Feature request: Path append operators for strings

John Colvin john.loughran.colvin at gmail.com
Mon Jul 8 03:48:04 PDT 2013

On Monday, 8 July 2013 at 09:02:44 UTC, Tommi wrote:
> On Sunday, 7 July 2013 at 20:35:49 UTC, Walter Bright wrote:
>> On 7/7/2013 8:38 AM, Andrei Alexandrescu wrote:
>>>> All Siri does is recognize a set of stock patterns, just 
>>>> like Eliza. Step out of that, even slightly, and it reverts 
>>>> to a default, again, just like Eliza.
>>>> Of course, Siri had a much larger set of patterns it 
>>>> recognized, but with a bit of experimentation you
>>>> quickly figure out what those stock patterns are.
>>>> There's nothing resembling human understanding there.
>>> But that applies to humans, too - they just have a much 
>>> larger set of patterns they recognize.
>> I don't buy that. Humans don't process data like computers do.
> Humans don't and _can't_ process data like computers do, but 
> computers _can_ process data like humans do.
> Human brain does it's computation in a highly parallel manner, 
> but signals run much slower than they do in computers. What 
> human brain does is a very specific process, optimized for 
> survival on planet Earth.
> But computers are generic computation devices. They can model 
> any computational processes, including the ones that human 
> brain uses (at least once we get some more cores in our 
> computers).
> Disclaimer: I'm basically just paraphrasing stuff I read from 
> "The Singularity Is Near" and "How to Create a Mind".

The human mind being so particularly powerful at some tasks is a 
product of both it's architecture *and* it's training. The 
importance of physical learning in artificial intelligence is 
getting some good recognition these days.

For me, the most interesting question in all of this is "What is 
intelligence?". While that might seem the preserve of 
philosophers, I believe that computers have the ability to (and 
already do) demonstrate new and diverse types of intelligence, 
entirely unlike human intelligence but nonetheless highly 

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