Yes an AGI* _in a box_* can attain more "data" by improving its intelligence. 
Say we have a dataset it has in the box "The cat ate food. The dog ate food. 
The cat meows." Now the AGI adds the ability to translate words cat=dog by 
seeing they share some contexts (eat) so maybe they share others too 
(dog>meows). All in the box, it has learnt not only cat=dog by how much amount 
X, but also dogs meow by a probability of X. I know I can generate discoveries 
in my brain in a closed session, if I could update my brain's algorithm, then I 
would be able to take my same dataset (if I had the original still) and would 
be able to as explained above glean more insight form the same dataset. Adding 
more data isn't the only way to be more sure if dog more often barks than dog 
swims or dog meows (the dataset may show dog bark 56 times seen, meow 0 times, 
swims 6 times), translation can help us find out if dog barks more often than 
other futures. Data/ intelligence shows which is more often seen. Simple. Data 
shows patterns (dog barks more than sleeps), and intelligence let's you SEE 
patterns in that data. So I can see patterns, upgrade my brain pattern finding 
mechanisms, then SEE more data suddenly. I can actually store discoveries 
already (generated probably true prediction, dog meows) and use those to find 
further discoveries without upgrading my brain, I can also manually do 
algorithms without upgrading my brain by hand or in mind I can do them I mean.

More data, more speed, are equivalent, you can't get more data better than a 
faster computer over your slow computer. You can do 2 things, 1) eat more data, 
2) do it faster too. The 3rd thing you need is not just data and compute, but 
intelligence that finds patterns in data. Upgrading intelligence gives you way 
more data than adding data can do and same for adding speed. Tests show this 
ex. if you add a>b and then add translation compared to more data/speed.
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Artificial General Intelligence List: AGI
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