On Friday, May 22, 2020, at 4:44 AM, immortal.discoveries wrote:
> And my approach to AGI is not wrong. AGI needs not just more existing 
> data/compute but a smarter discovery Extractor/Generator to create NEW 
> desired data to its held questions (duplicating old data with mutations). The 
> output of AGI is only to either implement plans or update where to collect 
> data from, those silly RL walker robots do this and GPT-2 should if we 
> improve it to do so. It is specializing in where to collect new data from, 
> which question, which source. I don't really need a body for my AGI 
> therefore. Output is just for implementation or data collection 
> specialization updates.
For example, my algorithm I made from scratch, compresses the dataset enwik8 
(100MB) to 21.8MB, which means it predicts pretty ok, and my net predicts 
better the more data it sees, for example if I used the dataset enwik2 (100 
bytes lol) it'd compress it to only ex. 70 bytes. Get it?

SO, with the same dataset enwik8 of 100MB, how can I predict better if I don't 
have more data? Add more data. WHAT!? Yeah. Let me show you. When you find 
discoveries in the enwik8 dataset ex. cat=dog by shared contexts, you can 
recognize longer unseen sentences more robustly, and more! Th world best 
compressor can get enwik8 to 14.8MB. See?
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Artificial General Intelligence List: AGI
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