It’s fine guys, the FBI has already caught all of the human traffickers and terrorists so going after people for photoshopping their image in the wrong way is the next priority.

On this topic, there is apparently only salt

literally never once put any genuine information in there. Who does? Why would anyone?

(That’s the joke) - 1mo ago

I was getting depressed that nobody would get the joke, what has the Internet become…

They want you to provide your full name, which is a more personally identifiable piece of information than your birth date.

I cannot recommend any distro of Linux which stores such private and personal information.

Just don’t go to Debian

next day edit: Some of you have never been trolled before, and it shows.

You see, the real_name field has been part of the GECOS field since the 70s. Anyone who has any actual experience with Linux knows this.

There is some bit of drama about adding birth_date to systemd. The person that I’m responding to appears to subscribe to this drama due to the fact that they’re recommending distros who either don’t use systemd or, even more stupid, ‘fork’ the project to remove that field.

So, I made a meme from the point of view of one of these people, expressing outrage that Debian is asking for a user’s Real Name… when only a newbie doesn’t know these things.

And lest you think I’m doing the “I was caught being dumb so I’m claiming to be trolling” here’s a comment of mine from over a month ago making this exact same joke, but more explicitly.

Congrats to the 3 people who got the joke.

I didn’t know Snapmaker had the same kind of mentality until now thanks to that move.

Smart move by Snapmaker, for the price of one hardware unit they get a lot of exposure to exactly the kind of people that they’re marketing towards.

I love that Rossman is picking a fight here. He has the resources to fight this to a trial and that alone is probably enough to make Bambu Labs back down.

They don’t have a case, the project is re-using their AGPL code. This is entirely a SLAPP threat, it only works if the target isn’t rich enough to defend themselves.

You’re so short sighted to not see the advantage of re-writing the Obama Nuclear Deal.

For the low, low price of many billions of dollars, a few tens of American lives, global stability, our military readiness, half of our stand-off munitions, our NATO allies and loss of US influence in the entire world we will have acquired an open* Strait of Hormuz, a ceasefire**, some pretty decent Lego propaganda, the one-time free passage of 8 tankers of oil and a doubling of gas prices to support our struggling fossil fuel industry.

*for China only

**not counting air strikes, anti-ship missiles, mines or fast boat attacks.

I also wrote text.

If you’re just going to cherry pick a single point and dismiss everything else then we’re done here.

We can only hope AI discovers necromancy before we all fall to techno-fascism.

Here is the paper: https://ai-project-website.github.io/AI-assistance-reduces-persistence/

No the test is not training, that’s a weird thing to claim.

The control group solved 12 questions manually and then the 3 test questions manually. The AI grouped solved 0 questions manually and the 3 test questions manually. One group had 12 more manual math tasks to prepare for the manual math test the other group had 0 and also had to context switch.

The AI-assisted group was dealt a context switch, which results in a pretty severe performance loss. A context switch causes performance loss of around 40% according to this paper, which was peer-reviewed and published and is also the most cited paper on the topic, in the APA: https://www.apa.org/pubs/journals/releases/xhp274763.pdf

The AI-assisted group also did not have 12 questions to adjust to the new context, like the control group did. If they wanted to wipe out the context switching performance loss they should have kept asking questions to see if, after 12 questions, the AI-assisted group had a similar performance.

The switch is what is tested, and you disregard that 2 other tests have shown similar results.

No, they did not switch what was tested. Here is an image from the actual paper.

They were given 12 tasks with one group using AI and another doing mental math and then 3 tasks doing mental math. One group had 12 more tasks worth of preparation than the other.

Nothing, not even the article in theOP, says that they did math and swapped to reading to test.

They did 3 different experiments, in each experiment they gave 12 tasks and then disabled the AI for one group and gave 3 more tasks as a test. At no point did they ask 12 math questions and then finish with 3 reading questions or vice versa. They did 2 experiments using math tasks and 1 experiment using reading comprehension tasks.

So one group had 15 math tasks and one group had 12 ‘how to ask an AI’ tasks and then 3 math questions.

They also did not control for context switching losses, which is a well documented (see the APA paper) effect. The proper control would be to continue asking questions so the AI group also had 12 math tasks before the test.

There’s a reason that this is published on arXiv and not in a peer-reviewed journal. Designing a poor quality experiment doesn’t tell you anything useful even if you do multiple different versions of the same experiment.

This paper demonstrates a lack of a proper control group, specifically a failure to control for context switching performance loss.

I’d like to see a study on that, I see it mentioned so much it’s almost achieved meme status.

It could very well be a Baader–(👀)Meinhof phenomenon.

AI being released was basically an apocalypse for people who use EM dash.

Here’s the most cited, human created (2001), paper on the topic of context switching performance loss: https://www.apa.org/pubs/journals/releases/xhp274763.pdf

It’s an HTC device, Google has just consumed the entire tech sector.

This paper shows that a person who has performed a task 12 times performs better than a person who has never performed the same task.

They also do not properly control for performance loss due to context switching which is a well known contributor to performance loss.

It’s a paper on arXiv, it hasn’t been peer reviewed or published.

To add to this, we already know that context switching causes a loss in performance.

A person who’s thinking about how to solve a problem one way and then has to suddenly think about solving it in another way will perform worse.

https://medium.com/@codewithmunyao/the-hidden-cost-of-context-switching-why-your-most-productive-hours-are-disappearing-43c5b501de19

The Neuroscience Behind the Pain

Context switching isn’t just annoying — it’s neurologically expensive. When you shift from debugging a race condition to answering emails, your brain doesn’t simply “change tabs.” It goes through a complex process:

-Memory consolidation: Storing your current mental model

-Attention disengagement: Breaking focus from the current task

-Cognitive reloading: Building a new mental model for the next task

-Re-engagement: Getting back into flow

Research from Carnegie Mellon shows that even brief interruptions can increase task completion time by up to 23%. For complex cognitive work like programming, this cost multiplies dramatically.

Here’s another article from CMU discussing the same thing: https://www.sei.cmu.edu/blog/addressing-the-detrimental-effects-of-context-switching-with-devops/

What this study shows is that a person who is faced with an unexpected context switch performs worse on a task than a user who has spent the last 12 questions performing the task the same way.

This exact problem would happen if you replaced AI with a calculator, or made a person swap from using paper to doing mental math. The problem here is context switching, not AI.

The way to ensure that the problem is AI and not the context switch, would be to continue the quest and see if the first group reverts back to baseline after 12 questions. 12 questions is how long the control group had to become acclimated to the task before their last context swap at the start of the test.

Also, of note, this is a paper on arXiv it is not published so it has not gone through a peer-review process which would certainly catch the failure to set a proper control group.

he thought it would be “too difficult”

A lot of people’s reluctance to focus on privacy is because they don’t understand the scale of the problem or the downstream consequences.

That isn’t too surprising, it’s an incredibly complex topic and the companies that benefit from our collective ignorance go out of their way to gaslight everyone.

They don’t call it a ‘We’re stealing all of you data’ disclosure they call it a ‘Privacy Notice’. They announce that they’ve added the option to opt-out (a Dark Pattern) of some new privacy destroying feature instead of announcing the privacy destroying feature. Bit by bit, people are bombarded with a bunch of messaging that makes them think that companies are looking to protect your privacy.

“Your privacy is valuable to us” is probably the most honest thing they say, it is incredibly valuable… many hundreds of billions of dollars worth of value.

every commercial modern IP surveillance system can (and does) share evidence digitally

Minor quibble.

Self-host Frigate (https://frigate.video/), buy generic Power over Ethernet security cameras (Amcrest has good ones in my experience) and keep everything wired and isolated from your regular LAN. Then you actually control your own security system.

Buy a Nest camera from Amazon and it’ll be easier. They’ll do all of the work for you while helping themselves to video of your property and family for them to do with as they please.