Even more proof: The proof that shows Temporarily Energized nodes do affect prediction is not just the fact that nodes recently heard must stay in memory active, but also if you had only a small dataset ex. 0KBs and were shown a prompt "the cat and dog cat saw a cat and the " - the next word is not going to be predicted well, much, but out of the 10 words in that prompt, 3 are "cat", so our probabilities can slap on 0.3 probability to predict "cat" next! This is much more powerful if discover cat=dog by shared context, we can see cat/dog appears 4 times in the prompt, often the past paragraph will talk about grass, leaves, trees etc if is about trees. Because all paragraphs will always contain "the" more than any other words, we ignore common words.
Also, Permanently Active nodes and Semi-Permanent Active nodes have reward on them which makes you talk about question goals you love/desire. So our "GPT-2" would talk about likely ways, to get what it wants. Mental RL. If nodes have Permanant activity which affects predictions, it's more likely that Temporarily Active nodes also affect prediction. ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Tf06e133ecd7df7c9-Mc6cf3748d78b0ab15a82d03c Delivery options: https://agi.topicbox.com/groups/agi/subscription
