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Joined 1 year ago
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Cake day: September 27th, 2023

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  • You don’t need the “literally”.

    And, while I’m at it, others may be revisionists, you lack nuance.

    At a surface level, you’re correct the Android re-design in 2008 was primarily because of the arrival of the iPhone in '07. The reason for the re-design was the inclusion of a touch-screen in Apple’s hardware spec. Apple was not the first company to introduce mobile computing handsets with touch screens; that honor goes to IBM.

    Android was founded in 2003, and was looking to come into the digital camera market initially, before their acquisition by Google. Then they were looking to compete against Blackberry and Windows phones. UI design experiences have been playing off each other since the beginning.

    Apple doesn’t solely define the market, and people who work for them wouldn’t assert that. They define their niche, which is the smarter business proposition.







  • You’re down-voted quite a bit, but I agree, and I’ll die on this hill with you.

    I noticed the decline in quality and usefulness of his videos for me, personally. I was very disappointed at the path he took when Gamers Nexus called him out for shitty testing.

    In the grand scheme of things, there’re way worse people and companies in the world, and I don’t think he should be cancelled after that fiasco.

    The vitriol against LTT is beyond ridiculous, and from what I’ve seen, there’s no substance in the alleged sexual harassment. I’m open to any links showing otherwise, but I’ve seen precisely zilch that’s concrete.

    He’s had some horrible takes and I don’t watch a lot of his videos anymore. But he and his employees are not the SS.




  • To an extent.

    My professional ANN experience is with computer vision and object detection. A bit with image and sound GANs too.

    LLMs that I’ve spent time training and experimenting with (and I argue GANs as a class of ANNs, in general) tend to “hallucinate” or “dream harder” after several tens of queries within the same instance.

    But one can improve output “fidelity” based on constraint parameters on the user and inference self-check algorithms.

    Addendum:

    • ANN = artificial neural network (a class of algorithms in machine learning whose architecture resembles a mesh of intercommunicative neuron cells in nervous tissue)
    • GAN = generative adversarial network (a categorical subset of ANNs
    • LLM = large language model (a categorical subset of GANs)