HN user
Blog: http://joelvh.com Twitter: @joelvh LinkedIn: http://www.linkedin.com/in/joelvh
I've created some command aliases in my bash profile. There are also tools to create shortcuts for git commands. Other than that, I have created shell scripts that I copy to projects, and also some Rake commands.
I haven't spent enough time on some sort of centralization of "snippets" per se, since what I listed above covers the stuff I reuse the most.
I wonder how many companies are currently running tests like this in the enterprise. Anyone have an idea of what people currently use?
You might be able to signup for a new account and get another free year.... if the deal is still on by then.
Great job! I wrote up that post about WolframAlpha and wonder if there's an API so you could integrate WA to make it more robust?
Interestingly enough, WolframAlpha can generate a CAPTCHA image of each of these text questions, as to make it harder for a bot to decode AND answer the question! Check it out: http://www.wolframalpha.com/input/?i=CAPTCHA+What+is+seven+h...
Exactly. The whole discussion here points to the major flaws in using text as CAPTCHA. Maybe if questions were more metaphorical they would be harder to guess, but then there is no absolute answer. I think a combination of text, image, and logic would be hardest to break.
Exactly!
Haha.
If you were able to analyze the sentence structure of all 180 million questions, how many different sentence structures would there be? This all points to the fact that you can build algorithms to guess the answers eventually.
Ha! Valid point!
Also think about the way algorithms (like WolframAlpha) interpret the structure of the questions. Like some of the other commenters, switching some words around makes WolframAlpha fail.
It might be interesting to come up with a methodology for question structure that is harder for algorithms to interpret...?
Right. And as a little experiment, it was surprising the results I got. It also implies that it is not hard to structure the sentences in a way that makes it harder for WolframAlpha's algorithms to get the right answer. But doing that for 180 million questions? I wonder what the percentage of success using only WolframAlpha would be on the whole data set.
Good point. That gives a good indicator as to how the algorithm works. Not necessarily based on colors, but rather words in a list...? Maybe the construction of Text CAPTCHA sentences needs to be chosen carefully when thinking like an algorithm....
I played around with the demo page and used WolframAlpha to answer the questions for me.... With a little massaging, WolframAlpha would get you pretty far in hacking it.