Re: [Idnet] Intelligence-Defined Network Architecture and Call for Interests

Pedro Martinez-Julia <> Tue, 28 March 2017 18:25 UTC

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Date: Wed, 29 Mar 2017 03:25:30 +0900
From: Pedro Martinez-Julia <>
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Subject: Re: [Idnet] Intelligence-Defined Network Architecture and Call for Interests
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On Tue, Mar 28, 2017 at 10:59:38AM -0700, David Meyer wrote:
> Hey Sheng,
> I just wanted to revive my key concern on [0] (same one I made at the
> NMRL): The hard parts of getting Machine Learning intelligence into
> Networking is the Machine Learning part. In addition, successful deployment
> of ML requires knowledge of ML combined with domain knowledge. We
> definitely have the domain knowledge; the problem is that we don't have the
> ML knowledge, and this is one of the big factors holding us back; see e.g.
> Andrew's discussion of talent in [1].  Slides such as [0] seem to imply
> that *someone else* (in particular, not us)  will handle the ML part of all
> of this. I'll just note that in general successful deployments of ML don't
> work this way; the domain experts will have to learn ML (and vice versa)
> for us to be successful (again, see [1] and many others).

Dear Dave,

You are true in that ML/domain knowledge is necessary but, however it is
worth to take into account that it is not strictly required and it will
even be counterproductive in some (or maybe most) situations. At the end
of the day, encouraging (or forcing) a network expert to learn ML is
quite difficult, the results will be delayed until the learning phase
ends, and (most probably) s/he will never get a better solution than a
person that has been an expert in ML from a long time ago. Therefore, it
is better to make separate experts (in ML and the domain itself) to
collaborate in a common solution. Therefore, and I think it has been
mentioned before, we have to (try to) enroll experts in ML to the IDNET
group and see what can we do together...

> Perhaps a useful exercise would be to write an ID that makes your
> assumptions explicit?
> Thanks,
> Dave


Pedro Martinez-Julia
Network Science and Convergence Device Technology Laboratory
Network System Research Institute
National Institute of Information and Communications Technology (NICT)
4-2-1, Nukui-Kitamachi, Koganei, Tokyo 184-8795, Japan
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