Which words were "uncommon confabulated"?  To the best of my knowledge I
used words that, if put into Google along with appropriate constraining
words like "machine learning", will produce the associated literature.

On Wed, Aug 26, 2020 at 5:25 PM <[email protected]> wrote:

> While you used all sorts of uncommon confabulated words, I believe I
> already "got" all of that. I believe there are specifics to the AGI
> tree/net that yous know that I don't know, and that's what I want from you.
> Q-learning may as well, I wish someone could explain it in few, concise
> words clearly. As far as I'm aware, external reward like food, genital,
> body acceleration, etc, reward senses when felt, just like frequency does
> in PPM (text prediction). And internal reward is just a static force for
> predicting certain domains over otherslike in Blender/ PPLM, but is also
> learnable if used ex. word2vec/seq2vec. As for the secret details in
> Q_learning, first of all I think it's for external body RL if I recall, not
> NLP? Now, external RL is very limited, it's just rewarding actions close in
> time to the trigger, and updates a hierarchy of motor programs, while
> external 'lab discovery tests' involve collecting specif data, not reward,
> and so is more of a sensory thing than motor thing. The AGI is searching
> for data/ patterns, the learnt motor hierarchy is only to help it do so, it
> controls nothing...but what you want it to, ignoring the few reflexes
> installed in us.
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