• 3 hours

    Its not all about the jobs. Its the water, environment, the data centers also. Communities left with little power and water, infrasound pollution, etc.

    It’s also the shit ass chat bots and frustrations trying to reach a human when I need support.

  • For those who haven’t seen the video, here’s a direct link of the commencement speech that was buried in a linked Twitter post in the article.

    And like… ho-leee fuck, that is an absolute doozy:

    • read the room bro
    • such transparently facile and smarmy rhetoric
    • really obviously hijacking other narratives
    • strongly status quo
    • completely ignores that he himself is a robber baron who stands to benefit immensely from ML chatbots
    • talks about highly targeted ML applications, which are good and groundbreaking in a lot of ways, but then proceeds to give colloquial examples of just using LLMs
    • exhaustingly condescending
    • i can go on but will stop there for now
  • Tell me about it when they stop using it so much.

    • 4 hours

      they will stop using it the second it’s no longer free… and it cannot be free forever because the bubble has to pop at some point

      sad that it will take this long but here we are

      • 2 hours

        I imagine the low level form of each model being free indefinitely, possibly ad supported. It’s already probably becoming the most consistent “we’re pretty sure this is from a human” training data they have.

    • I am quite surprised that in the school I am teaching in, student have a much more negative attitude towards genAI than professors, especially in the context of education.

      30% of the professor feel that genAI can play a role in education, whereas only 11% of the student holds the same view. That seems to reflect quite well in my homework, only a very small minority (10%) uses some extend of genAI in writing open-ended writing homeworks.

  • 12 hours

    IDK how many jobs AI is actually taking?

    With higher interest rates there’s less venture capital around to pour into the data centre build out, so tech companies are cutting back on their wage bills to channel money into building data centres.

    AI might give some jobs a productivity boost, but it’s more like: 90 people can do the work 100 people did before. It’s not like, oh we don’t need these 10,000 employees in mumbai anymore because AI is developing that product now.

    • IDK how many jobs AI is actually taking?

      Honestly, I think the layoffs are just cover to shore up the stock price before quarter-end and keep the gravy train rolling. This is a cycle that isn’t repeatable permanently, because eventually you have to actually produce something other than a talking parrot that gets a lot of shit wrong.

    • AI companies are switching to token based billing. Money is running out and heavy AI users are going to have to pay closer to the real price. People suddenly having to pay 10 times as much. You can just as well hire an intern for that money.

      • 5 hours

        So you’re saying AI is not replacing jobs at all?

        Inference providers have been charging per token forever.

        • 4 hours

          So you’re saying AI is not replacing jobs at all?

          Honestly, there is little evidence that it actually has (successfully).

          Of course, anything at a world wide scale will be true at some percentage; however, I doubt AI has actually replaced the labour of many. Even Meta gave up on pretending this and they are now firing people just to free money to pour on AI, not because AI is actually replacing those people

    • I think we’ll also see increased burnout as employees are expected to produce more with less.

      • yes, it’s when you tell boss, “I can’t do that in 3 hours, it’ll take two weeks”, and probably still have some unknown aspects of quality, that we might not want to sign off on. Maybe we can rush it in 1 week, if you’re ok with want want maybe’ 20% unverified.

        Boss fucks off to coprolite - gets it “done” in 3 hours. Gives it to someone else to QR. They comes back to me for advice on turd polishing (apparently that’s my SME). So I then waste time helping that person tactfully create a quality report that says it’s seriously defective and will take weeks to rectify to get it up to an acceptable standard - because it tells us nothing about how it got to it’s erroneous output.

        Now, we’ve wasted about a day between us, on dog-shite - and we’ve not learned anything useful.

        I don’t know what a “gen Z” is though, but whoever they are they should stand up to shite bosses.

      • “Here’s an expensive chatbot that lies exactly 73% of the time. Now stop reviewing and testing code.”

  • 11 hours

    www.businessinsider.com

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

    In 2023, Business Insider shifted its organizational model, adding multiple artificial intelligence (AI) products in 2024, and reducing its staff by nearly 40% between April 2023 and May 2025.[7]

    I suspect that the author is more likely to be impacted than most of the people involved.

    Journalism’s been having a rough time for some decades from technological change, though that predates AI as we know it today.

    First — in the US, not sure about everywhere else — there was a shift away from local news towards focusing on national news. You don’t need as many journalists to cover a limited number of national stories. IIRC, that started before widespread Internet adoption, but the Internet accelerated it a lot:

    https://theharvardpoliticalreview.com/local-news-democracy-risk/

    The appearance of news deserts across counties and communities in the U.S. has been a widespread phenomenon in recent years. But why? In an interview with the HPR, Jeremy Meserve, the Staff Producer and Archivist for the Belmont Media Center, pointed to the over-corporatization of media consumption as a cause of the decline in quantity and quality of local journalism.

    The rise of social media platforms like Facebook, Twitter, and Instagram has fundamentally changed how people consume media. Social media platforms like these have spelled the end for many local newspapers as people have shifted their media consumption priorities to more convenient options. Meserve believes that part of the downfall of local newspapers had to do with the old business model, where many local papers were free. So when social media emerged, people stopped reading, as social media platforms provided faster and equally free media. As a result of this, newspapers lost their audience and their benefactors which led to that old business model being unsustainable.

    Second, Google basically took over the ad market that a substantial amount of journalism relied on for revenue. Sure, some money came from subscriptions, but a lot of magazines and newspapers relied on their ability to put ads in front of a broad demographic’s eyeballs. You don’t want to pay a newspaper for relatively untargeted ads when you can pay Google, which can hit exactly the demographic that you want to advertise to.

    Third, my understanding is that some stuff — like “business news” articles, where one just wants a summary of earnings reports or someone talking about the general movement of stocks and a vaguely-plausible explanation attached — became largely automatically generated some time back. This predates the LLM boom as well:

    searches for an example

    https://www.ap.org/the-definitive-source/announcements/automated-earnings-stories-multiply/

    The Associated Press, working with Automated Insights and Zacks Investment Research, is now automatically generating more than 3,000 stories about U.S. corporate earnings each quarter, a tenfold increase over what AP reporters and editors created previously. Here, Assistant Business Editor Philana Patterson, who has been overseeing the rollout of this process in the newsroom, gives an update on AP’s automation efforts that began last summer.

    That might sound like something happening today, but…that’s a story from June 2015, over a decade ago.