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Cake day: July 18th, 2023

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  • For those that have trouble understanding what is being talked about here. A little background, data is often multiplied to higher dimensions in ai in order to make decisions and determine important information. This article is saying high dimensions and complicated machine learning models should only be used for tasks that converge on a specific point, such as feature selection (selecting the most relevant column or feature in a table of data). This is because as dimensions increase, even though the space increases, the distance between the data points that can be placed in that space decreases, this forces complicated ai models to converge on a specific point or opinion and overfit their answers to what they were trained to do (as opposed to thinking out of the box and coming up with new ideas). The author cautions that using very high dimensions to calculate data leads to overfitting and recommends a managed approach of using a lower dimension to train neural networks/machine learning models





  • Banks being unable to pay off their clients would result in a great depression-like economic crash (think about the movie, it’s a wonderful life at the end). Not to say that this wouldn’t be horrible as it would rebalance the ratio of wealth by basically taking all the money from rich people and destroying it. It would also raise the value of the dollar by increasing its scarcity. It would bankrupt companies as they would not be able to borrow money in order to stay afloat. Basically it would screw over everybody except for people that don’t use banks