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> My humble opinion; AI is supposed to be the acronym for artificial intelligence, but marketing has usurped it to refer to machine learning, which is nothing m

> My humble opinion; AI is supposed to be the acronym for artificial intelligence, but marketing has usurped it to refer to machine learning, which is nothing more than a neo-language for defining statistical equations in a semi-automated way. Sure. Hardly controversial. > An attempt to dispense with mathematicians to develop models. What...? No. Definitely not. > What amount of energy is necessary for an event to be reflected in a statistic? You have a box of 2x2 meters with balls of data, and a string with a diameter of 1 meter with which to surround the highest concentration of balls possible, and those that remain outside, there they stay. Statistics and lack of precision are concepts that go hand in hand (someones say even it is not an science). I have no idea what this is saying. It sounds like you're shitting on statistics all of a sudden, which is weird, given that you seemed to favor mathematicians in the first part.

drtgh 4y ago
>I have no idea what this is saying. It sounds like you're shitting on statistics all of a sudden, which is weird, given that you seemed to favor mathematicians in the first part. Mathematicians are specialized in problem solving, and as humans, their ability to predict and analyze data makes them more reliable developing models than a statistical equation. They have quite more tools than statistics one. Someway, it is like if using the acronym AI to define statistical algorithms leads to a false sense of greater reliability than such human review, or even that it is not needed a deep human review. ML statistics takes algorithms out of the oven long before mathematicians does, at the expense of a big in accuracy difference. The problem I think is people may take important decisions based in the result of such statistical algorithms without questioning
- spywaregorilla 4y ago
  I don't think most mathematicians have spent a great deal of time analyzing data tbh. Unless you mean statisticians.

drtgh 4y ago

>I have no idea what this is saying. It sounds like you're shitting on statistics all of a sudden, which is weird, given that you seemed to favor mathematicians in the first part. Mathematicians are specialized in problem solving, and as humans, their ability to predict and analyze data makes them more reliable developing models than a statistical equation. They have quite more tools than statistics one. Someway, it is like if using the acronym AI to define statistical algorithms leads to a false sense of greater reliability than such human review, or even that it is not needed a deep human review. ML statistics takes algorithms out of the oven long before mathematicians does, at the expense of a big in accuracy difference. The problem I think is people may take important decisions based in the result of such statistical algorithms without questioning

spywaregorilla 4y ago
I don't think most mathematicians have spent a great deal of time analyzing data tbh. Unless you mean statisticians.