[jasonlaska]

We think it's a good idea too ;) Machines and humans truly have different talents: machines are great at memory, keeping track of state, distributing information while people are great at understanding subtle nuance in natural language.

[visarga]

And in another 3-5 years, AI will start understanding subtle nuances too (probably) judging by the number of papers in computer language understanding.

[YeGoblynQueenne]

Unfortunately "machines" (AI software, really) are really bad at nuance, subtle or blatant.

The number of papers in the field is a very good example of why: until you've read (enough of) them you have no idea what the state of the field is.

Edit: By this I mean that your assessment about the 3-5 years to "subtle nuance" is extremely, unrealistically optimistic. We're nowhere near AI understanding language. Try 300 to 500 years and you might be closer.

[jasonlaska]

Even modern methods today (deep recurrent networks, etc.) can do pretty well with these kinds of tasks (a very large ontology for instance) if you have enough annotations of the nuance!

[YeGoblynQueenne]

>> Even modern methods today (deep recurrent networks, etc.) can do pretty well with these kinds of tasks (a very large ontology for instance) if you have enough annotations of the nuance!

Where do you get that from? NLP, with neural networks or not, stays as safely away from meaning as is humanely possible while working in an area very closely connected to it.

Also, ontologies? Very few people are interested in that nowadays, though that includes the team that made Watson. The push is instead to do away with all that and rely on statistical approximation.