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Cake day: July 23rd, 2023

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  • It would be more accurate to say that rather than knowing anything at all they have a model of the statistical relationship between a series of tokens and subsequent tokens which words are apt to follow other words and because the training set contains many true things the words produced in response to queries often contain true statements and almost always contain statements that LOOK like true statements.

    Since it has no inherent model of the world to draw on and only such statistical relationships you should check anything important




  • Two things.

    One: You could literally say use Linux Mint in 2010 and in 2025 and be ok. You don’t need to know about the totality of the ecosystem in order to use Linux any more than you must understand the totality automotive tech and every car to pick one and drive. If you pick the something different its also probably good enough.

    Two: If they really are too stupid at some degree of ineptitude they are just going to need to pay someone smarter their money whether that is Apple, another Windows machine, or even a Linux OEM. Installing your own OS on an infinite range of hardware with a range of support is never going to be so easy someone who is entirely tech illiterate can do it and that is ok.





  • We aren’t computers we are people. We are having this discussion about the computer. The computer given a massive corpus of input is about to discern that the following text and responses are statistically likely to follow one another

    foo = bar

    foo != bar you lied to me!

    yes I lied sorry foo = foo

    The computer doesn’t “know” foo it has no model of foo or how it relates to bar. it just knows the statistical likelihood of = bar following the token foo vs other possible token. YOU the user introduced the token lie and foo != bar to it and it discerned that it admitting it was a likely response especially if the text foo = bar is only comparatively weakly related.

    EG it will end up doubling down vs admitting more so when many responses contained similar sequences eg when its better supported by actual people’s thoughts and words. All the smarts and the ability to think, to lie, to have any motivation whatsoever come from the people’s words fed into the model. It isn’t in any way shape or form intelligent. It can’t per se lie, or even hallucinate. It has no thoughts and no intents.


  • You never have 100% of people using a word the same if only because some portion of the population is stupid and illiterate and you have both drift over time and geography. So say at a given time of a billion people 99.995% believe the definition is A and 0.005% believe B. Periodically people correct people in B and some of them shift back to the overwhelming majority and sometimes new folks drift into B.

    It is clearly at that point, 99.995% A, correct to say that the definition of the word is A and anyone who says B is wrong. This doesn’t change if B becomes 10% but it might change if B becomes overwhelmingly dominant in which case it becomes correct. There is constantly small drifts mostly by people simply to stupid to find out what words means. Treating most of these as alternative definitions would be in a word inefficient.

    Drift also isn’t neutral. For instance using lie to mean anything which is wrong actually deprives the language of a common word to even mean that. It impoverishes the language and makes it harder to express ideas. There is every reason to prefer the correct definition that is also overwhelmingly used.

    There are also words which belong to a technical nature which are defined not by usage but a particular discipline. A kidney is a kidney and it would be one if 90% of the dumb people said. Likewise a CPU never referred to the entire tower no matter how many AOL users said so.

    This is a long way of saying that just because definition follows usage we should let functionally illiterate people say what they want and treat it as alternative facts.