I think they supplement each other. Wikipedia is a great place to go explanatory material; statistics are a part of that but if you are really interested in the numbers behind something you'll probably follow up the citations. Alpha looks to have great potential as a tool for statistical discovery and analysis, but I rather doubt it auto-generate tutorials on what data mean or why they matter.
It would be nice if Wikipedia can improve the quality of its articles by linking to Alpha; I hope Wolfram research won't exert a propriety attitude to its search results, but will make them available with something like a creative commons license to the extent that the original sources are in the public domain.
Quoting Wikipedia is not respectable in an academic context because you are not quoting a primary source, or even a secondary source. You are typically quoting a tertiary or quaternary source. If the article is properly cited, however, it is not difficult to simply quote the original citation.
this sounds like something that spans the (rather wide) gap between google and aws + public data sets.
I wonder how far you can go in terms of combining data/hacking on it?
For example they mention real-time financial data. So can I write something that would connect online discussion/activity to stock movements?
A platform for doing large scale, real-time data analysis in a rich descriptive language without doing any of the dirty work would be quite something.
This is really interesting on many fronts... Google queries are trivial and dumb - they take virtually no CPU power to execute (on a per-query basis) in the grand scheme of things. But I'm trying to imagine how Wolfram Alpha will scale, and I'm not really seeing it. You can't precache results, queries require the aggregation and manipulation of huge data streams, and so on and so forth.
Wolfram Alpha is going to be _expensive_ to keep up. It's good to see they've already thought of this (with their Pro offerings), but the thought of the sort of power this thing would consume if it becomes popular en masse makes me shudder.
Indeed, Wolfram himself once solved a Google puzzle (to encourage job applicants) using Mathematica. It was, what's the pattern here, and what's the next row?
Yeah, the "next # in the sequence" things are in theory dubious but in practice the theoretical unsoundness doesn't really cause issues (in the sense that: the people you'd want to select for will often find the pattern you want them to find, and many of the people you want to select against won't find that pattern).
The real meaning of what they're asking for is something like:
- I assert that there's a simple-but-nontrivial "algorithm" that generates this sequence. Find that algorithm, and use it to find the "next number in the sequence".
...but then you need a definition of "trivial", which is a lot of work (and most applicants know "trivial" when they see it:
I'd ask it for the perfect recipe for a decent mug of tea. It'll hold up WA's severs for months on end, causing unmaskable interrupt that won't return until I get my tea.
It seems like it's worth going to - and it's directly related to something I'm doing at work (inference over topic maps).