Yup, for something like kernel dev you need strong leadership/management, like Linus was, until he somehow got confused weakness is a virtue.

No, the thing you have to understand is that contemporary art is basically just the ultimate speculator's market in arbitrary status-signalling symbols for the mega-wealthy, dressed in a thin veneer of faux-intellectualism and pretend-philosophy; it didn't sell for this much because there's something special going on with colors here, it sold for that much because Basquiat got famous because of the movie made about him, and therefore dealers pushed his work into the artificially-created market for in-demand rare pieces by famous artists, a market serviced by either people like billionaire oil tycoons who want something to show off to the women they bring home, or by collectors who invest speculatively on the (historically largely correct assumption) that there will continue to be people buying into the upward cycle of speculation on rare pieces in future (and that they can therefore potentially sell them later for more). If they can convince a few gullible people there's something magical going on re the 'colors in the piece', all the better, but the market would exist regardless, because that's neither why rich people buy such pieces, nor why speculative collectors buy them.

It does, by associating the 'negative emotional experience' of reading a manual (aka learning) with so-called "over-featuring", whatever "over" is supposed to mean. Of course reading a manual is unpleasant, for the same reason studying anything is unpleasant - e.g. engineers study advanced calculus (which tends to create a 'negative emotional experience') because it helps them later do useful things like build bridges that don't collapse.

Likewise, studying a user manual (unpleasant learning/studying) helps you later do useful things with the software - it's an investment, that pays off later, once you are able to get more power out of the software. It doesn't mean advanced calculus is "over-featured".

You don't read user guides because it's fun, just like most people don't study advanced calculus for fun. Most people don't study accounting for fun, but studying accounting has huge benefits later if you run a business.

The basics of software should usable by the average user with minimal studying, sure, but there is an inherent point at which you must invest in doing some unpleasant learning if you want to get the full power and return on investment from the software product.

Wine no longer stands for 'Wine Is Not an Emulator', it's just "Wine":

https://www.winehq.org/about "Wine (originally an acronym for "Wine Is Not an Emulator") "

and in fact it originally stood for "Windows Emulator":

https://en.wikipedia.org/wiki/...

"The name Wine initially was an abbreviation for Windows Emulator.[16] Wine later shifted to the recursive backronym Wine Is Not an Emulator in order to differentiate the software from CPU emulators.[17] No code emulation or virtualization occurs when running a Windows application under Wine.[18] "Emulation" usually would refer to execution of compiled code intended for one processor (such as x86) by interpreting/recompiling software running on a different processor (such as PowerPC). While the name sometimes appears in the forms WINE and wine, the project developers have agreed to standardize on the form Wine"

10 years ago most people were looking at RFID tags as the approach for doing this.

But the money has to come from somewhere. If a family in a village gets $500 per month and that comes from taxing me $500, then I have $500 less per month, and if my kids get sick I might no longer be able to afford their healthcare, or I may no longer be able to afford to send them to University. We do not yet live in a post-scarcity where machines produce everything for us; we still live in a society where to give to A we must take from B. These studies show benefits to the recipients of the welfare, that's great, but that's only one side of the coin, why don't these studies show where a middle-class family under pressure that are paying the welfare bill can no longer afford their own kids health or education.

This still doesn't make sense. You cannot reliably determine the best 'faked images', and there's a reason for that - the only way we can know a well-faked image is fake is if there are things that *semantically* don't make sense in an image - e.g. say it's supposedly a photo of a ball, but the lighting doesn't make sense for a ball as there's a shading anomaly on the surface of the ball - the human can say, OK, that's supposed to be round but it's not, that must be fake - but if the AI 'fake detector' doesn't know that's supposed to be a ball, and if the lighting is correct for the shading anomaly if it were a dimple on the ball, then the "fake" IS NOT ACTUALLY A FAKE - it's just a photo of a ball with a dimple, with correct lighting. (If the lighting is *inherently wrong*, e.g. we can see the scene is lit from the left but there's a shadow falling the wrong way - then sure, we can tell something is fake - but a well-done fake incorporates correct applied scene lighting.)

Now image this fake is not a ball, but the super-imposition of one face, over another face - e.g. we take a photo of an actor doing something, then super-impose Trump's face over it - AS LONG AS WE GET THE LIGHTING RIGHT for Trump's face, then there is no way to tell the image is "fake" (unless we know via some other means, that Trump was not in that location at that time) - a pixel is a pixel is a pixel, whether that pixel came from Photoshop or not.

Of course there are other little things like image grain, but that's trivial to apply, as long as we look at the granularity profile of the original we can simulate granularity on the faked parts (I have done this many times).

Your generator is creating 100% fake images, so a *true* reliable detector would detect 100% of the images generated by that generator.

"Agreed. If nothing else, we'll train an AI to spot the fakes. I mean, apparently AI can do anything these days, right?"

So you'll train the AI to spot fakes based on what, real-world training data for which you can't reliably determine they're fakes? Or you'll create your own fakes as training data? This doesn't make much sense; since it's impossible for a human to distinguish a very well-done fake from a legitimate image, you're basically just going to train your AI to at best determine badly-done fakes - the very ones that a human can easily spot anyway.

"Yes, Photoshop has made photo doctoring easy, but the digital age makes it easy enough to detect and debunk"

Considering how many people I've seen boldly declaring something 'obviously fake' on the basis of dumb crap like JPEG artifacts or H.264/H.265 encoding artifacts, I'm very wary of anyone who thinks it thinks it's "easy" to detect and debunk fakes - actually, I've been doctoring photos in Photoshop for over 10 years, and the bottom line is that while badly-done fakes are easy to spot, most well-done fakes are 'difficult to impossible' to detect. Yes, at a certain quality level of work, it is currently impossible to distinguish a well-done fake from a legitimate image - this will remain true until we have digital signing built in to cameras and then end-to-end in the workflow (which currently seems like that will never happen). There are many people with the skills to create well-done fakes - you think it's easy to spot fakes because you look on reddit or whatever and readily spot thousands of crappy fakes, but that's an example of selection bias - the fakes you didn't spot were those that were well done.

Photoshop isn't the only way to create fakes either - e.g. one can hire a few actors and create a fake scene, say, supposedly showing injured children in Gaza or something, and take quite "legitimate" photos (of the acted-out scene), "legitimate" in the sense that they need no Photoshop, and distribute those as propaganda too.

Sure, but in a typical court case, the defense and the prosecution will both put forth 'experts', one assuring everyone a video is fake, the other assuring everyone that video is real, and the jury (who have absolutely no clue how to tell which expert is reliable) will have to go off various internal biases.

Investigators, prosecutors, judges - none of these people have the knowledge to distinguish real videos from fake videos, and they also don't have the knowledge to distinguish real experts from bullsh-tters.

I was involved with an actual case where investigators and prosecution decided not to proceed with the case literally because the video footage evidence was from someone who theoretically had the know-how to fake such footage, and they knew it would 'stalemate' on whether the footage was real, as they basically had no forensic capacity to determine the reliability of the footage.

So a lie gets upvoted, but this bit of actually true news get downvoted, just because it's politically inconvenient. Hope the metamoderators are paying close attention.

You just don't like him because he's your political opposition. That's all you need to say, you don't need to make up strings of ad hominem and fake news.

So Trump's $3.1 billion net wealth just landed in his bank account how exactly, the bank made a mistake and transferred someone else's money into his account? He found a huge pile of gold in his yard? I wish I was such a business failure as Trump. Having some bankruptcies means nothing - 80% of business ventures fail.

A "moron" who managed to attain a $3,1 billion net wealth through business ventures, and win a presidential election with odds stacked against him. Yes, clearly he's a complete moron. Fact is you (and most Slashdot readers) don't like him simply because he's the political opposition, why don't you just admit that instead of making up BS and fake-news post hoc rationalizations and excuses for why he is supposedly flawed. Just say, "I don't like him because I support the other political party, he's done nothing really wrong though".

Apologize for putting bread on the table and a roof over their heads? You must be trolling.