700 karma · joined August 2, 2016
My suggestion was not that an entity use crowdsourced home computers, rather that it would be more efficient for a company to setup their own hardware and rent CPU cycles that way. The big difference is that Suchflex is limited to using hardware that consumers regularly purchase, whereas a company could use significantly more energy efficient setups and negotiate a better electricity rate. This is essentially what AWS already offers. Additionally, if you already have to transmit everything remotely, there's no need to stay in the US. Iceland offers rates around 4.3 cents. I chose the 980 TI for my example because it's about as close to perfect as you can find for this scenario while sticking with consumer grade hardware, average setups would be much worse.
My general point is that I don't think Suchflex's model is viable unless, as pliny mentioned, you have access to free electricity through some less-than-legal means (or you live in Iceland).
That's the issue though, this wouldn't be similar to your typical usage. Instead, if they're using your GPU to train neural networks, it'll be running close to or at full capacity.
I realize that you rounded the costs up, but lets just look at the costs of a GPU often used for machine learning - Nvidia GTX 980 TI. According to Nvidia, it draws 250W under load which according to your figures would result in a yearly cost of roughly $344. That's just for the reference card, a typical card that a consumer would purchase would draw even more. You can buy a 980 TI for a little more than $400. That doesn't even begin to look at hardware actually designed for commercial and research applications.
I think that it's possible to find a way of monetizing computer resources, however, I think it has more to do with arbitraging differences in electricity costs. Suchflex's model certainly wouldn't work where I live (electricity costs in NYC are roughly 20 cents per kw-hour) but parts of the US are under 10 cents. I could see a company attempting to profit from these differences by setting up hardware in a cheap state and negotiating a favorable electricity rate. Heavy computation could then be done on these networks for significantly less than it could in New York or California.
In summary, the value of a consumer's unused computer has more to do with their electricity rate than their hardware.
I understand the 'sharing economy' desire to make use of underutilized resources, but this doesn't seem like an economically feasible way of doing so. The model works for Uber/Lyft: cars are a relatively high upfront cost compared to the cost of gas, but computer hardware is often less expensive upfront than the electricity costs of running it for a year. Additionally, much of the economic value in a service like Uber or Lyft is provided by the driver, not just the use of the car. In this service, the user doesn't provide any value, in fact, they're using up cycles/space that could otherwise be monetized.
However, lots of the technology being developed (robust autonomous flight, improved endurance & range, lower costs) will speed up developments for other applications that make better use of their strengths. Even more importantly, companies like Google are finally forcing the FAA to craft realistic regulations that don't completely cripple commercial applications. The FAA's lethargic pace has already severely hampered domestic development to the degree that Google had to do most of their development in Australia.