E.W.Dijkstra: On the foolishness of "natural language programming"

If we don't keep trying to make AI, we're never gonna get there. I'm not saying data mining is AI. I'm saying human brains do data mining too, but differently, and figuring out how is what might come of all this.

Wolfram-Alpha-style natural language programming actually isn't that bad because it's a dialogue. The thing tells you its assumptions, so you're back to formal representations you can deal with. Natural language is mostly statistics, also known as guesswork. A machine can guess better than humans. Google proves that by suggesting "torrent" every time you search for a movie title.

Dijkstra fears a world where the lack of formalisms prevents progress. That's why he likes formalisms. I do too, maybe not for these exact reasons. Anyway, I take formalisms as a given because they've always been there my whole life.

Formalisms can be impractically formal. The level of precision required by machines is beyond even what most mathematicians are used to casually (i.e., pen and paper, or at a blackboard). If you had to do math like you write code, mathematicians would go bonkers. Include this, type-cast that, ... nah, everyone knows what this and that is supposed to mean, right?

A little NLP could make it easier to command computers. A little more NLP could turn machines into really useful slaves. AI would be opening a can of worms few in this world are prepared to deal with.

Wisdom is certainly something to take from, but embodying the limits imposed by someone as a roadblock to onself isn't the way to innovation.

NLP 2 : Natural Language Processing : modeling and processing of the natural language phenomenon

NLP 1 requires advancement in NLP 2 to a significant level of accuracy which in turn requires the accuracy and care of the formal symbolism of lower level programming automaton. Having said that, the progress has been slow which often times leads to denouncement of pursuit of research in the NLP field.

The article is 6 years old and a lot has happened in terms of both processing power capabilities that an individual has access to now (cloud computing) and amount of data available (online information explosion, particularly social media streams) which used to be a bottleneck earlier. This opens up a huge opportunity for breakthrough in NLPs by mathematicians as mentioned by Yuri yesterday at Web 2.0 Summit. AT&T's voice activated remote ( http://www.research.att.com/projects/WATSONASR/index.html ) is an example of natural language programming that is achievable today.

Or when dealing with each other, for that matter. In Lojban, it is grammatically incorrect for someone to give me vague directions like "we are at the pub to the left of the central plaza". They would instead have to say something like "we-not-you are now at the only pub to the left (when seen from the cinema) of the only plaza".

Imagine political debates where imprecise language and double meaning are much harder to express. Mmm...

.i mi batci le mlatu

Which plaza? Just because you said "the only plaza" doesn't make it unambiguous. There certainly exist more than one plaza in any given city.