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Been nearly 3 years since I last posted on DevRant, a lot has changed, but users are still usering….
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I'm sorry little unused tuple, I know you want to show who you are but if I let you, nothing will be orthogonal and you know that daddy just can't have that. Hey, at least I didn't disintegrate you like bad Mr.Black does everytime I look away, so heads up alright? :)
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Needed an application that generates data very fast for a networking application i'm writing but I did notice that /dev/urandom and /dev/random are not very consistent in speed.
Still, i needed something fairly random with more consistent speed. Now, I made an application that caches 1000 randoms upfront and use them for calculation. Now I have my own randomization algorithm backed by the uniqueness of the original rand(). For fun I added data in the set like some phone numbers. I can watch ages to the data to find smth in common or interesting combinations of the data.
I did verify with GPT is the algorithm is unique and it's fail. It generated a complete ML script for itself to check it. Very awesome.
You use urandom, i use retoordom. We are not the same.
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mama kiki just went to two sentence horror subreddit and casually smashed those amateurs three times in a row with her writing chops
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Black box. It does seem to put messages with an URL in a certain category though, but also that's not always correct. It's trained on 3000 normal dR messages, and 3000 spam dR messages. 6000 dR messages in total. Many epochs but not good for use yet. The idea that the system could classify without discriminating new users is from the table. That discrimination is needed as a safe margin. Original spam system is a bit simple, but it doesn't do false positive and works great. Still, I want to make smth advanced out of it for the sake of education. Tomorrow I'll have my neural networks book. Probably over two weeks I have some good insights how to improve this all. New hobby :)
(pretrained 3b models are fine for recognizing spam btw. But it costs resource. 8 CPU's 100%. A self trained model pure on spam doesn't and is fast. With a pretrained model you can't do mass classification.)
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