You'll always eventually expand past the limits of whatever storage you're using. It's clearly impossible to build totally unlimited storage with constant access time, and you'll always eventually need larger storage (to disk, to other machines, to other data centres, etc), at the cost of speed.
Take a look at [part two](http://www.ilikebigbits.com/blog/2014/4/28/the-myth-of-ram-p...), where he runs through this in more concrete depth to back his claims up. The theoretical physical limit for accessing N bits of data is O(sqrt(n)), no matter how you do it, just from the speed of light.
It's counter-intuitive, but this really is true in the general case, not only in the regions shown on that graph.
It's a great series for reminding us of that, though, and illustrating it well and actually putting numbers on it.
The ultimate theoretical limit is the berkenstein bound, which implies that the information content of a region is bounded by its area, not its volume. This is where r^2 comes from.
Part two is much better and is based on sound principles. The only complaint there is that it's a bit misleading; if you arrange your memory in a sphere, you get access times as the cube root of N for a very long time before you start running into information-theoretical limits based on the area of the memory region.
http://www.intel.com/content/www/us/en/solid-state-drives/3d...
Huh? Am I taking crazy pills, or is this a horrible analysis? It looks like the behavior is O(whatever it's supposed to be) times a constant multiplier at a few different regions. The OP conveniently cuts off the graph so you can't see it level off.