AI Explorables: big ideas in machine learning, simply explained

Re:AI Explorables: big ideas in machine learning, simply exp... by azinman2 on Tuesday July 06, 2021 @02:11AM (#27744737)

Garbage in means you have too much noise over signal coming in. You might be able to call current society garbage if you wish, but from an ML perspective it’s not accurate to say arbitrary input is garbage if it indeed is high quality data that reflects society as it is, or if you only have data on a certain set of classes but what you have is noiseless.

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Re:AI Explorables: big ideas in machine learning, simply exp... by nerdponx on Tuesday July 06, 2021 @03:19AM (#27745129)

If you are studying criminality and using conviction record data, I think it's fair to say that the biased introduced by biased policing, biased laws, etc. is a form of "garbage-ness" in the data, in that it might not reflect the reality that you were trying to model.

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Re:AI Explorables: big ideas in machine learning, simply exp... by Graffur on Tuesday July 06, 2021 @04:27AM (#27745533)

Biased data is garbage if your aim is to have unbiased results...

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