
Google Cuts Its Giant Electricity Bill with DeepMind-Powered AI - runesoerensen
http://www.bloomberg.com/news/articles/2016-07-19/google-cuts-its-giant-electricity-bill-with-deepmind-powered-ai
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bytefactory
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.

~~~
adrenalinelol
It's a shame too because one of the inhibiting factors of AI as complex as
DeepMind is the fact it isn't cost effective due to its power consumption for
quite a few tasks.

~~~
bytefactory
"In recent months, the Alphabet Inc. unit put a DeepMind AI system in control
of parts of its data centers to reduce power consumption by manipulating
computer servers and related equipment like cooling systems. It uses a similar
technique to DeepMind software that taught itself to play Atari video games,
Hassabis said in an interview at a recent AI conference in New York."

This part really incensed me. That's like describing SpaceX's rocket "as being
based on similar technology as Wernher von Braun's V2 rockets in World War 2".
I exaggerate for effect, but you get the point.

Edit: formatting.

~~~
arbre
I disagree. If you read the atari paper you will get plenty of details and you
can infer how it is applied to electricity consumption. They were using
reinforcement learning. The algorithms would learn to get a better score by
looking at the screen and sending actions accordingly. Here you could imagine
the same algorithm with energy consumption as a score, a set of datacenter
metrics as the screen (state) and change of metrics as actions.

~~~
argonaut
Errr... No. Just no. Deep reinforcement learning is not some pixie dust that
magically works for any problem with a reward function that you throw it at.
It's astounding how commenters on HN think this is all "easy".

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dmos62
This quickly went to you say this, I say this. These are very interesting
statements, it would be nice if they were supported by citations.

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argonaut
The poster I was replying to is really the one who needs to prove that deep RL
is super easy like they were claiming.

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fovc
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](https://ycharts.com/companies/GOOG/pe_ratio)

[2] [https://techcrunch.com/2014/01/26/google-
deepmind/](https://techcrunch.com/2014/01/26/google-deepmind/)

~~~
heydenberk
One might assume, though, that Google could've applied more homegrown ML to
the same problem and achieved significant savings as well.

~~~
ACow_Adonis
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 revenue/savings over three years.
What isn't reported is that the revenue was just being moved from another
project that was canned, and a guy in an office for a week looking at a
spreadsheet could have found similar savings without the expense/complexity.
(Not that I'm saying that's what's happening in google s case, but the fluff
peices are so universally fluffy, you aren't given enough information to know
that it isn't)

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Godel_unicode
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 apparently
accomplished here is amazing. If any other company said they used machine
learning to save that much money people would be singing their praises and
begging for it to be open-sourced. This thread effectively reads as "pics or
it didn't happen"

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hueving
>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.

~~~
Godel_unicode
While I agree that this is fluffy, I would submit that:

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

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tdaltonc
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.

~~~
Godel_unicode
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.

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tdaltonc
I imagine it's bad for the energy minimization (or uptime maximization)
function if the environmental control system goes down.

~~~
Godel_unicode
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.

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honkhonkpants
Very light on details. What is the baseline of the savings? For example, was
there a water pump that was always running at a fixed worst-case setting, and
the machine learning system now ramps it up and down? If so, what is the
marginal benefit over alternatives like a rudimentary closed-loop electronic
control? Would like to know more about the system that was replaced, instead
of these bare claims.

~~~
niels_olson
It be interesting if it cycled the motors too often and popped solinoids,
creating higher long term maintenance and down time, but they cut this study
before these long term effects showed?

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tdaltonc
They need to find some medium sized city that will let them play with their
traffic lights.

~~~
Houshalter
Or we could build a new city from the ground up so everything is run by the
AI.

~~~
Aelinsaar
Your Psycho Pass is a little cloudy...

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ehrtt
Those were human brains. That's cheating.

~~~
Aelinsaar
Wintermute then. :)

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throwaway3983
Related previous effort:

[https://googleblog.blogspot.com/2014/05/better-data-
centers-...](https://googleblog.blogspot.com/2014/05/better-data-centers-
through-machine.html)

~~~
signa11
this is waay better than the fluff piece posted. thank you !

edit-1: actually, the pdf in the article
([http://static.googleusercontent.com/media/www.google.com/en/...](http://static.googleusercontent.com/media/www.google.com/en//about/datacenters/efficiency/internal/assets/machine-
learning-applicationsfor-datacenter-optimization-finalv2.pdf)), contains
slightly more details. and this is _old_, circa 2014 stuff.

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zhanwei
"Now that DeepMind knows the approach works, it also knows where its AI system
lacks information, so it may ask Google to put additional sensors into its
data centers to let its software eke out even more efficiency."

Sounds like active learning to me. It's a type of machine learning where a
learner pro-actively ask for interesting data points to be labeled so that he
can learn more about the system. :)

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shepardrtc
I think they meant DeepMind as the team itself, not the software.

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zitterbewegung
This is very similar to DART where DARPA was able to recover all of its
investment to AI and a testament to its pragmatism. Also both are logistical
problems. See
[https://en.wikipedia.org/wiki/Dynamic_Analysis_and_Replannin...](https://en.wikipedia.org/wiki/Dynamic_Analysis_and_Replanning_Tool)

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sowbug
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/](https://www.google.com/contributor/)

~~~
Eyght
This is interesting to me. Is it a problem with the Adwords/doubleclick API,
or just some adblock checker hack from bloomberg's side?

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sowbug
I don't know. The nag's styling and language matched Bloomberg's, if that's
any clue. It had a stern warning of some kind, and the only way to continue
was to press a button in the alert, which I refused to do out of principle.

I refreshed a couple times and it didn't happen again.

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iamleppert
How exactly is this better than standard PID control? I'm thinking if you
actually look at what it came up with, is probably some form of PID control on
systems that previously didn't have it. Think fans that are simply left on all
the time.

We're talking about simple physics. Heat transfer. Cooling systems. They
should have been installed, operated and programmed correctly using very
simple techniques.

It's an interesting application but I'm thinking this is a prima facie example
of over-engineering.

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Xcelerate
Chemical engineering process design can become very complex and highly
nonlinear (in fact, Nick Sahinidis' group in the chemical engineering
department at CMU created BARON explicitly for solving these kinds of problems
to global optimality — see
[http://archimedes.cheme.cmu.edu/?q=baron](http://archimedes.cheme.cmu.edu/?q=baron)).
Granted, Google's systems don't involve chemical reactions, but that doesn't
automatically mean that designing these data centers is a simple task.

~~~
niels_olson
I work with a guy who has done ground-breaking linear algebra work, spent most
of career at Shell. The systems have been too complex to model for a long
time. I can imagine an AI instructed to optimize a parameter could be a huge
gain.

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Aelinsaar
This is kind of thrilling... the somewhat generalized use for an AI with such
a concrete benefit.

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jjp
[https://deepmind.com/blog](https://deepmind.com/blog) \- some more details.

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T-A
Not exactly a new idea. Here's a random book which I happened to be looking at
just yesterday: [https://www.crcpress.com/Artificial-Intelligence-in-Power-
Sy...](https://www.crcpress.com/Artificial-Intelligence-in-Power-System-
Optimization/Ongsakul-Dieu/p/book/9781578088058)

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polskibus
Is this similar to what WalMart has been doing with their energy efficiency in
shops for ages? I mean centralized power management, early warning system,
lots of sensors, etc.

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knowThySelfx
At some point will AI start to have questions like "Who am I? Who made me?
Whats the purpose of my existence?" etc. We will have atheist AI's and
theist/deist AI's and what not. I guess it will be time for some AI
philosophy.

Makes me wonder if there's a creator, will He/She be amused by our attempts at
answering "Who am I" and such questions. Will be fun :D

~~~
throwanem
It'll need to grow a concept of "I" first, and that's probably not very
likely; there's a reasonable case that self-awareness is an evolutionary cul-
de-sac.

~~~
liquidmetal
Tangent here - self-awareness is an evolutionary cul-de-sec? Do you have any
further reading suggestions on this?

~~~
throwanem
Peter Watts's _Blindsight_ \- good fiction on the one hand, and exhaustively
referenced on the other. (Watts is the only sf author I've run across whose
novels include discussions and bibliographies of the research he used to
inform and shape the narrative. In addition to earning him a new high score on
the hardness scale, this seems counterintuitively to produce better stories,
not worse ones.)

