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General Project Discussion / Re: Releasing full AGI/evolution research
« Last post by LOCKSUIT on March 06, 2021, 09:24:14 pm »I'm not sure of any libraries needed, my code should run as is in python3. I use PyCharm IDE.
Yes it works on other files like BOOK at least. Wikipedia data is quite diverse and is natural human/ world data. It's not overfitting, enwik8 is not a solid pattern like aaaaaaa but also not total random like abcd1234, the more I can Lossly Compress enwik8 or 1MB of it the more this shows I am finding patterns in it. As you can see my code is small, if my code was 1MB I could be perhaps storing the full 1MB in the code and cheating. Yes my program is "AI" - it isn't something like Burrows Wheeler Transform or Run Length Compression, a neural network is a predictor and all predictors use patterns to predict. Yes python is slower by x10, my program would take 10 hours for 100MB training. Shelwien's (is in C++), which I mostly followed, is ~10 faster.
Not there yet but hopefully I get farther towards AGI.
Yes it works on other files like BOOK at least. Wikipedia data is quite diverse and is natural human/ world data. It's not overfitting, enwik8 is not a solid pattern like aaaaaaa but also not total random like abcd1234, the more I can Lossly Compress enwik8 or 1MB of it the more this shows I am finding patterns in it. As you can see my code is small, if my code was 1MB I could be perhaps storing the full 1MB in the code and cheating. Yes my program is "AI" - it isn't something like Burrows Wheeler Transform or Run Length Compression, a neural network is a predictor and all predictors use patterns to predict. Yes python is slower by x10, my program would take 10 hours for 100MB training. Shelwien's (is in C++), which I mostly followed, is ~10 faster.
Not there yet but hopefully I get farther towards AGI.