skysight-inc/HackerNews huggingface dataset:
That's because self-driving cars aren't a car problem, they're a computer problem. Why would you think that a car company would be experts in machine learning? Doesn't matter how many decades they've been working on it, they just aren't domain experts.

Now it's possible they have since hired some experts, but a good 80%+ of all the well-known AI/Machine learning people I know of are working for Google.

Google have got the guys who literally wrote the book on AI.
This looks nice, but I do have some quibbles of a different nature.

https://github.com/Ehesp/Responsive-Dashboard/blob/master/js... - this is an expensive operation. It would be better to use window.matchMedia and do a $scope.$apply() only precisely when needed. https://github.com/Ehesp/Responsive-Dashboard/blob/master/js... is also expensive too, since getWidth is a function.

My other criticism is that it should avoid adding ngCookies as a requirement, as it is a not so great portion of angular.

I think some of the people criticizing this miss the point of something like this. It is a theme that is geared specifically towards people who use Angular & don't want to use jQuery. If you don't use Angular/want to use Angular, this isn't for you - or you can fork it and port it over.
I think all those sensors turn into big data. There's an enormous amount of information streaming off all those cameras, rangefinders, gps, accelerometers, and stock on-board car sensors (like traction control). Add hard realtime constraints for computing solutions, and you've got to handle a giant pile of unavoidable data to ensure safety.

Of course, I'm sure the data's culled a thousand ways to Sunday to make it manageable, but it's going to be like a self-contained industrial process, which can generate positively stupid amounts of data.
But make sure that you have proper isolation between the subtasks.
also in Eastern Europe...
It is the fundamental process of life

No it isn't, otherwise you wouldn't get things like hydra or the immortal jellyfish. Even lobsters appear to die through predation rather than through aging.
Calling someone an asshole isn't criticism, it's an insult.

That was criticism.
Self driving is not a big data problem at all.

It is all about sensors, algorithms, telemetry and maps. And pretty sure the car companies that participate in F1 would have a pretty good understanding of how to get all of those working together nicely. Not that it is a problem that only Google is qualified to solve.
I don't have time to write a detailed post, but would a book recommendation work? :)

"The Practice of Cloud System Administration: Designing and Operating Large Distributed Systems", coming out next month, provides a good viewpoint on how distributed systems design knowledge is useful to someone in a sysadmin role. (I've read a preview via Safari Online and found it an excellent resource.)

[0] http://www.amazon.com/The-Practice-Cloud-System-Administrati...
They PayPal guy has a track record of delivering stuff.

Google, aside from a few select areas (Search, Mail, Android) has a big track record of conceptual BS and half-baked products that get pulled back or fail in the market (Chromebook, Motorola phones, Glass, Wave, Plus, etc).
Unfortunately we don't mix the two. Npgsql is available though and I understand there is an NHibernate dialect available.
It seems Slavc was the only one of its kind from these scientists that survived the long migration.
Add alias numfiles="echo $(ls -1 | wc -l)" to your ~/.bashrc
That is another good idea. I may implement that as well.

The problem I'm focusing on at the moment is that the game is both less challenging and less fun when fewer players are online (if you have any ideas to increase player retention/engagement or make the game seem more "active" when fewer players are online).
Show HN: GoLearn
For reference, you can do this using the wc core utility. The -l option makes it count the number of lines so 'wc -l' will do the same thing as your sum expression.
There's a problem with his argument he doesn't really address. The baby analogy isn't perfect because having a baby is a physical process with a set success rate. So the math checks out, but debugging isn't a physical process. Debugging is problem solving.

When debugging there is likely to be a lot of overlap in the ideas and methods the individual debuggers use in order to find the bugs. Obviously, the debuggers can communicate with each other about what doesn't work so there are gains there. But in terms of thought processes, there will exist this overlap. It is only in the places where there is no overlap that an extra debugger is useful. And as more debuggers are added, the odds that any additional debugger will provide independent thought is diminished.

His model is too simple because it does not account for this overlap.
Angular Restmod – Rails-inspired REST ORM
'wc -l' counts the number of lines. It also supports '-c' and '-b'.

To work with input split into columns, use awk. By default, it assumes the columns are separated with spaces. This can be customized with the '-F' option.

So your last example can be rewritten as

awk -F, '{s+=$1} END{print s}' data.csv
He also ignores overhead. Say you assign 5 teams to fix a bug and 2 finish it that day. Which code get's committed? First sounds great but the odds of solving the wrong problem or introducing another bug are high. As first team may have just missed the real issue. So now you compare solutions which adds another step.

Now what happens if the bug is less than clear? You now have 5 teams that want to ask more or less the same questions.
The first two can be done with wc:

ls | wc -l
ls | grep .py | wc -l
If countries were people, then 2) would matter. As it is, real folks pay to have their children succeed. I would guess that many aren't as interested in Where (home or abroad) as When. So its not all bad or wrong.
Because the car companies ship tens of millions of cars today with auto parking and accident avoidance. They clearly know how to combine all the pieces in a robust and safe way.

And if 80% of the well known people in AI/machine learning are employed by Google then I assume that no interesting work is being done outside there. Pretty sure there are a few companies around who would disagree with you there.
Blinding ECC is as easy as RSA, if not easier. Coron's classic paper has 3 easy measures to blind a scalar multiplication, and more have appeared since then:

http://link.springer.com/chapter/10.1007%2F3-540-48059-5_25

The problem with GnuPG is not that it's using RSA/ElGamal instead of ECC; it's that it's using a general-purpose large integer arithmetic package, MPI, whose purpose is to optimize speed for a wide range of input arguments.
The article's conclusion seems to be that even if debugging/software development can't be parallelized perfectly (which is true because debugging requires a buildup of mental context about a codebase), since the amount of time required is a random variable, doing the entire task redundantly in parallel will necessarily reduce the expected value of the minimum amount of time required. For instance, if you throw $n$ developers with equal knowledge of a codebase independently at a problem whose time-to-solve is exponentially distributed with rate $\lambda$, then they'll solve it at a rate of $n \lambda$. Of course, this is almost always less efficient than letting them work on their own problems!

However, if you apply a similar analogy to reliability instead of time, having people work on the same task with what would appear at first to be redundant effort can increase reliability phenomenally. In a way, we see this in organizations that demarcate developers and test engineers - you're throwing bodies at a problem, creating a rivalry of two groups that challenge each other by attacking a problem from different angles, and in doing so you have a different distribution over the error/bug rate than you would otherwise.

An interesting read on this point is http://www.fastcompany.com/28121/they-write-right-stuff about the team that does (did :( ) software engineering for the space shuttle. Things like rigorous separation into development and testing sub-organizations... duplication of coding effort insofar as every line of code isn't just code-reviewed, but requires double-entry in a specification as well, and review of that specification... constant "process-ization" of debugging insights so the entire team doesn't make the mistake again. It's the exact opposite of "agile," but it makes sense if reliability is what you want to model and optimize.
>That's because self-driving cars aren't a car problem, they're a computer problem. Why would you think that a car company would be experts in machine learning?

Because they can hire expers in machine learning just fine. Just how they progressed from dumb cars in the 50's to modern cars full of real-time OSes, micro-computers and sensors and stuff.

Plus, I don't see Google as any kind of "experts in machine learning", with perhaps the exception of search.

Google having access to my email and web habits and showing me BS unrelated ads doesn't boost my confidence in their machine learning capabilities either.
Thanks for posting this - just what I needed!
>Yet UK pushed through with switching to metric and went way further than US did. So this excuse isn't really valid.

And yet they didn't switch over completely. People in the UK measure some things in metric and some things in the old Imperial units, which is the worst of both worlds. Pick up some random thing and its weight is measured in kg, but if you're weighing a person it's "stones". From here to the wall may be about two meters, but from here to London is 100 miles. I'd rather have what we have in the US, thanks all the same.

>The real answer is, that in US politicians were too weak to push this through, because all kind of manufacturers and unions were pressuring them to stop the effort. In UK they just ignored the pressure. In US they budged.

Politicians aren't supposed to be "strong". They're supposed to do what the voters want them to do. If politicians are forcing you to do something you don't want to do, your government is out of control. In the US the people didn't want to convert to metric because it's easier to estimate in whatever system you grew up with. Manufacturers were all for the metric system since it makes managing global supply chains easier.
Id go further. The best debuggers don't look for the bug; they look to prove what Can't be the problem, reducing the search space geometrically. With parallel debugging efforts, many of the debuggers will be pointlessly crawling through code and tests that have already been discounted.

In my experience hard bugs don't get solved until a skilled debugger is found to look for them. Up til then little or nothing gets done. And skilled debuggers are small in number, and their efforts are necessarily serialized.
Lowes and Home Depot have by-the-hour pickup truck rental in many locations.

UHaul is always an option, too.
What parts of the country don't have rail as an option? Pretty much the entire US is covered in rail, especially around population centers since that's why many developed there in the first place.

Most people don't get tractor trailer deliveries to their door so a driverless truck wouldn't have an advantage there.
99% of startups simply will never hit the performance problems you seem to be talking about.
Yeah but its the ones that matter, that do? The successful ones with traction.
Google's LIDAR builds a 3D 1cm-resolution map of the world around it in realtime as it drives which is then compared to a 3D map of the route it received from Google when the trip started.
The downloaded route has been manually processed to include data about where signage is (precisely, in 3 dimensions, so the car knows where to find a stoplight without having to continually hunt), which routes it can take and at what speeds, exactly where the lanes are, rules of the road, etc.
The map also allows the car to know where it exists in the world to the accuracy of a centimeter, and would enable things like navigation of parking lots and garages.
I would consider having to build such a thing for the entire world to be a "big data" problem.
Thanks! I bookmarked this one a few weeks ago and can't wait for it to come out next month.
I'd like to raise a related point. While I think it's too early to worry about acquisitions, a .NET stack may put off early employees. Many engineers want to work with "hot" technologies for professional development reasons.

For example, I would not work for a company whose stack is built on top of PHP or .NET, regardless of pay. Not because these are "bad" technologies (in fact, they are a lot more stable than the hot technologies, often resulting in shorter time to market and cheaper labor), but simply because working with these technologies doesn't benefit me as much personally/professionally as working with some of the upcoming frameworks. I probably wouldn't enjoy my work too much either. To quote rubiquity from another HN thread, "people that work for other people aren't trying to build that business, they're trying to build themselves within that business."
Have you read the rest of the submission? It is likewise a bit of a mess. I believe that my assessment informed partly by this item was more or less accurate.
You'll probably want to learn the regular unix way as well. Tools like this are nice, but you're already 99% there as it is for most things.

ls | wc -l

ls | grep -c .py

(note the cat and pipe are not needed)

awk -F',' '{sum+=$1}END{print sum}' data.csv
Concur (with anecdotal data from observation); Tons of Eastern European drivers now hauling through the heartland. I bet it pays better than being a software developer back home.
Managing for Monday Morning: How Do You Hit the Week Running?
Speaking of SSO.. I work in .Net and we have sold our product to companies who didn't have a single Windows server until the purchase. They SSO in and couldn't be happier.
A startup is mostly about managing risk. Assuming that your product is SaaS (i.e. your customers don't know or care what is written on), then in general the risk that your product will not be successful is probably bigger than that it is successful and you have problems with an acquisition. I would worry more initially about what you can be the most productive on and also whether you have access to talent for that particular stack (to grow the team if it starts to take off)

If you are truly successful at some point you will need to rewrite and you can change to a different stack then if it makes sense (it will be painful, but hopefully by then it means you will have the resources to do so)
True; yet no human driver works like this. Humans respond to changes in the environment dynamically. Wind blow down the sign? Check for environmental clues - "Hey! I can see that's University Ave over there, this must be my exit". Traffic light out/obscured? Look at what the other cars are doing and recover. Pickup parked on the curb, partially blocking the right lane? Span lanes, and expect others in traffic to give you some leeway.

Open-loop driving is a terrifying idea. Not because it wont work 99% of the time; but because it will fail catastrophically 1% of the time which is way, way too often.
I couldn't find a starting salary for a mid-level backend + senior-level frontend engineer in the Bay area above 80k. One company offered 60k, which would be low for Alabama - in SF, that's downright insulting. I'm pretty sure I just got unlucky with the companies I talked to, though.
I'll raise you the work to arrive at the solutions, as well. At least, in my school answers were a small, nearly insignificant portion of the credit for a problem - no work meant almost no credit, which is critical for engineers. (That way if you make a mistake you can debug it!)

I'd imagine all of it has to be available in order to even post the exercises, but editing/formatting the work and solutions almost certainly is quite a lot of work.

Edit: In retrospect, in this context the work is the answer, so my distinction may be irrelevant. (I'll leave the comment as a hearty agreement with the parent though - solutions often help solidify ideas for me, and are great references later when applying the ideas in the real world!)
One difference between pregnancies and debugging is that the success probabilities of pregnancies are more or less independent -- couple A's failure to conceive doesn't cause us to believe that couple B will be any more or less likely to succeed -- whereas bug-finding times are not independent, because all of your developers are searching for the same bug. If developer A fails to find the bug in a week, then, assuming she is competent, the bug is likely very subtle and so developer B will likely also fail to find it.

This doesn't invalidate the argument entirely; adding developer B is clearly no worse than just using developer A (assuming B doesn't disrupt A's work and also that we don't care about the cost of an extra developer), and, to whatever degree B and A are using different strategies (giving them some partial independence), it will somewhat reduce the tail probability that the bug takes a long time to find. But the lack of independence, relative to the pregnancy example, means that the gains probably won't be as dramatic as this post assumes.
> a .NET stack may put off early employees.

Any choice may put off early employees. By sheer numbers, choosing .NET gives you a much larger hiring pool than, say, Haskell or NodeJS.
Govt wants to keep cash found with woman at airport
Does anyone remember Genesis on the Archimedes? A multimedia authoring package with some programmable elements itself written in Acorn basic.
Given the 16 previous articles about LiveCode on HN, including the enthusiastic comments at https://news.ycombinator.com/item?id=5287634 , and previous comments making essentially the same point as Chapougniard (see https://news.ycombinator.com/item?id=7487763#up_7488904 for an example), I think it's more likely that you just annoyed a new HN commenter rather than spot a hidden member of the LiveCode development team.
Correct, I was a bit too narrow with my criticism. This article is a complete mess, not just that one phrase. It adds very little to a discussion of this topic and is all around poorly formed as is foreshadowed by a poor phrase choice early in the article.
As an aside, there are many differences between pregnancy and debugging.
That's pretty much a tautology - cities exist because trains went there. I live in a state covered with extinct towns, because the tracks went another way back in the day.

But sadly those tracks are bicycle trails or even roads now. Eminent domain space is problematical; rails always go interesting places; tracks have largely disappeared from the landscape by having their route repurposed.
Indeed. We thought it was the same and nearly lost two big clients because we didn't see it coming.
Yes, but it's not about the size of the hiring pool. It's about the "quality" of the hiring pool (HN likes to call them 10x engineers).

I don't have any hard numbers to back this up, but based on personal experience almost exclusively all of the best engineers I have worked with prefer to work with open source technologies and would not touch .NET. One can think of several reasons for this correlation that make intuitive sense.
Furthermore, so many discussions conflate what are effectively advanced assistive driving technologies with truly autonomous vehicles (i.e. Robocar: Gp pick up little Johnny from soccer practice). The former is certainly interesting but it doesn't fundamentally change the nature of automobiles and driving.
Which is Google's solution. But everything we've read today is that the big car companies are not using this approach. They are relying far more on the car alone to make decisions:

http://www.forbes.com/sites/haydnshaughnessy/2013/02/04/why-...
> If it makes any difference, I am funding this myself initially.

The primary concern, if you are funding this and building this yourself, is getting to market. Each day is coming out of your pocket. Choose the technology stack that gets you off the ground fastest. A suitor is not going to reject your company because you aren't using the "hot" technologies.
This money would be better spent in experiments to find out how neurons work. IF neurons are well studied, and large scale models of the brain using IF models have been done before[1]. The result? Nothing.

It would be an experiment if they were testing a new model. This is a simulation.

[1] http://www.izhikevich.org/human_brain_simulation/Blue_Brain.... of Large-Scale Brain Models
Why You Need Log Data When Load Testing
I tried this, but I just get prompted to install the silverlight plugin. I am using Lubuntu 14.04.
But 'off the ground fastest' is an algebra problem - cashflow rates are what matter, not time so much. So early expensive tools MIGHT be better, considering your rent and grocery bills over time.
Also, a group headed by Hachette author Douglas Preston just bought a $100K full-page ad in the NYT.

Just a coincidence, I'm sure.
Should Entrepreneurs Grow Revenue Or User Count?
Yeah, debugging and pregnancy are both difficult. But one involves long sleepless hours, takes way too long with everybody looking over your shoulder and giving advice, ruins your health and relationships. And the other one is debugging.
Margins are VERY tight in transportation. In a solid company most of this should be going to pay drivers, and in decent companies it does they can make a pretty decent paycheck (none of that per mile crap) BUT with licensing points and experience being the biggest roadblocks getting decent drivers. Plus how many kids are growing up to be truck drivers these days... not many
Making your customers happy is important.

Amazon's customers are readers.

Hachette's customers are large bookstores.
Author wrongly presumes that people using the metric system are not visualizing the measures in almost the same way. We do. One step is about a meter, or the width of finger is about 1 cm. More often used 10 centimeters (1 decimeter) is approx. a distance from your thumb to the index finger. It's all about being used to certain system of measures, so that you can automatically relate the measure to something from the real life for comparison, e.g. my car is 5m long, also the wall in my room is around 5m, so if you ask me how big is 5m I can instantly visualize the distance very accurately (without even consciously thinking about cars or walls)
Be fair; its both. Sensors and integration are part of the problem, and that's not Google's forte. In fact they had to hire the DARPA guys to get that expertise. Arguably car companies could do something similar to shore up their deficits in this field.
One way to deal with a telemarketer
> How is capitalism the thing valuing teacher's salaries? If referring to the US and public education, aren't they a branch of the government?

The tax base that funds the schools depends on the whims of capitalism.
Whereas my foot is ... a foot. My pace is a yard. My thumb is about an inch. Works both ways.