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Comment I read a big chunk of it (Score 1) 378

Back in high school, I thought I was the most badass programmer on this planet. Could hand assemble code and hyper-optimize my programs counting clock cycles everywhere. I got into college. There was a book on algorithms in the small library the computer room had. I learned about asymptotic behavior. So I realized that my cleverly optimized O(n^2) sorting assembly program was going to eventually lose badly to a straightforward interpreted implementation of quicksort. Clearly I had to become good at this. I started reading all books I could find on the topic and very quickly I noticed that they all included a sentence meaning "If you want to understand the subtle underpinnings of this, see TAOCP." So I got a copy of volumes 1 & 3. It was expensive (I was not in USA and books were VERY expensive because of currency exchange issues). Mom & Dad chipped in and I still thank them for that. I borrowed volume 2 from a friend.

I decided to go though the book solving all exercises up to level 30. Saturday was my TAOCP day. I cannot say I read ALL of the text nor that I solved ALL problems of difficulty below 30, but I solved all that I tried and they were way more than a few. I even solve some in the 35 level, whenever I considered them interesting.

FF to the beginning my PhD studies at a good school in the USA: When taking the grad level Algorithms class, I was doing VERY well. The professor, a scary smart guy (now full professor at Stanford) asked me how may courses on algorithms and information theory I had taken. The answer was none. My undergrad degree was in Systems Engineering, from a crappy school in South America. I was never formally taught what a big-Oh was. That professor become my thesis advisor. He used to joke saying I was a walking encyclopedia of algorithms.

Will it work for everybody? Probably not. If you want to do theoretical CS, as I did, you will have to handle that math and some more anyways. CLR is more up to date and time efficient for learning. If you want to be a software engineer, chances are you are not going to be doing the heavy math, you will be using off the shelf algorithms.

Still TAOCP is a hell of a reference. Funny thing is, after finishing my PhD, I browsed through it. It looked simple, not very formal at all. I guess PhD does mean "permanently head damaged" :-)

Submission + - BBC micro:bit specs released as open hardware (microbit.org)

TrixX writes: The makers of the BBC micro:bit have announced that they are releasing the full specs for the device under an open license, (Solderpad License, similar to Apache License but for hardware). This means that anyone can legally use the specs and build their own device, or fork the reference design github repo and design their derivatives.

Comment 100 port scans per hour. (Score 1) 279

You should install a firewall in your router, enable the few ports you want to use from the outside, and log every other connection attempt. That way you'll have an idea how often ports are scanned daily. For me is at least 100 times per hour in a single IP, most of them trying the telnet port, because a lot of surveillance cameras and other I(di)oT stuff still use telnet.

Submission + - Reporter of an e-voting vulnerability raided in Argentina

TrixX writes: There have just been police raids at the home of an Argentinian security professional who discovered and reported several vulnerabilities in the electronic ballot system to be used next weeks for elections in the city of Buenos Aires. The vulnerabilities (exposed SSL keys and ways to forge ballots with multiple votes) had been reported to the manufacturer of the voting machines, the media, and the public about a week ago.
There have been no arrest but his computers and electronics devices have been impounded. Meanwhile, the information security community in Argentina is trying to get the media to report this notorious attempt to "kill the messenger".
AI

Submission + - SimpleAI, an implementation of artificial intelligence algorithms (readthedocs.org)

machinalis writes: "SimpleAI is an easy to use lib implementing in python many of the artificial intelligence algorithms described on the book "Artificial Intelligence, a Modern Approach", from Stuart Russel and Peter Norvig.
This implementation takes some of the ideas from the Norvig's implementation (the aima-python lib), but it's made with a more "pythonic" approach, and more emphasis on creating a stable, modern, and maintainable version. We are testing the majority of the lib, it's available via pip install, has a standard repository and lib architecture, well documented, respects the python pep8 guidelines, provides only working code (no placeholders for future things), etc. Even the internal code is written with readability in mind, not only the external API.
This new release adds a few statistical classification methods to SimpleAI with
the intention of start replicating the machine learning aspects of aima-python, also includes lots of tests for the classifiers, documentation, and a few sample uses of the classifiers.
http://simpleai.readthedocs.org/
https://github.com/simpleai-team/simpleai
twitter: @machinalis""

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