skysight-inc/HackerNews huggingface dataset:
You bring up good points! As a beginner, you are uniquely poised to observe these things, so thanks for sharing! I think a big part of the install problem is that some of the options (stack, platform) are fairly recent.

I recently got a new machine and decided to try _only_ using stack. All I had to run to get started was

$ curl -sSL https://get.haskellstack.org/ | sh

The advantages of stack are that:

* I have an easy upgrade path for GHC (no need to install or uninstall) - I just change the global resolver
* I can have multiple GHC versions installed at once (great for debugging)
* getting rid of old versions (to clear up space) is just deleting a folder
* most of my dependency problems get solved by resolvers

The only downside I've encountered so far is that building GHC itself is quite finicky with this setup. Unlike the Haskell Platform, I will have to install manually the libraries I need - that makes development offline quite tough (you find yourself without internet and without the library you need installed).

That aside, one good starting point for building up Haskell is the 99 problems [1]. Haskell is more general purpose than Elixir, so past that, it really depends on what you want to do with it.

[1] https://wiki.haskell.org/H-99:_Ninety-Nine_Haskell_Problems
Here's the google cache: http://webcache.googleusercontent.com/search?q=cache:C8EN9HS...

I can't see much content in the cache but I watched the video. I think she's somewhat right, but we should be careful not to lump all H1Bs in the same category (also not a fan of the slightly nationalistic language, but it's not too bad).

There are essentially two types of H1B. The one that she describes in the video is one kind, where companies like Infosys and Tata bring over thousands of H1Bs, and then provide consulting services (which are banned by H1B). I don't have firsthand experience here, but you can look at the number of H1Bs by these companies (almost 50% of the allocation) which holds up.

The other type is companies like Google and Facebook who can't get enough good engineers, and try to bring in great engineers from abroad. (I've seen it argued that they do this to depress wages, but I'm skeptical of this).

The former seems like an abuse, the latter I don't think is.

(disclaimer: I'm a former H1B holder)
“I have always thought of Christmas time, when it has come round, as a good time; a kind, forgiving, charitable time; the only time I know of, in the long calendar of the year, when men and women seem by one consent to open their shut-up hearts freely, and to think of people below them as if they really were fellow passengers to the grave, and not another race of creatures bound on other journeys.”

(dialogue from Fred, nephew of Scrooge, in Dickens' _A Christmas Carol_)
When you spend half of your comment on justifying it's existence, it might be the wisest choice to just not post it at all...
Why is this upvoted to the front page? How is this article in any way interesting?
I've always been curious as to how you structure your models in Django.

I'm building a personal project in Tornado and MongoExpress, and the only thing I can see about structuring my models is to put all of them in one file called models.py

I'm used to the RoR way of doing things, so this seems very counter-intuitive to me.

In addition, whenever I try to break the classes into different files, I'm not sure of where to store my DB connection logic, and how to ensure that all models are accessible from the controllers.

Ideas?
Volunteer open source developers are not interchangeable cogs ('resources') to be redeployed across projects at will by anyone except themselves - they are volunteers and work on stuff they are passionate about.

The F/OSS 'community' has some of the most entitled folk on this blue planet - I'm yet to hear anyone suggest pet shelter volunteers work together on a mega-shelter instead of "wasting effort on duplicate roles".
I found it interesting, so here's your data point.
Starting with Astronomy. I like idea of stargazing & fascinated by reading about stars like KIC 8462852.

On programming front, Rust is looking good.
But it's old news. It just says "marriage isn't the honey-moon, but it's still worth it anyway," but in like 15 paragraphs.
Published May 28, 2016

Previously on HN:

- 2 weeks ago, 40 comments: https://news.ycombinator.com/item?id=13150655

- 208 days ago, 101 comments: https://news.ycombinator.com/item?id=11809381
Taxis are usually disgusting too. I won't take a cab because I frequently feel like I need to shower after sitting in one. I rate Uber drivers almost exclusively by their cleanliness, which is usualy very good.
This thread is awesome, so much enthusiasm and curiosity.

I'd like to learn/do a couple things in 2017:

- An overview of college-level conceptual physics. Historically I've tried to leap-frog into advanced physics because my math is pretty good, but I end up missing out on the concepts. So I'll stop rushing and do it step by step.

- Deep learning and deeper machine learning. I'm pretty familiar with ML in general but have never had the intimate understanding I've wanted, nor taken the time to properly dive into DL.

- Bahasa Indonesia and Mandarin ^_^ (while maintaining the rest)

- Abstract Algebra and Information Theory

- Keep up the pace with reading interesting books

- Become more familiar with devops and systems programming (Docker, Rust etc...but not an expert necessarily)

As an aside, I'm also trying to improve my running, swimming, and martial arts :)

I'm sure other things will also pop up in time!
Political quagmires like this only get untangled by terrifying psychos, unfortunately.

People only shut their mouths when they get threatened into a fearful silence, and/or sometimes if they get bribed enough.

Otherwise, you'll always have a substantially sized group of complainers dragging down a project this big, and the complainers leech into operations and mysterious expensive mistakes erode the budget of an already expensive operation.

There's just enough shrug factor here for people to not care about how much gas they burn driving to places that might not be very exciting to begin with.

Many would just as soon not have to travel at all, and even more would prefer to not be taxed so as to pay for trips they personally don't want to take to begin with. Most people just want their actual lives to be generally easier.

Without confrontational intimidation, bribery is probably the only other political lever to press in the United States.
Thanks for the suggestion. Is this [0] the book in question?

[0] https://zr9558.files.wordpress.com/2013/11/algebra-chapter-0...
Looking at four 9s (4.38 min a month). Solution must be self hosted and not reliant on commercial cloud infrastructure.
There's several good blogs out there but I really suggest reading Traction [0]. It's well organized and very practical/easy to put into action. I've bought copies for multiple people (including my wife who recently joined a startup doing marketing).

Also you used the word "sell". Don't forget that sales is different than marketing. If you plan on doing real sales the book Predictable Revenue is great (though designed for slightly larger teams than just 2).

Good luck! And don't forget, NPS tools are good for brick and mortar businesses too.

[0] http://tractionbook.com
While I agree with you in principle, your application is wrong.

IMO, China's innovation is in large-scale PCBs and other such manufacturing. See Apple's investment of CNC machines in China as an example. China has several other innovations that does in fact make them a world leader in certain fields.

As far as battery tech goes however, Japan has that on lockdown. Panasonic's Silicon-Lithium batteries are light-years ahead of the competition, even as US battery manufacturers (A123 systems) try to break through. Japan (and Panasonic really: now that Panasonic owns Sanyo / Eneloop) has all of the major high-quality battery manufacturing facilities: Energizer, Duracell, Panasonic (owner of Sanyo / Eneloop).

Korea has the next best bet as far as I can tell. LG Chem's batteries were chosen by GM probably for some reason.

If China were to be making good batteries, then we'd first see some manufacturing companies make some batteries. Most "top-down grown" companies, be in the USA or China, fall flat on their face for the first few decades. It takes a long time to build up expertise.

-------------

There's no reason why China can't grow into a battery powerhouse. Except for the fact that Panasonic is so massive.
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> as has been discussed elsewhere, the ability to avoid using google services is a serious disincentive for google to support cyanogenmod.

The same argument applies to AOSP (cyanogenmod's upstream), but that hasn't stopped Google from supporting it.
“Riding the Edge” of Technological Change
It's look like you follows utilitarian philosophy[1].

[1] https://en.wikipedia.org/wiki/Utilitarianism
While I agree that comparing China to California in terms of large scale engineering works is comparing apples to oranges (guess which is which). I disagree (kind of) on the following:

> There are also a lot of rather substantial engineering issues that have to be overcome in California

Japan is a mountainous, earthquake prone country, and they seem to have figured it out. The biggest problem geography-wise is probably all the NIMBY complaints. To be fair, they are really loud trains that would kill property values, and the complaints are valid. I think thats where a lot of those lawsuits are coming from.
I'm going with rust as well as a follow on from currently getting myself reacquainted with lower level programing (c), building desktop apps and flex/bison. I "knew" c++ >10 years bet went to more productive environments to build apps. What I'm discovering now is that this productive is more from experience than from using higher level languages.
Rush hour traffic is due to human drivers making bad decisions. They knee-jerk the brakes just in case, they rubber neck by accidents, they take too long to accelerate, they try to cut other people off from merging, etc etc etc...

Computer drivers could make much better use of the existing bandwidth on freeways. I'm guessing 6X better, since my 15 minutes drive takes 1.5 hours during rush hour.

It could be a long time before we ever have enough automated cars to realize this benefit. But when that days comes, we could safely increase speed limits too (computers generally have better reaction times).
Thank you for doing this.

In 2011, I donated a mass of Mac computers to a podcaster who wanted to set up a museum of Mac history. It was a lot of work.

Not news to the HN readers, but yeah: computers used to be even more difficult to use than they are now. And of course getting all of the bits together for a working system takes a lot of time.
This opinion is unfortunately common in the Haskell community and one of the biggest things holding back Haskell adoption. I'm a big fan of Haskell (see my recent comment history), but types are not sufficient documentation. Doubly-so with the cryptic symbols / function names that are so prolific.

Python, PHP, etc... are incredible in that every single page of their standard library docs have fully worked examples. When you're trying to get things done, it's great to have a foundation to start from and see how others have done something.
The issue isn't engineering, it's the cost and amount of labor. It can be significantly cheaper to tunnel through a mountain range in an almost straight line than to build on top of one. Once you've started digging into the mountain, you just keep digging and building the tunnel. Barring any maintenance and additional surveys, there is little interruption and the overhead costs can be amortized over the entire length. You will have to swap out drilling equipment as you hit different types and densities of rock but you can often go miles without doing so.

To build on top of a mountain range, there is a smaller overhead cost to survey, do an engineering/environmental study, cut earth, and lay down road but you literally have to pay that overhead for every few hundred feet because as the terrain changes, the equipment and other infrastructure you require also changes drastically. To build a highway you have to have strong ground to build on, which is why US freeways largely bob and weave all over the place instead of just going in a straight line, and civil engineers avoid weak ground where soil stabilization will be most expensive. On mountain roads, not only are the options for soil stabilization limited to very labor intensive methods, but you also often have no choice but to take a bad (expensive) route because you have to design safe turns and gradients. The problem isn't that the engineering is harder, there's just a lot more of it to do.

Also, United States property rights are pretty unique as far as Western countries go. To build a tunnel you'd have to get the mineral rights from every single property owner in your path whereas in most European countries, mineral rights are owned by the government. If you're going to compare a Swiss tunnel to any US road projects, you have to account for the massive differences in legal fees and land acquisition because whether you build above or below ground in the US, you have to deal with the property rights of private owners and all of the extra safety/environmental/etc regulations that come as a consequence.
LibrePilot: control multicopter and other RC-models
Artificial Intelligence, Autonomy, and the Economy [pdf]
the day internaut became a fashy goy
> Prior to 2003, people were less interested in non-sentient autonomous machines.

Yeah, you're just making shit up. The first machine intelligence in pop culture can be found in https://en.m.wikipedia.org/wiki/R.U.R. (the origin of the phrase "robot"). Non-sentient autonomous machines are even older. https://en.m.wikipedia.org/wiki/Golem Sci-fi authors have been talking about modern-looking self-replicating machines for decades.

Maybe you have some weird definition of a drone? Drones in common parlance have come to be associated with any robotic vehicle, and are used in technical parlance to refer to a huge variety of autonomous or semi-autonomous machines.
The most expensive line under construction is the Tokyo-Nagoya maglev line, at $50 billion for only 286km. It's maglev at 500km/hr, and it's 90% in tunnels. They're going straight through the Japanese Alps. Under construction since 2013, opening scheduled for 2027.

43km of track is already in operation as a test track. Here's a ride video.[1]

JR expects it to be profitable.

[1] https://www.youtube.com/watch?v=5CKwchJKTYU
Online Sexual Harassment Training Course
It's way more than playing music by speech. It's looking up stuff, controlling your house, checking restaurant hours, all sorts of functions that would otherwise be fulfilled by a smartphone with less input effort.

Give one of these devices a try, you might be surprised by how much you adapt to them.
You are misinformed. Tesla does not have a permit for every single "self driving" car they have on the road.

There are 10s of thousands of self driving Teslas on the road right now, in the hands of customers. You can buy one! You don't have to get a permit for them.
Learning Machine Learning: A beginner's journey
Fastlove :(
guy was a genius
I want to be able to get independent and start my own business. I love to write, which I have started slowly over the period of time.

All the best to everyone for their learning goals.
Oh really.

Starting in the 1950's the United States Air Force used unmanned drones as target practice. They were just cheap remote control aircraft. [0]

[0] https://en.wikipedia.org/wiki/Ryan_Firebee

Then comes The Global War on Terror, and suddenly drones find new uses. [1]

[1] https://en.wikipedia.org/wiki/Global_War_on_Terror

In 2002 the first Hellfire missile is launched from a Predator drone. It doesn't kill Osama Bin Laden, and people raise eyebrows, but it's not a trend yet. It's a brand new thing to conduct hostilities like this. [2]

[2] https://en.wikipedia.org/wiki/Operation_Anaconda

In 2003 Iraq gets invaded, and drones become way more interesting to everyone, everywhere, because now wars are being fought with them. [3]

[3] https://en.wikipedia.org/wiki/Iraq_War

The word "drone" has a specific meaning. They are a specific concept. I know what robots are. I know where the word came from, and when it was invented.

Spare me.

I continue to disagree with you. I am also done replying to you.
There's many options for Python but check out CherryPy. If you can write a class, and a few methods that return text (or HTML) you can write a full blown website with CherryPy. It maps methods to URLs.

http://cherrypy.org/

Just look at HelloWorld. As for templating, I personally use Mako:

http://www.makotemplates.org/

Mako is used by Reddit. A few months back I was hired to code a back-end API and I chose Python and CherryPy for the stack, never done as much web dev as I have since. Got a fully working app. Can't recommend much for MySQL, except either SQLAlchemy or PonyORM.

You can make a simple website / web service in CherryPy, and yes RESTful services can be made as well. I say start with basics. Even if you don't use CherryPy in the end, you can start testing it right away with the hello world example. Just don't forget to pip install cherrypy
Top priority: How to be Happy.

And also some Kubernetes, Docker in more detail, explore rkt and CoreOS, perhaps also get into details of linux kernel and finish a custom build from http://www.linuxfromscratch.org/
Get more depth into system security

If time permits, would love to learn more about Quantum Computing and explore if I can contribute in any way.
Self driving, privately owned cars, sure.

There are two issues that I think get talked about together, whenever the idea of self-driving cars comes up: self-driving cars themselves, and then self-driving cars as part of an Uber-like pooled vehicle business model.

I think that self driving cars as a technology are definitely on the horizon, and if they don't hit any major roadblocks (literally or figuratively...), some level of self-driving capabilities might become mandatory in the next couple of decades. It makes driving on freeways much safer, and also allows for types of interchanges that aren't possible with human drivers.

But the argument you sometimes hear tossed around, that self-driving cars will lead to Uber-like services displacing all or nearly all private car ownership... that strikes me as much more speculative. There are cultural-psychological aspects to car ownership, and I'm not convinced that the value proposition could be made sufficiently strong to cause people to not want to own their own car, while still creating a viable business for the pooling company, in a suburban or exurban (to say nothing of truly rural) area.

Owning a car in a dense city is a pain in the ass and a huge expense; owning a car in a rural area is basically a necessity to live as an independent adult. It'll be a lot harder to get people in that second group to switch to vehicle pooling than the people who probably detest having a car in the first place for all the expense and inconvenience it causes.
Environment setup has been heavily discussed[1] in the community and is definitely a pain point when getting started with Haskell. Unfortunately there are several sides with differing opinions on how to bootstrap a user and get them using Haskell, although the new Downloads page seems to be a good first step towards achieving a more unified goal.

The opinions kind of break down as:

1. Simply get GHC on their machine - Typically academic instructors trying to get their students started with low overhead. They simply want GHC and GHCi available so an assignment can compile, or code can be tested in the repl.

2. Install Haskell Platform - This has been strongly supported by what I would call the older Haskell community, although admittedly share your confusion as to its point. This seems to target point-and-click users and give them every tool in the ecosystem so that when they reference the random blogs/documentation out there they aren't confused by missing a command.

3. Use Stack - This has been heavily pushed by people trying to help Haskell grow in the programming industry. It's a fantastic tool and I recommend everyone use it if they plan on doing complex projects, especially in a team setting.

My hope is that over the next year or so we'll see more stack adoption, ideally because there are more consistent tutorials/guides/documentation published which target it as the basic tool to start developing Haskell in.

[1] https://www.reddit.com/r/haskell/comments/50prvg/haskellcomm...
this might be of interest: https://medium.com/@jlouis666/breaking-erlang-maps-1-31952b8...
You're not the target audience.
This is one reason I installed ReactOS. They make their own framework for the OS, and they haven't made too many apps, so my idea is to add in the things I need for myself.
As a California usually in favor of all sorts of new technologies and futuristic projects, I am totally opposed to building this train system. The air travel infrastructure is already in place and could work even better with an investment of a fraction of the $64B. Airplanes don't need expensive rails to ride on in the sky. What's better about getting into a coach of a train and rolling on the ground over getting in the coach of a plane and flying through the sky? Let's stick with what is and what works and spend the money on desalination plants, wind farms, solar plants and a smart electrical grid.
>China of course has IP laws, since they're a signatory to international conventions like the Berne Convention. Enforcement is quite another matter.

Laws which are not enforced (and will not be enforced) aren't real laws.
I'm not an expert on generalized A.I. training but it seems like the problem of training with audio and visual data input from games suffer the exact scale problem with Alpha Go at specific tasks. I could imagine training an A.I. to play a complex RPG game like Witcher, you would first probably need to train on a horse riding game, a running game, a weather reaction game, a free fighting game, a trading game and maybe a couple hundreds of thousands of games, each for a couple million times of trial and error? However, it also seems that human doesn't need to take this amount of reinforcement training data to quickly understand the complex mechanics in life. Wonder if there is any comparison between the amount of trials and errors a baby need to go through V.S. an A.I. need to go through using reinforcement learning to stand up and walk under similar gravity and muscle group setup?
How is it essential? It does nothing for the real transit issues in California, which is urban/suburban commuter traffic. There is no particular need for high speed rail between SF and LA - that need is served by air travel and the 5.
If that's implemented by way of some sort of public agency which obtains, analyzes, and releases sanitized versions of the data collected by self-driving cars for the benefit of the public... then sure, that sounds like something we ought to do.

But I would probably not phrase that as asking for a "central database" as though it's being fed by the cars themselves. That sort of centralization is... architecturally suspect, for a lot of reasons.