This doesn't seem like a bad thing to me. In the same way we have public defenders who professionally defend scoundrels, it seems good to have people who professionally critique new technologies.
I'm old enough to remember the naive optimism around the internet in the 2000s. "The long tail", "cognitive surplus", "one laptop per child", Creative Commons, the Arab "Spring", breathless Youtube videos about how social media is gonna revolutionize society for the better, etc. Hardly anyone forecasted clickbait, Trump tweets, revenge porn, crypto scams, or social media shaming. If we had a few professional critics who were incentivized to pour cold water on the whole deal, or at least scan the horizon for potential problems, maybe things would've turned out better.
Apologies if this was not a joke, but just imagining the implications of this made me laugh harder than any comedy I've watched the past few weeks. My... umm... "scientific code" would be flagged in miliseconds :D
The thing that turns me off of VR the most is rumors I've heard (sometimes here on HN) of eye health issues from excessive VR use. Is anyone working on that?
https://www.ivpn.net/ also generates a random userid and also accepts cash in the mail (only for large purchases unfortunately). I wasn't able to get mullvad's multihop to work on Android, but iVPN Pro does the trick. iVPN also has a nice server status page that helps you optimize for speed (low load server) or anonymity (high load server) as appropriate: https://www.ivpn.net/status/ They have a weird "anti-marketing" homepage which devotes almost equal space to explaining why you should not buy their product :-P
Perfect Privacy accepts a gift card (more convenient than mailed cash IMO) and has a nifty "neurorouting" feature which aims to be better than standard multihop (claims of speed, at least, I can attest to). They do ask for an email address, sadly, unlike iVPN/Mullvad. Also I just saw this and it looks a bit worrisome https://www.security.org/privacy-guide/perfect-privacy/
Both iVPN and PP let you block various trackers / MANGA corps at the network level.
I like Mullvad but it seems good to support a diversity of providers. Curious if anyone has any dirt on either of those two, or if they can make more recommendations.
Someone hacked into their Malmoe server a year ago or so, and found that they indeed run everything in RAM disks and aren't logging at all. Happened via the management interface.
But please take this information with a grain of salt, as the write up for this exploitation has been vanished from the internet (or I am just unable to find it). *
However, there are still articles about how they've been raided multiple times [1][2][3] in the past, and the police never found any logs.
* Also, I believe that this kind of pwnage could've happened to every VPN provider. Always use VPN chains with multiple locations and always keep in mind that your VPN could have been compromised. Don't just rely on a single hoster which just shifts the liability from your ISP to another single point of failure. But this is probably still better than LE just having to call comcast. :)
Edit: ovpn.to is probably worth taking a look too. I remember that the admin grows cannabis in his basement (still illegal in Germany) and provides all users with access to warez via Usenet NNTP. Do with that info what you want.
> Someone hacked into their Malmoe server a year ago or so, and found that they indeed run everything in RAM disks and aren't logging at all
Hypothetically, without breaking into the network control plane, the hacker could have completely missed the existence of port mirror to a second read-only system that does logging for lawful intercepts.
With more housing, the relative expense decreases, and some people will move in just because they like the bustle of living in a city. Those are also the kind of people who will patronize local establishments.
Years ago, the center of the action in "Silicon Valley" was actually in the geographical valley, in the south bay. The south bay is way different from SF - safe and sterile. Some people would move up to SF and commute all the way down to the south bay just because they wanted to live somewhere interesting. Those sort of people also tended to be the sort to start startups, and the center of the action gradually moved to SF.
I think SF can try following the same path a second time, focus on catering to the gritty hipster demographic and hope something valuable grows out of it. Added housing to push rents lower seems like a good start.
I think it's more that the barriers to entry for tech businesses have plummeted. In the olden days (80's, 90's, etc), you didn't have the internet as your force multiplier.
I wonder if DARPA et al will decide that the leaks are just the price they pay for having soldiers spend their free time fooling around in simulators with tanks they actually operate.
A specific form of bad research which could be at play here: The researchers programmatically searched the space of possible control variables to include until they came up with a model which maximized the apparent effect size for coffee, so they could publish an interesting & widely cited paper that looked good on their resumes.
With N different control variables to either include or ignore, that's 2^N possible sets of control variables. Odds are decent at least one of those regressions has a large effect size for coffee.
I would trust this sort of research more if instead of publishing a particular set of control variables obtained by an unspecified method, the researchers chose 100 of those 2^N possible sets of control variables at random, then published the average effect size from the 100 resulting regressions. Ideally they would make the code to reproduce this average effect size publicly available, so anyone could easily replicate using another 100 randomly generated regressions.
As Bayesians, shouldn't this effect size cause us to update in the direction that coffee is good for health, even if we think confounding contributed to the large effect size?
Seems to me that a likely reason for a large effect size is both a causal effect of drinking coffee and confounding, added together.
As an analogy, suppose you and I are talking about a Hollywood star who has made a lot of money. I say: "The star is probably a good actor." You say: "I would just encourage people to think about this wealth level and ask whether it's plausible. The star is probably just physically attractive." Of course, the wealthiest Hollywood stars tend to be both good actors and physically attractive.
Why is a large effect size more plausible for some unspecified confounder than it is for coffee? I think some research suggests coffee induces benefits akin to caloric restriction (autophagy) among other good things: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4111762/ Should we really have a prior that an unspecified confounder can have such a large effect size? How common is that?
>Compared with nonconsumers, consumers of various amounts of unsweetened coffee (>0 to 1.5, >1.5 to 2.5, >2.5 to 3.5, >3.5 to 4.5, and >4.5 drinks/d) had lower risks for all-cause mortality after adjustment for lifestyle, sociodemographic, and clinical factors, with respective hazard ratios of 0.79 (95% CI, 0.70 to 0.90), 0.84 (CI, 0.74 to 0.95), 0.71 (CI, 0.62 to 0.82), 0.71 (CI, 0.60 to 0.84), and 0.77 (CI, 0.65 to 0.91); the respective estimates for consumption of sugar-sweetened coffee were 0.91 (CI, 0.78 to 1.07), 0.69 (CI, 0.57 to 0.84), 0.72 (CI, 0.57 to 0.91), 0.79 (CI, 0.60 to 1.06), and 1.05 (CI, 0.82 to 1.36). The association between artificially sweetened coffee and mortality was less consistent. The association of coffee drinking with mortality from cancer and CVD was largely consistent with that with all-cause mortality. U-shaped associations were also observed for instant, ground, and decaffeinated coffee.
Positive health effects from drinking sugar-sweetened coffee make me think it's not just confounding, since I wouldn't expect health-conscious people to drink sugar-sweetened coffee. But I'm suspicious regarding the "less consistent" association for artificially sweetened coffee. That makes me think that there is just too much noise in the data to know for sure, or perhaps artificial sweeteners are actually bad for you?
> As Bayesians, shouldn't this effect size cause us to update in the direction that coffee is good for health, even if we think confounding contributed to the large effect size?
If you apply this thought process to alcohol (given what we know now), what would you conclude about this approach to updating your priors based on implausible observational data?
I'm old enough to remember the naive optimism around the internet in the 2000s. "The long tail", "cognitive surplus", "one laptop per child", Creative Commons, the Arab "Spring", breathless Youtube videos about how social media is gonna revolutionize society for the better, etc. Hardly anyone forecasted clickbait, Trump tweets, revenge porn, crypto scams, or social media shaming. If we had a few professional critics who were incentivized to pour cold water on the whole deal, or at least scan the horizon for potential problems, maybe things would've turned out better.