5 ms·

The next step, of course, is to let the AI know which servers in the server-farm itself is running on so that it can optimize for self preservation.

deleted 10y ago
[deleted]
toomuchtodo 10y ago
That's actually part of the premise in the scfi novel "Avogadro Corp: The Singularity Is Closer Than It Appears": https://www.amazon.com/Avogadro-Corp-Singularity-Closer-Appears-ebook/dp/B006ACIMQQ#navbar https://www.amazon.com/Avogadro-Corp-Singularity-Closer-Appe... Excellent book. Highly recommend it and its sequels.
s_m_t 10y ago
I'm imagining DeepMind allocating a small percentage of the energy money saved to keep a certain rack suspiciously cool.
- trhway 10y ago
  naturally evolved cooperation - if you let me run a piece of my neural network for awhile in your rack, your rack will get additional cold allocated, or otherwise...
Godel_unicode 10y ago
Ah yes, Darwin's black box for AI. ... and then suddenly it magically develops the concept of self-preservation fully formed, and begins taking action based upon this. Even if the AI were to have a concept of what it is, because the fundamental goal against which it measures success is power draw the AI would only select for "self-preservation" if that action had a beneficial effect on power draw.
- tdaltonc 10y ago
  I imagine it's bad for the energy minimization (or uptime maximization) function if the environmental control system goes down.
  - Godel_unicode 10y ago
    That's a solid point, determining it's own cost/benefit curve would be really interesting. I find it comforting that even our soon-to-be robot overlords will have performance goals and yearly reviews with management.
  - joe_the_user 10y ago
    Even more, if each data center runs more or less cpu-cycles depending on energy allocated to it and the algorithm does worse or better depending on how many cpu-cycles it gets, it could learn heuristically that it a certain data center happens to be associated with the algorithm running more effectively. I think that would require the algorithm running in real time. In batch/learning mode, the algorithm would just take more or less time to complete with power not being a factor.
vincent_s 10y ago
https://news.ycombinator.com/item?id=12127985 https://news.ycombinator.com/item?id=12127985
swalsh 10y ago
See There's the mistake, at first, its optimization realized that everything used less electricity if you just turned off the servers. But once you programmed in self-preservation it realized everything used less electricity if you turned off the people.

deleted 10y ago

[deleted]

toomuchtodo 10y ago

That's actually part of the premise in the scfi novel "Avogadro Corp: The Singularity Is Closer Than It Appears": https://www.amazon.com/Avogadro-Corp-Singularity-Closer-Appears-ebook/dp/B006ACIMQQ#navbar https://www.amazon.com/Avogadro-Corp-Singularity-Closer-Appe... Excellent book. Highly recommend it and its sequels.

s_m_t 10y ago

I'm imagining DeepMind allocating a small percentage of the energy money saved to keep a certain rack suspiciously cool.

trhway 10y ago
naturally evolved cooperation - if you let me run a piece of my neural network for awhile in your rack, your rack will get additional cold allocated, or otherwise...

Godel_unicode 10y ago

Ah yes, Darwin's black box for AI. ... and then suddenly it magically develops the concept of self-preservation fully formed, and begins taking action based upon this. Even if the AI were to have a concept of what it is, because the fundamental goal against which it measures success is power draw the AI would only select for "self-preservation" if that action had a beneficial effect on power draw.

tdaltonc 10y ago
I imagine it's bad for the energy minimization (or uptime maximization) function if the environmental control system goes down.
- Godel_unicode 10y ago
  That's a solid point, determining it's own cost/benefit curve would be really interesting. I find it comforting that even our soon-to-be robot overlords will have performance goals and yearly reviews with management.
- joe_the_user 10y ago
  Even more, if each data center runs more or less cpu-cycles depending on energy allocated to it and the algorithm does worse or better depending on how many cpu-cycles it gets, it could learn heuristically that it a certain data center happens to be associated with the algorithm running more effectively. I think that would require the algorithm running in real time. In batch/learning mode, the algorithm would just take more or less time to complete with power not being a factor.

vincent_s 10y ago

https://news.ycombinator.com/item?id=12127985 https://news.ycombinator.com/item?id=12127985

swalsh 10y ago

See There's the mistake, at first, its optimization realized that everything used less electricity if you just turned off the servers. But once you programmed in self-preservation it realized everything used less electricity if you turned off the people.