5 ms·

I remember reading the blog post. Did they ever follow up with a research paper explaining what they actually did?

by forgotmyhnacc 10y ago

gwern 10y ago
Sadly, not yet. Might be too secret sauce even for Google.
- conistonwater 10y ago
  Nonlinear control with neural networks has existed for a long time, though, it's not exactly new. Is there reason to think they did something profoundly new in that specific instance?
  - mooneater 10y ago
    Probably the use of a DNC for industrial application is novel.
    - gwern 10y ago
      Yes. When this came first up, someone on /r/machinelearning scoffed that using NNs to control fans/coolers/power systems to optimize was trivial and obvious and had been done for decades. When I challenged him for a ref, he produced a PDF which listed dozens of industrial applications for various nonlinear NN algorithms... none of which were actually autonomously controlling anything and most were predictive.
- haimez 10y ago
  Lol, no. It's just the scale of the use that makes it valuable. Google datacenter cooling problems only exist inside of Google data centers, and the control knobs therein are 1. measurable AND measured 2. deterministic 3. simple. They're innovating in a problem space that only exists at Google, Microsoft, and Amazon. This is the boringest of sauces.
- deepnotderp 10y ago
  It's not secret sauce, the algos are well known, read carefully, the guy who proposed it was an ML outsider. And besides, they stated they plan to release it.
mooneater 10y ago
Their past paper on this: https://www.google.com/about/datacenters/efficiency/internal/assets/machine-learning-applicationsfor-datacenter-optimization-finalv2.pdf https://www.google.com/about/datacenters/efficiency/internal... In the blog post in July 20 2016 they said "We are planning to roll out this system more broadly and will share how we did it in an upcoming publication" https://deepmind.com/blog/deepmind-ai-reduces-google-data-centre-cooling-bill-40/ https://deepmind.com/blog/deepmind-ai-reduces-google-data-ce...

I remember reading the blog post. Did they ever follow up with a research paper explaining what they actually did?

gwern 10y ago

Sadly, not yet. Might be too secret sauce even for Google.

conistonwater 10y ago
Nonlinear control with neural networks has existed for a long time, though, it's not exactly new. Is there reason to think they did something profoundly new in that specific instance?
- mooneater 10y ago
  Probably the use of a DNC for industrial application is novel.
  - gwern 10y ago
    Yes. When this came first up, someone on /r/machinelearning scoffed that using NNs to control fans/coolers/power systems to optimize was trivial and obvious and had been done for decades. When I challenged him for a ref, he produced a PDF which listed dozens of industrial applications for various nonlinear NN algorithms... none of which were actually autonomously controlling anything and most were predictive.
haimez 10y ago
Lol, no. It's just the scale of the use that makes it valuable. Google datacenter cooling problems only exist inside of Google data centers, and the control knobs therein are 1. measurable AND measured 2. deterministic 3. simple. They're innovating in a problem space that only exists at Google, Microsoft, and Amazon. This is the boringest of sauces.
deepnotderp 10y ago
It's not secret sauce, the algos are well known, read carefully, the guy who proposed it was an ML outsider. And besides, they stated they plan to release it.

mooneater 10y ago

Their past paper on this: https://www.google.com/about/datacenters/efficiency/internal/assets/machine-learning-applicationsfor-datacenter-optimization-finalv2.pdf https://www.google.com/about/datacenters/efficiency/internal... In the blog post in July 20 2016 they said "We are planning to roll out this system more broadly and will share how we did it in an upcoming publication" https://deepmind.com/blog/deepmind-ai-reduces-google-data-centre-cooling-bill-40/ https://deepmind.com/blog/deepmind-ai-reduces-google-data-ce...