nolemurs

I get so many contacts from recruiters that I'm never going to follow up on almost any of them.

Is salary information absolutely essential? No. But if I'm not pretty confident talking to you is a good use of time, you'll never hear from me, and not providing salary information is a great way to keep me uncertain.

I can think of two exceptions. For my first job I didn't really care about salary - my main goal was to get good experience and get into the field. Also, there weren't a ton of recruiters constantly spamming me. Alternatively, if you're a large well known company and I'm interested, then I'll just google to figure out what sort of salary to expect. In that case you don't have to explicitly tell me.

In all other cases, if you leave out the salary, I'll probably ignore your job.

Thanks for this. I read the title, and my thought process was:

"I agree".

Then:

"There's no way the study backing the article is good enough to draw meaningful conclusions. This is clickbait."

Then:

"I guess if i'm going to be intellectually humble I should still read the article."

I think based on your comment I can safely skip the read, and save myself some time. Intellectual humility is one thing, but I can go read something with a higher probability of being informative instead.

The issue I have is that when people talk about the dangers of automation they never compare them to the dangers of non-automated driving. They always make it sound as if automation is making things more dangerous.

The current evidence suggests that semi-autonomous cars are on balance safer than purely human driven cars. The evidence isn't conclusive, but I've literally seen no evidence presented to support the case that semi-autonomous cars are more dangerous - at best I've seen people argue that we can't yet trust the safety claims. Teslas have been on the road long enough now and in large enough numbers that if they were really more dangerous than non-semi-autonomous cars, I think we'd have seen some non-anecdotal evidence by now.

The reasonable presentation of the issue would be "semi-autonomous vehicles likely make people safer, but there are still dangers and people should pay attention."

Instead, the story you're telling is "Tesla drivers are dying, semi-autonomous cars are dangerous, and you should be scared."

You must see how this is misleading at best, and likely downright counterproductive from an overall safety point of view.

I feel like this angle is massively overplayed in articles about autonomous vehicles.

Is automation paradox a real issue? Absolutely. But at present, all the evidence seems to indicate that the people automated cars will save far outnumber the people they will kill.

Focusing on the dangers is alarmist and misleading. The 737 crash is a good example really - I've never heard anyone with experience in the field suggest anything other than that the automation makes planes safer. Focusing instead on the fact that the automation isn't perfectly safe only makes sense if you're a media company looking to scare people.

> This is a cohort study conducted over 15 years. You can't really criticize it only based on those numbers

You absolutely can.

Scientific studies should be judged on their potential to produce interesting results. This study has too small a sample size to provide results that merit making even the weakest claims about. Even the initial sample size was, frankly, just barely large enough to maybe provide suggestions for future research.

If a meaningful drop-out rate is expected, I would argue that the researchers running these sorts of studies are mostly wasting everyone's time and money for the sake of publishing a few papers.

This article is just fear-mongering and speculation. No facts are given to support the title, and the proposed solutions to the problem (which is never established) are vague to the point of meaninglessness.

Skip the read.

This is the best guarantee any company ever gives.

For smaller companies if something becomes too expensive or hard, they just go out of business. For larger companies, they have to draw the line somewhere. You won't get stronger guarantees from anyone, that would be insane.

Google definitely has a history of turning down free services when they're proving unprofitable, but that's only free services. There's no history of Google turning down paid services without good notice that I know of.

I'd add that there's a big difference between having a non-CS degree and having no degree at all.

With a non-CS degree it may be a little harder to get an interview, but if you can interview well, it's not going to count much against you. A degree in a strong technical field (like Physics or Engineering) might even count in your favor compared to a CS degree if you can still do well on an interview.

With no degree at all, you may find it harder to get interviews in the first place. There are definitely still jobs to be had, and companies who will interview you, but the options will, at least initially, be more limited.

The tone of this article makes it sound like it's a bad thing that Facebook and Google won't be much affected by this law, but I don't really think it is.

The reason the big players aren't much affected is that they've already had to make huge privacy changes in response to GDPR. They've already paid those costs.

A lot of what you see about privacy is uninformed fear mongering. This article is a good example: it seems to take it as a given that anything that doesn't substantially increase privacy protections is a bad thing, but no reasons are given, and the costs aren't weighed. In reality there's a balance to be had here and we need to be looking at both sides. I'm not saying there's nothing to fear, just that there's a real disconnect between what the media's afraid of and what we should actually fear, and there's a very real danger of legislative changes doing more harm than good.

GDPR actually provides some pretty substantial privacy guarantees and I think we should wait to see the effects of GDPR play out before we go fiddling with the system more.

The title of this article is pretty misleading. There is no confirmation that the cell-site simulators disrupt emergency calls. Rather:

> Harris Corporation claims that they have the ability to detect and deliver calls to 911, but they admit that this feature hasn’t been tested.

The fact that the feature isn't tested is a serious concern, and should be addressed, but this headline is completely inaccurate, frankly dishonest, and reduces my faith in the EFF.

I understand where the EFF is coming from, and for the most part believe in their causes, but this sort of willfully dishonest headline just serves to reduce credibility. In the future when I see EFF articles with dramatic headlines I'm going to assume they're probably not what they seem and be less likely to read the article.

Fans of he EFF will forgive these sorts of inaccuracies. Skeptics will not - this sort of article just serves to drive reasonable but undecided people away from your cause.

Repeating a study if, and only if, the study failed to provide the desired result is the most basic p-hacking technique there is. If this isn't p-hacking, I don't know what is!

To give a simple model, suppose you decide an effect is significant if there's only a 5% chance that you'd see this data if the effect didn't exist. If you run the experiment again with the same threshold for significance when don't get the desired result, then the probability of seeing an effect that doesn't exist rises to 9.75% (= 0.05 + 0.95 * 0.05).

The effect isn't merely "not 100% unproblematic" it's a serious problem! You've gone from what looks like a p-value of 5% to a p-value of 9.75%.

The fact that the second study is done with a larger sample is pretty much irrelevant unless it also comes with a higher p-value threshold for you to accept the result.

My own experience was that part of the problem was that there was no intellectual challenge. I actually suspect that if PhD programs were a little more intellectually challenging drop-out rates would go down.

> PhDs are intellectually demanding, and not everyone will be able to finish. In the US between 41 and 78% of people who start PhDs have finished them after ten years, depending on their sub field. Computer and Information Science has the lowest graduation rates (41%)

Right...

I've met a good number of PhD dropouts - I am one myself. None of them dropped out because it was too "intellectually demanding." They all dropped out because the work was unrewarding, the odds of employment in academia were poor, and the work in academia was unappealing.

Looking at Computer and Information Science in particular, I might suggest that high availability of high paying jobs in the private sector is worth looking at rather than the "intellectually demanding" academic program.

To be fair, input devices are a pretty serious issue here. Probably the single most common operation I do on code is search it. If I can't type what I'm searching for easily, that's pretty annoying.

I've had the same thought. Where is the skepticism coming from?

I've noticed a lot of articles lately that talk about how far off self-driving cars are. That said the articles all seem to rest on one of two arguments. Some (like this article) point to the failure of some startup that most sane people didn't have any faith in. The others point to the small handful of accidents we've had: the one from Uber (which was the result of borderline criminal irresponsibility), and the couple from Tesla (which were the result of drivers not paying attention or and with their hands off the wheels of their emphatically not-self-driving cars). These sheer number of these articles creates the impression that there's a lot more going bad in the field than I think there's any evidence for.

When I try to dig deeper and figure out why these articles are all appearing I can't find anything.

Probably it's just that after all the stories about the amazing future of self-driving cars, this is the next natural story to tell since we don't actually have the self-driving cars yet, but there's definitely a paranoid part of me that thinks some industry group is sponsoring these stories for some reason.

The substance of this article can be sumarized as "I talked to a bunch of people at a convention, and some had concerns, ohh, and I wrote a book about how I'm skeptical of driverless cars."

Regardless of how you feel about the future of driverless cars, this is a safe article to skip - there's no content.

I'm pretty sure the scale of the problem is large enough to make a manual approach completely and utterly impractical.

> I hope my feeling of relative safety is justified, but I'm not a security expert(?).

If you want to be properly paranoid, you should consider getting a VPN. If you're not hiding your IP address, hiding all the rest is of limited utility. A VM doesn't really provide much meaningful anonymity - if someone wants to prosecute you for piracy they'll start by finding the IP address that was downloading/sharing the stuff (that's publicly visible).

On the other hand, it's pretty likely that this sort of paranoia is totally unnecessary - piracy prosecution against individual downloaders has been historically a PR nightmare for the groups doing it, and more or less everyone seems to have given up on that particular approach.

Still, if you want to be paranoid, a VPN will do a lot more for you than a VM and some add blocking.

> I wish that if they’re gonna downrank “good” pirate content then they should do the same (or worse) for the bad/malicious ones.

I'm pretty confident they'd like to but it's a tricky problem. Based on this article, they're downranking based on number of legit DMCA requests - the good sites will generate a lot of signal on that front. The bad/malicious sites won't.

The malicious/scam sites usually come and go quickly, so it's hard to learn which ones they are - if you figure out one site is a scam, and a new one pops up.

A real solution would require being able to make an automatic judgement about whether a site is bad/malicious based on the content of the site, but that's really hard, and it's really bad when you get false positives, so you have to be super conservative about it.

I'm a little dismayed that someone would be willing to make use those factors and then claim it's about the best place to work. It's so obviously off point that I can't even buy that it's the result of stupidity - the blog post is consciously dishonest.

I know that that's pretty much the norm in blogs/reporting, but I'd really like to see this sort of behavior discouraged. LinkedIn in particular has a lot of practices that seem particularly skeezy to me. I'm not sure exactly what should be done about this sort of thing, but at the least I want to draw as much attention to it as possible.

Yeah, I'm pretty sure you're right. I've asked a dozen or so questions, of for every one of them I've gotten an answer that seems related to to the words in the question, but not in any logical way:

Q: What's the difference between a proton and a neutron?

A: Atoms are made of protons, neutrons, and electrons.

Q: What trajectory do planetary orbits follow?

A: Kepler's laws of planetary motion describe the orbits of objects about the Sun.

Q: How do you measure the charge of an electron?

A: Electrons have negative charge.

Q: What conservation law is the result of the time invariance of physics?

A: As a result, the law of conservation of energy has been changed into the Law of Conservation of Matter and Energy.

None with high confidence of course, but it gives you a sense of roughly the sort of 'reasoning' this thing is doing.

> It's a public standard that they're setting for themselves.

I'd like to really draw attention to the "for themselves" part here. Yes, this is a public document, and of course it serves a PR purpose, but the function of setting the terms for internal discussion at Google is at least as important.

I think that since most people aren't Google employees, they tend to focus on the PR angle of this, but I don't even think that's the primary motivation.

> You see, when you make any argument, you always omit the infinite number of things that don't support it and focus on the few things that do.

No. When I make an argument, I try to omit the infinite number of things I think are unlikely to be important, and focus on the few things that I think are most important whether they support my position or not.

Everyone's fallible, and I do my share of focusing too much on points that support my position over more important counter points, but I see that as a failing, not as the reasonable thing to do.

> Hi, it appears that "sensationalist garbage" triggered quite a bit of a discussion.

Yes. Sensationalist.

> I also omitted Cruise automation and a bunch of other companies, perhaps because they have more responsible backup drivers that so far avoided fatal crashes.

So your explicit reason for omitting Waymo, as I understand it, is that it didn't support your argument?

I've always understood the claim that deep learning scales to be a claim about deployment and use of trained models, not about training. The whole point is that you can invest (substantial) resources upfront to train a sufficiently good model, but then the results of that initial investment can be used with very small marginal costs.

OP's argument on this front seems disingenous to me.

His focus on Uber and Tesla (while not even mentioning Waymo) is also a truly strange omission. Uber's practices and culture have historically been so toxic that their failures here are truly irrelevant, and Tesla isn't even in the business of making actual self driving cars.

I'm the first to argue that right now AI is overhyped, but this is just sensationalist garbage from the other end of the spectrum.

Seriously. Frankly, based on Uber's culture I would have been surprised if they didn't kill at least one person with their self-driving efforts. It's a total non-data point. The fact that Uber got as far as they did without killing anyone is strong evidence that the problem is tractable.

As for Tesla - Tesla isn't even trying to make proper self-driving cars. Tesla's goal has always been assisted driving. However you feel about that, it's really not relevant to the success or failure of self-driving cars.

OP can't possibly have been ignorant of the fact that Waymo is the clear leader here with a substantial head start, and a proven record (and an actual fleet of self driving cars now on the road), and yet he chose not to mention it. That really undermines his credibility for me - he seems clearly more interested in making his point than in accurately engaging with reality.

Yeah... but they really don't like being told they're incompetent.

If one incident can reverse your conclusion then the sample size isn't large enough to draw that conclusion.

With only one death, the only conclusions you could reasonably reach from statistics are either "we don't know yet" or "we've gone so many miles with only one death that we know it's safe enough." There's no reasonable way to argue from the stats that we know it's not safe.

> Sure, with enough manipulation you can bring this down to the liars paradox, but that is the case for every paradox.

As @nwjtkjn said, I'm pretty sure the Barber's paradox was literally just Russel's conscious and direct attempt to reframe the Liar's paradox in the context of set theory.

I would be willing to wager that Russel himself would have accepted the idea that his Barber's paradox was basically just the Liar's paradox. It's not as if these are two random unrelated paradoxes here.

`alias rg='rg -S'` in your `.bashrc` will fix that for you.

Out of curiosity, what sort of searches do you do that smartcase is desirable? A meaningful number of people seem to prefer it, but I find that most of the time I want to be able to search for variables etc. case sensitively.