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You could use the same argument against pretty much any discipline that's undergoing active research. Of course no-one knows (yet) how to do it properly or else

by kleiba 9y ago

You could use the same argument against pretty much any discipline that's undergoing active research. Of course no-one knows (yet) how to do it properly or else there would be no research going on. Image understanding, robotics, even non-computational disciplines such as medicine... Staying with the latter, take HIV for example: no-one knows how to heal it but I'm sure a lot of people are very grateful for the 80% solutions that prolong lives today. So, in summary, you point is not wrong. But it's no reason for bashing computational linguistics. It is common across many disciplines to use not-yet-perfect solutions as long as you don't know how to do better. That said, I don't fully agree with the notion that "hacking a solution" is the suggested way of doing things. Computational linguistics is a pretty wild field with a lot of sub-disciplines. In a lot of those, the state of the art consists of quite sophisticated approaches that are the result of years of research. Take speech recognition, for instance. Currently, deep learning approaches take the cake, but there is also a plethora of insights that have been gained from improving the traditional methods over decades. I think, a more nuanced point of view is called for here.

boxy310 9y ago
Eh, that really comes down to applied theory vs. pure theory. There's no one Grand Unifying Theory of Natural Language Processing, and not likely to be a strong candidate for a while yet. Until then, there can still be a lot of good problem-solving that can be used with either traditional NLP or with neural networks, or even a hacked-together hybrid approach, and both application and research will feed into each other to refine the processes.
bhaak 9y ago
I didn't intend to bash computational linguistics. Those were some of my favorite course I wouldn't have attended more than I needed if I didn't like the topic and gotten something out of it. It's surprising how often you can get very far with imperfect solutions. ELIZA is the classic example. A simple program with very little code could convince people that they were talking to another human or at least machine with an understanding of their feelings. ELIZA was coded completely by humans. Of course, nowadays we have more sophisticated ways of doing that. We can throw a few topic tagged example sentences with connected replies at a computer and it will mostly reply with the right answers to similar sentences. This is only possible because computational linguistics provided the foundation for that. Still many solution are hacky to this day but that is because computational linguistics is more concerned about interaction with imperfect humans than most of the other disciplines in computer science.

by kleiba 9y ago

boxy310 9y ago

Eh, that really comes down to applied theory vs. pure theory. There's no one Grand Unifying Theory of Natural Language Processing, and not likely to be a strong candidate for a while yet. Until then, there can still be a lot of good problem-solving that can be used with either traditional NLP or with neural networks, or even a hacked-together hybrid approach, and both application and research will feed into each other to refine the processes.

bhaak 9y ago

I didn't intend to bash computational linguistics. Those were some of my favorite course I wouldn't have attended more than I needed if I didn't like the topic and gotten something out of it. It's surprising how often you can get very far with imperfect solutions. ELIZA is the classic example. A simple program with very little code could convince people that they were talking to another human or at least machine with an understanding of their feelings. ELIZA was coded completely by humans. Of course, nowadays we have more sophisticated ways of doing that. We can throw a few topic tagged example sentences with connected replies at a computer and it will mostly reply with the right answers to similar sentences. This is only possible because computational linguistics provided the foundation for that. Still many solution are hacky to this day but that is because computational linguistics is more concerned about interaction with imperfect humans than most of the other disciplines in computer science.