Recent submissions

Comment · 2 years ago
I have a serious question that might sound not serious. The articles I read about boeing seem to focus on assembly line issues. As someone who flies a lot, assembly problems scare me, but so far assembly qv hasn’t been catastrophic (right?). It seems the real issue is a design flaw in the 737max pilot interface. Aside from some articles that feel vague (like competition with airbus led to some poor decision making); the chain of decisions that led to the design flaw aren’t really reported on (right?). Do you all have the same read?
Comment · 3 years ago
Carnegie Observatories (in Pasadena CA, not the telescope) is hosting an open house today (https://carnegiescience.edu/carnegie-observatories-2023-open...). It’s also almost the 100-year anniversary of one of the most important discoveries in science (and took place at Carnegie).
Comment · 9 years ago
It turns out that this wavelength of infrared is short enough that it sees through windows just fine.
Comment · 16 years ago
I personally had a bad customer service experience from them and switched. It's not obvious to me if you can generalize from one person's experience -- however -- the crux of my issue is their choice to not allow you to call them on the phone. It looks like this is still true (but I'm not certain). As a result of their cheapo policy, and the particular problem I was having, I switched.
Comment · 16 years ago
Comment · 17 years ago
Being proud, egotistical, or a braggart are all human characteristics. I mention this for two reasons. First, without the benefit of direct contact, you really have no idea what kind of person sivers is, or what his intention was when posting. Second, even if he is an egotistical bastard, so what?

Few people are in a position to donate $20 M to charity. Fewer still who are willing to give up what they worked so hard to make. This puts sivers in the top (some small number) percent of human population in important objectively measurable criteria.

Personally, I enjoy learning more about people I admire, flaws and all.

Comment · 17 years ago
The standard deviation is simply a measure of the spread of a distribution. There's nothing wrong or right about high standard deviations. In fact, the high standard deviation means that you should expect highly variant performance.

Look at the figures. The performance of Slicehost follows a sawtooth like pattern. The quantity standard deviation is useful because it quantifies what to expect. Plus or minus one standard deviation means that ~ 2/3 of the time you will fall in that range.

If you think about the problem a little bit, you might be more worried about the standard deviation of the standard deviation. This, in fact, would be a useful quantity, but hard to measure.

EDIT below this line ------- Several comments below have commented that SD is somehow less useful if it's "large" (or large relative to the mean, or whatever). The reason people think large SDs are indicative of a poor experiment is that in school lab classes one calculates the SD and call it the "error".

The standard deviation is a measure of spread, if it's large then the spread is large. Knowing the spread has value. In this case, under the parent's experimental conditions EC2's performance is more constant than that of slicehost's.

A fair critique of the blog posting is that the error on the standard deviation may be large, depending on the experimental conditions. It is _not_ a fair critique to say that the SD is too high to make a prediction, you just have larger performance spread. Note that the performance spread described is not necessarily "error". The spread is inherit to either the server (as implied by the article) or the method (in which case it is an error).

Comment · 17 years ago
> "Long Jumps" is a myth imho.

You are 100% on point.

The parent's poster's point on conformity is well taken. Still, "independent" researchers are viewed with suspicion because research is hard. As psranga points out, to make a long jump a researcher has to stay on top of the incremental steps. Unfortunately, for 99.9% of people, to do this they must be fluent with the literature and much more importantly talk with other researchers. No one works in a vacuum (and don't bother bringing up counter examples like einstein or newton).

Conformity is a big problem. It might arise when too many PhDs are hustling for a small pie. I'm not sure.

Comment · 17 years ago
Sparkfun just started selling a book called "Electrical Engineering 101". I've never read it, but I imagine it's pretty good.

Do you have access to a good electronics lab? A lab + H&H might be sufficient. I learned 80% of my electronics this way, but the last 20% was learned from old crusty EEs. If you don't have access to a lab, you can build your own (oscilloscope, function generator, power supply) for a few hundred dollars. I don't know where you can find old crusty EEs.

Comment · 17 years ago
If you want to learn how to implement MCMC I recommend:

Bayesian Logical Analysis Physical Sciences by Gregory

Gregory's book explains a lot more of the engineering (autocorrelations, step size jumping, etc..). Even better, it discusses how to perform model selection using a clever annealing technique. Though model selection may not be of interest to you.

ps - MacKay's book is my nightly reading, so I'm not dissing MacKay :)

Comment · 17 years ago
Great ideas. I'm particularly impressed with the term "web 3d". The PR will just roll in -- especially in "today's economy" -- press will love to discuss Americans who actually (1) make things and (2) sell those things.

I've had a very nebulous idea that's been percolating in my mind: software designed for small machine shops to organize their work. It never occurred to me to organize hobby folk. awesome.

Comment · 17 years ago
The statement "only has meaning if the distribution is presumed to be normal" is wrong. The SD is a summary of the spread of a distribution. In fact, for most centrally concentrated distributions (including a uniform one) +/- 1 sigma corresponds to about 60% of the mass of the distribution. This is an amazingly useful thing to know.

As the above triva factoid points out, the standard deviation is an important summary statistic. More interestingly by using mean, variance (or sd), skew, and kurtosis, you can describe almost any centrally concentrated distribution. Even distribution with heavy tails.

I think what the OP meant is that most 3+ sigma results are not truly 3+ sigma, because most distributions in this world are not gaussian, but instead have large wings. SD is most useful when you know what the underlying distribution is. Currently it's more in fashion to communicate spread using confidence intervals because they presume less about the underlying distribution.

Comment · 17 years ago
Comment · 17 years ago
Fortunately for you 2009 happens to be the international year of astronomy. Buy your daughter this:

https://www.galileoscope.org/gs/

She'll be able to do a variety of experiments on it, and if it turns out she actually enjoys looking through it, you can then buy her something more pricey.

Comment · 18 years ago
How complicated is it? Can you make it yourself? It's probably best if you do. If you have something you want to make in quantitiy, you'll want to hire someone who is experienced with tooling up a factory efficiently. What you're doing is not really engineering, but more like "drafting".

If you live in the bay area: http://techshop.ws/

If it's relatively simple, you can find a CAM house that will build the part for you, but then it becomes expensive. This place has an FDM house (wikipedia for details): http://www.emachineshop.com

You can find cheap drafters on craigslist who can make a solid model of your part that you would ship to the machine shop.

good luck

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