I think we do know a little of it. They used limestone and an acid -- so the touching surfaces of the rock were softened, which is how they conformed so closely and precisely to each other.
394 karma · joined September 6, 2011
Recurse Center alum. (Winter 2013 batch) Currently at Stripe; previously at Google.
If the long list of evidence is too long for you, then it's totally worth clicking the "click here" link to jump to the author's summary at the end. The summary is readable and useful by itself -- and it is what you're looking for if you really just wanted him to summarize the research for you instead of telling you about all the relevant studies, one by one.
"Automatic speech recognition is not currently a substitute for human transcription, because computers are unable to use context or meaning to distinguish between similar words and phrases and are not able to recognize or correct errors, leading to faulty output. The best automatic speech recognition boasts that it's 80% to 90% accurate, but that means that, at best, one out of ten words will be wrong or missing, which results in a semantic accuracy rate that's often far lower than 90%, depending on which word it is."
(this is a subset of the answer to "Will speech recognition make CART obsolete?")
There's a lot that can be learned by paying attention to other people and trying to understand what they're thinking. The earlier that someone who's not naturally adept at it realizes that this is important to pay attention to, the earlier they get better at social skills. Some of that can be highlighted for little kids while reading (story) books; paying attention to and asking questions about why the characters do the things in their interactions highlights the idea that other people do things for reasons, and that you can guess what they are (the guessing well is a skill).
1 and end for the first and last, 2 and end-1 for the second and second to last, and so on.
They don't have IJulia (yet) though.
Multiple dispatch can make interfaces simpler: you can easily offer several "versions" of a function by changing which arguments they take, and you can define those functions where it makes sense, even if those places are spread across multiple modules or packages. Julia provides great tools (functions) that make methods discoverable, help you understand which method you're calling, and help you find the definition of methods.
Looking at some Julia code (the base library or major packages) might give you a better idea of how Julia uses multiple dispatch.
Strings in Julia are meant to be addressed in for loops; they index by byte not character because it's slow to index by character once you include Unicode. Julia trys, in general, to give you control over low-level things rather than hiding them with magic.
I like Julia because it's homoiconic, because of it's type system, because multiple dispatch is fun and new, and because it's just plain fun to write. I do static analysis, not math/science.
Manual entry on calling C: http://docs.julialang.org/en/latest/manual/calling-c-and-for...
Blog post on passing Juila callback functions to C code: http://julialang.org/blog/2013/05/callback/
The Julia plotting packages are Winston, Gadfly, and Gaston. You can find detailed discussions of which one to use on the julia-users mailing list.
I'm looking forward to giving the workshop at UChicago. It'll be my third time presenting an Intro to Julia workshop.
It may be that I'm just partially missing the point of the groups, but I think that what I was actually looking for from women-in-CS groups is "doing very technical things with other women". Most women-in-cs/tech groups I've encountered are more "doing/talking about female-focused things with women who are technical".
Do you think there are groups that do what I was really looking for?
I don't think I had anything useful to tell them at the time, and I'm still don't have especially clear ideas on how to solve the problem. Both companies are full of very nice, very smart people. They weren't doing anything wrong that I could see. It seems to me that the problem might be advertising.
They might be (unintentionally) advertising in male-dominated spaces (online or otherwise). This might be somewhat counteracted by the fact that both companies support/advertise-at specifically for-tech-women events (sponsoring a Girl Geek dinner; attending the Grace Hopper conference job fair).
Another possible factor is that both companies are known for having challenging interviews. (like a lot of well respected tech companies) It's possible that some potential female applicants talk themselves out of applying; I've seen (male) friends come pretty close to talking themselves out of applying because they felt they wouldn't get the job.
This is also something of a circular problem. The lack of female developers makes them less appealing places to work for potential new female hires; the imbalance signals that there might be problems at the company and the situation is a problem in itself. The company might also be less likely to hear about female-focused events to advertise at.
I don't claim to have a solution. I just wanted to back up that have enough women in general around does not really help with a lack of technical women.