The author is stuck on building a better horse.

Not to beat this analogy dead, but the reason Alan Kay et al. are so quick to discuss alternative computing methods should be quite obvious to anyone who doesn't limit their worldview to concepts that humans are already using.

Right now most processors are ridiculously general. They take a handful (ok, a couple thousand or so) instructions and they do their best to parallelize the instructions both on a single loop (core) and multiple cores. These instructions are of the "add, multiple, load, store" variety, with a few additional instructions for machine learning[1] and whatever HP wants[2].

This is it. This is the state of computing. How do bees work? Why can spiders hunt? When did crows start using tools? What makes us different than bonobos? How are all of these creatures so capable, yet so energy efficient?

We are taking a single solution, RISC/CISC architecture, and brute-forcing the hell out of it. Rather than build adaptive or purpose-built hardware, we're stuck on this concept of compile everything to x86/ARM and shrink the transistors (or try and offload parallel number crunching to the GPU).

What the author fails to realize is that computers are just fancy looping mechanisms. We use "HLLs" to compile abstract loops into instructions that run on general purpose machines. That's it.

The "apparently credible" people see the world in this light. They understand that the solution we've chosen is subpar, but the physics will make it work for some time.

A few other commenters have mentioned FPGAs. I'm not here to pitch a future on FPGAs; the die is still flat, the gates can only be reprogrammed so many times and they're generally "expensive."

I will say that we need better tools. FPGAs are a good start. Intel knows this[3]. Microsoft knows this[4].

With an FPGA you can dynamically program the exact logic a given operation will need. Whether it's real-time signal analysis, AI-built logic, or memcached, your logic will run exactly as specified.

Using purpose-built logic to run functions "natively" will drastically improve the efficiency of computation; both in time and energy.

It's really hard to build a horse that will fly to the moon. It's a lot easier to build a spaceship that can carry a horse to the moon.

[1]http://lemire.me/blog/2016/10/14/intel-will-add-deep-learnin...

[2]https://en.wikipedia.org/wiki/IA-64

[3]https://www.bloomberg.com/news/articles/2015-06-01/intel-buy...

[4]https://www.wired.com/2016/09/microsoft-bets-future-chip-rep...