two parties to positively identify each of those two parties.

I think the intellectual position "it should be illegal for institutions transmitting money between two parties to identify either of those parties" might require some kind of logical argument behind it. Are you saying all financial transactions should be anonmyous by law? How would banks function if they were required to be blind to their customers? How would the government prosecute money laundering if all cash-trails went cold after the first time they passed a bank?

I understand people often like to express extreme positions on the Internet, but I think it's pretty easy to see an ideal society has rules somewhere in between "you're not allowed to know your customers" and "you can't accept a penny unless the giver does a blood draw in front of you and is confirmed to be in a central register of DNA".

I don't think this is what the GP meant, but he's accidentally correct in that there is indeed no good reason for a password to reach the server.

The client could do a challenge-response PAKE with the server, proving the client held the password while not transmitting it. The session cookie could be sent from the server as part of that exchange, encrypted so only the holder of the user's password could decrypt it.

That's not how the web works, but it's strictly superior to the accepted standard of the client sending the raw password to the server, and it would be secure even over an active MITM unencrypted link.

> and by the same token

I don't think you intended this, but the word choice here gave me a chortle.

I think the most useful word in both cases is "extrapolating".

An LLM extrapolates from its context window to the immediate next token. This word applies whether you view what's happening as "reasoning", "prediction", or as a math function.

I believe the GrapheneOS team demands, in particular, a security feature called Memory Tagging Extensions (MTE). This feature has a phone's processor attach a "tag" to each memory location saying what's stored there and requires accesses to that memory to bear a matching tag. Buffer overflow type attacks are effectively prevented because a read into the adjoining region having a different tag gets rejected.

This feature is usually NOT present in desktop computers, and has only really been implemented by the Google Pixel hardware so far. It's unclear why it's viewed as being so critically necessary for Graphene: MTE is certainly useful but I personally wouldn't say its absence indicates an "insecure" device, and it imposes both a clear performance (and battery life!) penalty and a significant hardware burden on the SoC manufacturer. It's a pretty significant trade-off.

Anyway, that's the biggest single reason why GrapheneOS devs say "this hardware is not adequately secure": 99% of phone chips are excluded because they do not support MTE.

I do not feel you addressed my point at all.

I want to install an app now, and protect against its developer doing a rugpull on my local files later. I do not want to need to review each new app version in advance as I install it.

This is clearly a legitimate case where what the Android security model says I should be permitted to do makes me less secure against an attack by the app developer.

Let's say I want to secure my system against an app developer deciding to delete my data stored in their app.

To do that, I wish to store a copy of all the files the app has written to my filesystem, and put that copy outside the app's control. This is explicitly to contain data the app's developer does not WANT me to be able to keep.

A. Is my being unable to do this "more secure"? If so, why is the specific threat I described to my data integrity - an app developer deleting my data - invalid?

B. Does GrapheneOS support this protection, ensuring the device owner is secure against the app developer, or do they instead secure the app developer against the user?

Whether Claude is or is not available via AWS Bedrock is entirely decided by Anthropic, not by you and not by Amazon. And you can't buy the data sets (the REAL power...) from any AI company.

I think the three valid criticisms you listed are valid, but there are other quite a few other IMO-valid criticisms of AI. Here are a few as I see them:

- AI centralizes power in the hands of capital, rendering those who can afford compute hardware vastly more capable than those who cannot and thus increasing social stratification

- AI is generally trained on the creative output of humanity without those who train it giving back proportionally (copyright "rules for thee, not for me")

- AI breaks social processes built around the idea that TRYING something is inherently a cost in time or effort, such as filing a legal claim or sending someone a threatening letter. We haven't made the social changes to punish or charge people for using every appeal/option/application, so this makes asymmetric-effort tasks like applying for a job really bad in the interim

- AI use makes it harder to develop the ability to critically think for yourself, especially among those who most need to develop that ability

- AI produces large amounts of mid-tier content, making it harder to discover exceptional human-created creative content produced after AI started to exist

- AI leads to distrust in remote communication, increasing cynicism and breaking social bonds generally. This is NOT your point about "AI spreads misinformation" - no matter whether it's true or not that AI can be used to produce misinformation, having people doubt each other is a harm

- AI demand crunches hardware and time availability for other adjacent markets, such as computer gaming, construction, 3D graphics production, etc. This harms both hobbies and professions in those fields having to cope with rising prices and lower availability of materials

- Everyone is using the same or similar AI, leading to a homogenization of culture and process across humanity. This is perhaps a mixed blessing, because humans are capricious, but less variety can be viewed as a harm

I will also say I personally hate seeing "job loss" said to mean "wealth loss" or "people starving". The goal of life isn't to have a job, it's to be well and happy. If you can be well and happy without a job, great, so it's really painful to me how people don't even see those things are not the same.

They're both security, just security "against" different things. Graphene frequently fails to clearly describe the threat model when calling something "more secure".

For example, let's say hypothetically I want to be secure against the threat of Google pushing a targeted update to my phone that runs malicious code. Turning on automatic software updates from Google would make me vulnerable to that threat. Using MicroG instead of Google Play Services would make me less vulnerable to that threat. But Graphene devs say things like "MicroG is less secure than Google Play Services".

Similarly, if you want privacy you might secure your device by locking the bootloader with your own keys - not a third-party vendor's keys. Saying that's "insecure" is extremely misleading: it just puts you in charge of security, instead of abdicating to someone else.

I wish there were something like GrapheneOS that let you choose, yourself, who to trust instead of requiring you trust an OS vendor implicitly.

If all rights were inalienable, an employment contract would not mean I need to pay my employee, because I would have an inalienable right to keep my own property (cash).

Also nobody would offer the contract in the first place because the employee would keep their inalienable right to choose how they spend their own time (not working).

EVERY contract is about giving something up in exchange for getting something. In most legal systems a contract is void if either party gives nothing. So in a world where nothing can be signed away, no contracts exist at all.

I, personally, don't feel that "making money by doing business in a particular market" should be a right it is illegal to waive.

If it were inalienable, things like regional distribution agreements would be void, since you could sign away your ability to sell in a certain country and then compete with your distributor anyway.

Let's keep some perspective here - there is no "inalienable right to sell apps to smartphone users via a private commercial storefront".

There's no way to prove the second partition is real encrypted data instead of random garbage. It gets wear-leveled but that would also be the case if the true partition had been resized before.

It doesn't matter if the false partition is unlocked or not - you can plausibly deny there's anything on the phone at all.

Media converters are effectively a switch, but less flexible. I would buy a switch with an sfp+ port instead and use it with an appropriate sfp module.