We use Riemann at Two Sigma to monitor/alert/heal our Mesos cluster [1], precisely because of above reasons to reject.
>- You must pick up Clojure to understand and configure Riemann (we're not a Clojure shop, so this is a non-trivial requirement)
>- Config file isn't a config file, it's an executed bit of Clojure code
This is actually great -- static files quickly become their own franken-languages, with code generating config files.
>- Riemann is not a replacement for an alerting mechanism, it's another signal for alerting mechanisms (though since it's Clojure and the configuration file is a Clojure script, you can absolutely hack it into becoming an alerting system)
>- Riemann is not a replacement for a trend graphing mechanism.
You probably don't want another alerting mechanism; you probably already have pagerduty or something else -- what you want is a rich way to create the alert.
To load the framework (application) with the logic with the concern of deciding what resources it wants. The scheduler shouldn't care about what you get, just fairness. Two-tiered scheduling achieves this:
Mesos decides how many resources to offer each framework, while frameworks decide which resources to accept and which
computations to run on them.
This sounds like the story Jessica Livingston mentioned at Startup School 2012 <http://news.ycombinator.com/item?id=4699862 >, if I remember correctly -- business in Texas got a term sheet, moved to California, investors pulled out when their user acquisition metric changed. Anyone have more color on this?
Poor example-- the Famine should be known as the Starvation. There was plenty of food to ration to the Irish, even on Irish land; the British instead shipped it home, or fed it to cattle and then shipped that home, and let the Irish starve instead.
Sorry to be late to the party-- xaa, could you explain a little more what you mean by
"Ultimately I believe the breakthroughs will come fastest if we can "close the feedback loop" by automating a lot of bench biology, and then have computers both generate and test hypotheses."
I don't know anything about bioinformatics, so I'm trying to see how this differs from vanilla automated model selection. I'm really interested, so please feel free to send me an email if you feel that's more appropriate.
Ah, so I used a 2-degree heuristic to come to that conclusion--I haven't had any first hand experience with her, nor do I have contact with her former students. A few stats professors independently recommended her to me as a supervisor, her students seem to do well, and her research page is more welcoming than most (versus, say Ullman's page: http://infolab.stanford.edu/~ullman/ or say, read Brian Ripley's posts on the R mailing list). The one thing I'd add: my experience has been that academics generally have less empathy than others; I'd be interested to hear from old students how she compares to other faculty.
PGMs don't get the same sexy treatment that ML and AI seem to get in pop science articles, so it may be worth stating explicitly that they're very much used in ML and are intellectually fascinating in their own right. A graphical model can fully describe the distribution and dependences of a model. Why this is important: a graphical model makes it very easy to give a computer your model, and there has been great success over the past two decades in doing just this [1].
Further, Daphne Koller is a serious force in the field, and seems to be a pretty good supervisor, so I'm guessing/hoping she is an interesting/engaging lecturer as well. Though, Stanford CS/Stats students are more able to comment on this last point.
As to being bigger and stronger, perhaps we should look to the nation of Japan and the feats its military was able to achieve with men roughly the size of north american women. Women are perfectly capable of defending themselves, not that they should have to, just like smaller men are perfectly capable of defending themselves, not that they should have to. These are again averages and if you look at the deviances you'll see that there are a lot of women who are larger than a lot of men.
Also, keep in mind that a man is twice as likely to be assaulted as a woman so from a statistical perspective it is men who should be fearing for their safety as they post their gender online.
Blatant misuse of "statistics." Not all assaults are equal. How many assaults toward men lead to their having thoughts of or committing suicide? Also, the implication that we should train women to a military standard so they are ready to fend themselves off from attack is absurd-- by your rationale, we should put all be proficient with switchblades and blame ourselves if we were unable to stop an attack. The causal is the perpetrator, and the culture that breeds feeling of ownership by men of women.
It wasn't so long ago that the law explicitly treated women as property, so let's not forget that too quickly. In the UK, it was in our parents' generation that women were allowed to have a mortgage (Sex Discrimination Act of 1975) and only two decades ago that marital rape exemption was abolished (until 1991, in the UK, legally a husband could not be charged with raping his wife).