Friday, March 31, 2017

DARPA: three waves of AI

High production values for DARPA's US Military roadmap and vision for AI (February 2017).

This will be the basis of funding going forward. The images below are taken from this slide-pack, more sophisticated than anything I've seen from the likes of Accenture.

Click on any of the pictures to make larger - or better, review the entire slide-set.

Although this 'three wave' model is not too surprising, it's still an accurate view as to where research is heading.


If human beings are taken as exemplars of neural nets which can explain their own, contextual operation, it's worth noting that such explanations have a curious character.

No human can explain their own sub-conscious neural processes. If asked to explain how you know that a picture of a cat is indeed that of a cat, you are not going to elucidate details of early visual processing in your visual cortex.

Instead, you are going to traffic in high-level, symbolic descriptions of putative intermediate stages in scene interpretation. The talk will be of features such as fur, shape, the environment of said animal.

These intermediate-level symbolic descriptions are remote indeed from the actual neural processes which it is claimed implemented them .. and indeed will have only a contingent (although highly correlated if accurate) relationship with them.

Self-deception is never far away in the third wave!


If you have sixteen minutes, John Launchbury's presentation of DARPA's strategy is excellent.

Interestingly, John Launchbury is British.


  1. Yes interesting DARPA project, but I am not clear whether you are altogether convinced it will work...
    In fact the slide admits that the third wave will be lukewarm on Abstraction abilities, which are likely to be necessary in a more generic AI type system, which can shift around between domains and abstraction levels.
    In short your "curious problem" gap, seems to be a reflection of the old question of the link between "Symbolic AI" and "Sub-Symbolic AI". In this DARPA context we now have probabilistic reasoning more explicit.

    1. I think the concept of abstraction isn't well defined in the presentation. If it's feature abduction, akin to generalisation via analogy, then having a comprehensive library of 'feature lattices' induced from different domains is a prerequisite. We're not there yet.

      Something like wave three is bound to work, if only because the concept is drawn so loosely, and progress in AI will not be achieved at all unless problems in these areas are addressed with some success.


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