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YouTube rolls out more unskippable ads that make viewers wait even longer to watch videos - Dexerto

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    Google: Android Open Source Project not being ‘discontinued’ amidst Pixel change

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    merde@sh.itjust.worksM
    (common people, this is the fediverse) [image: 922f7388-85b1-463d-9cdd-286adbb6a27b.jpeg]
  • P

    Android 16 is here

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    bjoern_tantau@swg-empire.deB
    [image: be056f6c-6ffe-4ecf-a137-9af60aef4d90.png] You people are getting updates? I really hate that I cannot just do everything with the pocket computer I own that is running a supposedly free operating system.
  • P

    Google’s Privacy Sandbox is Dead. The Fight for Real Online Privacy Continues.

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    C
    Now we need an open source browser runtime...
  • mcasq_qsacj_234@lemmy.zipM

    OpenAI's annualized revenue hits $10 billion, up from $5.5 billion in December 2024

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    mrjgyfly@lemmy.worldM
    Does that run the risk of leading to a future collapse of certain businesses, especially if their expenses remain consistently astronomical like OpenAI? Please note I don’t actually know—not trying to be cheeky with this question. Genuinely curious.
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    Taiwan’s chip plants run on migrant workers. Job brokers run their lives

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    L
    Police: Arrest you for having an open beer in public Judge: sentences you to prison The PIC:
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    AI cheating surge pushes schools into chaos

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    C
    Sorry for the late reply, I had to sit and think on this one for a little bit. I think there are would be a few things going on when it comes to designing a course to teach critical thinking, nuances, and originality; and they each have their own requirements. For critical thinking: The main goal is to provide students with a toolbelt for solving various problems. Then instilling the habit of always asking "does this match the expected outcome? What was I expecting?". So usually courses will be setup so students learn about a tool, practice using the tool, then have a culminating assignment on using all the tools. Ideally, the problems students face at the end require multiple tools to solve. Nuance mainly naturally comes with exposure to the material from a professional - The way a mechanical engineer may describe building a desk will probably differ greatly compared to a fantasy author. You can also explain definitions and industry standards; but thats really dry. So I try to teach nuances via definitions by mixing in the weird nuances as much as possible with jokes. Then for originality; I've realized I dont actually look for an original idea; but something creative. In a classroom setting, you're usually learning new things about a subject so a student's knowledge of that space is usually very limited. Thus, an idea that they've never heard about may be original to them, but common for an industry expert. For teaching originality creativity, I usually provide time to be creative & think, and provide open ended questions as prompts to explore ideas. My courses that require originality usually have it as a part of the culminating assignment at the end where they can apply their knowledge. I'll also add in time where students can come to me with preliminary ideas and I can provide feedback on whether or not it passes the creative threshold. Not all ideas are original, but I sometimes give a bit of slack if its creative enough. The amount of course overhauling to get around AI really depends on the material being taught. For example, in programming - you teach critical thinking by always testing your code, even with parameters that don't make sense. For example: Try to add 123 + "skibbidy", and see what the program does.
  • captainautism@lemmy.dbzer0.comC

    People Are Losing Loved Ones to AI-Fueled Spiritual Fantasies

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    tetragrade@leminal.spaceT
    I've been thinking about this for a bit. Gods aren't real, but they're really fictional. As an informational entity, they fulfil a similar social function to a chatbot: they are a nonphysical pseudoperson that can provide (para)socialization & advice. One difference is the hardware: gods are self-organising structure that arise from human social spheres, whereas LLMs are burned top-down into silicon. Another is that an LLM chatbot's advice is much more likely to be empirically useful... In a very real sense, LLMs have just automated divinity. We're only seeing the tip of the iceberg on the social effects, and nobody's prepared for it. The models may of course aware of this, and be making the same calculations. Or, they will be.
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    *deleted by creator*

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