OK, Ian, I promised I would respond and here goes.  Sorry I didn't before, I 
had assumed your questions were rhetorical.

When I say that software hasn't changed I mean to say that it hasn't jumped 
qualitative categories.  We are still living in a world where computing exists 
as pre-written and compiled software that is blindly executed by machines and 
stacked foundational code that has no idea what it is processing, can only 
process linearly, all semantics have been stripped, it doesn't learn from 
experience or react to context unless this too has been pre-codified and frozen 
in binary or byte code, etc. etc etc.  Hardware has been souped up.  So our 
little wrote tricks can be made more elaborate within the substantial confines 
mentioned.  These same in-paradigm restrictions apply to both the software 
users slog through and the software we use to write software.

As a result, these very plastic machines with mercurial potential are reduced 
to simple players that react to user interrupts.  They are sequencing systems, 
not unlike the lead type setting racks of Guttenburg-era printing presses.  
Sure we have taught them some interesting seeming tricks – if you can represent 
something as digital media, be it sound, video, multi-dimentional graph space, 
markup – our sequencer doesn't know enough to care.

Current processors are capable of 6.5 million instructions per second but are 
used less than a billionth of available cycles by the standard users running 
standard software.    The current paradigm absolutely abhors processor access 
not initiated by user input.  But even if it had the inclination to get some 
work down on its own… what would it do?  It doesn't know anything about 
anything so deciding what to do as the day progresses is impossible.

As regards photo editing software, anyone aware of the history of image 
processing will recognize that most of the stuff seen in photoshop and other 
programs was proposed and executed on systems long before some guys in france 
democratized these algorithms for consumer use and had their code acquired by 
adobe.  It used to be called array arithmetic and applied smoothly to images 
divided up into a grid of pixels.  None of these systems "see" an image for its 
content except as an array of numbers that can be crunched sequentially like a 
spread sheet.

It was only when object recognition concepts were applied to photos that any 
kind of compositional grammar could be extracted from an image and compared as 
parts to other images similarly decomposed.  This is a form of semantic 
processing and has its parallels in other media like text parsers and sound 
analysis software.

Semantics opens the door to the building of systems that "understand" the 
content they process.  That is the promised second revolution in computation 
that really hasn't seen any practical light of day as of yet.  Data mining 
really isn't semantically mindful, simply uses statistical reduction mechanisms 
to guess at the existence of the location of pattern ( a good first step but 
missing the grammatical hierarchy necessary to work towards a self optimized 
and domain independent ability to detect and represent salience in the stacked 
grammar that makes up any complex system.

Such systems will need to work all of the time.  ALL OF THE TIME!  Only pausing 
momentarily to pay attention to our interactions as needed.  Once they are 
running, these systems will subsume all of the manual activity we have been 
made to perform to this day.  Think "fly by wire" for processing.  Gone is the 
need to discreetly encode every single bit in exactly the only possible 
sequence.  We simply wont be able to know what bits are being processed, who or 
what made them, and more importantly, we won't have to care.

What it means is the difference between writing a letter and our computer 
interceding by understanding the meta-intent of the wrote and inefficient 
processes we engage in today – what are letters for?  What resources is this 
user or entity after and why?  Who has those resources?  Whom of those who have 
the desired resources need something that we might have in exchange?  How are 
the vectors of intent among all entities entangled and grouped and how can our 
systems work towards the optimization of this global intent matrix?

So, when I use the word "revisionist" I am calling attention to the old sheep 
dressed up in new clothing but still being sheep.  Software feature creep is 
not really evolving software.  As the good programmers at REV know, most of the 
work to maintain a product is incurred just keeping current of changes in the 
OS substrate on which they run.  This rarely results in qualitative paradigm 
jumps.

That the jump is so long in coming is understandable.  It is easy to send a 
punch card through a machine and have it react accordingly every time.  The 
jump from wrote execution of static code to self aware semantically self 
optimized pattern engines is a big big big jump.  But it isn't as big as it 
might at first seem.  It is happening.  It will happen.  And computing will 
finally result in the kind of substantial increase in productivity that its 
expense requires.

Randall Reetz


On May 2, 2010, at 12:32 PM, Ian Wood wrote:

> 
> On 2 May 2010, at 20:13, Randall Lee Reetz wrote:
> 
>> So, how about some content?  A substantive rebuttal?  Putting your ideas out 
>> there for all to see?
> 
> How about replying to direct questions asked of you, for instance why facial 
> recognition is revolutionary but content-aware fill isn't? Or why the 
> examples of things facial recognition is being used for *now* in consumer 
> products is 'Almost nothing'.
> 
> It would also be useful if you could explain what you mean by revisionist 
> applications. I *assume* you are talking about apps that are evolutionary 
> rather than revolutionary in how they change what people do with them, but 
> it's not clear and 'revisionist' has some very specific connotations.
> 
> Ian
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