Stanford AI Class Lecture Notes

Google still has a very long way doing an adequate translation between a language such as Chinese and English. I'd be surprised if Google was taking such a pedestrian approach in solving that particular problem.

As it stands, languages such as Chinese are intrinsically implicit in nature. In fact, the more adept at the language, the more you can express with less. If you follow the literature back a couple thousand years, the amount expressed in a few characters is absolutely astounding.

If you take the example they use at the bottom regarding wonton, it's down right criminal to map the grammar in such a hurried manner. For one, just from the romanization of wonton, the AI should be able to gauge that it's looking for 2 characters and not 1 (1 character per syllable). However, in the case of the menu, the wonton egg drop soup drops a character to save some space.

Taking a straight forward CFG approach will never result in an accurate translation. What may work well is to do multi-pass contextual analytic processing in parallel.

I thought they were going to be posting videos of the lectures... but when I logged in today and couldn't see the it anywhere. Did I misunderstand something? Is it posted? If yes, where?

LOL, here's what I just got when I tried to log in

'Ooops

Our servers are off having a quick coffee break. Wait a second and refresh the page. If you still get this message, we apologize and ask that you try again a little later.'

I hope we can get discussion like this going on every lecture (if not here, on Reddit or in the official discussion forums). Do you have any pointers towards reading on translation strategies that are more "realistic"?