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Related previous effort: https://googleblog.blogspot.com/2014/05/better-data-centers-...
edit-1: actually, the pdf in the article (http://static.googleusercontent.com/media/www.google.com/en/...), contains slightly more details. and this is _old_, circa 2014 stuff.
Earlier quoted context omitted.
Indeed. One of the "elephant in the room" parts of all of these corporate/pr press releases dressed up as news/revenue reports is that they never report or investigate opportunity cost: say how much could google have saved with a simple algorithm, homegrown solution, or 4 heuristic if/then/else statements. I've been involved with similar multi-million dollar projects that were reported to be bringing in XX million in…
Deep mind is needed for other things (e.g. search results). Effectively, the cost of developing it is paid for by search et al, and the only cost core infrastructure has is adapting the existing technology to work on power data as well. This is that "synergy" thing we always snicker at when people in suits say it. It just happens to be true here. Sidebar: the sour grapes in this thread about what Google has apparentl…
Likely because it won't be open sources and because there are almost no details at all compared to how this would have worked with other ML techniques. It's nothing but a fluff piece to feed to investors wondering about the large purchase.
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.
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.
Earlier quoted context omitted.
Deep mind is needed for other things (e.g. search results). Effectively, the cost of developing it is paid for by search et al, and the only cost core infrastructure has is adapting the existing technology to work on power data as well. This is that "synergy" thing we always snicker at when people in suits say it. It just happens to be true here. Sidebar: the sour grapes in this thread about what Google has apparentl…
>begging for it to be open-sourced. This thread effectively reads as "pics or it didn't happen" Likely because it won't be open sources and because there are almost no details at all compared to how this would have worked with other ML techniques. It's nothing but a fluff piece to feed to investors wondering about the large purchase.
1 There are a number of other organizations with serious ML chops
2 Knowing that something is possible is frequently the biggest aid to making it happen
3 This solution is likely tightly coupled with Google's infrastructure
Earlier quoted context omitted.
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.
I imagine it's bad for the energy minimization (or uptime maximization) function if the environmental control system goes down.
They saved "several percentage points" off of 4.4M MWh, so maybe 250M KWH, which might be $10-20M. At 30x earnings [1], they just made back most if not all of the purchase price of Deepmind [2] [1] https://ycharts.com/companies/GOOG/pe_ratio [2] https://techcrunch.com/2014/01/26/google-deepmind/
One might assume, though, that Google could've applied more homegrown ML to the same problem and achieved significant savings as well.
OT: it's frustrating to pay Google Contributor to skip ads, and still get nagged by bloomberg.com for using an ad blocker (which I've never done). https://www.google.com/contributor/
The article was quite low on substance, but quite readable for me. With no ads at all. And no ad blocker nag. Firefox + NoScript for the win.
Earlier quoted context omitted.
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.
I imagine it's bad for the energy minimization (or uptime maximization) function if the environmental control system goes down.
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.
Very frustrating read. Read more like an advertisement than an informative article. The claims made would've made for a very interesting tech-dive into a novel use of machine intelligence, but no details were provided.
Ironically if you have an ad-block there is an interstitial annoyance-delay. Seems like my ad-blocker is doing its job.