Here's a big one: Levels of abstraction.
I assume many of you are using a GUI mail client to read this. You're 
interacting with it in terms of windows, panels, boxes, buttons, menus, 
dragging and dropping.
The GUI was written in terms of a toolkit that implements those concepts on 
top of an ontology involving events, queues, processes, locks, mutexes, and 
so forth. The program using the toolkit uses other libraries that are about 
rfc822-format messages, mime extensions, POP mailboxes, and the like.
Typically, the programs and many of the libraries are written in programming 
languages which offer a model providing concepts like objects, methods, and 
functions. These in turn are based on lower-level languages where records, 
pointers, and memory allocation are the order of the day. In order to write 
code in any of this you have to understand, at least implicitly, the syntax 
of the language and use the translator that reads your code and compiles it 
into some internal form, using (most likely) an automatically generated 
shift-reduce parser. At some stage further down, the result will be assembly 
language for the machine you're running on, and then binary machine language.
(And note that I somehow managed to leave out the entire level of the OS and 
hardware drivers and interrupt-level programming).
There's just a big a stack of abstractions standing between the machine 
language and the transistors, in the machine architecture. 

Most AI (including a lot of what gets talked about here) is the equivalent of 
trying to implement the mail-reader directly in machine code (or transistors, 
for connectionists). Why people can't get the notion that the brain is going 
to be at least as ontologically deep as a desktop GUI is beyond me, but it's 
pretty much universal.

Josh

On Sunday 10 June 2007 05:49:36 am Mike Tintner wrote:
> Josh: If you want to understand why existing approaches to AI haven't 
> worked, try
> Beyond AI by yours truly
> 
> Any major point or points worth raising here? 

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