I doubt google will jump in at this level any time soon. they've typically partnered with a hardware vendor for this kind of stuff, like microsoft. I do know they have custom hardware made for their datacenters though.
Who knows with google, they don't tend to follow a narrow path forward, so they might decide to experiment with SoC development of their own.
It makes more sense to me this large on-chip RAM is L-3 Cache for DRAM controller directly next to it. If I am Apple, I will never store direct finger print data in anywhere. Because wherever you store, people will figure out. A good choice is to apply special imaging hashing function to it and only store hashing value. Not sure this technology exist today.
Looking at the layout, Apple appears to have used 1 DDR channel to feed the CPU and another channel for GPU data. The large SRAM above the GPU appears to be the embedded cache for graphics memory, which is similar to approach used by Intel's IRIS Pro and XBOX One
To store finger print data? You need to use NVM, not SRAM or you have to keep feeding power to the chip, which is not possible
Also for the CPU highlighted by chipworks, it appears that the complex includes 2 memory controllers from layout, so the actual area for the CPU complex (excluding the memory controller) is likely smaller than 17% or ~17 sq mm
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.