A Learning Advance in Artificial Intelligence Rivals Human Abilities

You're operating under the presumption that rhaps0dy is not an AI.

There is tldr.io, with somewhat still buggy Chrome integration, that will display you a TL;DR below Reply box on HN (and in an expandable-on-hover box next to the link on HN main page) iff someone has already written a TL;DR for the article in this service.

What an amazing design idea that would be for dealing with clickbait though.

A crowd sourced subtitle could be added to the link and possibly voted on for accuracy (an expanding list shows alternate submissions or allows you to submit your own)

Since headlines can no longer be trusted, we could turn to the crowd.

This, actually, is much better; the Slashdot summary is often wildly inaccurate, alas.

Thanks intelligent commenters!

>By 'entire field' you mean handwriting recognition?

Classification of high-dimensional data is a huge portion of machine learning.

>They reduce the search space by limiting themselves to combinations of typical pen movements.

"They reduce the search space by limiting themselves to gradients of nearby pixels. Very smart, but I don't see how convolutional neural networks can be applied to machine learning in general."

All of machine learning involves some prior knowledge -- the question is always how much and at what level of abstraction.

I think the question is "why did they select Matlab as their language".

I think you misread my question or something.

Someone down-voted me just for asking. I have no idea about any of this stuff and I was just genuinely curious. Apparently people are pretty polarized about Matlab. Thanks for explaining that to me.

I'd add:

- That's what they teach you when you're a student.

Complete agreement - grad students have a few jobs they need to do and need to do quickly:

1) Large (within reason) easy matrix manipulations. MATLAB is fantastic at this. Matrices as first-class objects is so important, I don't know why more languages don't include them (though I am pleasantly unaware of the complications inherent to this).

2) Simple, decently pretty visualizations of data.

3) Trivial syntax. If you've programmed at all, it's easy to read MATLAB syntax.

IMO, the only threat to MATLAB on the horizon for academic work is Python + the associated SciPy tools (sckikit-learn, etc); especially as bundled in SPYDER, which I have had a blast with. But since cost is typically not an issue at a university (MATLAB is paid for by someone else), and everyone already speaks MATLAB, there's not a real impetus to change. (Julia may be int he running, too, but SPYDER seems more user friendly at this point)

Also, as someone who's been through this a dozen times before - as soon as a professor says "make me this visualization, the command in MATLAB is this" and the grad student says "SciPy (or whatever) doesn't have that", that student is converting his data to a text file, reading it into MATLAB, and making that damn plot :)

MATLAB is a terrible programming language. MATLAB is a fantastic workbench for exploring data and implementing numerical algorithms.

There's a lot of excitement around the numerical computing tools that have sprouted up around Python, but I find the visualization capabilities to be lacking and writing numerical code in Python is really quite clunky where the same expressions in MATLAB are much more clear and concise.

In short: If you're writing lots of loops and conditionals, MATLAB is the wrong tool. If you're analyzing data, applying linear algebra or exploring using the tools of mathematics, signal processing and machine learning... it really can't be beat. Everything is just there, everything just works, everything is very well documented and there's a MATLAB implementation of everything new.

Only bummer is that it's expensive.

> My guess is that most of the general purpose programming languages are usually poorly suited in one way or another for domain specific programming.

For this reason, Lisp would be ideal for this.

What do you think about alternatives? Like Anglican.

I find OpenCV to be a far better alternative to MATLAB for image processing and CV work. The API's are extremely similar and when things don't work the way you expect, you can modify OpenCV to fit your needs.

Plus, if you're a grad student and you write it in C++/Python with OpenCV, your algorithm might finish before it's time to graduate.

That's awesome that Matlab is such a good expensive product. Personally I'm an open source guy all the way so I support R and Python (and Julia, I suppose) at every opportunity. Yeah, maybe there are some rough edges, but my thinking is that since they're good enough at this point, I can work around those rough edges...and I anticipate that hundreds of thousands of users will eventually drive them to being as good or better than any commercial offering. Take SAS, for instance, I don't like it--largely due to the fact that it's so expensive most companies don't upgrade until they absolutely have to. So you'll run into lots of employers running a very old version of SAS (like 9.2), without any of the extensions which help you solve problems and be more productive. So when I started my new data science-ish job at my current employer and had the option of which tools to use for machine learning and modeling I chose R and Python. But to each their own. I just dislike contributing to the market share of software I could never afford to run on my personal computer.