Philosophy Before Formality: Some Definitions For Quantum AI

Philosophy Before Formality:  Some Definitions For Quantum AI

"Mathematicians are like Frenchmen: whatever you say
     to them they translate into their own language and
     forthwith it is something entirely different."
      -- Johann Wolfgang von Goethe

0.  PREFATORY NOTES

It is already very difficult to follow almost any proof in mathematical texts without substantial background, or inline, though extraneous comments and explanations just like it is difficult to follow someone else's uncommented computer code:  it can be done, but, it just takes a lot longer for no good reason.

William Kingdon Clifford said it like this in  Common Sense in the Exact Sciences (1885), 21.

" We may always depend on it that algebra, which cannot be translated into good English and sound common sense, is bad algebra."

So the idea in these blogs is to first express the philosophy, the idea and then formulate that in mathematical expression.  The goal is to state things in reasonable clear, simple and concise English before stating those things with equations.

What I am discovering for myself is that in writing this blog, I am revealing to myself my own mental machinery and its gaps, holes and deficiencies:  I hope those that read this will do the same and point out where I am being ambiguous or downright useless.

1. INTRODUCTION

I am going to define what I mean by Quantum Computing Artificial Intelligence (QCAI).

My definition is the not the right definition:  it is my point of view and I am writing exposition to clarify my point of view.  I welcome other viewpoints.

"The real danger is not that computers will begin to think like men,
      but that men will begin to think like computers."
      -- Sydney J. Harris

We seem to have descended closer to the way computers communicate, using short abbreviated codes in tweets, adjusting our mind space in order to search with specific combinations keywords:  the Search engines have us well trained!

QCAI in my view should contribute to bringing computers closer to the level at which the human operates and not diminish the human down to the level of a machine.  Yet software trains us.  We do not train software.  We buy an app and we have to "learn" it.  It does not learn us.

2.  Quantum Computing Artificial Intelligence (QCAI)

Quantum AI is concerned pattern discovery which then becomes the basis for pattern recognition.  Traditional computing is concerned, for the most part, with pattern-recognition. Usually parameters of recognition become statistical entities used later in discovery but these parameters also box-in what is possible --- nothing outside the realm of the parameters can be discovered.   Quantum AI focuses on the discovery of patterns, chains of patterns, and transformations of patterns utilizing the fundamental concepts essential to the identity of what we are called Quantum AI.  Patterns discovered are then learned and used in pattern recognition.

The words “artificial intelligence” were coined renowned computer scientist John McCarthy, in 1956 at the first conference in Dartmouth.   So defines the subject?  I will defer and refer the reader to the pages at Stanford from the great man himself:  
  
WHAT IS ARTIFICIAL INTELLIGENCE?,  by John McCarthy
http://www-formal.stanford.edu/jmc/whatisai/whatisai.html

One part of the document in FAQ is the following quote:

"Q. Are computers fast enough to be intelligent?
A. Some people think much faster computers are required as well as new ideas. My own opinion is that the computers of 30 years ago were fast enough if only we knew how to program them."

I underlined and italicized the words because our paradigm of programming AI has relied on classical physics.

So, the objective with QCAI is to answer the question "if only we knew how to program them".

So, here is my working definition:

Quantum Computing Artificial Intelligence, or Quantum Artificial Intelligence is the science, design and implementation of intelligent computer programs that have competency and performance at the level or beyond of human intelligence in complex understanding, value judgements, reasoning, and decision making.


So, clearly, this definition embodies the Science, the Design and the Implementation aspects.  For the next few blog entries we will focus on the Science, then the design and then the implementation.

3. CAVEATS

Here are all my caveats, as better written than I, by others I admire:

How to be a Bad Theoretical Physicist
http://www.staff.science.uu.nl/~hooft101/theoristbad.html

Are you a Quack?
http://insti.physics.sunysb.edu/~siegel/quack.html

The Crackpot Index
http://math.ucr.edu/home/baez/crackpot.html

How to be a Good Theoretical Physicist
http://www.staff.science.uu.nl/~Gadda001/goodtheorist/

4. POPULAR LINKS

And, to get familiar with some of the emerging sites and research:

http://www.nas.nasa.gov/quantum/research.html
"One of the central open questions in the field of quantum computing is the existence of efficient quantum heuristic algorithms for solving classically intractable instances of combinatorial optimization problems that are found at the core of many of NASA’s missions." - quoted from NASA

http://www.usra.edu/quantum/rfp/
"The Universities Space Research Association (USRA) is pleased to invite proposals for Cycle 1 of the Quantum Artificial Intelligence Laboratory Research Opportunity, which will allocate computer time for research projects to be run on the D-Wave System at NASA Ames Research Center (ARC) for the time period November 2014 through September 2015."

https://plus.google.com/+QuantumAILab/posts
"The Quantum Artificial Intelligence Lab is a collaboration between Google, NASA Ames Research Center and USRA. We're studying the application of quantum optimization to difficult problems in Artificial Intelligence."

5.  UNTIL NEXT TIME

It's all about the Science.