On 7/7/13 6:11 PM, Walter Bright wrote:
> On 7/7/2013 4:03 PM, Andrei Alexandrescu wrote:
>> Similarly, it would be an ignorant thing to say that Siri is just a
>> larger
>> Eliza. There is a world of difference between Eliza's and Siri's
>> approaches. In
>> fact the difference is even larger than between 1970s compilers and
>> today's
>> ones.
>
> I don't know how Siri is implemented. If it is using modern approaches,
> I'd love to sit down with you sometime and learn about it.
>

Zat's the spirit!

Andrei

On 7/7/2013 7:42 PM, Timothee Cour wrote:
> Can't speak for Siri, but the deep learning architecture used in google now has
> little to do with Eliza. Nor is the recognition accuracy. Try it if you haven't!

Can you give some examples demonstrating this?

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".

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 effective.

On Monday, 8 July 2013 at 10:48:05 UTC, John Colvin wrote:
> 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 effective.

A quite fitting quote from "How to Create a Mind", I think:

"American philosopher John Searle (born in 1932) argued recently that Watson is not capable of thinking. Citing his “Chinese room” thought experiment (which I will discuss further inchapter 11), he states that Watson is only manipulating symbols and does not understand the meaning of those symbols.

Actually, Searle is not describing Watson accurately, since its understanding of language is based on hierarchical statistical processes—not the manipulation of symbols. The only way that Searle’s characterization would be accurate is if we considered every step in Watson’s self-organizing processes to be “the manipulation of symbols.” But if that were the case, then the human brain would not be judged capable of thinking either.
It is amusing and ironic when observers criticize Watson for just doing statistical analysis of language as opposed to possessing the “true” understanding of language that humans have. Hierarchical statistical analysis is exactly what the human brain is doing when it is resolving multiple hypotheses based on statistical
inference (and indeed at every level of the neocortical hierarchy). Both Watson and the human brain learn and respond based on a similar approach to hierarchical understanding. In many respects Watson’s knowledge is far more extensive than a human’s; no human can claim to have mastered all of Wikipedia, which is only part of Watson’s knowledge base. Conversely, a human can today master more conceptual levels than Watson, but that is certainly not a permanent gap."

On 7/8/2013 2:02 AM, Tommi wrote:
>> 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).

Except that we have no idea how brains actually work.

Are fruit flies self-aware? Probably not. Are dogs? Definitely. So at what point between fruit flies and dogs does self-awareness start?

We have no idea. None at all.

On Monday, 8 July 2013 at 12:04:14 UTC, Walter Bright wrote:
> Except that we have no idea how brains actually work.
>
> Are fruit flies self-aware? Probably not. Are dogs? Definitely. So at what point between fruit flies and dogs does self-awareness start?
>
> We have no idea. None at all.

+1

Underestimating complexity of human thinking is a tempting mistake to do for a programmer :) Well, to be honest, there are _some_ ideas, but those are more guesses than precise knowledge.

On Monday, 8 July 2013 at 12:04:14 UTC, Walter Bright wrote:
> On 7/8/2013 2:02 AM, Tommi wrote:
>>> 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).
>
> Except that we have no idea how brains actually work.

"How to Create a Mind" makes a pretty convincing argument to the contrary. It's true that we don't have the full picture of how brains work. But both the temporal and spatial resolution of that picture is increasing rapidly with better brain scanners.

> Are fruit flies self-aware? Probably not. Are dogs? Definitely. So at what point between fruit flies and dogs does self-awareness start?
>
> We have no idea. None at all.

"How to Create a Mind" talks plenty of consciousness as well. My personal guess is that consciousness is not a binary property.

I feel I should get some royalties for plugging that book like this.

On Wednesday, 3 July 2013 at 12:24:33 UTC, Wyatt wrote:
> This is something I was discussing with a friend recently, and we agreed it would be cool if there were set of operators with no definition until overloaded, so you could use e.g. (.) for dot product, (*) for cross product, (+) (or maybe [+]?) for matrix add, etc. instead of overloading things that already have specific, well-understood meaning.
>
I'd like to clarify this a little with a concrete example I hit late yesterday.  I have a sparse tree-like recursive struct with an array of children and a single leaf value.  I thought it was fairly simple, but I quickly found the range of common operations I want to support exceeds the limits of orthogonal operations.

Like my opOpAssign!("~") adds the children of the RHS as children of LHS, while the opIndexAssign assigns a leaf value to a child of LHS, and the opIndexOpAssign!("~") makes the entire RHS tree a child of the LHS.  And I'm sure I'm not "done"; but I'm also VERY reluctant to go any further because it's getting ugly fast. (I think I may be able to _somewhat_ work around this with multiple overloads for different types. I haven't tried it, but I think that works?)

Having some way of differentiating the different semantic concepts (i.e. operating on trees vs. operating on leaf values) would be hugely useful for my ability to reason about the code easily.  Not just that, having a way of offsetting them _visually_ would be useful for me to keep track of them and know, at-a-glance, that I'm doing something different; something that's not QUITE like e.g. a concatenation. (As I think I mentioned, I see this as a major factor in favour of some kind of bracing, if not parentheses.)

IMO, it's the sort of thing where almost any non-trivial data structure you manipulate frequently could stand to benefit.  Unfortunately; conversely, I _also_ completely understand that adding more features to the language at this point is a fairly tall order.  Worse, I think this would require some compiler/spec changes.  Or maybe there's a third path I'm not seeing-- I don't know.

All that said, does anyone aside from myself and a few others have strong opinions on this?

-Wyatt

On Monday, 8 July 2013 at 12:04:14 UTC, Walter Bright wrote:
> On 7/8/2013 2:02 AM, Tommi wrote:
>>> 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).
>
> Except that we have no idea how brains actually work.
>
> Are fruit flies self-aware? Probably not. Are dogs? Definitely. So at what point between fruit flies and dogs does self-awareness start?
>
> We have no idea. None at all.

Problem A) Understanding how the human brain processes certain types of information.

Problem B) Making a decision about what constitutes self-awareness and where to draw the line.

Those are not equivalent problems in the slightest.


Ugh, the conciousness guys give the whole field of neuro-biology a bad name. Everyone goes "oh, neuroscience, that's cool, but YOU DON'T UNDERSTAND LOVE AND CONSCIOUSNESS LALALALALALA" because that's the only side the science media ever talk about.