Make sure to read my above post.

Really? You don't see how Blender (or my improvement above) is closer to AGI 
than GPT-2 is? Or that GPT-2 is close-ish to AGI? Do you have something better? 
Does it predict text/images better? What does OpenCog AI do if it can't compare 
to OpenAI's showcase!? Either you have better results showing it can think more 
like AGI than my vision of Blender or you haven't coded it yet and can explain 
it instead, but as far as I can see, OpenCog AI isn't as "AGI" as Blender or my 
vision of Blender. Explain OpenCog. Why doesn't it just recognize a 
sentence/image patch and predict the next item? What does it do? I can't even 
find out. AGI is just recognition, prediction, attention, it has to 
create/predict the future thoughts/discoveries it desires. Prediction is 90% of 
AGI and all new AGI mechanisms simply improve it or allow it to do interesting 
manipulation on data ex. logic AND OR or when you edit a Paper or delete things 
or clone paragraphs, or count how many letters in a sentence or how many times 
's' appears in a sentence, etc etc. These things are AGI like 'behavior', but 
still connected to Prediction and can be showcased.

GPT-2 is obviously very close to the AGI we're looking for. And Blender is even 
better because 1) it knows how to finish its replies (because of Byte Pair 
Encoding), 2) is trained not just on wikipedia but actual human-like chat log 
conversations, 3) is forced to talk about/stick to some domain/question and not 
just some nutty prompt like unicorns (which changes over time too) which is not 
about cancer or immortality (and my improvement is to set it to force it to 
talk about Survival, AND evolve it as explained how to let it find the right 
sub domains of sub domains as it thinks. This let's it much better answer the 
installed question/goal). There's no better than this. It's closer to natural 
AGI than all others.
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Artificial General Intelligence List: AGI
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