Live data from Hacker News

A Simple AI Capable of Basic Reading Comprehension

blog.ayoungprogrammer.com

31–40 of 64 posts

Re: A Simple AI Capable of Basic Reading Comprehension

#31

Not to be discouraging, but I think research along these lines http://arxiv.org/abs/1503.08895 stands an exponentially better chance of leading towards what OP is talking about. For anyone interested in "building AI", read that paper and all it's references.

You know, high order logic memories are a completely different kind of intelligence, that, if somebody makes it work, can be much more capable than plain pattern matching techniques.

Granted that it's a fundamentally more difficult problem, so the pattern matching will probably get there earlier.

Re: A Simple AI Capable of Basic Reading Comprehension

#32

Some thoughts about creating a system like this: Any successful implementation of comprehension must progressively enhance the world model based on additional information. Furthermore it must understand some basic rules, such as, "Any subject, set of subjects, or actions can be represented multiple ways." So if you said, "Mary's brother is Sam," or "Mary has a brother named Sam," or "Mary's brother is named Sam," the…

Not only this, the system would have to maintain multiple levels of world models and simulate them as well. Consider a sentence: "If he goes there, and then she does not reach in time, he will surely be disappointed."

There has to be a hierarchy of world models, and only the bottom-most layer would be the "real" one. Any kind of planning will require simulating hypothetical worlds.

Re: A Simple AI Capable of Basic Reading Comprehension

#33
post #26
post #14

Earlier quoted context omitted.

When was that xkcd posted? - couldn't not find a date. Since machine vision is such a fast moving field, I think date is relevant for understanding the context of this xkcd. Is image recognition of a bird so inconceivable at the moment? Perhaps the joke now would be - "I'll need one researcher and one year"

You are taking the xkcd strip very literally instead of understanding the central concept on it. You comment reminds me of this: http://www.uh.edu/engines/epi879.htm

Just pointing to the fact that 'Virtually impossible in CS' is a concept that changes over time. The better the context the better the joke.

Re: A Simple AI Capable of Basic Reading Comprehension

#34

I was intrigued by the initial transcript, but disappointed that it was edited (lightly). For the question "Why did Mary cheer?" the screenshot showed that the simple AI literally answered "because IT be HER FIRST TIME WINNING". This is correct, but the author edited it into a correct sentence for us. I think it is too much to call this "capable of basic reading comprehension". Surely, "simple sentence parser can ans…

> I was intrigued by the initial transcript, but disappointed that it was edited (lightly). For the question "Why did Mary cheer?" the screenshot showed that the simple AI literally answered "because IT be HER FIRST TIME WINNING". This is correct, but the author edited it into a correct sentence for us. For some reason, the library I used to get the present tense of "was" is "be". I had a manually fix for this but ac…

  > Would you say that 14-line Perl program is capable of
  basic reading comprehension? I wouldn't!

  I would say it is not because it does not understanding the 
  relation between objects; it only understands that sentences   
  starting with "why" should be answered with everything after 
  the string "because". Also, in your program, if there are 
  two instances of "because" in the source, your program will 
  only choose the first one.
This line is arbitrary. These programs aren't "understanding" anything, they are just able to generate different facts. Your "AI" is very input-dependent too, which was his point.

I am still bothered by the title, as your program doesn't "comprehend" the text -- only you do that. Your program restructures the text and answers to a very limited querying mechanism; there's no comprehension, only information retrieval. They're not the same. Knowledge Graph and Freebase are comparable (/ much larger) efforts.

Re: A Simple AI Capable of Basic Reading Comprehension

#35

The difference between this graph and propositional logic is only that the predicates joining concepts are arbitrary instead of logic operators. In that sense, this is like Google Knowledge Graph / Freebase. https://en.wikipedia.org/wiki/Propositional_calculus#Solvers Solving a set of propositional logic statements is NP-Complete. I'd argue "reading comprehension" is actually knowing the state of the world after a pi…

Classic example:

    The iron ball fell on the glass table, and it shattered.
    The glass ball fell on the iron table, and it shattered.
Human readers will pick the correct antecedent for "it" in each case, so it's not ambiguous. But correct interpretation depends on knowing something about how likely glass and iron are to shatter.

I love these kinds of examples, but I don't think they ought to significantly deter the kind of work shown here; it depends on the application, but basic interpretation could be very useful even if it can't handle every case.

Re: A Simple AI Capable of Basic Reading Comprehension

#36

I was intrigued by the initial transcript, but disappointed that it was edited (lightly). For the question "Why did Mary cheer?" the screenshot showed that the simple AI literally answered "because IT be HER FIRST TIME WINNING". This is correct, but the author edited it into a correct sentence for us. I think it is too much to call this "capable of basic reading comprehension". Surely, "simple sentence parser can ans…

>I think it is too much to call this "capable of basic reading comprehension". Surely, "simple sentence parser can answer reading comprehension questions" would be more correct? We test whether a human have "basic reading comprehension" by asking them reading comprehension questions. If they answer the questions successfully, then we assume that they have this "reading comprehension" skill. Therefore, if an AI can an…

We test human "reading comprehension" with the assumption that humans have an underlying world model.

This is starkly different from a machine whose only ability is information retrieval -- this program (and more advanced versions e.g Freebase) parse and restructure text to be more retrievable. But there is no comprehension because there is no world model.

You wouldn't call parsing a google search query "reading comprehension."

Re: A Simple AI Capable of Basic Reading Comprehension

#37

I was intrigued by the initial transcript, but disappointed that it was edited (lightly). For the question "Why did Mary cheer?" the screenshot showed that the simple AI literally answered "because IT be HER FIRST TIME WINNING". This is correct, but the author edited it into a correct sentence for us. I think it is too much to call this "capable of basic reading comprehension". Surely, "simple sentence parser can ans…

> I was intrigued by the initial transcript, but disappointed that it was edited (lightly). For the question "Why did Mary cheer?" the screenshot showed that the simple AI literally answered "because IT be HER FIRST TIME WINNING". This is correct, but the author edited it into a correct sentence for us. For some reason, the library I used to get the present tense of "was" is "be". I had a manually fix for this but ac…

Thanks for the reply! Thanks for sharing your work with us as well. It's impressive.

It's not disappointing, it's quite a feat. I suppose I would say that what I was trying to say is that "parsing", while impressive, is not a large part of "understanding" in my opinion. To use an analogy: almost by definition, compilers parse languages like C++ much better than humans do (basically perfectly, unless there's literally a bug in the compiler or it doesn't follow the standard due to some error).

But that doesn't mean they understand the programs (at all.) A compiler has no idea on an algorithmic level what a program might be doing (and if you remove comments, maybe a person won't understand it either, if they're not familiar with the algorithm.)

So my basic objection is that you're really calling this reading comprehension, but I don't think anything is actually being "understood"; just parsed. A better title would be as I suggested: simple AI correctly answers reading comprehension questions.

The reason that I object to "comprehension" is that these days there really are a few "deep learning" systems, that can possibly synthesize information. (I don't know that much about them.) I don't think it's fair to elevate semantic parsing to the level of comprehension.

However the comment by tariqali34 makes a good point, that perhaps this is a criticism of reading comprehension tests. I know in multiple-choice tests from standardized exams, I've been able to correctly answer reading comprehension questions about texts that I didn't even read (by finding just the sentence that talks about it), or in other cases, texts that were too technical and that I didn't understand.

I would say that I would be able to answer a question about some biomedical excerpt that I can't understand a word of, I just can't make heads or tails of it, let's say:

In order to study the physiological roles of AGC kinases, a commonly used approach has been to over-express the active forms in cells. However, due to the overlapping substrate specificities of many AGC kinases, it is likely that the over-expression of one member of this kinase subfamily will result in the phosphorylation of substrates that are normally phosphorylated by another AGC kinase. Another strategy has been to over-express catalytically inactive ‘dominant negative’ mutants of AGC kinases in cells. However, such mutants are likely to interact with and inhibit the upstream protein kinase(s) that they are is activated by, and thus prevent the ‘upstream’ kinase(s) from phosphorylation of other cellular substrates. For example, a dominant negative RSK may interact with ERK1/ERK2 preventing the activation of MSK isoforms and hence the phosphorylation of CREB (cAMP-response-element-binding protein) [9]. Furthermore, in Saccharomyces cerevisiae, over-expression of catalytically inactive Rck2p, a kinase that binds to and is activated by the Hog1P MAPK, sequestered the substrate-docking site of the Hog1P kinase, thereby preventing Hog1P from interacting with other substrates. Thus catalytically inactive Rck2P is acting as a dominant negative mutant of Hog1P and not Rck2P.

I couldn't answer a REAL reading-comprehension test about this: I just have no idea what it's REALLY talking about, I don't actually understand it. (Obviously on a syntactic level, it's not hard to parse.) I don't know what over-expression is, I don't know what a kinase is, I don't know what phosphorylation is. I don't understand the text. But if the questions are simple, perhaps I could answer some reading comprehension questions about this by parroting back quotations from it. Syntactically, there's nothing difficult here. I just don't understand it.

So I think it's unfair to call sentence parsing real reading comprehension, even if sometimes reading comprehension tests fail to differentiate between the two. You can parse sentences perfectly while understanding nothing. For example, I could answer the question "what is wrong with studying the physiological role of AGC kinases by overexpressing the active forms in cells?" which the first sentence refers to. I can just quote the second sentence "Due to the overlapping substrate specificities of many AGC kinases, it is likely that the over-expression of one member of this kinase subfamily will result in the phosphorylation of substrates that are normally phosphorylated by another AGC kinase". I don't understand, but I think I correctly parroted.

So there are real issues in determining comprehension. The higher the level of the question that is asked, the harder it is to answer without actually understanding the text.

I did find your work very interesting, thank you.

Re: A Simple AI Capable of Basic Reading Comprehension

#38
post #29
post #14

Earlier quoted context omitted.

When was that xkcd posted? - couldn't not find a date. Since machine vision is such a fast moving field, I think date is relevant for understanding the context of this xkcd. Is image recognition of a bird so inconceivable at the moment? Perhaps the joke now would be - "I'll need one researcher and one year"

Yeah, Randy was a bit miscalculating the estimate there. Within a month of that comic, flickr made http://code.flickr.net/2014/10/20/introducing-flickr-park-or...

Within a month they put forth an app, based on work they had already been doing for some time.

With a team of (unknown).

Re: A Simple AI Capable of Basic Reading Comprehension

#39
post #14

I love the ambition. But when you stated your next goals, I'm afraid I thought of this: http://xkcd.com/1425/ I may very well be wrong, and I'd love it if you showed me I am. Good luck. As I said, I really would be excited to see this go farther.

When was that xkcd posted? - couldn't not find a date. Since machine vision is such a fast moving field, I think date is relevant for understanding the context of this xkcd. Is image recognition of a bird so inconceivable at the moment? Perhaps the joke now would be - "I'll need one researcher and one year"

September 24, 2014

Re: A Simple AI Capable of Basic Reading Comprehension

#40
post #35

The difference between this graph and propositional logic is only that the predicates joining concepts are arbitrary instead of logic operators. In that sense, this is like Google Knowledge Graph / Freebase. https://en.wikipedia.org/wiki/Propositional_calculus#Solvers Solving a set of propositional logic statements is NP-Complete. I'd argue "reading comprehension" is actually knowing the state of the world after a pi…

Classic example: The iron ball fell on the glass table, and it shattered. The glass ball fell on the iron table, and it shattered. Human readers will pick the correct antecedent for "it" in each case, so it's not ambiguous. But correct interpretation depends on knowing something about how likely glass and iron are to shatter. I love these kinds of examples, but I don't think they ought to significantly deter the kind…

Yeah, it's a bit of a nitpick over definition of "comprehension" but the program itself is obviously useful, I mean it's a poor man's version of Freebase. Freebase/Google Knowledge Graph doesn't claim to "comprehend" anything, it is just a large graph datastructure with an efficient querying mechanism. That's what this is (...given this is a poor man's version, efficient querying mechanism may be lacking for larger graphs)
Post reply on HN