Is it really more expensive to not connect a water treatment plant to the internet? I can imagine the vendor selling that idea but I struggle to come up with how that could make a water treatment plant cheaper to operate.
Yes. Without a remote system you must have a real person check levels, pumps, pressures, and many other devices thus be present. This person must be trained and you will likely need a backup as well.
If not a person you need more redundancies built in. Bigger tanks, multiple backup systems. When items start failing you need them to be shutoff in a timely manner. Water pumps at these facilities are in the 50-100k range. When it starts failing you want to know.
Think of it like driving a car and it starts making funny noises. The longer you wait to fix it the more it costs.
Why that drastic, checking system state (telemetry) can be done using 'data diode' style networking - one network just broadcasting sensor data, other network allows changing parameters and 3rd one allows allows software upgrades and so on.
You can be very defensive and design any remote sensing controller to act as two systems - one management cpu only does data routing (no other connection than administrative tasks), sensor cpu works only with sensors. As bonus you can have management cpu act as active firewall.
Main problem it is necessary to have in house expertise (hw, fw and process knowing) which in making company lean are optimized first and outsourcing custom solutions suddenly too expensive.
Or you can just slap a lot of Windows XP boxes with closed source control software and remote access software and let the central team do it. Which will be a bit cheaper
Surely it isn't impossible to devise one-way data flows that provably work for remote sensing? And yeah then you have to send somebody to fix stuff if something is off..
Like something that would work but not not scale would be one computer writing data to an updating qr code and another reading it. Surely something like that can be made (and probably already exists?) on the cable level?
Most water treatment works are unmanned most of the time. You don't need 24/7 staffing or even close.
But more to the point, a modern water network has a huge number of nodes. If you can't centrally aggregate and control in a control room the costs and complexity explode, probably also the error rate.
Even if you demand a full air gap, the solution here can't be to get rid of computers or networks. They are much, much too valuable. Luckily industrial control is full of very low hanging fruits.
There is lots of infrastructure related to water that doesn't have someone physically there 24/7 as it would not be feasible to do so as 99.9% of the time there is nothing to do. So you need some sort of remote alarm system that can be monitored.
The expense usually comes in operations. By connecting the water treatment plant to the Internet and making it remotely operable, you can have one guy who sits in an office and is responsible for overseeing the water quality at many different treatment plants. If everything is local, you need one guy on site at each different plant. People are expensive, software is cheap.
Of course, by making it remotely operable, that one guy could be replaced with a guy in Russia who's job is to poison everyone.
Yes it sounds like people came in at high risk of suicide and then they gave them an app that surveyed them and would predict they were going to commit suicide. Given they were at high risk for suicide attempts, how does this compare to just predicting the people would always try to commit suicide in the following week?
Suicide attempt PPV = .16. This means, and correct me if I'm wrong, 84% of positive results would be wrong if the test was applied to the general population (population of psychiatric patients?).
> The most accurate prediction was achieved using bidirectional long short-term memory and simple lasso-penalized logistic regression models, with the best performing model using bidirectional long short-term memory to predict SRE, which with specificity at .90, had area under the curve = .94, sensitivity = .87, and positive predictive value = .30, and SAs with area under the curve = .90, sensitivity = .74, positive predictive value = .16.
Where SA is "Suicide Attempt" and SRE is "suicide-related event".
I understand building data centers, but what does maintaining data centers entail? Are those going to be high paying jobs and how many of them. I don’t know much about the area but it seems like they would be low wage and not very many needed once the data centers are built.
It that’s the whole point that it’s just a mirage and is the same with random data. The people on the low end can’t underestimate their results as much and the people on the upper end can’t overestimate their results as much. That will come out of any correlation that is not perfectly correlated, which is why the article talks about it being replicable with random data. An interesting graph that would demonstrate a novel effect would be something nonlinear.
Yes, this is slightly incorrect. The purpose of a college loan is 100% that the default rate will be low enough that the interest payments will provide a positive return for the lender. The expected default rate is given by the lendee’s expected future income. The majority of the expected income is driven by the expected job of that lender, but some of that expected income could come from other income sources such as investments especially in fields such as finance.
I very deliberately did not say that local news is now better, just back in the day when it was supported by an ad monopoly, it still had big problems. There was a lot of access journalism dependent on staying on the good side of the police, and on not annoying the car dealers running full page ads, for example.
Citizen journalism has issues, too. Many of them are resource issues, so supporting things like a cap on fees and short deadlines on FOIA requests, would help a lot.
Even beyond scams they are one of the biggest factors leading to the collapse of the local news industry that was funded by local classified ads. So it’s hard at a macro level to view them as doing it right in a global sense, but they did make Craig rich.
What don’t you understand? Those websites that defame a company are liable for that defamation. In this case Google defamed a company in its AI summary and is this liable for that defamation.
but if Wikipedia itself writes harmful content such as encouraging people to drink bleach, then wikipedia is liable. Google now generates its own content with AI, that defame others, so Google is liable.
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