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Why is this scummy exactly? If a salesperson was to try to sell to you in a store, they would take into account how you appear and act to tailor the sale. There's nothing wrong with that. Why is it suddenly bad if a machine does it?

Excellent! One of GCPs many advantages (outside of it's technical ones) is it's simpler pricing model.

To scale up the principle a little... Uber acts like a real estate agent, they charge the seller a percentage of the total for the service of connecting a buyer and a seller.

Imagine you were selling a house, and your agent came to you with an offer of $1M, of which they would take a 10% commission. You agree to this, but find out later that the buyer actually offered $1.1M. The fact that each party agreed to the transaction with the real estate agent isn't relevant here. What is relevant is that if you charge for services based on a percentage of the price, you can't then set different prices at both ends, this strongly violates the expectations of the contract.

Looking at https://www.uber.com/info/how-much-do-drivers-with-uber-make..., it says "Drivers using the partner app are charged an Uber Fee as a percentage of each trip fare." This is analogous to the real estate agent example, and this is why this is fraud on Uber's behalf. If they told drivers that they were simply buying their services for an arbitrary price, then it would be fine, but they don't say that.

Can you explain? The analogy seems like a terrible one to me.

We are not talking about charging different amounts of money depending on the brand of device you are consuming the data on. NN is about not differentiating the cost or quality of bits based on their source. In the US, can you not opt to pay a slightly higher rate for renewable energy? (This happens in Australia).

I'm all for NN, but the analogy Sam used doesn't hold in my opinion.

As an additional thought from someone outside the US: NN doesn't exist in places like Australia, and has actually overall led to better services, especially in the early days of the internet, because overseas data is significantly more costly to provide than local data. The difference is that we have more robust competition and we can more easily switch providers, where is seems in the US (purely based on things I've read on the internet) that the near-duopoly cuts consumer choice, so if NN was not in place, people would have little ability to switch providers, and they would be stuck with it.

Is the lack of competition the real issue here? If people in the US had a choice of many providers and it was easy to switch, then people would likely switch to services that are Net Neutral.

If that's true about this tech, then it will be awesome. The focus issue is the only thing that kills my enjoyment in 3D movies.

These types of articles seem to always get the same mixture of responses. The biggest problem that I see is that everyone starts with completely different sets of assumptions and they are almost never up front about them.

The lack of cited sources in articles like these leads people to bolster or criticize particular studies that they have read or heard about, usually without referencing those. Many of these studies are either flawed or contain assumptions that some people don't agree with, so this ends up going nowhere also.

Are there any really good studies on this topic that we may discuss as a common point of reference? Once that take into account all the facts, and don't start with assumptions like the following:

1. There should be equal numbers of men and women in tech (or there is some other ratio that is preferred or correct). 2. Women and men in tech should - on average - be paid the same.

Some people have these assumptions as part of their personal belief systems, but they entail a whole bunch of other assumptions that are not prima facie true.

One other huge weakness in these kinds of studies is that they measure the things that are easy to measure; things like education and experience. If companies are hiring compensating employees rationally, they would use these only as heuristics, and have some measure of how much an individual employee would contribute to the company as the determining factor.

Measuring job skill, as well as all the other skills that go into being a good employee is really hard, but until a study tries to actually do this, they are coming up with conclusions that aren't at all useful in the real world.

This is spot on. What makes the above probabilities look incorrect is that people are assuming that the algorithm understands the relationship between tiger and animal the same way that humans do. Clearly they are evaluating each independently.

This seems like a PR-based defensive move to me, rather that one rooted in principle.

This practice has been known for some time (the recent news is not new at all) and has been used to prevent drivers from being caught up in the regulation battles by taking fake fares. This move makes drivers' experience worse.

It seems inconsistent for Uber to maintain their position when it comes to undermining/circumventing taxi monopoly laws and also make this move.

Is there a broader context or principle that can explain this in a way consistent with Uber's values?

A cache seems like a particularly odd example to choose for this. If you are changing the way a cache functions, then presumably you either have fairly short expiration times (problem will fix itself) or you would have some form of cache invalidation as part of the deployment process.

Additionally, it would have been nice to see some mention of patterns that solve this issue more completely, like CQRS, where state is disposable.

Does anyone know why GCP isn't one of the supported cloud providers for EE? This is surprising to me since they had docker-related offerings a long time before AWS and Azure.

Can someone explain this to me?

If I own something, I want to sell it for as much as the market will bear. I don't want to sell it and have someone flip it for a huge margin almost immediately.

How is a large first-day bump not considered a failure for an IPO? What is it about the situation that reverses a common sense understanding?

companies normally try to price it so it goes up about 20 percent on the first day

Can someone explain this to me? Why would a company try to sell its shares for less than they could get? When I see something like this - 44% up on the first day - I immediately think that this was a complete failure as an IPO, because the company left so much money on the table.

Am I crazy? Or can someone set me straight.

There have been a lot of articles and suggestions for mitigating S3's single-region architecture (design flaw?) since the outage.

One solution that I haven't seen much of is to just use a service that gives you multi-region without any extra work, such as https://cloud.google.com/storage/docs/storage-classes#multi-...

Did Uber fire the driver? Or are they ok with passengers being recorded and those recordings being made public?

#23: Scrolljacking is still annoying as hell.

This isn't obviously true (nor obviously false) to me.

If airbnb added a unique index to the SSN (or a two-column index with SSN and locality) would you consider that a TOS violation?

This is a weird, seemingly openly biased article.

Tesla should make their seats more visible because someone was a moron? Someone being a moron means Tesla isn't putting users first?

Please... HN doesn't need garbage like this.

This headline is really bad. No evidence whatsoever was provided to suggest that being black causes you to get a lower salary.

What it does tell us is that black people ask for less salary on average, which might mean that either they are applying for lower paid jobs, or that their negotiating skills on the whole are poorer in this sample.

The average African-American candidate is nearly 50% more likely to get hired in tech but gets paid about $10,000 less in San Francisco and New York, putting black tech workers at a significant disadvantage, even compared to other minority groups.

This figure of $10k is false if you look at the data in the graph, but even if we were to accept the artificially inflated figure, would a job seeker prefer an 8% increase in salary IF they are hired, vs a 50% greater chance of actually being hired?

These kinds of topics are always full of emotion, and with that comes a lot of bullshit unfortunately. I wish reporters wrote articles that told us facts, rather than trying simply to push an agenda or point of view. If you care about a cause, making terrible arguments for it makes it look like there isn't actually any issue to deal with, and that it's all overblown. I think this is a real shame. Wouldn't it be nice to have an honest, fact-based conversation about these topics once in a while?

Can anyone recommend good non-smart TVs?

They also only have SMS as a 2FA option, which is neither convenient nor secure. I've been a customer of theirs for a long time, but they do indeed make some poor decisions every now and again.

This seems absurd. Are there any examples you can point to, or legal principle you are referencing here?

I understand that people underestimate the difficulty, but this guy was paying others to do his interview tasks, so I think this fits into an entirely different category.

I find these stories somewhat amazing. I could not in a million years imagine taking a job that I had no real idea about how to do. How is this scenario supposed to end exactly? What has to happen for this to work out? What's the plan when you can't do your job?

Can anyone at all offer insight into this? Would this person have some kind of delusional plan, or simply not think that far ahead? I'm genuinely curious about how the minds of people that can do this work.

It seems quite odd to list "Human Error" as a cause. This is only a secondary cause, because if a human is able to accidentally bring down an entire system, it's the system itself that is really the problem.

Why is it unfair? Both the human and computer players are unable to make reads on the other based on physical cues.

"which creates the most comprehensive API Integration Cloud"

What does this mean?

If you're going to post something old, please include the date in the title.

As someone unfamiliar with US law, could someone explain whether it's illegal for companies like Oracle to pay white, male workers more (as stated in the article) or if it's only illegal to pay them more because they are male and white?

The former seems obviously absurd. So, assuming it's the latter, has the government supplied any evidence that this has happened?

I was surprised also, the number of stars it has should put it into 3rd place, so I guess it had a bunch before 2016 started already, even though it only went out of beta in late 2016.

The article mentioned journals making special arrangements with the Gates Foundation. I hope that GF doesn't make any of these special arrangements, meaning that unless a journal is OA then they won't get any of these papers at all.