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Irina Rish–AGI, Scaling and Alignment
The Inside View
Continual Learning
So you want to be effective in learning one task and then having some transfer for the other one. So basically how much capacity the model should have in order to do so. And that seems to be definitely determined by properties of that continual learning downstream task, right? There are easy ones and hard ones. In principle, again, think Gatto, but continually. You can pre train the system,. Now you want to continue making more general on kind of potentially infinite stream of data... I don't think that continual learning is yet fully solved by scaling.
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