I remember COBOL, though fortunately, I never had to code in it.

I think that people who make statements like this significantly underestimate the complexity and ambiguity of natural language. There is a tendency to think that all terms are as well-defined as mathematical language.

Certainly, understanding language at the level of James Joyce or most "art" poetry is beyond the reach of current AI, and everyday language is almost as complex in semantics.

I read a book about musical interpretation that stated that the notation conveyed about 35% of the composer's intent, and the performer had to supply the rest by learning about context. Where the author got that number from is unknown, but it seems about right for understanding language as well. Of course, spoken language is more ambiguous and incomplete than written language, which is way more complicated than any coding language.

As an illustration, the dictionary used by WL has about 35,000 words, and is about at the level as one of those cheap paperback dictionaries students used to use. To make any sense of English in its full expression, you really need the equivalent of the Oxford English Dictionary, which has 800,000 words, plus historical context and multiple definitions for many words. As I recall, the definition for "is" runs for several pages.

One of the primary complaints of programmers (not just newbies) is that the program did what they typed, not what they meant. We can tell a person "you know what I mean" and most of the time they do, despite syntax errors and ambiguity, because of a shared cultural history and years of experience. I don't think that a computer will have an equal level of understanding until it can share the same cultural history and experience.

It is a constant source of frustration that W|A does not return what I expect in may cases. I have had many discussions about this issue with tech support since the service was implemented.

In addition, The W|A "universe" is a small subset of common discourse. You get far too many "I am not programmed to respond in that area" - type answers to too many queries, even what may be considered to be technical inquiries.

W|A does a fairly good job at providing the type of information that was in the old CRC handbooks or a decent almanac. You need patience to phrase the query in the form that W|A's parsers can handle.

However, this is by no means close to the type of natural language discourse.

I will know that there has been progress when you can ask W|A (probably its descendant) about the meaning of a phrase from Finnegan's Wake, and have it provide a meaningful answer on the fly (that is, not a canned response from a human authority).

For now, I am satisfied that it is a decent interface to the CRC tables and Information Please, and this is a major accomplishment. However, it does not cover the full range of natural language.

[quote="Morton Goldberg, Retired"] Please provide a reference to the quotation that appears in your question. I would to know the author, where it was published/expressed and its date. [/quote]

@Morton Goldberg,

The following link is the reference to the quotation that appears in my question: https://forum.osdev.org/viewtopic.php?p=286902#p286902

[quote="George Woodrow III, Freelance Mathematician"] I think that people who make statements like this significantly underestimate the complexity and ambiguity of natural language. [/quote]

@George Woodrow III, An intelligent compiler will ask for clarification whenever there’s an ambiguity and may suggest improved wordings to resolve the issue. Writing a program will end up being a conversation with an intelligent machine which anyone could handle even if they know nothing about programming - it will be a collaboration with an intelligent system which is in itself an expert programmer. The error messages will be comments and questions just like the ones you’d get if you were co-writing a program with a human programmer. (“When you say “print the result of that part”, do you mean this part [a section of the code is highlighted], and do you want it printed to the screen or the printer?”)

None of that will stop you putting in a line of C or any other programming language if you want to, but most of the work will simply be done in natural language, typically at a much higher level with the compiler working out how to carry out the tasks asked of it. The end user will also become a programmer, telling the machine how (s)he would prefer things to be done, and the machine will comply. That will rarely be done through anything other than natural language.

Where natural language is ambiguous, the machine can simply ask for clarification to make sure it has understood the instruction the right way, and if it hasn’t, it can help the programmer improve the wording of the instruction.

Wolfram Language programmers are using human language level programming?

no. I have been using Mathematica for 29+ years, and I can state unequivocally that it is not a human level language.

If you consider a scale where 0 is machine-code and 1 is "star-trek" style programming, I'd guess we are at about a 0.1 level. Compared to assembly code (which I programmed in), Wolfram Language is a big advance, and even compared to c or Swift, it is more expressive, but is is by no means even close to human level language.

Each era has its own hype about "natural language programming", and certainly COBOL was more natural than Assembly or even FORTRAN, and so forth. This is understandable, of course, but it is still hype.

I have started reading a book that may be pertinent to this thread:

Language at the Speed of Sight: How We Read, Why So many Can't, and What Can Be Done About It

Mark Seidenberg, Basic Books, 2017

I have only completed the first couple of chapters, but the discussion is quite relevant to this topic. Later chapters focus on how we learn to read, and that may be relevant for a different reason.

The examples that the author uses makes it clear that it is not just the inability of AI to recognize common metaphors, but the more immediate ambiguities of language that are at issue in "natural" language processing. Things such as words that different meaning depending on which syllables get an accent make AI understanding difficult.

My concern here is that people in the field (as well as people merely wanting to exploit the nascent technology) end up redefining the term to mean something that is currently tractable with current technology, and forgetting that it is a small subset of everyday language.

I believe that Wittgenstein discusses this problem in his Blue and Brown books or Philosophical Investigations, but it's been a while and I cannot recall exactly what he said. It is on my list of things to do to re-read this material.

Anyway, the book I recommend is quite interesting.

I'm unsure if Apple Siri (or MS Cortana) is enabled in mm to do anything beyond allow use as typing or simple commands (ie, if integrate is in it's vocab of having loaded special actions).

All language becomes binary, and conversion time is an issue. Coders don't like being "too distant" from machine level programming because there is the real possibility that algorithms made never finish (big O). Simplicity is good in limited situations - mathematica's power goes far beyond the simple side of things.

unix SH (bash) if i remember was developed by nasa engineers to be a human readable script because previous language used had more than once caused "an issue" due to legibility. mm has better legibility than sh, of course :)

you can say "let's add a bot" that understands i'm doing a specific school book problem. that's allot of bots - and could end up being gigabytes of extra install

you can say "let's add some chemistry formula and computation" or "celestial sciences" and they did: it's kept out of the normal distribution (it pulls the package upon request) because it's just too big. and some of the data owners also don't agree to give users rights to "just download and keep" it all.

a better question is how, with terrabyte drives, we are still in a position of "trying to stay thin" ?

Hi guys,

This is very interesting discussion for me. And educating too. I have no professional knowledge in Computer sciences nor in Mathematics nor in Linguistics. I am just an ordinary man who struggles with learning of English. If you allow me to speak I will say(just my unprofessional opinion):

I don't know what Language is(natural/programming language). But I want to know what Simple sentence is(as a unit of Language).

The root of the problem(as I see it) are poor definitions of:

• simple sentence;

• preposition;

• conjunction;

• grammatical case;

• "Definition is ... ." and so on.

Also I find term AI somehow confusing for me. Isn't the goal building of a Conscious machine and not a machine with Artificial Consciousness?

Here is a thought: there isn't Language (by itself/per se).

For every complex problem there is an answer that is clear, simple and wrong. /H. L. Mencken/

I believe that for every right question there is an answer that is clear, simple and right. /if you can't find the right answer, you have probably been asking the wrong question/

So, if there isn't Language( by itself), what is Simple sentence then? If we can't find answer of what is Consciousness, we have probably been using wrong definitions and wrong set of initial/basic terms.

Thank you and have a nice day.