Answers.Body: <p>My understanding of efficiency in this context is in regards to optimization of algorithms as opposed to hardware speed, which is more of a "brute force" component.  GPUs may be more <em>energy</em> efficient, but this is distinct from <a href="https://en.wikipedia.org/wiki/Linear_programming" rel="nofollow noreferrer">linear optimization</a> of algorithms.</p>
  
  <p>In terms of how much processor speed you need to tackle a given problem, that's in the realm of <a href="https://en.wikipedia.org/wiki/Computational_complexity_theory" rel="nofollow noreferrer">computational complexity theory</a> and <a href="https://en.wikipedia.org/wiki/Analysis_of_algorithms" rel="nofollow noreferrer">analysis of algorithms</a>. </p>
  
  <p>Amount of GPUs, RAM and storage needed to tackle a given problem are purely a function of the complexity of the problem and the efficiency of the algorithms. </p>
  
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Answers.CreationDate: 2017-06-15T15:35:31.977Z
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Answers.UserDisplayName: DukeZhou
Body: <p>I know nowadays agencies are using GPUs in order to accelerate AI, but how fast should be it to be efficient, I mean I know that depends of how large and complex the assignment is but what would be a way to measure its efficiency and what kind of technology(amount of GPUS,RAM,STORAGE) and techniques need to be used in order to get enough efficency?</p>
  
  <p>Any thoughts from experts would be appreciated</p>
  
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Comments.CreationDate: 2017-06-15T19:38:11.413Z
Comments.Text: Glad that was helpful.  If you haven't previously come across them, you will find the concepts of [bounded rationality](https://en.wikipedia.org/wiki/Bounded_rationality) and [automata theory](https://en.wikipedia.org/wiki/Automata_theory) quite useful.
Comments.UserDisplayName: DukeZhou
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Comments.CreationDate: 2017-06-15T19:47:46.973Z
Comments.Text: I asked a [sort of similar question a while ago, related to DeepBlue and AlphaGo](https://ai.stackexchange.com/questions/3072/what-are-the-general-sizes-of-alphago-and-deep-blue), but hardware and volume limitations don't seem to be very much emphasized currently.
Comments.UserDisplayName: DukeZhou
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Comments.CreationDate: 2017-06-15T19:52:42.900Z
Comments.Text: Wow..Now I got a lot to read and process. Thanks a lot for all of the information , you shared more than expected
Comments.UserDisplayName: Graphs Rodriguez
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2017-06-16T21:14:41.730Z
Comments.Text: This got me thinking about the architecture of self-driving cars (how they have to be fully autonomous i.e. can't rely on network connection) and I found a lot of links to the [Nvidia Drive PX-series](https://en.wikipedia.org/wiki/Drive_PX-series) which the manufacturer categorizes as a [supercomputer](http://www.nvidia.com/object/drive-px.html)
Comments.UserDisplayName: DukeZhou
Tags: <efficiency>
Title: how fast does need to be an AI agent to be efficient?
UserDisplayName: Graphs Rodriguez
ThreadText: # how fast does need to be an AI agent to be efficient?
  
  (Asked by: username_0 on 2017-06-15)
  
  I know nowadays agencies are using GPUs in order to accelerate AI, but how fast should be it to be efficient, I mean I know that depends of how large and complex the assignment is but what would be a way to measure its efficiency and what kind of technology(amount of GPUS,RAM,STORAGE) and techniques need to be used in order to get enough efficency?
  
  Any thoughts from experts would be appreciated
  
  **Tags:** efficiency
  
  > **Comments:**
  > **username_1**: Glad that was helpful.  If you haven't previously come across them, you will find the concepts of [bounded rationality](https://en.wikipedia.org/wiki/Bounded_rationality) and [automata theory](https://en.wikipedia.org/wiki/Automata_theory) quite useful.  
  > **username_1**: I asked a [sort of similar question a while ago, related to DeepBlue and AlphaGo](https://ai.stackexchange.com/questions/3072/what-are-the-general-sizes-of-alphago-and-deep-blue), but hardware and volume limitations don't seem to be very much emphasized currently.  
  > **username_0**: Wow..Now I got a lot to read and process. Thanks a lot for all of the information , you shared more than expected  
  > **username_1**: This got me thinking about the architecture of self-driving cars (how they have to be fully autonomous i.e. can't rely on network connection) and I found a lot of links to the [Nvidia Drive PX-series](https://en.wikipedia.org/wiki/Drive_PX-series) which the manufacturer categorizes as a [supercomputer](http://www.nvidia.com/object/drive-px.html)  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2017-06-15. Score: 1 | Accepted answer
  
  My understanding of efficiency in this context is in regards to optimization of algorithms as opposed to hardware speed, which is more of a "brute force" component. GPUs may be more *energy* efficient, but this is distinct from [linear optimization](https://en.wikipedia.org/wiki/Linear_programming) of algorithms.
  
  In terms of how much processor speed you need to tackle a given problem, that's in the realm of [computational complexity theory](https://en.wikipedia.org/wiki/Computational_complexity_theory) and [analysis of algorithms](https://en.wikipedia.org/wiki/Analysis_of_algorithms).
  
  Amount of GPUs, RAM and storage needed to tackle a given problem are purely a function of the complexity of the problem and the efficiency of the algorithms.
  
  
  ---
  
  