mikhael

#1: You preface that sentence with "But in French" so why mention English? Can /dʒ/ actually be written some other way than "dj" in French? From your post, it seems like the answer is no.

#2: The first paragraph of the third card neither mentions nor implies (to the non-linguists among us, at least) anything about English "j" having a hint of "d". This is something I'd never realized before, and only discovered it by saying "James" aloud a few times after this post; and I'm still not 100% sure that it's right, based on the post.

"... this falsehood perpetuated on the big screen in Quentin Tarantino's Django Unchained where the eponymous character spells his name, adding 'the D is silent'."

...

"The D is not silent, it's very much pronounced."

...

"... Tarantino's film teaches the correct pronunciation ... it is incorrect to say 'the D is silent'."

...

"But in French, /dʒ/ can be written 'dj' because the 'j' alone is just /ʒ/."

OK, if the "d" is not silent, don't you mean that /dʒ/ must be written "dj"?

Why not just say that, in English, "j" as in "James" has the tongue touching the roof of the mouth, so it always sounds a little like a "d", but in French it doesn't?

"The group has written sev- eral million lines of code, including: core libraries (includ- ing collections with polymorphism over element permis- sions and data-parallel operations when safe), a webserver, a high level optimizing compiler, and an MPEG decoder. These and other applications written in the source language are performance-competitive with established implementa- tions on standard benchmarks; we mention this not because our language design is focused on performance, but merely to point out that heavy use of reference immutability, includ- ing removing mutable static/global state, has not come at the cost of performance in the experience of the Microsoft team."

Thanks!

We are still in the honeymoon phase of free, online university courses, so I think there's been relatively little criticism of what's available now, but I'll go for it: I was disappointed by the Coursera/Stanford ML class. It was obviously watered down, the homeworks were very (very) easy, and I retained little or nothing of significance.

In contrast, the Caltech class was clearly not watered down, and, as the material was much more focused (with a strong theme of generalization, an idea almost entirely absent from the Stanford class, as I recall) I feel I learned far more.

Another big difference: the Caltech class had traditional hour-long lectures, a simple web form for submitting answers to the multiple-choice* homeworks, and a plain vBulletin forum. The lectures were live on ustream, but otherwise, no fancy infrastructure.

So I think that some interesting questions will come up. Do we need complex (new) platforms to deliver good classes? For me, the answer right now is no -- what clearly matters is the quality and thoughtfulness of the material and how well it is delivered. Can a topic like machine learning be taught effectively to someone who doesn't have a lot of time, or who doesn't have the appropriate background (in CS, math)? Can/should it be faked? I don't think so, but I think there are certainly nuances here.

* Despite being multiple-choice, the homeworks were not easy -- they typically required a lot of thought, and many required writing a lot of code from scratch.

On the contrary, the claims are meant to be understandable to any reasonably technical person (anyone "highly skilled in the art"). On the other hand, your average non-technical lawyer would be completely unable to read them.

This doesn't mean it won't take time to fully digest a patent's claims, as they tend to be written with a very high degree of precision.

> In fact it was just not feasible to implement hardware accelerated drawing inside windows until recently. Because Android is designed around having multiple windows on the screen, to have the drawing inside each window be hardware accelerated means requiring that the GPU and driver support multiple active GL contexts in different processes running at the same time. The hardware at that time just didn’t support this, even ignoring the additional memory needed for it that was not available. Even today we are in the early stages of this -- most mobile GPUs still have fairly expensive GL context switching.

i'm not sure how the author's formula was derived, but i get the same result calculating the series for a slightly different (but wrong) algorithm: just keep flipping until HT or TH appears (not flipping by pairs). this series is sum(n=1 to inf, (n+1)(qp^n + pq^n)), i.e. sum(n=0 to inf, (n+1)(qp^n + pq^n)) - (p+q). the series works out to 1/(p(1-p)), but that last term would account for the one-off difference.

as a visitor to japan, getting a temp. cell phone seemed ridiculously hard. there are no prepaid SIMs/phones; you can only do a rental. and no matter what plan you get, outgoing calls will be ~90yen/minute.

so: after two days in tokyo, i wound up renting an iphone (3GS), and it was immensely helpful. having maps + gps was really fantastic. i installed and used skype pretty often - it breaks up a lot over 3G, but again, it's far better than paying 90yen/minute. i highly recommend this company: http://jcrcorp.com. i have no association with them, but they were a pleasure to work with. (also note: an android phone may work better, as iphones are on softbank which is a newer and less well established carrier).

i also found that free wi-fi seemed to be very, very rare. you can find some coffee shops with wi-fi, but you have to buy a ticket at a nearby FamilyMart for ~500yen/day.

do you know any of the language? if the answer is no, it's probably too late now; but i found that using the japanese keyboard on iphone (just kana) was very helpful to mapping stuff out.

it's worth spending a few minutes to understand the addressing system: http://en.wikipedia.org/wiki/Japanese_addressing_system. there are no street names, and it's generally very different from the US.

finally, i assume you already know this, but tokyo is not cheap; be prepared to spend a lot of money, and enjoy yourself.

feel free to contact me off-list.

"This begins with the realization that every American adult is responsible for his or her own health."

the assumption that every american adult has complete control over his life is false. i don't even believe that this is approximately true -- especially when health care is the issue at hand.

the other is that addition of two D-digits numbers takes O(D) time (this is what the author means to expose in the article). as you have pointed out, the base (10, or 2, or anything else) does not matter for asymptotic analysis here, because the logarithm functions are all linearly related.

Scantegrity is an open source election verification technology for optical scan voting systems. It uses privacy preserving confirmation numbers to allow each voter to verify her vote is counted. The confirmation numbers also allow anyone to verify that all the votes were counted correcly.