You don’t have a moral or ethical obligation to respect their terms, but I wouldn’t go too wild with it, as using a ton of data might get noticed and fixed, causing someone else who’s benefiting from this and who can’t afford a replacement setup to lose it.

Certainly the latter.

I have pretty decent insurance through work, but if I’m picking up a prescription, it’s cheaper for me to say I don’t have insurance and use a free discount card (like GoodRx) than to use my insurance. We’re talking $150-$200 for one prescription (a one month supply) with insurance vs $30 without.

To be fair, I have an HDHP with an HSA so my insurance is only supposed to negotiate a discount until I hit the deductible, rather than paying for it. Full price is $200-$250, I think? (I get generics and each generic variant has a slightly different price.) So technically they’re providing a discount, just not a very good one.

Insurance also likes to require a “prior authorization,” which was always a fun surprise after making it through the pharmacy line. That normally takes a couple days to resolve, at minimum, and sometimes longer. If you’re not familiar with prior auths, it’s basically when the insurance company says “Hey doc, can you justify why you’re prescribing this and answer these eight questions?” and then they have someone without a medical degree review the answer and see if it’s good enough.

The only downside to paying out of pocket with a discount card is that the $30 doesn’t go toward my deductible. But since my deductible is multiple thousands of dollars, unless something else happens during the year, I won’t hit my deductible off the $150-$200 prescriptions + regular doctor visits alone. But that’s at most $360 out of pocket that wouldn’t have gone toward the deductible, assuming I had a health crisis in December, vs $1440-$2040 saved if I don’t.

X-rays are even worse, because you’re not told the price ahead of time.

Illegal vote suppression elected Trump, but even if it hadn’t, you should blame Democrats before blaming people who voted for third party candidates. Now, if you’re talking about people who “protest voted” by voting for Trump (in both the primaries and the election), then sure. Those people did, in fact, play an instrumental part in electing him.

Why blame Democrats? Well, beyond just kinda being Republican-lites:

• for opposing ranked choice voting (and alternatives)
• for not rallying around progressive candidates
• for not choosing Kamala via primary elections in 2024

Democrats are the bare minimum “harm reduction” party, and I don’t bare any ill will toward people who voted for them rather than a party that would actually try to effect change, but the opposite mindset - blaming third party voters for not voting for Democrats - is very shortsighted. And as third party voters have never had the power to enact RCV or STAR voting or otherwise improve the system, blaming them instead of the Democrats who have had that power is inane.

I’ve voted for a Democrat every single presidential election that I’ve been able to, but I honestly wish I hadn’t. I’d much rather there be more visibility for third parties, and for more people to feel empowered to vote for third party candidates.

Glaring doesn’t imply a negative meaning. In this case it’s used to mean “obvious”.

Unless you’re suggesting that “glaring” means “obviously staring” (it doesn’t - that would be “glaringly staring”) this doesn’t make any sense.

“[He’s] glaring at [direct object]” is an example of a sentence that uses the present participle form of the verb “glare,” which explicitly communicates anger or fierceness.

If you’re not convinced, read on.

—————

The verb form that takes an object is:

Glare (verb with object): to express with a glare. They glared their anger at each other

The noun form the above definition references is:

Glare (noun): a fiercely or angrily piercing stare.

“Glaring” can be an adjective and one of those definitions does mean “obvious” or “conspicuous,” but the use of that form of the word doesn’t make sense in her sentence. Think about a comparable sentence like “The undercover operative is conspicuous at the bar,” where the bar is the location. (Even then, most people wouldn’t use “glaring” in that sentence, as “conspicuous” or “obvious” are much less ambiguous; the operative could be staring piercingly or angrily at the bar rather than being glaring while being at the bar.) Another example that makes a bit more sense is “The effect of the invasive plants is glaring at the park.”

But for that interpretation to be valid here, you’d have to:

• believe that the dude is trying to hide/blend in, or otherwise explain how he - not what he’s doing, but the dude himself - is conspicuous
• believe that the woman’s referring to her own ass as a location
• assume that she isn’t commenting on how the guy is looking at her ass, even though the joke depends on giving him something different to look at

That’s a bit of a stretch.

There’s a whole history of people, both inside and outside the field, shifting the definition of AI to exclude any problem that had been the focus of AI research as soon as it’s solved.

Bertram Raphael said “AI is a collective name for problems which we do not yet know how to solve properly by computer.”

Pamela McCorduck wrote “it’s part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, but that’s not thinking” (Page 204 in Machines Who Think).

In Gödel, Escher, Bach: An Eternal Golden Braid, Douglas Hofstadter named “AI is whatever hasn’t been done yet” Tesler’s Theorem (crediting Larry Tesler).

https://praxtime.com/2016/06/09/agi-means-talking-computers/ reiterates the “AI is anything we don’t yet understand” point, but also touches on one reason why LLMs are still considered AI - because in fiction, talking computers were AI.

The author also quotes Jeff Hawkins’ book On Intelligence:

Now we can see the entire picture. Nature first created animals such as reptiles with sophisticated senses and sophisticated but relatively rigid behaviors. It then discovered that by adding a memory system and feeding the sensory stream into it, the animal could remember past experiences. When the animal found itself in the same or a similar situation, the memory would be recalled, leading to a prediction of what was likely to happen next. Thus, intelligence and understanding started as a memory system that fed predictions into the sensory stream. These predictions are the essence of understanding. To know something means that you can make predictions about it. …

The human cortex is particularly large and therefore has a massive memory capacity. It is constantly predicting what you will see, hear, and feel, mostly in ways you are unconscious of. These predictions are our thoughts, and, when combined with sensory input, they are our perceptions. I call this view of the brain the memory-prediction framework of intelligence.

If Searle’s Chinese Room contained a similar memory system that could make predictions about what Chinese characters would appear next and what would happen next in the story, we could say with confidence that the room understood Chinese and understood the story. We can now see where Alan Turing went wrong. Prediction, not behavior, is the proof of intelligence.

Another reason why LLMs are still considered AI, in my opinion, is that we still don’t understand how they work - and by that, I of course mean that LLMs have emergent capabilities that we don’t understand, not that we don’t understand how the technology itself works.

We are. Why do you think we stopped?

The witch turned the creep into a woman and the spell was complete by the time she flew away. Unfortunately, like many women, the creep was born with the body of a man (she’s AMAB). Maybe the witch could have changed her body, too, but that would have made things far too easy, given that the point of the curse was to teach her empathy.

I had never heard of this show before today but what you just described makes it sound cool as fuck, I’m gonna check it out now

This is an interesting parallel, but I feel like I missed some key part of it.

In the US, at least, we historically killed off a lot of deer’s natural predators - mostly wolves - and as a result, the deer population can get out of control, causing serious problems to the ecosystem. Hunters help to remedy that. The relatively small violences that they perform on an individual basis add up to improving the overall ecosystem.

That isn’t the same as being a bigot, or a sexist, or a fascist… and I don’t know why anyone would assume that a person holds those views because they’re mean and petty. They hold those views for a variety of reasons - sometimes because they’re a child or barely an adult and that’s just what they learned, and they either don’t know any better or haven’t cared enough to think it through; sometimes because they’ve been conditioned to think that way; sometimes because they’re sociopaths who recognize that it’s easier to oppress that particular group.

It doesn’t really matter what their reason is. Either way, they’re a worse person because of it, and often they’re overall a bad person, regardless of the rest of their views, actions, and contributions.

Being a hunter, by contrast, is neutral leaning positive.

It makes sense that a rational person who loves being in nature, who loves animals, who wants their local ecosystem to be successful, would as a result want to help out in some small way, even if that means they have to kill an animal to do so. It doesn’t make sense that a rational person who loves all people, who wants their local communities to be successful, would as a result want to oppress and harm the people in already marginalized groups.

I don’t think equating being bigoted with holding unjustifiable opinions does it justice. The way we use the word opinion generally applies to things that are trivial or unimportant, that don’t ultimately matter, e.g., likes and dislikes. Being a bigot is a viewpoint; it shapes you. For many bigots, their entire perspective is warped and wrong. And there’s a common misunderstanding that you can’t argue with someone’s opinions; because it’s just how they “feel.” But being a bigot, whether you’re sexist, racist, transphobic, queerphobic, homophobic, biphobic, etc., is a belief, and it’s one that, in most cases, the bigot chooses (consciously or not) to keep believing.

If an adult with functioning cognitive abilities refuses to question their bigoted beliefs, then they’ve made a choice to be a bigot.

It’s more likely that this is being done to either:

• Evade hiring restrictions
• Interview on someone else’s behalf

If you do not understand why this is inappropriate you are the problem.

Was it inappropriate for Elon Musk’s company to not properly secure the data of its customers? I would say so. It would therefore be appropriate for anyone harmed as a result to sue Tesla - or Elon directly - for any damages they suffered.

Wasn’t the estimated delivery date much sooner when you first placed the order? Per Amazon’s stated policy, you should be eligible for refund three days after that date.

Obviously it would be preferable for you to get it even sooner, but that’s still a lot better than two months from now.

If you have an email or any record of the original estimated date, contact Amazon CS and reference that. Don’t even mention the changed delivery - that’s not your problem, as you didn’t agree to a changed delivery date; you were promised delivery three days ago and haven’t received it.

You can control that with a setting. In Settings - Privacy, turn on “Query in the page’s title.”

My instance has a magnifying glass as the favicon.

Giant squids are the bears of the ocean

Wouldn’t be a huge change at this point. Israel has been using AI to determine targets for drone-delivered airstrikes for over a year now.

https://en.m.wikipedia.org/wiki/AI-assisted_targeting_in_the_Gaza_Strip gives a high level overview of Gospel and Lavender, and there are news articles in the references if you want to learn more.

This is at least being positioned better than the ways Lavender and Gospel were used, but I have no doubt that it will be used to commit atrocities as well.

For now, OpenAI’s models may help operators make sense of large amounts of incoming data to support faster human decision-making in high-pressure situations.

Yep, that was how they justified Gospel and Lavender, too - “a human presses the button” (even though they’re not doing anywhere near enough due diligence).

But it’s worth pointing out that the type of AI OpenAI is best known for comes from large language models (LLMs)—sometimes called large multimodal models—that are trained on massive datasets of text, images, and audio pulled from many different sources.

Yes, OpenAI is well known for this, but they’ve also created other types of AI models (e.g., Whisper). I suspect an LLM might be part of a solution they would build but that it would not be the full solution.

Thanks for clarifying! I’ve heard nothing but praise for Kagi from its users so that’s what I was assuming, but Searxng has also been great so I wouldn’t have been too surprised if you’d compared them and found its results to be on par or better.

By the way, if you’re self hosting Searxng, you can use add your own index. Searxng supports YaCy, which is an actively developed, open source search index and crawler that can be operated standalone or as part of a decentralized (P2P) network. Here are the Searxng docs for that engine. I can’t speak to its quality as I still haven’t set it up, though.

there is a better open source meta search engines

I already use Searxng and have never used Kagi, but I’m curious why you say that Searxng is “better.” Are you saying that because the quality of the searches is better, because it’s open source and Kagi isn’t, or for some other reason?

Your Passkeys have to be stored in something, but you don’t have to store them all in the same thing.

If you store them with Microsoft’s Windows Hello, Apple Keychain, or Google Password Manager, all of which are closed source, then you have to trust MS/Apple/Google. However, Keychain is end to end encrypted (according to Apple) and Windows Hello is currently not synced to the cloud, so if you trust those claims, you don’t need to trust that they won’t misuse your data. I don’t know if Google’s offering is end to end encrypted, but I wouldn’t trust it either way.

You can also store Passkeys in a password manager. Bitwarden is open source (though they did recently introduce a proprietary, source available SDK), as is KeepassXC. 1Password isn’t open source but can store Passkeys as well.

And finally, you can store Passkeys in a compatible security key, like the YubiKey 5 series keys, which can each store 100 Passkeys. This makes them basically immune to being stolen. Note that if your primary interest in Passkeys is in the phishing resistance (basically nearly perfect immunity to MitM attacks) then you can get that same benefit by using WebAuthn as a second factor. However, my experience has been that Passkey support is broader.

Revoking keys involves logging into the particular service and revoking them, just like changing your password. There isn’t a centralized way to do it as far as I’m aware. Each Passkey is only used for a single service, after all. However, in the same way that some password managers will offer to automatically change your passwords, they might develop a similar for passkeys.

Do any of the iOS or Android apps support passkeys? I looked into this a couple days ago and didn’t find any that did. (KeePassXC does.)

You have your link formatted backwards. It should be Vaultwarden, with the link in the parentheses.