Steve, I just read the first message in this thread. Yes, successive layers of speech may be necessary to determine what is being referenced. And of course having other information from other IO modalities about the referent would help. But first we have to figure out a way to do it with a computer. I think the idea I have in mind can be examined with examples. When you mentioned "payload" I had a pretty good idea about how you wanted to use the word. However, when you started off by saying that computerized text understanding is very similar to patent classification I realized that I did not have a good idea about the methodology of understanding that you were associating with the word. So I inhibited myself from making any assumptions about the words that you were using until I had a chance to reread what you were saying.
As I wrote, my new theory of understanding is based on acquiring insight into the specialization of the concepts that are being considered. So, while your use of the term payload to refer to something that I might call the semantic content or the intended meaning was not that different from what I thought you meant, your underlying theory about discovering the meaning was. Yes, if we don't understand something we need to speak about it with different kinds of remarks (or study it in other ways). However, I disagree that these are successive layers where all the details of differentiation of speech can be found on some bottom-level subclass. I just don't think it is that simple. My latest model of comprehension is that the complexity of knowledge is only found in a growing awareness of conceptual specialization (where concepts are either based on a group of shared concepts or from a process of observation and conjecture tied to some personal concepts. In other words we can build higher models by communicating or by using our imaginations.) In my opinion, the basis of differentiation or specialization will not be found in some bottom-level subclass but in examining some construct of thought using different ways to think about it. I now have a simplified model of what you were talking about in my mind. I can generalize this. I see you believe that there is a hierarchy of detail which would reveal the specialized meanings of words. I will remember this about you and look for it in other ideas that you talk about and I will look for in other people's ideas. (I disagree with the single hierarchy, a general hierarchy of differentiation and the bottom-level full of details. To my thinking these are metaphors which are standing in as substitutes for effective methods.) I did not have a substantial disagreement with most of the other things you said in this, the first message of this thread. The fact that you mentioned that an inability to precisely understand what someone said might lead to a mistaken misinterpretation of ignorance was a confirmation of my opinion that you can be open-minded and that you are able to use this ability to discover a context of misunderstanding in ways that some people are not. By being open minded one can see possibilities that closed-minded people may miss. This is an example of a conceptual specialization and it can be tied into the meaning of language even when the language is not about the subject of being open close minded. Jim On Thu, Mar 28, 2013 at 12:27 AM, Steve Richfield <[email protected] > wrote > > *Jim, et al,* > > *I'm starting a new thread with this...* > > It is my theory that computerized speech and text understanding has eluded > developers for the past ~40 years, because of a lack of a fundamental > understanding of the task, which turns out to be very similar to patent > classification. > > When classifying a patent, successive layers of sub-classification are > established, until only unique details distinguish one patent from another > in the bottom-level subclass. When reviewing the sub-classifications that a > particular patent is filed within, combined with the patent’s title, what > the patent is all about usually becomes apparent to anyone skilled in the > art. > > However, when a patent is filed into a different patent filing system, > e.g. filed in a different country where the sub-classifications may be > quite different, it may be possible that the claims overlap the claims of > other patents, and/or unclaimed disclosure would be patentable in a > different country. > > Similarly, when you speak or write, in your own mind, most of your words > are there to place a particular “payload” of information into its proper > context, much as patent disclosures place claims into the state of an art. > However, your listeners or readers may have a very different context in > which to file your words. They must pick and choose from your words in an > effort to place some of your words into their own context. What they end up > placing may not even be the “payload” you intended, but may be words you > only meant for placement. Where no placement seems possible, they might > simply ignore your words and file *you* as being ignorant or deranged. > > Many teachers have recorded a classroom presentation and transcribed the > recording, only to be quite surprised at what they actually said, which can > sometimes be the opposite of what they meant to say. Somehow the class > understood what they meant to say, even though their statement was quite > flawed. When you look at these situations, the placement words were > adequate, though imperfect, but the payload was okay. Indeed, where another > person’s world model is nearly identical to yours, very few placement words > are needed, and so these words are often omitted in casual speech. > > These omitted words fracture the structure of around half of all sentences > “in the wild”, rendering computerized parsing impossible. Major projects, > like the Russian Academy of Science’s Russian Translator project, have > wrestled with this challenge for more than a decade, with each new approach > producing a better result. The results are still far short of human > understanding due to the lack of a human-level domain context to guide the > identification and replacement of omitted words. > > As people speak or write to a computer, the computer must necessarily have > a *very* different point of view to even be useful. The computer must be > able to address issues that you can not successfully address yourself, so > its knowledge must necessarily exceed your own in its subject domain. This > leads to some curious conclusions: > > 1. Some of your placement words will probably be interpreted as > “statements of ignorance” by the computer and so be processed as valuable > payload to teach you. > > 2. Some of your placement words will probably refer to things outside of > the computer’s domain, and so must be ignored, other than being recognized > as non-understandable restrictions on the payload, that may itself be > impossible to isolate. > > 3. Some of your intended “payload” words must serve as placement, > especially for statements of ignorance. > > My invention seeks to intercept words written to other people who > presumably have substantial common domain knowledge. Further, the computer > seeks to compose human-appearing responses, despite its necessarily > different point of view and lack of original domain knowledge. While this > is simply not possible for the vast majority of writings, the computer can > simply ignore everything that it is unable to usefully respond to. > > If you speak a foreign language, especially if you don’t speak it well, > you will immediately recognize this situation as being all too common when > listening to others with greater language skills than your own speaking > among themselves. The best you can do is to quietly listen until some point > in the conversation when you understand enough of what they are saying, and > you have something useful to add to the conversation. > > Note the similarity to the advertising within the present Google Mail, > where they select advertisements based upon the content of email that is > being displayed. Had Google performed a deeper analysis they could probably > eliminate ~99% of the ads as not relating to users’ needs and greatly > improve the users’ experience, and customize the remaining 1% of the ads to > precisely target the users. > > That is very much the goal with my invention, where the computer knows > about certain products and solutions to common problems, etc., and scans > the vastness of the Internet to find people whose words have stated or > implied a need for things in the computer’s knowledge base, and have done > so in terms that the computer can “understand”. > Steve > ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-f452e424 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-58d57657 Powered by Listbox: http://www.listbox.com
