OP, you linked to the comments instead of the top of the article. 💀

I’m not agreeing with their dumb point, but just pointing out: this satellite works on radar. I’m genuinely concerned how many people seem to be commenting without reading the article.

I don’t know why you’re assuming their ‘/s’ is alluding to sarcasm around this being surveillance versus sarcasm around needing more surveillance. “We need more surveillance (we actually don’t)” seems to be indicated here, not “This is surveillance (it actually isn’t)”.

Especially when Reddit types are notoriously, chronically unable to read articles before they go spouting uninformed bullshit in the comments.

Did you read the part where this is a radar satellite designed for monitoring the climate? That is, did you read anything besides the headline before you decided: “Yeah, I think I’m able to make informed commentary about this”?

Fucking thank you. Yes, experienced editor to add to this: that’s called the lead, and that’s exactly what it exists to do. Readers are not even close to starved for summaries:

• Every single article has one of these. It is at the very beginning – at most around 600 words for very extensive, multifaceted subjects. 250 to 400 words is generally considered an excellent window to target for a well-fleshed-out article.
• Even then, the first sentence itself is almost always a definition of the subject, making it a summary unto itself.
• And even then, the first paragraph is also its own form of summary in a multi-paragraph lead.
• And even then, the infobox to the right of 99% of articles gives easily digestible data about the subject in case you only care about raw, important facts (e.g. when a politician was in office, what a country’s flag is, what systems a game was released for, etc.)
• And even then, if you just want a specific subtopic, there’s a table of contents, and we generally try as much as possible (without harming the “linear” reading experience) to make it so that you can intuitively jump straight from the lead to a main section (level 2 header).
• Even then, if you don’t want to click on an article and just instead hover over its wikilink, we provide a summary of fewer than 40 characters so that readers get a broad idea without having to click (e.g. Shoeless Joe Jackson’s is “American baseball player (1887–1951)”).

What’s outrageous here isn’t wanting summaries; it’s that summaries already exist in so many ways, written by the human writers who write the contents of the articles. Not only that, but as a free, editable encyclopedia, these summaries can be changed at any time if editors feel like they no longer do their job somehow.

This not only bypasses the hard work real, human editors put in for free in favor of some generic slop that’s impossible to QA, but it also bypasses the spirit of Wikipedia that if you see something wrong, you should be able to fix it.

OP, come the fuck on. Have some integrity and don’t post articles from The Economic Times.

No, they definitely are AI. ChatGPT for example is a generative pretrained transformer (GPT) is a transformer model is a deep learning model is a machine learning model is AI.

It’s just that the general public has no fucking idea what “AI” is due to being swamped in marketing about a field they have zero background in and have been led to believe is some kind of general intellect on the level of a human or smarter. In reality, a perceptron with one weight and one bias is machine learning is AI.

Since the start, what “AI” is has been fairly arbitrary; it’s just the ability for a machine to perform tasks we’d associate with human intelligence. It doesn’t even need to be machine learning; that’s just one branch. The game Video Checkers (1980) for the Atari 2600 running on 128 bytes of RAM has AI that you play against. The bar isn’t high at all.

The difference: Israel is in Syria for imperialist aggression. Ukraine is in Ukraine to protect their homeland from imperialist aggresssion. Combine that with Israel’s pathological need to cover up and deny their extensive, seemingly neverending war crimes in Gaza… Yeah, I don’t have any faith until Israel can prove this was opsec rather than covering up. Israel has destroyed their chance for benefit of the doubt.

Even if it is opsec, they have no right being there, so fuck 'em. I hope their opsec isn’t maintained and their soldiers do die in much the same way I’d hope for a Russian base in Donetsk.

I don’t at all understand why the second law of thermodynamics is being invoked. Nonetheless, capillary condensation is already a well-studied phenomenon. As the scientific article itself notes, the innovation here over traditional capillary condensation would be the ability to easily remove the water once it’s condensed.

Re: Entropy:

• Entropy is a statistical phenomenon that tends to increase over time averaged across the entire body, i.e. the Universe. Not literally every part of the Universe needs to increase its entropy as long as on average it is increasing. You’re evidence of that: your body is a machine that takes entropy and pushes it somewhere else.
• Water vapor is a high-energy state compared to liquid water. What you’re saying therefore is the opposite of how the second law works: water vapor’s energy tends to spread out over time until it eventually cools back to a liquid. Liquid water is a higher entropy state than water vapor.

“It was terrible. He would spend hours telling me about how NFTs are the future and I need to get in on the ground floor.”

I don’t disbelieve you, but I think a huge part of the mis/disinformation problem right now is that we can just say “I read something not that long ago that said [something that sounds true and confirms 90% of readers’ pre-existing bias]” and it’ll be uncritically accepted.

If we don’t know where it’s published, who published it, who wrote it, when it was written, what degree of correlation was established, the methodology to establish correlation, how it defines corruption, what kind and how many politicians over what time period and from where, or even if this comment accurately recalls what you read, then it’s about the same as pulling a Senator Armstrong even if it means well. And if anyone does step in to disagree, an absence of sources invites them to counterargue based on vibes and citing random anecdotes instead of empirical data.

What can I immediately find? An anti-term limits opinion piece from Anthony Fowler of the University of Chicago which does do a good job citing its sources but doesn’t seem to say anything about this specific claim. Likewise, this analysis in the European Journal of Political Economy which posits that term limits increase corruption but in return decrease the magnitude of the corruption because of an inability to develop connections.

Internet comments aren’t a thesis defense. But I think for anything to get better, we need to challenge ourselves to create a healthy information ecosystem where we still can.

Dude, I’m sorry, I just don’t know how else to tell you “you don’t know what you’re talking about”. I’d refer you to Chapter 20 of Goodfellow et al.'s 2016 book on Deep Learning, but 1) it tragically came out a year before transformer models, and 2) most of it will go over your head without a foundation from many previous chapters. What you’re describing – generative AI training on generative AI ad infinitum – is a death spiral. Literally the entire premise of adversarial training of generative AI is that for the classifier to get better, you need to keep funneling in real material alongside the fake material.

You keep anthropomorphizing with “AI can already understand X”, but that betrays a fundamental misunderstanding of what a deep learning model is: it doesn’t “understand” shit about fuck; it’s an unfathomably complex nonlinear algebraic function that transforms inputs to outputs. To summarize in a word why you’re so wrong: overfitting. This is one of the first things you’ll learn about in a ML class, and it’s what happens when you let a model train on the same data over and over again forever. It’s especially bad for a classifier to be overfitted when it’s pitted against a generator, because a sufficiently complex generator will learn how to outsmart the overfitted classifier and it will find a cozy little local minimum that in reality works like dogshit but outsmarts the classifier which is its only job.

You really, really, really just fundamentally do not understand how a machine learning model works, and that’s okay – it’s a complex tool being presented to people who have no business knowing what a Hessian matrix or a DCT is – but please understand when you’re talking about it that these are extremely advanced and complex statistical models that work on mathematics, not vibes.

Your analogy simply does not hold here. If you’re having an AI train itself to play chess, then you have adversarial reinforcement learning. The AI plays itself (or another model), and reward metrics tell it how well it’s doing. Chess has the following:

1. A very limited set of clearly defined, rigid rules.
2. One single end objective: put the other king in checkmate before yours is or, if you can’t, go for a draw.
3. Reasonable metrics for how you’re doing and an ability to reasonably predict how you’ll be doing later.

Here’s where generative AI is different: when you’re doing adversarial training with a generative deep learning model, you want one model to be a generator and the other to be a classifier. The classifier should be given some amount of human-made material and some amount of generator-made material and try to distinguish it. The classifier’s goal is to be correct, and the generator’s goal is for the classifier to pick completely randomly (i.e. it just picks on a coin flip). As you train, you gradually get both to be very, very good at their jobs. But you have to have human-made material to train the classifier, and if the classifier doesn’t improve, then the generator never does either.

Imagine teaching a 2nd grader the difference between a horse and a zebra having never shown them either before, and you hold up pictures asking if they contain a horse or a zebra. Except the entire time you just keep holding up pictures of zebras and expecting the child to learn what a horse looks like. That’s what you’re describing for the classifier.

Notepad and WFE get thrown off hell in a cell into an announcer’s table by Kate and Dolphin, respectively, but to say they “don’t work” is intellectually lazy and dishonest.

Who are you trying to convince right now? Linux and macOS users are probably never going back to Windows if they can help it, and Windows users will correctly say “but it’s right there; I’m using it right now”.

It’s an easy mistake to make. For future reference, Wikiquote – a sister project of Wikipedia like Wiktionary and Wikimedia Commons are – is very often a good benchmark for whether famous people have said a quote.

• For famous quotes that they’ve said, they’re usually listed (if they are, there’s a citation to exactly where that quote came from).
• For famous quotes they didn’t say, the “Misattributed” section often has the quote with a cited explanation of where it actually comes from.
• For famous quotes they might’ve or probably didn’t say, the “Disputed” section shows where it’s first attributed to them but of course cannot provide a source where they themselves say it.

It doesn’t have every quote, but for very famous people, it filters out a lot of false positives. Since it gives you a citation, often you can leave a URL to the original source alongside your quote for further context and just so people who’d otherwise call BS have the source. And it sets a good example for others to cite their sources.

Benito Mussolini did not say this.

The fact this comment is so low means one of three things:

• A shocking amount of /c/news readers have a subscription to The Wall Street Journal
• A shocking amount of /c/news readers interact in the comments without reading the article first
• A shocking amount of /c/news readers already know you can use archive.today to bypass paywalls (based tbh)

https://codeberg.org/

Honestly a good rule to live by. If it were really that outstandingly annoying, they’d just say what it is in the title knowing that it would drive clicks from people who would think “Oh my god, I hated that!”

The original AP article so you don’t have to use the slop site it’s syndicated to.