zhanwei

statements like that typically come from best-selling author and keynote speaker. This kind of articles seem valuable to some audience, but it's probably something I can never understand.

"What if a large class of algorithms used today -- from the algorithms that help us avoid traffic to the algorithms that identify new drug molecules -- worked exponentially faster?" -- these problems used as example in the opening line are only tangentially related to the problem of submodular maximisation that the paper it is talking about is tackling. I also don't think submodular maximisation is widely used today for identifying new drug molecules or avoiding traffic.

He already did his job of intellectually engaging the recruiter. If the other party is not interested, it will not be rude if he update his resume and move on.

The guy writes well. The recruiter is the one with bad attitude. But I would say that a practical communicator knows his audience, and in this case might want to give up explaining POSIX, change his resume, and move on.

I agree with this article more. Yes, $86M is sure expensive with lots of efficiencies. But the first one is oversimplifying the technical aspect, which is missing the point on the sources of inefficiencies. The project can't be using openALPR at its current level and it is hopeless to use it as a starting point to get decent accuracy.

So IBM Watson can do all the smart and complex stuff but we still need human to do the dumb stuff like importing excel files where the cost outweighs the benefit of getting Watson to do the smart stuff.