Reply to post: Re: So...

DeepMind AI bots tell Google to literally chill out: Software takes control of server cooling

Charlie Clark Silver badge

Re: So...

Themostats suffer from delays which makes them inefficient. If heating, or in Google's case cooling, is sufficiently expensive the investing in efficiency makes sense. A simple, rule-based approach might be sufficient. For example, last year I swapped the simple radio themostats in my flat for ones with clocks and schedules and was able to keep the flat at a more agreeable temperature as a result with less manual intervention, even though the principle of the thermostat remained the same. I don't have sufficient data but I think the rule to throttle back overnight and set holiday timings has reduced my heating bill while increasing comfort (especially when returning from a long trip during a cold spell).

The rules could be extended using measurements such as termperature and humidity, amount of daylight, etc. This makes it a good domain for machine learning but still requires people to select features and outcomes, something that itself can be optimised in certain environments. Clearly not relevant for my environment but for a company the size of Google the savings could be relevant and it's also an excellent test case and advert for the technology. Because, despite the savings, this is largely PR.

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