Yes good read, I think many of us already know all this though. BTW you made it 
into a blog post but really you only said a few things in there that was your 
point.* Only saying this because* the paper I read called foundation models was 
way too big, yes big is good but first of all it uses complex formal language 
which does not make life simple like markov chains, and second it is unfocused 
and can be summarized 100 times smaller.

Yes the multi-model GPT ex. DALL-E is a big improvement, using vision and text 
is a big jump up, we wouldn't need a multi-model if it wasn't so useful! It's 
like training on a dataset about dogs....just dogs....then multi-modal is like 
dogs+cats, or dogs+clothing....so it gives it a wider spectrum on data 
collection....similarly a vison that sees beyond our color spectrum will give 
it "more data" using the "same amount" of train data as well.

Yes, adding motor ability to our world will be another giant "multi-model" 
ability to add to its mix in neuronal mixing. It decides where to collect data 
from in the real world, or the internet, then it learns, and decides again 
where to search now, repeat, it is all about data collection to decide where to 
collect data. Adding motor ability doesn't need a body exactly, it can use 
Google to search specifically on the internet what to read, or what thoughts to 
think about and what to store it thinks up. For motor ability to figure out how 
far a face is by using your hand/etc instead of a distance sensor, yes, this 
collects you data. You can also use the size of the face etc to determine how 
far away it is. Deciding what data to eat/make on its own is a big step up from 
being fed image and text data from us, it allows it to have agency, to learn, 
instead of us making it learn. Using a body to do this is a great way but 
thinking / using Goole / using a machine using its thoughts is also great ways 
that fill that need of a humanoid robot.
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Artificial General Intelligence List: AGI
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