[Semi OT] The programming language wars

[Joakim via Digitalmars-d]

On Saturday, 21 March 2015 at 20:51:52 UTC, FG wrote:
> But if you look at my function definition, it doesn't have 
> that, nor does it use parentheses, semicolons, etc., so it's 
> "voice-ready". My question is: at which point would that be 
> considered an efficient method to define a program's component 
> that we would choose to use instead of the current succinct 
> symbolic notation?

We will probably keep some variation on the current textual 
symbolic notation but develop verbal shorthand and IDEs that 
enable faster programming than even keyboards allow today.

> Yeah, right, people will create drawings with voice commands. 
> :)  Every interface has its rightful domain and voice ain't 
> best for everything. Or do you mean that touch will go away but 
> instead people will be waving their hands around?

Yes, hand and fingers, as I said before, and you will even be 
able to "paint" in 3D:

https://www.thurrott.com/windows/windows-10/573/hands-microsoft-hololens

On Saturday, 21 March 2015 at 21:46:10 UTC, H. S. Teoh wrote:
> Of course. But we're talking here about interfaces for 
> *programmers*,
> not for your average Joe, for whom a pretty GUI with a button 
> or two
> would suffice.

When you said "I think rodent-based UIs will go the way of the 
dinosaur," you seemed to be talking about more than just 
programmers.

> This is the unpopular opinion, but I'm skeptical if this day 
> will ever
> come. The problem with voice recognition is that it's based on 
> natural
> language, and natural language is inherently ambiguous. You say 
> that
> heuristics can solve this, I call BS on that. Heuristics are 
> bug-prone
> and unreliable (because otherwise they'd be algorithms!), 
> precisely
> because they fail to capture the essence of the problem, but 
> are merely
> crutches to get us mostly there in lieu of an actual solution.

You don't have to handle full "natural language" to handle voice 
input, you can constrain the user to a verbal shorthand for 
certain tasks.  Eventually, you can loosen that requirement as 
the recognition engines get better.  You can never have 
algorithms that handle all the complexity of human speech, 
especially since the speech recognition engine has no 
understanding of what the words actually mean.  But thousands 
upon thousands of heuristics might just do the job.

> The inherent ambiguity in natural language comes not from some 
> kind of
> inherent flaw as most people tend to believe, but it's actually 
> a
> side-effect of the brain's ability at context-sensitive 
> comprehension.
> The exact same utterance, spoken in different contexts, can 
> mean totally
> different things, and the brain has no problem with that 
> (provided it is
> given sufficient context, of course). The brain is also 
> constantly
> optimizing itself -- if it can convey its intended meaning in 
> fewer,
> simpler words, it will prefer to do that instead of going 
> through the
> effort of uttering the full phrase. This is one of the main 
> factors
> behind language change, which happens over time and is mostly
> unconscious.  Long, convoluted phrases, if spoken often enough, 
> tend to
> contract into shorter, sometimes ambiguous, utterances, as long 
> as there
> is sufficient context to disambiguate. This is why we have a 
> tendency
> toward acronyms -- the brain is optimizing away the long 
> utterance in
> preference to a short acronym, which, based on the context of a 
> group of
> speakers who mutually share similar contexts (e.g., computer 
> lingo), is
> unambiguous, but may very well be ambiguous in a wider context. 
> If I
> talk to you about UFCS, you'd immediately understand what I was 
> talking
> about, but if I said that to my wife, she would have no idea 
> what I just
> said -- she may not even realize it's an acronym, because it 
> sounds like
> a malformed sentence "you ...". The only way to disambiguate 
> this kind
> of context-specific utterance is to *share* in that context in 
> the first
> place. Talk to a Java programmer about UFCS, and he probably 
> wouldn't
> know what you just said either, unless he has been reading up 
> on D.

This acronym example is actually fairly easy for the computer to 
handle, given its great memory.  But yes, there are many contexts 
where the meaning of the words is necessary to disambiguate what 
is meant and without some sort of AI, you have to rely on various 
heuristics.

> The only way speech recognition can acquire this level of 
> context in
> order to disambiguate is to customize itself to that specific 
> user -- in
> essence learn his personal lingo, pick up his (sub)culture, 
> learn the
> contexts associated with his areas of interest, even adapt to 
> his
> peculiarities of pronunciation. If software can get to this 
> level, it
> might as well pass the Turing test, 'cos then it'd have enough 
> context
> to carry out an essentially human conversation.  I'd say we're 
> far, far
> from that point today, and it's not clear we'd ever get there.

I'd say we're fairly close, given the vast computing power in 
even our mobile devices these days, and that is nowhere near the 
Turing test, as extracting a bunch of personalized info and 
contextual dictionaries is nowhere close to the complexity of a 
computer generating a human-like answer to any question a human 
asks it.

> We haven't even mastered context-sensitive languages, except 
> via the crutch
> of parsing a context-free grammar and then apply a patchwork of 
> semantic
> analysis after the fact, let alone natural language, which is 
> not only
> context-sensitive but may depend on context outside of the input
> (cultural background, implicit common shared knowledge, etc.). 
> Before we
> can get there, we'd have to grapple with knowledge 
> representation,
> context-sensitive semantics, and all those hard problems that 
> today seem
> to have no tractable solution in sight.

Certain of these can be dealt with by heuristics, others are too 
hard to deal with right now, but likely wouldn't make much of a 
difference in accuracy anyway.

> P.S. Haha, it looks like my Perl script has serendipitously 
> selected a
> quote that captures the inherent ambiguity of natural language 
> -- you
> can't even tell, at a glance, where the verbs are! I'd like to 
> see an
> algorithm parse *that* (and then see it fall flat on its face 
> when I
> actually meant one of the "non-standard" interpretations of it, 
> such as
> if this were in the context of a sci-fi movie where there are 
> insects
> called "time flies"...).

It took me a minute to even figure out what "Fruit flies like a 
banana" meant, as that pair of sentences takes advantage of the 
human heuristic of assuming that two rhyming sentences place 
their verb in the same spot.  But a speech recognition engine 
doesn't _need_ to parse the grammar in those sentences, as it'll 
likely get it just from the pronunciation, so it would likely 
confuse only us humans, who are trying to understand what it 
actually means, and not the computer, which just wants to 
transcribe literally what we said.

On Saturday, 21 March 2015 at 22:00:21 UTC, Ola Fosheim Grøstad 
wrote:
> Right, but it is likely that the nature of programming will 
> change. In the beginning of the web the search engines had 
> trouble matching anything but exact phrases, now they are 
> capable of figuring out what you probably wanted.
>
> Take music composition, people still write notes explicitly as 
> discrete symbols, yet others compose music by recording a song, 
> and then manipulating it (i.e. auto tune). So, even though you 
> can do pitch recognition many probably use discrete interfaces 
> like keyboard or a mouse for writing music, yet new forms of 
> music and composition has come with the ability to process 
> audio in a more intuitive, evolutionary fashion.

Good point, this was a good video from a couple years ago:

http://forum.dlang.org/thread/op.wn0ye9uy54xghj@puck.auriga.bhead.co.uk

On Saturday, 21 March 2015 at 23:58:18 UTC, Laeeth Isharc wrote:
> HS Teoh is right about context, and the superiority of the 
> written word for organizing and expressing thinking at a very 
> high level.  The nature of human memory and perception means 
> that is unlikely to change very soon, if ever.

Nobody is arguing against text, but of the best way to provide it 
to the computer, whether through tapping keys or voicing it.

On Sunday, 22 March 2015 at 09:30:38 UTC, Atila Neves wrote:
> On Friday, 20 March 2015 at 22:55:24 UTC, Laeeth Isharc wrote:
>> There is nothing intrinsically more scientific about basing a 
>> decision on a study rather than experience and judgement 
>> (including aesthetic judgement), which is not to say that more 
>> data cannot be useful,
>
>
> Of course there is. Experience and judgement aren't measurable. 
> You don't have science without numbers.

But it takes experience and judgement to interpret and 
contextualize those numbers, so we are back to square one. :) 
Note that Laeeth specifically said more data can be useful, only 
that one has to be careful that it's the right data, not just 
data that happens to be lying around.