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Joined 2 months ago
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Cake day: December 4th, 2024

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  • I agree with you. You hate them, that’s reasonable. They represent humanity’s failure at cooperation.

    You’re also totally justified to hate those who fetishize them.

    You are wrong about them being designed only to kill, though. The point of them is to wield deadly force, and they are designed to send a high-speed projectile in order to achieve that goal, of deadly force. It’s alittle semantic, but an important distinction imo, because the point of wielding deadly force is to make opponents compliant even if you never use it.

    Swords, spears, bows, atlatls, and pretty much every weapon of war was the exact same way. A key difference between them and the firearm, though, is that the firearm takes little to no training in comparison to the others, which take considerable amounts more.

    Everything else, we’re in agreement about. I think you hold a hate for violence as well, based on your stance. That is also healthy, but I hope you also see violence for the liberating force that it is, able to protect those that are targeted.

    We are on the brink of having the US become a full-blown fascist state - as opposed to the fascistic nation it’s always been. Should that happen, I fear the only way back is through violence, and I’d much prefer having a rifle in hand to the alternative of charging down gunfire armed with a lesser weapon, as the Egyptians had to during their revolution in 2011.









  • I think we should avoid simplifying it to VLMs, LMs, Medical AI and AI for disabled people.

    For instance, most automatic text capture ais (optical Character Recognition, or OCR) are powered by the same machine learning algorithms. Many of the finer-capability robot systems also utilize machine learning (Boston Dynamics utilizes machine learning for instance). There’s also the ability to ID objects within footage, as well as spot faces and referencing it with a large database in order to find the person with said face.

    All these are Machine Learning AI systems.

    I think it would also be prudent to cease using the term ‘AI’ when what we actually are discussing is machine learning, which is a much finer subset. Simply saying ‘AI’ diminishes the term’s actual broader meaning and removes the deeper nuance the conversation deserves.

    Here are some terms to use instead

    • Machine Learning = AI systems which increase their capability through automated iterative refinement.
    • Evolutionary Learning = a type of machine learning where many instances of randomly changed AI models (called a ‘generation’) are run simultaneously, and the most effective is/are used as a baseline for the next ‘generation’
    • Neural Network = a type of machine learning system which utilizes very simple nodes called ‘neurons’ for processing. These are often used for image processing, LMs, and OCR.
    • Convolution Neural Network (CNN) = a Neural network which has an architecture of neuron ‘fliters’ layered over each other for powerful data processing capabilities.

    This is not exhaustive but hopefully will help in talking about this topic in a more definite and nuanced fashion. Here is also a document related the different types of neural networks