
Darpa Perspective on AI - Dim25
http://www.darpa.mil/about-us/darpa-perspective-on-ai
======
daly
DARPA may be looking beyond the current Neural Network focus on perception and
manipulation but the rest of the field seems to be stuck on NNs. Good-Old-
Fashioned-AI (GOFAI) techniques, such as knowledge representation (e.g. SCONE
([http://www.aaai.org/ocs/index.php/FSS/FSS11/paper/viewFile/4...](http://www.aaai.org/ocs/index.php/FSS/FSS11/paper/viewFile/4212/4568\)))
or Subsumption Based systems
([http://dl.kr.org/oldproceedings/AIMag11-02-003.pdf](http://dl.kr.org/oldproceedings/AIMag11-02-003.pdf)),
or Rule-Based Programming
([http://mprc.pku.cn/mentors/training/ISCAreading/1986/p28-gup...](http://mprc.pku.cn/mentors/training/ISCAreading/1986/p28-gupta/p28-gupta.pdf)),
the whole large field
([http://dai.fmph.uniba.sk/~sefranek/kri/handbook/handbook_of_...](http://dai.fmph.uniba.sk/~sefranek/kri/handbook/handbook_of_kr.pdf))
are simply ignored these days. (disclaimer, I was involved with several of
these systems).

Suppose your problem is to replace a tire on a car using a wrench. Perception
is involved in finding the wrench. Manipulation is involved in recognizing
torque. NNs are excellent for both of these tasks. In fact, it would seem
ideal to bind both kinds of NNs to the concept "WRENCH". They provide
grounding for the concept.

But knowing how to find a wrench or how to use one is different from knowing
WHY you want to do either. This is where DARPA has lost the thread. In my
opinion, the future belongs to self-modifying systems that can do knowledge
representation and planning using NNs as the I/O subsystems. Self-modification
implies that the system gradually evolves as it acts in the world. The
mistakes it made yesterday will change the system to avoid those mistakes.
GOFAI techniques combined with self-modification fundamentally changes the
game.

An interesting side-effect is that, given two identical systems, they will
eventually diverge. One will "know" that a table has 4 legs. The second will
know that a table has rows and columns. Through self-modification their
knowledge nets will gradually diverge until they are nowhere the same. The
side-effect is that you can no longer "learn by copying" but have to "learn by
teaching".

------
Dim25
Direct links

PDF slides:
[http://www.darpa.mil/attachments/AIFull.pdf](http://www.darpa.mil/attachments/AIFull.pdf)

Video:
[https://www.youtube.com/watch?v=-O01G3tSYpU](https://www.youtube.com/watch?v=-O01G3tSYpU)

