morrowind

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[–] morrowind@lemmy.ml 1 points 1 day ago

The Henry Cahill solution might be among the best things I've seen on lemmy.

Gotta account for preferences though, I know women swoon over him but they night apply to men, speaking as one of them.

[–] morrowind@lemmy.ml 69 points 6 days ago (8 children)

In a weird sort of way it does. Consider all of the following

  1. big companies are often incompetent and inefficient in a lot of ways
  2. The mozilla foundation has confirmed the security issues that Anthropic found were real
  3. Generally over the past few years, anthropic has some of the best, most reliable models
  4. Claude code has been kinda bad for a while
  5. Claude code has been mainly bot-written for a while as well. This can lead to functional, decent code that's still terrible in many ways as seen from the leak. Also it's entirely possible that bots are worse at detecting issues in bot written code. You could argue if they were good at it, they would be less likely to write those security issues in the first place?
  6. Anthropic could have very skilled ml engineers but mediocre software developers
[–] morrowind@lemmy.ml 8 points 1 week ago

Oh sweet. Might try it again.

I've yet to even get the lemmy frontend successfully running for development. Maybe piefed will be easier

[–] morrowind@lemmy.ml 14 points 2 weeks ago (1 children)

Hajj? That was my guess too. The timing lines up

[–] morrowind@lemmy.ml 4 points 2 weeks ago

No one's going to attend a protest every weekend. Better, less frequent showings are probably better.

[–] morrowind@lemmy.ml 15 points 3 weeks ago (3 children)

No, it's a different format underneath.

Occasionally it'll work, cause an app will use a library that supports webp but forget to add it to the file picker (or deliberately don't want it) but generally no.

[–] morrowind@lemmy.ml 2 points 3 weeks ago (1 children)

Grades and even worse, extra curriculars.

The effect is stronger by class than race if I remember

[–] morrowind@lemmy.ml 3 points 3 weeks ago

You might be inadvertently making the problem worse. Your brain is generally pretty good at ignoring things after some exposure, but you're not giving it exposure and forcing yourself to think about it by having to position your finger

[–] morrowind@lemmy.ml 7 points 3 weeks ago (3 children)

It was a decent browser. And an independent engine, which everyone here seems rabid for

[–] morrowind@lemmy.ml 10 points 3 weeks ago

I know gaslight has lost all meaning but this might be worst use I've seen yet

[–] morrowind@lemmy.ml 27 points 3 weeks ago (1 children)

Most based take I've seen on LinkedIn. And I mean the original definition of based.

[–] morrowind@lemmy.ml 3 points 1 month ago

He runs a satire cringe YouTube channel so yes

 

I'm not the author, just sharing.

 

The messaging for climate change, often wrapped as a joke or not said directly to Gen Z is "this is your problem, [the consequences will come in your adulthood]" or "this is for your generation to solve".

B.S of course, By the time Gen-Z gets any power it'll be too late.

With AI I'm frequently seeing people, often fairly smart, good people saying things like "oh yeah AI is totally going to destroy X industry. I mean I'll be retired, so I'll be fine, but you'll have to figure something out".

My father says this frequently. My CTO at work who's been heavily pushing AI was asked "aren't you afraid it'll make you dumber?" responded "of course! But I'm retiring soon anyway, who cares". A lot of AI "leaders" often imply the same thing.

Often dressed up as a joke. I laugh along. It's never been funny and continues to get less funny.

Usually from older people, millennials are still young enough that ill effects will hit them before retirement (assuming you chaps manage to retire at all).

 

For context, Core devices is the new company by the founder of Pebble to make pebbles again. Rebble is the org that kept pebbles running when Pebble disappeared

 

cross-posted from: https://lemmy.ml/post/30013197

Significance

As AI tools become increasingly prevalent in workplaces, understanding the social dynamics of AI adoption is crucial. Through four experiments with over 4,400 participants, we reveal a social penalty for AI use: Individuals who use AI tools face negative judgments about their competence and motivation from others. These judgments manifest as both anticipated and actual social penalties, creating a paradox where productivity-enhancing AI tools can simultaneously improve performance and damage one’s professional reputation. Our findings identify a potential barrier to AI adoption and highlight how social perceptions may reduce the acceptance of helpful technologies in the workplace.

Abstract

Despite the rapid proliferation of AI tools, we know little about how people who use them are perceived by others. Drawing on theories of attribution and impression management, we propose that people believe they will be evaluated negatively by others for using AI tools and that this belief is justified. We examine these predictions in four preregistered experiments (N = 4,439) and find that people who use AI at work anticipate and receive negative evaluations regarding their competence and motivation. Further, we find evidence that these social evaluations affect assessments of job candidates. Our findings reveal a dilemma for people considering adopting AI tools: Although AI can enhance productivity, its use carries social costs.

 

cross-posted from: https://lemmy.ml/post/30013147

Significance

As AI tools become increasingly prevalent in workplaces, understanding the social dynamics of AI adoption is crucial. Through four experiments with over 4,400 participants, we reveal a social penalty for AI use: Individuals who use AI tools face negative judgments about their competence and motivation from others. These judgments manifest as both anticipated and actual social penalties, creating a paradox where productivity-enhancing AI tools can simultaneously improve performance and damage one’s professional reputation. Our findings identify a potential barrier to AI adoption and highlight how social perceptions may reduce the acceptance of helpful technologies in the workplace.

Abstract

Despite the rapid proliferation of AI tools, we know little about how people who use them are perceived by others. Drawing on theories of attribution and impression management, we propose that people believe they will be evaluated negatively by others for using AI tools and that this belief is justified. We examine these predictions in four preregistered experiments (N = 4,439) and find that people who use AI at work anticipate and receive negative evaluations regarding their competence and motivation. Further, we find evidence that these social evaluations affect assessments of job candidates. Our findings reveal a dilemma for people considering adopting AI tools: Although AI can enhance productivity, its use carries social costs.

 

Significance

As AI tools become increasingly prevalent in workplaces, understanding the social dynamics of AI adoption is crucial. Through four experiments with over 4,400 participants, we reveal a social penalty for AI use: Individuals who use AI tools face negative judgments about their competence and motivation from others. These judgments manifest as both anticipated and actual social penalties, creating a paradox where productivity-enhancing AI tools can simultaneously improve performance and damage one’s professional reputation. Our findings identify a potential barrier to AI adoption and highlight how social perceptions may reduce the acceptance of helpful technologies in the workplace.

Abstract

Despite the rapid proliferation of AI tools, we know little about how people who use them are perceived by others. Drawing on theories of attribution and impression management, we propose that people believe they will be evaluated negatively by others for using AI tools and that this belief is justified. We examine these predictions in four preregistered experiments (N = 4,439) and find that people who use AI at work anticipate and receive negative evaluations regarding their competence and motivation. Further, we find evidence that these social evaluations affect assessments of job candidates. Our findings reveal a dilemma for people considering adopting AI tools: Although AI can enhance productivity, its use carries social costs.

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