Another method of compressing is using a shorthand middle interpreter that takes out vowels that are not necessary for interpretation ( some removal makes it ambiguous) , using Huffman compression, or doing things like possibly training the network on compressed data and passing inputs as compressed data, there are even better middle ground compression methods than Huffman ( spell) algorithms and types of look up table substitutions. I have another method I theorize is far better but can’t yet prove it, two methods actually, that get closer to the entropy limit of compression, financial constraints, there are however other limits to developing a AGI that too are possible to overcome, but should we is the big question.