skysight-inc/HackerNews huggingface dataset:
As you said there has been a few tries but usually tied to the lender. Lenders like 'Prosper' and others use other criteria to make the credit decision (social contacts, other bill payments, etc...) There are several FICO scores for many financial products (e.g. your car FICO score, credit card FICO score) and the main one.
I guess one way to disrupt would be a way to collect the data not usually compiled (payment history for utilities bills, rent payments, micro loan payment, medical bills) However, in any case your customers are not the people, but the institutions who check for credit, so find a need where someone needs to make a credit decision but doesn't want to use existing credit reports and scores.
I wonder if it is possible to design a currency union with just a small amount of decoupling between the individual national bonds and the unified currency? e.g. all members of the union are required to make certain transactions in euro, but issue national debt in their own currency which floats in exchange vs the euro? I think this scheme has problems, but it seems like with the right decoupling points somewhere in the system, you might be able to operate the euro more robustly.
I can't disagree with you on all of that, but I feel like you might be making the problem harder than it needs to be:

Almost any initial solution is going to be imperfect, and is going to involve mistakes if you try to solve for the entire problem space. Usually, the way to address this is to solve a small subset of the problem. If you don't know how to pay for the parking in a particular place, don't park there. Things like that. You limit the problems that you have to address, and the lessons you learn while applying that technology and the infrastructure that develops around its use alters the difficulty of refining it to address other cases.

I can easily imagine the way that I would solve the parking problem, at least initially: Set it up so that the car can pay wirelessly and make it so that people who own parking spaces can add their carpark to a database as enabled for wireless payment. There are even systems which already exist that do something similar to this; toll roads, toll bridges, et cetera: you put a little device on the front of your car and that records your usage of the relevant infrastructure, which is then charged to your account.

Put a bunch of image recognition for parking signs in the car - good parking space usually follow fairly straightforward formats; I'm not sure whether the signage is defined in statute or regulation, but generally they're much alike. Do some simple correlations on whether the person actually indicates they want to park there to refine the algorithm....

Crime figures are publicly available, so you can hook into that database for avoiding bad areas...

And have a rule that says not to park somewhere if you're unsure.

#

In the case of taxis, it's even easier: there are designated taxi ranks where they have to wait. And, considering there commercial enterprise, (there are two types of taxi regulation here, it's a bit weird,) you could rely on the taxi company to fill out a database themselves of other places that the car could wait - it's in their financial interest to do so.
>Taxis are incredibly expensive today. Sure you save a lot of money when you don't have to pay a driver, but is it really enough to make car ownership undesirable?

This seems to be a point that is often missed. In denser cities--where utilization can be relatively high--drivers make maybe $15 per hour. (Maybe a bit higher when actually carrying passengers which is probably the relevant metric.) So it's not clear to me how these hypothetical vehicles are going to so revolutionize the way people get around by cutting costs by maybe $15/hour (ignoring other labor costs associated with cleaning or any incremental cost of the vehicle).
So in a way micro is to RISC ̶C̶I̶S̶C what monolithic is to CISC ̶R̶I̶S̶C.
First specification of requestIdleCallback
I expect that expectations will vary so its really a personal decision. When I came out of college I was interested in starting my own company but I wanted the company I built to grow into a big company, and to that end I wanted some experience working at a big company to understand a bit about where the destination was.

I've noticed that many people work for companies and don't bother to invest the time in figuring out how the company works from top to bottom, how do people pay, where does the money go, how do you decide what to spend it on, or how much to spend, how do you decide between path A and path B. All the very real decisions that are made and how they are made, how do you have 20 people make a decision that they are all signed up to support? How do you know if your company is getting bigger, smaller, or suffering.

A startup, at the initial stages, is a handful of people, its a group project to achieve a singular goal. It isn't really a company at that point. When it gets traction and needs to become a company, what is missing? what is needed first? What is less important? All of those things you learn at a company which is already established.

When I came to the valley I joined Intel a "big" corporation at the time (which was better than my other choice Western Digital :-) I spent a couple of years trying to figure out how the company was put together as a system. Then I joined a late stage startup (Sun Microsystems) and worked there while it went from a "small company" (something bigger than your basic startup but I still got to know a lot of the company) to a "large company" the first billion dollar a year in revenue, and on to a run rate of $5B. Then I went back and started a company with some friends and we took it from the 5 of us to product launch and into the second product before we were acquired. And then back to a larger company to figure out some of the things I couldn't quite figure out in growing a company how folks had got there (mostly around sales to enterprises and getting the business model right).

The point being that my career to this point has really never changed its objective, which is to learn how to build and grow a great technology company. And helping me learn has been a number of friends and companies over the years.

So your objectives will tell you whether or not you should start at a big company or a startup.
Yeah, those are the types of people who are like "You too can be rich just like me, buy my ten step book to learn how!"
There is a reason to fight them: layout. The battle is not developers vs users, its designers vs users. Designers want everything to look exactly like their vision (understandably), and that means things like bits of text fitting in exactly the right dimensions and placement. Once you let users resize things on a whim, that goes out the window, because most likely everything will look completely wrong.

It also opens the door for dead simple ad blocking that can't be stopped, and business owners will never stand for that. The purpose that the web has been bent to in the last 15 years is simply not compatible with user styles.
You not understanding a set of rulings != corruption
Its indirect to their business model, and will just mean more talent ready to go for those buying it for movies / tv production.
I think it all goes back to this: https://en.wikipedia.org/wiki/1953_Iranian_coup_d%27%C3%A9ta...
Yeah, the picture is super off-putting; I liked the app concept but any interest I had disappeared when I saw that login screen. It looks like something more suited for Tinder than a health tracking app, and frankly, I'm sick of seeing skimpily clad women as the metric for idealness. It's demeaning and demotivating as hell if you can't fit into that mold. Not to mention that some titillating picture of a woman's ass isn't in any way appropriate for a general interest app in the first place.
It depends on how fast the incoming car is travelling. If you are about to be rear ended by someone traveling 60 miles an hour (happens sometimes in rural areas where people don't pay attention and are traveling highway speeds on narrow two lane roads), then it would actually be safer to accelerate the car to 30mph and crash into the person in front of you so that it is a 30mph impact to front and 30mph impact to rear rather than a massive 60mph impact to the rear of the car.
I just started going down this path. I began with using audio analysis to do some machine learning. (Detecting a specific audio pattern very easily recognizable to humans). Can't get too specific about it, as it's under NDA. But I had a little under two weeks to get a prototype built that either proved or disproved it would be possible.

The very first thing I did was take a step back and understand the domain of the data I was working with, and what the best way to present it for machine learning would be. In my case, I had to understand what the best format for presenting my audio would be (slightly modified MFCCs), and what the best library would be to get my data in that format.

Next, I needed to build a data set of proper training data. This mean I had to manually build a (largish) data set that matched exactly what I was looking for. So I went and downloaded a bunch of example audio, and then manually went through it, tagging it into the two bins I was looking to differentiate against.

Once I had this, (which actually took much more time than the learning itself), I was ready to do the actual machine learning itself. I used Theano, and figuring out how to translate my dataset into a format digestible by Theano took another chunk of time. Once I had my data in the proper format for Theano, it came down to basically playing with how I presented my initial data to Theano, and then tweaking my gradient.

Finally, I was able to train and get a net that was about 80% right with my hypothesis. There were a few edge cases I hadn't anticipated that wouldn't necessarily work well, but it gave us enough confidence to go through with more machine learning for our project.

So, takeaway suggestions: find a real project, something you want to learn, and then just do it. Gather knowledge of your data, build a dataset, and test a hypothesis. Most of this isn't machine learning, it's mostly just moving and shaping data, and knowing what in your data is significant. The machine learning algorithms are really just a tiny piece of the whole picture. Good luck.
Jeff Atwood has two posts on the topic that support flat comments. Personally I prefer threaded.

http://blog.codinghorror.com/discussions-flat-or-threaded/

http://blog.codinghorror.com/web-discussions-flat-by-design/
That is similar to how it is here in the states but there are 3 main agencies today. There is one primary scoring system called FICO that is not very transparent either. They give rough ideas as to the weight things have on your score but that is about it. There are some alternative scoring systems too but not as widely used.

In the US banks are the primary funding source for most credit reporting agencies, so it seems to me that CRA's interests are more in line with the bank then in being neutral with their reporting. Meaning they would rather report something that is negative and maybe not accurate then not report it because it protects their client and raises consumer rates. Many stories exist around these types of issues. Is the funding source for Schufa similar in Germany, primarily banks?
UCLA Health information stolen. 4.5 million individuals affected.
VMS clusters on VAXen were doing fail-overs perfectly in the 80's. All kinds of products and software (even FOSS) do it today. You're telling me that, in 2015, you are doing manual failovers despite tons of free tools to automate it reliably?

Better to do an assessment of each thing that can fail, how to isolate/detect it, how to recover from it, how to implement that with available tools, and implement it. Test it in a number of situations on same hardware, network, and apps you'll use in production. Once it's solid, put them into production. Then, never worry about that stuff again past monitoring and maintenance.

Btw, Netflix employs Monkeys to do this. Open-sources their tools with blog writeups on their use, too. I'm sure you Humans will be able to handle it. ;)
I do not see a problem. A system or service that allows sender-initiated contact is valuable. A service that allows end-to-end encryption is valuable. They do not need to be the same service.
I bought 4 GameGrumps T-Shirts and I'm a Patreon on RedLetterMedia and Smarter Every Day.

I can verify all of these statements.
Tangent, but several friends said I should look into being a Scrum Master. Any advice on where to start? I'm going to a meetup on it Tuesday.
TL;DR Whiteboards are bad. Just kidding, keep the whiteboards and don't ask stupid questions.
Cleaning Startup Homejoy Shuts Down After Worker Lawsuits
Windows 10 updates to be automatic and mandatory for Home users
What? In the case of Microsoft rebooting/migrating an instance causing a failure, Keepalived will automatically failover.

The manual failover is in case of something going horribly wrong (outside of hardware failure), in which case a human steps in, looks at the situation, determines the best solution... and if it's failover, they initiate the failover.

I've personally used this procedure in the past and it worked 100% of the time there was a failure in a production environment. The tricky part is then notifying the hell out of everyone who needs to be notified that something really bad has happened, a failover occurred, everything is OK, but it needs some attention ASAP.

In PGSQL world, there are even a handful of tools to help you turn the old (failed) master into a slave, and correctly escalate the old (promoted) slave into a master; all in a single command on each side (which can be kicked off through keepalived).
In terms of progress on fundamental physics (i.e., ignoring things like material science), this is a very slow crawl on any sensible absolute scale, and certainly vastly slower than progress was made up until the 1970s. With respect, I think you're just renormalizing to the glacial pace we've come to expect.

The Standard Model (including the yet-to-be discovered Higgs and top quark) was completed in the mid '70s around when the bottom and charm quark were found. The pace of discovery of new fundamental particles has clearly slowed dramatically; the top quark was in 1994 and Higgs was just a couple of years ago, with serious pessimism that anything else will come out of the LHC (even with the luminosity upgrades). The existence of an LHC successor is uncertain, and even if it is built it is unlikely to find anything new.

The solar neutrino, compared to just about any other fundamental physics question in the 20th century, is boring. It was solved by adding a few additional free parameters to the SM with little conceptual insight and few implications for further post-SM physics. As you and I commented elsewhere, pentaquarks are a neat window into low-energy QCD, but they aren't new fundamental physics.

Precision cosmology's biggest result was to confirm the ad hoc and simplest inflationary models from the 1980's, with little hope in the near-term future to do anything besides rule out poorly motivated variations designed explicitly to be testable. What is the inflaton like, and what does it do besides adjust a couple of parameters in the CMB? No one knows, and know one has a serious expectation of finding out anytime soon.

None of this, obviously, means that these meager accomplishments weren't hard or that the people who made them aren't extremely clever. But they are undeniably less exciting then what was see before I was born in 1985, and pale in comparison to the absolute revolutions of the first half of the 20th century (quantum mechanics, relativity, GR, field theory).

I really want to call this out:

> huge swaths of parameter space (i.e. possible theories) have been ruled out.

This is the sort of comment that only us physicists can say with a straight face. Parameter space is bounded only by one's cleverness and stamina. Ruling it out says very little about reality because most proposals have very little a priori probability. The entire industry of constructing complicated models and then ruling them out is the lamest kind of progress I can imagine. Perhaps the open questions have really just gotten so hard that this is the best that can be hoped for. But we should be honest that this is essentially like hitting a brick wall and digging into it with spoons.
Exercise may reverse age-related bone loss in middle-aged men
I just finished a PhD in Transformation Optics and Metamaterials. Metamaterials are a real novel breakthrough in physics which have wide ranging applications for antennas and electromagnetic materials. Not to mention the recent confirmation of the Higgs Boson. Physics is moving along at a similar pace.
It seems to me that ground-breaking discoveries in physics are generally getting more expensive.

Up till about the early 20th century, ground breaking physics was largely "two guys in a garage" territory -- single individuals such as Newton or Cavendish tinkering in their own private laboratories using fairly modest equipment. Teenagers replicate their experiments in school physics lessons with equipment costing no more than a few hundred pounds today.

Throughout the mid-twentieth century, ground-breaking discoveries were increasingly made by teams of researchers, which seem to have grown larger over time, with equipment that has become increasingly large and expensive, and sponsored by universities, companies and governments.

Nowadays it seems that most ground-breaking discoveries are made by large, national or multinational teams working with equipment costing billions of dollars and processing petabytes of data. I couldn't see two guys in a garage producing their own space telescope or particle accelerator any time soon.
There's a significant competitive advantage to writing your own rules for the game you're playing in, so as long as that much power is concentrated in so few hands, businesses are going to find loopholes and other means of getting what they want. An example would be a business threatening to fire all their workers in a certain area and move somewhere else unless they were granted what they wanted. Boeing did that quite effectively just recently in the state of Washington and was able to get a massive, multi-billion dollar tax break. So now Washington taxpayers are essentially subsidizing the bottom line of an already hugely profitable business.
As a woman who also don't like to track her fitness by pounds, dress size is not a particularly useful metric, because it's so highly variable among manufacturers. I have pants that range from size 8 to size 16. If I tried to measure my fitness by what pant size I wore today, I'd go crazy in record time.
See also, previous discussion 10 months ago: https://news.ycombinator.com/item?id=8275970 (138 comments)
If you hover over "Connections", select "Add Connections", and then "Manage imported contacts" in the top right corner. I had to hunt around to find it.
I wonder about the African part. African cultures, and languages, vary a lot. There is zero cultural crossover between Zulus, Marsai and Egyptians for example.

(I worked in Africa for a number of years)
Although yes "connected to the drive shaft" in a sense is how it works but there can be some great discussions of 3 phase motor design, torque demand motor control systems, power electronics, regenerative breaking... The list goes on and on
What does "Batteries Not Included" mean for a highly available database? Is it a good thing?
I can't even dismiss it as typical Guardian progressive ranting

FYI because it is not clear from the article, but this is actually a marketing piece for a book:

Postcapitalism is published by Allen Lane on 30 July.

Paul Mason is the award-winning economics editor of Channel 4 News. His books include Why It's Kicking Off Everywhere: the New Global Revolutions ('Compact, urgent, present-tense, declarative and addictive' - Andy Beckett, Guardian); Live Working Die Fighting ('Indispensable, brilliant' - Ken Loach; longlisted for the Guardian First Book Award); and Meltdown: The End of the Age of Greed ('Lucid and sharply polemical' - Oliver Kamm, The Times).
So then the title should be "One of the Questions..."
Pig – A packet crafting tool
>An unregulated casino would never give payouts either.

An unregulated casino would not see many patrons then.
It's interesting to see Google's display of the situation.[1] Some of that has to be guessing by the software. They don't have an aerial view of the situation; that's reconstructed from their LIDAR scanner. That view is subject to occlusion by other vehicles. Their scanner is high enough that they can see over most small cars, but they can't see their far side. They show a map of all the vehicles in the intersection as if they had all that info, but if there's a truck or an SUV blocking their view, they can't see through it.

I'd like to see the video (they have cameras) that goes with the LIDAR reconstruction.

The CMU/Cadillac/Uber self-driving effort doesn't have a LIDAR on a tower, so they don't have as much information. They haven't been reporting accident data, which would be interesting.

[1] https://www.youtube.com/watch?v=WtLp2f-vM14
Reputation can go wrong, legitimate emails with double opt-in still can be marked as SPAM by the user. Gmail definitely is slowing that down by offering a warning to the user when there is a `List-Unsubscribe` header. Even that still does not work and probably the reason by AT&T bill is sometimes marked as SPAM.
Another good tool is Kadira Debug, a screencast can be found @ https://www.meteorcasts.net ...
How to Open and Connect Your Idea Machine
> Imagine if the door in Ubik were a refrigerator door that refused to open? What then?

What a silly way to make this real to people. What if, indeed.
The african channel that does not work in most of africa :-) No, I know it's hard to secure rights everywhere, but no streaming service works in my parts of africa.
Can I ask why HAProxy seems to be a more popular choice than the very, very simple (and robust) pgbouncer?
Two things, was it something that needed to get done in the next 45 minutes? If not then a meeting is a big hammer for a small problem. If it only took 10 mins spread out over the course of several weeks it is still a time savings.

Second sure the discussion part could have been dealt with in a 45 minute meeting but how long did the thinking part take? Perhaps someone tested a few theories before presenting what they thought was the best approach in a short email. You aren't going to do that in a meeting you either end up taking the path of least resistance or you end up in another meeting after everyone has had a chance to go think and try stuff out.
This Robot Is Hitchhiking Across the US (Please Don't Steal His Boots)
AIMA is about as introductory as these texts get (and still be valuable). It in an undergrad textbook after all.
Watch the moment when a really cute robot becomes self-aware
And you can do this 24/7 since you are awoke everyday and night?
I'm sorry but I don't see what this has to do with the point I raised. I am very familiar with Auernheimer's case, so if you could spell out in more detail what you're objecting to, I'm pretty sure I can follow along.

The point I was making upthread had less to do with Auernheimer's case than it did with the silly notion that the case turned on "incrementing a URL".