248 karma · joined June 10, 2010
They don't even mention haskell in the conclusion, they just say that functional programming is well-suited to rapid prototyping.
I suppose it's a matter of opinion, but to me the comparison of these two snippets is nowhere near "a wash". The readability of the former is leaps and bounds ahead of the java version, and it will only be more apparent as the example grows in complexity.
def fn(x, my_dict={}):
my_dict[x] = x * 2
return my_dict
>>> fn(1)
{1: 2}
>>> fn(2)
{1: 2, 2: 4}
(I would have expected the second call to return {2: 4} when I was learning python)adder(x,y) -> x + y
If you call adder with one argument, you get the same behaviour as your makeAdder (returned closure), but if you call it with 2 args you get addition.
Seems reasonable enough.
An improvement in intelligence that becomes apparent after only 19 days smells too good to be true. Correct me if I'm wrong, but surely someone that practices IQ test problems will appear to be more intelligent the next time they are evaluated. It seems like something like that might be what they're seeing here, but I don't know enough about this training to say that.
On slower devices (such as mobile phones) redirecting can be more noticeable. You're right though, in general it's not really a problem, but might be more so than a larger-than-normal JS file.
> Large JS files only need to be downloaded once and are cached.
Yeah, I was trying to say that. Larger JS files aren't a problem at all; load them once and they're cached.
Pretty much sums up why I'm disillusioned about Watson and all the hype it's receiving. Don't get me wrong, it is a huge engineering feat, and pretty incredible, but doesn't seem as "revolutionary" as it's made out to be.
Am I missing something?
A way to process your training data to fit your knowledge graph needs to be unambiguous. No sense it teaching it anything if it becomes full of contradictions.
Finding a dataset for it to learn would be tough as well. Given the breadth of possible questions, you'll need to parse huge encyclopedias and/or wikipedia.
Finally, a way to efficiently query this massive amount of data. If it has to come up with an answer faster than its competitors, it better be able to lookup information pretty damn fast.
The real delay cost was from the inevitable redirect to the root of the website. When you visit domain.com/user-name, a JS-controlled site will usually redirect you to domain.com#!/user-name, and then loading up the page. There is no avoiding this unless you want really ugly urls: domain.com/user-name#!/user-name...
So large JS files might increase the load speed slightly, but adding an entire redirect is the kicker.
Like most things, there's a time and a place. Using hashbang urls can increase response-time when navigating through a site and provide a really cool experience. On the other hand, it definitely doesn't work for all browsers and users.
(someone posted this on HN recently)
http://googleblog.blogspot.com/2011/02/new-chrome-extension-...
Instantly stopped reading, what kind of freak writes about that.