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This is also allowed at some crossings in The Netherlands. Typically on crossings with a traffic light cars are not allowed to "pre-sort" on the bicycle lane though.

Yet cars are allowed to drive on the cycle lane (if it has an interrupted line) before turning. If they are forced to stop (e.g. when a pedestrian crosses), even though they are in violation, I doubt that they would be fined.

I was using Google Maps in Amsterdam a few months ago and tried to go to a restaurant. Google Maps led me into a tunnel and in the middle was it was happy to announce I reached my destination. It happened to be that this restaurant was located on an island above the tunnel and I actually drove right under it. I have no experience with Apple Maps though.

I have a much simpler technique: Always have a non-empty drink on your desk. It makes you take breaks to get a new drink and to go to the restroom. During these breaks you can procrastinate.

It keeps you hydrated (drink water, tea [caffeine free in the afternoon] and coffee) and makes sure you don't sit at your desk for too long periods at a time.

I'm not sure. You could contact the organizers. In my case my university supported me.

I mastered in Software Engineering at the University of Twente in The Netherlands, however in the past few years that program has discontinued and I think has been replaced by a program called "Software Technology". I'm so surprised that these kinds of programs are disappearing while the work of Software Engineers has been becoming more and more complicated due to the myriad of external products and services we are supposed to be using (the cloud, containers, container orchestration, version control/continuous integration/deployment/delivery, DevOps, GitHub, unit testing, software for remote pair programming, etc.).

I was lucky enough to be able to attend the LASER Summer School on Software Engineering for Robotics this year, which was a nice experience and I'm really grateful for Bertrand Meyer for organizing it. The LASER Summer School in 2018 will be about cryptocurrencies, so if anyone is interested in that you should certainly check out http://www.laser-foundation.org

This is quite cool, though it seems similar to RxPy (https://github.com/ReactiveX/RxPY)

I think slide 12 touches on this. Even in the case of an image we can process it pixel by pixel, but that would be lunacy!

For text great results have been achieved using automatons, but they only work for structured strings and break if you add only a little bit of noise.

I feel like ML should be considered whenever you feel like programming something requires you to deal with many different cases, you have a lot of example data available, and having some false positives / true negatives is not a big problem.

Its mostly what I hear from the postdocs in my lab. In Japan older companies seem to prefer to hire a more homogeneous work force.

Also in The Netherlands some tech companies (including one I interned at) were reprimanded for having a hiring process that discriminated against older applicants. The company I worked for had as requirement in their job ad "graduated less than 3 years ago".

Starting from scratch is indeed a tall order, and probably not possible if you didn't study it before coming here. Many students spend some time as a "research student" before starting with the PhD, so that would be the best time to get a head start.

Coming from a final year PhD student (already passed "pre-defence") doing a three year PhD in Japan:

Advice I would have liked: Don't do a PhD if you like taking classes and just want to extent that experience, as doing a PhD is very different from taking classes. Also, the classes you are forced to take probably suck.

Advice I received but ignored but is probably true: Doing a PhD actually decreases your chance of getting a job (especially in Computer Science)

Advice that I would have liked to receive, know now but still ignore: If you are in a foreign country and you don't know the language but you want to stay in the country after you graduate, learn the language! Don't spend all your time doing research thinking that you will somehow compensate for not fluently speaking the language just because you have more research achievements. (Disclaimer: I live in Japan, and most jobs, even academic jobs, require a sufficient level of Japanese language abilities)

To be honest there is so much variability that it's hard to call the US extreme.

For example, in The Netherlands (at least at my previous university) for Computer Science, BSc is 3 years, MSc is 2 years, PhD is 4 years. Non-research programs ("HBO") are 4 years for bachelors, 1 year for masters.

In Japan (at least at my university) for Computer Science, Bachelor of Engineering is 4 years, Master of Engineering is 2 years, PhD is 3 years.

At least the videos can be found on YouTube: https://www.youtube.com/watch?v=bT5rFIZZeKI&list=PL2jykFOD1A...

Maybe the notes of his course at Berkeley can be used to supplement the videos? http://people.eecs.berkeley.edu/~vazirani/f16quantum.html

Signals have been part of FRP since the first papers about it were published twenty years ago (about FRAN)

Meh, I think other companies just don't have the bravoure a man like Musk has. Also it helps if your company is a start-up and no heads will roll if you don't make a profit. Established companies don't have that luxury.

I feel like the benefits you obtain through cold showers disappear after a while as you get used to them. That's similar to the benefits I felt of meditation.

I was reading through some of my journals that I wrote a few years ago and noticed that the ones written with a pencil are much more readable than the ones written with a fountain pen. I guess picking the right kind of paper and ink is very important for a notebook not to lose its quality.

In the case of the Computer Science course from Sedgwick, I have only been able to find it on Safari Books and InformIT (30$) http://www.informit.com/title/9780134493831

If you happen to be a member of ACM, you actually get free access to Safari Books through http://learning.acm.org

I used to think the same way about the CPU, even after getting a masters in Computer Science! About a year ago I read the book Code by Charles Petzold and watched some lectures about Computer Science by Robert Sedgewick which really opened up my mind.

Avi Pfeffer's "Practical Probabilistic Programming" (Manning) is a nice book to learn about the concepts. It uses his own Scala based framework Figaro.

I'm surprised this hasn't accelerated so much, considering the availability of the internet, relatively cheap hosting, donation services like Patreon, typesetting software and platforms, etc.

This is from the same guy who made the MarI/O video (https://www.youtube.com/watch?v=qv6UVOQ0F44 - using Neuroevolution). In the video he also compares MariFlow vs MarI/O.

It depends (TM)

Some companies value GPA a lot, others do not value it so much at all. See https://www.quora.com/How-much-does-GPA-matter-when-applying...

I was about to say that too. I've also used many languages (PHP, Java, C#, JavaScript, C, C++, Scala, Haskell), and even though one language might have been especially good for the task at hand, it would not have been so much harder to do it in one of the other languages. I feel like a statement like "use the right tool for the job" is pretty meaningless.

Even your example of Create React App sounds like nicely polished scaffolding a la Ruby on Rails and Django to me.

I only skimmed over the article, but I think the title on HN does not reflect the claims the authors are making.

The title of the paper is: A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs

The title of the article is: Common Sense, Cortex, and CAPTCHA

That's nowhere near the sensationalist title at HN: RCN is much more data efficient than traditional Deep Neural Networks

Suing the daughter? I think many people will not think bad for the engineer getting fired, but I doubt suing the daughter would be worth the damage in reputation such a lawsuit would cost.

It's not quite clear to me what kind of features you have to "reduce isolation"? Also, how easy is it to integrate an existing web page design into labit?

A nice beginner friendly book about Probabilistic Programming is the book by Avi Pfeffer: "Practical Probabilistic Programming" (published by Manning). The only downside of the book is that it used Pfeffer's own Scala library called Figaro, which does not seem to get as much attention as projects such as Stan and Edward.

It seems like "arbitrary" notation is also a problem in other fields of mathematics such as Linear Algebra - perhaps depending on the background of the author in math or CS. In Linear Algebra every text book has their own favorite notation for matrices, row/column vectors (special letter such as c for column vectors, roman letters, roman letters with an arrow on top) and scalars (greek letters or the letter c).