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."
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
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.
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.