e-dard

Another Flask hacker here. Use it for all internal projects at work. 4 so far in 2012.

I based my PhD thesis on the idea of trading computational cloud (or any, really) resources. I went a little further though, and looked at how to design algorithms for the actual marketplaces, which allowed them to optimise how they competed with other marketplaces. A bit like London Stock Exchange competing with the New York Stock Exchange.

While my research was a little blue sky (what isn't) I do think that electronic trading of computation resources is the future, and I think Amazon are ahead of the game in this respect.

[mistake]

So that you provide as little friction as possible to getting people to sign up. For example, with your current button I was reluctant to press it because I would assume there would be a big form on the other side. However, I'm more likely to sign up for more info if it's only an email required.

An alternative to Twitter has existed since 2008. It's called identi.ca

http://identi.ca/

The issue is getting people to start using such a service.

Is the point of this that the recipient can only temporarily see it, and not keep going back to it?

If so, what's to stop the user doing the equivalent of “menu button and power button” on the iPhone, to take a screen shot?

Ah, sorry, I missed the top of this reply-thread. I was referring to the story, not Facebook. :-)

I don't under stand the confusion in the other replies here.

1) lowercase inputted password. 2) hash password 3) compare hash to db hash (which was from a lowercased initial password).

And by encryption scheme, you really mean hashing scheme. Yup, it's easy to get confused.

We use SearchSpring. Does anyone know if this is an advantage over than? Currently, with SearchSpring we can:

- specify result rankings;

- add facets to our products and then SS allows the customer to do things like compare products, restrict to over $$, or only white, grey and red;

- does fuzzy completions etc.

I ask because while the product we use is OK, it doesn't have a great API, and I want to be able to integrate more tightly with the service and allow myself to do things like A/B tests, dynamic results, customer specific rankings etc.

This is great. However, did I read the article right - by the time they launched they had spent 300K?

Here's a question - is it possible to ever do something like this without the requirement of finding 300K via consulting gigs first? I assume that given there were 3 of them and they spent only a few months building it, they didn't need all of the 300K on salaries.

I suppose you would have to grow the product from a smaller stage, rather than build it and launch?

The SO API is read-only, so I assume this app won't allow you to submit questions/answers/comments etc.

Is it just me, or is using a proportional font for the code snippets not ideal?

Personally, I can't stand writing/reading code displayed in a proportional font.

Aren't Mixbook the jokers who tried to hire dhh for a Rails position?

I prefer "short but to the point". This is instinctively what I threw in iPython before looking past first snippet:

    print reduce(lambda x, y: x*y, xrange(2, 6+1))

As a newish Python guy (5 months), I'm interested as to why the preferable solution seems to be to import operator and use the multiplication function? (I'm purposely ignoring the more preferable call to the C library)

(iMac 2011) I had to return an Intel 510 120Gb after about 2 months due to it constantly failing verify disk in Disk Utility and corrupting various files.

I replaced it with an OWC Mercury Electra 120GB; had to return that one off-the-bat, as it was DOA! Not having much luck, but I'm hoping my OWC replacement will be OK. . .

Your argument, though, doesn't make Patrick's point necessarily false.

Even if Google take more value from people than any other company, they can still provide a portion of that value to n other people, and assuming n is larger than any other company's n, Patrick's point still holds.

</pedant>

I bought an Intel 510 120GB SSD for my iMac before Christmas. I chose it over the Vertexes/Agility models because of the supposed HW quality.

After the 6th time of it corrupting various parts of my filesystem (often the catalogue and other important parts), I'm returning it to Amazon.

It was twice as annoying because I had to re-rip open my iMac to get at it. I think I will be exchanging it for an OWC Mercury Extreme.

I listen to music all day every day when working (from home) and feel it helps me to be more productive, mainly because I'm relaxed and enjoying it, which in turn contributes to me enjoying my work. However, if my other half comes home and starts having a phone conversation–at a significantly lower volume in another room–the muffled voice really distracts me.

I certainly feel there is a correlation between _tolerance_ and performance.

I'd do something about the kerning of the h1 element, it's not particularly pleasant in my opinion.

(Apologies for being off topic)

In the list specifying the rewards for investment on the Kickstarter page, the author specifies investors receive free copies of the iOS game. I was under the impression that Apple didn't allow developers to sell copies of games outside of the app store?

The difference in performance between using evolutionary approaches and bandit algorithms is complex and problem dependent. There is no "one algorithm is better than the other".

I've used both approaches for a different application and neither dominate the other.

In a nutshell, the problem is that as you add more arms (e.g., landing page variations) the amount of page views you need (i.e., actions tested), in order to learn reasonably accurate reward distributions, grows significantly.

Further, there are some other challenging aspects to this. 1) The environment -- visitors' preferences over time, your competitors' pages -- is very dynamic; 2) because you have to test and learn in the real world, your actions may impact your future performance.

I used and designed these types of algorithms for my PhD research, but applied them to trader selection between market exchanges; my thesis is in my sig if anyone is interested.

I don't think Tumblr are making money at the moment. I mean, they might sell themes but that's hardly going to come close to their outgoings.

I guess they're working on the revenue generating bit, as seems to be the case for so many funded tech companies over the last few years.

This is neat. Would it be possible to extend it such that you could drop a key file into the password box to do the encryption/decryption?

Surely the mag-safe cables shouldn't get so damaged, because the cable detaches from the laptop under significant strain?

In terms of mag-safe on iOS devices, I guess it's not feasible due to it transmitting data.

Is it weird that I was very surprised that anybody writes anything important in anything other than LaTeX??

Well clearly they're more likely to hire someone who does go to the effort!

> To be clear, interpolation search can cut down the runtime by another log factor (`O(log log n)` instead of `O(log n)`) but it's just not worth the effort, especially in this case, precisely because the lines aren't uniformly distributed.

It doesn't matter what the distribution is as long as you can learn it. Uniform helps when you are cutting down the search space in regular chunks, sure. The Reddit data wont be uniform - so don't cut the search space uniformly.

As I said, something faster could be conceived if one studies the average number of visitors over a 24 hour period (I don't know where this data could be gathered from).

If you can make your first seek very accurate, then it may be the case that simple linear search from there will get you there faster than Binary Search.

You can still report average and worst-case complexities under the assumption you have taken about how the log data is distributed.

Sorry to keep going on about this, but I just wanted to make my point clear! Good discussion.

OK, you are simply proposing the most obvious solution to the problem, which is entirely correct - I must have misunderstood your reasoning.

I assumed Reddit would want something a bit more special that the hundreds of Binary Search implementations they are going to receive. There are always faster algorithms that can be designed for specific problems, even if realistically they only save (in this case) 100ms.

It's a competition - you're supposed to stand out.

You're ignoring real-world aspects of the problem. For example, you're assuming that the data points are evenly distributed across time.

Reddit will most likely have regular busy and quiet periods, which will impact the density of the log at certain times.

Thus, one can tune the algorithm to work better on Reddit's specific visitor pattern, if you can learn it. As an example, you need to jump back further in the file to get from 8pm to 6pm than you do to jump back from 4am to 2am. <- assuming US time, which they don't.