The reason I believe it's related to circuits is because:
1) I show in my attached file how my "hierarchy" (as shown in the images)
builds larger features as it reads text.
2) Then I show how, say it reads "my cat ran", then a day later reads "my dog
ran", this will activate the 'cat' node in the hierarchy by indirect paths.
3) I have proof and strong belief and tests with GPT-2 (I go through them) that
nodes retain energy for a while, which leads to much better prediction accuracy.
4) I propose to use reward for prediction.
5) I show how nodes can become less pure, ex. stores dog and cat as 'cotg', and
can works for words too.
And more...
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Artificial General Intelligence List: AGI
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