adamcanady

This is neat but the map by public transport time is probably non-euclidean because subways are like wormholes.

Apparently this isn't the same Krebs as https://krebsonsecurity.com/ [0]

[0] Funny enough, the website has a broken SSL cert at the time of writing.

I recently did this using Electron's BrowserView.

I had to step away from using electron because I encountered segfaults like `Received signal 11 SEGV_MAPERR 000000000060` just on visiting cnn.com and clicking one of their nav links (without much going on otherwise, which I found kinda crazy).

Electron also only recently added support for PDFs, and it's still a little buggy. I was able to get around most of these with pdf.js.

I ended up using a combination of chrome extension for injecting stuff into webpage + rpc to a local node.js server running inside an electron app (for convenience). I only made this for personal use, so I'm ok with <arbitrary_caveat>s.

Js_of_ocaml [1] is a good alternative to BuckleScript for standard OCaml (non-Reason).

For example, it works well with Core_kernel [2] and Async_kernel [3] to provide high-level functionality that is cross compatible between Unix applications and browser applications.

[1] https://github.com/ocsigen/js_of_ocaml

[2] https://github.com/janestreet/core_kernel

[3] https://github.com/janestreet/async_kernel

Didn't realize this system used a CVT-like system to generate electicity. I've generally been curious how this system seems to be significantly more complex yet more reliable than many modern internal combustion engine drivetrains. (My personal perception, haven't done much research to look it up).

I also wonder why Apple allows some apps to accept payments via credit card yet others need to use the built in payment solutions?

EDIT: some research later indicates that it's possible allowing a user to sign up outside the app (and outside a webview initiated by the app) skirts around the policy [1], since the user can return to the app and log in, then use their account for payments.

[1] https://www.designernews.co/stories/9695-how-do-apps-like-ly...

How does it work? Searching for book store (https://www.closient.com/?q=book_store the underscore was autocompleted) gave me results that were 1200+ km away from my current location. Other queries did the same.

I guess I wasn't too far off geographically with Romanian Wikipedia :)

Keep up the great work at https://www.seznam.cz/ ! Lots of interesting search features, maps, etc.

I work on Google Search. Having one search engine per country doesn't seem like the correct approach to the problem.

Every country has a mammoth collection of valid results for your query.

Having seen the corpus of content available from each language, this is categorically false. Consider Wikipedia, which is a fairly ubiquitous information source on the web that provides answers to tons of searches. English documents: 5.4M, Romanian documents: 376k.

Perhaps the solution to the OP's woes is more tools for filtering. This post conflates the ideas between language and country. Search typically returns to you results and search features that are in the query language. Today's solution where filtering is done through query refinement and query operators seems to cover a lot of use cases already.

Further, by having an integrated product, ML models can learn behaviors specific to certain locales where those behaviors differ from region to region, and balance with more universal behaviors that apply to more than one region.

Also the hostname of "TayandYou".

  Location: Minneapolis, Minnesota
  Remote: Yes.
  Willing to relocate: No.
  Technologies: Python, Node.js, Meteor, HTML5/CSS3/JS (lots of past frontend work 
    with SCSS, Rails, Flask, PostgreSQL, MySQL, Mongo). 
    Some Scala, Java, and Go as well.
  Résumé/CV: https://wheat.co
  Email: hello@wheat.co

you believe you'll be able to create more value for yourself by doing something else rather than seeing it through with a startup.

Just pointing out that there are other reasons to leave aside from rational economic thought about this individual's expected ability to produce higher output elsewhere. They may dislike the team, pivoted idea, or leadership decisions. But they may also want to keep hold of the equity in case it gets big (or they can sell it or a liquidity event occurs).

This is typically the way it's done in Node.js's Express library: http://expressjs.com/api.html#req

It's also about a lot more than ride sharing. These companies are hoping to turn their LaaS (labor) into self-driving car fleets as soon as possible. A lot of that money is going to be poured into research.

Actually, I think that's incorrect. I'd say that the median person who knows how to drive is better off than the median person without that skill. Certainly the best person who doesn't know how to drive is better off than the worst person who can drive, and it probably has nothing to do with driving ability.

To get this straight, when they indicate 96% utilization of the uranium, they don't mean converting 96% of the total energy to electricity, as it is assumed that some will be lost along the way, right?

If the above statement is true, what happens to the remaining 4% of the energy in the uranium? Is it just not effective to have it in the molten salt, so the entire batch is replaced? Or does this happen 'on the fly' so to speak?

Some day I may turn this into a chrome extension to highlight limericks on arbitrary pages. It would be joyous to see a highlighted section of some random wikipedia page pop out to be a limerick!

I'm a junior at Carleton, #2 on the list. It's interesting to see these rankings come out since I have been under the impression that our graduates don't enter STEM fields through normal channels. Until recently, our CS department didn't have very many majors, and many of the graduates majored in liberal arts areas. These folks found their way into big tech and financial companies or ended up starting their own businesses several years after graduation.

Talking to alumni, I've always heard this is because of the ability to learn how to communicate here, but I think the difficult course load contributes a lot to character throughout 4 years here. I'd be interested to hear how this compares to other institutions.

The additional stats on the Brookings.edu page [1] were interesting as well.

[1] http://www.brookings.edu/research/reports2/2015/04/29-beyond...

This is actually pretty neat. As someone who has worked on many wordpress sites for a long time, having faster everything would be amazing.

The product looks very polished and I hope to see it grow and develop a large community. That would make it a real WP competitor since the main reason WP is so powerful now is because of all the themes, documentation, and plugins.

The source code appears to indicate $5.99 for a 48 hour rental.

Wait a second.. can you explain the 10x the max frequency part to accurately reconstruct the shape of the signal?

It's my understanding that you just need 2x (two points in a sine wave) to construct a unique wave. If you're getting a sawtooth, it means that you're sampling a wave that is composed of very high frequencies, and you're accurately sampling it, so a DAC can reconstruct it uniquely.

Wow. I can make sense of a little bit of the original source, but I wonder more how RegPack [0] works to compress it into that final submission!

As a side note: I'm in college now and looking to propose an independent study on compression. Any suggested readings or algorithms I should look into?

[0] https://github.com/Siorki/RegPack

This is awesome, but I see a lot of complaints from people who can't get it to work. In the past, I've used netflix-desktop[0] to watch from my Ubuntu partition. I've found that it works exceptionally well.

[0] Google netflix-desktop, or here's a decent install guide I found on the fly: http://askubuntu.com/questions/419255/just-installed-ubuntu-...

Haven't done the math myself, but if you factor in years of salary earned while the doctor in training would be at school/residency/fellowship and the salary on that page is for folks who have been at it for a while and either have a private practice with many clients or have been in academia for 10-15 years.

Is it then possible to model 2nd order Markov chains with every two words containing their own file? Filename: this_example Contains: is, can, etc...

FYI I'm getting an SSL error on that domain using Chrome 34.0.1847.116 on Mac OS X 10.9.2

How much overhead does this add and how difficult would it be to implement in another language like Python or even C? I imagine implementing it for an interpreted language would be much easier if you could save and recover states at any given point.

For example, in a project I just completed where we implemented Scheme in C, perhaps we could just memcopy everything and add it to a stack upon each expression evaluation (much easier in Lisp dialects since expressions are nested and you could 'edit as you go' by just changing an inner expression).

At my undergrad institution, we have a class that does a project very similar to this. I recently completed the class and project and have a bit of advice for anyone looking to take up this challenge on their own.

First off, a small note: our project used C to implement Scheme (a lisp dialect), so it's similar but not exactly the same as this.

I'd recommend starting off with reading about the principles and coming up with a solution to each of the problems on your own instead of following a specific pattern as outlined in the book. For example, in our project, we decided to learn about the C basics, then just figure out how to make it 'act' like Scheme if given an input. Eventually, we thought of doing everything in a linked-list style to make organization and recursion easier and more natural, but coming to this conclusion on our own was very helpful.

Another thing is valgrind. As far as I could find, the text only mentions valgrind in one paragraph, but it's an excellent tool to check for memory leaks and errors.

Also, as mentioned in the book, a bonus is adding in GC. This turns out to be a pretty easy and a fun exploration of the different techniques available if you try a couple out for performance.

Our code in case you're interested: https://bitbucket.org/adamcanady/cs251_interpreter/src

Unless the satellites are in geosync, it's likely they are orbiting and could just randomly come across the correct area at that time.

If not, I'm wondering why people like Skybox [1] didn't deploy resources immediately to start covering ground. It seems like that approach would be much more effective than ships in the ocean?

[1] http://skyboximaging.com/

Probably counting \n as a character since Python is pretty good about never dealing with \0's.