I don't think it's a long-term view due to the numbers involved. For example, everyday developers might have access to 64-bit laptop computer with 4 cores @ 4 ghz and 16 GB of RAM (literally millions of people use such a machine, zero exaggeration).
When working on their own desktops, AI researches might use an 6-core or 8-core desktop with 64 GB of RAM or, rarely, 128 GB of RAM.
Access to 2-32 terabytes of RAM are not in the realm of what most AI researchers get to run their algorithms on on a daily basis.
Google's AlphaGo ran on[1] 1202 CPU's, 176 GPU's, and I didn't immediately find the amount of memory but on the order of magnitude you would think it is from 1 terabyte (if it's 1 GB of RAM per CPU) up to (reasonably) about 128 terabytes, with my guess being 4 TB-16 TB. However I didn't find this figure.
This is hardware that exists today, but AI researchers would have to wait a few years to have normal everyday access to this kind of thing in their normal everyday devices. Right now only datacenters match the processing ability of the human mind. Although they certainly exist in one cluster, they're far from the type of thing that is in everyone's hands yet.
On the other hand, once it is set up these clusters can be far faster than the human brain, which runs at really slow analog speeds. (Look up the propagation speed of neural signals.) The human brain is just slightly ahead of the curve right now without any specialized hardware.
There are 7 billion extant examples of intelligent human brains. There are probably less than 10,000 clusters AI researchers can play around with for months, which have 16-128 TB of RAM and aren't used for anything more important, just whatever they feel like running on it. (Versus easily more than 15 million computers with just 16 GB of RAM, though that may not be enough.)
I don't think this is very far-off.
[1] http://uk.businessinsider.com/heres-how-much-computing-power...