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Joined 1 year ago
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Cake day: June 5th, 2023

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  • You may be looking at the wrong things then:

    • While SSDs have been around for a while, they have only been commercially viable (for both home and enterprise use) for maybe 10-15 years.
    • Today, even a 300 dollar desktop 3d printer (especially a resin printer) will beat even the best industrial printers from just a decade ago.
    • For less than 50 bucks per month I can get an internet connection at home that’s 16000 times faster than what I had in 2004. Back then, I had to wait minutes to load a single photo, today I can stream three dozen 4k videos at once and still have bandwidth to spare.
    • The COVID-19 pandemic accelerated vaccine research a lot. We finally got mRNA vaccines to work and are now applying them to other diseases as well.
    • Ten years ago, the idea of fully reusing rockets was laughed at. The first time a first stage was reused was in 2017. Today, most new rocket designs are planned as fully or at least mostly reusable.+
    • First mass market VR headsets came out in 2012. We are are just now at a point where untethered headsets are reaching usable resolution and framerate. New headsets add features like eye tracking, finger tracking, external cameras for augmented reality…

    And so on…










  • No joke here. Large language Models (which people keep calling AI) have no way of checking if what they’re saying is correct. They are essentially just fancy text completion machines that answer the question what word comes next over and over. The result looks like natural language but tends to have logical and factual problems. The screenshot shows an extreme example of this.

    In general, never rely on any information an LLM gives you. It can’t look up external information that wasn’t in its training set. It can’t solve logic problems. It can’t even reliably count. It was made to give you a plausible answer, not a correct one. It’s not a librarian or a teacher, it’s an improv actor who will „yes, and“ everything. LLMs will often rather make up information than admit that they don’t know. As an easy demonstration, ask ChatGPT for a list of restaurants in your home town that offer both vegan and meat-based options. More often than not, it will happily make you a list with plausible names and descriptions but when you google them, none of the restaurants actually exist.