Other funny note…for all the Silicon Valley folk on HN…the trident missles the US uses on submarines are built in Sunnyvale.
I’m imaging most on here have read some/all of the secret history of Silicon Valley posts, but if you haven’t they are great
5,626 karma · joined October 6, 2015
I’m imaging most on here have read some/all of the secret history of Silicon Valley posts, but if you haven’t they are great
https://www.thedrive.com/the-war-zone/34043/france-just-test...
Generally the logic is don’t launch on trajectories over land unless you have to. I believe all of the land based is ICBMs are still tested from vandenberg on the (most beautiful section of) California coast near Lompoc for the same reason. Vandenberg doesn’t have any deployed ICBMs, they all fly to kwaj for testing. Same reason nasa/spacex/seemingly everyone but China make it a goal to not have launches go over populated areas.
The most interesting boring book I’ve ever read.
Some other interesting details…
Naval icbms have star tracking for alignment and correction but land based ones do not.
The reasoning is that they are all dead reckoning…which requires knowing the initial location. The silo doesn’t move, but the subs do. Their location is tracked with another inertial guidance system but that adds error, so they use the star tracking.
Overall, the inertial navigation systems in modern icbms are not the limited in accuracy.
My favorite…there was a lot of pushback inside the us military on investing in increasing the accuracy of naval ICBMs. Doing so was seen as communicating/implying a shift in strategic goal from targeting cities (lower required accuracy) to targeting hardened facilities (higher required accuracy). That was seen as confrontational because sun based nuclear weapons had been generally treated as a second strike capability, but the primary reason to have the ability to target hardened facilities was for a first strike
I appreciate it but no need - the people doing that (typically) are as much victims of this propaganda. They aren't malicious, they have been learned the same culture we're talking about.
Funny enough, the first place I ever interned had attempted to do a lights out factory in the 1980s. Short term, it was a disaster - in part because they literally had not installed sufficient lighting to trouble shoot problems, push automated transfer vehicles back onto control strips, and pry parts apart. The machining centers of the era could do the quality but required experts to operate, monitor, and adjust. When things went wrong they weren't small anymore, they were destructive and shut down production for 12+ hours. The shift had been made in part to leverage concessions from the workforce, and (IMHO) as a result it disregarded all the tacit skills those employees used to keep the place running. Long term, They ended up with higher quality, faster throughput, but more employees. But, it cost them a lot and they needed more employees to move stuff around the factory because they had built this huge space to do lights out and the irredeemable piece of lights out was material movement and handling. What I learned was that robots and machines can't tell you what went wrong - no matter how much you log.
I've got a ton of other examples. Every factory I've worked in I've learned how much of a myth 'low skilled labor' is. On the floor, in every factory, new hires were useless - which is a pretty definitive marker of 'skilled labor'. Same thing in the military - senior NCOs are often critical mentors to new LTs. As an engineer I've typically learned as much from the technicians and operators as from the other engineers. At each, I've also worked with really smart engineers who were terrible at their job because they had been socialized that their intelligence was all they needed and there was no need to learn from the 'floor guys'. Roger Smith (and Elon) thought engineers could make the transition to lights out with their knowledge alone because they had bought into the same narrative about blue collar work be low skill and low intelligence. The result was concerns about air friction on robots but not tolerance stack up of stampings or repairable castings.
The problem is, until you really engage with it, the narrative descriptions of certain work we get from the media and economists become a lens for making sense of reality. I'm not immune from that, I just had it beaten out of me. Oxen aren't stupid either, they're still really useful in situations where tractors struggle.
The point of governance to some extent is dealing with the tension between what competing groups of people say they want and actually need
A spring only suspension system responds quickly to a bump in the road. If that’s your only metric, it’s good. But a car without a damper is going to be hella uncomfortable. The shock makes it respond slower - it doesn’t mean it doesn’t respond.
> "Mass production technologies and the division of labor created a workforce consisting of relatively unskilled employees on the line combined with a smaller group of highly skilled workers and the engineering teams that designed it."
> "Japanese producers pursued precision production, just-in-time production, quality built into all production stages (not just at the end), continuous improvements by the entire workforce, and collaborative labor practices, all of which led to dramatically increased efficiencies and quality."
One (Ford) seeks to deskill its workforce in the name of efficiency because they see their opinions as irrelevant because they are not the capital class. One (Toyota) seeks their input as valuable specifically because they are the ones doing the work.
I've worked in both types of factories as an engineer. BOTH sought to apply the principles of lean manufacturing to build efficiency. It only worked in one of them, the one with a culture of treating factory staff with respect. In the one where management and engineering looked down on the employees they didn't listen for efficiency opportunities they only looked for them themselves, they presumed the unskilled workforce provided nothing. Funny enough - that plant couldn't attract better quality employees.
The articles has an entire section dedicated to workforce education...great! but as with all post secondary education in our modern society, the participants are (in large part) motivated by the economic potential of that pursuit. If I can make the same working at starbucks (with benefits because employer scale) as I can as an electrical tradesperson (yes, there are levels but not all are union) why would I pick the one that destroys my body? Why bother with workforce education if your leaders don't respect their work and will seek to Taylorize them instead of partner with them. Apprenticeship and training works in Germany and Japan because the jobs are not awful. It works because of the culture of work. I would argue this is actually the same reason we lag in another marker the article talks about - robots per worker.
That would seem to be simpler
I reported all this, with call recordings, logs, notes, etc. to my insurance's fraud hotline and they closed the file without doing anything.
Much of health care in the US is wrapped in a blanket of outright fraud. You can't agree to be a victim of fraud. Until I get to charge them for the time I spend correcting their billing mistakes I am totally fine deciding what bill is appropriate and what bill is not on my own.
* word processing software * CAD software * pretty much everything adobe * Xcode * photo software
and there are probably other's
Having been yelled at by colleagues for opting to not include Dr. on my own freaking business cards - here here.
Not saying it is one or the other, just that nordstrom would be particularly motivated to shift blame because of what the alternative says about their broader business model. So maybe not taking them at their word.
That being said, i'll note that I'm SHOCKED how normalized shoplifting has become not just among 'the criminal element' but among my social set which is decidedly not your typical criminals. Stealing, especially from self checkouts, is increasingly openly discussed in my experience - and generally framed as 'its them paying me for doing their job of checking me out' or 'countering inflation/corporate greed'. Whether I agree with the morality of it or not and juts note that it is increasingly normalized. More broadly, I struggle with feeling sorry for corporations when the public lives under a never ending stream of abuse from corporate policies and control (c.f., everything being a subscription).
I’m entirely agnostic to what the claim is, what ideology it supports, or even whether or not it’s true.
You use a citation to increase the credibility of you claim or argument. If the citation doesn’t actually say what you said that is a problem.
If I said aliens are real here is proof and cite a lasagna recipe that’s a problem
The entire article is about installing an app on their personal phones.
When these issues are takled about in words, through code, through hand waving whatever - I have experienced that the details often mask ensuring that everyone is on the same basic page. Often when there has been confusion it has taken someone pulling the group back and noting that 'Bob things A is connected to B and then connected to D but Alice thinks A connects to C before connecting to D"
Just putting a architecture diagram of a process up helps find shared understanding.
It is becoming increasingly common for “undergraduate research opportunities” to in fact just be a job annotating data. Researchers need some custom annotated dataset. Undergraduates want “research experience”. So researchers offer an opportunity to undergrads who think they will be doing meaningful research but instead are just mechanical turkers. No pay, perhaps a promise of research credit later…
It’s disingenuous to students but also disingenuous to companies looking for some meaningful research experience on resumes that list it.
Training in this sense is about how people use language not what is the right answer. Among other sources - the exact thing you describe is a contributor to some of the things within the (in my opinion misnamed) internal taxonomy of 'hallucinations'.
Right or wrong - reddit is human beings using (mostly english) language to speak to each other, and so if you want to train an ML model to do that - its a great source.
They are trying to figure out how to have people submit their bills and gather actual billing data and compare what actually happens with what is claimed. Gives them a better data set for comparison and evaluation and to spot 'oddities'. I imagine health insurance does the same thing...but its opaque and invisible to consumers.