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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.
"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. :)
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/
This is interesting to me. Is it a problem with the Adwords/doubleclick API, or just some adblock checker hack from bloomberg's side?
I refreshed a couple times and it didn't happen again.
Earlier quoted context omitted.
Please! Imagine all the time, gas, and sanity wasted at red lights when there is absolutely no cross traffic!
Yeah, that are exactly the arguments used by companies selling "Intelligent Transportation Systems". After deployment: surprise - there aren't any noticeable changes, except for places that are performing worse and require manual tweaking. Also the best way to reduce traffic in city is to reduce vehicle flow into the city which only moves jams to other places.
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.
More details available at http://googlegreenblog.blogspot.com/2016/07/deepmind-ai-redu...
Earlier quoted context omitted.
Please! Imagine all the time, gas, and sanity wasted at red lights when there is absolutely no cross traffic!
Yeah, that are exactly the arguments used by companies selling "Intelligent Transportation Systems". After deployment: surprise - there aren't any noticeable changes, except for places that are performing worse and require manual tweaking. Also the best way to reduce traffic in city is to reduce vehicle flow into the city which only moves jams to other places.
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.
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.
You are talking about the power required to execute the AI, where the article is discussing the application of the AI to make a system more efficient.
Earlier quoted context omitted.
"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 d…
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…
What you have described is easily instantiated with any numerical optimization technique of the last 40 years. The devil for any of these problems is in the details.