The question then becomes: How weak can the assumptions be and still allow all relevant knowledge to be derived from finite data? Notice the word relevant: we’re only interested in knowledge about our world, not about worlds that don’t exist. So inventing a universal learner boils down to discovering the deepest regularities in our universe, those that all phenomena share, and then figuring out a computationally efficient way to combine them with data.
