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.
Yeah I see a lot of reporters going gaga over Web 3.D because of the physical production aspect and the way it fits in with the whole numbering scheme. I see as many readers of this site rolling their eyes though.
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.
I should have said something more like "the standard deviation calculated from a sample set is only generally applicable in so far as one is willing to make assumptions that the sample set is representative of the distribution as a whole". The default assumption in traditional statistics (such as quoting p-values) is that the distribution is normal, and in real world situations often not the case.
Your restatement is right on, although I'd go farther and say that standard deviations (and confidence intervals) are only useful metrics with regard to the particular assumptions one is willing to make about underlying distribution. Yes, you can calculate these measures, but they won't help you if your assumptions are irreparably flawed.
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.
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 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.
I second http://www.emachineshop.com
The software is fairly easy to use. You can get your prototype built in pretty much any material you can imagine, and the price is pretty good too.
My only problem was the cost to ship custom cut boat glass to Alaska. Ouch.
I've asked this question months ago, but I never received a satisfactory answer:
What is the value of stock in a private company? Do you receive dividends on the stock? You can't sell the stock to other people? The only time it's of value is in a liquidity event. Suppose Fog Creek's not planning one in the future, what does this stock do?
Stock is obviously part-ownership of a company. When a company makes a profit, it has basically two options - 1) re-invest some or all of the profit back into the company, or 2) divvy it up amongst the owners (ie. stockholders), which is more or less a dividend.
My old man runs a small business with about five stockholders. It's a mature business and he has no real plans for expanding, so every year he divides the company profits up between the shareholders.
You could sell your stocks to other people, but this would depend on the rules governing the buying / selling of shares as set out by the company when you acquired the stocks. Often this is just by agreement because there isn't a very liquid market for shares in private companies (for obvious reasons like lack of transparency and difficulties in valuation).
If I were to buy shares in a company, my valuation would depend on the company's earnings and the opportunity cost of putting my money in a "risk-free" investment (like treasury bonds)... which would dictate the base price-earnings ratio for which I would be indifferent to investing in the company or bonds. Of course, the company's potential for growth would affect the valuation (ie. higher P/E for growing companies).
It has the same value as anything else: Whatever you can get someone to pay you for it.
I just sold a chunk of (common) stock in a privately held (VC-backed) firm. I found a buyer, made sure I followed all of the rules of the employee stock agreement, and made a sale.
It is harder than publicly traded stock, but it still has value.
I've been intending to play with CUDA compuation for a while, this seems like a great way to begin. It's especially nice that the documentation seems helpful. I'd be curious to hear peoples experiences with pycuda.
Greg and I talked about this last week, and it seems quite useful. I've been playing around with Cuda computations for dust temperatures and calling it from python would be useful. The biggest hurdle isn't the interface, though, it's rewriting your code to run on the GPU, so pycuda isn't such a big change since you still have to write the GPU code in C.
You're almost better off writing python modules in C that take advantage of CUDA for specific applications instead of using a general one that really doesn't hide any of the more difficult pats of the CUDA API anyways.
The point is that climate models are not testable. Bernoulli's equation is a "good" approximation because we know when it fails.
If we're going to rely on climate models to define policy, we should understand what they're good for. You say that 0.5 m v^2 is a good enough approximation until we say otherwise, but the same statement doesn't apply to climate models. The models are complicated, nonlinear, and the scientists running them have pressure to produce certain results.
Climate models are testable. It just takes a long time to test them, since they describe long term behavior. Fluid dynamics is nonlinear, and complicated, but certain effects, such as lift, or drag, are both simple and broadly applicable. So it is with radiative models of global heat balance. Heat powers the climate! Altering CO2 will alter the flux of infrared radiation which will alter the flux of heat. This basic mechanism is uncontested. I could be that the total heat flux doesn't change much because it's balanced by other effects. But we know of no other effects sufficiently strong to render the temperature change small. If we have a physically plausible model that fits measured datapoints, and we keep check its predictions against measurements, and we keep asking 'in which ways might this be different?' and looking for possible problems, or effects that we've missed, then this is science at work. If instead we say "it's complicated, and there are some areas in which there are gaps in understanding, therefore we should draw no conclusions and make no decisions," we achieve little.
This is tangential, but you seem like you are informed on the climate debate, unlike myself. Feel free to ignore this if you consider it a troll, or that I'm bringing up tired and often refuted points.
Anyways, I've been reading a climate change skeptic, James Hogan, and he makes a pretty interesting claim. James says that 90% of the earth's warming is caused by water vapor. Of the carbon dioxide that does contribute to warming, only about 2% (as I recall) of it is human contributed. I haven't checked his sources, but these numbers seem pretty hard to fudge. That means we contribute at most 0.2% to the earth's warming with our carbon dioxide.
James also made a number of other points, like the measurements used to prove global warming are taken around developing areas, and more objectively obtained warming and carbon cycles show very strong correlations with solar activity. But, the water vapor point stood out the most in my mind and seems to clearly demonstrate we're overreacting.
Is there some kind of fallacy that I'm missing? Am I significantly underestimating the potential for that 0.2% to push us over some kind of tipping point? Thanks for any input you can give.
[edited a couple times b/c I'm too tired to do basic math]
The IPCC models do account for both water vapor and solar irradiation. Water vapor is the dominant greenhouse gas. It is roughly correct to say that it accounts for 90% of the greenhouse effect (the lowering of infrared flux from the earth to space). However, it's not correct to say that 90% of the earth's warming is due to water vapor, if what one means by warming is change in average temperature over time. The amount of water vapor has apparently not changed very much.
Here's some figures tabulated from the standard models, from the fourth IPCC working group is found here:
These figures are estimates of anthropogenic forcing, in other words, how the components of the heat flux of the world changed due to the ecological changes. There are quite a few things here which can be measured quite accurately: cloud albedo being one, stratospheric water vapor content being another.
These were estimates made in 2005. According to them, additional stratospheric water vapor accounts for less than a twentieth of a watt per square meter, and variation in solar activity less than a tenth. Anthroprogenic carbon dioxide accounts for around 1.7 watts per square meter, averaged over the year, over the earth.
As for the claims that measurements of global warming are taken around developing areas, I think that claim is most fraudulent. First of all, one can measure the surface heat quite accurately by satellite by looking at the ratio of radiation in different 'infrared windows'. This allows you to calculate, via the Stefan-Boltzmann radiation law, the temperature at a surface.
Second of all, and perhaps more obviously, nearly all glaciers and icecaps are melting or receding, and these are not exactly developing areas! Melting ice-caps are measurements too!
You're wrong. The free market comes from the board of directors who approve such the "heads I win, tails I win" package. The board was not forced by any non-free-market laws. Thus, these compensation packages show the free market working.
"Free market" can mean a lot of things. I seem to recall that the robber barons were pretty forceful advocates of a "free market" (by their definition of course). However, my point really doesn't depend on that, and I don't want to dispute terminology, so I've revised the wording to say "entrepreneurial" instead (by which I mean something like rewards-following-value-creation).
You shouldn't have changed the wording, because you were right: the free market contains the seeds of its own destruction: in a free market manufacturers are free to form a cartel and deny others the chance to enter into their market. Which is exactly what happens when there's no government around to regulate the free market into, uhm, being more free.
The typical barrier to entry erected by many cartels in the US involves government action. The typical barrier to entry for non-regulated industries, like cocaine manufacture and exporting in Central America, involves firebombing a new market entrant's facilities and executing their families. Imperfect as it may be, I prefer the more heavily regulated version.
Yeah, that seems to be the historical lesson: free markets don't stay free on their own, so there's a limited role for government to play in keeping them free, much as there's a role for referees in sport. To me this isn't particularly controversial. But "free" is one of those words that easily leads to pointless arguments because people are working from different definitions. To me, "free" doesn't imply no government involvement, precisely because of the paradox you mention [~]. It has more to do with competition and meritocracy (may the best man/woman/product win).
[~] Edit: by contrast, npk's comment implies that "free" means "absence of laws". A different definition.
You shouldn't have changed the wording, because you were right: the free market contains the seeds of its own destruction: in a free market manufacturers are free to form a cartel and deny others the chance to enter into their market. Which is exactly what happens when there's no government around to regulate the free market into, uhm, being more free.
Alex3917 - I don't disagree. But, isn't Godin's approach still masterful self marketing? Being self-referential is tacky. So, justifiably, he avoids it.
My point: the fact that you know his style of promotion means he's self promoting. :)
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.