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When Will My Computer Understand Me?
aarondubrow writes "For more than 50 years, linguists and computer scientists have tried to get computers to understand human language by programming semantics as software, with mixed results. Enabled by supercomputers at the Texas Advanced Computing Center, University of Texas researchers are using new methods to more accurately represent language so computers can interpret it. Recently, they were awarded a grant from DARPA to combine distributional representation of word meanings with Markov logic networks to better capture the human understanding of language."
Actually, that would be considerably easier and cheaper to implement.
Instead of trying to build computers that can understand us, we should be building computers that can learn based on stimuli. If a computer can somehow see, and hear, at the very least and it could somehow capture this information and then over time, develop algorithms to make sense of these things. You know.. the code it would generate could then be used ... Anyways, sounds crazy, but, to me, it makes more sense that way. After all, we didn't just 'communicate' instantly, we learned over time.
It was on Star Trek only because tv and movies are dialogue driven media. But in reality voice limits input
Take the Siri sports example
Ask for your team scores
Get scores
Open app for detailed sports news
Or just open the app and get the scores and news in one step. Same with any other data. Modern GUI's can present a lot more data faster than using voice to ask for the data
voice recognition will need to be a lot better
I was going to say, your computer trying to understand you is probably like a man trying to understand a woman. Not likely to happen any time soon.
I do not fail; I succeed at finding out what does not work.
I'm struck by how much more accurate and responsive Dragon Naturally Speaking was in 1999 on my Pentium 2 than is Siri on my iPhone 5 and Apple's cloud servers today. Maybe it's a microphone problem, but in that case why was the $4.99 tiny microphone from Radioshack in 1999 better than the microphone in my iPhone 5 today?
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M-x doctor
Other people don't understand WTF you're talking about either, they're just better at faking it.
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Each time I've researched NLP solutions, the full sensory experience is ultimately found to play a role in full context and meaning. This begins in a very tight locale, and expands outward, or hopping around locations/time as part of context.
Instead, when most solutions attempt to pick a "general corpus" of a language, they pick such a general version of the language that contextual associations are difficult to follow for any conversation. Even the most ubiquitous vocabulary, such as in national broadcast news, there are assumptions that point all the way back to simplistic models of our experiences via sight/hearing, taste/smell, touch/movement and planning/expectation. Even in our best attempts, nothing such as metaphor or allusion is followed well, and only the most robotic - formal - language understood. This interaction is certainly nothing "natural".
I don't believe NLP problems will be (as easily) solved until we begin to solve the "general stimulus" for input, storage, searching and recall across the senses that humans have - their true "natural" habitat that language is describing. So that when apple goes from "round" to "red" to "about 4in" to "computer" to "beatles" to "not yet in season here" to "sometimes bitter" to "my favorite of grandma's pies", etc - and onward, like potential quantum states until the rest of the conversation collapses most of them - we may be able to get a computer to really understand natural language. This isn't possible in just the manipulation of pieces of text and pointers.
When computer scientist guys understand what it means to understand. Go read some epistemology books. You'll understand.
Dave's not here man!
You thought I was going to make a HAL quote, didn't you?
When will your computer understand you? Not for awhile.
Speech recognition is a part of AI, to the extent that the computer understands what you're saying. Sure, programs like SIRI or ELIZA can put words together, but only so long as we can anticipate the form and context of the question. SIRI only knows about the things it has been programmed to do, which is (unfortunately) not nearly the amount we expect an intelligence to do.
AI has languished for about 60 years now, mostly because it is not a science. There is no formal definition of intelligence, and no roadmap for what to study. As a result, the field studies everything-and-the-kitchen-sink and says: "this is AI!".
Contrast with, for example, Complexity: a straightforward definition drives a rich field of study, producing many interesting results.
In this particular misguided example, they are using Markov logic networks, even though the human brain does not make the Markov assumption(*). We have no definition for intelligence, and the model they work on is demonstrably different from the only real-world example we know of. This may be interesting mathematical research, but it isn't about AI.
Not to worry - most AI research isn't really related to AI.
This is why your computer doesn't understand you, and won't for quite some time.
(*) Check out Priming and note that psychologists have measured priming effects three days (!) after the initial stimulus.
Is the current "lack" of power of current computers an excuse for not being able to make a "clever" computer? In other words, is main the problem computer power or is it the design of algorithms that run on the computer (Power vs method)? Hard to say until someone realizes that clever computer, but the recent "history" of electronic devices would let me think the problem is the method (algorithm).
Slashdot, fix the reply notifications... You won't get away with it...
It would make for better TV too.
"He is so stupid. And now back to the wall!" Moe Szyslak
Sure, because
Computer, insert line... int line counter plus equals copy to tables bracket tables dot primary, comma tables uh, arrow thingy... last... comma sequelconne... no no, not that, erase last... ess que ell connection comma date helper bracket current date time bracket brack... uh, close bracket comma get cutoff bracket close bracket close bracket, semicolon.
Sounds so much easier than a keyboard and autocomplete.
Of course I know that, I was going for funny. I think it'll take getting computers a lot closer to the complexity of the human brain (and maybe something totally different than the current digital computers) before AI really starts working.
That's not what he is taking about. Have a look at this video of Steve Jobs is hacking together a database app by some drag&drop on a NeXTStep machine 20 years ago to get a sense of what he is getting at.
It's not like the computing world hasn't made any progress, as a lot of the stuff demoed back then is now more or less common place in every OS, which wasn't the case back then, but at least as far as desktops are concerned we haven't really made much progress beyond that. Human/computer interaction is still much the same as demoed back then.