So the approach is: make the UI first, make it fast, and then wrap an API around whatever evolved. A controversial methodology, but given the imperative for making a responsive UI, it makes sense.
However good this approach is for creating fast UIs, it's death for feature development and fast responsive innovation. With an API you can develop in parallel and release stuff faster and iterate faster.
從John Langford的個人部落格看到這個消息：由 Ron Bekkerman (LinkedIn)，John Langford (Yahoo! Research)和 Misha Bilenko（Microsoft Research）共同編輯的 Scaling up Machine Learning 將在今年底出版。而且他們將在 KDD 2011 以這本書為基礎發表 Scaling Up Machine Learning 的 Tutorial。This tutorial focuses on providing an integrated overview of state-of-the-art platforms and algorithm choices. These span a range of hardware options (from FPGAs and GPUs to multi-core systems and commodity clusters), programming frameworks (including CUDA, MPI, MapReduce, and DryadLINQ), and learning settings (e.g., semi-supervised and online learning). The tutorial is example-driven, covering a number of popular algorithms (e.g., boosted trees, spectral clustering, belief propagation) and diverse applications (e.g., speech recognition and object recognition in vision).
The Defense in Depth approach employs and integrates the abilities of people, operations, and technology to establish multilayer, multidimensional protection — like the defenses of a castle. The approach employs successive layers, using a variety of methods at multiple, key locations,to prevent the potential breakdown of barriers and penetration to the innermost areas of the system.
My arguments are not coming from a point of hatred towards any company or individual, but stemming from a determination to speak up for those who are voiceless in many of these discussions and to provide a different perspective with which to understand the issues.
And when I get pissed off about something, I rant. And that can be both good and bad. But I've found that my rants often make people think. That's what motivates me to keep ranting.
While I admire the insights of many of the people in the world of computing, I get this cold feeling that I speak a different language.
Why is it drug addicts and computer afficionados are both called users?
In the first group we would include (in no particular order) Clustrix, GenieDB, ScalArc,Schooner, VoltDB, RethinkDB, ScaleDB, Akiban, CodeFutures, ScaleBase, Translattice, andNimbusDB, as well as Drizzle, MySQL Cluster with NDB, and MySQL with HandlerSocket. The latter group includes Tokutek and JustOne DB. The associated “NewSQL-as-a-service” category includes Amazon Relational Database Service, Microsoft SQL Azure, Xeround, Database.com and FathomDB.
Kaptein, Nass, & Markopoulos (2010) published a paper in CHI last year found that in the previous year's CHI proceedings, 45% of the papers reported on likert type data but only 8% used non-parametric stats to do the analysis. 95% reported on small sample sizes (under 50 people). This is statistically problematic even if it gets past reviewers!
That's life, that's what all the people say.
You're riding high in April,
Shot down in May
But I know I'm gonna change that tune,
When I'm back on top, back on top in June.
I said that's life, and as funny as it may seem
Some people get their kicks,
Stompin' on a dream
But I don't let it, let it get me down,
'Cause this fine ol' world it keeps spinning around
I've been a puppet, a pauper, a pirate,
A poet, a pawn and a king.
I've been up and down and over and out
And I know one thing:
Each time I find myself, flat on my face,
I pick myself up and get back in the race.
That's life
I tell ya, I can't deny it,
I thought of quitting baby,
But my heart just ain't gonna buy it.
And if I didn't think it was worth one single try,
I'd jump right on a big bird and then I'd fly
I've been a puppet, a pauper, a pirate,
A poet, a pawn and a king.
I've been up and down and over and out
And I know one thing:
Each time I find myself laying flat on my face,
I just pick myself up and get back in the race
That's life
That's life and I can't deny it
Many times I thought of cutting out
But my heart won't buy it
But if there's nothing shakin' come this here july
I'm gonna roll myself up in a big ball and die
My, My!
天風吹我 墮湖山一角 果然清麗
曾是東華生小客 回首蒼茫無際
屠狗功名 雕龍文卷 豈是平生意
鄉親蘇小 定應笑我非計
才見一抹斜陽 半隄香草 頓惹清愁起
羅襪音塵何處覓 渺渺予懷孤寄
怨去吹簫 狂來說劍 兩樣銷魂味
兩般春夢 櫓聲盪入雲水
There are many holy grails in online commerce, but one that has frustrated C-level executives and engineers alike is how to produce better recommendation algorithms. Produce better recommendations, and you’ll sell more stuff.
Historically, however, there has been one major structural impediment to making significant breakthroughs on this front. But the Chief Scientist at RichRelevance, which provides personalization solutions for the likes of Walmart, Sears, and Overstock.com, may just have fixed that.
First, however, the impediment: The people who are likely to produce breakthroughs--the really smart smarty-pants in the math departments of the world’s universities--don’t have access to large bodies of real-world data. And without real-world data, they can come up with as many hypotheses and new types of math as they like, but they’ll never really know if it actually works in the real world. It’s like trying to learn how to serve without tennis balls. You can swing as much as you like, but until you actually hit a real-live ball, you can never be sure if your swing would actually place a ball in the serve box.
For their part, the people who have real-world data--the Amazons and eBays of the world--can’t share it with the researchers for reasons of customer privacy. “Even if we anonymize it, we’re handcuffed because we can’t give out data that can be reasonably be used to reconstruct who someone really is,” the Chief Scientist, Darren Vengroff, tells Fast Company.
Vengroff, however, has come up with a novel solution: He’s created a “black box” of sorts with real-world data that researchers can use to run experiments on. Researchers won’t be able to look at the data, but they will be able to dump their algorithms in and have the box spit out results, which the researchers can then use to refine their hypotheses.
It’s a simple idea, but it wasn’t really possible to execute until the advent of the cloud. Now researchers from any part of the globe will be able to use the system to run experiments. (In principle, of course--in practice, a committee will vet proposals and choose which ones will actually run.)
Vengroff, who once worked as a Principal Engineer at Amazon, says he got the idea for the project while attending a computing conference last fall. “In one of the sessions, there were three consecutive papers in a row where about two-thirds of the way through, I was really excited about what was being presented, and then they went down a different path than I thought they were going to go,” he says. “I realized if they only knew what the real-live data, that I look at every day, says, they wouldn’t have gone that way. They would have gone the right way and gotten to a much better solution.”
“Seeing these brilliant ideas get misapplied because of a very reasonable assumption about how shoppers might shop, but happens not to be true in the empirical data--I realized we’ve got to find a way to have this not happen anymore.”
 | 18:56 | Origin of NoSQL « myNoSQL |
 | 18:53 | Expert in NO SQL |
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| 18:45 | 鴻兔大展 |
| 16:13 | Liked/Commented: image001.jpg 1 |
| 09:19 | #read 每月7美元 紐時、華郵合推網路報 http://t.co/l7C1Hp4 |
| 00:04 | Daily Murmur 2011/01/26 |
Drink with me to days gone bye
To the life that used to be
~ 林徽因 · 馬雁散文集 · 蓮燈 ~ 馬雁 在她的散文《高貴一種，有詩為證》裡，提到「十多年前，還不知道林女士的八卦及成就前，在期刊上讀到別人引用的《蓮燈》」 覺得非常喜歡，比之卞之琳、徐志摩，別說是毫不遜色，簡直是勝出一籌。前面的韻腳和平仄的處理顯然高於戴...
